diff --git a/.gitignore b/.gitignore index 218d1ea..b58e2d1 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ -*.pyc -mp_data_manager.egg-info +*.pyc +mp_data_manager.egg-info +.vscode diff --git a/.project b/.project index 60f829a..092dc61 100644 --- a/.project +++ b/.project @@ -1,17 +1,17 @@ - - - mp-data-manager - - - - - - org.python.pydev.PyDevBuilder - - - - - - org.python.pydev.pythonNature - - + + + mp-data-manager + + + + + + org.python.pydev.PyDevBuilder + + + + + + org.python.pydev.pythonNature + + diff --git a/.pydevproject b/.pydevproject index a3b2a72..8a2f2ec 100644 --- a/.pydevproject +++ b/.pydevproject @@ -1,8 +1,8 @@ - - -python 2.7 -marco17 python2.7 - -/${PROJECT_DIR_NAME} - - + + +python 2.7 +marco17 python2.7 + +/${PROJECT_DIR_NAME} + + diff --git a/MANIFEST.in b/MANIFEST.in index 711781d..8e73171 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1 +1 @@ -recursive-include data_manager/static * +recursive-include data_manager/static * diff --git a/README.md b/README.md index b4f1875..b770277 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,3 @@ -# data-manager - -Test application for madrona refactor +# data-manager + +Test application for madrona refactor diff --git a/data_manager/admin.py b/data_manager/admin.py index 804b9fe..c106196 100644 --- a/data_manager/admin.py +++ b/data_manager/admin.py @@ -1,260 +1,411 @@ -from django.contrib import admin -from django import forms -from models import * -import nested_admin - -from import_export import fields, resources -from import_export.admin import ImportExportMixin - -class ThemeAdmin(admin.ModelAdmin): - list_display = ('display_name', 'name', 'order', 'primary_site', 'preview_site') - - def formfield_for_manytomany(self, db_field, request=None, **kwargs): - if db_field.name == 'site': - kwargs['widget'] = forms.CheckboxSelectMultiple() - kwargs['widget'].attrs['style'] = 'list-style-type: none;' - kwargs['widget'].can_add_related = False - - return db_field.formfield(**kwargs) - - def get_queryset(self, request): - # use our manager, rather than the default one - qs = self.model.all_objects.get_queryset() - - # we need this from the superclass method - ordering = self.ordering or () # otherwise we might try to *None, which is bad ;) - if ordering: - qs = qs.order_by(*ordering) - return qs - -class NestedMultilayerDimensionValueInline(nested_admin.NestedTabularInline): - model = MultilayerDimensionValue - fields = ('value', 'label', 'order') - extra = 1 - classes = ['collapse', 'open'] - verbose_name_plural = 'Multilayer Dimension Values' - -class NestedMultilayerDimensionInline(nested_admin.NestedTabularInline): - model = MultilayerDimension - fields = (('name', 'label', 'order', 'animated'),) - extra = 1 - classes = ['collapse', 'open'] - verbose_name_plural = 'Multilayer Dimensions' - inlines = [ - NestedMultilayerDimensionValueInline, - ] - -class NestedMultilayerAssociationInline(nested_admin.NestedTabularInline): - model = MultilayerAssociation - fk_name = 'parentLayer' - readonly_fields = ('get_values',) - fields = (('get_values', 'name', 'layer'),) - extra = 0 - classes = ['collapse', 'open'] - verbose_name_plural = 'Multilayer Associations' - - def get_values(self, obj): - return '| %s |' % ' | '.join([str(x) for x in obj.multilayerdimensionvalue_set.all()]) - - def get_readlony_values(self, obj): - return obj.multilayerdimensionvalue_set.all() - - def get_dimensions(self, obj): - dimensions = [] - for value in obj.multilayerdimensionvalue_set.all(): - dimension = value.dimension - if dimension not in dimensions: - dimensions.append(dimension) - return dimensions - -class LayerResource(resources.ModelResource): - class Meta: - model = Layer - -class LayerForm(forms.ModelForm): - exclude = ('slug_name',) - class Meta: - exclude = ('slug_name',) - model = Layer - widgets = { - 'themes': admin.widgets.FilteredSelectMultiple('Themes', False), - 'sublayers': admin.widgets.FilteredSelectMultiple('Sublayers', False), - 'connect_companion_layers_to': admin.widgets.FilteredSelectMultiple('Connect companion layers to', False), - 'attribute_fields': admin.widgets.FilteredSelectMultiple('Attribute fields', False), - 'lookup_table': admin.widgets.FilteredSelectMultiple('Lookup table', False), - } - -class LayerAdmin(ImportExportMixin, nested_admin.NestedModelAdmin): - resource_class = LayerResource - form = LayerForm - list_display = ('name', 'layer_type', 'Theme_', 'order', 'data_publish_date', 'data_source', 'primary_site', 'preview_site', 'url') - search_fields = ['name', 'layer_type', 'url', 'data_source'] - ordering = ('name',) - exclude = ('slug_name',) - - fieldsets = ( - ('BASIC INFO', { - 'fields': ( - ('name','layer_type'), - 'url', - 'site' - ) - }), - ('LAYER ORGANIZATION', { - 'fields': ( - ('order','themes'), - ('is_sublayer','sublayers'), - ('has_companion','connect_companion_layers_to'), - ('is_disabled','disabled_message') - ) - }), - ('METADATA', { - 'classes': ('collapse',), - 'fields': ( - 'description', 'data_overview','data_source','data_notes', 'data_publish_date' - ) - }), - ('LEGEND', { - 'classes': ('collapse',), - 'fields': ( - 'legend', - ('legend_title','legend_subtitle') - ) - }), - ('LINKS', { - 'classes': ('collapse',), - 'fields': ( - ('metadata','source'), - ('bookmark', 'kml'), - ('data_download','learn_more'), - ('map_tiles'), - ) - }), - ('SHARING', { - 'classes': ('collapse',), - 'fields': ( - 'shareable_url', - ) - }), - ('ArcGIS DETAILS', { - 'classes': ('collapse',), - 'fields': ( - ('arcgis_layers', 'disable_arcgis_attributes'), - ) - }), - ('WMS DETAILS', { - 'classes': ('collapse',), - 'fields': ( - 'wms_help', - ('wms_slug', 'wms_version'), - ('wms_format', 'wms_srs'), - ('wms_timing', 'wms_time_item'), - ('wms_styles', 'wms_additional'), - ) - }), - ('Dynamic Layers (MDAT & CAS)', { - 'classes': ('collapse',), - 'fields': ( - 'search_query', - ) - }), - ('UTF Grid Layers', { - 'classes': ('collapse',), - 'fields': ( - 'utfurl', - ) - }), - ('ATTRIBUTE REPORTING', { - 'classes': ('collapse',), - 'fields': ( - ('attribute_event', 'attribute_fields'), - ('lookup_field', 'lookup_table'), - ('mouseover_field'), - ('is_annotated', 'compress_display'), - ) - }), - ('STYLE', { - 'classes': ('collapse',), - 'fields': ( - ('opacity'), - ('vector_outline_color', 'vector_outline_opacity'), - ('vector_color', 'vector_fill'), - ('vector_graphic'), - ('point_radius'), - 'thumbnail', - ) - }), - ('ESPIS', { - 'classes': ('collapse',), - 'fields': ( - ('espis_enabled', 'espis_region'), - ('espis_search' ), - ) - }), - ) - - inlines = [ - NestedMultilayerAssociationInline, - NestedMultilayerDimensionInline, - ] - - from settings import BASE_DIR - add_form_template = '%s/data_manager/templates/admin/LayerForm.html' % BASE_DIR - change_form_template = '%s/data_manager/templates/admin/LayerForm.html' % BASE_DIR - - def Theme_(self, obj): - return obj.themes.first() - - Theme_.admin_order_field = 'themes' - - def formfield_for_manytomany(self, db_field, request=None, **kwargs): - if db_field.name == 'attribute_fields': - kwargs['queryset'] = AttributeInfo.objects.order_by('field_name') - elif db_field.name == 'sublayers': - kwargs['queryset'] = Layer.objects.order_by('name') - elif db_field.name == 'themes': - kwargs['queryset'] = Theme.objects.order_by('name') - elif db_field.name == 'lookup_table': - kwargs['queryset'] = LookupInfo.objects.order_by('value') - elif db_field.name == 'site': - kwargs['widget'] = forms.CheckboxSelectMultiple() - kwargs['widget'].attrs['style'] = 'list-style-type: none;' - kwargs['widget'].can_add_related = False - return db_field.formfield(**kwargs) - - return super(LayerAdmin, self).formfield_for_manytomany(db_field, request, **kwargs) - - # New Layer Form - def add_view(self, request, form_url='', extra_context={}): - # extra_context['test'] = 'BAR' - return super(LayerAdmin, self).add_view(request, form_url, extra_context) - - # Edit Layer Form - def change_view(self, request, id=None, extra_context={}): - # extra_context['test'] = 'BAR' - return super(LayerAdmin, self).change_view(request, id, extra_context=extra_context) - - def get_queryset(self, request): - # use our manager, rather than the default one - qs = self.model.all_objects.get_queryset() - - # we need this from the superclass method - ordering = self.ordering or () # otherwise we might try to *None, which is bad ;) - if ordering: - qs = qs.order_by(*ordering) - return qs - -class AttributeInfoAdmin(admin.ModelAdmin): - list_display = ('field_name', 'display_name', 'precision', 'order') - -class LookupInfoAdmin(admin.ModelAdmin): - list_display = ('value', 'color', 'dashstyle', 'fill', 'graphic') - -class DataNeedAdmin(admin.ModelAdmin): - list_display = ('name', 'description') - -admin.site.register(Theme, ThemeAdmin) -admin.site.register(Layer, LayerAdmin) -admin.site.register(AttributeInfo, AttributeInfoAdmin) -admin.site.register(LookupInfo, LookupInfoAdmin) -admin.site.register(DataNeed, DataNeedAdmin) +from django.conf import settings +from django.contrib import admin +from django.core.exceptions import PermissionDenied +from django.template.response import TemplateResponse +from django.urls import path, reverse +from django import forms + +from import_export import fields, resources +from import_export.admin import ImportExportMixin +import json + +import nested_admin +import requests + +from .models import * +from .forms import RemotePortalMigrationForm +from .views import compare_remote_layers + + +class ThemeAdmin(admin.ModelAdmin): + list_display = ('display_name', 'name', 'order', 'primary_site', 'preview_site') + + def formfield_for_manytomany(self, db_field, request=None, **kwargs): + if db_field.name == 'site': + kwargs['widget'] = forms.CheckboxSelectMultiple() + kwargs['widget'].attrs['style'] = 'list-style-type: none;' + kwargs['widget'].can_add_related = False + + return db_field.formfield(**kwargs) + + def get_queryset(self, request): + # use our manager, rather than the default one + qs = self.model.all_objects.get_queryset() + + # we need this from the superclass method + ordering = self.ordering or () # otherwise we might try to *None, which is bad ;) + if ordering: + qs = qs.order_by(*ordering) + return qs + +class NestedMultilayerDimensionValueInline(nested_admin.NestedTabularInline): + model = MultilayerDimensionValue + fields = ('value', 'label', 'order') + extra = 1 + classes = ['collapse', 'open'] + verbose_name_plural = 'Multilayer Dimension Values' + +class NestedMultilayerDimensionInline(nested_admin.NestedTabularInline): + model = MultilayerDimension + fields = (('name', 'label', 'order', 'animated', 'angle_labels'),) + extra = 1 + classes = ['collapse', 'open'] + verbose_name_plural = 'Multilayer Dimensions' + inlines = [ + NestedMultilayerDimensionValueInline, + ] + +class NestedMultilayerAssociationInline(nested_admin.NestedTabularInline): + model = MultilayerAssociation + fk_name = 'parentLayer' + readonly_fields = ('get_values',) + fields = (('get_values', 'name', 'layer'),) + extra = 0 + classes = ['collapse', 'open'] + verbose_name_plural = 'Multilayer Associations' + + def get_values(self, obj): + return '| %s |' % ' | '.join([str(x) for x in obj.multilayerdimensionvalue_set.all()]) + + def get_readlony_values(self, obj): + return obj.multilayerdimensionvalue_set.all() + + def get_dimensions(self, obj): + dimensions = [] + for value in obj.multilayerdimensionvalue_set.all(): + dimension = value.dimension + if dimension not in dimensions: + dimensions.append(dimension) + return dimensions + +class LayerResource(resources.ModelResource): + class Meta: + model = Layer + +class LayerForm(forms.ModelForm): + exclude = ('slug_name',) + class Meta: + exclude = ('slug_name',) + model = Layer + widgets = { + 'themes': admin.widgets.FilteredSelectMultiple('Themes', False), + 'sublayers': admin.widgets.FilteredSelectMultiple('Sublayers', False), + 'connect_companion_layers_to': admin.widgets.FilteredSelectMultiple('Connect companion layers to', False), + 'attribute_fields': admin.widgets.FilteredSelectMultiple('Attribute fields', False), + 'lookup_table': admin.widgets.FilteredSelectMultiple('Lookup table', False), + } + +class RemoteImportExportMixin(ImportExportMixin): + import_template_name = 'admin/data_manager/import.html' + compare_remote_template_name = 'admin/data_manager/compare_remote_layers.html' + + remote_import_form_class = RemotePortalMigrationForm + + # def get_remote_import_form_class(self, request): + def get_remote_import_form_class(self, request=None): + return self.remote_import_form_class + + # def create_remote_import_form(self, request): + def create_remote_import_form(self, request=None): + if request: + form_class= self.get_remote_import_form_class(request) + else: + form_class= self.get_remote_import_form_class() + return form_class() + + def get_context_data(self, **kwargs): + context_data = super(RemoteImportExportMixin, self).get_context_data(**kwargs) + # context_data['remote_import_form'] = self.create_remote_import_form(request) + context_data['remote_import_form'] = self.create_remote_import_form() + return context_data + + def import_remote_action(self, request, *args, **kwargs): + if not self.has_import_permission(request): + raise PermissionDenied + + view_context = self.get_import_context_data() + view_context['opts'] = self.model._meta + results = { + 'status': 'Error', + 'code': 500, + 'message': 'Unknown Error', + 'data': {} + } + portal_id = None + portal_name = None + portal_url = None + + if request.method == 'POST': + form = RemotePortalMigrationForm(request.POST) + + if form.is_valid(): + portal_id = int(form['portal'].value()) + + # * Get Remote Portal Object + portal = ExternalPortal.objects.get(pk=portal_id) + portal_name = portal.name + portal_url = portal.url + + # * Get Remote Portal Endpoint for layer status + remote_status = requests.get(f"{portal.layer_status_endpoint}") + # * Build layer status comparison dict + # TODO: Handle Error on request! + comparison_results = compare_remote_layers(remote_status.json()) + # * Feed comparison dict back to template + results = { + 'status': 'Success', + 'code': 200, + 'message': 'Success', + # 'data': comparison_results + } + remote_status_dict = { + # 'layers': [comparison_results['layers'][x] for x in comparison_results['layers'].keys() if not comparison_results['layers'][x]['source'] == 'local'], + 'layers': comparison_results['layers'], + 'themes': [remote_status.json()['themes'][key] for key in remote_status.json()['themes'].keys()] + } + local_status = {'layers': [comparison_results['layers'][x] for x in comparison_results['layers'].keys() if comparison_results['layers'][x]['source'] == 'local']} + for layer in local_status['layers']: + layer.pop('local_modified') + layer.pop('remote_modified') + layer['name'] = layer['local_name'] + + + view_context['results'] = results + view_context['remote_status'] = remote_status_dict + view_context['local_status'] = json.dumps(local_status) + view_context['remote_portal'] = { + 'id': portal_id, + 'name': portal_name, + 'url': portal_url + } + + return TemplateResponse(request, [self.compare_remote_template_name], view_context) + + def get_urls(self): + urls = super().get_urls() + info = self.get_model_info() + opts = self.model._meta + remote_import_urls = [ + path('import_remote', + self.admin_site.admin_view(self.import_remote_action), + name='%s_%s_import_remote' % info), + ] + return remote_import_urls + urls + + +class LayerAdmin(RemoteImportExportMixin, nested_admin.NestedModelAdmin): + resource_class = LayerResource + form = LayerForm + list_display = ('name', 'layer_type', 'date_modified', 'Theme_', 'order', 'data_publish_date', 'data_source', 'primary_site', 'preview_site', 'url') + search_fields = ['name', 'layer_type', 'date_modified', 'url', 'data_source'] + ordering = ('name', ) + exclude = ('slug_name',) + + if settings.CATALOG_TECHNOLOGY not in ['default', None]: + # catalog_fields = ('catalog_name', 'catalog_id',) + # catalog_fields = 'catalog_name' + basic_fields = ( + 'catalog_name', + ('name','layer_type',), + ('url', 'proxy_url'), + 'site' + ) + else: + basic_fields = ( + ('name','layer_type',), + ('url', 'proxy_url'), + 'site' + ) + + fieldsets = ( + ('BASIC INFO', { + 'fields': basic_fields + }), + ('LAYER ORGANIZATION', { + # 'classes': ('collapse', 'open',), + 'fields': ( + ('order','themes'), + ('is_sublayer','sublayers'), + ('has_companion','connect_companion_layers_to'), + # RDH 2019-10-25: We don't use this, and it doesn't seem helpful + # ('is_disabled','disabled_message') + ) + }), + ('METADATA', { + 'classes': ('collapse',), + 'fields': ( + 'description', 'data_overview','data_source','data_notes', 'data_publish_date' + ) + }), + ('LEGEND', { + 'classes': ('collapse',), + 'fields': ( + 'show_legend', + 'legend', + ('legend_title','legend_subtitle') + ) + }), + ('LINKS', { + 'classes': ('collapse',), + 'fields': ( + ('metadata','source'), + ('bookmark', 'kml'), + ('data_download','learn_more'), + ('map_tiles'), + ) + }), + ('SHARING', { + 'classes': ('collapse',), + 'fields': ( + 'shareable_url', + ) + }), + ('ArcGIS DETAILS', { + 'classes': ('collapse',), + 'fields': ( + ('arcgis_layers', 'password_protected', 'query_by_point', 'disable_arcgis_attributes'), + ) + }), + ('WMS DETAILS', { + 'classes': ('collapse',), + 'fields': ( + 'wms_help', + ('wms_slug', 'wms_version'), + ('wms_format', 'wms_srs'), + ('wms_timing', 'wms_time_item'), + ('wms_styles', 'wms_additional'), + ('wms_info', 'wms_info_format'), + ) + }), + ('Dynamic Layers (MDAT & CAS)', { + 'classes': ('collapse',), + 'fields': ( + 'search_query', + ) + }), + ('UTF Grid Layers', { + 'classes': ('collapse',), + 'fields': ( + 'utfurl', + ) + }), + ('ATTRIBUTE REPORTING', { + 'classes': ('collapse',), + 'fields': ( + ('label_field'), + ('attribute_event', 'attribute_fields'), + ('mouseover_field'), + ('is_annotated', 'compress_display'), + ) + }), + ('DISPLAY & STYLE', { + 'classes': ('collapse',), + 'fields': ( + 'opacity', + ( + 'minZoom', + 'maxZoom' + ), + 'custom_style', + ( + 'vector_outline_width', + 'vector_outline_color', + # 'vector_outline_opacity', + ), + ( + 'vector_fill', + 'vector_color', + ), + ( + 'point_radius', + 'vector_graphic', + 'vector_graphic_scale', + ), + ( + 'lookup_field', + 'lookup_table', + ), + # 'thumbnail', + ) + }), + ('ESPIS', { + 'classes': ('collapse',), + 'fields': ( + ('espis_enabled', 'espis_region'), + ('espis_search' ), + ) + }), + ) + + inlines = [ + NestedMultilayerAssociationInline, + NestedMultilayerDimensionInline, + ] + + from . import settings as data_manager_settings + BASE_DIR = data_manager_settings.DATA_MANAGER_BASE_DIR + add_form_template = '%s/data_manager/templates/admin/LayerForm.html' % BASE_DIR + change_form_template = '%s/data_manager/templates/admin/LayerForm.html' % BASE_DIR + + def Theme_(self, obj): + return obj.themes.first() + + Theme_.admin_order_field = 'themes' + + def formfield_for_manytomany(self, db_field, request=None, **kwargs): + if db_field.name == 'attribute_fields': + kwargs['queryset'] = AttributeInfo.objects.order_by('field_name') + elif db_field.name == 'sublayers': + kwargs['queryset'] = Layer.objects.order_by('name') + elif db_field.name == 'themes': + kwargs['queryset'] = Theme.objects.order_by('name') + elif db_field.name == 'lookup_table': + kwargs['queryset'] = LookupInfo.objects.order_by('value') + elif db_field.name == 'site': + kwargs['widget'] = forms.CheckboxSelectMultiple() + kwargs['widget'].attrs['style'] = 'list-style-type: none;' + kwargs['widget'].can_add_related = False + return db_field.formfield(**kwargs) + + return super(LayerAdmin, self).formfield_for_manytomany(db_field, request, **kwargs) + + # New Layer Form + def add_view(self, request, form_url='', extra_context={}): + extra_context['CATALOG_TECHNOLOGY'] = settings.CATALOG_TECHNOLOGY + extra_context['CATALOG_PROXY'] = settings.CATALOG_PROXY + return super(LayerAdmin, self).add_view(request, form_url, extra_context) + + # Edit Layer Form + def change_view(self, request, object_id, extra_context={}): + extra_context['CATALOG_TECHNOLOGY'] = settings.CATALOG_TECHNOLOGY + extra_context['CATALOG_PROXY'] = settings.CATALOG_PROXY + return super(LayerAdmin, self).change_view(request, object_id, extra_context=extra_context) + + def get_queryset(self, request): + # use our manager, rather than the default one + qs = self.model.all_objects.get_queryset() + + # we need this from the superclass method + ordering = self.ordering or () # otherwise we might try to *None, which is bad ;) + if ordering: + qs = qs.order_by(*ordering) + return qs + +class AttributeInfoAdmin(admin.ModelAdmin): + list_display = ('field_name', 'display_name', 'precision', 'order', 'preserve_format') + +class LookupInfoAdmin(admin.ModelAdmin): + list_display = ('value', 'description', 'color', 'stroke_color', 'dashstyle', 'fill', 'graphic') + +class DataNeedAdmin(admin.ModelAdmin): + list_display = ('name', 'description') + + + +if hasattr(settings, 'DATA_MANAGER_ADMIN'): + admin.site.register(Theme, ThemeAdmin) + admin.site.register(Layer, LayerAdmin) + admin.site.register(AttributeInfo, AttributeInfoAdmin) + admin.site.register(LookupInfo, LookupInfoAdmin) + admin.site.register(DataNeed, DataNeedAdmin) + admin.site.register(ExternalPortal) diff --git a/data_manager/fixtures/WC_MP_formatted_data_manager_20190729.json b/data_manager/fixtures/WC_MP_formatted_data_manager_20190729.json new file mode 100644 index 0000000..f66d9b0 --- /dev/null +++ b/data_manager/fixtures/WC_MP_formatted_data_manager_20190729.json @@ -0,0 +1,11401 @@ +[ +{ + "model": "data_manager.theme", + "pk": 9, + "fields": { + "display_name": "Biological", + "name": "Biological", + "header_image": "", + "header_attrib": "", + "overview": "", + "description": "", + "thumbnail": "", + "factsheet_thumb": "", + "factsheet_link": "", + "feature_image": "", + "feature_excerpt": "", + "feature_link": "" + } +}, +{ + "model": "data_manager.theme", + "pk": 10, + "fields": { + "display_name": "Human", + "name": "Human", + "header_image": "", + "header_attrib": "", + "overview": "", + "description": "", + "thumbnail": "", + "factsheet_thumb": "", + "factsheet_link": "", + "feature_image": "", + "feature_excerpt": "", + "feature_link": "" + } +}, +{ + "model": "data_manager.theme", + "pk": 11, + "fields": { + "display_name": "Physical", + "name": "Physical", + "header_image": "", + "header_attrib": "", + "overview": "", + "description": "", + "thumbnail": "", + "factsheet_thumb": "", + "factsheet_link": "", + "feature_image": "", + "feature_excerpt": "", + "feature_link": "" + } +}, +{ + "model": "data_manager.theme", + "pk": 12, + "fields": { + "display_name": "WCGA Priority Issues", + "name": "WCGA Priority 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The scatterometer has an approximate 390km swath.", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={8CFD0970-8640-4C0C-9DB7-F6EFD1909FFD}", + "source": "HTTP://PODAAC.JPL.NASA.GOV", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 256 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 438, + "fields": { + "name": "Wind Speed, Weekly (NASA, 2014)", + "slug_name": "wind-speed-weekly-nasa-2014", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "Aquarius_V3_scat_wind_speed_Weekly/scat_wind_speed", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=Aquarius_V3_scat_wind_speed_Weekly/scat_wind_speed&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "15FDF344-BFF9-47BF-AF5B-3CD967E5B5E2", + "description": "Aquarius Level 3 sea surface salinity (SSS) standard mapped image data contains gridded 1 degree spatial resolution SSS averaged over daily, 7 day, monthly, and seasonal time scales. 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A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={15FDF344-BFF9-47BF-AF5B-3CD967E5B5E2}", + "source": "HTTP://PODAAC.JPL.NASA.GOV", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 300 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 439, + "fields": { + "name": "Ocean Currents, Nowcast (ROMS, 2014)", + "slug_name": "ocean-currents-nowcast-roms-2014", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "CA_DAS/sea_water_velocity", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=CA_DAS/sea_water_velocity&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "6073E47B-3195-4999-80B0-0D04AFAB96FF", + "description": "The California ROMS model extends from just north of the CA-Oregon border south to Mexico and has a resolution of 3 km. 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The service displays the most recent time step for the layer.", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={6073E47B-3195-4999-80B0-0D04AFAB96FF}", + "source": "", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 256 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 440, + "fields": { + "name": "COAMPS Heat Flux (Navy, 2014)", + "slug_name": "coamps-heat-flux-navy-2014", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "COAMPS_4KM_IR_FLUX/IR_heat_flux", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=COAMPS_4KM_IR_FLUX/IR_heat_flux&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "4B8F13D5-21E3-4D6D-9421-451CFFEAA4B3", + "description": "Near-real-time 48-hour weather forecasts from the new CeNCOOS COAMPS model run (August 2013 - Present). 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More information: CeNCOOS COAMPS page: http://www.cencoos.org/sections/models/coamps/ ", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={C3FF12A7-274E-48D7-8D7E-A5486142EF8B}", + "source": "http://www.cencoos.org/sections/models/coamps/ ", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 300 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 442, + "fields": { + "name": "COAMPS Air Temperature, 2m (Navy, 2015)", + "slug_name": "coamps-air-temperature-2m-navy-2015", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "COAMPS_4KM_2M_AIR_TEMP/air_temperature", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=COAMPS_4KM_2M_AIR_TEMP/air_temperature&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "E0A42CD5-B53E-42AB-A1C8-75747FDCFBF1", + "description": "Near-real-time 48-hour weather forecasts from the new CeNCOOS COAMPS model run (August 2013 - Present). 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More information: CeNCOOS COAMPS page: http://www.cencoos.org/sections/models/coamps/ ", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={926A10BB-B9DA-4FEE-8E8B-8EBBA3517253}", + "source": "http://www.cencoos.org/sections/models/coamps/ ", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 300 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 444, + "fields": { + "name": "COAMPS Total Precipitation, 12hr (Navy, 2015)", + "slug_name": "coamps-total-precipitation-12hr-navy-2015", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "COAMPS_4KM_TTL_PRCP/total_precipitation_12-hour", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=COAMPS_4KM_TTL_PRCP/total_precipitation_12-hour&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "A6C5E927-F9E4-4A6C-BE2F-06416924B3E7", + "description": "Near-real-time 48-hour weather forecasts from the new CeNCOOS COAMPS model run (August 2013 - Present). 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More information: CeNCOOS COAMPS page: http://www.cencoos.org/sections/models/coamps/", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={A6C5E927-F9E4-4A6C-BE2F-06416924B3E7}", + "source": "http://www.cencoos.org/sections/models/coamps/", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 300 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 445, + "fields": { + "name": "COAMPS Solar Radiation, 4km (Navy, 2015)", + "slug_name": "coamps-solar-radiation-4km-navy-2015", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "COAMPS_4KM_SOL_RAD/Net_short-wave_radiation_surface", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=COAMPS_4KM_SOL_RAD/Net_short-wave_radiation_surface&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "DAD4ABE0-75C4-4F79-9BAE-ADBF5CAD1E86", + "description": "Near-real-time 48-hour weather forecasts from the new CeNCOOS COAMPS model run (August 2013 - Present). 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More information: CeNCOOS COAMPS page: http://www.cencoos.org/sections/models/coamps/", + "data_overview": "", + "data_source": "", + "data_notes": "", + "bookmark": "", + "kml": "", + "data_download": "", + "metadata": "http://portal.westcoastoceans.org/geoportal/rest/document?id={DAD4ABE0-75C4-4F79-9BAE-ADBF5CAD1E86}", + "source": "http://www.cencoos.org/sections/models/coamps/", + "map_tiles": "", + "compress_display": false, + "attribute_event": "click", + "lookup_field": "", + "vector_color": "", + "vector_fill": null, + "vector_graphic": "", + "opacity": 0.5, + "sublayers": [ + 300 + ], + "themes": [ + 11 + ], + "attribute_fields": [], + "lookup_table": [] + } +}, +{ + "model": "data_manager.layer", + "pk": 446, + "fields": { + "name": "COAMPS Visibility, 4km (Navy, 2015)", + "slug_name": "coamps-visibility-4km-navy-2015", + "layer_type": "WMS", + "url": "http://pdx.axiomalaska.com/ncWMS/wms?", + "shareable_url": true, + "arcgis_layers": "", + "wms_slug": "COAMPS_4KM_VISIB/visibility", + "is_sublayer": true, + "legend": "http://pdx.axiomalaska.com/ncWMS/wms?REQUEST=GetLegendGraphic&LAYER=COAMPS_4KM_VISIB/visibility&PALETTE=alg", + "legend_title": "", + "legend_subtitle": "", + "utfurl": "", + "filterable": false, + "geoportal_id": "6A564361-9B94-4C92-8B5A-A83E8BF1505C", + "description": "Near-real-time 48-hour weather forecasts from the new CeNCOOS COAMPS model run (August 2013 - Present). 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"header_attrib": "", - "display_name": "Fishing", - "name": "fishing", - "overview": "

\r\nThe Mid-Atlantic\u2019s highly productive estuaries and diverse coastal and ocean habitats support substantial commercial and recreational fisheries that provide income, food, and enjoyment for millions of people. Fishing is an essential component of the region\u2019s rich cultural heritage and directly connects coastal community residents and tourists to the ocean, whether through fresh seafood or the thrill of a day spent fishing on the ocean. \r\n

\r\nIn 2010, the Mid-Atlantic\u2019s commercial harvest was more than 800 million pounds, with Atlantic menhaden making up over 60% of the catch. Other key commercial species include sea scallop, surf clam, ocean quahog clam, summer flounder, lobster, squid, and striped bass. The total 2010 ex-vessel value (initial price paid to fishermen) was well over $500 million and sea scallops were the most valuable of the species. But the value of commercial fisheries extends beyond ex-vessel price. In 2009, the region\u2019s fisheries supported an estimated 116,000 jobs in industries ranging from equipment supply to seafood processing and retail.\r\n\r\nRoughly 2.6 million recreational anglers participated in 17 million saltwater fishing trips in 2009, mainly targeting striped bass, summer flounder, black seabass, tautog, scup, bluefish, drum, weakfish, spot, and croaker. They spent an estimated $3.5 billion on the fishing-related vehicles, tackle, boats, equipment, and second homes. That same year, the recreational fishing industry in the Mid-Atlantic supported approximately 25,000 jobs.\r\n

\r\nThe MARCO Ocean Data Portal includes commercial fishing effort for mobile bottom-contacting gear (e.g., trawls and dredges), pelagic gear (e.g., mid-water trawls, gill nets, and hook and line), and all gear combined. The map layers were created using Fishing Vessel Trip Report data provided by the National Marine Fisheries Service. These data are presented at a coarse spatial scale (i.e., 70-100 square nautical miles) and illustrate the regional importance of commercial fishing areas, but are less than ideal for coastal and marine planning. Further, MARCO does not include specific recreational fishing information, although for-hire sector fishing effort is included in the commercial pelagic gear map layer. \r\n

\r\nMARCO is working to improve the commercial fishing data represented here and to add recreational fishing information. Planned improvements include creation of higher resolution commercial fishing activity maps and development of products--in conjunction with stakeholders--that best represent commercial fishing interests and values, while protecting confidential information. Efforts to create maps of recreational use areas are being developed with assistance from anglers in all Mid-Atlantic states, and a new online recreational boater survey to enhance these efforts is being designed for implementation in late 2012. \r\n

\r\nThe Mid-Atlantic Fisheries Management Council and the Atlantic States Marine Fisheries Commission have management authority for most recreational and commercial ocean fisheries. Some migratory species (e.g., sharks and tunas), are managed separately by the National Marine Fisheries Service. MARCO will coordinate and consult with all of these institutions as appropriate to acquire and develop fishing data suitable for public display. ", - "feature_image": "", - "thumbnail": "", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/fishing.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/fishing_boats1.jpg", - "description": "The Portal will be collecting and integrating data on the productive habitats and rich species diversity that are essential for maintaining healthy fishing areas. " - } - }, - { - "pk": 9, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "", - "feature_link": "", - "header_attrib": "", - "display_name": "Relevant Data", - "name": "relevant-data", - "overview": "", - "feature_image": "", - "thumbnail": "", - "visible": false, - "factsheet_thumb": "", - "feature_excerpt": "", - "header_image": "", - "description": "" - } - }, - { - "pk": 11, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "", - "feature_link": "", - "header_attrib": "", - "display_name": "Broad Zones", - "name": "broad-zones", - "overview": "", - "feature_image": "", - "thumbnail": "", - "visible": false, - "factsheet_thumb": "", - "feature_excerpt": "", - "header_image": "", - "description": "" - } - }, - { - "pk": 2, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_ports_F.pdf", - "feature_link": "", - "header_attrib": "Photo \u00a9 Michael Eversmier", - "display_name": "Marine Life", - "name": "conservation", - "overview": "

\r\nThe Mid-Atlantic is well known for nutrient-rich and highly productive waters. The region is a transitional area between the rocky shores of New England and the gently sloping South Atlantic, and it is influenced by two large estuaries, Chesapeake Bay and Delaware Bay. As a result, the Mid-Atlantic region is home to a wealth of complex ecosystems and its estuaries, salt marshes, sea grasses, barrier islands, cold water corals, and submarine canyons provide spawning, nursery, and forage habitats that support diverse resident and migratory marine life including invertebrates, seabirds, fishes, and marine mammals. \r\n

\r\nThe topography is mostly flat, but features sandy shoals and swales, sand wedges and waves, and a broad continental shelf embedded cold water coral patch habitats and incised by submarine canyons along the shelf-slope break. These areas support biologically diverse and abundant benthic (seafloor) macrofauna, demersal fish, and foraging concentrations of sea birds, sea ducks, and bottlenose dolphins. Benthic habitats contain over 2000 species of invertebrates such as marine worms, sponges, shrimp, crab, clams, scallops, snails, sea stars, and anemones. Another invertebrate--corals--establish reefs that are known to be habitat for black seabass and tautog though research on the locations and extents of these ecologically important patchy habitats is scant.\r\n

\r\nDemersal fish (or groundfish) are characterized by their close association with the seafloor for feeding, spawning, and juvenile nursery areas. The Mid-Atlantic region is particularly productive for demersal fish with some such as summer flounder and black seabass supporting major historic and current recreational and commercial fisheries. \r\n

\r\nDiadromous fish use both freshwater and marine habitats during their life cycle and these species have great cultural and ecological significance in the Mid-Atlantic region. The diadromous fish of the region\u2014striped bass, alewife, American eel, American Shad, Atlantic salmon, Atlantic sturgeon, Atlantic tomcod, blueback herring, hickory shad, rainbow smelt, sea-run brook trout, and shortnose sturgeon--provide an important energy link between freshwater, estuarine, and marine food webs and many of these species are found only in the Northwest Atlantic ocean.\r\n

\r\nLarge pelagic fish are migratory are typically found well above the seafloor in the water column. Pelagic species play a key ecological role as predators that regulate their prey communities and structure marine food webs. Some inhabit the region only seasonally and many of the details of their life history are not known. A selection of important species includes albacore tuna, Atlantic bluefin tuna, blue marlin, swordfish, great hammerhead shark, sand tiger shark, sandbar shark. The wide ranging distribution of these species across diverse habitat types, their roles as apex predators, and their threatened population status make them ripe for inclusion in regional spatial and conservation plans.\r\n

\r\nMarine mammals are large migratory species that use this region primarily in spring and summer when food is abundant. Due to their seasonal abundance and charismatic nature, marine mammals have a long-standing, complex relationship with humans in this region. Ten species, among them bottlenose dolphin, fin whale, harbor porpoise, humpback whale, North Atlantic right whale, and sperm whale are important cultural and biodiversity icons of the region.\r\n

\r\nSea turtles use both oceanic (inner shelf region and offshore) and terrestrial (beach) ecosystems. Their highly migratory and long life history characteristics present unique challenges to their continued protection and recovery. Sea turtles may have once comprised an important component of the region\u2019s coastal food webs, consuming prey including fish, invertebrates, and sea grasses. Three species of sea turtle (green, leatherback and loggerhead) are present in the Mid-Atlantic.\r\n

\r\nThe varied habitats and abundant resources of the Mid-Atlantic support a highly diverse group of coastal and marine birds that depend on both the oceanic and terrestrial ecosystems of the region throughout the year. Millions of birds pass through the region, which is located along the globally significant migration corridor of the Atlantic Flyway, while traveling between breeding and wintering grounds that span the entire Western Hemisphere. Species of high conservation concern, like the Red Knot and Whimbrel depend on high quality coastal habitats for critical stopover areas. Pelagic species, like the Northern Gannet and Audubon\u2019s Shearwater, use open water habitats during both migration and wintering seasons. Shorebirds, waterbirds and waterfowl, such as the Piping Plover, American Oystercatcher, Least Terns, Black Duck and Brant breed or feed along shorelines in the region and can be heavily impacted by increasing human pressure to these coastal systems. Many of the species occurring in the Mid-Atlantic rank as species of high conservation concern.\r\n

\r\nTidal flows, complex seasonal temperature and circulation patterns, and varied seafloor topography combine to create both persistent and shifting habitats that serve as critical resources tracked by Mid-Atlantic marine species, and give rise to upwellings that fuel plankton blooms and key forage species such as menhaden, squid and butterfish. Millions of seabirds, invertebrates, fishes, marine mammals, and large pelagic fishes such as tunas and marlins use diverse Mid-Atlantic habitat and forage resources in specific ways. Cross shelf (east-west) migrants like summer flounder and black seabass and north-south migrants like striped bass, menhaden, and large whales all traverse the region twice a year as they move from southern and near shore locations in winter to offshore or northern locations in summer.\r\n

\r\nThe MARCO Ocean Data Portal has compiled habitat data, as well as known distributions and abundances of many of the key fish, mammal, bird, and reptile species found in the Mid-Atlantic region. In the future, additional data will be added to round out the collection and to allow regional planners to make management and policy decisions that are compatible with and enhance the conservation of these animals and their ecosystem.", - "feature_image": "", - "thumbnail": "", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_marine_life-0.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/conservation.jpg", - "description": "The Mid-Atlantic region is well known for nutrient-rich and highly productive waters. Its estuaries, salt marshes, sea grasses, barrier islands, cold water corals, and submarine canyons provide spawning, nursery, and forage habitats that support diverse resident and migratory marine life including invertebrates, seabirds, fishes, and marine mammals. " - } - }, - { - "pk": 1, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "", - "feature_link": "", - "header_attrib": "", - "display_name": "Administrative", - "name": "administrative", - "overview": "

\r\nNumerous management boundaries in the Mid-Atlantic are compiled here to provide administrative and regulatory contexts to help facilitate well-informed ocean planning decisions.\r\n

\r\nBoundaries are provided courtesy of the responsible agencies and these parties should be consulted to ensure that map layers represented here are current and correctly interpreted. The boundaries presented here should not be considered to be legally binding.", - "feature_image": "", - "thumbnail": "https://s3.amazonaws.com/marco-public-2d/Energy/energy_thumbnail.jpg", - "visible": true, - "factsheet_thumb": "", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/admin.jpg", - "description": "Numerous federal, regional, and state political and management boundaries of the Mid-Atlantic are compiled here to provide a regulatory context to help facilitate well-informed ocean planning decisions." - } - }, - { - "pk": 7, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_recreation_F.pdf", - "feature_link": "", - "header_attrib": "", - "display_name": "Recreation", - "name": "recreation", - "overview": "

\r\nRecreation in nature is a basic human need and reflects our values--Americans love to visit, play, and exercise in parks and other public trust lands. Recreation along the coasts and in the ocean is especially valued and, for many, is essential to their well-being and quality of life. The Mid-Atlantic boasts countless opportunities for entertainment and leisure activities and has flourishing travel, tourism, and outdoor recreation industries, many of which depend on the region\u2019s natural coastal and marine features. Visitors come from all over the country and around the world to enjoy the beaches, wetlands, and barrier islands where they surf, fish, kayak, and participate in organized or self-guided whale and bird watching tours and other pursuits. In addition to the cultural and traditional values coastal and marine ecosystems support, recreational service and supply industries are a significant driver for jobs and the region's economy. For both ethical and economic reasons, developing sound data and information on recreational uses to support forward looking regional ocean planning decisions is critical.\r\n

\r\nThe Mid-Atlantic is a prime location for underwater exploration, and scuba divers can discover a unique array of plants, animals, and historical artifacts. There are countless shipwrecks in the area, for example the 'Faithful Steward'--a British ship headed for Philadelphia in 1785 which lost most of its 250 passengers and was carrying copper coins that can still be found today on Coin Beach, Delaware--and remnants of the Civil War battle between the ironclads Monitor and Merrimac off the coast of Virginia.\r\n

\r\nVisitors who prefer to stay on--and not in--the water can experience the natural beauty of the region by sailing, power boating, kayaking, or canoeing. Surfing is also a popular sport with a long history in the region. Various surfing competitions are a big draw for pros and amateurs, as are the occasions when hurricanes bring unusually high waves to Mid-Atlantic shores. And no summary of regional outdoor activities would be complete without mention of the region\u2019s high quality, broad sandy beaches. These beaches are often the jumping off points for diverse active and leisurely pursuits and some of the most popular spots are Virginia Beach, Ocean City, Rehoboth, Cape May, and the beaches of Long Island.\r\n

\r\nWhale watching is a well-established ecotourism activity in the Mid-Atlantic. Key attractions are the humpback and right whales that migrate through the region on their long journeys north in the spring to feed in the Gulf of Maine and south to Georgia and northern Florida in the autumn to calve. Thousands of people every year take advantage of the special opportunity to make a connection with the largest animals on the planet and to do so in a non-intrusive way. During these cruises, it is also possible to spot other marine mammals such as dolphins and seals, any of three species of sea turtles including the endangered prehistoric giant that is the leatherback, and bird species that can only be seen at sea. \r\n

\r\nThe region's diverse habitats--from extensive coastal marshes and beaches to submarine canyons provide home and stopover sites for hundreds of different bird species and provide plentiful opportunity to see many different nesting and migratory species throughout the year. Many locations along the region\u2019s barrier island coastline including Cape May, Assateague and Chincoteague Islands and the lower eastern shore of Virginia are nationally and globally renowned as premier birding destinations for casual and avid birders alike.\r\n

\r\nThe MARCO Ocean Data Portal team is working with partners and stakeholders to develop data and information on recreational uses and places to enhance the ability of coastal and marine planners to account for, protect and increase coastal and marine recreation opportunities in the region. ", - "feature_image": "", - "thumbnail": "", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_recreation-0.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/recreation.jpg", - "description": "The Mid-Atlantic boasts countless opportunities for entertainment and leisure activities and has flourishing travel, tourism, and outdoor recreation industries, many of which are focused on the region\u2019s natural features. " - } - }, - { - "pk": 5, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_security_F.pdf", - "feature_link": "", - "header_attrib": "", - "display_name": "Security", - "name": "security", - "overview": "

\r\nThe Mid-Atlantic region is a busy corridor for commercial and recreational ship traffic and is home to the world\u2019s largest naval base, as well as many other military installations and training grounds. The U.S. Coast Guard works with other agencies to ensure that navigation routes for both commercial and defense vessels are accessible and safe. Their security focus is on the safety of ports, vessels, and facilities, both on and away from shore and their presence is notable throughout the region, with bases in Norfolk, Baltimore, Cape May, and Staten Island.\r\n

\r\nThe Naval Station at Norfolk, Virginia supports 75 large ships and 130 aircraft on seven miles of piers and wharfs, and it houses the largest concentration of Navy personnel in the country. Every year, its Port Services branch oversees more than 3,000 maneuvers as ships arrive and depart their berths. Spatial planners and resource managers must account for this intensive activity and work with military leaders to ensure their missions are not compromised as planning decisions are made. \r\n

\r\nThe legal framework supporting maritime security in the U.S. is based on five principal laws:\r\n

\r\n

\r\nData under development for the Security theme will include areas with potential hazards or public use restrictions and other information deemed to be critical for spatial planning. To ensure that security interests are fully considered, regional ocean planning leads will include defense representatives and officials responsible for maintaining the security of our vessels, ports and Nation.\r\n", - "feature_image": "", - "thumbnail": "", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_security-0.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/security.jpg", - "description": "The Mid-Atlantic is home to important naval installations and training areas, and it\u2019s a busy corridor for commercial shipping and naval and other defense and security operations. " - } - }, - { - "pk": 10, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "", - "feature_link": "", - "header_attrib": "", - "display_name": "Discrete Zones", - "name": "discrete-zone", - "overview": "", - "feature_image": "", - "thumbnail": "", - "visible": false, - "factsheet_thumb": "", - "feature_excerpt": "", - "header_image": "", - "description": "" - } - }, - { - "pk": 3, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_renewable_energy_WEB_F.pdf", - "feature_link": "", - "header_attrib": "", - "display_name": "Renewable Energy", - "name": "energy", - "overview": "

\r\nOffshore wind has the potential to be a key domestic renewable energy source, especially for the major cities and large population centers along the East coast of the U.S. The Mid-Atlantic\u2019s offshore wind resources have the potential to produce close to 200 gigawatts of energy every year, enough to power 40 million U.S. homes. Someday, the region\u2019s ocean wave energy could generate an additional 50,000 gigawatts of power and contribute even more significantly to the U.S. energy supply. These renewable energy sources could help meet growing electricity demands in the region and help to reduce carbon emissions. \r\n

\r\nProduction of electricity from renewable sources, such as wind and ocean waves, may be less damaging to the environment than production through burning of fossil fuels, like oil, natural gas, and coal because renewable energy facilities produce much lower emissions of greenhouse gasses and other harmful pollutants such as arsenic, lead and mercury. Additionally, renewable energy production may be more cost effective and efficient than traditional methods because once infrastructure is built, the amount of energy produced is quite stable for the remainder of that system\u2019s lifespan. While the inputs (wind and waves) may fluctuate daily or seasonally they should remain consistent over longer time scales, allowing producers and consumers to rely on steady energy levels. \r\n

\r\nThe Department of the Interior has identified Wind Planning Areas (WPA)--locations that may be suitable for wind development--along the Atlantic Ocean\u2019s outer shelf. Data are being collected inside and outside these high priority areas so regulators and stakeholders can make informed and responsible judgments when issuing permits and making siting and investment decisions. Annual average wind speeds are an indication of the potential available energy at a location. Here, wind speeds modeled from limited observations by the National Renewable Energy Laboratory (NREL) and AWS Truepower are expressed at a height of 90 meters above the ocean surface where wind turbine hubs are likely to be located. \r\n

\r\nNot all the wind and waves that exist offshore are available for harvest however, and all potential energy estimates should be constrained to account for various environmental and socioeconomic factors that may exist in an area. Some of these constraints include potential overlapping use conflicts with shipping lanes, marine mammal, bird, and bat migration pathways, and traditional areas for fishing and recreational use. Infrastructure may need to be built far enough from shore to address concerns over impacts to scenic views, but close enough that the cost of bringing the electricity to shore is not prohibitive. All of these issues should be accounted for in regional ocean planning and the MARCO Ocean Data Portal provides key information that will help to raise awareness of the potential for renewable energy and support decision maker\u2019s efforts to manage resources effectively and minimize conflicts.\r\n", - "feature_image": "", - "thumbnail": "https://s3.amazonaws.com/marco-public-2d/Energy/energy_thumbnail.jpg", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_renewable_energy-0.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/energy1.jpg", - "description": "Offshore wind in the Mid-Atlantic holds more than 60,000 Megawatts of potential energy \u2014 that\u2019s 10% of total U.S. offshore potential. This huge resource could help meet the growing electricity demand in the region, while reducing carbon emissions. \r\n" - } - }, - { - "pk": 8, - "model": "data_manager.theme", - "fields": { - "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_ports_F.pdf", - "feature_link": "", - "header_attrib": "", - "display_name": "Maritime", - "name": "maritime-industries", - "overview": "

\r\nMid-Atlantic maritime industries include shipping, transport, tourism, dredging, offshore sand mining, and some of the nation\u2019s busiest ports at New York-New Jersey, Philadelphia, Wilmington, Baltimore, and Norfolk. These ports are crucial links in the nation\u2019s transportation system, constitute a key element of the economy, employ many thousands of people, and have the potential to serve as environmental stewards of our region\u2019s harbors and surrounds.\r\n

\r\nThe U.S. seaport network unloads $3.8 billion in goods each day and Mid-Atlantic ports are a huge contributor, maintaining several national distinctions. The country\u2019s top port for fruits and juices is Wilmington; the fourth busiest tanker port is Philadelphia; products that go through Baltimore\u2019s ports reach over a third of the country within a day and anything entering the U.S. on wheels--from cars to giant tractors--alight in Baltimore, making it the nation\u2019s top Ro-Ro (roll on-roll off) port. The world\u2019s largest natural deep water harbor is at Hampton Roads and it stays ice-free throughout the year, making it suitable for a conglomeration of military facilities, coal piers, shipyards, and miles of waterfront property and beaches which add to the diversity and stability of our nation. The region supports important points of departure for the nation\u2019s cruise ship industry and, in 2011, close to one million people vacationed on ocean cruises originating in New York and Baltimore.\r\n

\r\nThe MARCO Ocean Data Portal contains Automatic Identification System (AIS) information from 2009, processed to focus on highly travelled shipping routes near port entrances. AIS data are collected by the U.S. Coast Guard using automated two-way radio transmissions that track real-time vessel information such as ship identity, purpose, course, and speed, primarily in coastal waters. AIS is required on all passenger vessels and vessels with gross tonnage greater than 300, so smaller vessel traffic is not represented in the database. MARCO is currently consulting with the Coast Guard and shipping industry stakeholders to evaluate how well these data indicate total ship traffic density and what additional data may be needed to fully represent shipping activity.\r\n

\r\nThe viability, safety, and growth needs of the commercial shipping industry need to be addressed in regional ocean planning. Accordingly, MARCO will consult with major port and navigation stakeholders to evaluate what additional map data may be needed to inform regional ocean planning decisions and help ensure stakeholder interests are well represented.\r\n", - "feature_image": "", - "thumbnail": "", - "visible": true, - "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_ports-0.jpg", - "feature_excerpt": "", - "header_image": "/media/marco/img/learn/industry.jpg", - "description": "The Mid-Atlantic ports are some of the busiest in the nation\u2019s seaport network, which unloads $3.8 billion in goods each day. 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} - }, - { - "pk": 11, - "model": "data_manager.lookupinfo", - "fields": { - "color": "#97E600", - "dashstyle": "solid", - "graphic": "/media/data_manager/images/awc_hub_icon.png", - "value": "Hub", - "fill": false - } - }, - { - "pk": 30, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Seasonal/anomaly maps including surface/bottom temperatures, currents, wind speed, and shear stress", - "expected_date": "TBD", - "notes": "Oceanographic data products currently in development include sea surface temperature anomaly maps and surface currents.", - "themes": [ - 2 - ], - "source": "Multiple sources including MARACOOS, UMASS Dartmouth, Rutgers, and NERACOOS", - "contact": "Rick Lathrop, Rutgers CRSSA; Jay Odell, TNC", - "contact_email": "", - "description": "Data needs include \"stand alone\" map layers for Portal display as well as spatial data inputs for models to support regional planning, e.g. pelagic habitat models." - } - }, - { - "pk": 11, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Municipal and private discharge", - "expected_date": "Fall, 2012", - "notes": "In addition to point locations, effluent plume models would be useful for informing ocean planning efforts.", - "themes": [ - 1 - ], - "source": "EPA", - "contact": "Rutgers CRSSA ", - "contact_email": "", - "description": "Discharge of effluent from waste water treatment plants receiving waste water from households, commercial establishments and industries in the coastal drainage basin." - } - }, - { - "pk": 19, - "model": "data_manager.dataneed", - "fields": { - "status": "Availability of suitable Mid-Atlantic specific models and model derived map layers is being evaluated.", - "archived": true, - "name": "Ocean model results", - "expected_date": "TBD", - "notes": "FVCOM can be used for all of the NROC area and the northern part of MARCO area; additional modeling may be needed for MARCO.", - "themes": [ - 2 - ], - "source": "Potentially multiple sources including UMASS Dartmouth, Rutgers, Old Dominion University, MARACOOS and NERACOOS", - "contact": "Rutgers CRSSA, MARACOOS", - "contact_email": "", - "description": "For example, Finite Volume Coastal Ocean Model (FVCOM) is a coastal ocean circulation model developed by UMASSD-WHOI that includes information on current, wave regime, temperature, salinity and density." - } - }, - { - "pk": 25, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Improved sediment and seafloor habitat maps, benthic resilence maps", - "expected_date": "Summer 2014", - "notes": "Two year project, all final products due 5/2015, sediment maps and other select products will be available sooner.", - "themes": [ - 2 - ], - "source": "Umass/Dartmouth (SMAST)", - "contact": "Kevin Stokesbury, SMAST", - "contact_email": "", - "description": "Analysis of 10 years of video survey data and integration with FVCOM oceanography data to produce high resolution sediment, habitat, andforce stability regime maps." - } - }, - { - "pk": 17, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate sampling of NCCOS models into Portal", - "archived": false, - "name": "Regional scale predictive distribution model for sea birds, sea ducks, and other bird species", - "expected_date": "June 2014", - "notes": "Several other survey and modeling efforts are under way; integration to create new spatial data for regional ocean planning will be provided by NROC project and may also be addressed through the Mid-Atlantic Regional Ocean Assessment.", - "themes": [ - 2 - ], - "source": " Multiple sources including USGS and BOEM Compendium of Avian Information in U.S. Atlantic OCS", - "contact": "NOAA National Centers for Coastal Ocean Science", - "contact_email": "", - "description": "A high resolution, predictive model created using historic bird survey and oceanographic model data." - } - }, - { - "pk": 31, - "model": "data_manager.dataneed", - "fields": { - "status": "Analysis under development", - "archived": false, - "name": "Vessel traffic trends 2011-2013", - "expected_date": "Oct-14", - "notes": "Currently, Rutgers and TNC are working with the USCG and the USACE to develop a process to analyze multiple years of AIS data to detect signficiant changes in vessel utilization patterns and trends. ", - "themes": [ - 8 - ], - "source": "U.S. Coast Guard and NOAA Coastal Services Center", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Using three years (2011, 2012, 2013) of Automated Identification System (AIS) traffic density data, these derived data products will depict the shifts in maritime traffic by vessel type over time. " - } - }, - { - "pk": 24, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Cultural use areas", - "expected_date": "June 2013", - "notes": "Development and use of these data based on outcome of discussions between Tribal leaders and state and federal agency representatives.", - "themes": [ - 1 - ], - "source": "Tribal leaders", - "contact": "MARCO", - "contact_email": "", - "description": "Areas significant to Tribal Nations and other cultures." - } - }, - { - "pk": 16, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate authorized data into Portal", - "archived": true, - "name": "Coldwater coral predictive distribution model", - "expected_date": "Spring 2013", - "notes": "NCCOS and NEFSC working on a predictive model for the Mid-Atlantic.", - "themes": [ - 2 - ], - "source": "Multiple sources ", - "contact": "NOAA Biogeography Branch ", - "contact_email": "", - "description": "A high resolution, predictive model of coral habitat and distribution." - } - }, - { - "pk": 18, - "model": "data_manager.dataneed", - "fields": { - "status": "Bird Focus Area data developed; awaiting authorization for posting on Portal. Bat data to be developed. ", - "archived": false, - "name": "Important coastal bird and bat habitat", - "expected_date": "July 2014", - "notes": "TNC working with USFWS to ensure data is properly licensed before displaying and making available on Portal. ", - "themes": [ - 2 - ], - "source": "Atlantic Coast Joint Venture U.S. Fish and Wildlife Service", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Atlantic Coast Joint Venture habitat focus areas in the Mid-Atlantic Bird Conservation Region for landbirds, shorebirds, waterbirds, and waterfowl, respectively. Bat habitat focus areas not yet established regionally. " - } - }, - { - "pk": 26, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development in disparate efforts; planning stages for data integration.", - "archived": false, - "name": "Nearshore benthic habitats", - "expected_date": "TBD", - "notes": "Several new survey efforts are underway or envisioned to support wind energy permitting and development processes; additional surveys to cover non-Wind Planning Areas and additional coordination and potential integration of parallel efforts needed.", - "themes": [ - 2 - ], - "source": "Multiple efforts underway including MD CZM studies, NOAA HabCam, BOEM funded work by SMAST, and historic and current investigations.", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Finer scale spatial data are needed to complement exising habitat models, especially for sensitive cold water coral patch communities and other sensitive or vulnerable habitat types." - } - }, - { - "pk": 8, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Vessel Monitoring System (VMS) fishing data", - "expected_date": "December 2012", - "notes": "Data has been transferred from NMFS and will need to be processed to provide maximum utility in consideration of confidentiality requirements.", - "themes": [ - 4 - ], - "source": "NOAA/ NMFS", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "VMS are required for many commercial fisheries to monitor the position, time at a position, course and speed of fishing vessels." - } - }, - { - "pk": 7, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Vessel Trip Report (VTR)", - "expected_date": "Fall 2013", - "notes": "Regional scale VTR data aggregated to ten minute squares are currently displayed on the portal and are available upon request. Finer resolution data linking fishing locations with communities are under development in consultation with fishing industry participants. All fishery data will be depicted in consideration of confidentiality requirements established by NOAA-Fisheries.", - "themes": [ - 4 - ], - "source": "NOAA/NMFS, analysis by Rutgers University", - "contact": "Center for Remote Sensing and Spatial Analysis, Rutgers University", - "contact_email": "", - "description": "Derived data products representing fishing effort by port and gear type." - } - }, - { - "pk": 27, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate authorized data into Portal", - "archived": false, - "name": "Live submarine telecommunications cables", - "expected_date": "TBD", - "notes": "Current data displayed on MMC and Portal are from NOAA ENCs. These data are incomplete and do not distinguish between in-service and out-of-service cables. The North American Submarine Cable Association (NASCA) is currently updating their national Route Position Line database for ocean planning. However, at this point in time, they will only make these data available as PDF documents. We are still in negotiations with NASCA regarding their making the actual RPL data available to the Portal. ", - "themes": [ - 8 - ], - "source": "Multiple sources including North American Submarine Cable Association and member companies.", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Vector data of live telecommunications cables running either underneath or on top of the sea floor." - } - }, - { - "pk": 9, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Sand, gravel, and cobble mining locations", - "expected_date": " October 2014", - "notes": "Currently, we have detailed information for MD only and work continues to develop a regional scale map layer using state and federal sources. ", - "themes": [ - 8 - ], - "source": "Multiple agencies including ACOE, BOEM, Mid-Atlantic States", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Areas where resources are actively mined from the seafloor and potential source areas." - } - }, - { - "pk": 3, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development\r\n", - "archived": false, - "name": "Marine mammal population density and migration paths", - "expected_date": "Fall 2014", - "notes": "OBIS Seamap is currently refining new marine mammal model data, expected Fall 2014. New data on marine mammals in Mid-Atlantic forthcoming from AMAPPS and BRI in 2015. The Northeast Regional Ocean Council is funding a new project to integrate past and ongoing marine mammal surveys to produce new spatial data for regional ocean planning.\r\n", - "themes": [ - 2 - ], - "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Coastal Zone Mgmt/VA Aquarium, and Duke University (OBIS)", - "contact": "The Nature Conservancy ", - "contact_email": "", - "description": "Population density distribution estimates (actual and modeled) and delineation of seasonal migratory pathways for large whales (toothed and baleen), dolphins and porpoises. \r\n" - } - }, - { - "pk": 21, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Recreational fishing activity", - "expected_date": "June 2013", - "notes": "Existing data on recreational fishing locations is of variable quality, resolution and geographic extent. Participatory GIS workshops with recreational fishery stakeholders began summer 2012 and will continue through the fall and winter; these efforts will be supplemented by other surveys planned for 2013.", - "themes": [ - 4 - ], - "source": "Recreational fishers via MARCO stakeholder engagement efforts", - "contact": "Rutgers CRSSA ", - "contact_email": "", - "description": "Areas where non-commercial fishing (recreational/sport fishing) occurs." - } - }, - { - "pk": 10, - "model": "data_manager.dataneed", - "fields": { - "status": "Not initiated.", - "archived": true, - "name": "State landings and fishing effort ", - "expected_date": "To be determined (beyond scope of current funding)", - "notes": "Most ocean fishery harvests are documented through federal reporting systems but there are gaps for some fisheries that do not require federal licenses, e.g. croaker and whelks (\"conch\") in Virginia.", - "themes": [ - 4 - ], - "source": "States", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Information about commercial harvest activity collected by state agencies in the Mid-Atlantic." - } - }, - { - "pk": 12, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Energy facilities", - "expected_date": "Spring 2013", - "notes": "In addition to point locations, plume models would be useful for informing ocean planning efforts.", - "themes": [ - 3 - ], - "source": "Multiple agencies including FERC, NREL, NRC, and the EPA", - "contact": "Rutgers CRSSA ", - "contact_email": "", - "description": "Examples include nuclear power plant locations and their discharge pipe locations, potential/existing hydrokinetic sites, etc." - } - }, - { - "pk": 5, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate authorized data into Portal", - "archived": true, - "name": "Turtles-Distribution and Nesting Areas (ESI)", - "expected_date": "As soon as vetted by Portal Data Review Group", - "notes": "ESI maps provide a concise summary of coastal resources that are at risk if an oil spill occurs nearby. Vector polygons in this data set represent turtle distribution.", - "themes": [ - 2 - ], - "source": "TNC NAM ERA compiled; source data from Environmental Sensitivity Index, NOAA", - "contact": "The Nature Conservancy ", - "contact_email": "", - "description": "Sea turtle areas displayed on the maps are limited to nesting beaches and several well-known in-water concentration areas. Sea turtle nesting beaches include sandy beach areas where sea turtles come ashore to nest." - } - }, - { - "pk": 20, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Commercial fishing activity (VTR)", - "expected_date": "September, 2014", - "notes": "Data developed using \"Communities at Sea\" mapping approach. Draft maps produced and currently under review by fishing industry contacts. Development of additional map layers to address key gaps including state managed fisheries will begin July 2014. Additional potential data sources include NOAA's Vessel Monitoring System, state agency collected data and participatory mapping projects with fishermen. ", - "themes": [ - 4 - ], - "source": "NOAA-NMFS, developed in consultation with Portal Team's commercial fishery advisory group.", - "contact": "Rick Lathrop, Rutgers CRSSA", - "contact_email": "", - "description": "Map layers developed using aggregated records from NOAA's Fishing Vessel Trip Report and permit databases in consultation with commercial fishing stakeholders to illustrate the distribution and importance of commercial fishing activity by diverse communities (port, vessel type and gear group combinations). Additional attributes collected through stakeholder engagement may include information about the specific socio-economic value of fishing locations to communities. " - } - }, - { - "pk": 28, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Municipal and private discharge", - "expected_date": " October 2014", - "notes": "In addition to point locations, effluent plume models may be useful for informing ocean planning efforts.", - "themes": [], - "source": "EPA", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Point locations for waste water treatment plant facilities and outfalls including attributes for volume of discharge. " - } - }, - { - "pk": 6, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate authorized data into Portal", - "archived": true, - "name": "Large Pelagic Species (sharks, tuna, marlin)-Species Richness, Persistence and EFH", - "expected_date": "As soon as vetted by Portal Data Review Group", - "notes": "14 species represented include: Albacore Tuna, Bigeye Thresher, Blue Marlin, Bluefin Tuna, Dusky shark, Great Hammerhead, Porbeagle, Sandbar shark, Sand Tiger, Shortfin Mako, Swordfish, Thresher, White Marlin, Scalloped Hammerhead\r\n", - "themes": [ - 2 - ], - "source": "TNC NAM ERA compiled; source data from NMFS- SEFSC and NMFS-NEFSC; EFH from NMFS and HMS FMP", - "contact": "The Nature Conservancy ", - "contact_email": "", - "description": "Target species richness refers to the total number of target species by age class observed within a TMS summed and mapped based on all available data (1965-2004). Persistence refers to the sum of the number of decades that a given target species was present (1-4) for combined juvenile and adult observations. Habitat refers to the number of target species whose EFH overlapped each TMS determined and summarized by total target species and by age class.\r\n" - } - }, - { - "pk": 23, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Areas of recreational activities including fishing, boating, surface water sports, wildlife viewing,", - "expected_date": " August 2014", - "notes": "Drafts of the data are complete and are under review by stakeholders, tribal leaders, and states. A regional dataset that integrates the three survey methods is under development.", - "themes": [ - 7 - ], - "source": "Recreational users, via stakeholder engagement efforts such as participatory workshops (pGIS), Surfrider Coastal Rec survey, and Mid-Atlantic Rec Boater Survey", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Activities include fishing, boating, diving, surfing, swimming, nature viewing. " - } - }, - { - "pk": 13, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Automatic Identification System (AIS) ship traffic", - "expected_date": "June 2013", - "notes": "", - "themes": [ - 8 - ], - "source": "USCG & NOAA", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "AIS is an automated tracking system used on ships and by Vessel Traffic Services for identifying and locating vessels by electronically exchanging data with other nearby ships and VTS stations. AIS provides information such as unique identification, position, course, and speed. A preliminary AIS map layer has been added to the Portal as a placeholder; enhanced AIS map layers showing traffic patterns by vessel type and other attributes are under development by NOAA Coastal Services Center and others." - } - }, - { - "pk": 2, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to incorporate authorized data into Portal\r\n", - "archived": false, - "name": "Coldwater coral predictive distribution model", - "expected_date": "May 2014", - "notes": "NCCOS and NEFSC working on a predictive model for the Mid-Atlantic and Northeast Atlantic. The Portal's separate coral point data set will continue to be updated as new survey data are released.", - "themes": [ - 2 - ], - "source": "Multiple sources ", - "contact": "Brian Kinlan, NOAA Biogeography Branch", - "contact_email": "", - "description": "A high resolution, predictive model of coral habitat and distribution.\r\n" - } - }, - { - "pk": 32, - "model": "data_manager.dataneed", - "fields": { - "status": "Dat under development", - "archived": false, - "name": "Danger Zones and restricted Areas", - "expected_date": "Winter 2015", - "notes": "NOAA is creating a national geospatial database of the Danger Zones and Restricted Areas based on the most current Code of Federal Regulations for the Cadastre. ", - "themes": [ - 5 - ], - "source": "NOAA is digitizing the areas as described in the Code of Federal Regulations ", - "contact": "NOAA Coastal Services Center", - "contact_email": "", - "description": "This fall, NOAA intends to release a revised version of Danger Zones and Restricted Areas based on the most current areas designated as such in the CFR. These areas are either high risk areas where hazardous operations occur on full time or intermittent basis or high security areas to protect Government property, usually for national security purposes, that are either closed to or restric public access." - } - }, - { - "pk": 14, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": true, - "name": "Port locations and attributes", - "expected_date": "Spring 2013", - "notes": "Port locations are known, additional work is underway to work with port's stakeholders to develop relevant spatial data and information for each port.", - "themes": [ - 8 - ], - "source": "ACOE; Individual ports", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Locations of ports, how they relate to shipping traffic and their capacity for servicing offshore energy development" - } - }, - { - "pk": 22, - "model": "data_manager.dataneed", - "fields": { - "status": "Data development not yet initiated", - "archived": true, - "name": "Recreational boating activity", - "expected_date": "TBD", - "notes": "Initial data is being collected via participatory GIS workshops with recreational stakeholders, summer 2012 and will continue through the fall and winter; these efforts will be supplemented by other surveys planned for 2013.", - "themes": [ - 7 - ], - "source": "Recreational boaters via MARCO stakeholder engagement efforts", - "contact": "Rutgers CRSSA ", - "contact_email": "", - "description": "Areas where recreational boating (regattas, pleasure, cruises, water skiing, etc.) occurs." - } - }, - { - "pk": 1, - "model": "data_manager.dataneed", - "fields": { - "status": "Efforts underway to develop and incorporate authorized data into Portal\r\n", - "archived": true, - "name": "Military, hazard and restricted areas", - "expected_date": "Unknown ", - "notes": "", - "themes": [ - 5 - ], - "source": "USCG & DOD including ACOE, Navy, etc. ", - "contact": "NOAA CSC ", - "contact_email": "", - "description": "Information pertaining to uses of the marine environment by the Department of Defense for training, classified or restricted areas, with unexploded ordinances, etc.\r\n" - } - }, - { - "pk": 15, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Marine wildlife (whales, birds, turtles, bats) distribution and migration paths", - "expected_date": "Fall 2014", - "notes": "OBIS Seamap is currently refining new marine mammal model data, expected Fall 2014. The Northeast Regional Ocean Council is funding a new project to integrate past and ongoing marine mammal surveys to produce new spatial data for regional ocean planning.", - "themes": [ - 2 - ], - "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Aquarium, and Duke University (OBIS).", - "contact": "The Nature Conservancy", - "contact_email": "", - "description": "Critical seasonal migratory pathways for large whales (toothed and baleen), dolphins and porpoises, sea turtles, sea birds and sea ducks, and bats." - } - }, - { - "pk": 4, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development\r\n", - "archived": false, - "name": "Sea turtle population density and migration paths", - "expected_date": "TBD", - "notes": "New data on sea turtles in Mid-Atlantic forthcoming from AMAPPS and BRI in 2015. \r\n", - "themes": [ - 2 - ], - "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Aquarium, and Duke University (OBIS)", - "contact": "The Nature Conservancy ", - "contact_email": "", - "description": "Population density distribution estimates (actual and modeled) and delineation of seasonal migratory pathways for sea turtles through Mid-Atlantic. " - } - }, - { - "pk": 29, - "model": "data_manager.dataneed", - "fields": { - "status": "Data under development", - "archived": false, - "name": "Department of Defense Operational Areas (OPAREAS) ", - "expected_date": "Fall 2015", - "notes": "U.S. Navy developing improved data that characterizes compatibility of human uses with military operational areas. ", - "themes": [ - 5 - ], - "source": "DOD Environmental Information Management System (EIMS)", - "contact": "U.S. Fleet Forces Command, U.S. Navy", - "contact_email": "", - "description": "OPAREA is an area where DOD's Atlantic Fleet routinely conducts training exercises and system qualification tests via ships and aircrafts. Data under development will include general attributes about specific activities occurring in OPAREAS related to testing and training. " - } - } -] +[ + { + "pk": 12, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "", + "feature_link": "", + "header_attrib": "", + "display_name": "Alternatives", + "name": "industry-alternatives", + "overview": "", + "feature_image": "", + "thumbnail": "", + "visible": false, + "factsheet_thumb": "", + "feature_excerpt": "", + "header_image": "", + "description": "" + } + }, + { + "pk": 4, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_fisheries_F.pdf", + "feature_link": "", + "header_attrib": "", + "display_name": "Fishing", + "name": "fishing", + "overview": "

\r\nThe Mid-Atlantic\u2019s highly productive estuaries and diverse coastal and ocean habitats support substantial commercial and recreational fisheries that provide income, food, and enjoyment for millions of people. Fishing is an essential component of the region\u2019s rich cultural heritage and directly connects coastal community residents and tourists to the ocean, whether through fresh seafood or the thrill of a day spent fishing on the ocean. \r\n

\r\nIn 2010, the Mid-Atlantic\u2019s commercial harvest was more than 800 million pounds, with Atlantic menhaden making up over 60% of the catch. Other key commercial species include sea scallop, surf clam, ocean quahog clam, summer flounder, lobster, squid, and striped bass. The total 2010 ex-vessel value (initial price paid to fishermen) was well over $500 million and sea scallops were the most valuable of the species. But the value of commercial fisheries extends beyond ex-vessel price. In 2009, the region\u2019s fisheries supported an estimated 116,000 jobs in industries ranging from equipment supply to seafood processing and retail.\r\n\r\nRoughly 2.6 million recreational anglers participated in 17 million saltwater fishing trips in 2009, mainly targeting striped bass, summer flounder, black seabass, tautog, scup, bluefish, drum, weakfish, spot, and croaker. They spent an estimated $3.5 billion on the fishing-related vehicles, tackle, boats, equipment, and second homes. That same year, the recreational fishing industry in the Mid-Atlantic supported approximately 25,000 jobs.\r\n

\r\nThe MARCO Ocean Data Portal includes commercial fishing effort for mobile bottom-contacting gear (e.g., trawls and dredges), pelagic gear (e.g., mid-water trawls, gill nets, and hook and line), and all gear combined. The map layers were created using Fishing Vessel Trip Report data provided by the National Marine Fisheries Service. These data are presented at a coarse spatial scale (i.e., 70-100 square nautical miles) and illustrate the regional importance of commercial fishing areas, but are less than ideal for coastal and marine planning. Further, MARCO does not include specific recreational fishing information, although for-hire sector fishing effort is included in the commercial pelagic gear map layer. \r\n

\r\nMARCO is working to improve the commercial fishing data represented here and to add recreational fishing information. Planned improvements include creation of higher resolution commercial fishing activity maps and development of products--in conjunction with stakeholders--that best represent commercial fishing interests and values, while protecting confidential information. Efforts to create maps of recreational use areas are being developed with assistance from anglers in all Mid-Atlantic states, and a new online recreational boater survey to enhance these efforts is being designed for implementation in late 2012. \r\n

\r\nThe Mid-Atlantic Fisheries Management Council and the Atlantic States Marine Fisheries Commission have management authority for most recreational and commercial ocean fisheries. Some migratory species (e.g., sharks and tunas), are managed separately by the National Marine Fisheries Service. MARCO will coordinate and consult with all of these institutions as appropriate to acquire and develop fishing data suitable for public display. ", + "feature_image": "", + "thumbnail": "", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/fishing.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/fishing_boats1.jpg", + "description": "The Portal will be collecting and integrating data on the productive habitats and rich species diversity that are essential for maintaining healthy fishing areas. " + } + }, + { + "pk": 9, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "", + "feature_link": "", + "header_attrib": "", + "display_name": "Relevant Data", + "name": "relevant-data", + "overview": "", + "feature_image": "", + "thumbnail": "", + "visible": false, + "factsheet_thumb": "", + "feature_excerpt": "", + "header_image": "", + "description": "" + } + }, + { + "pk": 11, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "", + "feature_link": "", + "header_attrib": "", + "display_name": "Broad Zones", + "name": "broad-zones", + "overview": "", + "feature_image": "", + "thumbnail": "", + "visible": false, + "factsheet_thumb": "", + "feature_excerpt": "", + "header_image": "", + "description": "" + } + }, + { + "pk": 2, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_ports_F.pdf", + "feature_link": "", + "header_attrib": "Photo \u00a9 Michael Eversmier", + "display_name": "Marine Life", + "name": "conservation", + "overview": "

\r\nThe Mid-Atlantic is well known for nutrient-rich and highly productive waters. The region is a transitional area between the rocky shores of New England and the gently sloping South Atlantic, and it is influenced by two large estuaries, Chesapeake Bay and Delaware Bay. As a result, the Mid-Atlantic region is home to a wealth of complex ecosystems and its estuaries, salt marshes, sea grasses, barrier islands, cold water corals, and submarine canyons provide spawning, nursery, and forage habitats that support diverse resident and migratory marine life including invertebrates, seabirds, fishes, and marine mammals. \r\n

\r\nThe topography is mostly flat, but features sandy shoals and swales, sand wedges and waves, and a broad continental shelf embedded cold water coral patch habitats and incised by submarine canyons along the shelf-slope break. These areas support biologically diverse and abundant benthic (seafloor) macrofauna, demersal fish, and foraging concentrations of sea birds, sea ducks, and bottlenose dolphins. Benthic habitats contain over 2000 species of invertebrates such as marine worms, sponges, shrimp, crab, clams, scallops, snails, sea stars, and anemones. Another invertebrate--corals--establish reefs that are known to be habitat for black seabass and tautog though research on the locations and extents of these ecologically important patchy habitats is scant.\r\n

\r\nDemersal fish (or groundfish) are characterized by their close association with the seafloor for feeding, spawning, and juvenile nursery areas. The Mid-Atlantic region is particularly productive for demersal fish with some such as summer flounder and black seabass supporting major historic and current recreational and commercial fisheries. \r\n

\r\nDiadromous fish use both freshwater and marine habitats during their life cycle and these species have great cultural and ecological significance in the Mid-Atlantic region. The diadromous fish of the region\u2014striped bass, alewife, American eel, American Shad, Atlantic salmon, Atlantic sturgeon, Atlantic tomcod, blueback herring, hickory shad, rainbow smelt, sea-run brook trout, and shortnose sturgeon--provide an important energy link between freshwater, estuarine, and marine food webs and many of these species are found only in the Northwest Atlantic ocean.\r\n

\r\nLarge pelagic fish are migratory are typically found well above the seafloor in the water column. Pelagic species play a key ecological role as predators that regulate their prey communities and structure marine food webs. Some inhabit the region only seasonally and many of the details of their life history are not known. A selection of important species includes albacore tuna, Atlantic bluefin tuna, blue marlin, swordfish, great hammerhead shark, sand tiger shark, sandbar shark. The wide ranging distribution of these species across diverse habitat types, their roles as apex predators, and their threatened population status make them ripe for inclusion in regional spatial and conservation plans.\r\n

\r\nMarine mammals are large migratory species that use this region primarily in spring and summer when food is abundant. Due to their seasonal abundance and charismatic nature, marine mammals have a long-standing, complex relationship with humans in this region. Ten species, among them bottlenose dolphin, fin whale, harbor porpoise, humpback whale, North Atlantic right whale, and sperm whale are important cultural and biodiversity icons of the region.\r\n

\r\nSea turtles use both oceanic (inner shelf region and offshore) and terrestrial (beach) ecosystems. Their highly migratory and long life history characteristics present unique challenges to their continued protection and recovery. Sea turtles may have once comprised an important component of the region\u2019s coastal food webs, consuming prey including fish, invertebrates, and sea grasses. Three species of sea turtle (green, leatherback and loggerhead) are present in the Mid-Atlantic.\r\n

\r\nThe varied habitats and abundant resources of the Mid-Atlantic support a highly diverse group of coastal and marine birds that depend on both the oceanic and terrestrial ecosystems of the region throughout the year. Millions of birds pass through the region, which is located along the globally significant migration corridor of the Atlantic Flyway, while traveling between breeding and wintering grounds that span the entire Western Hemisphere. Species of high conservation concern, like the Red Knot and Whimbrel depend on high quality coastal habitats for critical stopover areas. Pelagic species, like the Northern Gannet and Audubon\u2019s Shearwater, use open water habitats during both migration and wintering seasons. Shorebirds, waterbirds and waterfowl, such as the Piping Plover, American Oystercatcher, Least Terns, Black Duck and Brant breed or feed along shorelines in the region and can be heavily impacted by increasing human pressure to these coastal systems. Many of the species occurring in the Mid-Atlantic rank as species of high conservation concern.\r\n

\r\nTidal flows, complex seasonal temperature and circulation patterns, and varied seafloor topography combine to create both persistent and shifting habitats that serve as critical resources tracked by Mid-Atlantic marine species, and give rise to upwellings that fuel plankton blooms and key forage species such as menhaden, squid and butterfish. Millions of seabirds, invertebrates, fishes, marine mammals, and large pelagic fishes such as tunas and marlins use diverse Mid-Atlantic habitat and forage resources in specific ways. Cross shelf (east-west) migrants like summer flounder and black seabass and north-south migrants like striped bass, menhaden, and large whales all traverse the region twice a year as they move from southern and near shore locations in winter to offshore or northern locations in summer.\r\n

\r\nThe MARCO Ocean Data Portal has compiled habitat data, as well as known distributions and abundances of many of the key fish, mammal, bird, and reptile species found in the Mid-Atlantic region. In the future, additional data will be added to round out the collection and to allow regional planners to make management and policy decisions that are compatible with and enhance the conservation of these animals and their ecosystem.", + "feature_image": "", + "thumbnail": "", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_marine_life-0.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/conservation.jpg", + "description": "The Mid-Atlantic region is well known for nutrient-rich and highly productive waters. Its estuaries, salt marshes, sea grasses, barrier islands, cold water corals, and submarine canyons provide spawning, nursery, and forage habitats that support diverse resident and migratory marine life including invertebrates, seabirds, fishes, and marine mammals. " + } + }, + { + "pk": 1, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "", + "feature_link": "", + "header_attrib": "", + "display_name": "Administrative", + "name": "administrative", + "overview": "

\r\nNumerous management boundaries in the Mid-Atlantic are compiled here to provide administrative and regulatory contexts to help facilitate well-informed ocean planning decisions.\r\n

\r\nBoundaries are provided courtesy of the responsible agencies and these parties should be consulted to ensure that map layers represented here are current and correctly interpreted. The boundaries presented here should not be considered to be legally binding.", + "feature_image": "", + "thumbnail": "https://s3.amazonaws.com/marco-public-2d/Energy/energy_thumbnail.jpg", + "visible": true, + "factsheet_thumb": "", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/admin.jpg", + "description": "Numerous federal, regional, and state political and management boundaries of the Mid-Atlantic are compiled here to provide a regulatory context to help facilitate well-informed ocean planning decisions." + } + }, + { + "pk": 7, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_recreation_F.pdf", + "feature_link": "", + "header_attrib": "", + "display_name": "Recreation", + "name": "recreation", + "overview": "

\r\nRecreation in nature is a basic human need and reflects our values--Americans love to visit, play, and exercise in parks and other public trust lands. Recreation along the coasts and in the ocean is especially valued and, for many, is essential to their well-being and quality of life. The Mid-Atlantic boasts countless opportunities for entertainment and leisure activities and has flourishing travel, tourism, and outdoor recreation industries, many of which depend on the region\u2019s natural coastal and marine features. Visitors come from all over the country and around the world to enjoy the beaches, wetlands, and barrier islands where they surf, fish, kayak, and participate in organized or self-guided whale and bird watching tours and other pursuits. In addition to the cultural and traditional values coastal and marine ecosystems support, recreational service and supply industries are a significant driver for jobs and the region's economy. For both ethical and economic reasons, developing sound data and information on recreational uses to support forward looking regional ocean planning decisions is critical.\r\n

\r\nThe Mid-Atlantic is a prime location for underwater exploration, and scuba divers can discover a unique array of plants, animals, and historical artifacts. There are countless shipwrecks in the area, for example the 'Faithful Steward'--a British ship headed for Philadelphia in 1785 which lost most of its 250 passengers and was carrying copper coins that can still be found today on Coin Beach, Delaware--and remnants of the Civil War battle between the ironclads Monitor and Merrimac off the coast of Virginia.\r\n

\r\nVisitors who prefer to stay on--and not in--the water can experience the natural beauty of the region by sailing, power boating, kayaking, or canoeing. Surfing is also a popular sport with a long history in the region. Various surfing competitions are a big draw for pros and amateurs, as are the occasions when hurricanes bring unusually high waves to Mid-Atlantic shores. And no summary of regional outdoor activities would be complete without mention of the region\u2019s high quality, broad sandy beaches. These beaches are often the jumping off points for diverse active and leisurely pursuits and some of the most popular spots are Virginia Beach, Ocean City, Rehoboth, Cape May, and the beaches of Long Island.\r\n

\r\nWhale watching is a well-established ecotourism activity in the Mid-Atlantic. Key attractions are the humpback and right whales that migrate through the region on their long journeys north in the spring to feed in the Gulf of Maine and south to Georgia and northern Florida in the autumn to calve. Thousands of people every year take advantage of the special opportunity to make a connection with the largest animals on the planet and to do so in a non-intrusive way. During these cruises, it is also possible to spot other marine mammals such as dolphins and seals, any of three species of sea turtles including the endangered prehistoric giant that is the leatherback, and bird species that can only be seen at sea. \r\n

\r\nThe region's diverse habitats--from extensive coastal marshes and beaches to submarine canyons provide home and stopover sites for hundreds of different bird species and provide plentiful opportunity to see many different nesting and migratory species throughout the year. Many locations along the region\u2019s barrier island coastline including Cape May, Assateague and Chincoteague Islands and the lower eastern shore of Virginia are nationally and globally renowned as premier birding destinations for casual and avid birders alike.\r\n

\r\nThe MARCO Ocean Data Portal team is working with partners and stakeholders to develop data and information on recreational uses and places to enhance the ability of coastal and marine planners to account for, protect and increase coastal and marine recreation opportunities in the region. ", + "feature_image": "", + "thumbnail": "", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_recreation-0.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/recreation.jpg", + "description": "The Mid-Atlantic boasts countless opportunities for entertainment and leisure activities and has flourishing travel, tourism, and outdoor recreation industries, many of which are focused on the region\u2019s natural features. " + } + }, + { + "pk": 5, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_security_F.pdf", + "feature_link": "", + "header_attrib": "", + "display_name": "Security", + "name": "security", + "overview": "

\r\nThe Mid-Atlantic region is a busy corridor for commercial and recreational ship traffic and is home to the world\u2019s largest naval base, as well as many other military installations and training grounds. The U.S. Coast Guard works with other agencies to ensure that navigation routes for both commercial and defense vessels are accessible and safe. Their security focus is on the safety of ports, vessels, and facilities, both on and away from shore and their presence is notable throughout the region, with bases in Norfolk, Baltimore, Cape May, and Staten Island.\r\n

\r\nThe Naval Station at Norfolk, Virginia supports 75 large ships and 130 aircraft on seven miles of piers and wharfs, and it houses the largest concentration of Navy personnel in the country. Every year, its Port Services branch oversees more than 3,000 maneuvers as ships arrive and depart their berths. Spatial planners and resource managers must account for this intensive activity and work with military leaders to ensure their missions are not compromised as planning decisions are made. \r\n

\r\nThe legal framework supporting maritime security in the U.S. is based on five principal laws:\r\n

\r\n

\r\nData under development for the Security theme will include areas with potential hazards or public use restrictions and other information deemed to be critical for spatial planning. To ensure that security interests are fully considered, regional ocean planning leads will include defense representatives and officials responsible for maintaining the security of our vessels, ports and Nation.\r\n", + "feature_image": "", + "thumbnail": "", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_security-0.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/security.jpg", + "description": "The Mid-Atlantic is home to important naval installations and training areas, and it\u2019s a busy corridor for commercial shipping and naval and other defense and security operations. " + } + }, + { + "pk": 10, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "", + "feature_link": "", + "header_attrib": "", + "display_name": "Discrete Zones", + "name": "discrete-zone", + "overview": "", + "feature_image": "", + "thumbnail": "", + "visible": false, + "factsheet_thumb": "", + "feature_excerpt": "", + "header_image": "", + "description": "" + } + }, + { + "pk": 3, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_renewable_energy_WEB_F.pdf", + "feature_link": "", + "header_attrib": "", + "display_name": "Renewable Energy", + "name": "energy", + "overview": "

\r\nOffshore wind has the potential to be a key domestic renewable energy source, especially for the major cities and large population centers along the East coast of the U.S. The Mid-Atlantic\u2019s offshore wind resources have the potential to produce close to 200 gigawatts of energy every year, enough to power 40 million U.S. homes. Someday, the region\u2019s ocean wave energy could generate an additional 50,000 gigawatts of power and contribute even more significantly to the U.S. energy supply. These renewable energy sources could help meet growing electricity demands in the region and help to reduce carbon emissions. \r\n

\r\nProduction of electricity from renewable sources, such as wind and ocean waves, may be less damaging to the environment than production through burning of fossil fuels, like oil, natural gas, and coal because renewable energy facilities produce much lower emissions of greenhouse gasses and other harmful pollutants such as arsenic, lead and mercury. Additionally, renewable energy production may be more cost effective and efficient than traditional methods because once infrastructure is built, the amount of energy produced is quite stable for the remainder of that system\u2019s lifespan. While the inputs (wind and waves) may fluctuate daily or seasonally they should remain consistent over longer time scales, allowing producers and consumers to rely on steady energy levels. \r\n

\r\nThe Department of the Interior has identified Wind Planning Areas (WPA)--locations that may be suitable for wind development--along the Atlantic Ocean\u2019s outer shelf. Data are being collected inside and outside these high priority areas so regulators and stakeholders can make informed and responsible judgments when issuing permits and making siting and investment decisions. Annual average wind speeds are an indication of the potential available energy at a location. Here, wind speeds modeled from limited observations by the National Renewable Energy Laboratory (NREL) and AWS Truepower are expressed at a height of 90 meters above the ocean surface where wind turbine hubs are likely to be located. \r\n

\r\nNot all the wind and waves that exist offshore are available for harvest however, and all potential energy estimates should be constrained to account for various environmental and socioeconomic factors that may exist in an area. Some of these constraints include potential overlapping use conflicts with shipping lanes, marine mammal, bird, and bat migration pathways, and traditional areas for fishing and recreational use. Infrastructure may need to be built far enough from shore to address concerns over impacts to scenic views, but close enough that the cost of bringing the electricity to shore is not prohibitive. All of these issues should be accounted for in regional ocean planning and the MARCO Ocean Data Portal provides key information that will help to raise awareness of the potential for renewable energy and support decision maker\u2019s efforts to manage resources effectively and minimize conflicts.\r\n", + "feature_image": "", + "thumbnail": "https://s3.amazonaws.com/marco-public-2d/Energy/energy_thumbnail.jpg", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_renewable_energy-0.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/energy1.jpg", + "description": "Offshore wind in the Mid-Atlantic holds more than 60,000 Megawatts of potential energy \u2014 that\u2019s 10% of total U.S. offshore potential. This huge resource could help meet the growing electricity demand in the region, while reducing carbon emissions. \r\n" + } + }, + { + "pk": 8, + "model": "data_manager.theme", + "fields": { + "factsheet_link": "/media/marco/factsheets/MARCO_factsheet_ports_F.pdf", + "feature_link": "", + "header_attrib": "", + "display_name": "Maritime", + "name": "maritime-industries", + "overview": "

\r\nMid-Atlantic maritime industries include shipping, transport, tourism, dredging, offshore sand mining, and some of the nation\u2019s busiest ports at New York-New Jersey, Philadelphia, Wilmington, Baltimore, and Norfolk. These ports are crucial links in the nation\u2019s transportation system, constitute a key element of the economy, employ many thousands of people, and have the potential to serve as environmental stewards of our region\u2019s harbors and surrounds.\r\n

\r\nThe U.S. seaport network unloads $3.8 billion in goods each day and Mid-Atlantic ports are a huge contributor, maintaining several national distinctions. The country\u2019s top port for fruits and juices is Wilmington; the fourth busiest tanker port is Philadelphia; products that go through Baltimore\u2019s ports reach over a third of the country within a day and anything entering the U.S. on wheels--from cars to giant tractors--alight in Baltimore, making it the nation\u2019s top Ro-Ro (roll on-roll off) port. The world\u2019s largest natural deep water harbor is at Hampton Roads and it stays ice-free throughout the year, making it suitable for a conglomeration of military facilities, coal piers, shipyards, and miles of waterfront property and beaches which add to the diversity and stability of our nation. The region supports important points of departure for the nation\u2019s cruise ship industry and, in 2011, close to one million people vacationed on ocean cruises originating in New York and Baltimore.\r\n

\r\nThe MARCO Ocean Data Portal contains Automatic Identification System (AIS) information from 2009, processed to focus on highly travelled shipping routes near port entrances. AIS data are collected by the U.S. Coast Guard using automated two-way radio transmissions that track real-time vessel information such as ship identity, purpose, course, and speed, primarily in coastal waters. AIS is required on all passenger vessels and vessels with gross tonnage greater than 300, so smaller vessel traffic is not represented in the database. MARCO is currently consulting with the Coast Guard and shipping industry stakeholders to evaluate how well these data indicate total ship traffic density and what additional data may be needed to fully represent shipping activity.\r\n

\r\nThe viability, safety, and growth needs of the commercial shipping industry need to be addressed in regional ocean planning. Accordingly, MARCO will consult with major port and navigation stakeholders to evaluate what additional map data may be needed to inform regional ocean planning decisions and help ensure stakeholder interests are well represented.\r\n", + "feature_image": "", + "thumbnail": "", + "visible": true, + "factsheet_thumb": "/media/marco/img/themes/sheets/MARCO_factsheet_ports-0.jpg", + "feature_excerpt": "", + "header_image": "/media/marco/img/learn/industry.jpg", + "description": "The Mid-Atlantic ports are some of the busiest in the nation\u2019s seaport network, which unloads $3.8 billion in goods each day. 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ocean planning efforts.", + "themes": [ + 1 + ], + "source": "EPA", + "contact": "Rutgers CRSSA ", + "contact_email": "", + "description": "Discharge of effluent from waste water treatment plants receiving waste water from households, commercial establishments and industries in the coastal drainage basin." + } + }, + { + "pk": 19, + "model": "data_manager.dataneed", + "fields": { + "status": "Availability of suitable Mid-Atlantic specific models and model derived map layers is being evaluated.", + "archived": true, + "name": "Ocean model results", + "expected_date": "TBD", + "notes": "FVCOM can be used for all of the NROC area and the northern part of MARCO area; additional modeling may be needed for MARCO.", + "themes": [ + 2 + ], + "source": "Potentially multiple sources including UMASS Dartmouth, Rutgers, Old Dominion University, MARACOOS and NERACOOS", + "contact": "Rutgers CRSSA, MARACOOS", + "contact_email": "", + "description": "For example, Finite Volume Coastal Ocean Model (FVCOM) is a coastal ocean circulation model developed by UMASSD-WHOI that includes information on current, wave regime, temperature, salinity and density." + } + }, + { + "pk": 25, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Improved sediment and seafloor habitat maps, benthic resilence maps", + "expected_date": "Summer 2014", + "notes": "Two year project, all final products due 5/2015, sediment maps and other select products will be available sooner.", + "themes": [ + 2 + ], + "source": "Umass/Dartmouth (SMAST)", + "contact": "Kevin Stokesbury, SMAST", + "contact_email": "", + "description": "Analysis of 10 years of video survey data and integration with FVCOM oceanography data to produce high resolution sediment, habitat, andforce stability regime maps." + } + }, + { + "pk": 17, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate sampling of NCCOS models into Portal", + "archived": false, + "name": "Regional scale predictive distribution model for sea birds, sea ducks, and other bird species", + "expected_date": "June 2014", + "notes": "Several other survey and modeling efforts are under way; integration to create new spatial data for regional ocean planning will be provided by NROC project and may also be addressed through the Mid-Atlantic Regional Ocean Assessment.", + "themes": [ + 2 + ], + "source": " Multiple sources including USGS and BOEM Compendium of Avian Information in U.S. Atlantic OCS", + "contact": "NOAA National Centers for Coastal Ocean Science", + "contact_email": "", + "description": "A high resolution, predictive model created using historic bird survey and oceanographic model data." + } + }, + { + "pk": 31, + "model": "data_manager.dataneed", + "fields": { + "status": "Analysis under development", + "archived": false, + "name": "Vessel traffic trends 2011-2013", + "expected_date": "Oct-14", + "notes": "Currently, Rutgers and TNC are working with the USCG and the USACE to develop a process to analyze multiple years of AIS data to detect signficiant changes in vessel utilization patterns and trends. ", + "themes": [ + 8 + ], + "source": "U.S. Coast Guard and NOAA Coastal Services Center", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Using three years (2011, 2012, 2013) of Automated Identification System (AIS) traffic density data, these derived data products will depict the shifts in maritime traffic by vessel type over time. " + } + }, + { + "pk": 24, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Cultural use areas", + "expected_date": "June 2013", + "notes": "Development and use of these data based on outcome of discussions between Tribal leaders and state and federal agency representatives.", + "themes": [ + 1 + ], + "source": "Tribal leaders", + "contact": "MARCO", + "contact_email": "", + "description": "Areas significant to Tribal Nations and other cultures." + } + }, + { + "pk": 16, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate authorized data into Portal", + "archived": true, + "name": "Coldwater coral predictive distribution model", + "expected_date": "Spring 2013", + "notes": "NCCOS and NEFSC working on a predictive model for the Mid-Atlantic.", + "themes": [ + 2 + ], + "source": "Multiple sources ", + "contact": "NOAA Biogeography Branch ", + "contact_email": "", + "description": "A high resolution, predictive model of coral habitat and distribution." + } + }, + { + "pk": 18, + "model": "data_manager.dataneed", + "fields": { + "status": "Bird Focus Area data developed; awaiting authorization for posting on Portal. Bat data to be developed. ", + "archived": false, + "name": "Important coastal bird and bat habitat", + "expected_date": "July 2014", + "notes": "TNC working with USFWS to ensure data is properly licensed before displaying and making available on Portal. ", + "themes": [ + 2 + ], + "source": "Atlantic Coast Joint Venture U.S. Fish and Wildlife Service", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Atlantic Coast Joint Venture habitat focus areas in the Mid-Atlantic Bird Conservation Region for landbirds, shorebirds, waterbirds, and waterfowl, respectively. Bat habitat focus areas not yet established regionally. " + } + }, + { + "pk": 26, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development in disparate efforts; planning stages for data integration.", + "archived": false, + "name": "Nearshore benthic habitats", + "expected_date": "TBD", + "notes": "Several new survey efforts are underway or envisioned to support wind energy permitting and development processes; additional surveys to cover non-Wind Planning Areas and additional coordination and potential integration of parallel efforts needed.", + "themes": [ + 2 + ], + "source": "Multiple efforts underway including MD CZM studies, NOAA HabCam, BOEM funded work by SMAST, and historic and current investigations.", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Finer scale spatial data are needed to complement exising habitat models, especially for sensitive cold water coral patch communities and other sensitive or vulnerable habitat types." + } + }, + { + "pk": 8, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Vessel Monitoring System (VMS) fishing data", + "expected_date": "December 2012", + "notes": "Data has been transferred from NMFS and will need to be processed to provide maximum utility in consideration of confidentiality requirements.", + "themes": [ + 4 + ], + "source": "NOAA/ NMFS", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "VMS are required for many commercial fisheries to monitor the position, time at a position, course and speed of fishing vessels." + } + }, + { + "pk": 7, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Vessel Trip Report (VTR)", + "expected_date": "Fall 2013", + "notes": "Regional scale VTR data aggregated to ten minute squares are currently displayed on the portal and are available upon request. Finer resolution data linking fishing locations with communities are under development in consultation with fishing industry participants. All fishery data will be depicted in consideration of confidentiality requirements established by NOAA-Fisheries.", + "themes": [ + 4 + ], + "source": "NOAA/NMFS, analysis by Rutgers University", + "contact": "Center for Remote Sensing and Spatial Analysis, Rutgers University", + "contact_email": "", + "description": "Derived data products representing fishing effort by port and gear type." + } + }, + { + "pk": 27, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate authorized data into Portal", + "archived": false, + "name": "Live submarine telecommunications cables", + "expected_date": "TBD", + "notes": "Current data displayed on MMC and Portal are from NOAA ENCs. These data are incomplete and do not distinguish between in-service and out-of-service cables. The North American Submarine Cable Association (NASCA) is currently updating their national Route Position Line database for ocean planning. However, at this point in time, they will only make these data available as PDF documents. We are still in negotiations with NASCA regarding their making the actual RPL data available to the Portal. ", + "themes": [ + 8 + ], + "source": "Multiple sources including North American Submarine Cable Association and member companies.", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Vector data of live telecommunications cables running either underneath or on top of the sea floor." + } + }, + { + "pk": 9, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Sand, gravel, and cobble mining locations", + "expected_date": " October 2014", + "notes": "Currently, we have detailed information for MD only and work continues to develop a regional scale map layer using state and federal sources. ", + "themes": [ + 8 + ], + "source": "Multiple agencies including ACOE, BOEM, Mid-Atlantic States", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Areas where resources are actively mined from the seafloor and potential source areas." + } + }, + { + "pk": 3, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development\r\n", + "archived": false, + "name": "Marine mammal population density and migration paths", + "expected_date": "Fall 2014", + "notes": "OBIS Seamap is currently refining new marine mammal model data, expected Fall 2014. New data on marine mammals in Mid-Atlantic forthcoming from AMAPPS and BRI in 2015. The Northeast Regional Ocean Council is funding a new project to integrate past and ongoing marine mammal surveys to produce new spatial data for regional ocean planning.\r\n", + "themes": [ + 2 + ], + "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Coastal Zone Mgmt/VA Aquarium, and Duke University (OBIS)", + "contact": "The Nature Conservancy ", + "contact_email": "", + "description": "Population density distribution estimates (actual and modeled) and delineation of seasonal migratory pathways for large whales (toothed and baleen), dolphins and porpoises. \r\n" + } + }, + { + "pk": 21, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Recreational fishing activity", + "expected_date": "June 2013", + "notes": "Existing data on recreational fishing locations is of variable quality, resolution and geographic extent. Participatory GIS workshops with recreational fishery stakeholders began summer 2012 and will continue through the fall and winter; these efforts will be supplemented by other surveys planned for 2013.", + "themes": [ + 4 + ], + "source": "Recreational fishers via MARCO stakeholder engagement efforts", + "contact": "Rutgers CRSSA ", + "contact_email": "", + "description": "Areas where non-commercial fishing (recreational/sport fishing) occurs." + } + }, + { + "pk": 10, + "model": "data_manager.dataneed", + "fields": { + "status": "Not initiated.", + "archived": true, + "name": "State landings and fishing effort ", + "expected_date": "To be determined (beyond scope of current funding)", + "notes": "Most ocean fishery harvests are documented through federal reporting systems but there are gaps for some fisheries that do not require federal licenses, e.g. croaker and whelks (\"conch\") in Virginia.", + "themes": [ + 4 + ], + "source": "States", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Information about commercial harvest activity collected by state agencies in the Mid-Atlantic." + } + }, + { + "pk": 12, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Energy facilities", + "expected_date": "Spring 2013", + "notes": "In addition to point locations, plume models would be useful for informing ocean planning efforts.", + "themes": [ + 3 + ], + "source": "Multiple agencies including FERC, NREL, NRC, and the EPA", + "contact": "Rutgers CRSSA ", + "contact_email": "", + "description": "Examples include nuclear power plant locations and their discharge pipe locations, potential/existing hydrokinetic sites, etc." + } + }, + { + "pk": 5, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate authorized data into Portal", + "archived": true, + "name": "Turtles-Distribution and Nesting Areas (ESI)", + "expected_date": "As soon as vetted by Portal Data Review Group", + "notes": "ESI maps provide a concise summary of coastal resources that are at risk if an oil spill occurs nearby. Vector polygons in this data set represent turtle distribution.", + "themes": [ + 2 + ], + "source": "TNC NAM ERA compiled; source data from Environmental Sensitivity Index, NOAA", + "contact": "The Nature Conservancy ", + "contact_email": "", + "description": "Sea turtle areas displayed on the maps are limited to nesting beaches and several well-known in-water concentration areas. Sea turtle nesting beaches include sandy beach areas where sea turtles come ashore to nest." + } + }, + { + "pk": 20, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Commercial fishing activity (VTR)", + "expected_date": "September, 2014", + "notes": "Data developed using \"Communities at Sea\" mapping approach. Draft maps produced and currently under review by fishing industry contacts. Development of additional map layers to address key gaps including state managed fisheries will begin July 2014. Additional potential data sources include NOAA's Vessel Monitoring System, state agency collected data and participatory mapping projects with fishermen. ", + "themes": [ + 4 + ], + "source": "NOAA-NMFS, developed in consultation with Portal Team's commercial fishery advisory group.", + "contact": "Rick Lathrop, Rutgers CRSSA", + "contact_email": "", + "description": "Map layers developed using aggregated records from NOAA's Fishing Vessel Trip Report and permit databases in consultation with commercial fishing stakeholders to illustrate the distribution and importance of commercial fishing activity by diverse communities (port, vessel type and gear group combinations). Additional attributes collected through stakeholder engagement may include information about the specific socio-economic value of fishing locations to communities. " + } + }, + { + "pk": 28, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Municipal and private discharge", + "expected_date": " October 2014", + "notes": "In addition to point locations, effluent plume models may be useful for informing ocean planning efforts.", + "themes": [], + "source": "EPA", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Point locations for waste water treatment plant facilities and outfalls including attributes for volume of discharge. " + } + }, + { + "pk": 6, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate authorized data into Portal", + "archived": true, + "name": "Large Pelagic Species (sharks, tuna, marlin)-Species Richness, Persistence and EFH", + "expected_date": "As soon as vetted by Portal Data Review Group", + "notes": "14 species represented include: Albacore Tuna, Bigeye Thresher, Blue Marlin, Bluefin Tuna, Dusky shark, Great Hammerhead, Porbeagle, Sandbar shark, Sand Tiger, Shortfin Mako, Swordfish, Thresher, White Marlin, Scalloped Hammerhead\r\n", + "themes": [ + 2 + ], + "source": "TNC NAM ERA compiled; source data from NMFS- SEFSC and NMFS-NEFSC; EFH from NMFS and HMS FMP", + "contact": "The Nature Conservancy ", + "contact_email": "", + "description": "Target species richness refers to the total number of target species by age class observed within a TMS summed and mapped based on all available data (1965-2004). Persistence refers to the sum of the number of decades that a given target species was present (1-4) for combined juvenile and adult observations. Habitat refers to the number of target species whose EFH overlapped each TMS determined and summarized by total target species and by age class.\r\n" + } + }, + { + "pk": 23, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Areas of recreational activities including fishing, boating, surface water sports, wildlife viewing,", + "expected_date": " August 2014", + "notes": "Drafts of the data are complete and are under review by stakeholders, tribal leaders, and states. A regional dataset that integrates the three survey methods is under development.", + "themes": [ + 7 + ], + "source": "Recreational users, via stakeholder engagement efforts such as participatory workshops (pGIS), Surfrider Coastal Rec survey, and Mid-Atlantic Rec Boater Survey", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Activities include fishing, boating, diving, surfing, swimming, nature viewing. " + } + }, + { + "pk": 13, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Automatic Identification System (AIS) ship traffic", + "expected_date": "June 2013", + "notes": "", + "themes": [ + 8 + ], + "source": "USCG & NOAA", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "AIS is an automated tracking system used on ships and by Vessel Traffic Services for identifying and locating vessels by electronically exchanging data with other nearby ships and VTS stations. AIS provides information such as unique identification, position, course, and speed. A preliminary AIS map layer has been added to the Portal as a placeholder; enhanced AIS map layers showing traffic patterns by vessel type and other attributes are under development by NOAA Coastal Services Center and others." + } + }, + { + "pk": 2, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to incorporate authorized data into Portal\r\n", + "archived": false, + "name": "Coldwater coral predictive distribution model", + "expected_date": "May 2014", + "notes": "NCCOS and NEFSC working on a predictive model for the Mid-Atlantic and Northeast Atlantic. The Portal's separate coral point data set will continue to be updated as new survey data are released.", + "themes": [ + 2 + ], + "source": "Multiple sources ", + "contact": "Brian Kinlan, NOAA Biogeography Branch", + "contact_email": "", + "description": "A high resolution, predictive model of coral habitat and distribution.\r\n" + } + }, + { + "pk": 32, + "model": "data_manager.dataneed", + "fields": { + "status": "Dat under development", + "archived": false, + "name": "Danger Zones and restricted Areas", + "expected_date": "Winter 2015", + "notes": "NOAA is creating a national geospatial database of the Danger Zones and Restricted Areas based on the most current Code of Federal Regulations for the Cadastre. ", + "themes": [ + 5 + ], + "source": "NOAA is digitizing the areas as described in the Code of Federal Regulations ", + "contact": "NOAA Coastal Services Center", + "contact_email": "", + "description": "This fall, NOAA intends to release a revised version of Danger Zones and Restricted Areas based on the most current areas designated as such in the CFR. These areas are either high risk areas where hazardous operations occur on full time or intermittent basis or high security areas to protect Government property, usually for national security purposes, that are either closed to or restric public access." + } + }, + { + "pk": 14, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": true, + "name": "Port locations and attributes", + "expected_date": "Spring 2013", + "notes": "Port locations are known, additional work is underway to work with port's stakeholders to develop relevant spatial data and information for each port.", + "themes": [ + 8 + ], + "source": "ACOE; Individual ports", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Locations of ports, how they relate to shipping traffic and their capacity for servicing offshore energy development" + } + }, + { + "pk": 22, + "model": "data_manager.dataneed", + "fields": { + "status": "Data development not yet initiated", + "archived": true, + "name": "Recreational boating activity", + "expected_date": "TBD", + "notes": "Initial data is being collected via participatory GIS workshops with recreational stakeholders, summer 2012 and will continue through the fall and winter; these efforts will be supplemented by other surveys planned for 2013.", + "themes": [ + 7 + ], + "source": "Recreational boaters via MARCO stakeholder engagement efforts", + "contact": "Rutgers CRSSA ", + "contact_email": "", + "description": "Areas where recreational boating (regattas, pleasure, cruises, water skiing, etc.) occurs." + } + }, + { + "pk": 1, + "model": "data_manager.dataneed", + "fields": { + "status": "Efforts underway to develop and incorporate authorized data into Portal\r\n", + "archived": true, + "name": "Military, hazard and restricted areas", + "expected_date": "Unknown ", + "notes": "", + "themes": [ + 5 + ], + "source": "USCG & DOD including ACOE, Navy, etc. ", + "contact": "NOAA CSC ", + "contact_email": "", + "description": "Information pertaining to uses of the marine environment by the Department of Defense for training, classified or restricted areas, with unexploded ordinances, etc.\r\n" + } + }, + { + "pk": 15, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Marine wildlife (whales, birds, turtles, bats) distribution and migration paths", + "expected_date": "Fall 2014", + "notes": "OBIS Seamap is currently refining new marine mammal model data, expected Fall 2014. The Northeast Regional Ocean Council is funding a new project to integrate past and ongoing marine mammal surveys to produce new spatial data for regional ocean planning.", + "themes": [ + 2 + ], + "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Aquarium, and Duke University (OBIS).", + "contact": "The Nature Conservancy", + "contact_email": "", + "description": "Critical seasonal migratory pathways for large whales (toothed and baleen), dolphins and porpoises, sea turtles, sea birds and sea ducks, and bats." + } + }, + { + "pk": 4, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development\r\n", + "archived": false, + "name": "Sea turtle population density and migration paths", + "expected_date": "TBD", + "notes": "New data on sea turtles in Mid-Atlantic forthcoming from AMAPPS and BRI in 2015. \r\n", + "themes": [ + 2 + ], + "source": "Multiple sources include new survey and modeling projects by NOAA (AMAPPS), Biodiversity Research Inst., VA Aquarium, and Duke University (OBIS)", + "contact": "The Nature Conservancy ", + "contact_email": "", + "description": "Population density distribution estimates (actual and modeled) and delineation of seasonal migratory pathways for sea turtles through Mid-Atlantic. " + } + }, + { + "pk": 29, + "model": "data_manager.dataneed", + "fields": { + "status": "Data under development", + "archived": false, + "name": "Department of Defense Operational Areas (OPAREAS) ", + "expected_date": "Fall 2015", + "notes": "U.S. Navy developing improved data that characterizes compatibility of human uses with military operational areas. ", + "themes": [ + 5 + ], + "source": "DOD Environmental Information Management System (EIMS)", + "contact": "U.S. Fleet Forces Command, U.S. Navy", + "contact_email": "", + "description": "OPAREA is an area where DOD's Atlantic Fleet routinely conducts training exercises and system qualification tests via ships and aircrafts. Data under development will include general attributes about specific activities occurring in OPAREAS related to testing and training. " + } + } +] diff --git a/data_manager/forms.py b/data_manager/forms.py new file mode 100644 index 0000000..674832d --- /dev/null +++ b/data_manager/forms.py @@ -0,0 +1,5 @@ +from django import forms +from .models import ExternalPortal + +class RemotePortalMigrationForm(forms.Form): + portal = forms.ModelChoiceField(label='External Portal', queryset=ExternalPortal.objects.all()) \ No newline at end of file diff --git a/data_manager/management/commands/import_era.py b/data_manager/management/commands/import_era.py index 8480bab..901b656 100644 --- a/data_manager/management/commands/import_era.py +++ b/data_manager/management/commands/import_era.py @@ -1,490 +1,490 @@ -from django.core.management.base import BaseCommand -import sys - -import requests - -# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning -import urllib3 -urllib3.disable_warnings() - -# Identify and break up name and dimension/value dict -# Only deal with strings, finding and creating dimensions/associations done elsewhere -def parseLayerName(sublayer_name): - name_lookup = { - 'allSp': 'all species', - 'nefsc': '(NEFSC)', - 'neamap': '(NEAMAP)', - 'chla': 'Chlorophyll-a', - } - value_lookup = { - # TODO: determine if annual is dimension 'month' or 'season' - 'annual': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': 'annual', - 'name': 'annual', - 'label': 'Yr', - 'order': 1 - }, - 'month01': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '01', - 'name': 'january', - 'label': 'J', - 'order': 2 - }, - 'month02': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '02', - 'name': 'february', - 'label': 'F', - 'order': 3 - }, - 'month03': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '03', - 'name': 'march', - 'label': 'M', - 'order': 4 - }, - 'month04': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '04', - 'name': 'april', - 'label': 'A', - 'order': 5 - }, - 'month05': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '05', - 'name': 'may', - 'label': 'M', - 'order': 6 - }, - 'month06': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '06', - 'name': 'june', - 'label': 'J', - 'order': 7 - }, - 'month07': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '07', - 'name': 'july', - 'label': 'J', - 'order': 8 - }, - 'month08': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '08', - 'name': 'august', - 'label': 'A', - 'order': 9 - }, - 'month09': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '09', - 'name': 'september', - 'label': 'S', - 'order': 10 - }, - 'month10': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '10', - 'name': 'october', - 'label': 'O', - 'order': 11 - }, - 'month11': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '11', - 'name': 'november', - 'label': 'N', - 'order': 12 - }, - 'month12': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'month', - 'value': '12', - 'name': 'december', - 'label': 'D', - 'order': 13 - }, - 'season01': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'season', - 'value': '01', - 'name': 'winter', - 'label': "Win", - 'order': 2 - }, - 'season02': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'season', - 'value': '02', - 'name': 'spring', - 'label': 'Spr', - 'order': 3 - }, - 'season03': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'season', - 'value': '03', - 'name': 'summer', - 'label': 'Sum', - 'order': 4 - }, - 'season04': { - 'dimension_type': 'time', - 'dimension': 'time', - 'dimension_label': 'season', - 'value': '04', - 'name': 'fall', - 'label': 'Fall', - 'order': 5 - }, - 'original': { - 'dimension_type': 'threshold', - 'dimension': 'threshold', - 'dimension_label': 'threshold', - 'value': 'original', - 'name': 'all', - 'label': 'All', - 'order': 1 - }, - 'top50pctl': { - 'dimension_type': 'threshold', - 'dimension': 'threshold', - 'dimension_label': 'threshold', - 'value': '50', - 'name': '50', - 'label': 'Top 50%', - 'order': 2 - }, - 'top25pctl': { - 'dimension_type': 'threshold', - 'dimension': 'threshold', - 'dimension_label': 'threshold', - 'value': '25', - 'name': '25', - 'label': 'Top 25%', - 'order': 3 - }, - 'top10pctl': { - 'dimension_type': 'threshold', - 'dimension': 'threshold', - 'dimension_label': 'threshold', - 'value': '10', - 'name': '10', - 'label': 'Top 10%', - 'order': 4 - }, - } - - # Parse Name - name_parts = sublayer_name.split('_') - name_parts_clean = [] - dimensions_dict = {} - for part in name_parts: - if part in name_lookup.keys(): - name_parts_clean.append(name_lookup[part]) - else: - name_parts_clean.append(part) - if part in value_lookup.keys(): - val_dict = value_lookup[part] - dimensions_dict[val_dict['dimension_type']] = val_dict - name = ' '.join([x.capitalize() for x in name_parts_clean]) - - return { - 'name':name, - 'dimensions': dimensions_dict - } - -def createArcRestLayer(layer, url, layer_id, layer_source, theme, parent_layer=False): - from django.contrib.sites.models import Site - from data_manager.models import Layer, Theme - - parsed_layer_dict = parseLayerName(layer['name']) - layer_name = parsed_layer_dict['name'] - is_sublayer = not(parent_layer == False) - url_record_matches = Layer.objects.filter(url=url, arcgis_layers=str(layer_id), is_sublayer=is_sublayer, layer_type='ArcRest') - if len(url_record_matches) == 1: - layer_record = url_record_matches[0] - layer_created = False - else: - (layer_record, layer_created) = Layer.objects.get_or_create( - name=layer_name, - layer_type='ArcRest', - url=url, - is_sublayer=is_sublayer, - arcgis_layers=str(layer_id) - ) - if not theme in layer_record.themes.all(): - layer_record.themes.add(theme) - if is_sublayer and not parent_layer in layer_record.sublayers.all(): - layer_record.sublayers.add(parent_layer) - if not layer_record.data_source == layer_source: - layer_record.data_source = layer_source - if layer_created: - # Adds all sites to every layer record - we may want to limit this on Production - for site in Site.objects.all(): - layer_record.site.add(site) - layer_record.save() - return { - 'layer_record': layer_record, - 'layer_record_name_dict': parsed_layer_dict - } - -def setAssociation(parent, dimensionValues, layer): - from data_manager.models import Layer, Theme, MultilayerDimension, MultilayerAssociation, MultilayerDimensionValue - - # get list of associations for each dimension value - association_list = [] - for i, value in enumerate(dimensionValues): - # identify single association in all lists - if i == 0: - association_list = list(value.associations.all()) - # # TODO: TEST: - # if not len(association_list) == len(parent.parent_layer.all()): - # import ipdb; ipdb.set_trace() - else: - new_association_list = [] - for association in association_list: - if association in list(value.associations.all()): - new_association_list.append(association) - association_list = new_association_list - if len(association_list)> 1: - import ipdb; ipdb.set_trace() - sys.exit() - elif len(association_list) == 1: - association = association_list[0] - # create name for association from name of each dimension value (join(' ')) - association.name = ' '.join([x.value.capitalize() for x in dimensionValues]) - # Assign layer to association - association.layer = layer - association.save() - -class Command(BaseCommand): - help = "Import ERA Data from Duke and create necessary slider records" - - def handle(self, *args, **options): - if not len(args) == 0: - print('Usage: manage.py import_era (no arguments allowed)') - sys.exit() - - import json, requests - from data_manager.models import Layer, Theme, MultilayerDimension, MultilayerAssociation, MultilayerDimensionValue - from django.contrib.sites.models import Site - - ############ - # SETTINGS # - ############ - LAYER_SOURCE = 'MDAT ERA IMPORT' - ERA_CATEGORY_DISPLAY_NAME = 'Components of Ecological Richness' - ENDPOINT = 'https://mgelmaps.env.duke.edu/mdat_new/rest/services/' - SERVICE_ROOT = 'MDAT_Staging' - SERVICE_PREFIX = 'CEI_ERA_' - ERA_CATEGORIES = { - 'Abundance': { - 'name': 'Abundance', - 'order': 3, - 'type': 'checkbox' - }, - 'Biodiversity': { - 'name': 'Biodiversity', - 'order': 2, - 'type': 'radio' - }, - 'Habitat_Oceanographic': { - 'name': 'Habitat and Oceanographic Drivers', - 'order': 6, - 'type': 'radio' - }, - 'Productivity': { - 'name': 'Productivity', - 'order': 1, - 'type': 'checkbox' - }, - 'Rarity': { - 'name': 'Rarity', - 'order': 5, - 'type': 'radio' - }, - 'Vulnerability': { - 'name': 'Vulnerability', - 'order': 4, - 'type': 'radio' - }, - } - DIMENSION_SETTINGS = { - 'time': { - 'order': 1, - 'animated': True - }, - 'threshold': { - 'order': 2, - 'animated': False - }, - 'default': { - 'order': 10, - 'animated': False - } - } - ############# - ############# - - count = 0 - - # Get companion theme (used to hide multilayer sublayers) - companion_theme = Theme.objects.get(name='companion') - - # Ensure ERA Theme Exists - (era_theme, theme_created) = Theme.objects.get_or_create(name='ERA', display_name=ERA_CATEGORY_DISPLAY_NAME) - if theme_created: - for site in Site.objects.all(): - era_theme.site.add(site) - era_theme.save() - - service_categories = ['%s/%s%s' % (SERVICE_ROOT,SERVICE_PREFIX, x) for x in ERA_CATEGORIES.keys()] - services_json = '%s%s/?f=pjson' % (ENDPOINT,SERVICE_ROOT) - services_request = requests.get(services_json) - services = services_request.json()['services'] - for service_count, service_dict in enumerate(services): - service = service_dict['name'] - service_endpoint = '%s%s/MapServer' % (ENDPOINT, service) - # test if service matches given ERA_CATEGORIES - service_key_list = service.split('%s/%s' % (SERVICE_ROOT,SERVICE_PREFIX)) - if service in service_categories and len(service_key_list) == 2: - service_key = service_key_list[1] - category_dict = ERA_CATEGORIES[service_key] - (category_layer, category_layer_created) = Layer.objects.get_or_create( - name=category_dict['name'], - order=category_dict['order'], - layer_type=category_dict['type'] - ) - category_layer.themes.add(era_theme) - category_layer.data_source = LAYER_SOURCE - if len(category_layer.site.all()) == 0: - for site in Site.objects.all(): - category_layer.site.add(site) - category_layer.save() - - service_json = '%s?f=pjson' % (service_endpoint) - layers_request = requests.get(service_json) - layers = layers_request.json()['layers'] - for layer_count, layer in enumerate(layers): - if layer['parentLayerId'] == -1: - # Parent Layer - if layer['subLayerIds'] == 0: - # Standalone Layer - url = '%s/export' % service_endpoint - createArcRestLayer(layer, url, layer['id'], LAYER_SOURCE, era_theme, category_layer) - else: - # ERA Category MultiLayer Parent - parsed_layer_dict = parseLayerName(layer['name']) - (multilayer_parent, multilayer_parent_created) = Layer.objects.get_or_create( - name=parsed_layer_dict['name'], - layer_type='Vector', - is_sublayer=True - ) - multilayer_parent.themes.add(era_theme) - multilayer_parent.sublayers.add(category_layer) - if multilayer_parent_created or len(multilayer_parent.site.all()) == 0: - for site in Site.objects.all(): - multilayer_parent.site.add(site) - multilayer_parent.data_source = LAYER_SOURCE - multilayer_parent.save() - count += 1 - print('Service: %d, Layer: %d, Total: %d' % (service_count, layer_count, count)) - if layer['subLayerIds']: - for sublayer_count, sublayer_id in enumerate(layer['subLayerIds']): - sublayer_json = '%s/%s/?f=pjson' % (service_endpoint, sublayer_id) - sublayer_request = requests.get(sublayer_json) - sublayer = sublayer_request.json() - sublayer_url = '%s/export' % service_endpoint - sublayer_record_dict = createArcRestLayer(sublayer, sublayer_url, sublayer['id'], LAYER_SOURCE, companion_theme, False) - sublayer_record = sublayer_record_dict['layer_record'] - parsed_layer_dict = sublayer_record_dict['layer_record_name_dict'] - sublayerDimensionValues = [] - for dimension_value_dict_key in parsed_layer_dict['dimensions'].keys(): - if dimension_value_dict_key in DIMENSION_SETTINGS.keys(): - dimension_settings_dict = DIMENSION_SETTINGS[dimension_value_dict_key] - else: - dimension_settings_dict = DIMENSION_SETTINGS['default'] - - dimension_value_dict = parsed_layer_dict['dimensions'][dimension_value_dict_key] - (dimension, dimension_created) = MultilayerDimension.objects.get_or_create( - name=dimension_value_dict['dimension'].capitalize(), - label=dimension_value_dict['dimension'].capitalize(), - layer=multilayer_parent, - order=dimension_settings_dict['order'], - animated=dimension_settings_dict['animated'] - ) - if dimension_created: - # Save some time - dimension.save() - # Fix issue of old associations being duplicated - # matching_dimension_values = MultilayerDimensionValue.objects.filter(dimension=dimension,value=dimension_value_dict['name'],order=dimension_value_dict['order']) - matching_dimension_values = dimension.multilayerdimensionvalue_set.filter(value=dimension_value_dict['name'],order=dimension_value_dict['order']) - cleanup_count = 0 - while len(matching_dimension_values) > 1: - cleanup_count += 1 - #weird bug where many have no id yet - matching_dimension_values[1].save() - matching_dimension_values[1].delete() - matching_dimension_values = dimension.multilayerdimensionvalue_set.filter(value=dimension_value_dict['name'],order=dimension_value_dict['order']) - print('cleanup values count: %s' % cleanup_count) - (dimensionValue, dimension_value_created) = MultilayerDimensionValue.objects.get_or_create( - dimension=dimension, - value=dimension_value_dict['name'], - order=dimension_value_dict['order'] - ) - dimensionValue.label = dimension_value_dict['label'] # Capitalizing this creates dupes if not matching 'label' in value_lookup - dimensionValue.save() - sublayerDimensionValues.append(dimensionValue) - # Create Association - setAssociation(multilayer_parent, sublayerDimensionValues, sublayer_record) - # set cache - sublayer_record.data_source = LAYER_SOURCE - sublayer_record.save() - count += 1 - print('Service: %d, Layer: %d, Sublayer: %d, Total: %d' % (service_count, layer_count, sublayer_count, count)) - multilayer_parent.save() - for site in Site.objects.all(): - multilayer_parent.toDict(site.pk) - else: - # Child Layer - pass # Handle this in loop of parent layer - # set Cache - - -# https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/CEI_ERA_Abundance/MapServer/19/export?LAYERS=show%3A0&SRS=EPSG%3A3857&TRANSPARENT=true&FORMAT=png&BBOX=-9079495.966562%2C4383204.949375%2C-8766409.89875%2C4696291.017188&SIZE=256%2C256&F=image&BBOXSR=3857&IMAGESR=3857 -# https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/CEI_ERA_Abundance/MapServer/export?LAYERS=show%3A12&SRS=EPSG%3A3857&TRANSPARENT=true&FORMAT=png&BBOX=-7827151.695312%2C4539747.983281%2C-7670608.661406%2C4696291.017188&SIZE=256%2C256&F=image&BBOXSR=3857&IMAGESR=3857 +from django.core.management.base import BaseCommand +import sys + +import requests + +# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning +import urllib3 +urllib3.disable_warnings() + +# Identify and break up name and dimension/value dict +# Only deal with strings, finding and creating dimensions/associations done elsewhere +def parseLayerName(sublayer_name): + name_lookup = { + 'allSp': 'all species', + 'nefsc': '(NEFSC)', + 'neamap': '(NEAMAP)', + 'chla': 'Chlorophyll-a', + } + value_lookup = { + # TODO: determine if annual is dimension 'month' or 'season' + 'annual': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': 'annual', + 'name': 'annual', + 'label': 'Yr', + 'order': 1 + }, + 'month01': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '01', + 'name': 'january', + 'label': 'J', + 'order': 2 + }, + 'month02': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '02', + 'name': 'february', + 'label': 'F', + 'order': 3 + }, + 'month03': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '03', + 'name': 'march', + 'label': 'M', + 'order': 4 + }, + 'month04': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '04', + 'name': 'april', + 'label': 'A', + 'order': 5 + }, + 'month05': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '05', + 'name': 'may', + 'label': 'M', + 'order': 6 + }, + 'month06': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '06', + 'name': 'june', + 'label': 'J', + 'order': 7 + }, + 'month07': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '07', + 'name': 'july', + 'label': 'J', + 'order': 8 + }, + 'month08': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '08', + 'name': 'august', + 'label': 'A', + 'order': 9 + }, + 'month09': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '09', + 'name': 'september', + 'label': 'S', + 'order': 10 + }, + 'month10': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '10', + 'name': 'october', + 'label': 'O', + 'order': 11 + }, + 'month11': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '11', + 'name': 'november', + 'label': 'N', + 'order': 12 + }, + 'month12': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'month', + 'value': '12', + 'name': 'december', + 'label': 'D', + 'order': 13 + }, + 'season01': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'season', + 'value': '01', + 'name': 'winter', + 'label': "Win", + 'order': 2 + }, + 'season02': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'season', + 'value': '02', + 'name': 'spring', + 'label': 'Spr', + 'order': 3 + }, + 'season03': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'season', + 'value': '03', + 'name': 'summer', + 'label': 'Sum', + 'order': 4 + }, + 'season04': { + 'dimension_type': 'time', + 'dimension': 'time', + 'dimension_label': 'season', + 'value': '04', + 'name': 'fall', + 'label': 'Fall', + 'order': 5 + }, + 'original': { + 'dimension_type': 'threshold', + 'dimension': 'threshold', + 'dimension_label': 'threshold', + 'value': 'original', + 'name': 'all', + 'label': 'All', + 'order': 1 + }, + 'top50pctl': { + 'dimension_type': 'threshold', + 'dimension': 'threshold', + 'dimension_label': 'threshold', + 'value': '50', + 'name': '50', + 'label': 'Top 50%', + 'order': 2 + }, + 'top25pctl': { + 'dimension_type': 'threshold', + 'dimension': 'threshold', + 'dimension_label': 'threshold', + 'value': '25', + 'name': '25', + 'label': 'Top 25%', + 'order': 3 + }, + 'top10pctl': { + 'dimension_type': 'threshold', + 'dimension': 'threshold', + 'dimension_label': 'threshold', + 'value': '10', + 'name': '10', + 'label': 'Top 10%', + 'order': 4 + }, + } + + # Parse Name + name_parts = sublayer_name.split('_') + name_parts_clean = [] + dimensions_dict = {} + for part in name_parts: + if part in name_lookup.keys(): + name_parts_clean.append(name_lookup[part]) + else: + name_parts_clean.append(part) + if part in value_lookup.keys(): + val_dict = value_lookup[part] + dimensions_dict[val_dict['dimension_type']] = val_dict + name = ' '.join([x.capitalize() for x in name_parts_clean]) + + return { + 'name':name, + 'dimensions': dimensions_dict + } + +def createArcRestLayer(layer, url, layer_id, layer_source, theme, parent_layer=False): + from django.contrib.sites.models import Site + from data_manager.models import Layer, Theme + + parsed_layer_dict = parseLayerName(layer['name']) + layer_name = parsed_layer_dict['name'] + is_sublayer = not(parent_layer == False) + url_record_matches = Layer.objects.filter(url=url, arcgis_layers=str(layer_id), is_sublayer=is_sublayer, layer_type='ArcRest') + if len(url_record_matches) == 1: + layer_record = url_record_matches[0] + layer_created = False + else: + (layer_record, layer_created) = Layer.objects.get_or_create( + name=layer_name, + layer_type='ArcRest', + url=url, + is_sublayer=is_sublayer, + arcgis_layers=str(layer_id) + ) + if not theme in layer_record.themes.all(): + layer_record.themes.add(theme) + if is_sublayer and not parent_layer in layer_record.sublayers.all(): + layer_record.sublayers.add(parent_layer) + if not layer_record.data_source == layer_source: + layer_record.data_source = layer_source + if layer_created: + # Adds all sites to every layer record - we may want to limit this on Production + for site in Site.objects.all(): + layer_record.site.add(site) + layer_record.save() + return { + 'layer_record': layer_record, + 'layer_record_name_dict': parsed_layer_dict + } + +def setAssociation(parent, dimensionValues, layer): + from data_manager.models import Layer, Theme, MultilayerDimension, MultilayerAssociation, MultilayerDimensionValue + + # get list of associations for each dimension value + association_list = [] + for i, value in enumerate(dimensionValues): + # identify single association in all lists + if i == 0: + association_list = list(value.associations.all()) + # # TODO: TEST: + # if not len(association_list) == len(parent.parent_layer.all()): + # import ipdb; ipdb.set_trace() + else: + new_association_list = [] + for association in association_list: + if association in list(value.associations.all()): + new_association_list.append(association) + association_list = new_association_list + if len(association_list)> 1: + import ipdb; ipdb.set_trace() + sys.exit() + elif len(association_list) == 1: + association = association_list[0] + # create name for association from name of each dimension value (join(' ')) + association.name = ' '.join([x.value.capitalize() for x in dimensionValues]) + # Assign layer to association + association.layer = layer + association.save() + +class Command(BaseCommand): + help = "Import ERA Data from Duke and create necessary slider records" + + def handle(self, *args, **options): + if not len(args) == 0: + print('Usage: manage.py import_era (no arguments allowed)') + sys.exit() + + import json, requests + from data_manager.models import Layer, Theme, MultilayerDimension, MultilayerAssociation, MultilayerDimensionValue + from django.contrib.sites.models import Site + + ############ + # SETTINGS # + ############ + LAYER_SOURCE = 'MDAT ERA IMPORT' + ERA_CATEGORY_DISPLAY_NAME = 'Components of Ecological Richness' + ENDPOINT = 'https://mgelmaps.env.duke.edu/mdat_new/rest/services/' + SERVICE_ROOT = 'MDAT_Staging' + SERVICE_PREFIX = 'CEI_ERA_' + ERA_CATEGORIES = { + 'Abundance': { + 'name': 'Abundance', + 'order': 3, + 'type': 'checkbox' + }, + 'Biodiversity': { + 'name': 'Biodiversity', + 'order': 2, + 'type': 'radio' + }, + 'Habitat_Oceanographic': { + 'name': 'Habitat and Oceanographic Drivers', + 'order': 6, + 'type': 'radio' + }, + 'Productivity': { + 'name': 'Productivity', + 'order': 1, + 'type': 'checkbox' + }, + 'Rarity': { + 'name': 'Rarity', + 'order': 5, + 'type': 'radio' + }, + 'Vulnerability': { + 'name': 'Vulnerability', + 'order': 4, + 'type': 'radio' + }, + } + DIMENSION_SETTINGS = { + 'time': { + 'order': 1, + 'animated': True + }, + 'threshold': { + 'order': 2, + 'animated': False + }, + 'default': { + 'order': 10, + 'animated': False + } + } + ############# + ############# + + count = 0 + + # Get companion theme (used to hide multilayer sublayers) + companion_theme = Theme.objects.get(name='companion') + + # Ensure ERA Theme Exists + (era_theme, theme_created) = Theme.objects.get_or_create(name='ERA', display_name=ERA_CATEGORY_DISPLAY_NAME) + if theme_created: + for site in Site.objects.all(): + era_theme.site.add(site) + era_theme.save() + + service_categories = ['%s/%s%s' % (SERVICE_ROOT,SERVICE_PREFIX, x) for x in ERA_CATEGORIES.keys()] + services_json = '%s%s/?f=pjson' % (ENDPOINT,SERVICE_ROOT) + services_request = requests.get(services_json) + services = services_request.json()['services'] + for service_count, service_dict in enumerate(services): + service = service_dict['name'] + service_endpoint = '%s%s/MapServer' % (ENDPOINT, service) + # test if service matches given ERA_CATEGORIES + service_key_list = service.split('%s/%s' % (SERVICE_ROOT,SERVICE_PREFIX)) + if service in service_categories and len(service_key_list) == 2: + service_key = service_key_list[1] + category_dict = ERA_CATEGORIES[service_key] + (category_layer, category_layer_created) = Layer.objects.get_or_create( + name=category_dict['name'], + order=category_dict['order'], + layer_type=category_dict['type'] + ) + category_layer.themes.add(era_theme) + category_layer.data_source = LAYER_SOURCE + if len(category_layer.site.all()) == 0: + for site in Site.objects.all(): + category_layer.site.add(site) + category_layer.save() + + service_json = '%s?f=pjson' % (service_endpoint) + layers_request = requests.get(service_json) + layers = layers_request.json()['layers'] + for layer_count, layer in enumerate(layers): + if layer['parentLayerId'] == -1: + # Parent Layer + if layer['subLayerIds'] == 0: + # Standalone Layer + url = '%s/export' % service_endpoint + createArcRestLayer(layer, url, layer['id'], LAYER_SOURCE, era_theme, category_layer) + else: + # ERA Category MultiLayer Parent + parsed_layer_dict = parseLayerName(layer['name']) + (multilayer_parent, multilayer_parent_created) = Layer.objects.get_or_create( + name=parsed_layer_dict['name'], + layer_type='Vector', + is_sublayer=True + ) + multilayer_parent.themes.add(era_theme) + multilayer_parent.sublayers.add(category_layer) + if multilayer_parent_created or len(multilayer_parent.site.all()) == 0: + for site in Site.objects.all(): + multilayer_parent.site.add(site) + multilayer_parent.data_source = LAYER_SOURCE + multilayer_parent.save() + count += 1 + print('Service: %d, Layer: %d, Total: %d' % (service_count, layer_count, count)) + if layer['subLayerIds']: + for sublayer_count, sublayer_id in enumerate(layer['subLayerIds']): + sublayer_json = '%s/%s/?f=pjson' % (service_endpoint, sublayer_id) + sublayer_request = requests.get(sublayer_json) + sublayer = sublayer_request.json() + sublayer_url = '%s/export' % service_endpoint + sublayer_record_dict = createArcRestLayer(sublayer, sublayer_url, sublayer['id'], LAYER_SOURCE, companion_theme, False) + sublayer_record = sublayer_record_dict['layer_record'] + parsed_layer_dict = sublayer_record_dict['layer_record_name_dict'] + sublayerDimensionValues = [] + for dimension_value_dict_key in parsed_layer_dict['dimensions'].keys(): + if dimension_value_dict_key in DIMENSION_SETTINGS.keys(): + dimension_settings_dict = DIMENSION_SETTINGS[dimension_value_dict_key] + else: + dimension_settings_dict = DIMENSION_SETTINGS['default'] + + dimension_value_dict = parsed_layer_dict['dimensions'][dimension_value_dict_key] + (dimension, dimension_created) = MultilayerDimension.objects.get_or_create( + name=dimension_value_dict['dimension'].capitalize(), + label=dimension_value_dict['dimension'].capitalize(), + layer=multilayer_parent, + order=dimension_settings_dict['order'], + animated=dimension_settings_dict['animated'] + ) + if dimension_created: + # Save some time + dimension.save() + # Fix issue of old associations being duplicated + # matching_dimension_values = MultilayerDimensionValue.objects.filter(dimension=dimension,value=dimension_value_dict['name'],order=dimension_value_dict['order']) + matching_dimension_values = dimension.multilayerdimensionvalue_set.filter(value=dimension_value_dict['name'],order=dimension_value_dict['order']) + cleanup_count = 0 + while len(matching_dimension_values) > 1: + cleanup_count += 1 + #weird bug where many have no id yet + matching_dimension_values[1].save() + matching_dimension_values[1].delete() + matching_dimension_values = dimension.multilayerdimensionvalue_set.filter(value=dimension_value_dict['name'],order=dimension_value_dict['order']) + print('cleanup values count: %s' % cleanup_count) + (dimensionValue, dimension_value_created) = MultilayerDimensionValue.objects.get_or_create( + dimension=dimension, + value=dimension_value_dict['name'], + order=dimension_value_dict['order'] + ) + dimensionValue.label = dimension_value_dict['label'] # Capitalizing this creates dupes if not matching 'label' in value_lookup + dimensionValue.save() + sublayerDimensionValues.append(dimensionValue) + # Create Association + setAssociation(multilayer_parent, sublayerDimensionValues, sublayer_record) + # set cache + sublayer_record.data_source = LAYER_SOURCE + sublayer_record.save() + count += 1 + print('Service: %d, Layer: %d, Sublayer: %d, Total: %d' % (service_count, layer_count, sublayer_count, count)) + multilayer_parent.save() + for site in Site.objects.all(): + multilayer_parent.toDict(site.pk) + else: + # Child Layer + pass # Handle this in loop of parent layer + # set Cache + + +# https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/CEI_ERA_Abundance/MapServer/19/export?LAYERS=show%3A0&SRS=EPSG%3A3857&TRANSPARENT=true&FORMAT=png&BBOX=-9079495.966562%2C4383204.949375%2C-8766409.89875%2C4696291.017188&SIZE=256%2C256&F=image&BBOXSR=3857&IMAGESR=3857 +# https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/CEI_ERA_Abundance/MapServer/export?LAYERS=show%3A12&SRS=EPSG%3A3857&TRANSPARENT=true&FORMAT=png&BBOX=-7827151.695312%2C4539747.983281%2C-7670608.661406%2C4696291.017188&SIZE=256%2C256&F=image&BBOXSR=3857&IMAGESR=3857 diff --git a/data_manager/management/commands/import_espis.py b/data_manager/management/commands/import_espis.py index 08eca93..e1f8d58 100644 --- a/data_manager/management/commands/import_espis.py +++ b/data_manager/management/commands/import_espis.py @@ -1,83 +1,83 @@ -from django.core.management.base import BaseCommand -import sys - -import requests - -class Command(BaseCommand): - help = "Import TSV of ESPIS Links and apply to layers." - - def handle(self, *args, **options): - if not len(args) == 1 or not args[0][-2:] == 'sv': - print('Usage: manage.py import_espis /full/path/to/input/file.csv (Must be .csv or .tsv)') - sys.exit() - - import csv - # infile = '/home/vagrant/marco_portal2/apps/mp-data-manager/import_files/ESPIS_Links-Sheet1.tsv' - infile = args[0] - if infile[-3:].lower() == 'tsv': - delimiter = '\t' - elif infile[-3:].lower() == 'csv': - delimiter = ',' - else: - print('Input file must be .csv or .tsv') - sys.exit() - try: - f = open(infile, 'rb') - reader = csv.reader(f, delimiter=delimiter) - headers = reader.next() - if not 'Layer Name' in headers: - '"Layer Name" must be a header - make sure to keep header row attached when importing file' - sys.exit() - else: - layer_idx = headers.index("Layer Name") - if not 'Subject Keyword' in headers: - '"Subject Keyword" must be a header - make sure to keep header row attached when importing file' - sys.exit() - else: - keyword_idx = headers.index("Subject Keyword") - if not 'Location Key' in headers: - '"Location Key" must be a header - make sure to keep header row attached when importing file' - sys.exit() - else: - geo_idx = headers.index("Location Key") - - from data_manager.models import Layer - for row in reader: - try: - layer = Layer.objects.get(name=row[layer_idx].strip()) - if row[keyword_idx] == 'No relevant links': - print("No relevant links") - layer.espis_enabled = False - layer.espis_search = None - layer.espis_region = None - layer.save() - elif row[layer_idx] == '': - print("") - layer.espis_enabled = False - layer.espis_search = None - layer.espis_region = None - layer.save() - else: - if len(row[keyword_idx]) > 0 or len(row[geo_idx]) > 0: - layer.espis_enabled = True - else: - layer.espis_enabled = False - layer.espis_search = row[keyword_idx] - layer.espis_region = row[geo_idx] - layer.save() - print("ESPIS LINK SAVED: layer - [%s], search - [%s], region = [%s]" % (row[layer_idx], row[keyword_idx], row[geo_idx])) - - except: - if row[keyword_idx] == 'No relevant links': - print("No relevant links") - elif row[layer_idx] == '': - print("") - else: - print('Match not found for layer "%s"' % (row[layer_idx])) - pass - - - f.close() - except IOError: - print('No such file or directory: %s' % args[0]) - sys.exit() +from django.core.management.base import BaseCommand +import sys + +import requests + +class Command(BaseCommand): + help = "Import TSV of ESPIS Links and apply to layers." + + def handle(self, *args, **options): + if not len(args) == 1 or not args[0][-2:] == 'sv': + print('Usage: manage.py import_espis /full/path/to/input/file.csv (Must be .csv or .tsv)') + sys.exit() + + import csv + # infile = '/home/vagrant/marco_portal2/apps/mp-data-manager/import_files/ESPIS_Links-Sheet1.tsv' + infile = args[0] + if infile[-3:].lower() == 'tsv': + delimiter = '\t' + elif infile[-3:].lower() == 'csv': + delimiter = ',' + else: + print('Input file must be .csv or .tsv') + sys.exit() + try: + f = open(infile, 'rb') + reader = csv.reader(f, delimiter=delimiter) + headers = reader.next() + if not 'Layer Name' in headers: + '"Layer Name" must be a header - make sure to keep header row attached when importing file' + sys.exit() + else: + layer_idx = headers.index("Layer Name") + if not 'Subject Keyword' in headers: + '"Subject Keyword" must be a header - make sure to keep header row attached when importing file' + sys.exit() + else: + keyword_idx = headers.index("Subject Keyword") + if not 'Location Key' in headers: + '"Location Key" must be a header - make sure to keep header row attached when importing file' + sys.exit() + else: + geo_idx = headers.index("Location Key") + + from data_manager.models import Layer + for row in reader: + try: + layer = Layer.objects.get(name=row[layer_idx].strip()) + if row[keyword_idx] == 'No relevant links': + print("No relevant links") + layer.espis_enabled = False + layer.espis_search = None + layer.espis_region = None + layer.save() + elif row[layer_idx] == '': + print("") + layer.espis_enabled = False + layer.espis_search = None + layer.espis_region = None + layer.save() + else: + if len(row[keyword_idx]) > 0 or len(row[geo_idx]) > 0: + layer.espis_enabled = True + else: + layer.espis_enabled = False + layer.espis_search = row[keyword_idx] + layer.espis_region = row[geo_idx] + layer.save() + print("ESPIS LINK SAVED: layer - [%s], search - [%s], region = [%s]" % (row[layer_idx], row[keyword_idx], row[geo_idx])) + + except: + if row[keyword_idx] == 'No relevant links': + print("No relevant links") + elif row[layer_idx] == '': + print("") + else: + print('Match not found for layer "%s"' % (row[layer_idx])) + pass + + + f.close() + except IOError: + print('No such file or directory: %s' % args[0]) + sys.exit() diff --git a/data_manager/management/commands/mdat_2_fish.py b/data_manager/management/commands/mdat_2_fish.py index a7fbabc..1840d0e 100644 --- a/data_manager/management/commands/mdat_2_fish.py +++ b/data_manager/management/commands/mdat_2_fish.py @@ -1,301 +1,301 @@ -from django.core.management.base import BaseCommand -import sys - -# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning -import urllib3 -urllib3.disable_warnings() - -class Command(BaseCommand): - - help = "Generate staging layers for MDAT Fish Summary (V2.1)" - - def handle(self, *args, **options): - ############################################## - # DEPENDENCIES - ############################################## - import requests - from django.forms.models import model_to_dict - from datetime import date - from django.contrib.sites.models import Site - from data_manager.models import Layer, Theme - - ############################################## - # SETTINGS - ############################################## - #--------------------------------------------- - #- new server/layers settings - #--------------------------------------------- - # mdat_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT/' - mdat_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT_Staging/' - data_source = 'Marine-Life Data and Analysis Team (V2.1)' - publish_date = date(2019,6,24) - source_site = 'http://seamap.env.duke.edu/models/mdat/' - source_metadata = 'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf' - # RDH 2019-06-03: Are we worried about other services? - services = ['fish'] - fish_service = 'Fish_SummaryProducts_NEFSC' - - #--------------------------------------------- - #- old layer settings - #--------------------------------------------- - old_layer_name = 'Fish' - old_layer_type = 'checkbox' - old_theme_name = 'conservation' - old_data_source = 'Marine Life Data and Analysis Team V2' - parent_theme = Theme.all_objects.get(name='conservation') - try: - fish_parent = Layer.all_objects.get(name__iexact=old_layer_name, layer_type=old_layer_type, themes=parent_theme, data_source=old_data_source) - except Exception as e: - parent_layer_dict = { - 'data_source': u'Marine Life Data and Analysis Team V2', - 'layer_type': u'checkbox', - 'metadata': u'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf', - 'name': u'Fish', - 'order': 10, - 'source': u'http://seamap.env.duke.edu/models/mdat/', - } - fish_parent = Layer.all_objects.create(**parent_layer_dict) - - ############################################## - # VALIDATE USAGE - ############################################## - if not len(args) == 0: - print('Usage: manage.py mdat_2_fish (no arguments allowed)') - sys.exit() - - ############################################## - # PREPARE FOR IMPORT - ############################################## - # Site management: Prod vs Stage - django_prod_site = Site.objects.get(pk=1) - django_stage_site = Site.objects.get(pk=2) - - try: - parent_theme = Theme.all_objects.get(name='conservation') - except: - print("Parent Theme 'conservation' not found. Please set parent_theme.") - import ipdb; ipdb.set_trace() - - # Delete previously imported layers - previous_imports = Layer.all_objects.filter(data_source=data_source,is_sublayer=True,data_publish_date=publish_date) - print("Deleting %d previously imported MDAT V2.1 layers" % previous_imports.count()) - previous_imports.delete() - - # Get existing parent layer - # fish_parent = Layer.all_objects.get(url='', name='Fish', layer_type='checkbox') - - # Update existing parent layer - fish_parent_dict = model_to_dict(fish_parent) - fish_parent_dict['data_source'] = "%s (updated)" % data_source - fish_parent_dict['source'] = source_site - fish_parent_dict['metadata'] = source_metadata - for key in ['pk','id','name','slug_name','attribute_fields','connect_companion_layers_to','lookup_table','site','sublayers','themes','bookmark']: - try: - del fish_parent_dict[key] - except: - pass - - ############################################## - # GET OR CREATE NEW PARENT LAYERS (SPRING AND FALL) - ############################################## - # Make Fish - spring & fish - fall - (new_fish_parent_spring, created) = Layer.all_objects.get_or_create(name='Fish - Spring 2010-2017') - if created: - for key in fish_parent_dict.keys(): - setattr(new_fish_parent_spring, key, fish_parent_dict[key]) - else: - for key in ['metadata', 'data_source', 'source']: - setattr(new_fish_parent_spring, key, fish_parent_dict[key]) - new_fish_parent_spring.site.add(django_stage_site) - new_fish_parent_spring.themes.add(parent_theme) - new_fish_parent_spring.save(recache=False) - - (new_fish_parent_fall, created) = Layer.all_objects.get_or_create(name='Fish - Fall 2010-2016') - if created: - for key in fish_parent_dict.keys(): - setattr(new_fish_parent_fall, key, fish_parent_dict[key]) - else: - for key in ['metadata', 'data_source', 'source']: - setattr(new_fish_parent_fall, key, fish_parent_dict[key]) - new_fish_parent_fall.site.add(django_stage_site) - new_fish_parent_fall.themes.add(parent_theme) - new_fish_parent_fall.save(recache=False) - - - ############################################## - # MAP OUT IMPORT PATTERNS - ############################################## - service_value_lookup = { - 'fish': { - 'url': { - # 'v1': '%s%s/MapServer' % (mdat_prod_base, fish_v1_service), - # 'staging': '%s%s/MapServer' % (mdat_stage_base, fish_v2_service), - 'prod': '%s%s/MapServer' % (mdat_base, fish_service), - }, - 'parent_layer': { - # 'staging': fish_stage_parent, - 'prod': fish_parent - }, - 'exclude_words': [ - 'diversity', - 'northeast', - ' - atlantic scale' - ] - }, - } - - all_layer_dict = { - 'data_publish_date': publish_date, - 'data_source': data_source, - 'source': source_site, - 'layer_type': 'ArcRest', - 'is_sublayer': True, - } - parent_layer_map = { - 'All': 'All Fish Species', - 'Diadromous': 'Diadromous Fish', - 'Forage': 'Forage Fish', - 'Demersal': 'Demersal Fish', - 'NEFMC multispecies': 'NEFMC multispecies', - 'NEFMC small mesh multispecies': 'NEFMC small mesh multispecies', - 'NEFMC Skates': 'NEFMC Skates', - 'MAFMC FMPs': 'MAFMC FMPs', - 'ASMFC FMPs': 'ASMFC FMPs', - 'EFH Species': 'EFH Species', - 'Highly Migratory Species': 'Highly Migratory Species', - 'Abundance Vulnerable to Climate Changes': 'Abundance Vulnerable to Climate Changes', - 'Distribution Vulnerable to Climate Changes': 'Distribution Vulnerable to Climate Changes', - } - topic_layer_map = { - 'Biomass': 'Biomass', - 'Species Richness': 'Species Richness', - 'Shannon Diversity': None, - 'Simpson Diversity': None, - 'Core Biomass Area - Northeast scale': None, - 'Core Biomass Area - Mid-Atlantic scale': 'Core Biomass Area - Mid-Atlantic scale', - 'Core Biomass Area - Northeast Shelf scale': None, - - } - - for service in services: # For the fish import, this is just 'fish' - layer_name_lookup = {} - for parent_mapping in parent_layer_map.keys(): - for topic_mapping in topic_layer_map.keys(): - if topic_layer_map[topic_mapping]: - layer_name_lookup['%s, %s' % (parent_mapping, topic_mapping)] = "%s: %s" % (parent_layer_map[parent_mapping], topic_layer_map[topic_mapping]) - for server in ['prod']: - all_service_dict = { - 'url': "%s/export" % service_value_lookup[service]['url'][server], - 'metadata': service_value_lookup[service]['parent_layer'][server].metadata - } - all_service_dict.update(all_layer_dict) - - # Get Layer info from staging - print("Getting V2.1 layers for %s on %s server" % (service, server)) - v2_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url'][server]) - v2_json = requests.get(v2_json_url) - v2_layers = v2_json.json()['layers'] - if not v2_layers or len(v2_layers) < 1: - print('ERROR: Did not get layers for V2 %s on %s server' % (service, server)) - import ipdb; ipdb.set_trace() - - # print('Found %d layers for V2 %s on %s server' % (len(v2_layers),service, server)) - layers_saved = 0 - layers_skipped = 0 - for layer in v2_layers: - if (not layer['subLayerIds'] or len(layer['subLayerIds']) == 0) and not any(x.lower() in layer['name'].lower() for x in service_value_lookup[service]['exclude_words']): - current_layer = False - new_layer = False # really bad var name for 'layer we wish to update' - existing_match = False # 'a counterpart of this layer has been located from v1' - db_clones = False # 'one or more nearly identical layers have already been created' - companion_layers = False # v1 layer companion layers that need to be hooked up to new layer - attribute_fields = False # v1 layer attribute fileds to copy over - lookup_table = False # v1 layer lookup_table to copy over - # break new layer name by comma and grab 1st 2 to make layer_name_lookup id. - try: - layer_name_parts = layer['name'].split(',') - parent_value = layer_name_parts[0].strip(' ') - topic_value = layer_name_parts[1].strip(' ') - time_value = layer_name_parts[2].strip(' ') - if topic_value in topic_layer_map.keys() and topic_layer_map[topic_value]: - existing_layer_name = "%s: %s" % (parent_layer_map[parent_value], topic_layer_map[topic_value]) - new_layer = Layer.all_objects.get(name__iexact=existing_layer_name, data_source=old_data_source, sublayers=fish_parent) - except Exception as e: - pass - if time_value: - if time_value.lower() == 'Spring 2010-2017'.lower(): - parent = new_fish_parent_spring - name_suffix = " (spring)" - else: - parent = new_fish_parent_fall - name_suffix = " (fall)" - else: - import ipdb; ipdb.set_trace() - - # import ipdb; ipdb.set_trace() - # exit() - - if not new_layer: - if existing_layer_name: - new_layer_name = "%s%s" % (existing_layer_name, name_suffix) - else: - new_layer_name = "%s%s" % (layer['name'], name_suffix) - new_layer_dict = { - 'layer_type': all_layer_dict['layer_type'], - 'data_publish_date': all_layer_dict['data_publish_date'], - # 'site': [django_stage_site.pk], - # 'themes': [parent_theme.pk], - 'is_sublayer': True, - 'source': all_layer_dict['source'], - 'metadata': all_service_dict['metadata'], - 'description': u'We are currently updating this layer. Please come back later for a full description of this layer.', - 'data_overview': u'We are currently updating this layer. Please come back later for a full overview of this layer.', - # 'slug_name': u'all-fish-species-biomass-v2-prod-1295', - 'data_source': all_layer_dict['data_source'], - 'name': new_layer_name, - 'url': all_service_dict['url'], - 'arcgis_layers': layer['id'], - 'order': layer['id'], - # 'sublayers': [parent.pk], - 'espis_region': u'Mid Atlantic', - } - new_layer = Layer.all_objects.create(**new_layer_dict) - new_layer.site.add(django_stage_site) - new_layer.site.add(django_prod_site) - new_layer.themes.add(parent_theme.pk) - new_layer.sublayers.add(parent.pk) - new_layer.save(recache=False) - new_layer.save(recache=False,slug_name="%s-v2.1-%s" % (new_layer.slug,server)) - - else: - # Create new spring/fall layers from existing layer - new_layer_dict = model_to_dict(new_layer) - new_layer_dict['name'] = "%s%s" % (new_layer_dict['name'], name_suffix) - new_layer_dict['data_publish_date'] = all_layer_dict['data_publish_date'] - for attr in ['site','id','themes','connect_companion_layers_to','lookup_table','attribute_fields','slug_name','sublayers']: - new_layer_dict.pop(attr) - new_layer_dict['source']= all_layer_dict['source'] - new_layer_dict['data_source'] = all_layer_dict['data_source'] - new_layer_dict['arcgis_layers'] = layer['id'] - new_layer_dict['order'] = layer['id'] - for key in ['metadata', 'url']: - new_layer_dict[key] = all_service_dict[key] - new_layer = Layer.all_objects.create(**new_layer_dict) - new_layer.site.add(django_stage_site) - new_layer.site.add(django_prod_site) - new_layer.themes.add(parent_theme.pk) - new_layer.sublayers.add(parent.pk) - new_layer.save(recache=False,slug_name="%s-v2.1-%s" % (new_layer.slug,server)) - layers_saved += 1 - else: - layers_skipped += 1 - - service_value_lookup[service]['parent_layer'][server].save(recache=False) - print('created %d layers for V2 %s on %s server' % (layers_saved, service, server)) - if len(v2_layers) > layers_saved + layers_skipped: - missed_layers = len(layers) - layers_saved - layers_skipped - print('Missed %d layers for V2 %s on %s server' % (missed_layers, service, server)) - import ipdb; ipdb.set_trace() - - from django.core.cache import cache - cache.clear() +from django.core.management.base import BaseCommand +import sys + +# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning +import urllib3 +urllib3.disable_warnings() + +class Command(BaseCommand): + + help = "Generate staging layers for MDAT Fish Summary (V2.1)" + + def handle(self, *args, **options): + ############################################## + # DEPENDENCIES + ############################################## + import requests + from django.forms.models import model_to_dict + from datetime import date + from django.contrib.sites.models import Site + from data_manager.models import Layer, Theme + + ############################################## + # SETTINGS + ############################################## + #--------------------------------------------- + #- new server/layers settings + #--------------------------------------------- + # mdat_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT/' + mdat_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT_Staging/' + data_source = 'Marine-Life Data and Analysis Team (V2.1)' + publish_date = date(2019,6,24) + source_site = 'http://seamap.env.duke.edu/models/mdat/' + source_metadata = 'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf' + # RDH 2019-06-03: Are we worried about other services? + services = ['fish'] + fish_service = 'Fish_SummaryProducts_NEFSC' + + #--------------------------------------------- + #- old layer settings + #--------------------------------------------- + old_layer_name = 'Fish' + old_layer_type = 'checkbox' + old_theme_name = 'conservation' + old_data_source = 'Marine Life Data and Analysis Team V2' + parent_theme = Theme.all_objects.get(name='conservation') + try: + fish_parent = Layer.all_objects.get(name__iexact=old_layer_name, layer_type=old_layer_type, themes=parent_theme, data_source=old_data_source) + except Exception as e: + parent_layer_dict = { + 'data_source': u'Marine Life Data and Analysis Team V2', + 'layer_type': u'checkbox', + 'metadata': u'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf', + 'name': u'Fish', + 'order': 10, + 'source': u'http://seamap.env.duke.edu/models/mdat/', + } + fish_parent = Layer.all_objects.create(**parent_layer_dict) + + ############################################## + # VALIDATE USAGE + ############################################## + if not len(args) == 0: + print('Usage: manage.py mdat_2_fish (no arguments allowed)') + sys.exit() + + ############################################## + # PREPARE FOR IMPORT + ############################################## + # Site management: Prod vs Stage + django_prod_site = Site.objects.get(pk=1) + django_stage_site = Site.objects.get(pk=2) + + try: + parent_theme = Theme.all_objects.get(name='conservation') + except: + print("Parent Theme 'conservation' not found. Please set parent_theme.") + import ipdb; ipdb.set_trace() + + # Delete previously imported layers + previous_imports = Layer.all_objects.filter(data_source=data_source,is_sublayer=True,data_publish_date=publish_date) + print("Deleting %d previously imported MDAT V2.1 layers" % previous_imports.count()) + previous_imports.delete() + + # Get existing parent layer + # fish_parent = Layer.all_objects.get(url='', name='Fish', layer_type='checkbox') + + # Update existing parent layer + fish_parent_dict = model_to_dict(fish_parent) + fish_parent_dict['data_source'] = "%s (updated)" % data_source + fish_parent_dict['source'] = source_site + fish_parent_dict['metadata'] = source_metadata + for key in ['pk','id','name','slug_name','attribute_fields','connect_companion_layers_to','lookup_table','site','sublayers','themes','bookmark']: + try: + del fish_parent_dict[key] + except: + pass + + ############################################## + # GET OR CREATE NEW PARENT LAYERS (SPRING AND FALL) + ############################################## + # Make Fish - spring & fish - fall + (new_fish_parent_spring, created) = Layer.all_objects.get_or_create(name='Fish - Spring 2010-2017') + if created: + for key in fish_parent_dict.keys(): + setattr(new_fish_parent_spring, key, fish_parent_dict[key]) + else: + for key in ['metadata', 'data_source', 'source']: + setattr(new_fish_parent_spring, key, fish_parent_dict[key]) + new_fish_parent_spring.site.add(django_stage_site) + new_fish_parent_spring.themes.add(parent_theme) + new_fish_parent_spring.save(recache=False) + + (new_fish_parent_fall, created) = Layer.all_objects.get_or_create(name='Fish - Fall 2010-2016') + if created: + for key in fish_parent_dict.keys(): + setattr(new_fish_parent_fall, key, fish_parent_dict[key]) + else: + for key in ['metadata', 'data_source', 'source']: + setattr(new_fish_parent_fall, key, fish_parent_dict[key]) + new_fish_parent_fall.site.add(django_stage_site) + new_fish_parent_fall.themes.add(parent_theme) + new_fish_parent_fall.save(recache=False) + + + ############################################## + # MAP OUT IMPORT PATTERNS + ############################################## + service_value_lookup = { + 'fish': { + 'url': { + # 'v1': '%s%s/MapServer' % (mdat_prod_base, fish_v1_service), + # 'staging': '%s%s/MapServer' % (mdat_stage_base, fish_v2_service), + 'prod': '%s%s/MapServer' % (mdat_base, fish_service), + }, + 'parent_layer': { + # 'staging': fish_stage_parent, + 'prod': fish_parent + }, + 'exclude_words': [ + 'diversity', + 'northeast', + ' - atlantic scale' + ] + }, + } + + all_layer_dict = { + 'data_publish_date': publish_date, + 'data_source': data_source, + 'source': source_site, + 'layer_type': 'ArcRest', + 'is_sublayer': True, + } + parent_layer_map = { + 'All': 'All Fish Species', + 'Diadromous': 'Diadromous Fish', + 'Forage': 'Forage Fish', + 'Demersal': 'Demersal Fish', + 'NEFMC multispecies': 'NEFMC multispecies', + 'NEFMC small mesh multispecies': 'NEFMC small mesh multispecies', + 'NEFMC Skates': 'NEFMC Skates', + 'MAFMC FMPs': 'MAFMC FMPs', + 'ASMFC FMPs': 'ASMFC FMPs', + 'EFH Species': 'EFH Species', + 'Highly Migratory Species': 'Highly Migratory Species', + 'Abundance Vulnerable to Climate Changes': 'Abundance Vulnerable to Climate Changes', + 'Distribution Vulnerable to Climate Changes': 'Distribution Vulnerable to Climate Changes', + } + topic_layer_map = { + 'Biomass': 'Biomass', + 'Species Richness': 'Species Richness', + 'Shannon Diversity': None, + 'Simpson Diversity': None, + 'Core Biomass Area - Northeast scale': None, + 'Core Biomass Area - Mid-Atlantic scale': 'Core Biomass Area - Mid-Atlantic scale', + 'Core Biomass Area - Northeast Shelf scale': None, + + } + + for service in services: # For the fish import, this is just 'fish' + layer_name_lookup = {} + for parent_mapping in parent_layer_map.keys(): + for topic_mapping in topic_layer_map.keys(): + if topic_layer_map[topic_mapping]: + layer_name_lookup['%s, %s' % (parent_mapping, topic_mapping)] = "%s: %s" % (parent_layer_map[parent_mapping], topic_layer_map[topic_mapping]) + for server in ['prod']: + all_service_dict = { + 'url': "%s/export" % service_value_lookup[service]['url'][server], + 'metadata': service_value_lookup[service]['parent_layer'][server].metadata + } + all_service_dict.update(all_layer_dict) + + # Get Layer info from staging + print("Getting V2.1 layers for %s on %s server" % (service, server)) + v2_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url'][server]) + v2_json = requests.get(v2_json_url) + v2_layers = v2_json.json()['layers'] + if not v2_layers or len(v2_layers) < 1: + print('ERROR: Did not get layers for V2 %s on %s server' % (service, server)) + import ipdb; ipdb.set_trace() + + # print('Found %d layers for V2 %s on %s server' % (len(v2_layers),service, server)) + layers_saved = 0 + layers_skipped = 0 + for layer in v2_layers: + if (not layer['subLayerIds'] or len(layer['subLayerIds']) == 0) and not any(x.lower() in layer['name'].lower() for x in service_value_lookup[service]['exclude_words']): + current_layer = False + new_layer = False # really bad var name for 'layer we wish to update' + existing_match = False # 'a counterpart of this layer has been located from v1' + db_clones = False # 'one or more nearly identical layers have already been created' + companion_layers = False # v1 layer companion layers that need to be hooked up to new layer + attribute_fields = False # v1 layer attribute fileds to copy over + lookup_table = False # v1 layer lookup_table to copy over + # break new layer name by comma and grab 1st 2 to make layer_name_lookup id. + try: + layer_name_parts = layer['name'].split(',') + parent_value = layer_name_parts[0].strip(' ') + topic_value = layer_name_parts[1].strip(' ') + time_value = layer_name_parts[2].strip(' ') + if topic_value in topic_layer_map.keys() and topic_layer_map[topic_value]: + existing_layer_name = "%s: %s" % (parent_layer_map[parent_value], topic_layer_map[topic_value]) + new_layer = Layer.all_objects.get(name__iexact=existing_layer_name, data_source=old_data_source, sublayers=fish_parent) + except Exception as e: + pass + if time_value: + if time_value.lower() == 'Spring 2010-2017'.lower(): + parent = new_fish_parent_spring + name_suffix = " (spring)" + else: + parent = new_fish_parent_fall + name_suffix = " (fall)" + else: + import ipdb; ipdb.set_trace() + + # import ipdb; ipdb.set_trace() + # exit() + + if not new_layer: + if existing_layer_name: + new_layer_name = "%s%s" % (existing_layer_name, name_suffix) + else: + new_layer_name = "%s%s" % (layer['name'], name_suffix) + new_layer_dict = { + 'layer_type': all_layer_dict['layer_type'], + 'data_publish_date': all_layer_dict['data_publish_date'], + # 'site': [django_stage_site.pk], + # 'themes': [parent_theme.pk], + 'is_sublayer': True, + 'source': all_layer_dict['source'], + 'metadata': all_service_dict['metadata'], + 'description': u'We are currently updating this layer. Please come back later for a full description of this layer.', + 'data_overview': u'We are currently updating this layer. Please come back later for a full overview of this layer.', + # 'slug_name': u'all-fish-species-biomass-v2-prod-1295', + 'data_source': all_layer_dict['data_source'], + 'name': new_layer_name, + 'url': all_service_dict['url'], + 'arcgis_layers': layer['id'], + 'order': layer['id'], + # 'sublayers': [parent.pk], + 'espis_region': u'Mid Atlantic', + } + new_layer = Layer.all_objects.create(**new_layer_dict) + new_layer.site.add(django_stage_site) + new_layer.site.add(django_prod_site) + new_layer.themes.add(parent_theme.pk) + new_layer.sublayers.add(parent.pk) + new_layer.save(recache=False) + new_layer.save(recache=False,slug_name="%s-v2.1-%s" % (new_layer.slug,server)) + + else: + # Create new spring/fall layers from existing layer + new_layer_dict = model_to_dict(new_layer) + new_layer_dict['name'] = "%s%s" % (new_layer_dict['name'], name_suffix) + new_layer_dict['data_publish_date'] = all_layer_dict['data_publish_date'] + for attr in ['site','id','themes','connect_companion_layers_to','lookup_table','attribute_fields','slug_name','sublayers']: + new_layer_dict.pop(attr) + new_layer_dict['source']= all_layer_dict['source'] + new_layer_dict['data_source'] = all_layer_dict['data_source'] + new_layer_dict['arcgis_layers'] = layer['id'] + new_layer_dict['order'] = layer['id'] + for key in ['metadata', 'url']: + new_layer_dict[key] = all_service_dict[key] + new_layer = Layer.all_objects.create(**new_layer_dict) + new_layer.site.add(django_stage_site) + new_layer.site.add(django_prod_site) + new_layer.themes.add(parent_theme.pk) + new_layer.sublayers.add(parent.pk) + new_layer.save(recache=False,slug_name="%s-v2.1-%s" % (new_layer.slug,server)) + layers_saved += 1 + else: + layers_skipped += 1 + + service_value_lookup[service]['parent_layer'][server].save(recache=False) + print('created %d layers for V2 %s on %s server' % (layers_saved, service, server)) + if len(v2_layers) > layers_saved + layers_skipped: + missed_layers = len(layers) - layers_saved - layers_skipped + print('Missed %d layers for V2 %s on %s server' % (missed_layers, service, server)) + import ipdb; ipdb.set_trace() + + from django.core.cache import cache + cache.clear() diff --git a/data_manager/management/commands/mdat_2_transition.py b/data_manager/management/commands/mdat_2_transition.py index 9b59f94..656bc06 100644 --- a/data_manager/management/commands/mdat_2_transition.py +++ b/data_manager/management/commands/mdat_2_transition.py @@ -1,317 +1,317 @@ -from django.core.management.base import BaseCommand -import sys - -# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning -import urllib3 -urllib3.disable_warnings() - -class Command(BaseCommand): - - help = "Generate staging layers for MDAT V2" - - def handle(self, *args, **options): - import requests - from django.forms.models import model_to_dict - from datetime import date - from django.contrib.sites.models import Site - from data_manager.models import Layer, Theme - - if not len(args) == 0: - print('Usage: manage.py import_era (no arguments allowed)') - sys.exit() - - django_prod_site = Site.objects.get(pk=1) - django_stage_site = Site.objects.get(pk=2) - - try: - parent_theme = Theme.objects.get(name='conservation') - except: - print("Parent Theme 'conservation' not found. Please set parent_theme.") - import ipdb; ipdb.set_trace() - - data_source = 'Marine Life Data and Analysis Team V2' - source_site = 'http://seamap.env.duke.edu/models/mdat/' - - mdat_prod_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT/' - mdat_stage_base = 'https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/' - avian_v1_service = 'AvianModels_SyntheticProducts' - avian_v2_service = 'Avian_SummaryProducts' - mammal_v1_service = 'Mammal_SyntheticProducts' - mammal_v2_service = 'Mammal_SummaryProducts' - fish_v1_service = 'Fish_NEFSC_SyntheticProducts' - fish_v2_service = 'Fish_SummaryProducts_NEFSC' - - # Delete previously imported layers - # print("Deleting previously imported MDAT V2 layers") - # Layer.objects.filter(data_source=data_source,is_sublayer=True,data_publish_date=date(2018,8,8)).delete() - - services = ['avian', 'mammal', 'fish'] - - avian_v1_parent = Layer.all_objects.get(url='', name='Birds - V1', layer_type='checkbox') - avian_parent_dict = model_to_dict(avian_v1_parent) - mammal_v1_parent = Layer.all_objects.get(url='', name='Marine Mammals - V1', layer_type='checkbox') - mammal_parent_dict = model_to_dict(avian_v1_parent) - fish_v1_parent = Layer.all_objects.get(url='', name='Fish - V1', layer_type='checkbox') - fish_parent_dict = model_to_dict(avian_v1_parent) - - for parent_dict in [avian_parent_dict, mammal_parent_dict, fish_parent_dict]: - parent_dict['data_source'] = data_source - parent_dict['source'] = source_site - - for key in ['pk','id','name','slug_name','attribute_fields','connect_companion_layers_to','lookup_table','site','sublayers','themes','bookmark']: - try: - del parent_dict[key] - except: - pass - - # Set metadata links - avian_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Avian/MDAT_Avian_Summary_Products_Metadata.pdf' - mammal_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Mammal/MDAT_Mammal_Summary_Products_Metadata.pdf' - fish_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf' - - # create 2 parent layers for each service: - # one to point at dev server - # one to point at anticipated live server - (avian_stage_parent, created) = Layer.all_objects.get_or_create(name='Birds - Stage V2') - if created: - for key in avian_parent_dict.keys(): - setattr(avian_stage_parent, key, avian_parent_dict[key]) - else: - for key in ['metadata']: - setattr(avian_stage_parent, key, avian_parent_dict[key]) - (avian_prod_parent, created) = Layer.all_objects.get_or_create(name='Birds') - if created: - for key in avian_parent_dict.keys(): - setattr(avian_prod_parent, key, avian_parent_dict[key]) - else: - for key in ['metadata']: - setattr(avian_prod_parent, key, avian_parent_dict[key]) - (mammal_stage_parent, created) = Layer.all_objects.get_or_create(name='Marine Mammals - Stage V2') - if created: - for key in mammal_parent_dict.keys(): - setattr(mammal_stage_parent, key, mammal_parent_dict[key]) - else: - for key in ['metadata']: - setattr(mammal_stage_parent, key, mammal_parent_dict[key]) - (mammal_prod_parent, created) = Layer.all_objects.get_or_create(name='Marine Mammals') - if created: - for key in mammal_parent_dict.keys(): - setattr(mammal_prod_parent, key, mammal_parent_dict[key]) - else: - for key in ['metadata']: - setattr(mammal_prod_parent, key, mammal_parent_dict[key]) - (fish_stage_parent, created) = Layer.all_objects.get_or_create(name='Fish - Stage V2') - if created: - for key in fish_parent_dict.keys(): - setattr(fish_stage_parent, key, fish_parent_dict[key]) - else: - for key in ['metadata']: - setattr(fish_stage_parent, key, fish_parent_dict[key]) - (fish_prod_parent, created) = Layer.all_objects.get_or_create(name='Fish') - if created: - for key in fish_parent_dict.keys(): - setattr(fish_prod_parent, key, fish_parent_dict[key]) - else: - for key in ['metadata']: - setattr(fish_prod_parent, key, fish_parent_dict[key]) - - parent_layers = [ - avian_stage_parent, - avian_prod_parent, - mammal_stage_parent, - mammal_prod_parent, - fish_stage_parent, - fish_prod_parent, - ] - - for parent_layer in parent_layers: - parent_layer.site.add(django_stage_site) - parent_layer.themes.add(parent_theme) - parent_layer.save(recache=False) - - service_value_lookup = { - 'avian': { - 'url': { - 'v1': '%s%s/MapServer' % (mdat_prod_base, avian_v1_service), - 'staging': '%s%s/MapServer' % (mdat_stage_base, avian_v2_service), - 'prod': '%s%s/MapServer' % (mdat_prod_base, avian_v2_service), - }, - 'parent_layer': { - 'staging': avian_stage_parent, - 'prod': avian_prod_parent - }, - 'exclude_words': [ - 'diversity', - 'northeast', - ' - atlantic scale', - 'breeding', - 'feeding', - 'resident', - ] - }, - 'mammal': { - 'url': { - 'v1': '%s%s/MapServer' % (mdat_prod_base, mammal_v1_service), - 'staging': '%s%s/MapServer' % (mdat_stage_base, mammal_v2_service), - 'prod': '%s%s/MapServer' % (mdat_prod_base, mammal_v2_service), - }, - 'parent_layer': { - 'staging': mammal_stage_parent, - 'prod': mammal_prod_parent - }, - 'exclude_words': [ - 'diversity', - 'northeast', - ' - atlantic scale' - ] - }, - 'fish': { - 'url': { - 'v1': '%s%s/MapServer' % (mdat_prod_base, fish_v1_service), - 'staging': '%s%s/MapServer' % (mdat_stage_base, fish_v2_service), - 'prod': '%s%s/MapServer' % (mdat_prod_base, fish_v2_service), - }, - 'parent_layer': { - 'staging': fish_stage_parent, - 'prod': fish_prod_parent - }, - 'exclude_words': [ - 'diversity', - 'northeast', - ' - atlantic scale' - ] - }, - } - - all_layer_dict = { - 'data_publish_date': date(2018,8,8), - 'data_source': data_source, - 'source': source_site, - 'layer_type': 'ArcRest', - 'is_sublayer': True, - } - - for service in services: - # RDH: V1 services are no longer available - # print("Getting V1 layers for %s" % service) - # # query v1.1 prod for layernames (to be used to lookup and modify fields as needed to preserve work) - # v1_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url']['v1']) - # v1_json = requests.get(v1_json_url) - # v1_layers = v1_json.json()['layers'] - # if not v1_layers or len(v1_layers) < 1: - # print('ERROR: Did not get layers for V1 %s' % service) - # import ipdb; ipdb.set_trace() - # - # # print('Found %d layers for V1 %s' % (len(v1_layers),service)) - # - # layer_name_lookup = {} - # for layer in v1_layers: - # v1_matches = Layer.all_objects.filter(url="%s/export" % service_value_lookup[service]['url']['v1'], arcgis_layers=str(layer['id'])) - # # # if layer exists for v1.1 in db - # if v1_matches.count() == 1: - # layer_name_lookup[layer['name']] = v1_matches[0] - # elif v1_matches.count() > 0: - # print('Multiple matches for %s. Please pick the match you want from v1_matches for the layer_name_lookup, or set to None to skip' % layer['name']) - # layer_name_lookup[layer['name']] = v1_matches[0] - # import ipdb; ipdb.set_trace() - - for server in ['staging', 'prod']: - all_service_dict = { - 'url': "%s/export" % service_value_lookup[service]['url'][server], - 'metadata': service_value_lookup[service]['parent_layer'][server].metadata - } - all_service_dict.update(all_layer_dict) - - # Get Layer info from staging - print("Getting V2 layers for %s on %s server" % (service, server)) - v2_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url']['staging']) - v2_json = requests.get(v2_json_url) - v2_layers = v2_json.json()['layers'] - if not v2_layers or len(v2_layers) < 1: - print('ERROR: Did not get layers for V2 %s on %s server' % (service, server)) - import ipdb; ipdb.set_trace() - - # print('Found %d layers for V2 %s on %s server' % (len(v2_layers),service, server)) - layers_saved = 0 - layers_skipped = 0 - for layer in v2_layers: - if (not layer['subLayerIds'] or len(layer['subLayerIds']) == 0) and not any(x.lower() in layer['name'].lower() for x in service_value_lookup[service]['exclude_words']): - current_layer = False - new_layer = False # really bad var name for 'layer we wish to update' - existing_match = False # 'a counterpart of this layer has been located from v1' - db_clones = False # 'one or more nearly identical layers have already been created' - companion_layers = False # v1 layer companion layers that need to be hooked up to new layer - attribute_fields = False # v1 layer attribute fileds to copy over - lookup_table = False # v1 layer lookup_table to copy over - created = True # a new layer is being created - try: - new_layer = Layer.objects.get(arcgis_layers=str(layer['id']),url=all_service_dict['url']) - created = False - except: - pass - if not new_layer: - if layer['name'] in layer_name_lookup.keys(): - # print('Match found, new layer name SHOULD be "%s"' % layer_name_lookup[layer['name']]) - # existing_matches = Layer.all_objects.filter(arcgis_layers=str(layer['id']),url=all_service_dict['url'],name=current_layer.name,order=current_layer.order) - current_layer = layer_name_lookup[layer['name']] - # EXISTING_MATCHES should in this case be a queryset of a single existing v1 record - the match - existing_match = Layer.all_objects.get(id=current_layer.id) - # DB_CLONES are already created v2 layers matching old v1 layers - db_clones = Layer.all_objects.filter(name=current_layer.name,**all_service_dict) - if existing_match and not db_clones.count() > 0: - companion_layers = existing_match.connect_companion_layers_to.all() - attribute_fields = existing_match.attribute_fields.all() - lookup_table = existing_match.lookup_table.all() - new_layer = existing_match - new_layer.pk = None - new_layer.bookmark = None - new_layer.arcgis_layers=str(layer['id']) - - else: - try: - (new_layer, created) = Layer.all_objects.get_or_create(arcgis_layers=str(layer['id']),**all_service_dict) - if created: - new_layer.name = layer['name'] - new_layer.order = layer['id'] - except: - import ipdb; ipdb.set_trace() - - if new_layer: - if created: - for key in all_service_dict.keys(): - setattr(new_layer, key, all_service_dict[key]) - new_layer.save(recache=False) - new_layer.site.add(django_prod_site) - new_layer.site.add(django_stage_site) - new_layer.themes.add(parent_theme) - # new_layer.slug = "%s-v2-%s" % (new_layer.slug_name,server) - new_layer.sublayers.add(service_value_lookup[service]['parent_layer'][server]) - if current_layer and not current_layer.name == new_layer.name: - print("Name attribute did not copy from old to new layer. Investigate.") - import ipdb; ipdb.set_trace() - if companion_layers and not new_layer.connect_companion_layers_to.all() == companion_layers: - for companion_layer in companion_layers: - new_layer.connect_companion_layers_to.add(companion_layer) - if attribute_fields and not new_layer.attribute_fields.all() == attribute_fields: - for attribute_field in attribute_fields: - new_layer.attribute_fields.add(attribute_field) - if lookup_table and not new_layer.lookup_table.all() == lookup_table: - for lookup in lookup_table: - new_layer.lookup_table.add(lookup) - else: - for key in ['metadata']: - setattr(new_layer, key, all_service_dict[key]) - new_layer.save(recache=False,slug_name="%s-v2-%s" % (new_layer.slug,server)) - layers_saved += 1 - else: - layers_skipped += 1 - - service_value_lookup[service]['parent_layer'][server].save(recache=False) - print('created %d layers for V2 %s on %s server' % (layers_saved, service, server)) - if len(v2_layers) > layers_saved + layers_skipped: - missed_layers = len(layers) - layers_saved - layers_skipped - print('Missed %d layers for V2 %s on %s server' % (missed_layers, service, server)) - import ipdb; ipdb.set_trace() - - from django.core.cache import cache - cache.clear() +from django.core.management.base import BaseCommand +import sys + +# Ignore the nasty SNIMissingWarning and the InsecurePlatformWarning +import urllib3 +urllib3.disable_warnings() + +class Command(BaseCommand): + + help = "Generate staging layers for MDAT V2" + + def handle(self, *args, **options): + import requests + from django.forms.models import model_to_dict + from datetime import date + from django.contrib.sites.models import Site + from data_manager.models import Layer, Theme + + if not len(args) == 0: + print('Usage: manage.py import_era (no arguments allowed)') + sys.exit() + + django_prod_site = Site.objects.get(pk=1) + django_stage_site = Site.objects.get(pk=2) + + try: + parent_theme = Theme.objects.get(name='conservation') + except: + print("Parent Theme 'conservation' not found. Please set parent_theme.") + import ipdb; ipdb.set_trace() + + data_source = 'Marine Life Data and Analysis Team V2' + source_site = 'http://seamap.env.duke.edu/models/mdat/' + + mdat_prod_base = 'https://mgelmaps.env.duke.edu/mdat/rest/services/MDAT/' + mdat_stage_base = 'https://mgelmaps.env.duke.edu/mdat_new/rest/services/MDAT_Staging/' + avian_v1_service = 'AvianModels_SyntheticProducts' + avian_v2_service = 'Avian_SummaryProducts' + mammal_v1_service = 'Mammal_SyntheticProducts' + mammal_v2_service = 'Mammal_SummaryProducts' + fish_v1_service = 'Fish_NEFSC_SyntheticProducts' + fish_v2_service = 'Fish_SummaryProducts_NEFSC' + + # Delete previously imported layers + # print("Deleting previously imported MDAT V2 layers") + # Layer.objects.filter(data_source=data_source,is_sublayer=True,data_publish_date=date(2018,8,8)).delete() + + services = ['avian', 'mammal', 'fish'] + + avian_v1_parent = Layer.all_objects.get(url='', name='Birds - V1', layer_type='checkbox') + avian_parent_dict = model_to_dict(avian_v1_parent) + mammal_v1_parent = Layer.all_objects.get(url='', name='Marine Mammals - V1', layer_type='checkbox') + mammal_parent_dict = model_to_dict(avian_v1_parent) + fish_v1_parent = Layer.all_objects.get(url='', name='Fish - V1', layer_type='checkbox') + fish_parent_dict = model_to_dict(avian_v1_parent) + + for parent_dict in [avian_parent_dict, mammal_parent_dict, fish_parent_dict]: + parent_dict['data_source'] = data_source + parent_dict['source'] = source_site + + for key in ['pk','id','name','slug_name','attribute_fields','connect_companion_layers_to','lookup_table','site','sublayers','themes','bookmark']: + try: + del parent_dict[key] + except: + pass + + # Set metadata links + avian_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Avian/MDAT_Avian_Summary_Products_Metadata.pdf' + mammal_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Mammal/MDAT_Mammal_Summary_Products_Metadata.pdf' + fish_parent_dict['metadata'] = 'http://seamap.env.duke.edu/models/mdat/Fish/MDAT_NEFSC_Fish_Summary_Products_Metadata.pdf' + + # create 2 parent layers for each service: + # one to point at dev server + # one to point at anticipated live server + (avian_stage_parent, created) = Layer.all_objects.get_or_create(name='Birds - Stage V2') + if created: + for key in avian_parent_dict.keys(): + setattr(avian_stage_parent, key, avian_parent_dict[key]) + else: + for key in ['metadata']: + setattr(avian_stage_parent, key, avian_parent_dict[key]) + (avian_prod_parent, created) = Layer.all_objects.get_or_create(name='Birds') + if created: + for key in avian_parent_dict.keys(): + setattr(avian_prod_parent, key, avian_parent_dict[key]) + else: + for key in ['metadata']: + setattr(avian_prod_parent, key, avian_parent_dict[key]) + (mammal_stage_parent, created) = Layer.all_objects.get_or_create(name='Marine Mammals - Stage V2') + if created: + for key in mammal_parent_dict.keys(): + setattr(mammal_stage_parent, key, mammal_parent_dict[key]) + else: + for key in ['metadata']: + setattr(mammal_stage_parent, key, mammal_parent_dict[key]) + (mammal_prod_parent, created) = Layer.all_objects.get_or_create(name='Marine Mammals') + if created: + for key in mammal_parent_dict.keys(): + setattr(mammal_prod_parent, key, mammal_parent_dict[key]) + else: + for key in ['metadata']: + setattr(mammal_prod_parent, key, mammal_parent_dict[key]) + (fish_stage_parent, created) = Layer.all_objects.get_or_create(name='Fish - Stage V2') + if created: + for key in fish_parent_dict.keys(): + setattr(fish_stage_parent, key, fish_parent_dict[key]) + else: + for key in ['metadata']: + setattr(fish_stage_parent, key, fish_parent_dict[key]) + (fish_prod_parent, created) = Layer.all_objects.get_or_create(name='Fish') + if created: + for key in fish_parent_dict.keys(): + setattr(fish_prod_parent, key, fish_parent_dict[key]) + else: + for key in ['metadata']: + setattr(fish_prod_parent, key, fish_parent_dict[key]) + + parent_layers = [ + avian_stage_parent, + avian_prod_parent, + mammal_stage_parent, + mammal_prod_parent, + fish_stage_parent, + fish_prod_parent, + ] + + for parent_layer in parent_layers: + parent_layer.site.add(django_stage_site) + parent_layer.themes.add(parent_theme) + parent_layer.save(recache=False) + + service_value_lookup = { + 'avian': { + 'url': { + 'v1': '%s%s/MapServer' % (mdat_prod_base, avian_v1_service), + 'staging': '%s%s/MapServer' % (mdat_stage_base, avian_v2_service), + 'prod': '%s%s/MapServer' % (mdat_prod_base, avian_v2_service), + }, + 'parent_layer': { + 'staging': avian_stage_parent, + 'prod': avian_prod_parent + }, + 'exclude_words': [ + 'diversity', + 'northeast', + ' - atlantic scale', + 'breeding', + 'feeding', + 'resident', + ] + }, + 'mammal': { + 'url': { + 'v1': '%s%s/MapServer' % (mdat_prod_base, mammal_v1_service), + 'staging': '%s%s/MapServer' % (mdat_stage_base, mammal_v2_service), + 'prod': '%s%s/MapServer' % (mdat_prod_base, mammal_v2_service), + }, + 'parent_layer': { + 'staging': mammal_stage_parent, + 'prod': mammal_prod_parent + }, + 'exclude_words': [ + 'diversity', + 'northeast', + ' - atlantic scale' + ] + }, + 'fish': { + 'url': { + 'v1': '%s%s/MapServer' % (mdat_prod_base, fish_v1_service), + 'staging': '%s%s/MapServer' % (mdat_stage_base, fish_v2_service), + 'prod': '%s%s/MapServer' % (mdat_prod_base, fish_v2_service), + }, + 'parent_layer': { + 'staging': fish_stage_parent, + 'prod': fish_prod_parent + }, + 'exclude_words': [ + 'diversity', + 'northeast', + ' - atlantic scale' + ] + }, + } + + all_layer_dict = { + 'data_publish_date': date(2018,8,8), + 'data_source': data_source, + 'source': source_site, + 'layer_type': 'ArcRest', + 'is_sublayer': True, + } + + for service in services: + # RDH: V1 services are no longer available + # print("Getting V1 layers for %s" % service) + # # query v1.1 prod for layernames (to be used to lookup and modify fields as needed to preserve work) + # v1_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url']['v1']) + # v1_json = requests.get(v1_json_url) + # v1_layers = v1_json.json()['layers'] + # if not v1_layers or len(v1_layers) < 1: + # print('ERROR: Did not get layers for V1 %s' % service) + # import ipdb; ipdb.set_trace() + # + # # print('Found %d layers for V1 %s' % (len(v1_layers),service)) + # + # layer_name_lookup = {} + # for layer in v1_layers: + # v1_matches = Layer.all_objects.filter(url="%s/export" % service_value_lookup[service]['url']['v1'], arcgis_layers=str(layer['id'])) + # # # if layer exists for v1.1 in db + # if v1_matches.count() == 1: + # layer_name_lookup[layer['name']] = v1_matches[0] + # elif v1_matches.count() > 0: + # print('Multiple matches for %s. Please pick the match you want from v1_matches for the layer_name_lookup, or set to None to skip' % layer['name']) + # layer_name_lookup[layer['name']] = v1_matches[0] + # import ipdb; ipdb.set_trace() + + for server in ['staging', 'prod']: + all_service_dict = { + 'url': "%s/export" % service_value_lookup[service]['url'][server], + 'metadata': service_value_lookup[service]['parent_layer'][server].metadata + } + all_service_dict.update(all_layer_dict) + + # Get Layer info from staging + print("Getting V2 layers for %s on %s server" % (service, server)) + v2_json_url = '%s/?f=pjson' % (service_value_lookup[service]['url']['staging']) + v2_json = requests.get(v2_json_url) + v2_layers = v2_json.json()['layers'] + if not v2_layers or len(v2_layers) < 1: + print('ERROR: Did not get layers for V2 %s on %s server' % (service, server)) + import ipdb; ipdb.set_trace() + + # print('Found %d layers for V2 %s on %s server' % (len(v2_layers),service, server)) + layers_saved = 0 + layers_skipped = 0 + for layer in v2_layers: + if (not layer['subLayerIds'] or len(layer['subLayerIds']) == 0) and not any(x.lower() in layer['name'].lower() for x in service_value_lookup[service]['exclude_words']): + current_layer = False + new_layer = False # really bad var name for 'layer we wish to update' + existing_match = False # 'a counterpart of this layer has been located from v1' + db_clones = False # 'one or more nearly identical layers have already been created' + companion_layers = False # v1 layer companion layers that need to be hooked up to new layer + attribute_fields = False # v1 layer attribute fileds to copy over + lookup_table = False # v1 layer lookup_table to copy over + created = True # a new layer is being created + try: + new_layer = Layer.objects.get(arcgis_layers=str(layer['id']),url=all_service_dict['url']) + created = False + except: + pass + if not new_layer: + if layer['name'] in layer_name_lookup.keys(): + # print('Match found, new layer name SHOULD be "%s"' % layer_name_lookup[layer['name']]) + # existing_matches = Layer.all_objects.filter(arcgis_layers=str(layer['id']),url=all_service_dict['url'],name=current_layer.name,order=current_layer.order) + current_layer = layer_name_lookup[layer['name']] + # EXISTING_MATCHES should in this case be a queryset of a single existing v1 record - the match + existing_match = Layer.all_objects.get(id=current_layer.id) + # DB_CLONES are already created v2 layers matching old v1 layers + db_clones = Layer.all_objects.filter(name=current_layer.name,**all_service_dict) + if existing_match and not db_clones.count() > 0: + companion_layers = existing_match.connect_companion_layers_to.all() + attribute_fields = existing_match.attribute_fields.all() + lookup_table = existing_match.lookup_table.all() + new_layer = existing_match + new_layer.pk = None + new_layer.bookmark = None + new_layer.arcgis_layers=str(layer['id']) + + else: + try: + (new_layer, created) = Layer.all_objects.get_or_create(arcgis_layers=str(layer['id']),**all_service_dict) + if created: + new_layer.name = layer['name'] + new_layer.order = layer['id'] + except: + import ipdb; ipdb.set_trace() + + if new_layer: + if created: + for key in all_service_dict.keys(): + setattr(new_layer, key, all_service_dict[key]) + new_layer.save(recache=False) + new_layer.site.add(django_prod_site) + new_layer.site.add(django_stage_site) + new_layer.themes.add(parent_theme) + # new_layer.slug = "%s-v2-%s" % (new_layer.slug_name,server) + new_layer.sublayers.add(service_value_lookup[service]['parent_layer'][server]) + if current_layer and not current_layer.name == new_layer.name: + print("Name attribute did not copy from old to new layer. Investigate.") + import ipdb; ipdb.set_trace() + if companion_layers and not new_layer.connect_companion_layers_to.all() == companion_layers: + for companion_layer in companion_layers: + new_layer.connect_companion_layers_to.add(companion_layer) + if attribute_fields and not new_layer.attribute_fields.all() == attribute_fields: + for attribute_field in attribute_fields: + new_layer.attribute_fields.add(attribute_field) + if lookup_table and not new_layer.lookup_table.all() == lookup_table: + for lookup in lookup_table: + new_layer.lookup_table.add(lookup) + else: + for key in ['metadata']: + setattr(new_layer, key, all_service_dict[key]) + new_layer.save(recache=False,slug_name="%s-v2-%s" % (new_layer.slug,server)) + layers_saved += 1 + else: + layers_skipped += 1 + + service_value_lookup[service]['parent_layer'][server].save(recache=False) + print('created %d layers for V2 %s on %s server' % (layers_saved, service, server)) + if len(v2_layers) > layers_saved + layers_skipped: + missed_layers = len(layers) - layers_saved - layers_skipped + print('Missed %d layers for V2 %s on %s server' % (missed_layers, service, server)) + import ipdb; ipdb.set_trace() + + from django.core.cache import cache + cache.clear() diff --git a/data_manager/management/commands/mdat_update.py b/data_manager/management/commands/mdat_update.py index 1acf2b7..e698121 100644 --- a/data_manager/management/commands/mdat_update.py +++ b/data_manager/management/commands/mdat_update.py @@ -1,119 +1,117 @@ -from django.core.management.base import BaseCommand -from data_manager.models import Layer, Theme - -import requests - -class Command(BaseCommand): - help = "Run an update on MDAT layers" - - def handle(self, *args, **options): - #theme object for mdat synthetic products - 'conservation' - mdat = Theme.objects.all().filter(name='conservation')[0] - mdat_id = mdat.pk - - #allows initial endpoint url to be updated via a faux layer - mdat_rest_path = Layer.objects.all().filter(name='MDAT', layer_type="placeholder")[0].url - - #grab all parent service directories for enpoint - r = requests.get(mdat_rest_path+'MDAT?f=json') - - if r.status_code != 200: - return - #request status is OK - else: - print "**** Request 200 - is OK *****" - parent_json = r.json() - mdat_dirs = parent_json['services'] - - #loop through mdat service *parent* directory array - for directory in mdat_dirs: - print "***** Entering %s *****" % directory['name'] - #defaults for parent directories - parent_defaults = { - 'name':directory['name'], - 'layer_type':'checkbox', - } - - synthetic_list = [ - 'MDAT/AvianModels_SyntheticProducts', - 'MDAT/Fish_NEFSC_SyntheticProducts', - 'MDAT/Mammal_SyntheticProducts' - ] - - excluded_list = [ - 'Core Abundance Area - Northeast scale', - 'Core Abundance Area - Atlantic scale', - 'Diversity', - 'Core Biomass Area - Northeast Shelf scale', - 'Core Biomass Area - Northeast scale', - 'Breeding: Abundance', - 'Breeding: Species Richness', - 'Breeding: Core Abundance Area - Mid-Atlantic scale', - 'Nonbreeding: Abundance', - 'Nonbreeding: Species Richness', - 'Nonbreeding: Core Abundance Area - Mid-Atlantic scale', - 'Resident: Abundance', - 'Resident: Species Richness', - 'Resident: Core Abundance Area - Mid-Atlantic scale' - ] - - if directory['type'] != 'MapServer': - print "***** %s is not a MapServer Layer" % directory['name'] - return - #continue on if it's a MapServer layer && a synthetic product - elif directory['name'] in synthetic_list: - #does layer exist? - try: - obj = Layer.objects.get(themes=mdat, name=directory['name']) - #create parent layer/directory - if not - except Layer.DoesNotExist: - print "***** Adding %s *****" % directory['name'] - obj = Layer.objects.create(**parent_defaults) - obj.site = [1,2] - obj.themes = [mdat_id] - obj.save() - - #get pk for current layer - layer_id = obj.pk - - #set path - layer_path = mdat_rest_path+directory['name']+'/MapServer' - - #grab all layers of parent endpoint in the loop - blob = requests.get(layer_path+'?f=json') - layer_json = blob.json() - mdat_layers = layer_json['layers'] - layer_url = layer_path + '/export' - - #loop through layers within parent directory array - for layer in mdat_layers: - print "***** Looping through %s *****" % layer['name'] - layer_defaults = { - 'name':layer['name'], - 'layer_type':'ArcRest', - 'arcgis_layers':layer['id'], - 'is_sublayer': 1, - 'url':layer_url - } - #no aggregate layers or excluded layers - if layer['subLayerIds'] is None and not any(substring in layer['name'] for substring in excluded_list): - try: - lyr = Layer.objects.get(themes=mdat, arcgis_layers=layer['id'], url=layer_url) - #update name, just incase it changed - lyr.name = layer['name'] - lyr.save() - print "***** Layer %s exists *****" % layer['name'] - #create layers of parent directory - if they don't exist - except Layer.DoesNotExist: - print "***** Adding %s *****" % layer['name'] - lyr = Layer.objects.create(**layer_defaults) - lyr.site = [1,2] - lyr.themes = [mdat_id] - lyr.sublayers = [layer_id] - lyr.save() - - #sublayer fields need to be filled with pks for parent dir - obj.sublayers.add(lyr.pk) - obj.save() - - +from django.core.management.base import BaseCommand +from data_manager.models import Layer, Theme + +import requests + +class Command(BaseCommand): + help = "Run an update on MDAT layers" + + def handle(self, *args, **options): + #theme object for mdat synthetic products - 'conservation' + mdat = Theme.objects.all().filter(name='conservation')[0] + mdat_id = mdat.pk + + #allows initial endpoint url to be updated via a faux layer + mdat_rest_path = Layer.objects.all().filter(name='MDAT', layer_type="placeholder")[0].url + + #grab all parent service directories for enpoint + r = requests.get(mdat_rest_path+'MDAT?f=json') + + if r.status_code != 200: + return + #request status is OK + else: + print("**** Request 200 - is OK *****") + parent_json = r.json() + mdat_dirs = parent_json['services'] + + #loop through mdat service *parent* directory array + for directory in mdat_dirs: + print("***** Entering %s *****" % directory['name']) + #defaults for parent directories + parent_defaults = { + 'name':directory['name'], + 'layer_type':'checkbox', + } + + synthetic_list = [ + 'MDAT/AvianModels_SyntheticProducts', + 'MDAT/Fish_NEFSC_SyntheticProducts', + 'MDAT/Mammal_SyntheticProducts' + ] + + excluded_list = [ + 'Core Abundance Area - Northeast scale', + 'Core Abundance Area - Atlantic scale', + 'Diversity', + 'Core Biomass Area - Northeast Shelf scale', + 'Core Biomass Area - Northeast scale', + 'Breeding: Abundance', + 'Breeding: Species Richness', + 'Breeding: Core Abundance Area - Mid-Atlantic scale', + 'Nonbreeding: Abundance', + 'Nonbreeding: Species Richness', + 'Nonbreeding: Core Abundance Area - Mid-Atlantic scale', + 'Resident: Abundance', + 'Resident: Species Richness', + 'Resident: Core Abundance Area - Mid-Atlantic scale' + ] + + if directory['type'] != 'MapServer': + print("***** %s is not a MapServer Layer" % directory['name']) + return + #continue on if it's a MapServer layer && a synthetic product + elif directory['name'] in synthetic_list: + #does layer exist? + try: + obj = Layer.objects.get(themes=mdat, name=directory['name']) + #create parent layer/directory - if not + except Layer.DoesNotExist: + print("***** Adding %s *****" % directory['name']) + obj = Layer.objects.create(**parent_defaults) + obj.site = [1,2] + obj.themes = [mdat_id] + obj.save() + + #get pk for current layer + layer_id = obj.pk + + #set path + layer_path = mdat_rest_path+directory['name']+'/MapServer' + + #grab all layers of parent endpoint in the loop + blob = requests.get(layer_path+'?f=json') + layer_json = blob.json() + mdat_layers = layer_json['layers'] + layer_url = layer_path + '/export' + + #loop through layers within parent directory array + for layer in mdat_layers: + print("***** Looping through %s *****" % layer['name']) + layer_defaults = { + 'name':layer['name'], + 'layer_type':'ArcRest', + 'arcgis_layers':layer['id'], + 'is_sublayer': 1, + 'url':layer_url + } + #no aggregate layers or excluded layers + if layer['subLayerIds'] is None and not any(substring in layer['name'] for substring in excluded_list): + try: + lyr = Layer.objects.get(themes=mdat, arcgis_layers=layer['id'], url=layer_url) + #update name, just incase it changed + lyr.name = layer['name'] + lyr.save() + print("***** Layer %s exists *****" % layer['name']) + #create layers of parent directory - if they don't exist + except Layer.DoesNotExist: + print("***** Adding %s *****" % layer['name']) + lyr = Layer.objects.create(**layer_defaults) + lyr.site = [1,2] + lyr.themes = [mdat_id] + lyr.sublayers = [layer_id] + lyr.save() + + #sublayer fields need to be filled with pks for parent dir + obj.sublayers.add(lyr.pk) + obj.save() diff --git a/data_manager/migrations/0001_initial.py b/data_manager/migrations/0001_initial.py index 9b9bb12..7f51df5 100644 --- a/data_manager/migrations/0001_initial.py +++ b/data_manager/migrations/0001_initial.py @@ -1,150 +1,150 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ] - - operations = [ - migrations.CreateModel( - name='AttributeInfo', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('display_name', models.CharField(max_length=255, null=True, blank=True)), - ('field_name', models.CharField(max_length=255, null=True, blank=True)), - ('precision', models.IntegerField(null=True, blank=True)), - ('order', models.IntegerField(default=1)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='DataNeed', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('name', models.CharField(max_length=100)), - ('archived', models.BooleanField(default=False)), - ('description', models.TextField(null=True, blank=True)), - ('source', models.CharField(max_length=255, null=True, blank=True)), - ('status', models.TextField(null=True, blank=True)), - ('contact', models.CharField(max_length=255, null=True, blank=True)), - ('contact_email', models.CharField(max_length=255, null=True, blank=True)), - ('expected_date', models.CharField(max_length=255, null=True, blank=True)), - ('notes', models.TextField(null=True, blank=True)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='Layer', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('name', models.CharField(max_length=100)), - ('slug_name', models.CharField(max_length=100, null=True, blank=True)), - ('layer_type', models.CharField(help_text=b'use placeholder to temporarily remove layer from TOC', max_length=50, choices=[(b'XYZ', b'XYZ'), (b'WMS', b'WMS'), (b'ArcRest', b'ArcRest'), (b'radio', b'radio'), (b'checkbox', b'checkbox'), (b'Vector', b'Vector'), (b'placeholder', b'placeholder')])), - ('url', models.CharField(max_length=255, null=True, blank=True)), - ('shareable_url', models.BooleanField(default=True, help_text=b'Indicates whether the data layer (e.g. map tiles) can be shared with others (through the Map Tiles Link)')), - ('arcgis_layers', models.CharField(help_text=b'comma separated list of arcgis layer IDs', max_length=255, null=True, blank=True)), - ('is_sublayer', models.BooleanField(default=False)), - ('is_disabled', models.BooleanField(default=False, help_text=b'when disabled, the layer will still appear in the TOC, only disabled')), - ('disabled_message', models.CharField(max_length=255, null=True, blank=True)), - ('legend', models.CharField(help_text=b'URL or path to the legend image file', max_length=255, null=True, blank=True)), - ('legend_title', models.CharField(help_text=b'alternative to using the layer name', max_length=255, null=True, blank=True)), - ('legend_subtitle', models.CharField(max_length=255, null=True, blank=True)), - ('utfurl', models.CharField(max_length=255, null=True, blank=True)), - ('description', models.TextField(null=True, blank=True)), - ('data_overview', models.TextField(null=True, blank=True)), - ('data_source', models.CharField(max_length=255, null=True, blank=True)), - ('data_notes', models.TextField(null=True, blank=True)), - ('bookmark', models.CharField(help_text=b'link to view data layer in the planner', max_length=755, null=True, blank=True)), - ('kml', models.CharField(help_text=b'link to download the KML', max_length=255, null=True, blank=True)), - ('data_download', models.CharField(help_text=b'link to download the data', max_length=255, null=True, blank=True)), - ('learn_more', models.CharField(help_text=b'link to view description in the Learn section', max_length=255, null=True, blank=True)), - ('metadata', models.CharField(help_text=b'link to view/download the metadata', max_length=255, null=True, blank=True)), - ('source', models.CharField(help_text=b'link back to the data source', max_length=255, null=True, blank=True)), - ('map_tiles', models.CharField(help_text=b'internal link to a page that details how others might consume the data', max_length=255, null=True, blank=True)), - ('thumbnail', models.URLField(help_text=b'not sure we are using this any longer...', max_length=255, null=True, blank=True)), - ('compress_display', models.BooleanField(default=False)), - ('attribute_event', models.CharField(default=b'click', max_length=35, choices=[(b'click', b'click'), (b'mouseover', b'mouseover')])), - ('mouseover_field', models.CharField(help_text=b'feature level attribute used in mouseover display', max_length=75, null=True, blank=True)), - ('lookup_field', models.CharField(max_length=255, null=True, blank=True)), - ('is_annotated', models.BooleanField(default=False)), - ('vector_outline_color', models.CharField(max_length=7, null=True, blank=True)), - ('vector_outline_opacity', models.FloatField(null=True, blank=True)), - ('vector_color', models.CharField(max_length=7, null=True, blank=True)), - ('vector_fill', models.FloatField(null=True, blank=True)), - ('vector_graphic', models.CharField(max_length=255, null=True, blank=True)), - ('opacity', models.FloatField(default=0.5, null=True, blank=True)), - ('attribute_fields', models.ManyToManyField(to='data_manager.AttributeInfo', null=True, blank=True)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='LookupInfo', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('value', models.CharField(max_length=255, null=True, blank=True)), - ('color', models.CharField(max_length=7, null=True, blank=True)), - ('dashstyle', models.CharField(default=b'solid', max_length=11, choices=[(b'dot', b'dot'), (b'dash', b'dash'), (b'dashdot', b'dashdot'), (b'longdash', b'longdash'), (b'longdashdot', b'longdashdot'), (b'solid', b'solid')])), - ('fill', models.BooleanField(default=False)), - ('graphic', models.CharField(max_length=255, null=True, blank=True)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='Theme', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('display_name', models.CharField(max_length=100)), - ('name', models.CharField(max_length=100)), - ('visible', models.BooleanField(default=True)), - ('header_image', models.CharField(max_length=255, null=True, blank=True)), - ('header_attrib', models.CharField(max_length=255, null=True, blank=True)), - ('overview', models.TextField(null=True, blank=True)), - ('description', models.TextField(null=True, blank=True)), - ('thumbnail', models.URLField(max_length=255, null=True, blank=True)), - ('factsheet_thumb', models.CharField(max_length=255, null=True, blank=True)), - ('factsheet_link', models.CharField(max_length=255, null=True, blank=True)), - ('feature_image', models.CharField(max_length=255, null=True, blank=True)), - ('feature_excerpt', models.TextField(null=True, blank=True)), - ('feature_link', models.CharField(max_length=255, null=True, blank=True)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.AddField( - model_name='layer', - name='lookup_table', - field=models.ManyToManyField(to='data_manager.LookupInfo', null=True, blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='sublayers', - field=models.ManyToManyField(related_name='sublayers_rel_+', null=True, to='data_manager.Layer', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='themes', - field=models.ManyToManyField(to='data_manager.Theme', null=True, blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='dataneed', - name='themes', - field=models.ManyToManyField(to='data_manager.Theme', null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ] + + operations = [ + migrations.CreateModel( + name='AttributeInfo', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('display_name', models.CharField(max_length=255, null=True, blank=True)), + ('field_name', models.CharField(max_length=255, null=True, blank=True)), + ('precision', models.IntegerField(null=True, blank=True)), + ('order', models.IntegerField(default=1)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='DataNeed', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('name', models.CharField(max_length=100)), + ('archived', models.BooleanField(default=False)), + ('description', models.TextField(null=True, blank=True)), + ('source', models.CharField(max_length=255, null=True, blank=True)), + ('status', models.TextField(null=True, blank=True)), + ('contact', models.CharField(max_length=255, null=True, blank=True)), + ('contact_email', models.CharField(max_length=255, null=True, blank=True)), + ('expected_date', models.CharField(max_length=255, null=True, blank=True)), + ('notes', models.TextField(null=True, blank=True)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='Layer', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('name', models.CharField(max_length=100)), + ('slug_name', models.CharField(max_length=100, null=True, blank=True)), + ('layer_type', models.CharField(help_text='use placeholder to temporarily remove layer from TOC', max_length=50, choices=[('XYZ', 'XYZ'), ('WMS', 'WMS'), ('ArcRest', 'ArcRest'), ('radio', 'radio'), ('checkbox', 'checkbox'), ('Vector', 'Vector'), ('placeholder', 'placeholder')])), + ('url', models.CharField(max_length=255, null=True, blank=True)), + ('shareable_url', models.BooleanField(default=True, help_text='Indicates whether the data layer (e.g. map tiles) can be shared with others (through the Map Tiles Link)')), + ('arcgis_layers', models.CharField(help_text='comma separated list of arcgis layer IDs', max_length=255, null=True, blank=True)), + ('is_sublayer', models.BooleanField(default=False)), + ('is_disabled', models.BooleanField(default=False, help_text='when disabled, the layer will still appear in the TOC, only disabled')), + ('disabled_message', models.CharField(max_length=255, null=True, blank=True)), + ('legend', models.CharField(help_text='URL or path to the legend image file', max_length=255, null=True, blank=True)), + ('legend_title', models.CharField(help_text='alternative to using the layer name', max_length=255, null=True, blank=True)), + ('legend_subtitle', models.CharField(max_length=255, null=True, blank=True)), + ('utfurl', models.CharField(max_length=255, null=True, blank=True)), + ('description', models.TextField(null=True, blank=True)), + ('data_overview', models.TextField(null=True, blank=True)), + ('data_source', models.CharField(max_length=255, null=True, blank=True)), + ('data_notes', models.TextField(null=True, blank=True)), + ('bookmark', models.CharField(help_text='link to view data layer in the planner', max_length=755, null=True, blank=True)), + ('kml', models.CharField(help_text='link to download the KML', max_length=255, null=True, blank=True)), + ('data_download', models.CharField(help_text='link to download the data', max_length=255, null=True, blank=True)), + ('learn_more', models.CharField(help_text='link to view description in the Learn section', max_length=255, null=True, blank=True)), + ('metadata', models.CharField(help_text='link to view/download the metadata', max_length=255, null=True, blank=True)), + ('source', models.CharField(help_text='link back to the data source', max_length=255, null=True, blank=True)), + ('map_tiles', models.CharField(help_text='internal link to a page that details how others might consume the data', max_length=255, null=True, blank=True)), + ('thumbnail', models.URLField(help_text='not sure we are using this any longer...', max_length=255, null=True, blank=True)), + ('compress_display', models.BooleanField(default=False)), + ('attribute_event', models.CharField(default='click', max_length=35, choices=[('click', 'click'), ('mouseover', 'mouseover')])), + ('mouseover_field', models.CharField(help_text='feature level attribute used in mouseover display', max_length=75, null=True, blank=True)), + ('lookup_field', models.CharField(max_length=255, null=True, blank=True)), + ('is_annotated', models.BooleanField(default=False)), + ('vector_outline_color', models.CharField(max_length=7, null=True, blank=True)), + ('vector_outline_opacity', models.FloatField(null=True, blank=True)), + ('vector_color', models.CharField(max_length=7, null=True, blank=True)), + ('vector_fill', models.FloatField(null=True, blank=True)), + ('vector_graphic', models.CharField(max_length=255, null=True, blank=True)), + ('opacity', models.FloatField(default=0.5, null=True, blank=True)), + ('attribute_fields', models.ManyToManyField(to='data_manager.AttributeInfo', null=True, blank=True)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='LookupInfo', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('value', models.CharField(max_length=255, null=True, blank=True)), + ('color', models.CharField(max_length=7, null=True, blank=True)), + ('dashstyle', models.CharField(default='solid', max_length=11, choices=[('dot', 'dot'), ('dash', 'dash'), ('dashdot', 'dashdot'), ('longdash', 'longdash'), ('longdashdot', 'longdashdot'), ('solid', 'solid')])), + ('fill', models.BooleanField(default=False)), + ('graphic', models.CharField(max_length=255, null=True, blank=True)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='Theme', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('display_name', models.CharField(max_length=100)), + ('name', models.CharField(max_length=100)), + ('visible', models.BooleanField(default=True)), + ('header_image', models.CharField(max_length=255, null=True, blank=True)), + ('header_attrib', models.CharField(max_length=255, null=True, blank=True)), + ('overview', models.TextField(null=True, blank=True)), + ('description', models.TextField(null=True, blank=True)), + ('thumbnail', models.URLField(max_length=255, null=True, blank=True)), + ('factsheet_thumb', models.CharField(max_length=255, null=True, blank=True)), + ('factsheet_link', models.CharField(max_length=255, null=True, blank=True)), + ('feature_image', models.CharField(max_length=255, null=True, blank=True)), + ('feature_excerpt', models.TextField(null=True, blank=True)), + ('feature_link', models.CharField(max_length=255, null=True, blank=True)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.AddField( + model_name='layer', + name='lookup_table', + field=models.ManyToManyField(to='data_manager.LookupInfo', null=True, blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='sublayers', + field=models.ManyToManyField(related_name='sublayers_rel_+', null=True, to='data_manager.Layer', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='themes', + field=models.ManyToManyField(to='data_manager.Theme', null=True, blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='dataneed', + name='themes', + field=models.ManyToManyField(to='data_manager.Theme', null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0002_layer_point_radius.py b/data_manager/migrations/0002_layer_point_radius.py index 0f22dc4..667d9e4 100644 --- a/data_manager/migrations/0002_layer_point_radius.py +++ b/data_manager/migrations/0002_layer_point_radius.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0001_initial'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='point_radius', - field=models.IntegerField(help_text=b'Used only for for Point layers (default is 2)', null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0001_initial'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='point_radius', + field=models.IntegerField(help_text='Used only for for Point layers (default is 2)', null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0003_auto_20150709_2140.py b/data_manager/migrations/0003_auto_20150709_2140.py index 6ed11e9..38881df 100644 --- a/data_manager/migrations/0003_auto_20150709_2140.py +++ b/data_manager/migrations/0003_auto_20150709_2140.py @@ -1,86 +1,87 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - -def reverse_m2ms(apps, schema_editor): - # Do nothing, the M2M table will be destroyed - pass - -def add_default_m2m_relationships(apps, schema_editor): - """After the m2m fields to Site are created, add M2M from each existing - Layer and Theme to the "default" site (1). - """ - Site = apps.get_model('sites', 'Site') - Layer = apps.get_model('data_manager', 'Layer') - LayerSite = apps.get_model('data_manager', 'LayerSite') - Theme = apps.get_model('data_manager', 'Theme') - ThemeSite = apps.get_model('data_manager', 'ThemeSite') - - try: - site1 = Site.objects.get(id=1) - except Site.DoesNotExist: - site1 = Site(id=1, name='site one', domain='set-domain') - site1.save() - - for layer in Layer.objects.all(): - LayerSite.objects.create(layer=layer, site=site1) - - for theme in Theme.objects.all(): - ThemeSite.objects.create(theme=theme, site=site1) - - -class Migration(migrations.Migration): - - dependencies = [ - ('sites', '0001_initial'), - ('data_manager', '0002_layer_point_radius'), - ] - - operations = [ - migrations.CreateModel( - name='ThemeSite', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('site', models.ForeignKey(to='sites.Site')), - ('theme', models.ForeignKey(to='data_manager.Theme')), - ], - options={}, - bases=(models.Model,), - ), - migrations.AlterUniqueTogether( - name='themesite', - unique_together=set([('theme', 'site')]), - ), - migrations.AddField( - model_name='theme', - name='site', - field=models.ManyToManyField(to='sites.Site', through='data_manager.ThemeSite'), - preserve_default=True, - ), - - - - migrations.CreateModel( - name='LayerSite', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('site', models.ForeignKey(to='sites.Site')), - ('layer', models.ForeignKey(to='data_manager.Layer')), - ], - options={}, - bases=(models.Model,), - ), - migrations.AlterUniqueTogether( - name='layersite', - unique_together=set([('layer', 'site')]), - ), - migrations.AddField( - model_name='layer', - name='site', - field=models.ManyToManyField(to='sites.Site', through='data_manager.LayerSite'), - preserve_default=True, - ), - - migrations.RunPython(add_default_m2m_relationships, reverse_m2ms) - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations +import django.db.models.deletion + +def reverse_m2ms(apps, schema_editor): + # Do nothing, the M2M table will be destroyed + pass + +def add_default_m2m_relationships(apps, schema_editor): + """After the m2m fields to Site are created, add M2M from each existing + Layer and Theme to the "default" site (1). + """ + Site = apps.get_model('sites', 'Site') + Layer = apps.get_model('data_manager', 'Layer') + LayerSite = apps.get_model('data_manager', 'LayerSite') + Theme = apps.get_model('data_manager', 'Theme') + ThemeSite = apps.get_model('data_manager', 'ThemeSite') + + try: + site1 = Site.objects.get(id=1) + except Site.DoesNotExist: + site1 = Site(id=1, name='site one', domain='set-domain') + site1.save() + + for layer in Layer.objects.all(): + LayerSite.objects.create(layer=layer, site=site1) + + for theme in Theme.objects.all(): + ThemeSite.objects.create(theme=theme, site=site1) + + +class Migration(migrations.Migration): + + dependencies = [ + ('sites', '0001_initial'), + ('data_manager', '0002_layer_point_radius'), + ] + + operations = [ + migrations.CreateModel( + name='ThemeSite', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('site', models.ForeignKey(to='sites.Site', on_delete=django.db.models.deletion.CASCADE)), + ('theme', models.ForeignKey(to='data_manager.Theme', on_delete=django.db.models.deletion.CASCADE)), + ], + options={}, + bases=(models.Model,), + ), + migrations.AlterUniqueTogether( + name='themesite', + unique_together=set([('theme', 'site')]), + ), + migrations.AddField( + model_name='theme', + name='site', + field=models.ManyToManyField(to='sites.Site', through='data_manager.ThemeSite'), + preserve_default=True, + ), + + + + migrations.CreateModel( + name='LayerSite', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('site', models.ForeignKey(to='sites.Site', on_delete=django.db.models.deletion.CASCADE)), + ('layer', models.ForeignKey(to='data_manager.Layer', on_delete=django.db.models.deletion.CASCADE)), + ], + options={}, + bases=(models.Model,), + ), + migrations.AlterUniqueTogether( + name='layersite', + unique_together=set([('layer', 'site')]), + ), + migrations.AddField( + model_name='layer', + name='site', + field=models.ManyToManyField(to='sites.Site', through='data_manager.LayerSite'), + preserve_default=True, + ), + + migrations.RunPython(add_default_m2m_relationships, reverse_m2ms) + ] diff --git a/data_manager/migrations/0004_layer_wms_slug.py b/data_manager/migrations/0004_layer_wms_slug.py index a7a1906..7a5bba3 100644 --- a/data_manager/migrations/0004_layer_wms_slug.py +++ b/data_manager/migrations/0004_layer_wms_slug.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0003_auto_20150709_2140'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='wms_slug', - field=models.CharField(max_length=255, null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0003_auto_20150709_2140'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='wms_slug', + field=models.CharField(max_length=255, null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0005_layer_wms_version.py b/data_manager/migrations/0005_layer_wms_version.py index 4799071..cc9a0e5 100644 --- a/data_manager/migrations/0005_layer_wms_version.py +++ b/data_manager/migrations/0005_layer_wms_version.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0004_layer_wms_slug'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='wms_version', - field=models.CharField(help_text=b'WMS Versioning - usually either 1.1.1 or 1.3.0', max_length=10, null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0004_layer_wms_slug'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='wms_version', + field=models.CharField(help_text='WMS Versioning - usually either 1.1.1 or 1.3.0', max_length=10, null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0006_auto_20160304_0025.py b/data_manager/migrations/0006_auto_20160304_0025.py index 2d89a8c..3db3748 100644 --- a/data_manager/migrations/0006_auto_20160304_0025.py +++ b/data_manager/migrations/0006_auto_20160304_0025.py @@ -1,26 +1,26 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0005_layer_wms_version'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='order_num', - field=models.PositiveSmallIntegerField(default=10, null=True, blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='theme', - name='order_num', - field=models.PositiveSmallIntegerField(default=10, null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0005_layer_wms_version'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='order_num', + field=models.PositiveSmallIntegerField(default=10, null=True, blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='theme', + name='order_num', + field=models.PositiveSmallIntegerField(default=10, null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0007_auto_20160304_0057.py b/data_manager/migrations/0007_auto_20160304_0057.py index 28eaa84..ed6a0d6 100644 --- a/data_manager/migrations/0007_auto_20160304_0057.py +++ b/data_manager/migrations/0007_auto_20160304_0057.py @@ -1,34 +1,34 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0006_auto_20160304_0025'), - ] - - operations = [ - migrations.RemoveField( - model_name='layer', - name='order_num', - ), - migrations.RemoveField( - model_name='theme', - name='order_num', - ), - migrations.AddField( - model_name='layer', - name='order', - field=models.PositiveSmallIntegerField(default=10, help_text=b'input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True, blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='theme', - name='order', - field=models.PositiveSmallIntegerField(default=10, help_text=b'input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0006_auto_20160304_0025'), + ] + + operations = [ + migrations.RemoveField( + model_name='layer', + name='order_num', + ), + migrations.RemoveField( + model_name='theme', + name='order_num', + ), + migrations.AddField( + model_name='layer', + name='order', + field=models.PositiveSmallIntegerField(default=10, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True, blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='theme', + name='order', + field=models.PositiveSmallIntegerField(default=10, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0008_layer_search_query.py b/data_manager/migrations/0008_layer_search_query.py index b37b25d..03ff05c 100644 --- a/data_manager/migrations/0008_layer_search_query.py +++ b/data_manager/migrations/0008_layer_search_query.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0007_auto_20160304_0057'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='search_query', - field=models.BooleanField(default=False, help_text=b'Select when layers are queryable - e.g. MDAT and CAS'), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0007_auto_20160304_0057'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='search_query', + field=models.BooleanField(default=False, help_text='Select when layers are queryable - e.g. MDAT and CAS'), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0009_auto_20160919_2237.py b/data_manager/migrations/0009_auto_20160919_2237.py index d33bcda..34dc4e6 100644 --- a/data_manager/migrations/0009_auto_20160919_2237.py +++ b/data_manager/migrations/0009_auto_20160919_2237.py @@ -1,26 +1,26 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0008_layer_search_query'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='connect_companion_layers_to', - field=models.ManyToManyField(help_text=b'Select which main layer(s) you would like to use in conjuction with this companion layer.', related_name='connect_companion_layers_to_rel_+', null=True, to='data_manager.Layer', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='has_companion', - field=models.BooleanField(default=False, help_text=b'Check if this layer has a companion layer'), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0008_layer_search_query'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='connect_companion_layers_to', + field=models.ManyToManyField(help_text='Select which main layer(s) you would like to use in conjuction with this companion layer.', related_name='connect_companion_layers_to_rel_+', null=True, to='data_manager.Layer', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='has_companion', + field=models.BooleanField(default=False, help_text='Check if this layer has a companion layer'), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0010_layer_disable_arcgis_attributes.py b/data_manager/migrations/0010_layer_disable_arcgis_attributes.py index 222d183..9177ac7 100644 --- a/data_manager/migrations/0010_layer_disable_arcgis_attributes.py +++ b/data_manager/migrations/0010_layer_disable_arcgis_attributes.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0009_auto_20160919_2237'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='disable_arcgis_attributes', - field=models.BooleanField(default=False, help_text=b'Click to disable clickable ArcRest layers'), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0009_auto_20160919_2237'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='disable_arcgis_attributes', + field=models.BooleanField(default=False, help_text='Click to disable clickable ArcRest layers'), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0011_auto_20170723_2036.py b/data_manager/migrations/0011_auto_20170723_2036.py index 14bf944..dc4d471 100644 --- a/data_manager/migrations/0011_auto_20170723_2036.py +++ b/data_manager/migrations/0011_auto_20170723_2036.py @@ -1,32 +1,32 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0010_layer_disable_arcgis_attributes'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='espis_enabled', - field=models.BooleanField(default=False), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='espis_region', - field=models.CharField(blank=True, max_length=100, null=True, help_text=b'Region to search within', choices=[(b'Mid Atlantic', b'Mid Atlantic')]), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='espis_search', - field=models.CharField(help_text=b'keyphrase search for ESPIS Link', max_length=255, null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0010_layer_disable_arcgis_attributes'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='espis_enabled', + field=models.BooleanField(default=False), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='espis_region', + field=models.CharField(blank=True, max_length=100, null=True, help_text='Region to search within', choices=[('Mid Atlantic', 'Mid Atlantic')]), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='espis_search', + field=models.CharField(help_text='keyphrase search for ESPIS Link', max_length=255, null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0012_auto_20171116_2357.py b/data_manager/migrations/0012_auto_20171116_2357.py index ea814f2..396788a 100644 --- a/data_manager/migrations/0012_auto_20171116_2357.py +++ b/data_manager/migrations/0012_auto_20171116_2357.py @@ -1,80 +1,80 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0011_auto_20170723_2036'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='site_migrate', - field=models.CharField(max_length=255, null=True, blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_additional', - field=models.TextField(help_text=b'additional WMS key-value pairs: &key=value...', null=True, verbose_name=b'WMS Additional Fields', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_format', - field=models.CharField(help_text=b'most common: image/png. Only image types supported.', max_length=100, null=True, verbose_name=b'WMS Format', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_help', - field=models.BooleanField(default=False, help_text=b'Enable simple selection for WMS fields. Only supports WMS 1.1.1'), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_srs', - field=models.CharField(help_text=b'If not EPSG:3857 WMS requests will be proxied', max_length=100, null=True, verbose_name=b'WMS SRS', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_styles', - field=models.CharField(help_text=b'pre-determined styles, if exist', max_length=255, null=True, verbose_name=b'WMS Styles', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_time_item', - field=models.CharField(help_text=b'Time Attribute Field, if different from "TIME". Proxy only.', max_length=255, null=True, verbose_name=b'WMS Time Field', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='layer', - name='wms_timing', - field=models.CharField(help_text=b'http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', max_length=255, null=True, verbose_name=b'WMS Time', blank=True), - preserve_default=True, - ), - migrations.AddField( - model_name='theme', - name='site_migrate', - field=models.CharField(max_length=255, null=True, blank=True), - preserve_default=True, - ), - migrations.AlterField( - model_name='layer', - name='wms_slug', - field=models.CharField(max_length=255, null=True, verbose_name=b'WMS Layer Name', blank=True), - preserve_default=True, - ), - migrations.AlterField( - model_name='layer', - name='wms_version', - field=models.CharField(blank=True, max_length=10, null=True, help_text=b'WMS Versioning - usually either 1.1.1 or 1.3.0', choices=[(None, b''), (b'1.0.0', b'1.0.0'), (b'1.1.0', b'1.1.0'), (b'1.1.1', b'1.1.1'), (b'1.3.0', b'1.3.0')]), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0011_auto_20170723_2036'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='site_migrate', + field=models.CharField(max_length=255, null=True, blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_additional', + field=models.TextField(help_text='additional WMS key-value pairs: &key=value...', null=True, verbose_name='WMS Additional Fields', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_format', + field=models.CharField(help_text='most common: image/png. Only image types supported.', max_length=100, null=True, verbose_name='WMS Format', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_help', + field=models.BooleanField(default=False, help_text='Enable simple selection for WMS fields. Only supports WMS 1.1.1'), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_srs', + field=models.CharField(help_text='If not EPSG:3857 WMS requests will be proxied', max_length=100, null=True, verbose_name='WMS SRS', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_styles', + field=models.CharField(help_text='pre-determined styles, if exist', max_length=255, null=True, verbose_name='WMS Styles', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_time_item', + field=models.CharField(help_text='Time Attribute Field, if different from "TIME". Proxy only.', max_length=255, null=True, verbose_name='WMS Time Field', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='layer', + name='wms_timing', + field=models.CharField(help_text='http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', max_length=255, null=True, verbose_name='WMS Time', blank=True), + preserve_default=True, + ), + migrations.AddField( + model_name='theme', + name='site_migrate', + field=models.CharField(max_length=255, null=True, blank=True), + preserve_default=True, + ), + migrations.AlterField( + model_name='layer', + name='wms_slug', + field=models.CharField(max_length=255, null=True, verbose_name='WMS Layer Name', blank=True), + preserve_default=True, + ), + migrations.AlterField( + model_name='layer', + name='wms_version', + field=models.CharField(blank=True, max_length=10, null=True, help_text='WMS Versioning - usually either 1.1.1 or 1.3.0', choices=[(None, ''), ('1.0.0', '1.0.0'), ('1.1.0', '1.1.0'), ('1.1.1', '1.1.1'), ('1.3.0', '1.3.0')]), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0013_auto_20171116_2358.py b/data_manager/migrations/0013_auto_20171116_2358.py index 32d9405..d5338ae 100644 --- a/data_manager/migrations/0013_auto_20171116_2358.py +++ b/data_manager/migrations/0013_auto_20171116_2358.py @@ -1,38 +1,38 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - -def migrate_site_data(apps, schema_editor): - Layer = apps.get_model("data_manager", "Layer") - Theme = apps.get_model("data_manager", "Theme") - ThemeSite = apps.get_model("data_manager", "ThemeSite") - LayerSite = apps.get_model("data_manager", "LayerSite") - for layer_site in LayerSite.objects.all(): - layer = layer_site.layer - if not layer.site_migrate or len(layer.site_migrate) == 0: - layer_sites = [] - else: - layer_sites = eval(layer.site_migrate) - layer_sites.append(layer_site.site.pk) - layer.site_migrate = str(layer_sites) - layer.save() - for theme_site in ThemeSite.objects.all(): - theme = theme_site.theme - if not theme.site_migrate or len(theme.site_migrate) == 0: - theme_sites = [] - else: - theme_stires = eval(theme.site_migrate) - theme_sites.append(theme_site.site.pk) - theme.site_migrate = str(theme_sites) - theme.save() - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0012_auto_20171116_2357'), - ] - - operations = [ - migrations.RunPython(migrate_site_data), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + +def migrate_site_data(apps, schema_editor): + Layer = apps.get_model("data_manager", "Layer") + Theme = apps.get_model("data_manager", "Theme") + ThemeSite = apps.get_model("data_manager", "ThemeSite") + LayerSite = apps.get_model("data_manager", "LayerSite") + for layer_site in LayerSite.objects.all(): + layer = layer_site.layer + if not layer.site_migrate or len(layer.site_migrate) == 0: + layer_sites = [] + else: + layer_sites = eval(layer.site_migrate) + layer_sites.append(layer_site.site.pk) + layer.site_migrate = str(layer_sites) + layer.save() + for theme_site in ThemeSite.objects.all(): + theme = theme_site.theme + if not theme.site_migrate or len(theme.site_migrate) == 0: + theme_sites = [] + else: + theme_stires = eval(theme.site_migrate) + theme_sites.append(theme_site.site.pk) + theme.site_migrate = str(theme_sites) + theme.save() + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0012_auto_20171116_2357'), + ] + + operations = [ + migrations.RunPython(migrate_site_data), + ] diff --git a/data_manager/migrations/0014_auto_20171117_0014.py b/data_manager/migrations/0014_auto_20171117_0014.py index 0e5c2d5..8f1f642 100644 --- a/data_manager/migrations/0014_auto_20171117_0014.py +++ b/data_manager/migrations/0014_auto_20171117_0014.py @@ -1,52 +1,52 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0013_auto_20171116_2358'), - ] - - operations = [ - migrations.AlterUniqueTogether( - name='layersite', - unique_together=None, - ), - migrations.RemoveField( - model_name='layersite', - name='layer', - ), - migrations.RemoveField( - model_name='layersite', - name='site', - ), - migrations.AlterUniqueTogether( - name='themesite', - unique_together=None, - ), - migrations.RemoveField( - model_name='themesite', - name='site', - ), - migrations.RemoveField( - model_name='themesite', - name='theme', - ), - migrations.RemoveField( - model_name='layer', - name='site', - ), - migrations.DeleteModel( - name='LayerSite', - ), - migrations.RemoveField( - model_name='theme', - name='site', - ), - migrations.DeleteModel( - name='ThemeSite', - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0013_auto_20171116_2358'), + ] + + operations = [ + migrations.AlterUniqueTogether( + name='layersite', + unique_together=None, + ), + migrations.RemoveField( + model_name='layersite', + name='layer', + ), + migrations.RemoveField( + model_name='layersite', + name='site', + ), + migrations.AlterUniqueTogether( + name='themesite', + unique_together=None, + ), + migrations.RemoveField( + model_name='themesite', + name='site', + ), + migrations.RemoveField( + model_name='themesite', + name='theme', + ), + migrations.RemoveField( + model_name='layer', + name='site', + ), + migrations.DeleteModel( + name='LayerSite', + ), + migrations.RemoveField( + model_name='theme', + name='site', + ), + migrations.DeleteModel( + name='ThemeSite', + ), + ] diff --git a/data_manager/migrations/0015_auto_20171117_0015.py b/data_manager/migrations/0015_auto_20171117_0015.py index d210688..ec1f34b 100644 --- a/data_manager/migrations/0015_auto_20171117_0015.py +++ b/data_manager/migrations/0015_auto_20171117_0015.py @@ -1,27 +1,27 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('sites', '0001_initial'), - ('data_manager', '0014_auto_20171117_0014'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='site', - field=models.ManyToManyField(to='sites.Site'), - preserve_default=True, - ), - migrations.AddField( - model_name='theme', - name='site', - field=models.ManyToManyField(to='sites.Site'), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('sites', '0001_initial'), + ('data_manager', '0014_auto_20171117_0014'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='site', + field=models.ManyToManyField(to='sites.Site'), + preserve_default=True, + ), + migrations.AddField( + model_name='theme', + name='site', + field=models.ManyToManyField(to='sites.Site'), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0016_auto_20171117_0020.py b/data_manager/migrations/0016_auto_20171117_0020.py index 59e3176..2dd7156 100644 --- a/data_manager/migrations/0016_auto_20171117_0020.py +++ b/data_manager/migrations/0016_auto_20171117_0020.py @@ -1,31 +1,31 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - -def migrate_site_data2(apps, schema_editor): - Site = apps.get_model("sites", "Site") - Layer = apps.get_model("data_manager", "Layer") - Theme = apps.get_model("data_manager", "Theme") - for layer in Layer.objects.all(): - if layer.site_migrate: - layer_sites = eval(layer.site_migrate) - for site_pk in layer_sites: - layer.site.add(Site.objects.get(pk=site_pk)) - layer.save() - for theme in Theme.objects.all(): - if theme.site_migrate: - theme_sites = eval(theme.site_migrate) - for site_pk in theme_sites: - theme.site.add(Site.objects.get(pk=site_pk)) - theme.save() - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0015_auto_20171117_0015'), - ] - - operations = [ - migrations.RunPython(migrate_site_data2), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + +def migrate_site_data2(apps, schema_editor): + Site = apps.get_model("sites", "Site") + Layer = apps.get_model("data_manager", "Layer") + Theme = apps.get_model("data_manager", "Theme") + for layer in Layer.objects.all(): + if layer.site_migrate: + layer_sites = eval(layer.site_migrate) + for site_pk in layer_sites: + layer.site.add(Site.objects.get(pk=site_pk)) + layer.save() + for theme in Theme.objects.all(): + if theme.site_migrate: + theme_sites = eval(theme.site_migrate) + for site_pk in theme_sites: + theme.site.add(Site.objects.get(pk=site_pk)) + theme.save() + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0015_auto_20171117_0015'), + ] + + operations = [ + migrations.RunPython(migrate_site_data2), + ] diff --git a/data_manager/migrations/0017_auto_20171117_0041.py b/data_manager/migrations/0017_auto_20171117_0041.py index 855beaa..0a44d89 100644 --- a/data_manager/migrations/0017_auto_20171117_0041.py +++ b/data_manager/migrations/0017_auto_20171117_0041.py @@ -1,22 +1,22 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0016_auto_20171117_0020'), - ] - - operations = [ - migrations.RemoveField( - model_name='layer', - name='site_migrate', - ), - migrations.RemoveField( - model_name='theme', - name='site_migrate', - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0016_auto_20171117_0020'), + ] + + operations = [ + migrations.RemoveField( + model_name='layer', + name='site_migrate', + ), + migrations.RemoveField( + model_name='theme', + name='site_migrate', + ), + ] diff --git a/data_manager/migrations/0018_layer_data_publish_date.py b/data_manager/migrations/0018_layer_data_publish_date.py index 8d29566..fae7f61 100644 --- a/data_manager/migrations/0018_layer_data_publish_date.py +++ b/data_manager/migrations/0018_layer_data_publish_date.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0017_auto_20171117_0041'), - ] - - operations = [ - migrations.AddField( - model_name='layer', - name='data_publish_date', - field=models.DateField(default=None, null=True, verbose_name=b'Date created/published', blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0017_auto_20171117_0041'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='data_publish_date', + field=models.DateField(default=None, null=True, verbose_name='Date created/published', blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0019_auto_20171120_2310.py b/data_manager/migrations/0019_auto_20171120_2310.py index f1a6e61..12dd58f 100644 --- a/data_manager/migrations/0019_auto_20171120_2310.py +++ b/data_manager/migrations/0019_auto_20171120_2310.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0018_layer_data_publish_date'), - ] - - operations = [ - migrations.AlterField( - model_name='layer', - name='data_publish_date', - field=models.DateField(default=None, help_text=b'YYYY-MM-DD', null=True, verbose_name=b'Date published', blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0018_layer_data_publish_date'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='data_publish_date', + field=models.DateField(default=None, help_text='YYYY-MM-DD', null=True, verbose_name='Date published', blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0020_auto_20180808_2254.py b/data_manager/migrations/0020_auto_20180808_2254.py index f2d6c14..e804da2 100644 --- a/data_manager/migrations/0020_auto_20180808_2254.py +++ b/data_manager/migrations/0020_auto_20180808_2254.py @@ -1,20 +1,20 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0019_auto_20171120_2310'), - ] - - operations = [ - migrations.AlterField( - model_name='layer', - name='slug_name', - field=models.CharField(max_length=200, null=True, blank=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0019_auto_20171120_2310'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='slug_name', + field=models.CharField(max_length=200, null=True, blank=True), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0020_auto_20180808_2254.pyc b/data_manager/migrations/0020_auto_20180808_2254.pyc deleted file mode 100644 index f41b62b..0000000 Binary files a/data_manager/migrations/0020_auto_20180808_2254.pyc and /dev/null differ diff --git a/data_manager/migrations/0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue.py b/data_manager/migrations/0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue.py index 153dedd..6447408 100644 --- a/data_manager/migrations/0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue.py +++ b/data_manager/migrations/0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue.py @@ -1,55 +1,56 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0019_auto_20171120_2310'), - ] - - operations = [ - migrations.CreateModel( - name='MultilayerAssociation', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('name', models.CharField(max_length=200)), - ('layer', models.ForeignKey(default=None, blank=True, to='data_manager.Layer', null=True)), - ], - options={ - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='MultilayerDimension', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('name', models.CharField(help_text=b'name to be used for selection in admin tool forms', max_length=200)), - ('label', models.CharField(help_text=b'label to be used in mapping tool slider', max_length=50)), - ('order', models.IntegerField(default=100, help_text=b'the order in which this dimension will be presented among other dimensions on this layer')), - ('animated', models.BooleanField(default=False, help_text=b'enable auto-toggling of layers across this dimension')), - ('layer', models.ForeignKey(to='data_manager.Layer')), - ], - options={ - 'ordering': ('order',), - }, - bases=(models.Model,), - ), - migrations.CreateModel( - name='MultilayerDimensionValue', - fields=[ - ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), - ('value', models.CharField(help_text=b'Actual value of selection', max_length=200)), - ('label', models.CharField(help_text=b'Label for this selection seen in mapping tool slider', max_length=50)), - ('order', models.IntegerField(default=100)), - ('associations', models.ManyToManyField(to='data_manager.MultilayerAssociation')), - ('dimension', models.ForeignKey(to='data_manager.MultilayerDimension')), - ], - options={ - 'ordering': ('order',), - }, - bases=(models.Model,), - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations +import django.db.models.deletion + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0019_auto_20171120_2310'), + ] + + operations = [ + migrations.CreateModel( + name='MultilayerAssociation', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('name', models.CharField(max_length=200)), + ('layer', models.ForeignKey(default=None, blank=True, to='data_manager.Layer', null=True, on_delete=django.db.models.deletion.SET_NULL)), + ], + options={ + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='MultilayerDimension', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('name', models.CharField(help_text='name to be used for selection in admin tool forms', max_length=200)), + ('label', models.CharField(help_text='label to be used in mapping tool slider', max_length=50)), + ('order', models.IntegerField(default=100, help_text='the order in which this dimension will be presented among other dimensions on this layer')), + ('animated', models.BooleanField(default=False, help_text='enable auto-toggling of layers across this dimension')), + ('layer', models.ForeignKey(to='data_manager.Layer', on_delete=django.db.models.deletion.CASCADE)), + ], + options={ + 'ordering': ('order',), + }, + bases=(models.Model,), + ), + migrations.CreateModel( + name='MultilayerDimensionValue', + fields=[ + ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), + ('value', models.CharField(help_text='Actual value of selection', max_length=200)), + ('label', models.CharField(help_text='Label for this selection seen in mapping tool slider', max_length=50)), + ('order', models.IntegerField(default=100)), + ('associations', models.ManyToManyField(to='data_manager.MultilayerAssociation')), + ('dimension', models.ForeignKey(to='data_manager.MultilayerDimension', on_delete=django.db.models.deletion.CASCADE)), + ], + options={ + 'ordering': ('order',), + }, + bases=(models.Model,), + ), + ] diff --git a/data_manager/migrations/0022_auto_20180501_2245.py b/data_manager/migrations/0022_auto_20180501_2245.py index fa6a123..ea88fe3 100644 --- a/data_manager/migrations/0022_auto_20180501_2245.py +++ b/data_manager/migrations/0022_auto_20180501_2245.py @@ -1,26 +1,27 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue'), - ] - - operations = [ - migrations.AddField( - model_name='multilayerassociation', - name='parentLayer', - field=models.ForeignKey(related_name='parent_layer', db_column=b'parentlayer', default=1, to='data_manager.Layer'), - preserve_default=False, - ), - migrations.AlterField( - model_name='multilayerassociation', - name='layer', - field=models.ForeignKey(related_name='associated_layer', db_column=b'associatedlayer', default=None, blank=True, to='data_manager.Layer', null=True), - preserve_default=True, - ), - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations +import django.db.models.deletion + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0021_multilayerassociation_multilayerdimension_multilayerdimensionvalue'), + ] + + operations = [ + migrations.AddField( + model_name='multilayerassociation', + name='parentLayer', + field=models.ForeignKey(related_name='parent_layer', db_column='parentlayer', default=1, to='data_manager.Layer', on_delete=django.db.models.deletion.SET_DEFAULT), + preserve_default=False, + ), + migrations.AlterField( + model_name='multilayerassociation', + name='layer', + field=models.ForeignKey(related_name='associated_layer', db_column='associatedlayer', default=None, blank=True, to='data_manager.Layer', null=True, on_delete=django.db.models.deletion.SET_NULL), + preserve_default=True, + ), + ] diff --git a/data_manager/migrations/0023_merge.py b/data_manager/migrations/0023_merge.py index b1ad267..fc2807c 100644 --- a/data_manager/migrations/0023_merge.py +++ b/data_manager/migrations/0023_merge.py @@ -1,15 +1,15 @@ -# -*- coding: utf-8 -*- -from __future__ import unicode_literals - -from django.db import models, migrations - - -class Migration(migrations.Migration): - - dependencies = [ - ('data_manager', '0022_auto_20180501_2245'), - ('data_manager', '0020_auto_20180808_2254'), - ] - - operations = [ - ] +# -*- coding: utf-8 -*- +from __future__ import unicode_literals + +from django.db import models, migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0022_auto_20180501_2245'), + ('data_manager', '0020_auto_20180808_2254'), + ] + + operations = [ + ] diff --git a/data_manager/migrations/0024_auto_20190710_0058.py b/data_manager/migrations/0024_auto_20190710_0058.py new file mode 100644 index 0000000..32c6503 --- /dev/null +++ b/data_manager/migrations/0024_auto_20190710_0058.py @@ -0,0 +1,247 @@ +# Generated by Django 2.2.3 on 2019-07-10 00:58 + +import django.contrib.sites.managers +from django.db import migrations, models +import django.db.models.deletion + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0023_merge'), + ] + + operations = [ + migrations.AlterModelManagers( + name='layer', + managers=[ + ('objects', django.contrib.sites.managers.CurrentSiteManager('site')), + ], + ), + migrations.AlterModelManagers( + name='theme', + managers=[ + ('objects', django.contrib.sites.managers.CurrentSiteManager('site')), + ], + ), + migrations.AlterField( + model_name='layer', + name='arcgis_layers', + field=models.CharField(blank=True, help_text='comma separated list of arcgis layer IDs', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='attribute_event', + field=models.CharField(choices=[('click', 'click'), ('mouseover', 'mouseover')], default='click', max_length=35), + ), + migrations.AlterField( + model_name='layer', + name='bookmark', + field=models.CharField(blank=True, help_text='link to view data layer in the planner', max_length=755, null=True), + ), + migrations.AlterField( + model_name='layer', + name='connect_companion_layers_to', + field=models.ManyToManyField(blank=True, help_text='Select which main layer(s) you would like to use in conjuction with this companion layer.', null=True, related_name='_layer_connect_companion_layers_to_+', to='data_manager.Layer'), + ), + migrations.AlterField( + model_name='layer', + name='data_download', + field=models.CharField(blank=True, help_text='link to download the data', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='data_publish_date', + field=models.DateField(blank=True, default=None, help_text='YYYY-MM-DD', null=True, verbose_name='Date published'), + ), + migrations.AlterField( + model_name='layer', + name='disable_arcgis_attributes', + field=models.BooleanField(default=False, help_text='Click to disable clickable ArcRest layers'), + ), + migrations.AlterField( + model_name='layer', + name='espis_region', + field=models.CharField(blank=True, choices=[('Mid Atlantic', 'Mid Atlantic')], help_text='Region to search within', max_length=100, null=True), + ), + migrations.AlterField( + model_name='layer', + name='espis_search', + field=models.CharField(blank=True, help_text='keyphrase search for ESPIS Link', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='has_companion', + field=models.BooleanField(default=False, help_text='Check if this layer has a companion layer'), + ), + migrations.AlterField( + model_name='layer', + name='is_disabled', + field=models.BooleanField(default=False, help_text='when disabled, the layer will still appear in the TOC, only disabled'), + ), + migrations.AlterField( + model_name='layer', + name='kml', + field=models.CharField(blank=True, help_text='link to download the KML', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='layer_type', + field=models.CharField(choices=[('XYZ', 'XYZ'), ('WMS', 'WMS'), ('ArcRest', 'ArcRest'), ('radio', 'radio'), ('checkbox', 'checkbox'), ('Vector', 'Vector'), ('placeholder', 'placeholder')], help_text='use placeholder to temporarily remove layer from TOC', max_length=50), + ), + migrations.AlterField( + model_name='layer', + name='learn_more', + field=models.CharField(blank=True, help_text='link to view description in the Learn section', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='legend', + field=models.CharField(blank=True, help_text='URL or path to the legend image file', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='legend_title', + field=models.CharField(blank=True, help_text='alternative to using the layer name', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='map_tiles', + field=models.CharField(blank=True, help_text='internal link to a page that details how others might consume the data', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='metadata', + field=models.CharField(blank=True, help_text='link to view/download the metadata', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='mouseover_field', + field=models.CharField(blank=True, help_text='feature level attribute used in mouseover display', max_length=75, null=True), + ), + migrations.AlterField( + model_name='layer', + name='order', + field=models.PositiveSmallIntegerField(blank=True, default=10, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True), + ), + migrations.AlterField( + model_name='layer', + name='point_radius', + field=models.IntegerField(blank=True, help_text='Used only for for Point layers (default is 2)', null=True), + ), + migrations.AlterField( + model_name='layer', + name='search_query', + field=models.BooleanField(default=False, help_text='Select when layers are queryable - e.g. MDAT and CAS'), + ), + migrations.AlterField( + model_name='layer', + name='shareable_url', + field=models.BooleanField(default=True, help_text='Indicates whether the data layer (e.g. map tiles) can be shared with others (through the Map Tiles Link)'), + ), + migrations.AlterField( + model_name='layer', + name='source', + field=models.CharField(blank=True, help_text='link back to the data source', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='thumbnail', + field=models.URLField(blank=True, help_text='not sure we are using this any longer...', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='wms_additional', + field=models.TextField(blank=True, help_text='additional WMS key-value pairs: &key=value...', null=True, verbose_name='WMS Additional Fields'), + ), + migrations.AlterField( + model_name='layer', + name='wms_format', + field=models.CharField(blank=True, help_text='most common: image/png. Only image types supported.', max_length=100, null=True, verbose_name='WMS Format'), + ), + migrations.AlterField( + model_name='layer', + name='wms_help', + field=models.BooleanField(default=False, help_text='Enable simple selection for WMS fields. Only supports WMS 1.1.1'), + ), + migrations.AlterField( + model_name='layer', + name='wms_slug', + field=models.CharField(blank=True, max_length=255, null=True, verbose_name='WMS Layer Name'), + ), + migrations.AlterField( + model_name='layer', + name='wms_srs', + field=models.CharField(blank=True, help_text='If not EPSG:3857 WMS requests will be proxied', max_length=100, null=True, verbose_name='WMS SRS'), + ), + migrations.AlterField( + model_name='layer', + name='wms_styles', + field=models.CharField(blank=True, help_text='pre-determined styles, if exist', max_length=255, null=True, verbose_name='WMS Styles'), + ), + migrations.AlterField( + model_name='layer', + name='wms_time_item', + field=models.CharField(blank=True, help_text='Time Attribute Field, if different from "TIME". Proxy only.', max_length=255, null=True, verbose_name='WMS Time Field'), + ), + migrations.AlterField( + model_name='layer', + name='wms_timing', + field=models.CharField(blank=True, help_text='http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', max_length=255, null=True, verbose_name='WMS Time'), + ), + migrations.AlterField( + model_name='layer', + name='wms_version', + field=models.CharField(blank=True, choices=[(None, ''), ('1.0.0', '1.0.0'), ('1.1.0', '1.1.0'), ('1.1.1', '1.1.1'), ('1.3.0', '1.3.0')], help_text='WMS Versioning - usually either 1.1.1 or 1.3.0', max_length=10, null=True), + ), + migrations.AlterField( + model_name='lookupinfo', + name='dashstyle', + field=models.CharField(choices=[('dot', 'dot'), ('dash', 'dash'), ('dashdot', 'dashdot'), ('longdash', 'longdash'), ('longdashdot', 'longdashdot'), ('solid', 'solid')], default='solid', max_length=11), + ), + migrations.AlterField( + model_name='multilayerassociation', + name='layer', + field=models.ForeignKey(blank=True, db_column='associatedlayer', default=None, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='associated_layer', to='data_manager.Layer'), + ), + migrations.AlterField( + model_name='multilayerassociation', + name='parentLayer', + field=models.ForeignKey(db_column='parentlayer', on_delete=django.db.models.deletion.CASCADE, related_name='parent_layer', to='data_manager.Layer'), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='animated', + field=models.BooleanField(default=False, help_text='enable auto-toggling of layers across this dimension'), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='label', + field=models.CharField(help_text='label to be used in mapping tool slider', max_length=50), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='name', + field=models.CharField(help_text='name to be used for selection in admin tool forms', max_length=200), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='order', + field=models.IntegerField(default=100, help_text='the order in which this dimension will be presented among other dimensions on this layer'), + ), + migrations.AlterField( + model_name='multilayerdimensionvalue', + name='label', + field=models.CharField(help_text='Label for this selection seen in mapping tool slider', max_length=50), + ), + migrations.AlterField( + model_name='multilayerdimensionvalue', + name='value', + field=models.CharField(help_text='Actual value of selection', max_length=200), + ), + migrations.AlterField( + model_name='theme', + name='order', + field=models.PositiveSmallIntegerField(blank=True, default=10, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)', null=True), + ), + ] diff --git a/data_manager/migrations/0025_auto_20190710_2305.py b/data_manager/migrations/0025_auto_20190710_2305.py new file mode 100644 index 0000000..fdaf9c4 --- /dev/null +++ b/data_manager/migrations/0025_auto_20190710_2305.py @@ -0,0 +1,43 @@ +# Generated by Django 2.2.3 on 2019-07-10 23:05 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0024_auto_20190710_0058'), + ] + + operations = [ + migrations.AlterField( + model_name='dataneed', + name='themes', + field=models.ManyToManyField(blank=True, to='data_manager.Theme'), + ), + migrations.AlterField( + model_name='layer', + name='attribute_fields', + field=models.ManyToManyField(blank=True, to='data_manager.AttributeInfo'), + ), + migrations.AlterField( + model_name='layer', + name='connect_companion_layers_to', + field=models.ManyToManyField(blank=True, help_text='Select which main layer(s) you would like to use in conjuction with this companion layer.', related_name='_layer_connect_companion_layers_to_+', to='data_manager.Layer'), + ), + migrations.AlterField( + model_name='layer', + name='lookup_table', + field=models.ManyToManyField(blank=True, to='data_manager.LookupInfo'), + ), + migrations.AlterField( + model_name='layer', + name='sublayers', + field=models.ManyToManyField(blank=True, related_name='_layer_sublayers_+', to='data_manager.Layer'), + ), + migrations.AlterField( + model_name='layer', + name='themes', + field=models.ManyToManyField(blank=True, to='data_manager.Theme'), + ), + ] diff --git a/data_manager/migrations/0026_auto_20190725_2149.py b/data_manager/migrations/0026_auto_20190725_2149.py new file mode 100644 index 0000000..86aca90 --- /dev/null +++ b/data_manager/migrations/0026_auto_20190725_2149.py @@ -0,0 +1,23 @@ +# Generated by Django 2.2.3 on 2019-07-25 21:49 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0025_auto_20190710_2305'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='wms_info', + field=models.BooleanField(default=False, help_text='enable Feature Info requests on click'), + ), + migrations.AddField( + model_name='layer', + name='wms_info_format', + field=models.CharField(blank=True, default=None, help_text='Available supported feature info formats', max_length=255, null=True), + ), + ] diff --git a/data_manager/migrations/0027_auto_20190730_0022.py b/data_manager/migrations/0027_auto_20190730_0022.py new file mode 100644 index 0000000..adf33af --- /dev/null +++ b/data_manager/migrations/0027_auto_20190730_0022.py @@ -0,0 +1,118 @@ +# Generated by Django 2.2.3 on 2019-07-30 00:22 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0026_auto_20190725_2149'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='filterable', + field=models.BooleanField(default=False), + ), + migrations.AddField( + model_name='layer', + name='geoportal_id', + field=models.CharField(blank=True, default=None, help_text='GeoPortal UUID', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='disabled_message', + field=models.CharField(blank=True, default=None, max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='espis_region', + field=models.CharField(blank=True, choices=[('Mid Atlantic', 'Mid Atlantic')], default=True, help_text='Region to search within', max_length=100, null=True), + ), + migrations.AlterField( + model_name='layer', + name='espis_search', + field=models.CharField(blank=True, default=True, help_text='keyphrase search for ESPIS Link', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='learn_more', + field=models.CharField(blank=True, default=None, help_text='link to view description in the Learn section', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='mouseover_field', + field=models.CharField(blank=True, default=True, help_text='feature level attribute used in mouseover display', max_length=75, null=True), + ), + migrations.AlterField( + model_name='layer', + name='point_radius', + field=models.IntegerField(blank=True, default=True, help_text='Used only for for Point layers (default is 2)', null=True), + ), + migrations.AlterField( + model_name='layer', + name='thumbnail', + field=models.URLField(blank=True, default=None, help_text='not sure we are using this any longer...', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_color', + field=models.CharField(blank=True, default=True, max_length=7, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_fill', + field=models.FloatField(blank=True, default=True, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_graphic', + field=models.CharField(blank=True, default=True, max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=models.CharField(blank=True, default=True, max_length=7, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_opacity', + field=models.FloatField(blank=True, default=True, null=True), + ), + migrations.AlterField( + model_name='layer', + name='wms_additional', + field=models.TextField(blank=True, default=None, help_text='additional WMS key-value pairs: &key=value...', null=True, verbose_name='WMS Additional Fields'), + ), + migrations.AlterField( + model_name='layer', + name='wms_format', + field=models.CharField(blank=True, default=None, help_text='most common: image/png. Only image types supported.', max_length=100, null=True, verbose_name='WMS Format'), + ), + migrations.AlterField( + model_name='layer', + name='wms_srs', + field=models.CharField(blank=True, default=None, help_text='If not EPSG:3857 WMS requests will be proxied', max_length=100, null=True, verbose_name='WMS SRS'), + ), + migrations.AlterField( + model_name='layer', + name='wms_styles', + field=models.CharField(blank=True, default=None, help_text='pre-determined styles, if exist', max_length=255, null=True, verbose_name='WMS Styles'), + ), + migrations.AlterField( + model_name='layer', + name='wms_time_item', + field=models.CharField(blank=True, default=None, help_text='Time Attribute Field, if different from "TIME". Proxy only.', max_length=255, null=True, verbose_name='WMS Time Field'), + ), + migrations.AlterField( + model_name='layer', + name='wms_timing', + field=models.CharField(blank=True, default=None, help_text='http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', max_length=255, null=True, verbose_name='WMS Time'), + ), + migrations.AlterField( + model_name='layer', + name='wms_version', + field=models.CharField(blank=True, choices=[(None, ''), ('1.0.0', '1.0.0'), ('1.1.0', '1.1.0'), ('1.1.1', '1.1.1'), ('1.3.0', '1.3.0')], default=None, help_text='WMS Versioning - usually either 1.1.1 or 1.3.0', max_length=10, null=True), + ), + ] diff --git a/data_manager/migrations/0028_auto_20191106_0005.py b/data_manager/migrations/0028_auto_20191106_0005.py new file mode 100644 index 0000000..06036b4 --- /dev/null +++ b/data_manager/migrations/0028_auto_20191106_0005.py @@ -0,0 +1,63 @@ +# Generated by Django 2.2.3 on 2019-11-06 00:05 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0027_auto_20190730_0022'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='espis_region', + field=models.CharField(blank=True, choices=[('Mid Atlantic', 'Mid Atlantic')], default=None, help_text='Region to search within', max_length=100, null=True), + ), + migrations.AlterField( + model_name='layer', + name='espis_search', + field=models.CharField(blank=True, default=None, help_text='keyphrase search for ESPIS Link', max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='layer_type', + field=models.CharField(choices=[('XYZ', 'XYZ'), ('WMS', 'WMS'), ('ArcRest', 'ArcRest'), ('radio', 'radio'), ('checkbox', 'checkbox'), ('Vector', 'Vector'), ('VectorTile', 'VectorTile'), ('placeholder', 'placeholder')], help_text='use placeholder to temporarily remove layer from TOC', max_length=50), + ), + migrations.AlterField( + model_name='layer', + name='mouseover_field', + field=models.CharField(blank=True, default=None, help_text='feature level attribute used in mouseover display', max_length=75, null=True), + ), + migrations.AlterField( + model_name='layer', + name='point_radius', + field=models.IntegerField(blank=True, default=None, help_text='Used only for for Point layers (default is 2)', null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_color', + field=models.CharField(blank=True, default=None, max_length=7, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_fill', + field=models.FloatField(blank=True, default=None, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_graphic', + field=models.CharField(blank=True, default=None, max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=models.CharField(blank=True, default=None, max_length=7, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_opacity', + field=models.FloatField(blank=True, default=None, null=True), + ), + ] diff --git a/data_manager/migrations/0029_auto_20191107_0132.py b/data_manager/migrations/0029_auto_20191107_0132.py new file mode 100644 index 0000000..feb7b74 --- /dev/null +++ b/data_manager/migrations/0029_auto_20191107_0132.py @@ -0,0 +1,33 @@ +# Generated by Django 2.2.3 on 2019-11-07 01:32 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0028_auto_20191106_0005'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='opacity', + field=models.FloatField(blank=True, default=0.5, null=True, verbose_name='Initial Opacity'), + ), + migrations.AlterField( + model_name='layer', + name='vector_color', + field=models.CharField(blank=True, default=None, max_length=100, null=True), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=models.CharField(blank=True, default=None, max_length=100, null=True, verbose_name='Vector Stroke Color'), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_opacity', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Vector Stroke Width'), + ), + ] diff --git a/data_manager/migrations/0030_auto_20191107_1900.py b/data_manager/migrations/0030_auto_20191107_1900.py new file mode 100644 index 0000000..cda0525 --- /dev/null +++ b/data_manager/migrations/0030_auto_20191107_1900.py @@ -0,0 +1,43 @@ +# Generated by Django 2.2.3 on 2019-11-07 19:00 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0029_auto_20191107_0132'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='vector_graphic_scale', + field=models.FloatField(blank=True, default=True, help_text='Scale for the vector graphic from original size.', null=True, verbose_name='Vector Graphic Scale'), + ), + migrations.AddField( + model_name='layer', + name='vector_outline_width', + field=models.IntegerField(blank=True, default=None, null=True, verbose_name='Vector Stroke Width'), + ), + migrations.AlterField( + model_name='layer', + name='vector_color', + field=models.CharField(blank=True, default=None, max_length=100, null=True, verbose_name='Vector Fill Color'), + ), + migrations.AlterField( + model_name='layer', + name='vector_fill', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Vector Fill Opacity'), + ), + migrations.AlterField( + model_name='layer', + name='vector_graphic', + field=models.CharField(blank=True, default=None, help_text='address of image to use for point data', max_length=255, null=True, verbose_name='Vector Graphic'), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_opacity', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Vector Stroke Opacity'), + ), + ] diff --git a/data_manager/migrations/0031_lookupinfo_graphic_scale.py b/data_manager/migrations/0031_lookupinfo_graphic_scale.py new file mode 100644 index 0000000..1c04ce8 --- /dev/null +++ b/data_manager/migrations/0031_lookupinfo_graphic_scale.py @@ -0,0 +1,18 @@ +# Generated by Django 2.2.3 on 2019-11-07 19:10 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0030_auto_20191107_1900'), + ] + + operations = [ + migrations.AddField( + model_name='lookupinfo', + name='graphic_scale', + field=models.FloatField(blank=True, default=None, help_text='Scale the graphic from its original size.', null=True, verbose_name='Graphic Scale'), + ), + ] diff --git a/data_manager/migrations/0032_auto_20191113_0013.py b/data_manager/migrations/0032_auto_20191113_0013.py new file mode 100644 index 0000000..ccd62a0 --- /dev/null +++ b/data_manager/migrations/0032_auto_20191113_0013.py @@ -0,0 +1,28 @@ +# Generated by Django 2.2.7 on 2019-11-13 00:13 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0031_lookupinfo_graphic_scale'), + ] + + operations = [ + migrations.AddField( + model_name='lookupinfo', + name='stroke_color', + field=models.CharField(blank=True, max_length=50, null=True, verbose_name='Stroke Color'), + ), + migrations.AddField( + model_name='lookupinfo', + name='stroke_width', + field=models.IntegerField(blank=True, default=None, null=True, verbose_name='Stroke Width'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='color', + field=models.CharField(blank=True, max_length=50, null=True, verbose_name='Fill Color'), + ), + ] diff --git a/data_manager/migrations/0033_layer_show_legend.py b/data_manager/migrations/0033_layer_show_legend.py new file mode 100644 index 0000000..8415e7f --- /dev/null +++ b/data_manager/migrations/0033_layer_show_legend.py @@ -0,0 +1,18 @@ +# Generated by Django 2.2.7 on 2019-11-18 18:22 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0032_auto_20191113_0013'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='show_legend', + field=models.BooleanField(default=True, help_text='show the legend for this layer if available'), + ), + ] diff --git a/data_manager/migrations/0034_layer_catalog_id.py b/data_manager/migrations/0034_layer_catalog_id.py new file mode 100644 index 0000000..fe24626 --- /dev/null +++ b/data_manager/migrations/0034_layer_catalog_id.py @@ -0,0 +1,18 @@ +# Generated by Django 2.2.9 on 2020-09-09 18:34 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0033_layer_show_legend'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='catalog_id', + field=models.TextField(blank=True, help_text='unique ID of associated record in catalog', null=True), + ), + ] diff --git a/data_manager/migrations/0034_layer_label_field.py b/data_manager/migrations/0034_layer_label_field.py new file mode 100644 index 0000000..918ddd6 --- /dev/null +++ b/data_manager/migrations/0034_layer_label_field.py @@ -0,0 +1,18 @@ +# Generated by Django 2.2.12 on 2021-02-05 22:22 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0033_layer_show_legend'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='label_field', + field=models.CharField(blank=True, help_text='Which field should be used for labels and feature identification in reports?', max_length=255, null=True), + ), + ] diff --git a/data_manager/migrations/0035_auto_20200911_2051.py b/data_manager/migrations/0035_auto_20200911_2051.py new file mode 100644 index 0000000..c7916b2 --- /dev/null +++ b/data_manager/migrations/0035_auto_20200911_2051.py @@ -0,0 +1,23 @@ +# Generated by Django 2.2.9 on 2020-09-11 20:51 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0034_layer_catalog_id'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='catalog_name', + field=models.TextField(blank=True, help_text='name of associated record in catalog', null=True, verbose_name='Catalog Record Name'), + ), + migrations.AlterField( + model_name='layer', + name='catalog_id', + field=models.TextField(blank=True, help_text='unique ID of associated record in catalog', null=True, verbose_name='Catalog Record Id'), + ), + ] diff --git a/data_manager/migrations/0035_multilayerdimension_angle_labels.py b/data_manager/migrations/0035_multilayerdimension_angle_labels.py new file mode 100644 index 0000000..76972e2 --- /dev/null +++ b/data_manager/migrations/0035_multilayerdimension_angle_labels.py @@ -0,0 +1,18 @@ +# Generated by Django 2.2.12 on 2021-04-05 23:44 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0034_layer_label_field'), + ] + + operations = [ + migrations.AddField( + model_name='multilayerdimension', + name='angle_labels', + field=models.BooleanField(default=False, help_text='display labels at an angle to make more fit'), + ), + ] diff --git a/data_manager/migrations/0036_auto_20211021_1845.py b/data_manager/migrations/0036_auto_20211021_1845.py new file mode 100644 index 0000000..cb60def --- /dev/null +++ b/data_manager/migrations/0036_auto_20211021_1845.py @@ -0,0 +1,23 @@ +# Generated by Django 2.2.24 on 2021-10-21 18:45 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0035_multilayerdimension_angle_labels'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='query_by_point', + field=models.BooleanField(default=False, help_text='Do not buffer selection clicks (not recommended for point or line data)'), + ), + migrations.AlterField( + model_name='layer', + name='layer_type', + field=models.CharField(choices=[('XYZ', 'XYZ'), ('WMS', 'WMS'), ('ArcRest', 'ArcRest'), ('ArcFeatureServer', 'ArcFeatureServer'), ('radio', 'radio'), ('checkbox', 'checkbox'), ('Vector', 'Vector'), ('VectorTile', 'VectorTile'), ('placeholder', 'placeholder')], help_text='use placeholder to temporarily remove layer from TOC', max_length=50), + ), + ] diff --git a/data_manager/migrations/0037_merge_0035_auto_20200911_2051_0036_auto_20211021_1845.py b/data_manager/migrations/0037_merge_0035_auto_20200911_2051_0036_auto_20211021_1845.py new file mode 100644 index 0000000..3b782e6 --- /dev/null +++ b/data_manager/migrations/0037_merge_0035_auto_20200911_2051_0036_auto_20211021_1845.py @@ -0,0 +1,14 @@ +# Generated by Django 3.2.9 on 2021-11-24 17:52 + +from django.db import migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0035_auto_20200911_2051'), + ('data_manager', '0036_auto_20211021_1845'), + ] + + operations = [ + ] diff --git a/data_manager/migrations/0038_auto_20211216_1650.py b/data_manager/migrations/0038_auto_20211216_1650.py new file mode 100644 index 0000000..d348b31 --- /dev/null +++ b/data_manager/migrations/0038_auto_20211216_1650.py @@ -0,0 +1,53 @@ +# Generated by Django 3.2.9 on 2021-12-16 16:50 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0037_merge_0035_auto_20200911_2051_0036_auto_20211021_1845'), + ] + + operations = [ + migrations.AlterField( + model_name='attributeinfo', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='dataneed', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='layer', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='multilayerassociation', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='multilayerdimensionvalue', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + migrations.AlterField( + model_name='theme', + name='id', + field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), + ), + ] diff --git a/data_manager/migrations/0039_alter_layer_url.py b/data_manager/migrations/0039_alter_layer_url.py new file mode 100644 index 0000000..be821cd --- /dev/null +++ b/data_manager/migrations/0039_alter_layer_url.py @@ -0,0 +1,18 @@ +# Generated by Django 3.2.9 on 2022-02-24 18:18 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0038_auto_20211216_1650'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='url', + field=models.TextField(blank=True, null=True), + ), + ] diff --git a/data_manager/migrations/0040_layer_date_modified.py b/data_manager/migrations/0040_layer_date_modified.py new file mode 100644 index 0000000..4766786 --- /dev/null +++ b/data_manager/migrations/0040_layer_date_modified.py @@ -0,0 +1,36 @@ +# Generated by Django 3.2.9 on 2022-02-28 21:38 + +from django.db import migrations, models +from datetime import datetime + +def get_last_change(apps, self): + ContentType = apps.get_model('contenttypes', 'ContentType') + LogEntry = apps.get_model('admin', 'LogEntry') + layer_ct = ContentType.objects.get(model='layer') + logs = LogEntry.objects.filter(content_type=layer_ct, object_id=self.pk) + if len(logs) > 0: + last_log = logs.order_by('-action_time')[0] + return last_log.action_time + else: + return datetime.now() + +def populate_date_modified(apps, schema_editor): + Layer = apps.get_model('data_manager', 'Layer') + for layer in Layer.objects.all(): + layer.date_modified = get_last_change(apps, layer) + layer.save() + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0039_alter_layer_url'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='date_modified', + field=models.DateTimeField(null=True), + ), + migrations.RunPython(populate_date_modified) + ] diff --git a/data_manager/migrations/0041_alter_layer_date_modified.py b/data_manager/migrations/0041_alter_layer_date_modified.py new file mode 100644 index 0000000..e9f4414 --- /dev/null +++ b/data_manager/migrations/0041_alter_layer_date_modified.py @@ -0,0 +1,20 @@ +# Generated by Django 3.2.9 on 2022-02-28 21:56 + +import datetime +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0040_layer_date_modified'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='date_modified', + field=models.DateTimeField(auto_now=True, default=datetime.datetime(2022, 2, 28, 21, 56, 2, 836174)), + preserve_default=False, + ), + ] diff --git a/data_manager/migrations/0042_auto_20220525_2017.py b/data_manager/migrations/0042_auto_20220525_2017.py new file mode 100644 index 0000000..fd51e95 --- /dev/null +++ b/data_manager/migrations/0042_auto_20220525_2017.py @@ -0,0 +1,23 @@ +# Generated by Django 3.2.12 on 2022-05-25 20:17 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0041_alter_layer_date_modified'), + ] + + operations = [ + migrations.AddField( + model_name='lookupinfo', + name='description', + field=models.CharField(blank=True, default=None, max_length=255, null=True), + ), + migrations.AlterField( + model_name='layer', + name='lookup_field', + field=models.CharField(blank=True, help_text='To override the style based on specific attributes, provide the attribute name here and define your attributes in the Lookup table below.', max_length=255, null=True), + ), + ] diff --git a/data_manager/migrations/0043_auto_20220525_2100.py b/data_manager/migrations/0043_auto_20220525_2100.py new file mode 100644 index 0000000..80a066b --- /dev/null +++ b/data_manager/migrations/0043_auto_20220525_2100.py @@ -0,0 +1,34 @@ +# Generated by Django 3.2.12 on 2022-05-25 21:00 + +import colorfield.fields +from django.db import migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0042_auto_20220525_2017'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='vector_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Fill Color'), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Stroke Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Fill Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='stroke_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Stroke Color'), + ), + ] diff --git a/data_manager/migrations/0044_layer_proxy_url.py b/data_manager/migrations/0044_layer_proxy_url.py new file mode 100644 index 0000000..bbd8e44 --- /dev/null +++ b/data_manager/migrations/0044_layer_proxy_url.py @@ -0,0 +1,18 @@ +# Generated by Django 3.2.12 on 2022-06-07 00:27 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0043_auto_20220525_2100'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='proxy_url', + field=models.BooleanField(default=False, help_text='proxy layer url through marine planner'), + ), + ] diff --git a/data_manager/migrations/0045_layer_custom_style.py b/data_manager/migrations/0045_layer_custom_style.py new file mode 100644 index 0000000..7fe388b --- /dev/null +++ b/data_manager/migrations/0045_layer_custom_style.py @@ -0,0 +1,34 @@ +# Generated by Django 3.2.12 on 2022-06-21 22:58 + +from django.db import migrations, models + + +def maintain_custom_vector_styles(apps, schema_editor): + Layer = apps.get_model('data_manager', 'Layer') + for layer in Layer.objects.all(): + if layer.vector_color in ['custom:color', 'custom:random']: + layer.custom_style = layer.vector_color.split('custom:')[1] + layer.save() + +def reverse_custom_vector_styles(apps, schema_editor): + Layer = apps.get_model('data_manager', 'Layer') + for layer in Layer.objects.all(): + if not layer.custom_style == None: + layer.vector_color = f"custom:{layer.custom_style}" + layer.save() + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0044_layer_proxy_url'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='custom_style', + field=models.CharField(blank=True, choices=[(None, '------'), ('color', 'color'), ('random', 'random')], default=None, help_text="Apply a custom styling rule: i.e. 'color' for Native-Land.ca layers, or 'random' to assign arbitary colors", max_length=255, null=True), + ), + migrations.RunPython(maintain_custom_vector_styles, reverse_code=reverse_custom_vector_styles) + ] diff --git a/data_manager/migrations/0046_attributeinfo_preserve_format.py b/data_manager/migrations/0046_attributeinfo_preserve_format.py new file mode 100644 index 0000000..09c640b --- /dev/null +++ b/data_manager/migrations/0046_attributeinfo_preserve_format.py @@ -0,0 +1,18 @@ +# Generated by Django 3.2.12 on 2022-08-22 22:52 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0045_layer_custom_style'), + ] + + operations = [ + migrations.AddField( + model_name='attributeinfo', + name='preserve_format', + field=models.BooleanField(default=False, help_text='Prevent portal from making any changes to the data to make it human-readable'), + ), + ] diff --git a/data_manager/migrations/0047_auto_20220829_2040.py b/data_manager/migrations/0047_auto_20220829_2040.py new file mode 100644 index 0000000..b96edc0 --- /dev/null +++ b/data_manager/migrations/0047_auto_20220829_2040.py @@ -0,0 +1,23 @@ +# Generated by Django 3.2.12 on 2022-08-29 20:40 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0046_attributeinfo_preserve_format'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='maxZoom', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Maximum zoom scale at which to display this layer.'), + ), + migrations.AddField( + model_name='layer', + name='minZoom', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Minimum zoom scale at which to display this layer.'), + ), + ] diff --git a/data_manager/migrations/0048_auto_20221005_2315.py b/data_manager/migrations/0048_auto_20221005_2315.py new file mode 100644 index 0000000..2835e62 --- /dev/null +++ b/data_manager/migrations/0048_auto_20221005_2315.py @@ -0,0 +1,41 @@ +# Generated by Django 3.2.12 on 2022-10-05 23:15 + +from django.db import migrations, models +import django.utils.timezone + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0047_auto_20220829_2040'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='date_created', + field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now), + preserve_default=False, + ), + migrations.AddField( + model_name='theme', + name='date_created', + field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now), + preserve_default=False, + ), + migrations.AddField( + model_name='theme', + name='date_modified', + field=models.DateTimeField(auto_now=True), + ), + migrations.AlterField( + model_name='layer', + name='maxZoom', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Maximum zoom'), + ), + migrations.AlterField( + model_name='layer', + name='minZoom', + field=models.FloatField(blank=True, default=None, null=True, verbose_name='Minimum zoom'), + ), + ] diff --git a/data_manager/migrations/0049_auto_20221007_2051.py b/data_manager/migrations/0049_auto_20221007_2051.py new file mode 100644 index 0000000..2b43de2 --- /dev/null +++ b/data_manager/migrations/0049_auto_20221007_2051.py @@ -0,0 +1,49 @@ +# Generated by Django 3.2.12 on 2022-10-07 20:51 + +from django.db import migrations, models +import uuid + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0048_auto_20221005_2315'), + ] + + operations = [ + migrations.AddField( + model_name='attributeinfo', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='layer', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='lookupinfo', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='multilayerassociation', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='multilayerdimension', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='multilayerdimensionvalue', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + migrations.AddField( + model_name='theme', + name='uuid', + field=models.UUIDField(default=uuid.uuid4), + ), + ] diff --git a/data_manager/migrations/0050_set_UUID_values.py b/data_manager/migrations/0050_set_UUID_values.py new file mode 100644 index 0000000..7a58a5c --- /dev/null +++ b/data_manager/migrations/0050_set_UUID_values.py @@ -0,0 +1,79 @@ +# Generated by Django 3.2.12 on 2022-10-07 20:51 + +from django.db import migrations, models +import uuid + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0049_auto_20221007_2051'), + ] + + def gen_uuid(apps, schema_editor): + from data_manager.models import AllObjectsManager + + AIModel = apps.get_model('data_manager', 'attributeinfo') + for row in AIModel.objects.all(): + while True: + row.uuid = uuid.uuid4() + if not AIModel.objects.filter(uuid=row.uuid).exists(): + break + + row.save() + + LIModel = apps.get_model('data_manager', 'lookupinfo') + for row in LIModel.objects.all(): + while True: + row.uuid = uuid.uuid4() + if not LIModel.objects.filter(uuid=row.uuid).exists(): + break + + row.save() + MDVModel = apps.get_model('data_manager', 'multilayerdimensionvalue') + for row in MDVModel.objects.all(): + while True: + row.uuid = uuid.uuid4() + if not MDVModel.objects.filter(uuid=row.uuid).exists(): + break + + row.save() + + MDModel = apps.get_model('data_manager', 'multilayerdimension') + for row in MDModel.objects.all(): + while True: + row.uuid = uuid.uuid4() + if not MDModel.objects.filter(uuid=row.uuid).exists(): + break + + row.save() + MAModel = apps.get_model('data_manager', 'multilayerassociation') + for row in MAModel.objects.all(): + while True: + row.uuid = uuid.uuid4() + if not MAModel.objects.filter(uuid=row.uuid).exists(): + break + + row.save() + theme_manager = AllObjectsManager() + theme_manager.model = apps.get_model('data_manager', 'theme') + for row in theme_manager.all(): + while True: + row.uuid = uuid.uuid4() + if not theme_manager.filter(uuid=row.uuid).exists(): + break + + row.save() + layer_manager = AllObjectsManager() + layer_manager.model = apps.get_model('data_manager', 'layer') + for row in layer_manager.all(): + while True: + row.uuid = uuid.uuid4() + if not layer_manager.filter(uuid=row.uuid).exists(): + break + + row.save() + + operations = [ + migrations.RunPython(gen_uuid, reverse_code=migrations.RunPython.noop), + ] diff --git a/data_manager/migrations/0051_auto_20221008_0046.py b/data_manager/migrations/0051_auto_20221008_0046.py new file mode 100644 index 0000000..86a7918 --- /dev/null +++ b/data_manager/migrations/0051_auto_20221008_0046.py @@ -0,0 +1,49 @@ +# Generated by Django 3.2.16 on 2022-10-08 00:46 + +from django.db import migrations, models +import uuid + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0050_set_UUID_values'), + ] + + operations = [ + migrations.AlterField( + model_name='attributeinfo', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='layer', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='lookupinfo', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='multilayerassociation', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='multilayerdimension', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='multilayerdimensionvalue', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + migrations.AlterField( + model_name='theme', + name='uuid', + field=models.UUIDField(default=uuid.uuid4, unique=True), + ), + ] diff --git a/data_manager/migrations/0052_externalportal.py b/data_manager/migrations/0052_externalportal.py new file mode 100644 index 0000000..d4a13a5 --- /dev/null +++ b/data_manager/migrations/0052_externalportal.py @@ -0,0 +1,21 @@ +# Generated by Django 3.2.16 on 2022-10-19 15:34 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0051_auto_20221008_0046'), + ] + + operations = [ + migrations.CreateModel( + name='ExternalPortal', + fields=[ + ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), + ('name', models.CharField(blank=True, default=None, max_length=255, null=True)), + ('url', models.URLField(help_text='URL endpoint of the remote Portal')), + ], + ), + ] diff --git a/data_manager/migrations/0053_auto_20230703_2345.py b/data_manager/migrations/0053_auto_20230703_2345.py new file mode 100644 index 0000000..b86c1ee --- /dev/null +++ b/data_manager/migrations/0053_auto_20230703_2345.py @@ -0,0 +1,18 @@ +# Generated by Django 3.2.16 on 2023-07-03 23:45 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0052_externalportal'), + ] + + operations = [ + migrations.AddField( + model_name='layer', + name='password_protected', + field=models.BooleanField(default=False, help_text='check this if the server requires a password to show layers'), + ), + ] diff --git a/data_manager/migrations/0054_auto_20231212_0006.py b/data_manager/migrations/0054_auto_20231212_0006.py new file mode 100644 index 0000000..c693c41 --- /dev/null +++ b/data_manager/migrations/0054_auto_20231212_0006.py @@ -0,0 +1,50 @@ +# Generated by Django 3.2.23 on 2023-12-12 00:06 + +import colorfield.fields +import data_manager.models +import django.contrib.sites.managers +from django.db import migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0053_auto_20230703_2345'), + ] + + operations = [ + migrations.AlterModelManagers( + name='layer', + managers=[ + ('objects', django.contrib.sites.managers.CurrentSiteManager('site')), + ('all_objects', data_manager.models.AllObjectsManager()), + ], + ), + migrations.AlterModelManagers( + name='theme', + managers=[ + ('objects', django.contrib.sites.managers.CurrentSiteManager('site')), + ('all_objects', data_manager.models.AllObjectsManager()), + ], + ), + migrations.AlterField( + model_name='layer', + name='vector_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=25, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Fill Color'), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=25, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Stroke Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=25, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Fill Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='stroke_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=25, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Stroke Color'), + ), + ] diff --git a/data_manager/migrations/0055_auto_20240328_0110.py b/data_manager/migrations/0055_auto_20240328_0110.py new file mode 100644 index 0000000..e3a06ed --- /dev/null +++ b/data_manager/migrations/0055_auto_20240328_0110.py @@ -0,0 +1,34 @@ +# Generated by Django 3.2.12 on 2024-03-28 01:10 + +import colorfield.fields +from django.db import migrations + + +class Migration(migrations.Migration): + + dependencies = [ + ('data_manager', '0054_auto_20231212_0006'), + ] + + operations = [ + migrations.AlterField( + model_name='layer', + name='vector_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Fill Color'), + ), + migrations.AlterField( + model_name='layer', + name='vector_outline_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Vector Stroke Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Fill Color'), + ), + migrations.AlterField( + model_name='lookupinfo', + name='stroke_color', + field=colorfield.fields.ColorField(blank=True, default=None, image_field=None, max_length=18, null=True, samples=[('#FFFFFF', 'white'), ('#888888', 'gray'), ('#000000', 'black'), ('#FF0000', 'red'), ('#FFFF00', 'yellow'), ('#00FF00', 'green'), ('#00FFFF', 'cyan'), ('#0000FF', 'blue'), ('#FF00FF', 'magenta')], verbose_name='Stroke Color'), + ), + ] diff --git a/data_manager/models.py b/data_manager/models.py index e9bfbf0..12d5a83 100644 --- a/data_manager/models.py +++ b/data_manager/models.py @@ -1,808 +1,1231 @@ -from django.contrib.sites.managers import CurrentSiteManager -from django.contrib.sites.models import Site -from django.db import models -from django.template.defaultfilters import slugify -from django.core.urlresolvers import reverse -#from sorl.thumbnail import ImageField - -# From MARCO/utils.py -def get_domain(port=8010): - try: - #domain = Site.objects.all()[0].domain - domain = Site.objects.get(id=SITE_ID).domain - if 'localhost' in domain: - domain = 'localhost:%s' %port - domain = 'http://' + domain - except: - domain = '..' - #print domain - return domain - -def reset_cache(sites): - from django.core.cache import cache - import requests - from requests.exceptions import ConnectionError - for site in sites: - cache.delete('data_manager_json_site_%s' % site.pk) - from marco.settings import DEBUG - if DEBUG and ('localhost:' in site.domain or '127.0.0.1:' in site.domain): - url = "http://%s:8000/data_manager/get_json" % site.domain[:site.domain.index(':')] - else: - url = "http://%s/data_manager/get_json" % site.domain - try: - requests.get(url) - except ConnectionError: - #sometimes testing overdoes this a bit and we get 'Max retries exceeded' - print('recache error - either port isn\'t listening or you\'ve maxed out your retries') - -class SiteFlags(object):#(models.Model): - """Add-on class for displaying sites in the list_display - in the admin. - """ - def primary_site(self): - return self.site.filter(id=1).exists() - primary_site.boolean = True - - def preview_site(self): - return self.site.filter(id=2).exists() - preview_site.boolean = True - -class Theme(models.Model, SiteFlags): - site = models.ManyToManyField(Site) - display_name = models.CharField(max_length=100) - name = models.CharField(max_length=100) - order = models.PositiveSmallIntegerField(default=10, blank=True, null=True, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)') - visible = models.BooleanField(default=True) - header_image = models.CharField(max_length=255, blank=True, null=True) - header_attrib = models.CharField(max_length=255, blank=True, null=True) - overview = models.TextField(blank=True, null=True) - description = models.TextField(blank=True, null=True) - thumbnail = models.URLField(max_length=255, blank=True, null=True) - - factsheet_thumb = models.CharField(max_length=255, blank=True, null=True) - factsheet_link = models.CharField(max_length=255, blank=True, null=True) - - # not really using these atm - feature_image = models.CharField(max_length=255, blank=True, null=True) - feature_excerpt = models.TextField(blank=True, null=True) - feature_link = models.CharField(max_length=255, blank=True, null=True) - - # objects = models.Manager() - objects = CurrentSiteManager('site') - all_objects = models.Manager() - - def url(self): - id = self.id - return '/visualize/#x=-73.24&y=38.93&z=7&logo=true&controls=true&basemap=Ocean&themes[ids][]=%s&tab=data&legends=false&layers=true' % (id) - - def __unicode__(self): - return unicode('%s' % (self.name)) - - @property - def learn_link(self): - domain = get_domain(8000) - return '%s/learn/%s' %(domain, self.name) - - def dictCache(self, site_id=None): - themes_dict = None - if site_id in [x.id for x in self.site.all()]: - themes_dict = self.toDict - themes_dict['layers'] = [layer.id for layer in Layer.all_objects.filter(site__in=[site_id],is_sublayer=False,themes__in=[self.id]).exclude(layer_type='placeholder')] - return themes_dict - - - @property - def toDict(self): - layers = [layer.id for layer in Layer.objects.filter(is_sublayer=False,sublayers__in=[self.id]).exclude(layer_type='placeholder')] - themes_dict = { - 'id': self.id, - 'name': self.name, - 'display_name': self.display_name, - 'learn_link': self.learn_link, - 'is_visible': self.visible, - 'layers': layers, - 'description': self.description - } - - return themes_dict - - def save(self, *args, **kwargs): - if 'recache' in kwargs.keys(): #crufty - impacted when MDAT v2 import is run. - kwargs.pop('recache', None) - super(Theme, self).save(*args, **kwargs) - -class Layer(models.Model, SiteFlags): - TYPE_CHOICES = ( - ('XYZ', 'XYZ'), - ('WMS', 'WMS'), - ('ArcRest', 'ArcRest'), - ('radio', 'radio'), - ('checkbox', 'checkbox'), - ('Vector', 'Vector'), - ('placeholder', 'placeholder'), - ) - WMS_VERSION_CHOICES = ( - (None, ''), - ('1.0.0', '1.0.0'), - ('1.1.0', '1.1.0'), - ('1.1.1', '1.1.1'), - ('1.3.0', '1.3.0'), - ) - site = models.ManyToManyField(Site) - name = models.CharField(max_length=100) - order = models.PositiveSmallIntegerField(default=10, blank=True, null=True, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)') - slug_name = models.CharField(max_length=200, blank=True, null=True) - layer_type = models.CharField(max_length=50, choices=TYPE_CHOICES, help_text='use placeholder to temporarily remove layer from TOC') - url = models.CharField(max_length=255, blank=True, null=True) - shareable_url = models.BooleanField(default=True, help_text='Indicates whether the data layer (e.g. map tiles) can be shared with others (through the Map Tiles Link)') - arcgis_layers = models.CharField(max_length=255, blank=True, null=True, help_text='comma separated list of arcgis layer IDs') - disable_arcgis_attributes = models.BooleanField(default=False, help_text='Click to disable clickable ArcRest layers') - wms_help = models.BooleanField(default=False, help_text='Enable simple selection for WMS fields. Only supports WMS 1.1.1') - wms_slug = models.CharField(max_length=255, blank=True, null=True, verbose_name='WMS Layer Name') - wms_version = models.CharField(max_length=10, blank=True, null=True, choices=WMS_VERSION_CHOICES, help_text='WMS Versioning - usually either 1.1.1 or 1.3.0') - wms_format = models.CharField(max_length=100, blank=True, null=True, help_text='most common: image/png. Only image types supported.', verbose_name='WMS Format') - wms_srs = models.CharField(max_length=100, blank=True, null=True, help_text='If not EPSG:3857 WMS requests will be proxied', verbose_name='WMS SRS') - wms_styles = models.CharField(max_length=255, blank=True, null=True, help_text='pre-determined styles, if exist', verbose_name='WMS Styles') - wms_timing = models.CharField(max_length=255, blank=True, null=True, help_text='http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', verbose_name='WMS Time') - wms_time_item = models.CharField(max_length=255, blank=True, null=True, help_text='Time Attribute Field, if different from "TIME". Proxy only.', verbose_name='WMS Time Field') - wms_additional = models.TextField(blank=True, null=True, help_text='additional WMS key-value pairs: &key=value...', verbose_name='WMS Additional Fields') - is_sublayer = models.BooleanField(default=False) - sublayers = models.ManyToManyField('self', blank=True, null=True) - themes = models.ManyToManyField("Theme", blank=True, null=True) - search_query = models.BooleanField(default=False, help_text='Select when layers are queryable - e.g. MDAT and CAS') - has_companion = models.BooleanField(default=False, help_text='Check if this layer has a companion layer') - connect_companion_layers_to = models.ManyToManyField('self', blank=True, null=True, help_text='Select which main layer(s) you would like to use in conjuction with this companion layer.') - is_disabled = models.BooleanField(default=False, help_text='when disabled, the layer will still appear in the TOC, only disabled') - disabled_message = models.CharField(max_length=255, blank=True, null=True) - legend = models.CharField(max_length=255, blank=True, null=True, help_text='URL or path to the legend image file') - legend_title = models.CharField(max_length=255, blank=True, null=True, help_text='alternative to using the layer name') - legend_subtitle = models.CharField(max_length=255, blank=True, null=True) - utfurl = models.CharField(max_length=255, blank=True, null=True) - - #tooltip - description = models.TextField(blank=True, null=True) - - #data description (updated fact sheet) (now the Learn pages) - data_overview = models.TextField(blank=True, null=True) - data_source = models.CharField(max_length=255, blank=True, null=True) - data_notes = models.TextField(blank=True, null=True) - data_publish_date = models.DateField(auto_now=False, auto_now_add=False, null=True, blank=True, default=None, verbose_name='Date published', help_text='YYYY-MM-DD') - - #data catalog links - bookmark = models.CharField(max_length=755, blank=True, null=True, help_text='link to view data layer in the planner') - kml = models.CharField(max_length=255, blank=True, null=True, help_text='link to download the KML') - data_download = models.CharField(max_length=255, blank=True, null=True, help_text='link to download the data') - learn_more = models.CharField(max_length=255, blank=True, null=True, help_text='link to view description in the Learn section') - metadata = models.CharField(max_length=255, blank=True, null=True, help_text='link to view/download the metadata') - source = models.CharField(max_length=255, blank=True, null=True, help_text='link back to the data source') - map_tiles = models.CharField(max_length=255, blank=True, null=True, help_text='internal link to a page that details how others might consume the data') - thumbnail = models.URLField(max_length=255, blank=True, null=True, help_text='not sure we are using this any longer...') - - #geojson javascript attribution - EVENT_CHOICES = ( - ('click', 'click'), - ('mouseover', 'mouseover') - ) - attribute_fields = models.ManyToManyField('AttributeInfo', blank=True, null=True) - compress_display = models.BooleanField(default=False) - attribute_event = models.CharField(max_length=35, choices=EVENT_CHOICES, default='click') - mouseover_field = models.CharField(max_length=75, blank=True, null=True, help_text='feature level attribute used in mouseover display') - lookup_field = models.CharField(max_length=255, blank=True, null=True) - lookup_table = models.ManyToManyField('LookupInfo', blank=True, null=True) - is_annotated = models.BooleanField(default=False) - vector_outline_color = models.CharField(max_length=7, blank=True, null=True) - vector_outline_opacity = models.FloatField(blank=True, null=True) - vector_color = models.CharField(max_length=7, blank=True, null=True) - vector_fill = models.FloatField(blank=True, null=True) - vector_graphic = models.CharField(max_length=255, blank=True, null=True) - point_radius = models.IntegerField(blank=True, null=True, help_text='Used only for for Point layers (default is 2)') - opacity = models.FloatField(default=.5, blank=True, null=True) - - # objects = models.Manager() - objects = CurrentSiteManager('site') - all_objects = models.Manager() - - #ESPIS Upgrade - RDH 7/23/2017 - ESPIS_REGION_CHOICES = ( - ('Mid Atlantic', 'Mid Atlantic'), - ) - espis_enabled = models.BooleanField(default=False) - espis_search = models.CharField(max_length=255, blank=True, null=True, help_text="keyphrase search for ESPIS Link") - espis_region = models.CharField(max_length=100, blank=True, null=True, choices=ESPIS_REGION_CHOICES, help_text="Region to search within") - - def __unicode__(self): - return unicode('%s' % (self.name)) - - @property - def is_parent(self): - return self.sublayers.all().count() > 0 and not self.is_sublayer - - @property - def parent(self): - if self.is_sublayer: - if self.sublayers.all().count() > 0: - return self.sublayers.all()[0] - else: - return None - return self - - def get_absolute_url(self): - theme = self.themes.filter(visible=True).first() - if theme: - theme_url = reverse('portal.data_catalog.views.theme', args=[theme.name]) - if theme_url: - return "{0}#layer-info-{1}".format(theme_url, self.slug_name) - - @property - def slug(self): - # RDH Hack for MDAT v2 transition 8/8/2018. - # Slug just takes name, but if name is the same then multiple layers have same slug. Should slug include ID? - if self.slug_name and ('-v2-prod' in self.slug_name or '-v2-staging' in self.slug_name): - slug_string = "%s-v2%s" % (slugify(self.name),self.slug_name.split('v2')[1]) - return slug_string - return slugify(self.name) - - @property - def data_overview_text(self): - if not self.data_overview and self.is_sublayer and self.parent: - return self.parent.data_overview - else: - return self.data_overview - - @property - def data_source_text(self): - if not self.data_source and self.is_sublayer: - return self.parent.data_source - else: - return self.data_source - - @property - def data_notes_text(self): - if not self.data_notes and self.is_sublayer: - return self.parent.data_notes - else: - return self.data_notes - - @property - def bookmark_link(self): - if self.bookmark and "%%5D=%d&" % self.id in self.bookmark: - return self.bookmark - - if self.is_sublayer and self.parent.bookmark and len(self.parent.bookmark) > 0: - return self.parent.bookmark.replace('', str(self.id)) - - if self.is_parent: - for theme in self.themes.all(): - return theme.url() - - # RDH: Most Marine Life layers seem to have bogus bookmarks. If the first line of this def - # isn't true, then we likely need to give users something that will work. This should do it. - root_str = '/visualize/#x=-73.24&y=38.93&z=7&logo=true&controls=true&basemap=Ocean' - layer_str = '&dls%%5B%%5D=true&dls%%5B%%5D=%s&dls%%5B%%5D=%d' % (str(self.opacity), self.id) - companion_str = '' - if self.has_companion: - for companion in self.connect_companion_layers_to.all(): - companion_str += '&dls%%5B%%5D=false&dls%%5B%%5D=%s&dls%%5B%%5D=%d' % (str(companion.opacity), companion.id) - themes_str = '' - if self.themes.all().count() > 0: - for theme in self.themes.all(): - themes_str = '&themes%%5Bids%%5D%%5B%%5D=%d' % theme.id - - panel_str = '&tab=data&legends=false&layers=true' - - return "%s%s%s%s%s" % (root_str, layer_str, companion_str, themes_str, panel_str) - - - @property - def data_download_link(self): - if self.data_download and self.data_download.lower() == 'none': - return None - if self.parent and not self.data_download and self.is_sublayer: - return self.parent.data_download - else: - return self.data_download - - @property - def metadata_link(self): - if self.metadata and self.metadata.lower() == 'none': - return None - if not self.metadata: - if self.is_sublayer and self.parent: - return self.parent.metadata - else: - return None - else: - return self.metadata - - @property - def source_link(self): - if self.source and self.source.lower() == 'none': - return None - if not self.source: - if self.is_sublayer and self.parent: - return self.parent.source - else: - return None - else: - return self.source - - @property - def description_link(self): - theme_name = self.themes.all()[0].name - domain = get_domain(8000) - return '%s/learn/%s#%s' %(domain, theme_name, self.slug_name) - - @property - def tiles_link(self): - if self.is_shareable and self.layer_type in ['XYZ', 'ArcRest', 'WMS']: - domain = get_domain(8000) - return self.slug_name - return None - - @property - def tooltip(self): - if self.description and self.description.strip() != '': - return self.description - elif self.parent and self.parent.description and self.parent.description.strip() != '': - return self.parent.description - else: - return self.data_overview_text - - @property - def is_shareable(self): - if self.shareable_url == False: - return False - if self.parent and self.parent.shareable_url == False: - return False - return True - - def serialize_attributes(self): - return {'compress_attributes': self.compress_display, - 'event': self.attribute_event, - 'attributes': [{'display': attr.display_name, 'field': attr.field_name, 'precision': attr.precision} for attr in self.attribute_fields.all().order_by('order')], - 'mouseover_attribute': self.mouseover_field } - - @property - def serialize_lookups(self): - return {'field': self.lookup_field, - 'details': [{'value': lookup.value, 'color': lookup.color, 'dashstyle': lookup.dashstyle, 'fill': lookup.fill, 'graphic': lookup.graphic} for lookup in self.lookup_table.all()]} - - def get_espis_link(self): - if self.espis_enabled: - search_dict = {} - if self.espis_search: - search_dict['txt'] = self.espis_search - if self.espis_region: - search_dict['geo'] = self.espis_region - if len(search_dict) > 0: - from urllib import urlencode - return 'https://marinecadastre.gov/espis/#/search/%s' % urlencode(search_dict) - return None - - def dimensionRecursion(self, dimensions, associations): - associationArray = {} - dimension = dimensions.pop(0) - for value in sorted(dimension.multilayerdimensionvalue_set.all(), key=lambda x: x.order): - value_associations = associations.filter(pk__in=[x.pk for x in value.associations.all()]) - if len(dimensions) > 0: - associationArray[str(value.value)] = self.dimensionRecursion(list(dimensions), value_associations) - else: - if len(value_associations) == 1 and value_associations[0].layer: - associationArray[str(value.value)] = value_associations[0].layer.pk - else: - associationArray[str(value.value)] = None - return associationArray - - @property - def isMultilayerParent(self): - return len(self.multilayerdimension_set.all()) > 0 - - @property - def isMultilayer(self): - return len(self.associated_layer.all()) > 0 - - @property - def dimensions(self): - return sorted([ - { - 'label': x.label, - 'name': x.name, - 'order': x.order, - 'animated': x.animated, - 'nodes': sorted([ - { - 'value': y.value, - 'label': y.label, - 'order': y.order - } - for y in x.multilayerdimensionvalue_set.all() - ], key=lambda y: y['order']) - } - for x in self.multilayerdimension_set.all() - ], key=lambda x: x['order']) - - @property - def associatedMultilayers(self): - if len(self.multilayerdimension_set.all()) > 0: - return self.dimensionRecursion(sorted(self.multilayerdimension_set.all(), key=lambda x: x.order), self.parent_layer.all()) - else: - return {} - - def dictCache(self, site_id=None): - from django.core.cache import cache - layers_dict = None - if site_id in [x.id for x in self.site.all()]: - if site_id: - layers_dict = cache.get('data_manager_layer_%d_%d' % (self.id, site_id)) - if not layers_dict: - layers_dict = self.toDict - if site_id: - # Cache for 1 week, will be reset if layer data changes - cache.set('data_manager_layer_%d_%d' % (self.id, site_id), layers_dict, 60*60*24*7) - else: - for site in Site.objects.all(): - cache.set('data_manager_layer_%d_%d' % (self.id, site.id), layers_dict, 60*60*24*7) - return layers_dict - - @property - def toDict(self, site_id=None): - sublayers = [ - { - 'id': layer.id, - 'name': layer.name, - 'order': layer.order, - 'type': layer.layer_type, - 'url': layer.url, - 'arcgis_layers': layer.arcgis_layers, - 'disable_arcgis_attributes': layer.disable_arcgis_attributes, - 'wms_slug': layer.wms_slug, - 'wms_version': layer.wms_version, - 'wms_format': layer.wms_format, - 'wms_srs': layer.wms_srs, - 'wms_styles': layer.wms_styles, - 'wms_timing': layer.wms_timing, - 'wms_time_item': layer.wms_time_item, - 'wms_additional': layer.wms_additional, - 'utfurl': layer.utfurl, - 'parent': self.id, - 'legend': layer.legend, - 'legend_title': layer.legend_title, - 'legend_subtitle': layer.legend_subtitle, - 'description': layer.tooltip, - 'overview': layer.data_overview_text, - 'data_source': layer.data_source, - 'data_notes': layer.data_notes, - 'kml': layer.kml, - 'data_download': layer.data_download_link, - 'learn_more': layer.learn_more, - 'metadata': layer.metadata_link, - 'source': layer.source_link, - 'tiles': layer.tiles_link, - 'attributes': layer.serialize_attributes(), - 'lookups': layer.serialize_lookups, - 'outline_color': layer.vector_outline_color, - 'outline_opacity': layer.vector_outline_opacity, - 'point_radius': layer.point_radius, - 'color': layer.vector_color, - 'fill_opacity': layer.vector_fill, - 'graphic': layer.vector_graphic, - 'opacity': layer.opacity, - 'annotated': layer.is_annotated, - 'is_disabled': layer.is_disabled, - 'disabled_message': layer.disabled_message, - 'data_url': layer.get_absolute_url(), - 'has_companion': layer.has_companion, - 'is_multilayer': layer.isMultilayer, - 'is_multilayer_parent': layer.isMultilayerParent, - 'dimensions': layer.dimensions, - 'associated_multilayers': layer.associatedMultilayers - } - for layer in self.sublayers.all() - ] - connect_companion_layers_to = [ - { - 'id': layer.id, - 'name': layer.name, - 'order': layer.order, - 'type': layer.layer_type, - 'url': layer.url, - 'arcgis_layers': layer.arcgis_layers, - 'disable_arcgis_attributes': layer.disable_arcgis_attributes, - 'wms_slug': layer.wms_slug, - 'wms_version': layer.wms_version, - 'wms_format': layer.wms_format, - 'wms_srs': layer.wms_srs, - 'wms_styles': layer.wms_styles, - 'wms_timing': layer.wms_timing, - 'wms_time_item': layer.wms_time_item, - 'wms_additional': layer.wms_additional, - 'utfurl': layer.utfurl, - 'parent': self.id, - 'legend': layer.legend, - 'legend_title': layer.legend_title, - 'legend_subtitle': layer.legend_subtitle, - 'description': layer.tooltip, - 'overview': layer.data_overview_text, - 'data_source': layer.data_source, - 'data_notes': layer.data_notes, - 'kml': layer.kml, - 'data_download': layer.data_download_link, - 'learn_more': layer.learn_more, - 'metadata': layer.metadata_link, - 'source': layer.source_link, - 'tiles': layer.tiles_link, - 'attributes': layer.serialize_attributes(), - 'lookups': layer.serialize_lookups, - 'outline_color': layer.vector_outline_color, - 'outline_opacity': layer.vector_outline_opacity, - 'point_radius': layer.point_radius, - 'color': layer.vector_color, - 'fill_opacity': layer.vector_fill, - 'graphic': layer.vector_graphic, - 'opacity': layer.opacity, - 'annotated': layer.is_annotated, - 'is_disabled': layer.is_disabled, - 'disabled_message': layer.disabled_message, - 'data_url': layer.get_absolute_url(), - 'has_companion': layer.has_companion, - 'is_multilayer': layer.isMultilayer, - 'is_multilayer_parent': layer.isMultilayerParent, - 'dimensions': layer.dimensions, - 'associated_multilayers': layer.associatedMultilayers - } - for layer in self.connect_companion_layers_to.all() - ] - layers_dict = { - 'id': self.id, - 'name': self.name, - 'order': self.order, - 'type': self.layer_type, - 'url': self.url, - 'arcgis_layers': self.arcgis_layers, - 'disable_arcgis_attributes': self.disable_arcgis_attributes, - 'wms_slug': self.wms_slug, - 'wms_version': self.wms_version, - 'wms_format': self.wms_format, - 'wms_srs': self.wms_srs, - 'wms_styles': self.wms_styles, - 'wms_timing': self.wms_timing, - 'wms_time_item': self.wms_time_item, - 'wms_additional': self.wms_additional, - 'utfurl': self.utfurl, - 'subLayers': sublayers, - 'companion_layers': connect_companion_layers_to, - 'has_companion': self.has_companion, - 'queryable': self.search_query, - 'legend': self.legend, - 'legend_title': self.legend_title, - 'legend_subtitle': self.legend_subtitle, - 'description': self.description, - 'overview': self.data_overview, - 'data_source': self.data_source, - 'data_notes': self.data_notes, - 'kml': self.kml, - 'data_download': self.data_download_link, - 'learn_more': self.learn_more, - 'metadata': self.metadata_link, - 'source': self.source_link, - 'tiles': self.tiles_link, - 'attributes': self.serialize_attributes(), - 'lookups': self.serialize_lookups, - 'outline_color': self.vector_outline_color, - 'outline_opacity': self.vector_outline_opacity, - 'point_radius': self.point_radius, - 'color': self.vector_color, - 'fill_opacity': self.vector_fill, - 'graphic': self.vector_graphic, - 'opacity': self.opacity, - 'annotated': self.is_annotated, - 'is_disabled': self.is_disabled, - 'disabled_message': self.disabled_message, - 'data_url': self.get_absolute_url(), - 'is_multilayer': self.isMultilayer, - 'is_multilayer_parent': self.isMultilayerParent, - 'dimensions': self.dimensions, - 'associated_multilayers': self.associatedMultilayers - } - - return layers_dict - - def save(self, *args, **kwargs): - from django.core.cache import cache - if 'slug_name' in kwargs.keys(): - self.slug_name = kwargs['slug_name'] - kwargs.pop('slug_name', None) - else: - if self.id: - self.slug_name = '%s%d' % (self.slug, self.id) - else: - self.slug_name = '%s_new' % self.slug - if self.url == None: - self.url = '' - if 'recache' in kwargs.keys(): - kwargs.pop('recache', None) - super(Layer, self).save(*args, **kwargs) - for site in Site.objects.all(): - cache.delete('data_manager_json_site_%s' % site.pk) - cache.delete('data_manager_layer_%d_%d' % (self.id, site.pk)) - self.dictCache(site.pk) - # Delete cache for all sublayers - for sublayer in self.sublayers.all(): - cache.delete('data_manager_layer_%d_%d' % (sublayer.id, site.pk)) - sublayer.dictCache(site.pk) - # Delete cache for parent layers (in case not double-linked) - for parentlayer in Layer.objects.filter(sublayers__in=[self]): - cache.delete('data_manager_layer_%d_%d' % (parentlayer.id, site.pk)) - parentlayer.dictCache(site.pk) - # Delete cache for companion layers - for companion in self.connect_companion_layers_to.all(): - cache.delete('data_manager_layer_%d_%d' % (companion.id, site.pk)) - companion.dictCache(site.pk) - for companion in Layer.objects.filter(connect_companion_layers_to__in=[self]): - cache.delete('data_manager_layer_%d_%d' % (companion.id, site.pk)) - companion.dictCache(site.pk) - for association in self.associated_layer.all(): - cache.delete('data_manager_layer_%d_%d' % (association.parentLayer.pk, site.pk)) - association.layer.dictCache(site.pk) - - -class AttributeInfo(models.Model): - display_name = models.CharField(max_length=255, blank=True, null=True) - field_name = models.CharField(max_length=255, blank=True, null=True) - precision = models.IntegerField(blank=True, null=True) - order = models.IntegerField(default=1) - - def __unicode__(self): - return unicode('%s' % (self.field_name)) - -class LookupInfo(models.Model): - DASH_CHOICES = ( - ('dot', 'dot'), - ('dash', 'dash'), - ('dashdot', 'dashdot'), - ('longdash', 'longdash'), - ('longdashdot', 'longdashdot'), - ('solid', 'solid') - ) - value = models.CharField(max_length=255, blank=True, null=True) - color = models.CharField(max_length=7, blank=True, null=True) - dashstyle = models.CharField(max_length=11, choices=DASH_CHOICES, default='solid') - fill = models.BooleanField(default=False) - graphic = models.CharField(max_length=255, blank=True, null=True) - - def __unicode__(self): - return unicode('%s' % (self.value)) - -class DataNeed(models.Model): - name = models.CharField(max_length=100) - archived = models.BooleanField(default=False) - description = models.TextField(blank=True, null=True) - source = models.CharField(max_length=255, blank=True, null=True) - status = models.TextField(blank=True, null=True) - contact = models.CharField(max_length=255, blank=True, null=True) - contact_email = models.CharField(max_length=255, blank=True, null=True) - expected_date = models.CharField(max_length=255, blank=True, null=True) - notes = models.TextField(blank=True, null=True) - themes = models.ManyToManyField("Theme", blank=True, null=True) - - @property - def html_name(self): - return self.name.lower().replace(' ', '-') - - def __unicode__(self): - return unicode('%s' % (self.name)) - -class MultilayerDimension(models.Model): - name = models.CharField(max_length=200, help_text='name to be used for selection in admin tool forms') - label = models.CharField(max_length=50, help_text='label to be used in mapping tool slider') - order = models.IntegerField(default=100, help_text='the order in which this dimension will be presented among other dimensions on this layer') - animated = models.BooleanField(default=False, help_text='enable auto-toggling of layers across this dimension') - layer = models.ForeignKey(Layer) - - def __unicode__(self): - return self.name - - def __str__(self): - return self.name - - class Meta: - ordering = ('order',) - - def save(self, *args, **kwargs): - super(MultilayerDimension, self).save(*args, **kwargs) - - def delete(self, *args, **kwargs): - if len(self.layer.dimensions) == 1: - last = True - else: - last = False - for value in self.multilayerdimensionvalue_set.all().order_by('-order'): - value.delete((),last=last) - super(MultilayerDimension, self).delete(*args, **kwargs) - -class MultilayerAssociation(models.Model): - name = models.CharField(max_length=200) - parentLayer = models.ForeignKey(Layer, related_name="parent_layer", db_column='parentlayer') - layer = models.ForeignKey(Layer, null=True, blank=True, default=None, related_name="associated_layer", db_column='associatedlayer') - - def __unicode__(self): - return self.name - - def __str__(self): - return self.name - - # def save(self, *args, **kwargs): - # super(MultilayerAssociation, self).save(*args, **kwargs) - # print("Association: %s +++SAVED+++" % str(self)) - # - # def delete(self, *args, **kwargs): - # super(MultilayerAssociation, self).delete(*args, **kwargs) - # print("Association: %s ---DELETED---" % str(self)) - -class MultilayerDimensionValue(models.Model): - dimension = models.ForeignKey(MultilayerDimension) - value = models.CharField(max_length=200, help_text="Actual value of selection") - label = models.CharField(max_length=50, help_text="Label for this selection seen in mapping tool slider") - order = models.IntegerField(default=100) - associations = models.ManyToManyField(MultilayerAssociation) - - def __unicode__(self): - return '%s: %s' % (self.dimension, self.value) - - def __str__(self): - return '%s: %s' % (self.dimension, self.value) - - class Meta: - ordering = ('order',) - - def save(self, *args, **kwargs): - if self.pk is None: - super(MultilayerDimensionValue, self).save(*args, **kwargs) - parentLayer = self.dimension.layer - associations = MultilayerAssociation.objects.filter(parentLayer=parentLayer) - if len(associations) == 0: - MultilayerAssociation.objects.create(name=str(self), parentLayer=parentLayer) - associations.update() - siblingValues = [x for x in self.dimension.multilayerdimensionvalue_set.all() if x != self] - if len(siblingValues) == 0: - for association in associations: - self.associations.add(association) - else: - # If this is not the first value saved to this dimension, choosing - # an arbitrary sibling value and copying all of its associations - # is the closest thing we can do to smart generation of associations - from copy import deepcopy - siblingValue = siblingValues[0] - for association in siblingValue.associations.all(): - dimensionValues = [x for x in association.multilayerdimensionvalue_set.all() if x.dimension != self.dimension] - # create a clone of association - newAssociation = deepcopy(association) - newAssociation.id = None - newAssociation.name = 'NEW' - newAssociation.save() - # restore value/association relationships - for value in dimensionValues: - value.associations.add(newAssociation) - self.associations.add(newAssociation) - - else: - super(MultilayerDimensionValue, self).save(*args, **kwargs) - - def delete(self, *args, **kwargs): - delete_all = False - if kwargs.has_key('last'): - if kwargs['last']: - delete_all = True - kwargs.pop('last', None) - try: - for association in self.associations.all(): - if delete_all or len(self.dimension.multilayerdimensionvalue_set.all()) > 1 or len(self.dimension.layer.parent_layer.all()) == 1: - association.multilayerdimensionvalue_set.clear() - association.delete() - except ValueError: - # ValueError: "" needs to have a value for field "multilayerdimensionvalue" before this many-to-many relationship can be used. - pass - - if self.id: - # AssertionError: MultilayerDimensionValue object can't be deleted because its id attribute is set to None. - super(MultilayerDimensionValue, self).delete(*args, **kwargs) +from django.contrib.sites.managers import CurrentSiteManager +from django.contrib.sites.models import Site +from django.db import models +from django.template.defaultfilters import slugify +from django.urls import reverse +from django.conf import settings +#from sorl.thumbnail import ImageField +from django.contrib.contenttypes.models import ContentType +from django.contrib.admin.models import LogEntry +from colorfield.fields import ColorField +# From MARCO/utils.py + +import uuid + +def get_domain(port=8010): + try: + #domain = Site.objects.all()[0].domain + domain = Site.objects.get(id=SITE_ID).domain + if 'localhost' in domain: + domain = 'localhost:%s' %port + domain = 'http://' + domain + except: + domain = '..' + #print(domain) + return domain + +def reset_cache(sites): + from django.core.cache import cache + import requests + from requests.exceptions import ConnectionError + for site in sites: + cache.delete('data_manager_json_site_%s' % site.pk) + from marco.settings import DEBUG + if DEBUG and ('localhost:' in site.domain or '127.0.0.1:' in site.domain): + url = "http://%s:8000/data_manager/get_json" % site.domain[:site.domain.index(':')] + else: + url = "http://%s/data_manager/get_json" % site.domain + try: + requests.get(url) + except ConnectionError: + #sometimes testing overdoes this a bit and we get 'Max retries exceeded' + print('recache error - either port isn\'t listening or you\'ve maxed out your retries') + +class SiteFlags(object):#(models.Model): + """Add-on class for displaying sites in the list_display + in the admin. + """ + def primary_site(self): + return self.site.filter(id=1).exists() + primary_site.boolean = True + + def preview_site(self): + return self.site.filter(id=2).exists() + preview_site.boolean = True + +class AllObjectsManager(models.Manager): + use_in_migrations = True + +class Theme(models.Model, SiteFlags): + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + site = models.ManyToManyField(Site) + display_name = models.CharField(max_length=100) + name = models.CharField(max_length=100) + order = models.PositiveSmallIntegerField(default=10, blank=True, null=True, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)') + visible = models.BooleanField(default=True) + header_image = models.CharField(max_length=255, blank=True, null=True) + header_attrib = models.CharField(max_length=255, blank=True, null=True) + overview = models.TextField(blank=True, null=True) + description = models.TextField(blank=True, null=True) + thumbnail = models.URLField(max_length=255, blank=True, null=True) + + factsheet_thumb = models.CharField(max_length=255, blank=True, null=True) + factsheet_link = models.CharField(max_length=255, blank=True, null=True) + + date_created = models.DateTimeField(auto_now_add=True) + date_modified = models.DateTimeField(auto_now=True) + + # not really using these atm + feature_image = models.CharField(max_length=255, blank=True, null=True) + feature_excerpt = models.TextField(blank=True, null=True) + feature_link = models.CharField(max_length=255, blank=True, null=True) + + # objects = models.Manager() + objects = CurrentSiteManager('site') + all_objects = AllObjectsManager() + + def url(self): + id = self.id + return '/visualize/#x=-73.24&y=38.93&z=7&logo=true&controls=true&basemap=Ocean&themes[ids][]=%s&tab=data&legends=false&layers=true' % (id) + + def __unicode__(self): + return unicode('%s' % (self.name)) + + def __str__(self): + return str(self.name) + + @property + def learn_link(self): + domain = get_domain(8000) + return '%s/learn/%s' %(domain, self.name) + + def dictCache(self, site_id=None): + from django.core.cache import cache + themes_dict = None + if site_id in [x.id for x in self.site.all()]: + if site_id: + themes_dict = cache.get('data_manager_theme_%d_%d' % (self.id, site_id)) + if not themes_dict: + themes_dict = self.toDict + themes_dict['layers'] = [layer.id for layer in Layer.all_objects.filter(site__in=[site_id],is_sublayer=False,themes__in=[self.id]).exclude(layer_type='placeholder').order_by('order', 'name')] + if site_id: + # Cache for 1 week, will be reset if layer data changes + cache.set('data_manager_theme_%d_%d' % (self.id, site_id), themes_dict, 60*60*24*7) + else: + for site in Site.objects.all(): + cache.set('data_manager_theme_%d_%d' % (self.id, site.id), themes_dict, 60*60*24*7) + + return themes_dict + + + @property + def toDict(self): + layers = [layer.id for layer in Layer.objects.filter(is_sublayer=False,sublayers__in=[self.id]).exclude(layer_type='placeholder')] + themes_dict = { + 'id': self.id, + 'name': self.name, + 'display_name': self.display_name, + 'learn_link': self.learn_link, + 'is_visible': self.visible, + 'layers': layers, + 'description': self.description + } + + return themes_dict + + def getInitDict(self): + theme_dict = { + 'id': self.id, + 'name': self.name, + 'display_name': self.display_name, + 'is_visible': self.visible, + } + + return theme_dict + + def save(self, *args, **kwargs): + from django.core.cache import cache + for site in Site.objects.all(): + cache.delete('data_manager_json_site_%s' % site.pk) + # 'data_manager_theme_%d_%d' % (self.id, site_id) + if self.id: + cache.delete('data_manager_theme_%d_%d' % (self.id, site.pk)) + super(Theme, self).save(*args, **kwargs) + + class Meta: + app_label = 'data_manager' + +class Layer(models.Model, SiteFlags): + + WMS_VERSION_CHOICES = ( + (None, ''), + ('1.0.0', '1.0.0'), + ('1.1.0', '1.1.0'), + ('1.1.1', '1.1.1'), + ('1.3.0', '1.3.0'), + ) + COLOR_PALETTE = [] + + COLOR_PALETTE.append(("#FFFFFF", 'white')) + COLOR_PALETTE.append(("#888888", 'gray')) + COLOR_PALETTE.append(("#000000", 'black')) + COLOR_PALETTE.append(("#FF0000", 'red')) + COLOR_PALETTE.append(("#FFFF00", 'yellow')) + COLOR_PALETTE.append(("#00FF00", 'green')) + COLOR_PALETTE.append(("#00FFFF", 'cyan')) + COLOR_PALETTE.append(("#0000FF", 'blue')) + COLOR_PALETTE.append(("#FF00FF", 'magenta')) + + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + site = models.ManyToManyField(Site) + ###################################################### + # BASIC INFO # + ###################################################### + #name you wish to give layer, readable in the tool + name = models.CharField(max_length=100) + #XYZ, WMS, ArcRest, radio, checkbox, Vector, Vectortile, placeholder + layer_type = models.CharField(max_length=50, choices=settings.LAYER_TYPE_CHOICES, help_text='use placeholder to temporarily remove layer from TOC') + #required for XYZ, WMS, ArcRest, Vector and Vectortile, endpoint for webserver + #XYZ: will contain x,y,z somewhere in the url, each map tile called separately + #WMS: urls vary wildly, often have wms in the URL + #Arcrest: must end in "/export" + #Vector: likely will end with series of arguments after a "?" including "format=json" or "f=json" + #Vectortile: uses tiles and provides template for intended file using x,y,z in URL + url = models.TextField(blank=True, null=True) + proxy_url = models.BooleanField(default=False, help_text="proxy layer url through marine planner") + + ###################################################### + # LAYER ORGANIZATION # + ###################################################### + #putting layers in order under a theme or sublayers in order under a layer is managed by assigning every layer "order" value + order = models.PositiveSmallIntegerField(default=10, blank=True, null=True, help_text='input an integer to determine the priority/order of the layer being displayed (1 being the highest)') + themes = models.ManyToManyField("Theme", blank=True) + is_sublayer = models.BooleanField(default=False) + sublayers = models.ManyToManyField('self', blank=True) + has_companion = models.BooleanField(default=False, help_text='Check if this layer has a companion layer') + connect_companion_layers_to = models.ManyToManyField('self', blank=True, help_text='Select which main layer(s) you would like to use in conjuction with this companion layer.') + + ###################################################### + # METADATA # + ###################################################### + description = models.TextField(blank=True, null=True) + data_overview = models.TextField(blank=True, null=True) + data_source = models.CharField(max_length=255, blank=True, null=True) + data_notes = models.TextField(blank=True, null=True) + data_publish_date = models.DateField(auto_now=False, auto_now_add=False, null=True, blank=True, default=None, verbose_name='Date published', help_text='YYYY-MM-DD') + + ###################################################### + # LEGEND # + ###################################################### + show_legend = models.BooleanField(default=True, help_text='show the legend for this layer if available') + legend = models.CharField(max_length=255, blank=True, null=True, help_text='URL or path to the legend image file') + legend_title = models.CharField(max_length=255, blank=True, null=True, help_text='alternative to using the layer name') + legend_subtitle = models.CharField(max_length=255, blank=True, null=True) + + ###################################################### + # LINKS # + ###################################################### + metadata = models.CharField(max_length=255, blank=True, null=True, help_text='link to view/download the metadata') + source = models.CharField(max_length=255, blank=True, null=True, help_text='link back to the data source') + bookmark = models.CharField(max_length=755, blank=True, null=True, help_text='link to view data layer in the planner') + kml = models.CharField(max_length=255, blank=True, null=True, help_text='link to download the KML') + data_download = models.CharField(max_length=255, blank=True, null=True, help_text='link to download the data') + learn_more = models.CharField(max_length=255, blank=True, null=True, default=None, help_text='link to view description in the Learn section') + map_tiles = models.CharField(max_length=255, blank=True, null=True, help_text='internal link to a page that details how others might consume the data') + + + slug_name = models.CharField(max_length=200, blank=True, null=True) + + ###################################################### + # SHARING # + ###################################################### + shareable_url = models.BooleanField(default=True, help_text='Indicates whether the data layer (e.g. map tiles) can be shared with others (through the Map Tiles Link)') + + ###################################################### + # ArcGIS Details # + ###################################################### + arcgis_layers = models.CharField(max_length=255, blank=True, null=True, help_text='comma separated list of arcgis layer IDs') + password_protected = models.BooleanField(default=False, help_text='check this if the server requires a password to show layers') + query_by_point = models.BooleanField(default=False, help_text='Do not buffer selection clicks (not recommended for point or line data)') + disable_arcgis_attributes = models.BooleanField(default=False, help_text='Click to disable clickable ArcRest layers') + + ###################################################### + # WMS Details # + ###################################################### + wms_help = models.BooleanField(default=False, help_text='Enable simple selection for WMS fields. Only supports WMS 1.1.1') + wms_slug = models.CharField(max_length=255, blank=True, null=True, verbose_name='WMS Layer Name') + wms_version = models.CharField(max_length=10, blank=True, null=True, default=None, choices=WMS_VERSION_CHOICES, help_text='WMS Versioning - usually either 1.1.1 or 1.3.0') + wms_format = models.CharField(max_length=100, blank=True, null=True, default=None, help_text='most common: image/png. Only image types supported.', verbose_name='WMS Format') + wms_srs = models.CharField(max_length=100, blank=True, null=True, default=None, help_text='If not EPSG:3857 WMS requests will be proxied', verbose_name='WMS SRS') + wms_timing = models.CharField(max_length=255, blank=True, null=True, default=None, help_text='http://docs.geoserver.org/stable/en/user/services/wms/time.html#specifying-a-time', verbose_name='WMS Time') + wms_time_item = models.CharField(max_length=255, blank=True, null=True, default=None, help_text='Time Attribute Field, if different from "TIME". Proxy only.', verbose_name='WMS Time Field') + wms_styles = models.CharField(max_length=255, blank=True, null=True, default=None, help_text='pre-determined styles, if exist', verbose_name='WMS Styles') + wms_additional = models.TextField(blank=True, null=True, default=None, help_text='additional WMS key-value pairs: &key=value...', verbose_name='WMS Additional Fields') + wms_info = models.BooleanField(default=False, help_text='enable Feature Info requests on click') + wms_info_format = models.CharField(max_length=255, blank=True, null=True, default=None, help_text='Available supported feature info formats') + + ###################################################### + # DYNAMIC LAYERS(MDAT & CAS) # + ###################################################### + search_query = models.BooleanField(default=False, help_text='Select when layers are queryable - e.g. MDAT and CAS') + + ###################################################### + # UTF Grid Layers # + ###################################################### + utfurl = models.CharField(max_length=255, blank=True, null=True) + + ###################################################### + # Attribute Reporting # + ###################################################### + label_field = models.CharField(max_length=255, blank=True, null=True, help_text="Which field should be used for labels and feature identification in reports?") + #geojson javascript attribution + EVENT_CHOICES = ( + ('click', 'click'), + ('mouseover', 'mouseover') + ) + # RDH: Adds a 'title' to the serialize_attributes dict - not sure if that's used. + # attribute_title = models.CharField(max_length=255, blank=True, null=True) + attribute_event = models.CharField(max_length=35, choices=EVENT_CHOICES, default='click') + attribute_fields = models.ManyToManyField('AttributeInfo', blank=True) + #feature level attribute used in mouseover display + mouseover_field = models.CharField(max_length=75, blank=True, null=True, default=None, help_text='feature level attribute used in mouseover display') + + is_annotated = models.BooleanField(default=False) + compress_display = models.BooleanField(default=False) + ###################################################### + # DISPLAY & STYLE # + ###################################################### + #default opacity, somewhat transparent (.5) + opacity = models.FloatField(default=.5, blank=True, null=True, verbose_name="Initial Opacity") + minZoom = models.FloatField(blank=True, null=True, default=None, verbose_name="Minimum zoom") + maxZoom = models.FloatField(blank=True, null=True, default=None, verbose_name="Maximum zoom") + CUSTOM_STYLE_CHOICES = ( + (None, '------'), + ('color', 'color'), + ('random', 'random'), + ) + custom_style = models.CharField( + max_length=255, + null=True, blank=True, default=None, + choices=CUSTOM_STYLE_CHOICES, + help_text="Apply a custom styling rule: i.e. 'color' for Native-Land.ca layers, or 'random' to assign arbitary colors" + ) + #width of layer's features' lines/outlines in pixels + vector_outline_width = models.IntegerField(blank=True, null=True, default=None, verbose_name="Vector Stroke Width") + #sets the color of the layer's features' lines or outlines, can be either color's name or hex value (Starts with #) + vector_outline_color = ColorField( + blank=True, + null=True, + default=None, + verbose_name="Vector Stroke Color", + samples=COLOR_PALETTE, + ) + # RDH 20191106 - This is not a thing. + vector_outline_opacity = models.FloatField(blank=True, null=True, default=None, verbose_name="Vector Stroke Opacity") + + #set the color to fill any polygons or circle-icons for points + vector_fill = models.FloatField(blank=True, null=True, default=None, verbose_name="Vector Fill Opacity") + vector_color = ColorField( + blank=True, + null=True, + default=None, + verbose_name="Vector Fill Color", + samples=COLOR_PALETTE, + ) + #set radius of circle in pixels, only applies to point data with no graphics + point_radius = models.IntegerField(blank=True, null=True, default=None, help_text='Used only for for Point layers (default is 2)') + #enter URL for image from online for layer's point data + vector_graphic = models.CharField(max_length=255, blank=True, null=True, default=None, verbose_name="Vector Graphic", help_text="address of image to use for point data") + #if you need to resize vector graphic image so it looks appropriate on map + #to make image smaller, use value less than 1, to make image larger, use values larger than 1 + vector_graphic_scale = models.FloatField(blank=True, null=True, default=True, verbose_name="Vector Graphic Scale", help_text="Scale for the vector graphic from original size.") + + #use field to specify attribute on layer that you wish to be considered in adding conditional style formatting + lookup_field = models.CharField(max_length=255, blank=True, null=True, help_text="To override the style based on specific attributes, provide the attribute name here and define your attributes in the Lookup table below.") + #use widget along with creating Lookup Info records to apply conditional styling to your layer + lookup_table = models.ManyToManyField('LookupInfo', blank=True) + + objects = CurrentSiteManager('site') + all_objects = AllObjectsManager() + + ###################################################### + # ESPIS # + ###################################################### + #ESPIS Upgrade - RDH 7/23/2017 + espis_enabled = models.BooleanField(default=False) + ESPIS_REGION_CHOICES = ( + ('Mid Atlantic', 'Mid Atlantic'), + ) + espis_search = models.CharField(max_length=255, blank=True, null=True, default=None, help_text="keyphrase search for ESPIS Link") + espis_region = models.CharField(max_length=100, blank=True, null=True, default=None, choices=ESPIS_REGION_CHOICES, help_text="Region to search within") + + ###################################################### + # DATES # + ###################################################### + date_created = models.DateTimeField(auto_now_add=True) + date_modified = models.DateTimeField(auto_now=True) + + + is_disabled = models.BooleanField(default=False, help_text='when disabled, the layer will still appear in the TOC, only disabled') + disabled_message = models.CharField(max_length=255, blank=True, null=True, default=None) + + # RDH: utfjsonp does not appear to be used. + # utfjsonp = models.BooleanField(default=False) + # RDH: summarize_to_grid does not appear to be used. + # summarize_to_grid = models.BooleanField(default=False) + # RDH: filterable is used in planner.html and filters.html, regarding visibility + # TODO: need to identify how/why this is used and integrate into ocean_portal code base + # Filterable is used for 'beach cleanup' and 'derelict gear' layers. + filterable = models.BooleanField(default=False) + # RDH: geoportal_id is used in data_manager view 'geoportal_ids', which is never used + geoportal_id = models.CharField(max_length=255, blank=True, null=True, default=None, help_text="GeoPortal UUID") + # RDH: proj does not appear to be used. + # proj = models.CharField(max_length=255, blank=True, null=True, help_text="will be EPSG:3857, if unspecified") + + #data catalog links + catalog_name = models.TextField(null=True, blank=True, help_text="name of associated record in catalog", verbose_name='Catalog Record Name') + catalog_id = models.TextField(null=True, blank=True, help_text="unique ID of associated record in catalog", verbose_name='Catalog Record Id') + + thumbnail = models.URLField(max_length=255, blank=True, null=True, default=None, help_text='not sure we are using this any longer...') + + + def __unicode__(self): + return unicode('%s' % (self.name)) + + def __str__(self): + return str(self.name) + + @property + def is_parent(self): + return self.sublayers.all().count() > 0 and not self.is_sublayer + + # Currently parent layer is stored within sublayers, making nesting impossible + @property + def parent(self): + if self.is_sublayer: + if self.sublayers.all().count() > 0: + return self.sublayers.all()[0] + else: + return None + return self + + @property + def last_change(self): + layer_ct = ContentType.objects.get(model='layer') + logs = LogEntry.objects.filter(content_type=layer_ct, object_id=self.pk) + if len(logs) > 0: + last_log = logs.order_by('-action_time')[0] + return last_log.action_time + else: + return None + + def get_absolute_url(self): + if settings.DATA_CATALOG_ENABLED: + theme = self.themes.filter(visible=True).first() + if theme: + theme_url = reverse('portal.data_catalog.views.theme', args=[theme.name]) + if theme_url: + return "{0}#layer-info-{1}".format(theme_url, self.slug_name) + return None + + @property + def slug(self): + # RDH Hack for MDAT v2 transition 8/8/2018. + # Slug just takes name, but if name is the same then multiple layers have same slug. Should slug include ID? + if self.slug_name and ('-v2-prod' in self.slug_name or '-v2-staging' in self.slug_name): + slug_string = "%s-v2%s" % (slugify(self.name),self.slug_name.split('v2')[1]) + return slug_string + return slugify(self.name) + + @property + def data_overview_text(self): + if not self.data_overview and self.is_sublayer and self.parent: + return self.parent.data_overview + else: + return self.data_overview + + @property + def data_source_text(self): + if not self.data_source and self.is_sublayer: + return self.parent.data_source + else: + return self.data_source + + @property + def data_notes_text(self): + if not self.data_notes and self.is_sublayer: + return self.parent.data_notes + else: + return self.data_notes + + @property + def bookmark_link(self): + if self.bookmark and "%%5D=%d&" % self.id in self.bookmark: + return self.bookmark + + if self.is_sublayer and self.parent.bookmark and len(self.parent.bookmark) > 0: + return self.parent.bookmark.replace('', str(self.id)) + + if self.is_parent: + for theme in self.themes.all(): + return theme.url() + + # RDH: Most Marine Life layers seem to have bogus bookmarks. If the first line of this def + # isn't true, then we likely need to give users something that will work. This should do it. + root_str = '/visualize/#x=-73.24&y=38.93&z=7&logo=true&controls=true&basemap=Ocean' + layer_str = '&dls%%5B%%5D=true&dls%%5B%%5D=%s&dls%%5B%%5D=%d' % (str(self.opacity), self.id) + companion_str = '' + if self.has_companion: + for companion in self.connect_companion_layers_to.all(): + companion_str += '&dls%%5B%%5D=false&dls%%5B%%5D=%s&dls%%5B%%5D=%d' % (str(companion.opacity), companion.id) + themes_str = '' + if self.themes.all().count() > 0: + for theme in self.themes.all(): + themes_str = '&themes%%5Bids%%5D%%5B%%5D=%d' % theme.id + + panel_str = '&tab=data&legends=false&layers=true' + + return "%s%s%s%s%s" % (root_str, layer_str, companion_str, themes_str, panel_str) + + @property + def data_download_link(self): + if self.data_download and self.data_download.lower() == 'none': + return None + if self.parent and not self.data_download and self.is_sublayer: + return self.parent.data_download + else: + return self.data_download + + @property + def metadata_link(self): + if self.metadata and self.metadata.lower() == 'none': + return None + if not self.metadata: + if self.is_sublayer and self.parent: + return self.parent.metadata + else: + return None + else: + return self.metadata + + @property + def source_link(self): + if self.source and self.source.lower() == 'none': + return None + if not self.source: + if self.is_sublayer and self.parent: + return self.parent.source + else: + return None + else: + return self.source + + @property + def description_link(self): + theme_name = self.themes.all()[0].name + domain = get_domain(8000) + return '%s/learn/%s#%s' %(domain, theme_name, self.slug_name) + + @property + def tiles_link(self): + if self.is_shareable and self.layer_type in ['XYZ', 'ArcRest', 'WMS']: + domain = get_domain(8000) + return self.slug_name + return None + + @property + def tooltip(self): + if self.description and self.description.strip() != '': + return self.description + elif self.parent and self.parent.description and self.parent.description.strip() != '': + return self.parent.description + else: + return self.data_overview_text + + @property + def is_shareable(self): + if self.shareable_url == False: + return False + if self.parent and self.parent.shareable_url == False: + return False + return True + + def serialize_attributes(self): + return {'compress_attributes': self.compress_display, + 'event': self.attribute_event, + 'attributes': [{'display': attr.display_name, 'field': attr.field_name, 'precision': attr.precision} for attr in self.attribute_fields.all().order_by('order')], + 'mouseover_attribute': self.mouseover_field, + 'preserved_format_attributes': [attr.field_name for attr in self.attribute_fields.filter(preserve_format=True)] + } + + @property + def serialize_lookups(self): + return {'field': self.lookup_field, + 'details': [{'value': lookup.value, 'color': lookup.color, 'stroke_color': lookup.stroke_color, 'stroke_width': lookup.stroke_width, 'dashstyle': lookup.dashstyle, 'fill': lookup.fill, 'graphic': lookup.graphic, 'graphic_scale': lookup.graphic_scale} for lookup in self.lookup_table.all()]} + + def get_espis_link(self): + if self.espis_enabled: + search_dict = {} + if self.espis_search: + search_dict['txt'] = self.espis_search + if self.espis_region: + search_dict['geo'] = self.espis_region + if len(search_dict) > 0: + try: + # python 3 + from urllib.parse import urlencode + except (ModuleNotFoundError, ImportError) as e: + #python 2 + from urllib import urlencode + return 'https://marinecadastre.gov/espis/#/search/%s' % urlencode(search_dict) + return None + + def dimensionRecursion(self, dimensions, associations): + associationArray = {} + dimension = dimensions.pop(0) + for value in sorted(dimension.multilayerdimensionvalue_set.all(), key=lambda x: x.order): + value_associations = associations.filter(pk__in=[x.pk for x in value.associations.all()]) + if len(dimensions) > 0: + associationArray[str(value.value)] = self.dimensionRecursion(list(dimensions), value_associations) + else: + if len(value_associations) == 1 and value_associations[0].layer: + associationArray[str(value.value)] = value_associations[0].layer.pk + else: + associationArray[str(value.value)] = None + return associationArray + + @property + def isMultilayerParent(self): + return len(self.multilayerdimension_set.all()) > 0 + + @property + def isMultilayer(self): + return len(self.associated_layer.all()) > 0 + + @property + def dimensions(self): + return sorted([ + { + 'label': x.label, + 'name': x.name, + 'order': x.order, + 'animated': x.animated, + 'angle_labels': x.angle_labels, + 'nodes': sorted([ + { + 'value': y.value, + 'label': y.label, + 'order': y.order + } + for y in x.multilayerdimensionvalue_set.all() + ], key=lambda y: y['order']) + } + for x in self.multilayerdimension_set.all() + ], key=lambda x: x['order']) + + @property + def catalog_html(self): + from django.template.loader import render_to_string + try: + return render_to_string( + "data_catalog/includes/cacheless_layer_info.html", + { + 'layer': self, + # 'sub_layers': self.sublayers.exclude(layer_type="placeholder") + } + ) + except Exception as e: + print(e) + + @property + def associatedMultilayers(self): + if len(self.multilayerdimension_set.all()) > 0: + return self.dimensionRecursion(sorted(self.multilayerdimension_set.all(), key=lambda x: x.order), self.parent_layer.all()) + else: + return {} + + def dictCache(self, site_id=None): + from django.core.cache import cache + layers_dict = None + if site_id in [x.id for x in self.site.all()]: + if site_id: + layers_dict = cache.get('data_manager_layer_%d_%d' % (self.id, site_id)) + if not layers_dict: + layers_dict = self.toDict + if site_id: + # Cache for 1 week, will be reset if layer data changes + cache.set('data_manager_layer_%d_%d' % (self.id, site_id), layers_dict, 60*60*24*7) + else: + for site in Site.objects.all(): + cache.set('data_manager_layer_%d_%d' % (self.id, site.id), layers_dict, 60*60*24*7) + return layers_dict + + @property + def toDict(self, site_id=None): + parent = self.parent + if parent == self: + parent = None + elif not parent == None: + try: + parent = parent.toDict + except Exception as e: + parent = None + sublayers = [ + { + 'id': layer.id, + 'uuid': layer.uuid, + 'is_sublayer': layer.is_sublayer, + 'name': layer.name, + 'order': layer.order, + 'type': layer.layer_type, + 'url': layer.url, + 'arcgis_layers': layer.arcgis_layers, + 'password_protected': layer.password_protected, + 'query_by_point': layer.query_by_point, + 'proxy_url': layer.proxy_url, + 'disable_arcgis_attributes': layer.disable_arcgis_attributes, + 'wms_slug': layer.wms_slug, + 'wms_version': layer.wms_version, + 'wms_format': layer.wms_format, + 'wms_srs': layer.wms_srs, + 'wms_styles': layer.wms_styles, + 'wms_timing': layer.wms_timing, + 'wms_time_item': layer.wms_time_item, + 'wms_additional': layer.wms_additional, + 'wms_info': layer.wms_info, + 'wms_info_format': layer.wms_info_format, + 'utfurl': layer.utfurl, + 'parent': self.id, + 'legend': layer.legend, + 'legend_title': layer.legend_title, + 'legend_subtitle': layer.legend_subtitle, + 'show_legend': layer.show_legend, + 'description': layer.tooltip, + 'overview': layer.data_overview_text, + 'data_source': layer.data_source, + 'data_notes': layer.data_notes, + 'kml': layer.kml, + 'data_download': layer.data_download_link, + 'learn_more': layer.learn_more, + 'metadata': layer.metadata_link, + 'source': layer.source_link, + 'tiles': layer.tiles_link, + 'label_field': layer.label_field, + 'attributes': layer.serialize_attributes(), + 'lookups': layer.serialize_lookups, + 'minZoom': layer.minZoom, + 'maxZoom': layer.maxZoom, + 'custom_style': layer.custom_style, + 'outline_color': layer.vector_outline_color, + 'outline_opacity': layer.vector_outline_opacity, + 'outline_width': layer.vector_outline_width, + 'point_radius': layer.point_radius, + 'color': layer.vector_color, + 'fill_opacity': layer.vector_fill, + 'graphic': layer.vector_graphic, + 'graphic_scale': layer.vector_graphic_scale, + 'opacity': layer.opacity, + 'annotated': layer.is_annotated, + 'is_disabled': layer.is_disabled, + 'disabled_message': layer.disabled_message, + 'data_url': layer.get_absolute_url(), + 'has_companion': layer.has_companion, + 'is_multilayer': layer.isMultilayer, + 'is_multilayer_parent': layer.isMultilayerParent, + 'dimensions': layer.dimensions, + 'associated_multilayers': layer.associatedMultilayers, + 'date_modified': layer.date_modified + } + for layer in self.sublayers.filter(is_sublayer=True) + ] + connect_companion_layers_to = [ + { + 'id': layer.id, + 'uuid': layer.uuid, + 'name': layer.name, + 'order': layer.order, + 'type': layer.layer_type, + 'url': layer.url, + 'arcgis_layers': layer.arcgis_layers, + 'password_protected': layer.password_protected, + 'query_by_point': layer.query_by_point, + 'proxy_url': layer.proxy_url, + 'disable_arcgis_attributes': layer.disable_arcgis_attributes, + 'wms_slug': layer.wms_slug, + 'wms_version': layer.wms_version, + 'wms_format': layer.wms_format, + 'wms_srs': layer.wms_srs, + 'wms_styles': layer.wms_styles, + 'wms_timing': layer.wms_timing, + 'wms_time_item': layer.wms_time_item, + 'wms_additional': layer.wms_additional, + 'wms_info': layer.wms_info, + 'wms_info_format': layer.wms_info_format, + 'utfurl': layer.utfurl, + 'parent': self.id, + 'legend': layer.legend, + 'legend_title': layer.legend_title, + 'legend_subtitle': layer.legend_subtitle, + 'show_legend': layer.show_legend, + 'description': layer.tooltip, + 'overview': layer.data_overview_text, + 'data_source': layer.data_source, + 'data_notes': layer.data_notes, + 'kml': layer.kml, + 'data_download': layer.data_download_link, + 'learn_more': layer.learn_more, + 'metadata': layer.metadata_link, + 'source': layer.source_link, + 'tiles': layer.tiles_link, + 'label_field': layer.label_field, + 'attributes': layer.serialize_attributes(), + 'lookups': layer.serialize_lookups, + 'minZoom': layer.minZoom, + 'maxZoom': layer.maxZoom, + 'custom_style': layer.custom_style, + 'outline_color': layer.vector_outline_color, + 'outline_opacity': layer.vector_outline_opacity, + 'outline_width': layer.vector_outline_width, + 'point_radius': layer.point_radius, + 'color': layer.vector_color, + 'fill_opacity': layer.vector_fill, + 'graphic': layer.vector_graphic, + 'graphic_scale': layer.vector_graphic_scale, + 'opacity': layer.opacity, + 'annotated': layer.is_annotated, + 'is_disabled': layer.is_disabled, + 'disabled_message': layer.disabled_message, + 'data_url': layer.get_absolute_url(), + 'has_companion': layer.has_companion, + 'is_multilayer': layer.isMultilayer, + 'is_multilayer_parent': layer.isMultilayerParent, + 'dimensions': layer.dimensions, + 'associated_multilayers': layer.associatedMultilayers, + 'date_modified': layer.date_modified + } + for layer in self.connect_companion_layers_to.all() + ] + layers_dict = { + 'id': self.id, + 'uuid': self.uuid, + 'name': self.name, + 'order': self.order, + 'type': self.layer_type, + 'url': self.url, + 'arcgis_layers': self.arcgis_layers, + 'password_protected': self.password_protected, + 'query_by_point': self.query_by_point, + 'proxy_url': self.proxy_url, + 'disable_arcgis_attributes': self.disable_arcgis_attributes, + 'wms_slug': self.wms_slug, + 'wms_version': self.wms_version, + 'wms_format': self.wms_format, + 'wms_srs': self.wms_srs, + 'wms_styles': self.wms_styles, + 'wms_timing': self.wms_timing, + 'wms_time_item': self.wms_time_item, + 'wms_additional': self.wms_additional, + 'wms_info': self.wms_info, + 'wms_info_format': self.wms_info_format, + 'utfurl': self.utfurl, + 'subLayers': sublayers, + 'companion_layers': connect_companion_layers_to, + 'has_companion': self.has_companion, + 'queryable': self.search_query, + 'legend': self.legend, + 'legend_title': self.legend_title, + 'legend_subtitle': self.legend_subtitle, + 'show_legend': self.show_legend, + 'description': self.description, + 'overview': self.data_overview, + 'data_source': self.data_source, + 'data_notes': self.data_notes, + 'kml': self.kml, + 'data_download': self.data_download_link, + 'learn_more': self.learn_more, + 'metadata': self.metadata_link, + 'source': self.source_link, + 'tiles': self.tiles_link, + 'label_field': self.label_field, + 'attributes': self.serialize_attributes(), + 'lookups': self.serialize_lookups, + 'minZoom': self.minZoom, + 'maxZoom': self.maxZoom, + 'custom_style': self.custom_style, + 'outline_color': self.vector_outline_color, + 'outline_opacity': self.vector_outline_opacity, + 'outline_width': self.vector_outline_width, + 'point_radius': self.point_radius, + 'color': self.vector_color, + 'fill_opacity': self.vector_fill, + 'graphic': self.vector_graphic, + 'graphic_scale': self.vector_graphic_scale, + 'opacity': self.opacity, + 'annotated': self.is_annotated, + 'is_disabled': self.is_disabled, + 'disabled_message': self.disabled_message, + 'data_url': self.get_absolute_url(), + 'is_multilayer': self.isMultilayer, + 'is_multilayer_parent': self.isMultilayerParent, + 'dimensions': self.dimensions, + 'associated_multilayers': self.associatedMultilayers, + 'catalog_html': self.catalog_html, + 'parent': parent, + 'date_modified': self.date_modified + } + + return layers_dict + + def catalogDict(self, site_id=None): + parent = self.parent + if parent == self: + parent = None + elif not parent == None: + try: + parent = { + 'id':parent.id, + 'name': parent.name, + } + except Exception as e: + parent = None + + sublayers = [sublayer.catalogDict(site_id) for sublayer in self.sublayers.filter(is_sublayer=True).order_by('order')] + # companions = [companion.catalogDict(site_id) for companion in self.connect_companion_layers_to.all().order_by('order')] + layers_dict = { + 'id': self.id, + 'name': self.name, + 'slug_name': self.slug_name, + 'bookmark_link': self.bookmark_link, + 'is_sublayer': self.is_sublayer, + 'parent': parent, + 'kml': self.kml, + 'data_download_link': self.data_download_link, + 'metadata_link': self.metadata_link, + 'source': self.source_link, + 'tiles_link': self.tiles_link, + 'description': self.description, + 'data_overview': self.data_overview, + 'espis_enabled': self.espis_enabled, + 'espis_search': self.espis_search, + 'espis_region': self.espis_region, + 'get_espis_link': self.get_espis_link, + 'sublayers': sublayers, + # 'companions': companions + } + + return layers_dict + + def shortDict(self, site_id=None): + sublayers = [{ + 'id':sublayer.id, + 'parent': {'name':self.name}, + 'name':sublayer.name, + 'slug_name': sublayer.slug_name, + 'bookmark_link': sublayer.bookmark_link, + 'is_sublayer': True, + 'sublayers': [], + } for sublayer in self.sublayers.filter(is_sublayer=True).order_by('name')] + # sublayers = [sublayer.shortDict(site_id) for sublayer in self.sublayers.filter(is_sublayer=True).order_by('order')] + # companions = [{ + # 'id':companion.id, + # 'parent': {'name':self.name}, + # 'name':companion.name, + # 'slug_name': companion.slug_name, + # 'bookmark_link': companion.bookmark_link, + # 'is_sublayer': companion.is_sublayer, + # 'sublayers': [], + # } for companion in self.connect_companion_layers_to.all().order_by('name')] + layers_dict = { + 'id': self.id, + 'parent': None, + 'name': self.name, + 'slug_name': self.slug_name, + 'bookmark_link': self.bookmark_link, + 'is_sublayer': self.is_sublayer, + 'sublayers': sublayers, + # 'companions': companions, + } + return layers_dict + + def save(self, *args, **kwargs): + from django.core.cache import cache + if 'slug_name' in kwargs.keys(): + self.slug_name = kwargs['slug_name'] + kwargs.pop('slug_name', None) + else: + if self.id: + self.slug_name = '%s%d' % (self.slug, self.id) + else: + self.slug_name = '%s_new' % self.slug + if self.url == None: + self.url = '' + if 'recache' in kwargs.keys(): + kwargs.pop('recache', None) + # TODO: determine all themes, companions, ancestors, and decendants prior to saving + # clear all of their caches. + # How do we do this thoroughly? + # How do we avoid infinite loops? (companions)(recursion?) + super(Layer, self).save(*args, **kwargs) + for site in Site.objects.all(): + cache.delete('data_manager_json_site_%s' % site.pk) + cache.delete('data_manager_layer_%d_%d' % (self.id, site.pk)) + self.dictCache(site.pk) + # Delete cache for all sublayers + for sublayer in self.sublayers.all(): + cache.delete('data_manager_layer_%d_%d' % (sublayer.id, site.pk)) + sublayer.dictCache(site.pk) + # Delete cache for parent layers (in case not double-linked) + for parentlayer in Layer.objects.filter(sublayers__in=[self]): + cache.delete('data_manager_layer_%d_%d' % (parentlayer.id, site.pk)) + parentlayer.dictCache(site.pk) + # Delete cache for companion layers + for companion in self.connect_companion_layers_to.all(): + cache.delete('data_manager_layer_%d_%d' % (companion.id, site.pk)) + companion.dictCache(site.pk) + for companion in Layer.objects.filter(connect_companion_layers_to__in=[self]): + cache.delete('data_manager_layer_%d_%d' % (companion.id, site.pk)) + companion.dictCache(site.pk) + for association in self.associated_layer.all(): + cache.delete('data_manager_layer_%d_%d' % (association.parentLayer.pk, site.pk)) + association.layer.dictCache(site.pk) + # TODO: if len(self.themes.all() == 0): delete all theme caches? + # On initial save, layers don't seem to know what themes they are associated with. :( + for theme in self.themes.all(): + cache.delete('data_manager_theme_%d_%d' % (theme.pk, site.pk)) + theme.dictCache(site.pk) + +class AttributeInfo(models.Model): + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + display_name = models.CharField(max_length=255, blank=True, null=True) + field_name = models.CharField(max_length=255, blank=True, null=True) + precision = models.IntegerField(blank=True, null=True) + order = models.IntegerField(default=1) + preserve_format = models.BooleanField(default=False, help_text='Prevent portal from making any changes to the data to make it human-readable') + + def __unicode__(self): + return unicode('%s' % (self.field_name)) + + def __str__(self): + return str(self.field_name) + +class LookupInfo(models.Model): + DASH_CHOICES = ( + ('dot', 'dot'), + ('dash', 'dash'), + ('dashdot', 'dashdot'), + ('longdash', 'longdash'), + ('longdashdot', 'longdashdot'), + ('solid', 'solid') + ) + COLOR_PALETTE = [] + + COLOR_PALETTE.append(("#FFFFFF", 'white')) + COLOR_PALETTE.append(("#888888", 'gray')) + COLOR_PALETTE.append(("#000000", 'black')) + COLOR_PALETTE.append(("#FF0000", 'red')) + COLOR_PALETTE.append(("#FFFF00", 'yellow')) + COLOR_PALETTE.append(("#00FF00", 'green')) + COLOR_PALETTE.append(("#00FFFF", 'cyan')) + COLOR_PALETTE.append(("#0000FF", 'blue')) + COLOR_PALETTE.append(("#FF00FF", 'magenta')) + + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + value = models.CharField(max_length=255, blank=True, null=True) + description = models.CharField(max_length=255, blank=True, null=True, default=None) + color = ColorField( + blank=True, + null=True, + default=None, + verbose_name="Fill Color", + samples=COLOR_PALETTE, + ) + stroke_color = ColorField( + blank=True, + null=True, + default=None, + verbose_name="Stroke Color", + samples=COLOR_PALETTE, + ) + stroke_width = models.IntegerField(null=True, blank=True, default=None, verbose_name="Stroke Width") + dashstyle = models.CharField(max_length=11, choices=DASH_CHOICES, default='solid') + fill = models.BooleanField(default=False) + graphic = models.CharField(max_length=255, blank=True, null=True) + graphic_scale = models.FloatField(null=True, blank=True, default=None, verbose_name="Graphic Scale", help_text="Scale the graphic from its original size.") + + def __unicode__(self): + if self.description: + return unicode('{}: {}'.format(self.value, self.description)) + return unicode('%s' % (self.value)) + + def __str__(self): + if self.description: + return '{}: {}'.format(self.value, self.description) + return str(self.value) + +class DataNeed(models.Model): + name = models.CharField(max_length=100) + archived = models.BooleanField(default=False) + description = models.TextField(blank=True, null=True) + source = models.CharField(max_length=255, blank=True, null=True) + status = models.TextField(blank=True, null=True) + contact = models.CharField(max_length=255, blank=True, null=True) + contact_email = models.CharField(max_length=255, blank=True, null=True) + expected_date = models.CharField(max_length=255, blank=True, null=True) + notes = models.TextField(blank=True, null=True) + themes = models.ManyToManyField("Theme", blank=True) + + @property + def html_name(self): + return self.name.lower().replace(' ', '-') + + def __unicode__(self): + return unicode('%s' % (self.name)) + + def __str__(self): + return str(self.name) + +class MultilayerDimension(models.Model): + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + name = models.CharField(max_length=200, help_text='name to be used for selection in admin tool forms') + label = models.CharField(max_length=50, help_text='label to be used in mapping tool slider') + order = models.IntegerField(default=100, help_text='the order in which this dimension will be presented among other dimensions on this layer') + animated = models.BooleanField(default=False, help_text='enable auto-toggling of layers across this dimension') + angle_labels = models.BooleanField(default=False, help_text='display labels at an angle to make more fit') + layer = models.ForeignKey(Layer, on_delete=models.CASCADE) + + def __unicode__(self): + return self.name + + def __str__(self): + return str(self.name) + + class Meta: + ordering = ('order',) + + def save(self, *args, **kwargs): + super(MultilayerDimension, self).save(*args, **kwargs) + + def delete(self, *args, **kwargs): + if len(self.layer.dimensions) == 1: + last = True + else: + last = False + for value in self.multilayerdimensionvalue_set.all().order_by('-order'): + value.delete((),last=last) + super(MultilayerDimension, self).delete(*args, **kwargs) + +class MultilayerAssociation(models.Model): + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + name = models.CharField(max_length=200) + parentLayer = models.ForeignKey(Layer, related_name="parent_layer", + db_column='parentlayer', on_delete=models.CASCADE) + layer = models.ForeignKey(Layer, null=True, blank=True, default=None, + related_name="associated_layer", db_column='associatedlayer', + on_delete=models.SET_NULL) + + def __unicode__(self): + return self.name + + def __str__(self): + return str(self.name) + + # def save(self, *args, **kwargs): + # super(MultilayerAssociation, self).save(*args, **kwargs) + # print("Association: %s +++SAVED+++" % str(self)) + # + # def delete(self, *args, **kwargs): + # super(MultilayerAssociation, self).delete(*args, **kwargs) + # print("Association: %s ---DELETED---" % str(self)) + +class MultilayerDimensionValue(models.Model): + uuid = models.UUIDField(default=uuid.uuid4, unique=True) + dimension = models.ForeignKey(MultilayerDimension, on_delete=models.CASCADE) + value = models.CharField(max_length=200, help_text="Actual value of selection") + label = models.CharField(max_length=50, help_text="Label for this selection seen in mapping tool slider") + order = models.IntegerField(default=100) + associations = models.ManyToManyField(MultilayerAssociation) + + def __unicode__(self): + return '%s: %s' % (self.dimension, self.value) + + def __str__(self): + return '%s: %s' % (self.dimension, self.value) + + class Meta: + ordering = ('order',) + + def save(self, *args, **kwargs): + if self.pk is None: + super(MultilayerDimensionValue, self).save(*args, **kwargs) + parentLayer = self.dimension.layer + associations = MultilayerAssociation.objects.filter(parentLayer=parentLayer) + if len(associations) == 0: + MultilayerAssociation.objects.create(name=str(self), parentLayer=parentLayer) + associations.update() + siblingValues = [x for x in self.dimension.multilayerdimensionvalue_set.all() if x != self] + if len(siblingValues) == 0: + for association in associations: + self.associations.add(association) + else: + # If this is not the first value saved to this dimension, choosing + # an arbitrary sibling value and copying all of its associations + # is the closest thing we can do to smart generation of associations + from copy import deepcopy + siblingValue = siblingValues[0] + for association in siblingValue.associations.all(): + dimensionValues = [x for x in association.multilayerdimensionvalue_set.all() if x.dimension != self.dimension] + # create a clone of association + newAssociation = deepcopy(association) + newAssociation.id = None + newAssociation.name = 'NEW' + newAssociation.uuid = uuid.uuid4() + newAssociation.save() + # restore value/association relationships + for value in dimensionValues: + value.associations.add(newAssociation) + self.associations.add(newAssociation) + + else: + super(MultilayerDimensionValue, self).save(*args, **kwargs) + + def delete(self, *args, **kwargs): + delete_all = False + if 'last' in kwargs.keys(): + if kwargs['last']: + delete_all = True + kwargs.pop('last', None) + try: + for association in self.associations.all(): + if delete_all or len(self.dimension.multilayerdimensionvalue_set.all()) > 1 or len(self.dimension.layer.parent_layer.all()) == 1: + association.multilayerdimensionvalue_set.clear() + association.delete() + except ValueError: + # ValueError: "" needs to have a value for field "multilayerdimensionvalue" before this many-to-many relationship can be used. + pass + + if self.id: + # AssertionError: MultilayerDimensionValue object can't be deleted because its id attribute is set to None. + super(MultilayerDimensionValue, self).delete(*args, **kwargs) + + +class ExternalPortal(models.Model): + name = models.CharField(max_length=255, blank=True, null=True, default=None) + url = models.URLField(help_text='URL endpoint of the remote Portal') + + def __str__(self): + if not self.name == None: + return self.name + else: + return str(self.url) + + @property + def layer_status_endpoint(self): + return "{}/data_manager/migration/layer_status".format(self.url) + + @property + def layer_detail_endpoint(self): + return "{}/data_manager/migration/layer_details/".format(self.url) + + @property + def get_layer_detail_endpoint(self): + return f"{self.url}/data_manager/migration/get_layer_details/" \ No newline at end of file diff --git a/data_manager/requirements.txt b/data_manager/requirements.txt index c4e5cb5..42b9680 100644 --- a/data_manager/requirements.txt +++ b/data_manager/requirements.txt @@ -1 +1,3 @@ -django-nested-admin +django-nested-admin +django-colorfield +django-import-export \ No newline at end of file diff --git a/data_manager/serializers.py b/data_manager/serializers.py index 4139567..5abaca9 100644 --- a/data_manager/serializers.py +++ b/data_manager/serializers.py @@ -1,7 +1,17 @@ -from rest_framework import serializers -from .models import Layer - -class BriefLayerSerializer(serializers.ModelSerializer): - class Meta: - model = Layer - fields = ('id', 'name', 'layer_type', 'url', 'opacity', 'vector_color', 'vector_fill', 'vector_outline_color', 'vector_outline_opacity', 'arcgis_layers') +from rest_framework import serializers +from .models import Layer, Theme + +class BriefLayerSerializer(serializers.ModelSerializer): + class Meta: + model = Layer + fields = ('id', 'name', 'layer_type', 'url', 'opacity', 'vector_color', 'vector_fill', 'vector_outline_color', 'vector_outline_opacity', 'arcgis_layers') + +class ThemeSerializer(serializers.ModelSerializer): + class Meta: + model = Theme + fields = '__all__' + +class LayerSerializer(serializers.ModelSerializer): + class Meta: + model = Layer + fields = '__all__' \ No newline at end of file diff --git a/data_manager/settings.py b/data_manager/settings.py index 0a63fc1..a930d9c 100644 --- a/data_manager/settings.py +++ b/data_manager/settings.py @@ -1,2 +1,20 @@ -import os -BASE_DIR = os.path.dirname(os.path.dirname(__file__)) +import os +DATA_MANAGER_BASE_DIR = os.path.dirname(os.path.dirname(__file__)) + +DATA_MANAGER_ADMIN = True + +DATA_CATALOG_ENABLED = True + +DATA_CATALOG_NAME_FIELD = 'title' + +CATALOG_TECHNOLOGY = 'default' + +CATALOG_SOURCE = None + +ELASTICSEARCH_INDEX = 'metadata' + +ELASTICSEARCH_SEARCH_FIELDS = [ + 'title', +] + +CATALOG_PROXY = '' diff --git a/data_manager/static/admin/data_manager/css/layer_form.css b/data_manager/static/admin/data_manager/css/layer_form.css new file mode 100644 index 0000000..5b7fca5 --- /dev/null +++ b/data_manager/static/admin/data_manager/css/layer_form.css @@ -0,0 +1,96 @@ +.select2-container .select2-selection--single .select2-selection__rendered.select2-textarea { + white-space: normal; + text-overflow: unset; + height: 100%; + overflow: auto; + line-height: 20px; +} + +.select2-container--default .select2-selection--single .select2-selection__arrow { + visibility: hidden; +} + +/* override 'dark mode' printing light text on select2 white background */ +span.select2-results { + color: black; +} + +/************************************* + * Spinner Dialog + ************************************/ +.ui-dialog.ui-widget.ui-widget-content { + border-radius: 10px; + padding: 0 +} +.ui-dialog.ui-widget.ui-widget-content .ui-dialog-titlebar { + border-radius: 9px 9px 0 0; +} + +#spinner-dialog img { + display: block; + margin: 30px auto; +} + +/************************************* + * Collapse animation support + ************************************/ +/* fieldset.late-transition.collapse table, +fieldset.late-transition.collapse input, +fieldset.late-transition.collapse div { */ +fieldset.late-transition.collapse * { + max-height: 1000px; + transition: max-height 0.5s, padding-top 0.5s, padding-bottom 0.5s; +} +fieldset.late-transition.collapse *:not(.related-widget-wrapper):not(.related-widget-wrapper *) { + height: auto; +} + +fieldset.late-transition.collapse div.argis-details-table-wrapper, +fieldset.late-transition.collapse div.argis-zoom-table-wrapper { + max-height: 500px; + overflow-y: auto; + max-width: 50vw; + float: right; + border: 1px solid #888; + padding-right: 1rem; +} +fieldset.late-transition.collapse div.argis-details-table-wrapper { + margin-top: -50px; +} + +fieldset.late-transition.collapse h2 { + transition: background 0.5s; +} + +/* fieldset.late-transition.collapse.collapsed table, +fieldset.late-transition.collapse.collapsed input, +fieldset.late-transition.collapse.collapsed div { */ +fieldset.late-transition.collapse.collapsed * { + max-height: 0; + display: block; + padding: 0; + border: none; +} + +fieldset.late-transition.collapse h2, +fieldset.late-transition.collapse.collapsed h2 { + max-height: 31px; + padding: 4px; + display: flex; +} + +a.collapse-toggle { + display: inline; +} + + +/************************************* + * Additional Page Layout + ************************************/ +.aligned label { + padding: unset; +} + +div.form-row>div { + margin: 0.2rem; +} \ No newline at end of file diff --git a/data_manager/static/data_manager/css/migration.css b/data_manager/static/data_manager/css/migration.css new file mode 100644 index 0000000..3d96f8b --- /dev/null +++ b/data_manager/static/data_manager/css/migration.css @@ -0,0 +1,7 @@ +tr.synced { + background-color: rgba(0,160,205,0.2); +} + +tr.theme-row { + background-color: rgba(100,50,200,0.3); +} \ No newline at end of file diff --git a/data_manager/static/data_manager/geojson/AWCRoutesAndHubs.json b/data_manager/static/data_manager/geojson/AWCRoutesAndHubs.json index d595726..e3ee307 100644 --- a/data_manager/static/data_manager/geojson/AWCRoutesAndHubs.json +++ b/data_manager/static/data_manager/geojson/AWCRoutesAndHubs.json @@ -1,22 +1,22 @@ -{"name":"AWC_Route_r_03Feb2012","type":"FeatureCollection" -,"crs":{"type":"name","properties":{"name":"EPSG:3857"}} -,"features":[ 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Jersey","INFO":"New Jersey Call Area / WEA","LINK2":"http://www.boemre.gov/offshore/RenewableEnergy/PDFs/stateactivities/NJ/NewJerseyCallFederalRegister4-20-2011.pdf"}} +]} diff --git a/data_manager/static/data_manager/js/catalog/GeoPortal2.js b/data_manager/static/data_manager/js/catalog/GeoPortal2.js new file mode 100644 index 0000000..1ae451e --- /dev/null +++ b/data_manager/static/data_manager/js/catalog/GeoPortal2.js @@ -0,0 +1,298 @@ +//////////////////////////////////////////////////////////////////////////////// +// +// Elasticsearch + Geoportal +// +//////////////////////////////////////////////////////////////////////////////// + + +var populate_fields_from_catalog = function(catalog_record_data, record_id){ + if (record_id == null || record_id == "null") { + replace_all_select2_with_input(); + hide_spinner(); + } else { + es_index = catalog_record_data.ELASTICSEARCH_INDEX; + // handle multiple IDs + id_list = record_id.split(","); + aggregate_json = false; + for (var i = 0; i < id_list.length; i++) { + id = id_list[i]; + } + url = CATALOG_PROXY + "/" + es_index + "/_doc/" + record_id; + $.ajax({ + url: url, + success: function(data) { + // get id from data + record_json = data._source; + record_json.id = data._id; + aggregate_catalog_record_values(record_json); + } + }); + } +} + +var aggregate_catalog_record_values = function(record_json){ + record_id = record_json.id; + id_list.splice(id_list.indexOf(record_id),1); + + if (!aggregate_json) { + aggregate_json = record_json + } else { + for (var i = 0; i < Object.keys(record_json); i++) { + key = Object.keys(record_json)[i]; + if (Object.keys(aggregate_json).indexOf(key) != -1) { + if (aggregate_json[key].constructor != Array) { + aggregate_json[key] = [ aggregate_json[key] ]; + } + if (record_json[key].constructor != Array) { + record_json[key] = [ record_json[key] ]; + } + aggregate_json[key] = union(aggregate_json[key], record_json[key]); + } else { + aggregate_json[key] = record_json[key]; + } + } + } + + if (id_list.length == 0) { + assign_field_values_from_catalog_record(record_json); + } +} + +var assign_field_values_from_catalog_record = function(record_json){ + // TODO: write function to create appropriate list of links and associate them with tech options + if (!record_json.hasOwnProperty('links_s')) { + record_json.links_s = []; + // replace_input_with_select2('id_url', union([],[])); + } + replace_input_with_select2('id_url', union([],record_json.links_s)); + + // Metadata & Links + /* + id_description + id_kml + id_data_download + id_metadata + id_source + */ + + + replace_input_with_select2('id_description', union([record_json.description], [record_json.apiso_Abstract_txt])); + $('#select2-id_description-container').addClass('select2-textarea'); + $('#id_description').siblings('.select2').find('span.select2-selection').height(150); + + var kml_options = []; + for (var i = 0; i < record_json.links_s.length; i++) { + if (record_json.links_s[i].toLowerCase().indexOf('kml') != -1) { + kml_options.push(record_json.links_s[i]); + } + } + if (kml_options.length > 0) { + replace_input_with_select2('id_kml', union([],kml_options)); + } else { + replace_input_with_select2('id_kml', union([],record_json.links_s)); + } + replace_input_with_select2('id_data_download', union([record_json.url_http_download_s], record_json.links_s)); + replace_input_with_select2('id_metadata', union([record_json.src_uri_s],record_json.links_s)); + replace_input_with_select2('id_source', union([],record_json.links_s)); + + // Legend + /* + This is technology dependent (ArcGIS and WMS will have very specific options) + id_show_legend [checkbox] + id_legend (url to image file) + id_legend_title + id_legend_subtitle + */ + + // ArcGIS Details (ArcGIS only!) + /* + id_arcgis_layers (comma separated ID #s) + id_query_by_point [ checkbox ] + id_disable_arcgis_attributes [ checkbox ] + */ + + // if (get_service_type($('#id_url').val()) == "ArcRest" && $('#id_layer_type').val() == "ArcRest") { + + + + // WMS Details (WMS Only!) + /* + This section is already managed by selecting 'WMS help' + If the user selects "WMS" for technology, perhaps explode this and scroll them to it to manage themselves? + */ + + // Attribute Reporting + /* + This cannot be set from the catalog record + */ + + // Style (Arc FeatureService only, which isn't supported yet) + /* + Tackle this when we add FeatureServices + */ + + + + + hide_spinner(); +} + +/* + * A lot of the code below is either copied from or inspired by work from ESRI's + * GeoPortal Server Catalog work, licensed under the Apache License, Version 2.0 + * Their licence note is copied verbatim below. + * You can find the whole project (license, code, and all) at this site: + * + * https://github.com/Esri/geoportal-server-catalog + * + * In particular, this leverages code and logic from this file: + * + * https://github.com/Esri/geoportal-server-catalog/blob/master/geoportal/src/main/webapp/app/etc/ServiceType.js + * + */ + +/* < ESRI License Disclaimer > */ + + /* See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * Esri Inc. licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +/* */ + +get_service_type = function(url) { + + /* + type + ArcGIS - FeatureServer MapServer ImageServer VectorTileServer StreamServer + -- Currently of these we support MapServer as "ArcRest" + -- In theory 'Vector' nearly supports FeatureServer + -- In theory 'VectorTile' nearly supports VectorTileServer + WMS + WMTS - not yet working with wab 2.0 + -- Not sure if we support this, we have WMS with extra settings to suppot "T" + -- Wait, this might just by XYZ tiles + WFS - not yet with wab 2.0 + -- I do not believe this is supported + KML + -- Not supported, but good to find for a KML link. + GeoRSS + -- Not Supported + CSV + -- Not Supported + TO ADD: + -- XYZ + -- Vector (.json, etc..) + -- VectorTile (?) + */ + + /* + http://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/World_Cities/FeatureServer/0 + http://services.arcgisonline.com/ArcGIS/rest/services/Demographics/USA_Tapestry/MapServer + http://imagery.arcgisonline.com/ArcGIS/rest/services/LandsatGLS/VegetationAnalysis/ImageServer + + http://mesonet.agron.iastate.edu/cgi-bin/wms/nexrad/n0r.cgi?service=WMS&request=GetCapabilities + http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/2.5_month_age_animated.kml + http://www.gdacs.org/xml/rss.xml + http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/2.5_week.csv + + http://services2.arcgis.com/NZMqCJwY3kMjFOqf/arcgis/rest/services/Metro/FeatureServer + http://services2.arcgis.com/NZMqCJwY3kMjFOqf/arcgis/rest/services/Metro/FeatureServer/8 + http://maps7.arcgisonline.com/arcgis/rest/services/USDA_USFS_2014_Wildfire_Hazard_Potential/MapServer + http://services.arcgisonline.com/ArcGIS/rest/services/Demographics/USA_Tapestry/MapServer (tiles) + http://imagery.arcgisonline.com/ArcGIS/rest/services/LandsatGLS/VegetationAnalysis/ImageServer + https://geoeventsample3.esri.com:6443/arcgis/rest/services/SeattleBus/StreamServer + + http://basemaps.arcgis.com/arcgis/rest/services/World_Basemap/VectorTileServer + http://basemaps.arcgis.com/arcgis/rest/services/World_Basemap/VectorTileServer/resources/styles/root.json + http://geodesign.maps.arcgis.com/sharing/rest/content/items/bdf1eec3fa79456c8c7c2bb62f86dade/resources/styles/root.json + + http://suite.opengeo.org/geoserver/wfs?request=GetCapabilities&service=WFS&version=1.1.0 + http://v2.suite.opengeo.org/geoserver/gwc/service/wmts?request=GetCapabilities&service=WMTS&version=1.0.0 + http://www.ndbc.noaa.gov/kml/marineobs_as_kml.php + */ + + var endsWith = function(v,sfx) { + return (v.indexOf(sfx,(v.length-sfx.length)) !== -1); + }; + + var lc, type = null; + if (typeof url === "string" && + (url.indexOf("http://") === 0 || url.indexOf("https://") === 0)) { + lc = url.toLowerCase(); + if (lc.indexOf("?service=") > 0 || lc.indexOf("&service=") > 0) { + if (lc.indexOf("?service=wms") > 0 || lc.indexOf("&service=wms") > 0) { + type = "WMS"; + } else if (lc.indexOf("?service=wmts") > 0 || lc.indexOf("&service=wmts") > 0) { + //type = "WMTS"; + } else if (lc.indexOf("?service=wfs") > 0 || lc.indexOf("&service=wfs") > 0) { + //type = "WFS"; + } else if (lc.indexOf("?service=wcs") > 0 || lc.indexOf("&service=wcs") > 0) { + } + } else if (lc.indexOf("/com.esri.wms.esrimap") !== -1) { + type = "WMS"; + } else if (lc.indexOf("/mapserver/wmsserver") !== -1) { + type = "WMS"; + } else if (lc.indexOf("/rest/services") > 0) { + if (lc.indexOf("/mapserver") > 0) { + type = "MapServer"; + } else if (lc.indexOf("/featureserver") > 0) { + type = "FeatureServer"; + } else if (lc.indexOf("/imageserver") > 0) { + if (endsWith(lc,"/imageserver")) type = "ImageServer"; + } else if (lc.indexOf("/streamserver") > 0) { + type = "StreamServer"; + } else if (lc.indexOf("/vectortileserver") > 0 || + lc.indexOf("/resources/styles/root.json") > 0) { + if (VectorTileLayer && VectorTileLayer.supported()) { + type = "VectorTileServer"; + } + } + } + if (type === null) { + if (endsWith(lc,".kml") || endsWith(lc,".kmz") || endsWith(lc,"kml.php") || + lc.indexOf("?f=kml") > 0 || lc.indexOf("&f=kml") > 0 || + lc.indexOf("?f=kmz") > 0 || lc.indexOf("&f=kmz") > 0) { + type = "KML"; + } else if (endsWith(lc,".csv") || lc.indexOf("f=kml") > 0) { + type = "CSV"; + } else if (endsWith(lc,".xml") && + (lc.indexOf("rss") > 0 || lc.indexOf("georss") > 0)) { + type = "GeoRSS"; + } else if (endsWith(lc,".zip")) { + type = "Shapefile"; + } else if (endsWith(lc, ".json") || lc.indexOf("json") > 0) { // Begin MarinePlanner edits + type = "Vector"; + } else if (endsWith(lc, "wms") || endsWith(lc, "wms?") || + lc.indexOf("/wms/") > 0 || lc.indexOf('mapcache') > 0 || + lc.indexOf("wms?/") > 0 || endsWith(lc, "ows") || + endsWith(lc, "ows?") ) { + type = "WMS"; + } else if (endsWith(lc, ".png") || lc.indexOf("/tiles/") > 0 || + lc.indexOf("/tile/") > 0) { + type = "XYZ"; + } + } + } + if (type === "MapServer" || type === "ImageServer") { + type = "ArcRest"; + } + if (type === "FeatureServer") { + type = "Vector"; + } + if (type === "VectorTileServer") { + type = "VectorTile"; + } + + return type +}; diff --git a/data_manager/static/data_manager/js/layer_form.js b/data_manager/static/data_manager/js/layer_form.js index e557fcd..8b18047 100644 --- a/data_manager/static/data_manager/js/layer_form.js +++ b/data_manager/static/data_manager/js/layer_form.js @@ -1,202 +1,616 @@ - - -show_layertype_form = function(layertype) { - $('.field-wms_help').parent().addClass('collapsed'); - $('.field-wms_help').parent().children('h2').children('a').text('Show'); - - var url = $('#id_url').val() - - if (url.length > 0) { - - if ($('#id_wms_help').is(':checked')) { - - $.ajax({ - url: '/data_manager/wms_capabilities/', - data: { - url: url - }, - success: function(data) { - // SWITCH WMS INPUTS TO SELECTORS - - // Replace WMS Layer Name - slug_val = $('#id_wms_slug').val(); - layer_name_html = ''; - $('#id_wms_slug').replaceWith( layer_name_html); - if (data.layers.indexOf(slug_val) >= 0) { - $('#id_wms_slug').val(slug_val); - } - slug_val = $('#id_wms_slug').val(); - $('#id_wms_slug').change(function() { - show_layertype_form($('#id_layer_type option:selected').text()); - }); - - // Set wms version (only 1.1.1 supported) - $('#id_wms_version').val(data.version); - $('.field-wms_version.field-box').hide() - - // Replace WMS Format - format_val = $('#id_wms_format').val(); - format_html = ''; - $('#id_wms_format').replaceWith(format_html); - if (data.formats.indexOf(format_val) >= 0) { - $('#id_wms_format').val(format_val); - } - - // Replace SRS - srs_val = $('#id_wms_srs').val(); - srs_html = ''; - $('#id_wms_srs').replaceWith(srs_html); - if (data.srs[slug_val].indexOf(srs_val) >= 0) { - $('#id_wms_srs').val(srs_val); - } - - $('#id_wms_srs').change(function() { - if ($('#id_wms_srs').val() == 'EPSG:3857') { - $('#id_wms_time_item').prop('disabled', true); - $('#id_wms_additional').prop('disabled', false); - } else { - $('#id_wms_time_item').prop('disabled', false); - $('#id_wms_additional').prop('disabled', true); - } - }); - - // Replace Styles - style_keys = Object.keys(data.styles[slug_val]); - if (style_keys.length == 0) { - $('#id_wms_styles').val(null); - $('#id_wms_styles').prop('disabled', true); - } else { - $('#id_wms_styles').prop('disabled', false); - style_val = $('#id_wms_styles').val(); - style_html = ''; - $('#id_wms_styles').replaceWith(style_html); - if (data.styles[slug_val].indexOf(style_val) >= 0) { - $('#id_wms_styles').val(style_val); - } - } - - // Replace Time - $('#wms_timing_default').remove(); - $('#wms_timing_position_label').remove(); - $('#wms_timing_position_options').remove(); - - if (data.time[slug_val].default == null) { - $('#id_wms_timing').val(null); - $('#id_wms_timing').prop('disabled', true); - } else { - $('#id_wms_timing').prop('disabled', false); - $('

*** Default = ' + data.time[slug_val].default + '***

').insertAfter('#id_wms_timing'); - if (data.time[slug_val].positions.length > 0) { - $('

Position options:

').insertAfter('#wms_timing_default'); - wms_timing_positions_html = '
    '; - for (var i = 0; i < data.time[slug_val].positions.length; i++) { - wms_timing_positions_html += '
  • ' + data.time[slug_val].positions[i] + '
    • '; - } - wms_timing_positions_html += '
'; - $(wms_timing_positions_html).insertAfter('#wms_timing_position_label'); - } - } - - }, - error: function(data) { - url = $('#id_url').val(); - err_msg = 'ERROR: Layer url ' + url + ' does not appear to be a valid WMS endpoint.' - window.alert(err_msg); - } - }); - } else { - // SWITCH SELECTORS TO INPUTS - - // Replace WMS Layer Name - slug_val = $('#id_wms_slug').val(); - $('#id_wms_slug').replaceWith('' + - ''); - - // Release lock on WMS version field - $('.field-wms_version.field-box').show(); - - // Replace WMS format - format_val = $('#id_wms_format').val(); - $('#id_wms_format').replaceWith('' + - ''); - - // Replace SRS - srs_val = $('#id_wms_srs').val(); - $('#id_wms_srs').replaceWith('' + - ''); - - $('#id_wms_srs').blur(function() { - if ($('#id_wms_srs').val() == 'EPSG:3857') { - $('#id_wms_time_item').prop('disabled', true); - $('#id_wms_additional').prop('disabled', false); - } else { - $('#id_wms_time_item').prop('disabled', false); - $('#id_wms_additional').prop('disabled', true); - } - }); - - // Replace Styles - style_val = $('#id_wms_styles').val(); - $('#id_wms_styles').replaceWith('' + - ''); - - // Replace Time - $('#id_wms_timing').prop('disabled', false); - $('#wms_timing_default').remove(); - $('#wms_timing_position_label').remove(); - $('#wms_timing_position_options').remove(); - - } - - switch(layertype) { - case '---------': - break; - case 'WMS': - $('.field-wms_help').parent().removeClass('collapsed'); - $('.field-wms_help').parent().children('h2').children('a').text('Hide'); - break; - default: - break; - } - } -} - -$(document).ready(function() { - show_layertype_form($('#id_layer_type option:selected').text()); - - $('#id_layer_type').change(function() { - show_layertype_form($('#id_layer_type option:selected').text()); - }); - - $('#id_url').blur(function() { - show_layertype_form($('#id_layer_type option:selected').text()); - }); - - $('#id_wms_help').change(function() { - show_layertype_form($('#id_layer_type option:selected').text()); - }); - -}); +show_layertype_form = function(layertype) { + + if (layertype == null) { + layertype = $('#id_layer_type').val(); + } + + var url = $('#id_url').val(); + + if (url.length > 0) { + + if ($('#id_layer_type').val() == "WMS" && $('#id_wms_help').is(':checked')) { + get_wms_capabilities(); + } + + var organization_section = $('.field-order.field-themes').parent(); + var metadata_section = $('.field-description').parent(); + var legend_section = $('.field-show_legend').parent(); + var arcgis_section = $('.field-arcgis_layers').parent(); + var wms_section = $('.field-wms_help').parent(); + var attribute_section = $('.field-attribute_fields').parent(); + var style_section = $('.field-opacity').parent(); + var multi_association_section = $('#id_parent_layer-TOTAL_FORMS').parent(); + var multi_dimensions_section = $('#id_multilayerdimension_set-TOTAL_FORMS').parent(); + + switch(layertype) { + case '---------': + hide_section(arcgis_section); + hide_section(wms_section); + hide_section(style_section); + break; + case 'WMS': + hide_section(arcgis_section); + show_section(wms_section); + hide_section(style_section); + break; + case 'ArcRest': + show_section(arcgis_section); + hide_section(wms_section); + hide_section(style_section); + break; + case 'ArcFeatureServer': + show_section(arcgis_section); + hide_section(wms_section); + hide_section(style_section); + break; + case 'Vector': + hide_section(arcgis_section); + hide_section(wms_section); + show_section(style_section); + break; + case 'VectorTile': + hide_section(arcgis_section); + hide_section(wms_section); + show_section(style_section); + break; + default: + hide_section(arcgis_section); + hide_section(wms_section); + hide_section(style_section); + break; + } + } +} + +show_section = function(section) { + section.removeClass('collapsed'); + section.children('h2').children('a').text('Hide'); +} + +hide_section = function(section) { + section.addClass('collapsed'); + section.children('h2').children('a').text('Show'); +} + +get_wms_capabilities = function() { + if ($('#id_layer_type').val() == "WMS" && $('#id_url').length > 0 && $('#id_wms_help').prop('checked') == true) { + show_spinner(); + var url = $('#id_url').val(); + $.ajax({ + url: '/data_manager/wms_capabilities/', + data: { + url: url + }, + success: function(data) { + // SWITCH WMS INPUTS TO SELECTORS + var blank_option = ''; + + // Replace WMS Layer Name + var slug_val = $('#id_wms_slug').val(); + var layer_name_html = ''; + $('#id_wms_slug').replaceWith( layer_name_html); + if (data.layers.indexOf(slug_val) >= 0) { + $('#id_wms_slug').val(slug_val); + } + slug_val = $('#id_wms_slug').val(); + $('#id_wms_slug').change(function() { + get_wms_capabilities(); + }); + + // Set wms version (only 1.1.1 supported) + $('#id_wms_version').val(data.version); + $('.field-wms_version.field-box').hide() + + // Replace WMS Format + var format_val = $('#id_wms_format').val(); + var format_html = ''; + $('#id_wms_format').replaceWith(format_html); + if (data.formats.indexOf(format_val) >= 0) { + $('#id_wms_format').val(format_val); + } + + // Replace SRS + var srs_val = $('#id_wms_srs').val(); + var srs_html = ''; + $('#id_wms_srs').replaceWith(srs_html); + if (data.srs[slug_val].indexOf(srs_val) >= 0) { + $('#id_wms_srs').val(srs_val); + } + + $('#id_wms_srs').change(function() { + if ($('#id_wms_srs').val().toLowerCase() == 'epsg:3857') { + $('#id_wms_time_item').prop('disabled', true); + $('#id_wms_additional').prop('disabled', false); + } else { + $('#id_wms_time_item').prop('disabled', false); + $('#id_wms_additional').prop('disabled', true); + } + }); + + // Replace Styles + var style_keys = Object.keys(data.styles[slug_val]); + if (style_keys.length == 0) { + $('#id_wms_styles').val(null); + $('#id_wms_styles').prop('disabled', true); + } else { + $('#id_wms_styles').prop('disabled', false); + var style_val = $('#id_wms_styles').val(); + var style_html = ''; + $('#id_wms_styles').replaceWith(style_html); + if (Object.keys(data.styles[slug_val]).indexOf(style_val) >= 0) { + $('#id_wms_styles').val(style_val); + } + } + + // Replace Time + $('#wms_timing_default').remove(); + $('#wms_timing_position_label').remove(); + $('#wms_timing_position_options').remove(); + + if (data.time[slug_val].default == null) { + $('#id_wms_timing').val(null); + $('#id_wms_timing').prop('disabled', true); + } else { + $('#id_wms_timing').prop('disabled', false); + $('

*** Default = ' + data.time[slug_val].default + '***

').insertAfter('#id_wms_timing'); + if (data.time[slug_val].positions.length > 0) { + $('

Position options:

').insertAfter('#wms_timing_default'); + var wms_timing_positions_html = '
    '; + for (var i = 0; i < data.time[slug_val].positions.length; i++) { + wms_timing_positions_html += '
  • ' + data.time[slug_val].positions[i] + '
    • '; + } + wms_timing_positions_html += '
'; + $(wms_timing_positions_html).insertAfter('#wms_timing_position_label'); + } + } + + /* CAPABILITIES */ + if (Object.keys(data.capabilities).length > 0) { + var info_bool_field = $('#id_wms_info'); + var info_format_field = $('#id_wms_info_format'); + if (data.capabilities.hasOwnProperty('featureInfo') && data.capabilities.featureInfo.available) { + $('.form-row.field-wms_info.field-wms_info_format').show(); + info_format_field.prop('disabled', false); + info_bool_field.prop('disabled', false); + + var info_formats = data.capabilities.featureInfo.formats; + var info_format_val = info_format_field.val(); + var info_format_html = ''; + info_format_field.replaceWith(info_format_html); + + if (info_formats.indexOf(info_format_val) >= 0) { + $('#id_wms_info_format').val(info_format_val); + } + + } else { + // set featureInfo to false, hide section + info_bool_field.prop('checked', false); + info_bool_field.prop('disabled', true); + info_format_field.val(null); + info_format_field.prop('disabled', true); + $('.form-row.field-wms_info.field-wms_info_format').hide(); + } + } + check_queryable(data.queryable); + hide_spinner(); + }, + error: function(data) { + var url = $('#id_url').val(); + err_msg = 'ERROR: Layer url ' + url + ' does not appear to be a valid WMS endpoint.' + hide_spinner(); + window.alert(err_msg); + } + }); + } else { + // SWITCH SELECTORS TO INPUTS + + // Replace WMS Layer Name + if ($('#id_wms_slug').is('select')) { + var slug_val = $('#id_wms_slug').val(); + $('#id_wms_slug').replaceWith('' + + ''); + } + + // Release lock on WMS version field + $('.field-wms_version.field-box').show(); + + // Replace WMS format + if ($('#id_wms_format').is('select')) { + format_val = $('#id_wms_format').val(); + $('#id_wms_format').replaceWith('' + + ''); + } + + // Replace SRS + if ($('#id_wms_srs').is('select')) { + srs_val = $('#id_wms_srs').val(); + $('#id_wms_srs').replaceWith('' + + ''); + } + + $('#id_wms_srs').blur(function() { + if ($('#id_wms_srs').val() == 'EPSG:3857') { + $('#id_wms_time_item').prop('disabled', true); + $('#id_wms_additional').prop('disabled', false); + } else { + $('#id_wms_time_item').prop('disabled', false); + $('#id_wms_additional').prop('disabled', true); + } + }); + + // Replace Styles + if ($('#id_wms_styles').is('select')) { + style_val = $('#id_wms_styles').val(); + $('#id_wms_styles').replaceWith('' + + ''); + } + + // Replace Time + $('#id_wms_timing').prop('disabled', false); + $('#wms_timing_default').remove(); + $('#wms_timing_position_label').remove(); + $('#wms_timing_position_options').remove(); + + } +} + +check_queryable = function(queryable_layers) { + var selected_layer = $('#id_wms_slug').val(); + if (queryable_layers.indexOf(selected_layer) >= 0) { + $('#id_wms_info').attr('disabled', false); + $('#id_wms_info_format').attr('disabled', false); + } else { + $('#id_wms_info').attr('checked', false); + $('#id_wms_info').attr('disabled', true); + $('#id_wms_info_format').attr('disabled', true); + } + if (!$('#queryable_layer_list').length > 0) { + if ($('.form-row.field-wms_info.field-wms_info_format').length > 0) { + $('.form-row.field-wms_info.field-wms_info_format').append('
'); + } else { + console.log('need to re-write identification of WMS Info section of form. See layer_form.js "check_queryable()"'); + } + } + if ($('#queryable_layer_list').length > 0) { + q_layers_html = "Queryable Layers: " + queryable_layers.join(', '); + $('#queryable_layer_list').html(q_layers_html); + } +} + +var change_layer_url = function(self) { + var url = $(this).val(); + var type = null; + if (typeof(get_service_type) == "function") { + type = get_service_type(url); + if ($('#id_layer_type option').map(function() { return $(this).val(); }).toArray().indexOf(type) >= 0) { + $('#id_layer_type').val(type); + $('#id_layer_type').trigger('change'); + } + } else { + console.log('No get_service_type() function defined for CATALOG_TECHNOLOGY: ' + CATALOG_TECHNOLOGY); + } +} + +var replace_all_select2_with_input = function() { + var sel2_fields = $('.select2').siblings('select.select2-hidden-accessible').not('#id_catalog_name'); + for (var i = 0; i < sel2_fields.length; i++) { + var field_id = $(sel2_fields[i]).attr('id'); + var field_name = $(sel2_fields[i]).attr('name'); + var field_value = $(sel2_fields[i]).val(); + var textarea_fields = ['id_description']; + if (textarea_fields.indexOf(field_id) >= 0) { + var field_open = '