From fe7bda3ef1419d29129b1be031db9b305898a06e Mon Sep 17 00:00:00 2001 From: Jordan Landers Date: Fri, 6 Feb 2026 14:45:31 -0800 Subject: [PATCH 1/3] fixed typo in highlight_intervals --- pyleoclim/utils/plotting.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pyleoclim/utils/plotting.py b/pyleoclim/utils/plotting.py index 779d554e..5433a53e 100644 --- a/pyleoclim/utils/plotting.py +++ b/pyleoclim/utils/plotting.py @@ -1086,7 +1086,7 @@ def label_intervals(fig, ax, labels, x_locs, orientation='north', overlapping_se ax['epochs'].set_ylim([-1,0]) colors = ['r', 'm', 'orange', 'blue', 'green', 'aqua', 'navy', 'pink']#['r', 'b']#'r' if ik%2 ==0 else 'b' for ik, _ts in enumerate(geo_ts)] - ax['epochs'] = pyleo.utils.plotting.hightlight_intervals(ax['epochs'], + ax['epochs'] = pyleo.utils.plotting.highlight_intervals(ax['epochs'], ceno_intervals_pairs, color=colors, alpha=.1) @@ -2027,7 +2027,7 @@ def add_GTS(fig, ax, GTS_df=None, ranks=None, time_units='Ma',location='above', # summarize_geol).sort_values('End').reset_index() # ldf = ldf.loc[ldf.End <= max(xlims)] # intervals = ldf[['End', 'Start']].values.reshape(-1, 2) -# ax[stage_ax_name] = hightlight_intervals(ax[stage_ax_name], intervals, color=ldf['Color'].values, alpha=1) +# ax[stage_ax_name] = highlight_intervals(ax[stage_ax_name], intervals, color=ldf['Color'].values, alpha=1) # add_geol_labels(fig, ax, ldf, key=stage_ax_name, y_gts=.5, fontsize=fontsize, # allow_abbreviations=allow_abbreviations, verbose=verbose) # ax[stage_ax_name].grid(False) @@ -2045,7 +2045,7 @@ def add_GTS(fig, ax, GTS_df=None, ranks=None, time_units='Ma',location='above', # summarize_geol).sort_values('End').reset_index() # ldf = ldf.loc[ldf.End <= max(xlims)] # intervals = ldf[['End', 'Start']].values.reshape(-1, 2) -# ax[epoch_ax_name] = hightlight_intervals(ax[epoch_ax_name], intervals, color=ldf['Color'].values, alpha=1) +# ax[epoch_ax_name] = highlight_intervals(ax[epoch_ax_name], intervals, color=ldf['Color'].values, alpha=1) # add_geol_labels(fig, ax, ldf, key=epoch_ax_name, y_gts=.45, fontsize=fontsize, # allow_abbreviations=allow_abbreviations, orientation='north', verbose=verbose) # ax[epoch_ax_name].grid(False) @@ -2064,7 +2064,7 @@ def add_GTS(fig, ax, GTS_df=None, ranks=None, time_units='Ma',location='above', # summarize_geol).sort_values('End').reset_index() # ldf = ldf.loc[ldf.End <= max(xlims)] # intervals = ldf[['End', 'Start']].values.reshape(-1, 2) -# ax[period_ax_name] = hightlight_intervals(ax[period_ax_name], intervals, color=ldf['Color'].values, alpha=1) +# ax[period_ax_name] = highlight_intervals(ax[period_ax_name], intervals, color=ldf['Color'].values, alpha=1) # add_geol_labels(fig, ax, ldf, key=period_ax_name, y_gts=.5, fontsize=fontsize, # allow_abbreviations=allow_abbreviations, verbose=verbose) # ax[period_ax_name].grid(False) From b059c9e9e50c3226652a5b030e5ca3a15c0b332c Mon Sep 17 00:00:00 2001 From: khider <11758571+khider@users.noreply.github.com> Date: Mon, 9 Feb 2026 12:57:05 -0800 Subject: [PATCH 2/3] compliance with new pandas --- pyleoclim/tests/conftest.py | 2 +- pyleoclim/tests/test_core_MultipleSeries.py | 2 +- pyleoclim/utils/mapping.py | 5 ++++- pyleoclim/utils/tsbase.py | 2 +- 4 files changed, 7 insertions(+), 4 deletions(-) diff --git a/pyleoclim/tests/conftest.py b/pyleoclim/tests/conftest.py index beb587fc..273a0179 100644 --- a/pyleoclim/tests/conftest.py +++ b/pyleoclim/tests/conftest.py @@ -75,7 +75,7 @@ def geo_metadata(): def dataframe_dt(): """Pandas dataframe with a datetime index and random values""" length = 5 - dti = pd.date_range("2018-01-01", periods=length, freq="Y", unit="s") + dti = pd.date_range("2018-01-01", periods=length, freq="YE", unit="s") df = pd.DataFrame(np.array(range(length)), index=dti) return df diff --git a/pyleoclim/tests/test_core_MultipleSeries.py b/pyleoclim/tests/test_core_MultipleSeries.py index ecb4ae3a..e319ed29 100644 --- a/pyleoclim/tests/test_core_MultipleSeries.py +++ b/pyleoclim/tests/test_core_MultipleSeries.py @@ -605,7 +605,7 @@ def test_to_pandas_defau(self): dtype="datetime64[s]", ), name="datetime", - freq="31556926S", + freq="31556926s", ) expected = pd.DataFrame( {"foo": [7, 4, np.nan, 9], "bar": [7, np.nan, 8, 1]}, index=expected_index diff --git a/pyleoclim/utils/mapping.py b/pyleoclim/utils/mapping.py index 7bb35331..bc64c894 100644 --- a/pyleoclim/utils/mapping.py +++ b/pyleoclim/utils/mapping.py @@ -795,7 +795,8 @@ def plot_scatter(df=None, x=None, y=None, hue_var=None, size_var=None, marker_va if edgecolor_var in _df.columns: _df['edgecolor'] = _df[edgecolor_var].apply(lambda x: edgecolor[x]) - _df = _df.apply(lambda x: tidy_labels(x) if x.dtype == "str" else x) + #_df = _df.apply(lambda x: tidy_labels(str(x)) if x.dtype == "str" else x) + _df = _df.map(lambda x: tidy_labels(str(x)) if isinstance(x, str) else x) hue_var = hue_var if hue_var in _df.columns else None hue_var_type_numeric = False if hue_var is not None: @@ -900,6 +901,8 @@ def plot_scatter(df=None, x=None, y=None, hue_var=None, size_var=None, marker_va palette = {key: value[0] for key, value in plot_defaults.items()} elif isinstance(hue_var,str): #hue_var) == str: hue_data = _df[_df[hue_var] != missing_val] + if isinstance(hue_data, pd.Series): + hue_data = hue_data.to_frame().T # If scalar mappable was passed, try to extract components. if ax_sm is not None: try: diff --git a/pyleoclim/utils/tsbase.py b/pyleoclim/utils/tsbase.py index 4e4e6251..4bbb68b8 100644 --- a/pyleoclim/utils/tsbase.py +++ b/pyleoclim/utils/tsbase.py @@ -226,7 +226,7 @@ def convert_datetime_index_to_time(datetime_index, time_unit, time_name): time_unit = 'ga' time_name = None - dti = pd.date_range("2018-01-01", periods=5, freq="Y", unit='s') + dti = pd.date_range("2018-01-01", periods=5, freq="YE", unit='s') df = pd.DataFrame(np.array(range(5)), index=dti) time = convert_datetime_index_to_time( df.index, From 361d7045c94c7073bad57a2d620722b3cd656ace Mon Sep 17 00:00:00 2001 From: khider <11758571+khider@users.noreply.github.com> Date: Wed, 11 Feb 2026 13:33:53 -0800 Subject: [PATCH 3/3] fixes to Pandas 3.0 and prepare for release --- .gitignore | 1 + CITATION.cff | 6 +- README.md | 13 +- doc_build/LR04_benthic_stack.csv | 2 +- doc_build/enso.csv | 3374 ++++++++++++++++++++++-------- doc_build/soi.json | 2 +- environment.yml | 2 +- pyleoclim/core/geoseries.py | 12 +- pyleoclim/core/series.py | 4 +- pyleoclim/utils/tsutils.py | 2 +- pyproject.toml | 5 +- 11 files changed, 2572 insertions(+), 851 deletions(-) diff --git a/.gitignore b/.gitignore index 8efe899d..f1b873a4 100644 --- a/.gitignore +++ b/.gitignore @@ -20,3 +20,4 @@ __pycache__ *.png *.ipynb +/doc_build diff --git a/CITATION.cff b/CITATION.cff index 1cb1f49f..a70d1151 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -1,4 +1,4 @@ -cff-version: 1.2.1 +cff-version: 1.2.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Khider" @@ -33,7 +33,7 @@ authors: title: "Pyleoclim: A Python package for the analysis and visualization of paleoclimate data" -version: v1.2.1 +version: v1.2.2 doi: 10.5281/zenodo.1205661 -date-released: 2025-07-09 +date-released: 2026-02-12 url: "https://github.com/LinkedEarth/Pyleoclim_util" diff --git a/README.md b/README.md index bfe65666..d2111036 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ [![PyPI version](https://badge.fury.io/py/pyleoclim.svg)](https://badge.fury.io/py/pyleoclim) -[![PyPI](https://img.shields.io/badge/python-3.10-yellow.svg)]() +[![PyPI](https://img.shields.io/badge/python-3.12-yellow.svg)]() [![license](https://img.shields.io/github/license/linkedearth/Pyleoclim_util.svg)]() [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6999279.svg)](https://doi.org/10.5281/zenodo.6999279) [![NSF-1541029](https://img.shields.io/badge/NSF-1541029-blue.svg)](https://nsf.gov/awardsearch/showAward?AWD_ID=1541029) @@ -21,7 +21,7 @@ There are many entry points to Pyleoclim, thanks to its underlying [data structu We've worked hard to make Pyleoclim accessible to a wide variety of users, from establisher researchers to high-school students, and from seasoned Pythonistas to first-time programmers. A progressive introduction to the package is available at [PyleoTutorials](http://linked.earth/PyleoTutorials/). Examples of scientific use are given [this paper](https://doi.org/10.1029/2022PA004509). A growing collection of research-grade workflows using Pyleoclim and the LinkedEarth research ecosystem are available as Jupyter notebooks on [paleoBooks](http://linked.earth/PaleoBooks/), with video tutorials on the LinkedEarth [YouTube channel](https://www.youtube.com/watch?v=LJaQBFMK2-Q&list=PL93NbaRnKAuF4WpIQf-4y_U4lo-GqcrcW). Pyleoclim is part of the broader Python ecosystem of [Computational Tools for Climate Science](https://neuromatch.io/computational-tools-for-climate-science-course/). Python novices are encouraged to follow these [self-paced tutorials](http://linked.earth/LeapFROGS) before trying Pyleoclim. -Science-based training materials are also available from the [paleoHackathon repository](https://github.com/LinkedEarth/paleoHackathon). We also run live training workshops every so often. Follow us on [Twitter](https://twitter.com/Linked_Earth), or join our [Discourse Forum](https://discourse.linked.earth) for more information. +Science-based training materials are also available from the [paleoHackathon repository](https://github.com/LinkedEarth/paleoHackathon). We also run live training workshops every so often. Follow us on [Twitter](https://x.com/Linked_Earth), or join our [Discourse Forum](https://discourse.linked.earth) for more information. ### Versions @@ -33,17 +33,18 @@ Online documentation is available through [readthedocs](https://pyleoclim-util.r ### Dependencies -pyleoclim **only** supports Python 3.11 +pyleoclim supports Python 3.11 and 3.12 but has only been tested with 3.12 recently. ### Installation The latest stable release is available through Pypi. We recommend using Anaconda or Miniconda with a dedicated environment. Full installation instructions are available in the [package documentation](https://pyleoclim-util.readthedocs.io/en/latest/installation.html) ## Citation -If you use our code in any way, please consider adding these citations to your publications: +If you use our code in any way, please consider adding this citation to your publications: - Khider, D., Emile-Geay, J., Zhu, F., James, A., Landers, J., Ratnakar, V., & Gil, Y. (2022). Pyleoclim: Paleoclimate timeseries analysis and visualization with Python. Paleoceanography and Paleoclimatology, 37, e2022PA004509. https://doi.org/10.1029/2022PA004509 -- Khider, Deborah, Emile-Geay, Julien, Zhu, Feng, James, Alexander, Landers, Jordan, Kwan, Myron, & Athreya, Pratheek. (2022). Pyleoclim: A Python package for the analysis and visualization of paleoclimate data (v0.9.1). Zenodo. https://doi.org/10.5281/zenodo.7523617 + +To cite the current version of the software, please use the [`citation.cff` file](https://github.com/LinkedEarth/Pyleoclim_util/blob/master/CITATION.cff). To cite older version of the software, please refer to the [Zenodo releases](https://zenodo.org/records/15858384). ### Development @@ -62,4 +63,4 @@ If you use the code in publications, please credit the work using the citation f This material is based upon work supported by the National Science Foundation under Grant Number ICER-1541029. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the investigators and do not necessarily reflect the views of the National Science Foundation. -This research is funded in part by JP Morgan Chase & Co. Any views or opinions expressed herein are solely those of the authors listed, and may differ from the views and opinions expressed by JP Morgan Chase & Co. or its affilitates. This material is not a product of the Research Department of J.P. Morgan Securities LLC. This material should not be construed as an individual recommendation of for any particular client and is not intended as a recommendation of particular securities, financial instruments or strategies for a particular client. This material does not constitute a solicitation or offer in any jurisdiction. +This research is funded in part by JP Morgan Chase & Co. Any views or opinions expressed herein are solely those of the authors listed, and may differ from the views and opinions expressed by JP Morgan Chase & Co. or its affiliates. This material is not a product of the Research Department of J.P. Morgan Securities LLC. This material should not be construed as an individual recommendation of for any particular client and is not intended as a recommendation of particular securities, financial instruments or strategies for a particular client. This material does not constitute a solicitation or offer in any jurisdiction. diff --git a/doc_build/LR04_benthic_stack.csv b/doc_build/LR04_benthic_stack.csv index 0dacc30f..1d9da64f 100644 --- a/doc_build/LR04_benthic_stack.csv +++ b/doc_build/LR04_benthic_stack.csv @@ -1,5 +1,5 @@ ###,Series metadata -written by,Pyleoclim 0.12.1b0 +written by,Pyleoclim 1.2.1b0 time_unit,ky BP time_name,Age value_unit,‰ diff --git a/doc_build/enso.csv b/doc_build/enso.csv index fb1ebde2..bc45d4ce 100644 --- a/doc_build/enso.csv +++ b/doc_build/enso.csv @@ -1,1789 +1,3507 @@ Time,Southern Oscillation Index,NINO3 SST +1866.002894179598,-0.62, +1866.0877693668122,-0.12, +1866.1644308262314,-0.62, +1866.2493060134457,-0.65, +1866.331443291395,0.04, +1866.4163184786094,-0.82, +1866.4984557565585,-0.34, +1866.5833309437728,0.36, +1866.668206130987,-0.18, +1866.7503434089363,0.07, +1866.8352185961505,1.1, +1866.9173558741,-0.16, +1867.0022310613142,0.09, +1867.0871062485285,-0.01, 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--git a/environment.yml b/environment.yml index 02a88e5e..a8d8e1dc 100644 --- a/environment.yml +++ b/environment.yml @@ -5,7 +5,7 @@ channels: - default - conda-forge dependencies: - - python=3.11.0 + - python=3.12 - cartopy - numba - scipy diff --git a/pyleoclim/core/geoseries.py b/pyleoclim/core/geoseries.py index 355a849d..9e6b01fa 100644 --- a/pyleoclim/core/geoseries.py +++ b/pyleoclim/core/geoseries.py @@ -935,11 +935,11 @@ def resample(self, rule, keep_log = False, **kwargs): This is a convenience method: doing - ser.resample('AS').mean() + ser.resample('YS').mean() will do the same thing as - ser.pandas_method(lambda x: x.resample('AS').mean()) + ser.pandas_method(lambda x: x.resample('YS').mean()) but will also accept some extra resampling rules, such as `'Ga'` (see below). @@ -990,13 +990,13 @@ def resample(self, rule, keep_log = False, **kwargs): multiplier = int(multiplier) unit = search.group(2) if unit.lower() in tsbase.MATCH_A: - rule = f'{multiplier}AS' + rule = f'{multiplier}YS' elif unit.lower() in tsbase.MATCH_KA: - rule = f'{1_000*multiplier}AS' + rule = f'{1_000*multiplier}YS' elif unit.lower() in tsbase.MATCH_MA: - rule = f'{1_000_000*multiplier}AS' + rule = f'{1_000_000*multiplier}YS' elif unit.lower() in tsbase.MATCH_GA: - rule = f'{1_000_000_000*multiplier}AS' + rule = f'{1_000_000_000*multiplier}YS' ser = self.to_pandas() diff --git a/pyleoclim/core/series.py b/pyleoclim/core/series.py index a7da9b64..a42a748c 100644 --- a/pyleoclim/core/series.py +++ b/pyleoclim/core/series.py @@ -4660,11 +4660,11 @@ def resample(self, rule, keep_log = False, **kwargs): This is a convenience method: doing - ser.resample('AS').mean() + ser.resample('YS').mean() will do the same thing as - ser.pandas_method(lambda x: x.resample('AS').mean()) + ser.pandas_method(lambda x: x.resample('YS').mean()) but will also accept some extra resampling rules, such as `'Ga'` (see below). diff --git a/pyleoclim/utils/tsutils.py b/pyleoclim/utils/tsutils.py index 1a7a474a..0ff648e9 100644 --- a/pyleoclim/utils/tsutils.py +++ b/pyleoclim/utils/tsutils.py @@ -2068,7 +2068,7 @@ def custom_year_averages( import pyleoclim.utils.tsutils as ut # Create sample monthly data - dates = pd.date_range('2020-01-01', '2023-12-31', freq='M') + dates = pd.date_range('2020-01-01', '2023-12-31', freq='ME') values = np.arange(len(dates)) # Sequential values for clarity ts = pd.Series(values, index=dates, name='monthly_values') diff --git a/pyproject.toml b/pyproject.toml index e4b5a517..32f5ce59 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "pyleoclim" -version = "1.2.1b0" +version = "1.3.0" description = "Python Package for the Analysis of Paleoclimate Data" readme = "README.md" license = { text = "GPL-3.0" } @@ -15,7 +15,8 @@ authors = [ { name = "Daniel Garijo"}, { name = "Lionel Voirol"}, { name = "Robert McGibbon"}, - { name = "Dominik Stiller"} + { name = "Dominik Stiller"}, + { name = "Jordan Landers"} ] requires-python = ">=3.11" dependencies = [