diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 632f820b..7cfd79f4 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -1,86 +1,14 @@ -name: Docs +name: Docs on: pull_request: push: branches: [main] + tags: + - '*' merge_group: - jobs: - - test: - name: Build docs - runs-on: ubuntu-24.04 - defaults: - run: - shell: bash - steps: - - name: Cancel Previous Runs - uses: styfle/cancel-workflow-action@0.12.1 - with: - access_token: ${{ github.token }} - - - name: Checkout - uses: actions/checkout@v4.2.2 - with: - submodules: true - - - name: Cache conda and dependencies - id: cache - uses: actions/cache@v4.2.2 - env: - # Increase this to reset the cache if the key hasn't changed. - CACHE_NUM: 3 - with: - path: | - /usr/share/miniconda/envs/anaconda-client-env - ~/osx-conda - ~/.profile - key: conda-v${{ env.CACHE_NUM }}-${{ hashFiles('pyproject.toml') }} - - - name: Install Conda - uses: conda-incubator/setup-miniconda@v3.1.1 - if: steps.cache.outputs.cache-hit != 'true' - with: - activate-environment: anaconda-client-env - python-version: "3.10" - channels: conda-forge - channel-priority: strict - auto-update-conda: true - - - name: Install slim - if: steps.cache.outputs.cache-hit != 'true' - shell: bash -l {0} #We need a login shell to get conda - run: | - conda install --yes slim - - - name: Install uv and pip deps - if: steps.cache.outputs.cache-hit != 'true' - shell: bash -l {0} - run: | - pip install uv - uv pip install --system -r pyproject.toml --extra docs - # Install current pyslim as editable to ensure we get the latest version - uv pip install --system -e . - - # # Retaining commented block for next devel cycle - # - name: Build SLiM - # run: | - # git clone https://github.com/messerlab/SLiM.git - # cd SLiM - # mkdir -p Release - # cd Release - # cmake -D CMAKE_BUILD_TYPE=Release .. - # make -j 2 - - - name: Build docs - run: | - source ~/.profile - conda activate anaconda-client-env - export PATH=$PWD/SLiM/Release:$PATH - slim -v - pip list - cd docs && make - - - + Docs: + uses: tskit-dev/.github/.github/workflows/docs.yml@v14 + with: + install-slim: true diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml new file mode 100644 index 00000000..edde45a0 --- /dev/null +++ b/.github/workflows/lint.yml @@ -0,0 +1,11 @@ +name: Lint + +on: + pull_request: + push: + branches: [main] + merge_group: + +jobs: + Lint: + uses: tskit-dev/.github/.github/workflows/lint.yml@v14 diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 9ab1deed..66269b29 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -7,12 +7,16 @@ on: merge_group: jobs: + packaging: + name: Python packaging + uses: tskit-dev/.github/.github/workflows/python-packaging.yml@v14 + test: name: Python runs-on: ${{ matrix.os }} strategy: matrix: - python: ["3.10", 3.13] + python: ["3.11", "3.13"] os: [macos-latest, ubuntu-24.04, windows-latest] sys: [mingw64, ucrt64] env: [x86_64, ucrt-x86_64] @@ -33,7 +37,6 @@ jobs: - os: windows-latest sys: mingw64 env: ucrt-x86_64 - defaults: run: shell: bash -l {0} @@ -78,8 +81,8 @@ jobs: path: D:\a\pyslim\pyslim\SLiM key: ${{runner.os}}-${{matrix.sys}}-${{matrix.env}}-key - - name: Build SLiM windows - if: ( matrix.os == 'windows-latest' && steps.cache-slim.outputs.cache-hit != 'true' ) + - name: Build SLiM (Windows) + if: matrix.os == 'windows-latest' && steps.cache-slim.outputs.cache-hit != 'true' shell: msys2 {0} run: | git clone https://github.com/messerlab/SLiM.git @@ -92,37 +95,29 @@ jobs: make -j 2 - name: Install uv and dependencies - shell: bash -l {0} run: | pip install uv - uv pip install --system -r pyproject.toml --extra test + uv sync --locked --group test --no-default-groups - - name: Install SLiM macos / linux - if: (matrix.os == 'macos-latest' || matrix.os == 'ubuntu-24.04') - run: | - micromamba install slim -y + - name: Install SLiM (macOS / Linux) + if: matrix.os == 'macos-latest' || matrix.os == 'ubuntu-24.04' + run: micromamba install slim -y - name: Run tests - shell: bash -l {0} run: | - micromamba info - micromamba list - export PATH=$PWD/SLiM/Release:$PATH - which slim - slim -v - python -m pytest \ - -n 0 \ - -v \ - --cov=pyslim \ - --cov-branch \ - --cov-report=term-missing \ + export PATH=$PWD/SLiM/Release:$PATH + uv run --no-default-groups --group test pytest \ + -n 0 -v \ + --cov=pyslim --cov-branch \ --cov-report=xml \ tests - - - name: upload coverage report to codecov + - name: Upload coverage to Codecov uses: codecov/codecov-action@v5.4.0 with: - fail_ci_if_error: true - env_vars: OS,PYTHON token: ${{ secrets.CODECOV_TOKEN }} + fail_ci_if_error: true + flags: python-tests + files: coverage.xml + disable_search: true + verbose: true diff --git a/.github/workflows/wheels.yml b/.github/workflows/wheels.yml new file mode 100644 index 00000000..b8201fea --- /dev/null +++ b/.github/workflows/wheels.yml @@ -0,0 +1,52 @@ +name: Publish Python release + +on: + push: + branches: [test-publish] + release: + types: [published] + +jobs: + build: + runs-on: ubuntu-24.04 + steps: + - uses: actions/checkout@v4.2.2 + with: + fetch-depth: 0 + + - name: Install uv + uses: astral-sh/setup-uv@v6 + with: + python-version: "3.12" + version: "0.8.15" + + - name: Build + run: uv build + + - uses: actions/upload-artifact@v4 + with: + name: dist + path: dist/ + + publish: + runs-on: ubuntu-24.04 + environment: release + needs: [build] + permissions: + id-token: write + steps: + - uses: actions/download-artifact@v7.0.0 + with: + name: dist + path: dist + + - name: Publish to TestPyPI + if: github.event_name == 'push' && github.ref_name == 'test-publish' + uses: pypa/gh-action-pypi-publish@v1.13.0 + with: + repository-url: https://test.pypi.org/legacy/ + verbose: true + + - name: Publish to PyPI + if: github.event_name == 'release' + uses: pypa/gh-action-pypi-publish@v1.13.0 diff --git a/docs/Makefile b/docs/Makefile index a490de99..208507ae 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -1,18 +1,7 @@ -# Need to set PYTHONPATH so that we pick up the local pyslim -PYPATH=${PWD}/.. -PYSLIM_VERSION:=$(shell PYTHONPATH=${PYPATH} \ - python3 -c 'import pyslim; print(pyslim.__version__.split("+")[0])') - -dev: prereqs +all: prereqs if (cd _static && md5sum -c pedigrees.ink.svg.md5 | grep -l "FAILED"); then echo "remaking figures with inkscape"; $(MAKE) -C _static; else echo "not remaking figures"; fi - PYTHONPATH=${PYPATH} ./build.sh - -dist: prereqs - @echo Building distribution for pyslim version ${PYSLIM_VERSION} - sed -i s/__PYSLIM_VERSION__/${PYSLIM_VERSION}/g _config.yml - $(MAKE) -C _static - PYTHONPATH=${PYPATH} ./build.sh + ./build.sh clean: rm -fR _build diff --git a/docs/_config.yml b/docs/_config.yml index 3931cabd..4b0c8d50 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -42,7 +42,7 @@ sphinx: logo: text: | pyslim
- version __PYSLIM_VERSION__ + version __PKG_VERSION__ issues_github_path: tskit-dev/pyslim todo_include_todos: true intersphinx_mapping: diff --git a/docs/build.sh b/docs/build.sh index ad8b7876..7ccf7e4b 100755 --- a/docs/build.sh +++ b/docs/build.sh @@ -6,8 +6,7 @@ REPORTDIR=_build/html/reports -# TODO add -n for nitpick mode. -jupyter-book build -W --keep-going . +uv run --project=.. --group docs jupyter-book build . -vnW --keep-going RETVAL=$? if [ $RETVAL -ne 0 ]; then if [ -e $REPORTDIR ]; then diff --git a/docs/conf.py b/docs/conf.py deleted file mode 100644 index 7341218e..00000000 --- a/docs/conf.py +++ /dev/null @@ -1,200 +0,0 @@ -# -*- coding: utf-8 -*- -# -# Configuration file for the Sphinx documentation builder. -# -# This file does only contain a selection of the most common options. For a -# full list see the documentation: -# http://www.sphinx-doc.org/en/master/config - -# -- Path setup -------------------------------------------------------------- - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -# -import os -import sys -sys.path.insert(0, os.path.abspath('..')) - -from unittest.mock import MagicMock - -MODULES = ['msprime'] -for mod_name in MODULES: - sys.modules[mod_name] = MagicMock() - -# -- Project information ----------------------------------------------------- - -project = 'pyslim' -copyright = '2020, pySLiM developers' -author = 'pySLiM developers' - -with open(os.path.abspath('../pyslim/_version.py')) as f: - exec(f.read()) -# pyslim_version is defined in the specified file. -release = pyslim_version -version = '.'.join(release.split('.')[:2]) - - - -# -- General configuration --------------------------------------------------- - -# If your documentation needs a minimal Sphinx version, state it here. -# -# needs_sphinx = '1.0' - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. -extensions = [ - 'sphinx.ext.autodoc', - 'sphinx.ext.doctest', - 'sphinx.ext.intersphinx', - 'sphinx.ext.viewcode', - 'sphinx.ext.todo', -] - -# Github repo -issues_github_path = "tskit-dev/pyslim" - -# Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] - -# The suffix(es) of source filenames. -# You can specify multiple suffix as a list of string: -# -# source_suffix = ['.rst', '.md'] -source_suffix = '.rst' - -# The master toctree document. -master_doc = 'index' - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -# -# This is also used if you do content translation via gettext catalogs. -# Usually you set "language" from the command line for these cases. -language = None - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -# This pattern also affects html_static_path and html_extra_path. -exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = None - - -# -- Options for HTML output ------------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -# -html_theme = 'sphinx_rtd_theme' - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -# -# html_theme_options = {} - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['_static'] - -# Custom sidebar templates, must be a dictionary that maps document names -# to template names. -# -# The default sidebars (for documents that don't match any pattern) are -# defined by theme itself. Builtin themes are using these templates by -# default: ``['localtoc.html', 'relations.html', 'sourcelink.html', -# 'searchbox.html']``. -# -# html_sidebars = {} - - -# -- Options for HTMLHelp output --------------------------------------------- - -# Output file base name for HTML help builder. -htmlhelp_basename = 'pyslimdoc' - - -# -- Options for LaTeX output ------------------------------------------------ - -latex_elements = { - # The paper size ('letterpaper' or 'a4paper'). - # - # 'papersize': 'letterpaper', - - # The font size ('10pt', '11pt' or '12pt'). - # - # 'pointsize': '10pt', - - # Additional stuff for the LaTeX preamble. - # - # 'preamble': '', - - # Latex figure (float) alignment - # - # 'figure_align': 'htbp', -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, -# author, documentclass [howto, manual, or own class]). -latex_documents = [ - (master_doc, 'pyslim.tex', 'pyslim Documentation', - 'pySLiM developers', 'manual'), -] - - -# -- Options for manual page output ------------------------------------------ - -# One entry per manual page. List of tuples -# (source start file, name, description, authors, manual section). -man_pages = [ - (master_doc, 'pyslim', 'pyslim Documentation', - [author], 1) -] - - -# -- Options for Texinfo output ---------------------------------------------- - -# Grouping the document tree into Texinfo files. List of tuples -# (source start file, target name, title, author, -# dir menu entry, description, category) -texinfo_documents = [ - (master_doc, 'pyslim', 'pyslim Documentation', - author, 'pyslim', 'One line description of project.', - 'Miscellaneous'), -] - - -# -- Options for Epub output ------------------------------------------------- - -# Bibliographic Dublin Core info. -epub_title = project - -# The unique identifier of the text. This can be a ISBN number -# or the project homepage. -# -# epub_identifier = '' - -# A unique identification for the text. -# -# epub_uid = '' - -# A list of files that should not be packed into the epub file. -epub_exclude_files = ['search.html'] - - -# -- Extension configuration ------------------------------------------------- - -# -- Options for intersphinx extension --------------------------------------- - -# Example configuration for intersphinx: refer to the Python standard library. -intersphinx_mapping = { - 'python': ('https://docs.python.org/3', None), - 'tskit': ('https://tskit.dev/tskit/docs/stable', None), - 'msprime': ('https://tskit.dev/tskit/docs/stable', None) - } diff --git a/docs/metadata.md b/docs/metadata.md index a46ac88d..e4255d51 100644 --- a/docs/metadata.md +++ b/docs/metadata.md @@ -109,7 +109,7 @@ So, `ts.mutation(12).metadata["mutation_list"]` is a list, each of whose entries ## Metadata tools The dictionaries describing the schema for these metadata entries -are available in {data}`.slim_metadata_schemas`. +are available in `pyslim.slim_metadata_schemas`. Furthermore, this method may be useful in working with metadata: ```{eval-rst} diff --git a/docs/python_api.md b/docs/python_api.md index 059a50f4..b570cd69 100644 --- a/docs/python_api.md +++ b/docs/python_api.md @@ -174,7 +174,7 @@ underlying tables), which can then be modified and loaded into SLiM. .. autodata:: NUCLEOTIDES ``` -This is a flag used in `node.flags` (see {meth}`.remove_vacant`): +This is a flag used in `node.flags` (see {func}`.remove_vacant`): ```{eval-rst} .. autodata:: NODE_IS_VACANT_SAMPLE @@ -207,4 +207,3 @@ Finally, these are used in ``individual.flags``: .. autodata:: INDIVIDUAL_RETAINED ``` - diff --git a/docs/tutorial.md b/docs/tutorial.md index 3bd9b20a..8646cd2e 100644 --- a/docs/tutorial.md +++ b/docs/tutorial.md @@ -1026,7 +1026,7 @@ ts = tables.tree_sequence() Next, we need to generate a reference sequence and nucleotides for each mutation. -This is easy with {meth}`.generate_nucleotides`: +This is easy with {func}`.generate_nucleotides`: ```{code-cell} ts = pyslim.generate_nucleotides(ts) diff --git a/docs/util.py b/docs/util.py index 8d51caf5..f75bcd91 100644 --- a/docs/util.py +++ b/docs/util.py @@ -1,10 +1,10 @@ def pp(x): - ''' + """ Hacky way to pretty-print nested dict __repr__'s - ''' + """ if not isinstance(x, str): x = x.__repr__() - delims = {"'" : "'", '"' : '"', "(" : ")", "[" : "]"} + delims = {"'": "'", '"': '"', "(": ")", "[": "]"} out = [] indent = [0] inside = [] @@ -20,7 +20,7 @@ def pp(x): else: prefix += 1 out.append(a) - if a == '{': + if a == "{": indent.append(min(prefix, 4)) prefix = 0 out.append("\n" + " " * sum(indent)) @@ -32,10 +32,10 @@ def pp(x): if a in delims: inside.append(a) if name: - if a == ':': + if a == ":": name = False else: - if a == ',': + if a == ",": name = True prefix = 0 out.append("\n" + " " * sum(indent)) diff --git a/docs/vignette_coalescent_diversity.md b/docs/vignette_coalescent_diversity.md index efd7776d..589d1bd1 100644 --- a/docs/vignette_coalescent_diversity.md +++ b/docs/vignette_coalescent_diversity.md @@ -124,7 +124,7 @@ ots = pyslim.annotate(ots, model_type="WF", tick=1, stage="late") This method adds default metadata to everything that needs it: in this case, all individuals, all nodes that are part of alive individuals, and all populations referenced by nodes. -These default values are returned by {func}`.slim_default_metadata` +These default values are returned by {func}`.default_slim_metadata` (e.g., all individuals are hermaphrodite, all chromosomes are autosomal); see {func}`.annotate` for more information. @@ -328,7 +328,7 @@ s = np.array([sum([sum([md["selection_coeff"] for md in m.metadata["mutation_lis for m in site.mutations]) for site in ts.sites()]) ``` -To do this, we used the `time=t` argument to {func}`tskit.TreeSequence.samples` +To do this, we used the `time=t` argument to {meth}`tskit.TreeSequence.samples` to find the nodes alive at each of the two times (0 and 100 generations ago); then computed an array ``p`` of allele frequencies, with one row per site, the first column giving the frequency among the initial generation, diff --git a/prek.toml b/prek.toml new file mode 100644 index 00000000..d8096287 --- /dev/null +++ b/prek.toml @@ -0,0 +1,40 @@ +# The prek configuration defining linting requirements. This +# setup is optimised for long-term stability and determinism, +# and therefore only uses either "builtin" rules or "local" +# rules implementing lint workflows. We do not use any remote +# workflow repos. + +[[repos]] +repo = "builtin" +hooks = [ + { id = "check-added-large-files" }, + { id = "check-merge-conflict" }, + { id = "mixed-line-ending" }, + { id = "check-case-conflict" }, + { id = "check-yaml" }, + { id = "check-toml" }, +] + +[[repos]] +repo = "local" +hooks = [ + { + id = "ruff-check", + name = "ruff check", + language = "system", + entry = "uv run --only-group=lint ruff check --fix --force-exclude", + types = ["python"], + }, +] + +[[repos]] +repo = "local" +hooks = [ + { + id = "ruff-format", + name = "ruff format", + language = "system", + entry = "uv run --only-group=lint ruff format --force-exclude", + types = ["python"], + }, +] diff --git a/pyproject.toml b/pyproject.toml index d8ca75b3..7d491d83 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -21,7 +21,6 @@ classifiers = [ "Operating System :: Microsoft :: Windows", "Programming Language :: Python", "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", @@ -29,7 +28,7 @@ classifiers = [ "Topic :: Scientific/Engineering :: Bio-Informatics", ] keywords = ["tree sequences", "tskit"] -requires-python = ">=3.10" +requires-python = ">=3.11" dependencies = [ "msprime>=1.0.1", "tskit", @@ -48,44 +47,83 @@ include-package-data = true [tool.setuptools.dynamic] version = {attr = "pyslim._version.pyslim_version"} -[project.optional-dependencies] +[dependency-groups] test = [ - "flake8==7.1.2", - "pytest==8.3.5", - "pytest-cov==6.1.1", - "pytest-xdist==3.6.1", - "filelock==3.19.1", - "tskit==0.6.4", - "msprime>=1.2.0", - "matplotlib==3.9.4", - "pandas==2.3.2", + "pytest", + "pytest-cov", + "pytest-xdist", + "filelock", + "tskit", + "msprime", + "matplotlib", + "pandas", ] docs = [ - "jupyter-book==1.0.4.post1", - "matplotlib==3.10.3", - "msprime==1.3.4", - "pandas==2.2.3", - "PyGithub==2.6.1", - "setuptools-scm==8.2.1", - "sphinx-argparse==0.5.2", - "sphinx-issues==5.0.0", - "tskit==0.6.3", + "jupyter-book<2", + "matplotlib", + "msprime", + "pandas", + "setuptools-scm", + "sphinx-argparse", + "sphinx-issues", +] + +lint = [ + "ruff==0.15.1", + "prek==0.3.3", +] + +packaging = [ + "twine", + "validate-pyproject[all]", ] dev = [ - "flake8>=7.0", - "pytest>=8.0", - "pytest-cov>=6.0", - "pytest-xdist>=3.0", - "numpy", - "filelock", - "tskit>=0.6.3", - "msprime>=1.2.0", - "matplotlib>=3.0", - "pandas>=2.0", - "jupyter-book>=1.0", - "setuptools-scm>=8.0", - "sphinx-argparse>=0.5", - "sphinx-issues>=5.0", -] \ No newline at end of file + {include-group = "docs"}, + {include-group = "lint"}, + {include-group = "test"}, + {include-group = "packaging"}, +] + +[tool.ruff] +target-version = "py311" +line-length = 89 + +[tool.ruff.lint] +select = ["E", "F", "B", "W", "I", "N", "UP", "A", "PT"] + +ignore = [ + "A001", "A002", "RUF", + "B905", #Don't add strict=False to zips (B905) + "N806", "N802", "N803", # Various nags about uppercase vars + "UP032", # Don't upgrade to f strings + "PT011", # pytest.raises(ValueError)` is too broad + "PT030", # `pytest.warns(Warning)` is too broad, set the `match` + "E722", # Do not use bare `except` + "PT006", # Wrong type passed to first argument of `pytest.mark.parametrize` + "PT031", # `pytest.warns()` block should contain a single + "F841", # Local variable is assigned to but never used + "B007", # Loop control variable `j` not used within loop body + "B028", # No explicit `stacklevel` keyword argument found + "B904", # Within an `except` clause, raise exceptions with `raise + "E712", # Avoid equality comparisons to `False`; + "PT018", # Assertion should be broken down into multiple parts + "E501", # Line too long + "F821", # Undefined name + "F401", # unused import + "F405", # `slim_file_version` may be undefined, or defined from star imports + "E721", # Use `is` and `is not` for type comparisons, or `isinstance()` +] + +fixable = ["ALL"] +unfixable = [] + +[tool.ruff.lint.isort] +known-first-party = ["tstrait"] +known-third-party = [ + "msprime", + "tskit", + "pytest", + "numpy", +] diff --git a/pyslim/__init__.py b/pyslim/__init__.py index a3300640..6f7c8f44 100644 --- a/pyslim/__init__.py +++ b/pyslim/__init__.py @@ -1,6 +1,3 @@ -from __future__ import print_function -from __future__ import division - import numpy as np #: Used in ``individual.flags`` to denote the individual is alive @@ -22,7 +19,7 @@ #: Mutation metadata records the nucleotide as an integer, #: translated to ACGT by indexing this array, #: so a nucleotide value of ``k`` actually means NUCLEOTIDES[k]. -NUCLEOTIDES = ['A', 'C', 'G', 'T'] +NUCLEOTIDES = ["A", "C", "G", "T"] #: A value used in node metadata ("genome_type") to indicate the node is an autosome. #: **DEPRECATED.** @@ -58,10 +55,9 @@ #: flag is not expected to be set). NODE_IS_VACANT_SAMPLE = np.uint32(1 << 16) -from pyslim.slim_metadata import * # NOQA +from pyslim.slim_metadata import * # NOQA from pyslim.slim_tree_sequence import * # NOQA -from pyslim.provenance import * # NOQA -from pyslim.methods import * # NOQA -from pyslim.spatial import * # NOQA -from pyslim._version import pyslim_version as __version__ - +from pyslim.provenance import * # NOQA +from pyslim.methods import * # NOQA +from pyslim.spatial import * # NOQA +from pyslim._version import pyslim_version as __version__ # NOQA diff --git a/pyslim/_version.py b/pyslim/_version.py index b3173583..3a0cf017 100644 --- a/pyslim/_version.py +++ b/pyslim/_version.py @@ -1,5 +1,4 @@ -# coding: utf-8 -pyslim_version = '1.1.0' -slim_file_version = '0.9' +pyslim_version = "1.1.0" +slim_file_version = "0.9" # other file versions that require no modification -compatible_slim_file_versions = ['0.9'] +compatible_slim_file_versions = ["0.9"] diff --git a/pyslim/methods.py b/pyslim/methods.py index d916dc9c..19c12206 100644 --- a/pyslim/methods.py +++ b/pyslim/methods.py @@ -1,15 +1,19 @@ -import msprime -import tskit import warnings + +import msprime import numpy as np +import tskit + +from pyslim import INDIVIDUAL_ALIVE, NODE_IS_VACANT_SAMPLE, NUCLEOTIDES +from .slim_metadata import ( + default_slim_metadata, + is_current_version, + set_metadata_schemas, + set_tree_sequence_metadata, +) from .util import unique_labels_by_group -from .slim_metadata import default_slim_metadata, is_current_version -from .slim_metadata import set_metadata_schemas, set_tree_sequence_metadata -from pyslim import NUCLEOTIDES -from pyslim import NODE_IS_VACANT_SAMPLE -from pyslim import INDIVIDUAL_ALIVE def _mark_samples(tables, nodes): # Modifies tables in place. @@ -51,13 +55,15 @@ def _chromosome_index(ts): :param tskit.TreeSequence ts: The tree sequence or table collection. """ if not ( - isinstance(ts.metadata, dict) - and 'SLiM' in ts.metadata - and 'this_chromosome' in ts.metadata['SLiM'] - ): - raise ValueError("The tree sequence does not have the necessary " - "information in top-level metadata.") - k = ts.metadata['SLiM']['this_chromosome']['index'] + isinstance(ts.metadata, dict) + and "SLiM" in ts.metadata + and "this_chromosome" in ts.metadata["SLiM"] + ): + raise ValueError( + "The tree sequence does not have the necessary " + "information in top-level metadata." + ) + k = ts.metadata["SLiM"]["this_chromosome"]["index"] return k @@ -94,7 +100,7 @@ def has_vacant_samples(ts): for n in ts.samples(): md = ts.node(n).metadata if md is not None: - if _is_chrom_vacant(k, md['is_vacant']): + if _is_chrom_vacant(k, md["is_vacant"]): out = True break return out @@ -112,8 +118,8 @@ def node_is_vacant(ts, node): :param tskit.Node node: The node object. """ # not using chrom_index here because we expect people to call this on lots of nodes - k = ts.metadata['SLiM']['this_chromosome']['index'] - return node.metadata is not None and _is_chrom_vacant(k, node.metadata['is_vacant']) + k = ts.metadata["SLiM"]["this_chromosome"]["index"] + return node.metadata is not None and _is_chrom_vacant(k, node.metadata["is_vacant"]) def _record_vacant_tables(tables): @@ -124,18 +130,20 @@ def _record_vacant_tables(tables): :param tskit.TableCollection tables: The table collection. """ if np.any(tables.nodes.flags & NODE_IS_VACANT_SAMPLE): - warnings.warn("Some nodes are already flagged as vacant samples, and these " - "flags are being overwritten; this may mean you've already run " - "remove_vacant and so don't need to run it again.") + warnings.warn( + "Some nodes are already flagged as vacant samples, and these " + "flags are being overwritten; this may mean you've already run " + "remove_vacant and so don't need to run it again." + ) k = _chromosome_index(tables) dn = tables.nodes.asdict() - dn['flags'] &= ~NODE_IS_VACANT_SAMPLE + dn["flags"] &= ~NODE_IS_VACANT_SAMPLE samples = np.where(tables.nodes.flags & tskit.NODE_IS_SAMPLE > 0)[0] for s in samples: n = tables.nodes[s] - if _is_chrom_vacant(k, n.metadata['is_vacant']): - dn['flags'][s] |= NODE_IS_VACANT_SAMPLE + if _is_chrom_vacant(k, n.metadata["is_vacant"]): + dn["flags"][s] |= NODE_IS_VACANT_SAMPLE tables.nodes.set_columns(**dn) @@ -144,7 +152,7 @@ def _remove_vacant_sample_flags(tables): Set all NODE_IS_VACANT_SAMPLE flags off. """ dn = tables.nodes.asdict() - dn['flags'] &= ~NODE_IS_VACANT_SAMPLE + dn["flags"] &= ~NODE_IS_VACANT_SAMPLE tables.nodes.set_columns(**dn) @@ -212,22 +220,21 @@ def restore_vacant_tables(tables): for j in is_vacant: n = tables.nodes[j] if n.metadata is None: - raise ValueError("Something is wrong: node that is flagged as " - "a vacant sample node has no metadata.") - if not _is_chrom_vacant(k, n.metadata['is_vacant']): - raise ValueError("Something is wrong: node that is flagged as " - "a vacant sample node is not vacant.") + raise ValueError( + "Something is wrong: node that is flagged as " + "a vacant sample node has no metadata." + ) + if not _is_chrom_vacant(k, n.metadata["is_vacant"]): + raise ValueError( + "Something is wrong: node that is flagged as " + "a vacant sample node is not vacant." + ) _remove_vacant_sample_flags(tables) _mark_samples(tables, is_vacant) -def recapitate(ts, - ancestral_Ne=None, - *, - keep_vacant=False, - **kwargs - ): - ''' +def recapitate(ts, ancestral_Ne=None, *, keep_vacant=False, **kwargs): + """ Returns a "recapitated" tree sequence, by using msprime to run a coalescent simulation from the "top" of this tree sequence, i.e., allowing any uncoalesced lineages to coalesce. @@ -247,7 +254,7 @@ def recapitate(ts, You may control the ancestral demography by passing in a ``demography`` argument: see :func:`msprime.sim_ancestry`. - + In general, all defaults are whatever the defaults of :func:`msprime.sim_ancestry` are; this includes recombination rate, so that if neither ``recombination_rate`` or a ``recombination_map`` are @@ -265,7 +272,7 @@ def recapitate(ts, :param bool keep_vacant: Whether to restore the sample flags on any vacant sample nodes. Default: False. :param dict kwargs: Any other arguments to :func:`msprime.sim_ancestry`. - ''' + """ is_current_version(ts, _warn=True) # we need to ask msprime to *not* simulate from any 'vacant' haplosomes; @@ -308,29 +315,27 @@ def recapitate(ts, demography = msprime.Demography.from_tree_sequence(ts) # must set pop sizes to >0 even though we merge immediately for pop in demography.populations: - pop.initial_size=1.0 + pop.initial_size = 1.0 ancestral_name = "ancestral" derived_names = [pop.name for pop in demography.populations] while ancestral_name in derived_names: - ancestral_name = (ancestral_name + "_ancestral") + ancestral_name = ancestral_name + "_ancestral" demography.add_population( - name=ancestral_name, - description="ancestral population simulated by msprime", - initial_size=ancestral_Ne, + name=ancestral_name, + description="ancestral population simulated by msprime", + initial_size=ancestral_Ne, ) # the split has to come slightly longer ago than slim's tick # since that's when all the linages are at, and otherwise the event # won't apply to them demography.add_population_split( - np.nextafter( recap_time, 2 * recap_time), - derived=derived_names, - ancestral=ancestral_name, + np.nextafter(recap_time, 2 * recap_time), + derived=derived_names, + ancestral=ancestral_name, ) kwargs["demography"] = demography - recap = msprime.sim_ancestry( - initial_state = ts, - **kwargs) + recap = msprime.sim_ancestry(initial_state=ts, **kwargs) if has_vacant and keep_vacant: recap = restore_vacant(recap) @@ -366,10 +371,7 @@ def convert_alleles(ts): :param tskit.TreeSequence ts: The tree sequence to transform. """ tables = ts.dump_tables() - has_refseq = ( - ts.has_reference_sequence() - and len(ts.reference_sequence.data) > 0 - ) + has_refseq = ts.has_reference_sequence() and len(ts.reference_sequence.data) > 0 if not has_refseq: raise ValueError("Tree sequence must have a valid reference sequence.") # unfortunately, nucleotide mutations may be stacked (e.g., substitutions @@ -377,8 +379,10 @@ def convert_alleles(ts): # so we must guess which is the most recent, by choosing the one that # has the largest SLiM time, doesn't appear in the parent list, or has # the lagest SLiM ID. - nuc_inds = tables.mutations.metadata_vector(['mutation_list', 0, 'nucleotide'], dtype='int') - num_stacked = np.array([len(m.metadata['mutation_list']) for m in ts.mutations()]) + nuc_inds = tables.mutations.metadata_vector( + ["mutation_list", 0, "nucleotide"], dtype="int" + ) + num_stacked = np.array([len(m.metadata["mutation_list"]) for m in ts.mutations()]) for k in np.where(num_stacked > 1)[0]: mut = ts.mutation(k) if mut.parent == tskit.NULL: @@ -386,26 +390,21 @@ def convert_alleles(ts): else: pids = ts.mutation(mut.parent).derived_state.split(",") x = [ - ( - md['slim_time'], - i not in pids, - int(i), - j - ) for j, (i, md) in - enumerate( - zip(mut.derived_state.split(","), mut.metadata['mutation_list']) + (md["slim_time"], i not in pids, int(i), j) + for j, (i, md) in enumerate( + zip(mut.derived_state.split(","), mut.metadata["mutation_list"]) ) ] x.sort() j = x[-1][3] - nuc_inds[k] = mut.metadata['mutation_list'][j]['nucleotide'] + nuc_inds[k] = mut.metadata["mutation_list"][j]["nucleotide"] if np.any(nuc_inds == -1): raise ValueError("All mutations must be nucleotide mutations.") da = np.array(NUCLEOTIDES)[nuc_inds] tables.mutations.packset_derived_state(da) - k = tables.sites.position.astype('int') - aa = np.frombuffer(ts.reference_sequence.data.encode('utf-8'), dtype='S1')[k] - tables.sites.packset_ancestral_state(aa.tobytes().decode('utf-8')) + k = tables.sites.position.astype("int") + aa = np.frombuffer(ts.reference_sequence.data.encode("utf-8"), dtype="S1")[k] + tables.sites.packset_ancestral_state(aa.tobytes().decode("utf-8")) return tables.tree_sequence() @@ -426,7 +425,7 @@ def generate_nucleotides(ts, reference_sequence=None, keep=True, seed=None): each mutation and picking a random nucleotide uniformly out of the three possible nucleotides that differ from the parental state (i.e., the derived state of the parental mutation, or the ancestral state if the mutation has - no parent). If ``keep=True`` (the default), the mutations that already have a + no parent). If ``keep=True`` (the default), the mutations that already have a nucleotide (i.e., an integer 0-3 in metadata) will not be modified. Technical note: in the case of stacked mutations, the SLiM mutation that @@ -444,16 +443,24 @@ def generate_nucleotides(ts, reference_sequence=None, keep=True, seed=None): rng = np.random.default_rng(seed=seed) if reference_sequence is None: if not ts.has_reference_sequence(): - reference_sequence = rng.choice( + reference_sequence = ( + rng.choice( np.array([65, 67, 71, 84], dtype=np.int8), int(ts.sequence_length), replace=True, - ).tobytes().decode('ascii') + ) + .tobytes() + .decode("ascii") + ) else: if len(reference_sequence) != ts.sequence_length: - raise ValueError("Reference sequence must have length equal to sequence_length.") + raise ValueError( + "Reference sequence must have length equal to sequence_length." + ) if len([x for x in reference_sequence if x not in NUCLEOTIDES]) > 0: - raise ValueError("Reference sequence must be a string of A, C, G, and T only.") + raise ValueError( + "Reference sequence must be a string of A, C, G, and T only." + ) tables = ts.dump_tables() if reference_sequence is not None: @@ -461,10 +468,10 @@ def generate_nucleotides(ts, reference_sequence=None, keep=True, seed=None): tables.mutations.clear() sets = [[k for k in range(4) if k != i] for i in range(4)] states = np.full((ts.num_mutations,), -1) - k = tables.sites.position.astype('int') + k = tables.sites.position.astype("int") aa_list = np.searchsorted( - NUCLEOTIDES, - np.frombuffer(tables.reference_sequence.data.encode('utf-8'), dtype='S1')[k], + NUCLEOTIDES, + np.frombuffer(tables.reference_sequence.data.encode("utf-8"), dtype="S1")[k], ) for site in ts.sites(): aa = aa_list[site.id] @@ -479,14 +486,14 @@ def generate_nucleotides(ts, reference_sequence=None, keep=True, seed=None): this_da = pa ml = mut.metadata max_time = -np.inf - for i, md in zip(mut.derived_state.split(","), ml['mutation_list']): - da = md['nucleotide'] + for i, md in zip(mut.derived_state.split(","), ml["mutation_list"]): + da = md["nucleotide"] if da == -1 or not keep: if i in muts: da = muts[i] else: da = sets[pa][rng.integers(3)] - md['nucleotide'] = da + md["nucleotide"] = da muts[i] = da # the official nucleotide state is from the SLiM mutation with # the largest slim_time attribute that was not present in the parent @@ -497,7 +504,7 @@ def generate_nucleotides(ts, reference_sequence=None, keep=True, seed=None): states[mut.id] = this_da tables.mutations.append(mut.replace(metadata=ml)) md = tables.metadata - md['SLiM']['nucleotide_based'] = True + md["SLiM"]["nucleotide_based"] = True tables.metadata = md return tables.tree_sequence() @@ -510,15 +517,16 @@ def individual_ages(ts): :return: An array of ages of individuals. """ - if ts.metadata['SLiM']['model_type'] != "WF": + if ts.metadata["SLiM"]["model_type"] != "WF": ages = ts.tables.individuals.metadata_vector("age") else: - ages = np.zeros(ts.num_individuals, dtype='int') + ages = np.zeros(ts.num_individuals, dtype="int") return ages -def individuals_alive_at(ts, time, stage='late', remembered_stage=None, - population=None, samples_only=False): +def individuals_alive_at( + ts, time, stage="late", remembered_stage=None, population=None, samples_only=False +): """ Returns an array giving the IDs of all individuals that are known to be alive at the given time ago. This is determined using their birth time @@ -530,7 +538,7 @@ def individuals_alive_at(ts, time, stage='late', remembered_stage=None, alive during "late()" for the time step when they have age zero, while in nonWF models, birth occurs before "early()", so they are alive for both stages. - + In both WF and nonWF models, mortality occurs between "early()" and "late()", so that individuals are last alive during the "early()" stage of the time step of their final age, and if individuals @@ -571,21 +579,26 @@ def individuals_alive_at(ts, time, stage='late', remembered_stage=None, """ is_current_version(ts, _warn=True) if stage not in ("late", "early", "first"): - raise ValueError(f"Unknown stage '{stage}': " - "should be either 'first', 'early' or 'late'.") + raise ValueError( + f"Unknown stage '{stage}': should be either 'first', 'early' or 'late'." + ) if remembered_stage is None: - remembered_stage = ts.metadata['SLiM']['stage'] + remembered_stage = ts.metadata["SLiM"]["stage"] if remembered_stage not in ("late", "early", "first"): - raise ValueError(f"Unknown remembered_stage '{remembered_stage}': " - "should be either 'first', 'early' or 'late'.") - if remembered_stage != ts.metadata['SLiM']['stage']: - warnings.warn(f"Provided remembered_stage '{remembered_stage}' does not" - " match the stage at which the tree sequence was saved" - f" ('{ts.metadata['SLiM']['stage']}'). This is not necessarily" - " an error, but mismatched stages will lead to inconsistencies:" - " make sure you know what you're doing.") + raise ValueError( + f"Unknown remembered_stage '{remembered_stage}': " + "should be either 'first', 'early' or 'late'." + ) + if remembered_stage != ts.metadata["SLiM"]["stage"]: + warnings.warn( + f"Provided remembered_stage '{remembered_stage}' does not" + " match the stage at which the tree sequence was saved" + f" ('{ts.metadata['SLiM']['stage']}'). This is not necessarily" + " an error, but mismatched stages will lead to inconsistencies:" + " make sure you know what you're doing." + ) # An individual's tskit time is the tskit counter at the time of their birth. # The tskit counter clicks once at the start of each reproduction bout. @@ -602,31 +615,30 @@ def individuals_alive_at(ts, time, stage='late', remembered_stage=None, # let x = 1 if the stage is 'first' or (is 'early' and WF) # and y = 1 if remembered stage is 'late' or (is 'early' and nonWF); # then t = time + x + y - 1 . - is_wf = (ts.metadata['SLiM']['model_type'] == "WF") - x = (stage == "first" or (stage == "early" and is_wf)) - y = (remembered_stage == "late" or (remembered_stage == "early" and not is_wf)) + is_wf = ts.metadata["SLiM"]["model_type"] == "WF" + x = stage == "first" or (stage == "early" and is_wf) + y = remembered_stage == "late" or (remembered_stage == "early" and not is_wf) t = time + x + y - 1 birth_times = ts.individuals_time ages = individual_ages(ts) if is_wf: - alive_bool = (birth_times == t) + alive_bool = birth_times == t else: age_offset = (stage == "early") + (remembered_stage == "late") alive_bool = np.logical_and( - birth_times >= t, - birth_times - ages < t + age_offset + birth_times >= t, birth_times - ages < t + age_offset ) if population is not None: - alive_bool &= np.isin( - ts.individuals_population, - population - ) + alive_bool &= np.isin(ts.individuals_population, population) if samples_only: nodes = ts.tables.nodes alive_bool &= ( - 0 < np.bincount(1 + nodes.individual, - nodes.flags & tskit.NODE_IS_SAMPLE, - minlength=1 + ts.num_individuals)[1:] + 0 + < np.bincount( + 1 + nodes.individual, + nodes.flags & tskit.NODE_IS_SAMPLE, + minlength=1 + ts.num_individuals, + )[1:] ) return np.where(alive_bool)[0] @@ -660,14 +672,11 @@ def individual_ages_at(ts, time, stage="late", remembered_stage="late"): """ ages = np.repeat(np.nan, ts.num_individuals) alive = individuals_alive_at( - ts, - time, - stage=stage, - remembered_stage=remembered_stage + ts, time, stage=stage, remembered_stage=remembered_stage ) # to convert individuals_time to number of ticks ago we subtract (y - 1), so - is_wf = (ts.metadata['SLiM']['model_type'] == "WF") - y = (remembered_stage == "late" or (remembered_stage == "early" and not is_wf)) + is_wf = ts.metadata["SLiM"]["model_type"] == "WF" + y = remembered_stage == "late" or (remembered_stage == "early" and not is_wf) t = time + y - 1 ages[alive] = ts.individuals_time[alive] - t return ages @@ -704,11 +713,11 @@ def slim_time(ts, time, stage="late"): should be computed for. """ is_current_version(ts, _warn=True) - is_wf = (ts.metadata['SLiM']['model_type'] == "WF") - remembered_stage = ts.metadata['SLiM']['stage'] - x = (stage == "first" or (stage == "early" and is_wf)) - y = (remembered_stage == "late" or (remembered_stage == "early" and not is_wf)) - slim_time = ts.metadata['SLiM']['tick'] - time + x + y - 1 + is_wf = ts.metadata["SLiM"]["model_type"] == "WF" + remembered_stage = ts.metadata["SLiM"]["stage"] + x = stage == "first" or (stage == "early" and is_wf) + y = remembered_stage == "late" or (remembered_stage == "early" and not is_wf) + slim_time = ts.metadata["SLiM"]["tick"] - time + x + y - 1 return slim_time @@ -721,10 +730,10 @@ def _shift_times(ts, dt): tables = ts.dump_tables() if dt != 0: d = tables.nodes.asdict() - d['time'] += dt + d["time"] += dt tables.nodes.set_columns(**d) d = tables.mutations.asdict() - d['time'] += dt + d["time"] += dt tables.mutations.set_columns(**d) return tables @@ -763,31 +772,31 @@ def set_slim_state(ts, time=0, individuals=None): :param tskit.TreeSequence ts: A SLiM-compatible TreeSequence. :param int time: The number of time units (ticks) into the past to shift times. (Default: zero; can be positive or negative.) - :param np.ndarray individuals: An array of the tskit IDs of the individuals + :param numpy.ndarray individuals: An array of the tskit IDs of the individuals that should be marked as alive (all others will be not alive). (Default: leave unchanged.) """ tables = _shift_times(ts, -time) if time != 0: md = tables.metadata - md['SLiM']['tick'] -= time - md['SLiM']['cycle'] -= time + md["SLiM"]["tick"] -= time + md["SLiM"]["cycle"] -= time tables.metadata = md if individuals is not None: d = tables.individuals.asdict() - d['flags'] &= ~INDIVIDUAL_ALIVE - d['flags'][individuals] |= INDIVIDUAL_ALIVE + d["flags"] &= ~INDIVIDUAL_ALIVE + d["flags"][individuals] |= INDIVIDUAL_ALIVE tables.individuals.set_columns(**d) return tables.tree_sequence() def _do_individual_parents_stuff(ts, return_parents=False): warnings.warn( - "The individual_parents( ) and has_individual_parents( ) methods are " - "no longer needed and will be removed in a future version of pyslim: " - "obtain this information from the `parents' property of individuals " - "instead.", - FutureWarning, + "The individual_parents( ) and has_individual_parents( ) methods are " + "no longer needed and will be removed in a future version of pyslim: " + "obtain this information from the `parents' property of individuals " + "instead.", + FutureWarning, ) # Helper for has_individual_parents and individual_parents, @@ -799,15 +808,14 @@ def _do_individual_parents_stuff(ts, return_parents=False): edge_child_indiv = nodes.individual[edges.child] # nodes whose parent nodes are all in the same individual unique_parent_nodes = unique_labels_by_group( - edges.child, - edge_parent_indiv, - minlength=nodes.num_rows) + edges.child, edge_parent_indiv, minlength=nodes.num_rows + ) unique_parent_edges = unique_parent_nodes[edges.child] # edges describing relationships between individuals indiv_edges = np.logical_and( - np.logical_and(edge_parent_indiv != tskit.NULL, - edge_child_indiv != tskit.NULL), - unique_parent_edges) + np.logical_and(edge_parent_indiv != tskit.NULL, edge_child_indiv != tskit.NULL), + unique_parent_edges, + ) # individual edges where the parent was alive during "late" # of the time step before the child is born ind_times = ts.individuals_time @@ -815,33 +823,41 @@ def _do_individual_parents_stuff(ts, return_parents=False): child_births = ind_times[edge_child_indiv[indiv_edges]] parent_births = ind_times[edge_parent_indiv[indiv_edges]] alive_edges = indiv_edges.copy() - if ts.metadata['SLiM']['model_type'] == "WF": - alive_edges[indiv_edges] = (child_births + 1 == parent_births) + if ts.metadata["SLiM"]["model_type"] == "WF": + alive_edges[indiv_edges] = child_births + 1 == parent_births else: parent_deaths = parent_births - ind_ages[edge_parent_indiv[indiv_edges]] - alive_edges[indiv_edges] = (child_births + 1 >= parent_deaths) + alive_edges[indiv_edges] = child_births + 1 >= parent_deaths edge_spans = edges.right - edges.left - parental_span = np.bincount(edge_child_indiv[alive_edges], - weights=edge_spans[alive_edges], minlength=ts.num_individuals) + parental_span = np.bincount( + edge_child_indiv[alive_edges], + weights=edge_spans[alive_edges], + minlength=ts.num_individuals, + ) # we could also check for edges without individual parents terminating # in this individual, but this is unnecessary as the entire genome is # accounted for - has_all_parents = (parental_span == 2 * ts.sequence_length) + has_all_parents = parental_span == 2 * ts.sequence_length if return_parents: full_parent_edges = np.logical_and( - alive_edges, - has_all_parents[edge_child_indiv]) - parents = np.unique(np.column_stack( - [edge_parent_indiv[full_parent_edges], - edge_child_indiv[full_parent_edges]] - ), axis=0) + alive_edges, has_all_parents[edge_child_indiv] + ) + parents = np.unique( + np.column_stack( + [ + edge_parent_indiv[full_parent_edges], + edge_child_indiv[full_parent_edges], + ] + ), + axis=0, + ) return parents else: return has_all_parents def individual_parents(ts): - ''' + """ **DEPRECATED:** now SLiM records `parents` directly in the individual table (see for instance `ind.parents`). @@ -856,12 +872,12 @@ def individual_parents(ts): :param tskit.TreeSequence ts: A :class:`tskit.TreeSequence`. :return: An array of individual IDs, with row [i, j] if individual i is a parent of individual j. - ''' + """ return _do_individual_parents_stuff(ts, return_parents=True) def has_individual_parents(ts): - ''' + """ **DEPRECATED:** now SLiM records `parents` directly in the individual table (see for instance `ind.parents`). @@ -883,12 +899,12 @@ def has_individual_parents(ts): :param tskit.TreeSequence ts: A :class:`tskit.TreeSequence`. :return: A boolean array of length equal to ``targets``. - ''' + """ return _do_individual_parents_stuff(ts, return_parents=False) def annotate(ts, **kwargs): - ''' + """ Takes a tree sequence (as produced by msprime, for instance), and adds in the information necessary for SLiM to use it as an initial state, filling in mostly default values. Returns a :class:`tskit.TreeSequence`. @@ -905,19 +921,26 @@ def annotate(ts, **kwargs): equal to ts.sequence_length. :param bool annotate_mutations: Whether to replace mutation metadata with defaults. (If False, the mutation table is unchanged.) - ''' + """ tables = ts.dump_tables() annotate_tables(tables, **kwargs) return tables.tree_sequence() -def annotate_tables(tables, model_type, tick, cycle=None, stage="early", reference_sequence=None, - annotate_mutations=True): - ''' +def annotate_tables( + tables, + model_type, + tick, + cycle=None, + stage="early", + reference_sequence=None, + annotate_mutations=True, +): + """ Does the work of :func:`annotate`, but modifies the tables in place: so, takes tables as produced by ``msprime``, and makes them look like the tables as output by SLiM. See :func:`annotate` for details. - ''' + """ if stage not in ("early", "late"): raise ValueError(f"stage must be 'early' or 'late' (provided {stage})") if (type(tick) is not int) or (tick < 1): @@ -933,15 +956,15 @@ def annotate_tables(tables, model_type, tick, cycle=None, stage="early", referen cycle = tick if not np.allclose(tables.sites.position, np.floor(tables.sites.position)): raise ValueError( - "Site positions in this tree sequence are not at integer values, " - "but must be for loading into SLiM: generate mutations with " - "sim_mutations(..., discrete_genome=True), not simulate()." + "Site positions in this tree sequence are not at integer values, " + "but must be for loading into SLiM: generate mutations with " + "sim_mutations(..., discrete_genome=True), not simulate()." ) - top_metadata = default_slim_metadata('tree_sequence')['SLiM'] - top_metadata['model_type'] = model_type - top_metadata['tick'] = tick - top_metadata['cycle'] = cycle - top_metadata['stage'] = stage + top_metadata = default_slim_metadata("tree_sequence")["SLiM"] + top_metadata["model_type"] = model_type + top_metadata["tick"] = tick + top_metadata["cycle"] = cycle + top_metadata["stage"] = stage set_tree_sequence_metadata(tables, **top_metadata) set_metadata_schemas(tables) _annotate_nodes_individuals(tables, age=default_ages) @@ -951,19 +974,20 @@ def annotate_tables(tables, model_type, tick, cycle=None, stage="early", referen if reference_sequence is not None: tables.reference_sequence.data = reference_sequence + def next_slim_mutation_id(ts): - ''' - Returns the next SLiM mutation ID for this tree sequence. This is useful - because if you want to add more mutations to your SLiM tree sequence using - :func:`msprime.sim_mutations`, you may need to specify the parameter - `next_id` in your :class:`msprime.SLiMMutationModel` to be larger than any - existing mutation IDs. Setting `next_id` equal to the output of this + """ + Returns the next SLiM mutation ID for this tree sequence. This is useful + because if you want to add more mutations to your SLiM tree sequence using + :func:`msprime.sim_mutations`, you may need to specify the parameter + `next_id` in your :class:`msprime.SLiMMutationModel` to be larger than any + existing mutation IDs. Setting `next_id` equal to the output of this function will allow the mutated tree sequence to be read in by SLiM. To do this, recall that the "derived state" of SLiM's mutations are comma-separated strings of mutation IDs; this function just parses all derived states and returns one larger than the largest integer found. It will return an error if it encounters derived states that are not comma-separated strings of integers. - ''' + """ max_id = 0 for mut in ts.mutations(): ds = mut.derived_state @@ -972,14 +996,16 @@ def next_slim_mutation_id(ts): try: max_id = max(max_id, int(d)) except ValueError: - raise ValueError(f"The derived state of a mutation ({ds}) in the tree " - "sequence is not a comma-separated list of values " - "coercible to int. This is not a valid SLiM tree sequence.") + raise ValueError( + f"The derived state of a mutation ({ds}) in the tree " + "sequence is not a comma-separated list of values " + "coercible to int. This is not a valid SLiM tree sequence." + ) return max_id + 1 def _annotate_nodes_individuals(tables, age): - ''' + """ Adds to a TableCollection the information relevant to individuals required for SLiM to load in a tree sequence, that is found in Node and Individual tables. This will replace the metadata in those tables. For this to work, @@ -996,19 +1022,19 @@ def _annotate_nodes_individuals(tables, age): If you have other situations, like non-alive "remembered" individuals, you will need to edit the tables by hand, afterwards. - ''' + """ if len(tables.nodes.metadata) > 0: warnings.warn( - "The provided tree sequence already has some nodes with " - "metadata; this metadata will be overwritten." + "The provided tree sequence already has some nodes with " + "metadata; this metadata will be overwritten." ) if len(tables.individuals.metadata) > 0: warnings.warn( - "The provided tree sequence already has some individuals with " - "metadata; this metadata will be overwritten." + "The provided tree sequence already has some individuals with " + "metadata; this metadata will be overwritten." ) ind_population = np.full(tables.individuals.num_rows, -1, dtype="int") - ind_slim_id = np.full(tables.individuals.num_rows, 0, dtype='int') + ind_slim_id = np.full(tables.individuals.num_rows, 0, dtype="int") nid = 0 node_metadata = [] for j, n in enumerate(tables.nodes): @@ -1026,12 +1052,11 @@ def _annotate_nodes_individuals(tables, age): md = None node_metadata.append(md) nms = tables.nodes.metadata_schema - tables.nodes.packset_metadata([ - nms.validate_and_encode_row(x) - for x in node_metadata - ]) + tables.nodes.packset_metadata( + [nms.validate_and_encode_row(x) for x in node_metadata] + ) - slim_ind = (ind_slim_id != 0) + slim_ind = ind_slim_id != 0 ind_slim_id = np.cumsum(ind_slim_id) - 1 ind_metadata = [] @@ -1055,27 +1080,23 @@ def _annotate_nodes_individuals(tables, age): parents_offset=tables.individuals.parents_offset, ) ims = tables.individuals.metadata_schema - tables.individuals.packset_metadata([ - ims.validate_and_encode_row(x) - for x in ind_metadata - ]) - tables.individuals.packset_location( - [[0.0] * 3 if si else [] for si in slim_ind] + tables.individuals.packset_metadata( + [ims.validate_and_encode_row(x) for x in ind_metadata] ) + tables.individuals.packset_location([[0.0] * 3 if si else [] for si in slim_ind]) def _annotate_populations(tables): - ''' + """ Adds to a TableCollection the information about populations required for SLiM to load a tree sequence. This will replace anything already in the Population table for populations referenced by nodes alive at time zero. - ''' - alive_ind = (tables.individuals.flags & INDIVIDUAL_ALIVE > 0) + """ + alive_ind = tables.individuals.flags & INDIVIDUAL_ALIVE > 0 do_pops = np.unique( tables.nodes.population[ np.logical_and( - tables.nodes.individual >= 0, - alive_ind[tables.nodes.individual] + tables.nodes.individual >= 0, alive_ind[tables.nodes.individual] ) ] ) @@ -1089,7 +1110,7 @@ def _annotate_populations(tables): def _annotate_sites_mutations(tables): - ''' + """ Adds to a TableCollection the information relevant to mutations required for SLiM to load in a tree sequence. This means adding to the metadata column of the Mutation table, It will also @@ -1098,39 +1119,48 @@ def _annotate_sites_mutations(tables): This will replace any information already in the metadata or derived state columns of the Mutation table. We set slim_time in metadata so that - tick = floor(tskit time) + slim_time - ''' + """ if len(tables.mutations.metadata) > 0: warnings.warn( - "The provided tree sequence already has some mutations with " - "metadata; this metadata will be overwritten." + "The provided tree sequence already has some mutations with " + "metadata; this metadata will be overwritten." ) num_mutations = tables.mutations.num_rows default_mut = default_slim_metadata("mutation_list_entry") dsb, dso = tskit.pack_bytes([str(j).encode() for j in range(num_mutations)]) - slim_time = tables.metadata["SLiM"]["tick"] - np.floor(tables.mutations.time).astype("int") + slim_time = tables.metadata["SLiM"]["tick"] - np.floor(tables.mutations.time).astype( + "int" + ) mms = tables.mutations.metadata_schema mutation_metadata = [ - mms.encode_row( - {"mutation_list": - [{"mutation_type": default_mut["mutation_type"], - "selection_coeff": default_mut["selection_coeff"], - "subpopulation": default_mut["subpopulation"], - "slim_time": st, - "nucleotide": default_mut["nucleotide"] - }] - }) - for st in slim_time] + mms.encode_row( + { + "mutation_list": [ + { + "mutation_type": default_mut["mutation_type"], + "selection_coeff": default_mut["selection_coeff"], + "subpopulation": default_mut["subpopulation"], + "slim_time": st, + "nucleotide": default_mut["nucleotide"], + } + ] + } + ) + for st in slim_time + ] mdb, mdo = tskit.pack_bytes(mutation_metadata) tables.mutations.set_columns( - site=tables.mutations.site, - node=tables.mutations.node, - time=tables.mutations.time, - derived_state=dsb, - derived_state_offset=dso, - parent=tables.mutations.parent, - metadata=mdb, - metadata_offset=mdo) + site=tables.mutations.site, + node=tables.mutations.node, + time=tables.mutations.time, + derived_state=dsb, + derived_state_offset=dso, + parent=tables.mutations.parent, + metadata=mdb, + metadata_offset=mdo, + ) tables.sites.set_columns( - position=tables.sites.position, - ancestral_state=np.array([], dtype='int8'), - ancestral_state_offset=np.zeros(tables.sites.num_rows + 1, dtype='uint32')) + position=tables.sites.position, + ancestral_state=np.array([], dtype="int8"), + ancestral_state_offset=np.zeros(tables.sites.num_rows + 1, dtype="uint32"), + ) diff --git a/pyslim/provenance.py b/pyslim/provenance.py index a1ebe1bf..19da8525 100644 --- a/pyslim/provenance.py +++ b/pyslim/provenance.py @@ -1,10 +1,5 @@ -from __future__ import print_function - -import platform -import warnings import json -import msprime -import tskit +import platform from . import _version @@ -45,7 +40,7 @@ def slim_provenance_version(provenance): file_version = record["file_version"] except: pass - is_slim = (software_name == "SLiM") + is_slim = software_name == "SLiM" return is_slim, file_version @@ -55,11 +50,8 @@ def get_environment(): currently running. """ env = { - "libraries": { - }, - "parameters" : { - "command" : [] - }, + "libraries": {}, + "parameters": {"command": []}, "os": { "system": platform.system(), "node": platform.node(), @@ -70,7 +62,7 @@ def get_environment(): "python": { "implementation": platform.python_implementation(), "version": platform.python_version_tuple(), - } + }, } return env @@ -82,12 +74,10 @@ def make_pyslim_provenance_dict(): document = { "schema_version": "1.0.0", "software": { - "name" : "pyslim", + "name": "pyslim", "version": __version__, - }, - "parameters": { - "command": {} - }, - "environment": get_environment() + }, + "parameters": {"command": {}}, + "environment": get_environment(), } return document diff --git a/pyslim/slim_metadata.py b/pyslim/slim_metadata.py index 4833f30c..0fb4144b 100644 --- a/pyslim/slim_metadata.py +++ b/pyslim/slim_metadata.py @@ -1,28 +1,24 @@ -import tskit import json import warnings -import numpy as np -from ._version import * -from .provenance import slim_provenance_version, get_environment +import tskit + +from ._version import * # noqa F403 +from .provenance import get_environment, slim_provenance_version -from pyslim import INDIVIDUAL_ALIVE -from pyslim import GENOME_TYPE_AUTOSOME -from pyslim import GENOME_TYPE_X -from pyslim import GENOME_TYPE_Y def is_vacant_num_bytes(num_chromosomes): """ TODO document """ # see _is_chrom_vacant - return int((num_chromosomes + 7)/8) + return int((num_chromosomes + 7) / 8) # def _isvacant_values(vacancy): # """ # Returns the correct is_vacant metadata for the given vacancy pattern. -# +# # :param list vacancy: A list of booleans. # """ # out = [0 for _ in is_vacant_num_bytes(len(vacancy))] @@ -40,200 +36,160 @@ def is_vacant_num_bytes(num_chromosomes): # json.dump(..., indent=True), then lightly edited. _raw_slim_metadata_schemas = { - "tree_sequence" : { - "$schema": "http://json-schema.org/schema#", - "codec": "json", - "examples": [ - { - "SLiM": { - "file_version": "0.9", - "name": "fox", - "description": "foxes on Catalina island", - "cycle": 123, - "tick": 123, - "model_type": "WF", - "this_chromosome": { - "id": 1, - "index": 0, - "symbol": "1", - "name": "autosome_1", - "type": "A" - }, - "chromosomes": [ - { - "id": 1, - "symbol": "1", - "name": "autosome_1", - "type": "A" - }, - { - "id": 35, - "symbol": "MT", - "name": "mtDNA", - "type": "HF" - } - ], - "nucleotide_based": False, - "separate_sexes": True, - "spatial_dimensionality": "xy", - "spatial_periodicity": "x" - } - } - ], - "properties": { - "SLiM": { - "description": "Top-level metadata for a SLiM tree sequence, file format version 0.9", - "properties": { - "file_version": { - "description": "The SLiM 'file format version' of this tree sequence.", - "type": "string" - }, - "name": { - "description": "The SLiM species name represented by this tree sequence.", - "type": "string" - }, - "description": { - "description": "A user-configurable description of the species represented by this tree sequence.", - "type": "string" - }, - "cycle": { - "description": "The 'SLiM cycle' counter when this tree sequence was recorded.", - "type": "integer" - }, - "tick": { - "description": "The 'SLiM tick' counter when this tree sequence was recorded.", - "type": "integer" - }, - "model_type": { - "description": "The model type used for the last part of this simulation (WF or nonWF).", - "enum": [ - "WF", - "nonWF" - ], - "type": "string" - }, - "this_chromosome": { - "description": "The chromosome represented by the tree sequence in this file.", - "properties": { - "id": { - "description": "An integer identifier for the chromosome, unique within this set of tree sequences; often the chromosome number in the organism being represented, such as 1.", - "type": "integer" - }, - "index": { - "description": "The (zero-based) index of this chromosome in the chromosomes metadata array (if present), which should match the information given here.", - "type": "integer" - }, - "symbol": { - "description": "A short string symbol for the chromosome, unique within this set of tree sequences, such as \"1\" or \"MT\".", - "type": "string" - }, - "name": { - "description": "A user-specified name for the chromosome, such as an accession identifier.", - "type": "string" - }, - "type": { - "description": "The type of chromosome, as specified by SLiM.", - "type": "string" - } - }, - "required": [ - "id", - "index", - "symbol", - "type" - ], - "type": "object" - }, - "chromosomes": { - "description": "The chromosomes represented by the collection of tree sequences, of which this tree sequence is one member.", - "items": { - "properties": { - "id": { - "description": "An integer identifier for the chromosome, unique within this set of tree sequences; often the chromosome number in the organism being represented, such as 1.", - "type": "integer" - }, - "symbol": { - "description": "A short string symbol for the chromosome, unique within this set of tree sequences, such as \"1\" or \"MT\".", - "type": "string" - }, - "name": { - "description": "A user-specified name for the chromosome, such as an accession identifier.", - "type": "string" - }, - "type": { - "description": "The type of chromosome, as specified by SLiM.", - "type": "string" - } - }, - "required": [ - "id", - "symbol", - "type" - ], - "type": "object" - }, - "type": "array" - }, - "nucleotide_based": { - "description": "Whether the simulation was nucleotide-based.", - "type": "boolean" - }, - "separate_sexes": { - "description": "Whether the simulation had separate sexes.", - "type": "boolean" - }, - "spatial_dimensionality": { - "description": "The spatial dimensionality of the simulation.", - "enum": [ - "", - "x", - "xy", - "xyz" - ], - "type": "string" - }, - "spatial_periodicity": { - "description": "The spatial periodicity of the simulation.", - "enum": [ - "", - "x", - "y", - "z", - "xy", - "xz", - "yz", - "xyz" - ], - "type": "string" - }, - "stage": { - "description": "The stage of the SLiM life cycle when this tree sequence was recorded.", - "type": "string" + "tree_sequence": { + "$schema": "http://json-schema.org/schema#", + "codec": "json", + "examples": [ + { + "SLiM": { + "file_version": "0.9", + "name": "fox", + "description": "foxes on Catalina island", + "cycle": 123, + "tick": 123, + "model_type": "WF", + "this_chromosome": { + "id": 1, + "index": 0, + "symbol": "1", + "name": "autosome_1", + "type": "A", + }, + "chromosomes": [ + {"id": 1, "symbol": "1", "name": "autosome_1", "type": "A"}, + {"id": 35, "symbol": "MT", "name": "mtDNA", "type": "HF"}, + ], + "nucleotide_based": False, + "separate_sexes": True, + "spatial_dimensionality": "xy", + "spatial_periodicity": "x", + } } - }, - "required": [ - "model_type", - "tick", - "file_version", - "spatial_dimensionality", - "spatial_periodicity", - "this_chromosome", - "separate_sexes", - "nucleotide_based" - ], - "type": "object" - } - }, - "required": [ - "SLiM" - ], - "type": "object" - } - , - "edge" : None, - "site" : None, - "mutation" : - { + ], + "properties": { + "SLiM": { + "description": "Top-level metadata for a SLiM tree sequence, file format version 0.9", + "properties": { + "file_version": { + "description": "The SLiM 'file format version' of this tree sequence.", + "type": "string", + }, + "name": { + "description": "The SLiM species name represented by this tree sequence.", + "type": "string", + }, + "description": { + "description": "A user-configurable description of the species represented by this tree sequence.", + "type": "string", + }, + "cycle": { + "description": "The 'SLiM cycle' counter when this tree sequence was recorded.", + "type": "integer", + }, + "tick": { + "description": "The 'SLiM tick' counter when this tree sequence was recorded.", + "type": "integer", + }, + "model_type": { + "description": "The model type used for the last part of this simulation (WF or nonWF).", + "enum": ["WF", "nonWF"], + "type": "string", + }, + "this_chromosome": { + "description": "The chromosome represented by the tree sequence in this file.", + "properties": { + "id": { + "description": "An integer identifier for the chromosome, unique within this set of tree sequences; often the chromosome number in the organism being represented, such as 1.", + "type": "integer", + }, + "index": { + "description": "The (zero-based) index of this chromosome in the chromosomes metadata array (if present), which should match the information given here.", + "type": "integer", + }, + "symbol": { + "description": 'A short string symbol for the chromosome, unique within this set of tree sequences, such as "1" or "MT".', + "type": "string", + }, + "name": { + "description": "A user-specified name for the chromosome, such as an accession identifier.", + "type": "string", + }, + "type": { + "description": "The type of chromosome, as specified by SLiM.", + "type": "string", + }, + }, + "required": ["id", "index", "symbol", "type"], + "type": "object", + }, + "chromosomes": { + "description": "The chromosomes represented by the collection of tree sequences, of which this tree sequence is one member.", + "items": { + "properties": { + "id": { + "description": "An integer identifier for the chromosome, unique within this set of tree sequences; often the chromosome number in the organism being represented, such as 1.", + "type": "integer", + }, + "symbol": { + "description": 'A short string symbol for the chromosome, unique within this set of tree sequences, such as "1" or "MT".', + "type": "string", + }, + "name": { + "description": "A user-specified name for the chromosome, such as an accession identifier.", + "type": "string", + }, + "type": { + "description": "The type of chromosome, as specified by SLiM.", + "type": "string", + }, + }, + "required": ["id", "symbol", "type"], + "type": "object", + }, + "type": "array", + }, + "nucleotide_based": { + "description": "Whether the simulation was nucleotide-based.", + "type": "boolean", + }, + "separate_sexes": { + "description": "Whether the simulation had separate sexes.", + "type": "boolean", + }, + "spatial_dimensionality": { + "description": "The spatial dimensionality of the simulation.", + "enum": ["", "x", "xy", "xyz"], + "type": "string", + }, + "spatial_periodicity": { + "description": "The spatial periodicity of the simulation.", + "enum": ["", "x", "y", "z", "xy", "xz", "yz", "xyz"], + "type": "string", + }, + "stage": { + "description": "The stage of the SLiM life cycle when this tree sequence was recorded.", + "type": "string", + }, + }, + "required": [ + "model_type", + "tick", + "file_version", + "spatial_dimensionality", + "spatial_periodicity", + "this_chromosome", + "separate_sexes", + "nucleotide_based", + ], + "type": "object", + } + }, + "required": ["SLiM"], + "type": "object", + }, + "edge": None, + "site": None, + "mutation": { "$schema": "http://json-schema.org/schema#", "additionalProperties": False, "codec": "struct", @@ -246,7 +202,7 @@ def is_vacant_num_bytes(num_chromosomes): "nucleotide": 3, "selection_coeff": -0.2, "slim_time": 243, - "subpopulation": 0 + "subpopulation": 0, } ] } @@ -260,92 +216,74 @@ def is_vacant_num_bytes(num_chromosomes): "binaryFormat": "i", "description": "The index of this mutation's mutationType.", "index": 1, - "type": "integer" + "type": "integer", }, "nucleotide": { "binaryFormat": "b", "description": "The nucleotide for this mutation (0=A , 1=C , 2=G, 3=T, or -1 for none)", "index": 5, - "type": "integer" + "type": "integer", }, "selection_coeff": { "binaryFormat": "f", "description": "This mutation's selection coefficient.", "index": 2, - "type": "number" + "type": "number", }, "slim_time": { "binaryFormat": "i", "description": "The SLiM tick counter when this mutation occurred.", "index": 4, - "type": "integer" + "type": "integer", }, "subpopulation": { "binaryFormat": "i", "description": "The ID of the subpopulation this mutation occurred in.", "index": 3, - "type": "integer" - } + "type": "integer", + }, }, "required": [ "mutation_type", "selection_coeff", "subpopulation", "slim_time", - "nucleotide" + "nucleotide", ], - "type": "object" + "type": "object", }, "noLengthEncodingExhaustBuffer": True, - "type": "array" + "type": "array", } }, - "required": [ - "mutation_list" - ], - "type": "object" + "required": ["mutation_list"], + "type": "object", }, - "node" : - { - "$schema": "http://json-schema.org/schema#", - "additionalProperties": False, - "codec": "struct", - "description": "SLiM schema for node metadata.", - "examples": [ - { - "slim_id": 123, - "is_vacant": 0 - } - ], - "properties": { - "slim_id": { - "binaryFormat": "q", - "description": "The 'pedigree ID' of the haplosomes associated with this node in SLiM.", - "index": 0, - "type": "integer" - }, - "is_vacant": { - "description": "A vector of byte (uint8_t) values, with each bit representing whether the node represents a vacant position, either unused or a null haplosome (1), or a non-null haplosome (0), in the corresponding chromosome. This field encodes vacancy for all of the chromosomes in the model, not just the chromosome represented in this file (so that the node table is identical across all chromosomes for a multi-chromosome model). Each chromosome receives one bit here; there are two node table entries per individual, used for the two haplosomes of every chromosome, so only one bit is needed in each entry (making two bits total per chromosome, across the two node table entries). The least significant bit of the first byte is used first (for one haplosome of the first chromosome); the most significant bit of the last byte is used last. The number of bytes present in this field is indicated by this schema's 'binaryFormat' field, which is variable (!), and can also be deduced from the number of chromosomes in the model as given in the top-level 'chromosomes' metadata key, which should always be present if this metadata is present.", - "index": 1, - "type": "array", - "length": 1, # MAY NEED TO BE CHANGED (in SLiM code is "%d") - "items": { - "type": "number", - "binaryFormat": "B" - } - } - }, - "required": [ - "slim_id", - "is_vacant" - ], - "type": [ - "object", - "null" - ] + "node": { + "$schema": "http://json-schema.org/schema#", + "additionalProperties": False, + "codec": "struct", + "description": "SLiM schema for node metadata.", + "examples": [{"slim_id": 123, "is_vacant": 0}], + "properties": { + "slim_id": { + "binaryFormat": "q", + "description": "The 'pedigree ID' of the haplosomes associated with this node in SLiM.", + "index": 0, + "type": "integer", + }, + "is_vacant": { + "description": "A vector of byte (uint8_t) values, with each bit representing whether the node represents a vacant position, either unused or a null haplosome (1), or a non-null haplosome (0), in the corresponding chromosome. This field encodes vacancy for all of the chromosomes in the model, not just the chromosome represented in this file (so that the node table is identical across all chromosomes for a multi-chromosome model). Each chromosome receives one bit here; there are two node table entries per individual, used for the two haplosomes of every chromosome, so only one bit is needed in each entry (making two bits total per chromosome, across the two node table entries). The least significant bit of the first byte is used first (for one haplosome of the first chromosome); the most significant bit of the last byte is used last. The number of bytes present in this field is indicated by this schema's 'binaryFormat' field, which is variable (!), and can also be deduced from the number of chromosomes in the model as given in the top-level 'chromosomes' metadata key, which should always be present if this metadata is present.", + "index": 1, + "type": "array", + "length": 1, # MAY NEED TO BE CHANGED (in SLiM code is "%d") + "items": {"type": "number", "binaryFormat": "B"}, + }, + }, + "required": ["slim_id", "is_vacant"], + "type": ["object", "null"], }, - "individual" : - { + "individual": { "$schema": "http://json-schema.org/schema#", "additionalProperties": False, "codec": "struct", @@ -358,184 +296,171 @@ def is_vacant_num_bytes(num_chromosomes): "pedigree_p1": 12, "pedigree_p2": 23, "sex": 0, - "subpopulation": 0 + "subpopulation": 0, } ], "flags": { "SLIM_INDIVIDUAL_METADATA_MIGRATED": { "description": "Whether this individual was a migrant, either in the tick when the tree sequence " - "was written out (if the individual was alive then), or in the tick of the last time " - "they were Remembered (if not).", - "value": 1 + "was written out (if the individual was alive then), or in the tick of the last time " + "they were Remembered (if not).", + "value": 1, } }, "properties": { "age": { "binaryFormat": "i", "description": "The age of this individual, either when the tree sequence was written out " - "(if the individual was alive then), or the last time they were Remembered (if not).", - "index": 4, - "type": "integer" + "(if the individual was alive then), or the last time they were Remembered (if not).", + "index": 4, + "type": "integer", }, "flags": { "binaryFormat": "I", "description": "Other information about the individual: see 'flags'.", "index": 7, - "type": "integer" + "type": "integer", }, "pedigree_id": { "binaryFormat": "q", "description": "The 'pedigree ID' of this individual in SLiM.", "index": 1, - "type": "integer" + "type": "integer", }, "pedigree_p1": { "binaryFormat": "q", "description": "The 'pedigree ID' of this individual's first parent in SLiM.", "index": 2, - "type": "integer" + "type": "integer", }, "pedigree_p2": { "binaryFormat": "q", "description": "The 'pedigree ID' of this individual's second parent in SLiM.", "index": 3, - "type": "integer" + "type": "integer", }, "sex": { "binaryFormat": "i", "description": "The sex of the individual (0 for female, 1 for male, -1 for hermaphrodite).", "index": 6, - "type": "integer" + "type": "integer", }, "subpopulation": { "binaryFormat": "i", "description": "The ID of the subpopulation the individual was part of, either when the tree sequence " - "was written out (if the individual was alive then), or the last time they were Remembered (if not).", - "index": 5, - "type": "integer" - } + "was written out (if the individual was alive then), or the last time they were Remembered (if not).", + "index": 5, + "type": "integer", + }, }, "required": [ - "pedigree_id", - "pedigree_p1", - "pedigree_p2", - "age", - "subpopulation", - "sex", - "flags" - ], - "type": "object" + "pedigree_id", + "pedigree_p1", + "pedigree_p2", + "age", + "subpopulation", + "sex", + "flags", + ], + "type": "object", }, - "population": - { - "$schema": "http://json-schema.org/schema#", - "additionalProperties": True, - "codec": "json", - "description": "SLiM schema for population metadata.", - "examples": [ - { - "bounds_x0": 0.0, - "bounds_x1": 100.0, - "bounds_y0": 0.0, - "bounds_y1": 100.0, - "female_cloning_fraction": 0.25, - "male_cloning_fraction": 0.0, - "migration_records": [ - { - "migration_rate": 0.9, - "source_subpop": 1 + "population": { + "$schema": "http://json-schema.org/schema#", + "additionalProperties": True, + "codec": "json", + "description": "SLiM schema for population metadata.", + "examples": [ + { + "bounds_x0": 0.0, + "bounds_x1": 100.0, + "bounds_y0": 0.0, + "bounds_y1": 100.0, + "female_cloning_fraction": 0.25, + "male_cloning_fraction": 0.0, + "migration_records": [ + {"migration_rate": 0.9, "source_subpop": 1}, + {"migration_rate": 0.1, "source_subpop": 2}, + ], + "selfing_fraction": 0.5, + "sex_ratio": 0.5, + "slim_id": 2, + "name": "p2", + } + ], + "properties": { + "bounds_x0": { + "description": "The minimum x-coordinate in this subpopulation.", + "type": "number", + }, + "bounds_x1": { + "description": "The maximum x-coordinate in this subpopulation.", + "type": "number", + }, + "bounds_y0": { + "description": "The minimum y-coordinate in this subpopulation.", + "type": "number", + }, + "bounds_y1": { + "description": "The maximum y-coordinate in this subpopulation.", + "type": "number", + }, + "bounds_z0": { + "description": "The minimum z-coordinate in this subpopulation.", + "type": "number", + }, + "bounds_z1": { + "description": "The maximum z-coordinate in this subpopulation.", + "type": "number", + }, + "description": { + "description": "A description of this subpopulation.", + "type": "string", + }, + "female_cloning_fraction": { + "description": "The frequency with which females in this subpopulation reproduce clonally (for WF models).", + "type": "number", + }, + "male_cloning_fraction": { + "description": "The frequency with which males in this subpopulation reproduce clonally (for WF models).", + "type": "number", + }, + "migration_records": { + "items": { + "properties": { + "migration_rate": { + "description": "The fraction of children in this subpopulation that are composed of 'migrants' from the source subpopulation (in WF models).", + "type": "number", }, - { - "migration_rate": 0.1, - "source_subpop": 2 - } - ], - "selfing_fraction": 0.5, - "sex_ratio": 0.5, - "slim_id": 2, - "name": "p2" - } - ], - "properties": { - "bounds_x0": { - "description": "The minimum x-coordinate in this subpopulation.", - "type": "number" - }, - "bounds_x1": { - "description": "The maximum x-coordinate in this subpopulation.", - "type": "number" - }, - "bounds_y0": { - "description": "The minimum y-coordinate in this subpopulation.", - "type": "number" - }, - "bounds_y1": { - "description": "The maximum y-coordinate in this subpopulation.", - "type": "number" - }, - "bounds_z0": { - "description": "The minimum z-coordinate in this subpopulation.", - "type": "number" - }, - "bounds_z1": { - "description": "The maximum z-coordinate in this subpopulation.", - "type": "number" - }, - "description": { - "description": "A description of this subpopulation.", - "type": "string" - }, - "female_cloning_fraction": { - "description": "The frequency with which females in this subpopulation reproduce clonally (for WF models).", - "type": "number" - }, - "male_cloning_fraction": { - "description": "The frequency with which males in this subpopulation reproduce clonally (for WF models).", - "type": "number" - }, - "migration_records": { - "items": { - "properties": { - "migration_rate": { - "description": "The fraction of children in this subpopulation that are composed of 'migrants' from the source subpopulation (in WF models).", - "type": "number" - }, - "source_subpop": { - "description": "The ID of the subpopulation migrants come from (in WF models).", - "type": "integer" - } + "source_subpop": { + "description": "The ID of the subpopulation migrants come from (in WF models).", + "type": "integer", }, - "required": [ - "source_subpop", - "migration_rate" - ], - "type": "object" }, - "type": "array" - }, - "name": { - "description": "A human-readable name for this subpopulation.", - "type": "string" - }, - "selfing_fraction": { - "description": "The frequency with which individuals in this subpopulation self (for WF models).", - "type": "number" - }, - "sex_ratio": { - "description": "This subpopulation's sex ratio (for WF models).", - "type": "number" + "required": ["source_subpop", "migration_rate"], + "type": "object", }, - "slim_id": { - "description": "The ID of this population in SLiM. Note that this is called a 'subpopulation' in SLiM.", - "type": "integer" - } + "type": "array", + }, + "name": { + "description": "A human-readable name for this subpopulation.", + "type": "string", + }, + "selfing_fraction": { + "description": "The frequency with which individuals in this subpopulation self (for WF models).", + "type": "number", + }, + "sex_ratio": { + "description": "This subpopulation's sex ratio (for WF models).", + "type": "number", + }, + "slim_id": { + "description": "The ID of this population in SLiM. Note that this is called a 'subpopulation' in SLiM.", + "type": "integer", + }, }, "required": [], - "type": [ - "object", - "null" - ] - } + "type": ["object", "null"], + }, } @@ -596,40 +521,33 @@ def default_slim_metadata(name, num_chromosomes=1): """ if name == "tree_sequence": out = { - "SLiM" : { - "model_type" : "nonWF", - "cycle" : 1, - "tick" : 1, - "file_version" : slim_file_version, - "spatial_dimensionality" : "", - "spatial_periodicity" : "", - "separate_sexes" : False, - "nucleotide_based" : False, - "stage" : "late", - "name" : "sim", - "description" : "", - "this_chromosome" : { - "id": 1, - "index": 0, - "symbol": "A", - "type": "A", - }, - "chromosomes": [{ - 'id': 1, - "index": 0, - 'symbol': 'A', - 'type': 'A' - }], - } - } + "SLiM": { + "model_type": "nonWF", + "cycle": 1, + "tick": 1, + "file_version": slim_file_version, + "spatial_dimensionality": "", + "spatial_periodicity": "", + "separate_sexes": False, + "nucleotide_based": False, + "stage": "late", + "name": "sim", + "description": "", + "this_chromosome": { + "id": 1, + "index": 0, + "symbol": "A", + "type": "A", + }, + "chromosomes": [{"id": 1, "index": 0, "symbol": "A", "type": "A"}], + } + } elif name == "edge": out = None elif name == "site": out = None elif name == "mutation": - out = { - "mutation_list": [] - } + out = {"mutation_list": []} elif name == "mutation_list_entry": out = { "mutation_type": 0, @@ -668,13 +586,14 @@ def default_slim_metadata(name, num_chromosomes=1): "bounds_y1": 1.0, "bounds_z0": 0.0, "bounds_z1": 1.0, - "migration_records": [] + "migration_records": [], } else: raise ValueError( "Unknown metadata request: name should be one of 'tree_sequence', " "'edge', 'site', 'mutation', 'mutation_list_entry', 'node', " - "'individual', or 'population'.") + "'individual', or 'population'." + ) return out @@ -682,28 +601,33 @@ def default_slim_metadata(name, num_chromosomes=1): # Top-level, a.k.a., tree sequence metadata ########### -def set_tree_sequence_metadata(tables, - model_type, - tick, - cycle=None, - spatial_dimensionality='', - spatial_periodicity='', - separate_sexes=False, - nucleotide_based=False, - stage='late', - name='', - description='', - this_chromosome=None, - chromosomes=None, - file_version=None, - set_table_schemas=True): + +def set_tree_sequence_metadata( + tables, + model_type, + tick, + cycle=None, + spatial_dimensionality="", + spatial_periodicity="", + separate_sexes=False, + nucleotide_based=False, + stage="late", + name="", + description="", + this_chromosome=None, + chromosomes=None, + file_version=None, + set_table_schemas=True, +): if file_version is None: file_version = slim_file_version if isinstance(tables.metadata, bytes): if len(tables.metadata) > 0: - raise ValueError("Tree sequence has top-level metadata but no schema: this is a problem " - "since pyslim is trying to add to the metadata.") - schema_dict = slim_metadata_schemas['tree_sequence'].schema + raise ValueError( + "Tree sequence has top-level metadata but no schema: this is a problem " + "since pyslim is trying to add to the metadata." + ) + schema_dict = slim_metadata_schemas["tree_sequence"].schema metadata_dict = {} else: # we need to keep other keys in the metadata (and schema) if there are any @@ -713,45 +637,48 @@ def set_tree_sequence_metadata(tables, cycle = tick defaults = default_slim_metadata("tree_sequence") if this_chromosome is None: - this_chromosome = defaults['SLiM']['this_chromosome'] + this_chromosome = defaults["SLiM"]["this_chromosome"] if chromosomes is None: - chromosomes = defaults['SLiM']['chromosomes'] - assert(schema_dict['codec'] == 'json') - assert(schema_dict['type'] == 'object') + chromosomes = defaults["SLiM"]["chromosomes"] + assert schema_dict["codec"] == "json" + assert schema_dict["type"] == "object" if "properties" not in schema_dict: schema_dict["properties"] = {} - schema_dict['properties']['SLiM'] = slim_metadata_schemas['tree_sequence'].schema['properties']['SLiM'] + schema_dict["properties"]["SLiM"] = slim_metadata_schemas["tree_sequence"].schema[ + "properties" + ]["SLiM"] tables.metadata_schema = tskit.MetadataSchema(schema_dict) - metadata_dict['SLiM'] = { - "model_type": model_type, - "tick": tick, - "cycle": cycle, - "file_version": file_version, - "spatial_dimensionality": spatial_dimensionality, - "spatial_periodicity": spatial_periodicity, - "separate_sexes": separate_sexes, - "nucleotide_based": nucleotide_based, - "stage": stage, - "name": name, - "description": description, - "this_chromosome": this_chromosome, - "chromosomes": chromosomes, - } + metadata_dict["SLiM"] = { + "model_type": model_type, + "tick": tick, + "cycle": cycle, + "file_version": file_version, + "spatial_dimensionality": spatial_dimensionality, + "spatial_periodicity": spatial_periodicity, + "separate_sexes": separate_sexes, + "nucleotide_based": nucleotide_based, + "stage": stage, + "name": name, + "description": description, + "this_chromosome": this_chromosome, + "chromosomes": chromosomes, + } tables.metadata = metadata_dict def set_metadata_schemas(tables, num_chromosomes=1): - tables.edges.metadata_schema = slim_metadata_schemas['edge'] - tables.sites.metadata_schema = slim_metadata_schemas['site'] - tables.mutations.metadata_schema = slim_metadata_schemas['mutation'] + tables.edges.metadata_schema = slim_metadata_schemas["edge"] + tables.sites.metadata_schema = slim_metadata_schemas["site"] + tables.mutations.metadata_schema = slim_metadata_schemas["mutation"] tables.nodes.metadata_schema = slim_node_metadata_schema(num_chromosomes) - tables.individuals.metadata_schema = slim_metadata_schemas['individual'] - tables.populations.metadata_schema = slim_metadata_schemas['population'] + tables.individuals.metadata_schema = slim_metadata_schemas["individual"] + tables.populations.metadata_schema = slim_metadata_schemas["population"] ################################ # Previous versions of metadata schema: + def _old_metadata_schema(name, file_version): # Returns a metadata schema *if the format has changed*, # and None otherwise. @@ -772,7 +699,7 @@ def _old_metadata_schema(name, file_version): "nucleotide_based": False, "separate_sexes": True, "spatial_dimensionality": "xy", - "spatial_periodicity": "x" + "spatial_periodicity": "x", } } ], @@ -782,139 +709,160 @@ def _old_metadata_schema(name, file_version): "properties": { "file_version": { "description": "The SLiM 'file format version' of this tree sequence.", - "type": "string" + "type": "string", }, "name": { "description": "The SLiM species name represented by this tree sequence.", - "type": "string" + "type": "string", }, "description": { "description": "A user-configurable description of the species represented by this tree sequence.", - "type": "string" + "type": "string", }, "cycle": { "description": "The 'SLiM cycle' counter when this tree sequence was recorded.", - "type": "integer" + "type": "integer", }, "tick": { "description": "The 'SLiM tick' counter when this tree sequence was recorded.", - "type": "integer" + "type": "integer", }, "model_type": { "description": "The model type used for the last part of this simulation (WF or nonWF).", - "enum": [ "WF", "nonWF" ], - "type": "string" + "enum": ["WF", "nonWF"], + "type": "string", }, "nucleotide_based": { "description": "Whether the simulation was nucleotide-based.", - "type": "boolean" + "type": "boolean", }, "separate_sexes": { "description": "Whether the simulation had separate sexes.", - "type": "boolean" + "type": "boolean", }, "spatial_dimensionality": { "description": "The spatial dimensionality of the simulation.", "enum": ["", "x", "xy", "xyz"], - "type": "string" + "type": "string", }, "spatial_periodicity": { "description": "The spatial periodicity of the simulation.", "enum": ["", "x", "y", "z", "xy", "xz", "yz", "xyz"], - "type": "string" + "type": "string", }, "stage": { "description": "The stage of the SLiM life cycle when this tree sequence was recorded.", - "type": "string" - } + "type": "string", + }, }, "required": [ - "model_type", - "tick", - "file_version", - "spatial_dimensionality", - "spatial_periodicity", - "separate_sexes", - "nucleotide_based" + "model_type", + "tick", + "file_version", + "spatial_dimensionality", + "spatial_periodicity", + "separate_sexes", + "nucleotide_based", ], - "type": "object" + "type": "object", } }, "required": ["SLiM"], - "type": "object" + "type": "object", } ms = pre_0_9_tree_sequence - if (name == "tree_sequence" - and file_version in ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7"]): + if name == "tree_sequence" and file_version in [ + "0.1", + "0.2", + "0.3", + "0.4", + "0.5", + "0.6", + "0.7", + ]: pre_0_8_tree_sequence = { "$schema": "http://json-schema.org/schema#", "codec": "json", "type": "object", "properties": { - "SLiM" : { + "SLiM": { "description": "Top-level metadata for a SLiM tree sequence, file format version 0.7", "type": "object", "properties": { - "model_type" : { + "model_type": { "type": "string", "enum": ["WF", "nonWF"], - "description": "The model type used for the last part of this simulation (WF or nonWF)." + "description": "The model type used for the last part of this simulation (WF or nonWF).", }, - "generation" : { + "generation": { "type": "integer", - "description": "The 'SLiM generation' counter when this tree sequence was recorded." + "description": "The 'SLiM generation' counter when this tree sequence was recorded.", }, - "stage" : { + "stage": { "type": "string", - "description": "The stage of the SLiM life cycle when this tree sequence was recorded." + "description": "The stage of the SLiM life cycle when this tree sequence was recorded.", }, - "file_version" : { + "file_version": { "type": "string", - "description": "The SLiM 'file format version' of this tree sequence." + "description": "The SLiM 'file format version' of this tree sequence.", }, "spatial_dimensionality": { "type": "string", "enum": ["", "x", "xy", "xyz"], - "description": "The spatial dimensionality of the simulation." + "description": "The spatial dimensionality of the simulation.", }, "spatial_periodicity": { "type": "string", "enum": ["", "x", "y", "z", "xy", "xz", "yz", "xyz"], - "description": "The spatial periodicity of the simulation." + "description": "The spatial periodicity of the simulation.", }, "separate_sexes": { "type": "boolean", - "description": "Whether the simulation had separate sexes." + "description": "Whether the simulation had separate sexes.", }, "nucleotide_based": { "type": "boolean", - "description": "Whether the simulation was nucleotide-based." - } + "description": "Whether the simulation was nucleotide-based.", + }, }, - "required": ["model_type", "generation", "file_version", "spatial_dimensionality", "spatial_periodicity", "separate_sexes", "nucleotide_based"] + "required": [ + "model_type", + "generation", + "file_version", + "spatial_dimensionality", + "spatial_periodicity", + "separate_sexes", + "nucleotide_based", + ], } }, "required": ["SLiM"], "examples": [ { - "SLiM" : { - "model_type" : "WF", - "generation" : 123, - "file_version" : "0.7", - "spatial_dimensionality" : "xy", - "spatial_periodicity" : "x", - "separate_sexes" : True, - "nucleotide_based" : False - } + "SLiM": { + "model_type": "WF", + "generation": 123, + "file_version": "0.7", + "spatial_dimensionality": "xy", + "spatial_periodicity": "x", + "separate_sexes": True, + "nucleotide_based": False, + } } - ] + ], } - ms = pre_0_8_tree_sequence + ms = pre_0_8_tree_sequence - if (name == "population" - and file_version in ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6"]): + if name == "population" and file_version in [ + "0.1", + "0.2", + "0.3", + "0.4", + "0.5", + "0.6", + ]: pre_0_7_population = { "$schema": "http://json-schema.org/schema#", "description": "SLiM schema for population metadata.", @@ -925,57 +873,68 @@ def _old_metadata_schema(name, file_version): "type": "integer", "description": "The ID of this population in SLiM. Note that this is called a 'subpopulation' in SLiM.", "binaryFormat": "i", - "index": 1}, + "index": 1, + }, "selfing_fraction": { "type": "number", "description": "The frequency with which individuals in this subpopulation self (for WF models).", "binaryFormat": "d", - "index": 2}, + "index": 2, + }, "female_cloning_fraction": { "type": "number", "description": "The frequency with which females in this subpopulation reproduce clonally (for WF models).", "binaryFormat": "d", - "index": 3}, + "index": 3, + }, "male_cloning_fraction": { "type": "number", "description": "The frequency with which males in this subpopulation reproduce clonally (for WF models).", "binaryFormat": "d", - "index": 4}, + "index": 4, + }, "sex_ratio": { "type": "number", "description": "This subpopulation's sex ratio (for WF models).", "binaryFormat": "d", - "index": 5}, + "index": 5, + }, "bounds_x0": { "type": "number", "description": "The minimum x-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 6}, + "index": 6, + }, "bounds_x1": { "type": "number", "description": "The maximum x-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 7}, + "index": 7, + }, "bounds_y0": { "type": "number", "description": "The minimum y-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 8}, + "index": 8, + }, "bounds_y1": { "type": "number", "description": "The maximum y-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 9}, + "index": 9, + }, "bounds_z0": { "type": "number", "description": "The minimum z-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 10}, + "index": 10, + }, "bounds_z1": { "type": "number", "description": "The maximum z-coordinate in this subpopulation.", "binaryFormat": "d", - "index": 11}, + "index": 11, + }, "migration_records": { "type": "array", "index": 13, @@ -987,23 +946,31 @@ def _old_metadata_schema(name, file_version): "type": "integer", "description": "The ID of the subpopulation migrants come from (in WF models).", "binaryFormat": "i", - "index": 1}, + "index": 1, + }, "migration_rate": { "type": "number", "description": "The fraction of children in this subpopulation that are composed of 'migrants' from the source subpopulation (in WF models).", "binaryFormat": "d", - "index": 2} + "index": 2, + }, }, "required": ["source_subpop", "migration_rate"], - "additionalProperties": False - } - } - } + "additionalProperties": False, + }, + }, + }, } - ms = pre_0_7_population + ms = pre_0_7_population - if (name == "individual" - and file_version in ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6"]): + if name == "individual" and file_version in [ + "0.1", + "0.2", + "0.3", + "0.4", + "0.5", + "0.6", + ]: pre_0_7_individual = { "$schema": "http://json-schema.org/schema#", "description": "SLiM schema for individual metadata.", @@ -1014,43 +981,43 @@ def _old_metadata_schema(name, file_version): "type": "integer", "description": "The 'pedigree ID' of this individual in SLiM.", "binaryFormat": "q", - "index": 1 + "index": 1, }, "age": { "type": "integer", "description": "The age of this individual, either when the tree sequence was written out (if the individual was alive then), or the last time they were Remembered (if not).", "binaryFormat": "i", - "index": 2 + "index": 2, }, "subpopulation": { "type": "integer", "description": "The ID of the subpopulation the individual was part of, either when the tree sequence was written out (if the individual was alive then), or the last time they were Remembered (if not).", "binaryFormat": "i", - "index": 3 + "index": 3, }, "sex": { "type": "integer", "description": "The sex of the individual (0 for female, 1 for male, -1 for hermaphrodite).", "binaryFormat": "i", - "index": 4 + "index": 4, }, "flags": { "type": "integer", "description": "Other information about the individual: see 'flags'.", "binaryFormat": "I", - "index": 5 - } + "index": 5, + }, }, "required": ["pedigree_id", "age", "subpopulation", "sex", "flags"], "additionalProperties": False, "flags": { - "SLIM_INDIVIDUAL_METADATA_MIGRATED": { - "value": 1, - "description": "Whether this individual was a migrant, either in the generation when the tree sequence was written out (if the individual was alive then), or in the generation of the last time they were Remembered (if not)." - } + "SLIM_INDIVIDUAL_METADATA_MIGRATED": { + "value": 1, + "description": "Whether this individual was a migrant, either in the generation when the tree sequence was written out (if the individual was alive then), or in the generation of the last time they were Remembered (if not).", + } }, } - ms = pre_0_7_individual + ms = pre_0_7_individual if name == "mutation" and file_version in ["0.1", "0.2"]: mutation_pre_0_3 = { @@ -1069,31 +1036,35 @@ def _old_metadata_schema(name, file_version): "type": "integer", "description": "The index of this mutation's mutationType.", "binaryFormat": "i", - "index": 1 + "index": 1, }, "selection_coeff": { "type": "number", "description": "This mutation's selection coefficient.", "binaryFormat": "f", - "index": 2 + "index": 2, }, "subpopulation": { "type": "integer", "description": "The ID of the subpopulation this mutation occurred in.", "binaryFormat": "i", - "index": 3 + "index": 3, }, "slim_time": { "type": "integer", "description": "The SLiM generation counter when this mutation occurred.", "binaryFormat": "i", - "index": 4 + "index": 4, }, }, - "required": ["mutation_type", "selection_coeff", "subpopulation", - "slim_time"], - "additionalProperties": False - } + "required": [ + "mutation_type", + "selection_coeff", + "subpopulation", + "slim_time", + ], + "additionalProperties": False, + }, } }, "required": ["mutation_list"], @@ -1101,49 +1072,44 @@ def _old_metadata_schema(name, file_version): } ms = mutation_pre_0_3 - if (name == "node" - and file_version in ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8"]): + if name == "node" and file_version in [ + "0.1", + "0.2", + "0.3", + "0.4", + "0.5", + "0.6", + "0.7", + "0.8", + ]: node_pre_0_9 = { - "$schema": "http://json-schema.org/schema#", - "additionalProperties": False, - "codec": "struct", - "description": "SLiM schema for node metadata.", - "examples": [ - { - "genome_type": 0, - "is_null": False, - "slim_id": 123 - } - ], - "properties": { - "genome_type": { - "binaryFormat": "B", - "description": "The 'type' of this genome (0 for autosome, 1 for X, 2 for Y).", - "index": 2, - "type": "integer" + "$schema": "http://json-schema.org/schema#", + "additionalProperties": False, + "codec": "struct", + "description": "SLiM schema for node metadata.", + "examples": [{"genome_type": 0, "is_null": False, "slim_id": 123}], + "properties": { + "genome_type": { + "binaryFormat": "B", + "description": "The 'type' of this genome (0 for autosome, 1 for X, 2 for Y).", + "index": 2, + "type": "integer", }, - "is_null": { - "binaryFormat": "?", - "description": "Whether this node describes a 'null' (non-existant) chromosome.", - "index": 1, - "type": "boolean" + "is_null": { + "binaryFormat": "?", + "description": "Whether this node describes a 'null' (non-existant) chromosome.", + "index": 1, + "type": "boolean", + }, + "slim_id": { + "binaryFormat": "q", + "description": "The 'pedigree ID' of this chromosome in SLiM.", + "index": 0, + "type": "integer", }, - "slim_id": { - "binaryFormat": "q", - "description": "The 'pedigree ID' of this chromosome in SLiM.", - "index": 0, - "type": "integer" - } }, - "required": [ - "slim_id", - "is_null", - "genome_type" - ], - "type": [ - "object", - "null" - ] + "required": ["slim_id", "is_null", "genome_type"], + "type": ["object", "null"], } ms = node_pre_0_9 @@ -1164,16 +1130,14 @@ def is_current_version(ts, _warn=False): """ out = ( isinstance(ts.metadata, dict) - and - ('SLiM' in ts.metadata) - and - (ts.metadata['SLiM']['file_version'] == slim_file_version) + and ("SLiM" in ts.metadata) + and (ts.metadata["SLiM"]["file_version"] == slim_file_version) ) if _warn and not out: warnings.warn( - "This tree sequence is not the current SLiM format, " - "so some operations may not work. " - "Use `pyslim.update( )` to update the tree sequence." + "This tree sequence is not the current SLiM format, " + "so some operations may not work. " + "Use `pyslim.update( )` to update the tree sequence." ) return out @@ -1197,44 +1161,46 @@ def update_tables(tables): """ # First we ensure we can find the file format version number # in top-level metadata. Then we proceed to fix up the tables as necessary. - if not (isinstance(tables.metadata, dict) and 'SLiM' in tables.metadata): + if not (isinstance(tables.metadata, dict) and "SLiM" in tables.metadata): # Old versions kept information in provenance, not top-level metadata. # Note this uses defaults on keys not present in provenance, # which prior to 0.5 was everything but generation and model_type. - values = default_slim_metadata('tree_sequence')['SLiM'] + values = default_slim_metadata("tree_sequence")["SLiM"] prov = None - file_version = 'unknown' + file_version = "unknown" # use only the last SLiM provenance for p in tables.provenances: - is_slim, this_file_version = slim_provenance_version(p) + is_slim, this_file_version = slim_provenance_version(p) if is_slim: prov = p file_version = this_file_version - values['file_version'] = file_version + values["file_version"] = file_version try: record = json.loads(prov.record) if file_version == "0.1": - values['model_type'] = record['model_type'] - values['tick'] = record['generation'] - values['cycle'] = record['generation'] + values["model_type"] = record["model_type"] + values["tick"] = record["generation"] + values["cycle"] = record["generation"] else: - if 'generation' in record['slim']: - values['tick'] = record['slim']['generation'] - values['cycle'] = record['slim']['generation'] + if "generation" in record["slim"]: + values["tick"] = record["slim"]["generation"] + values["cycle"] = record["slim"]["generation"] for k in values: - if k in record['parameters']: - values[k] = record['parameters'][k] - if k in record['slim']: - values[k] = record['slim'][k] + if k in record["parameters"]: + values[k] = record["parameters"][k] + if k in record["slim"]: + values[k] = record["slim"][k] except: raise ValueError("Failed to obtain metadata from provenance.") set_tree_sequence_metadata(tables, **values) - file_version = tables.metadata['SLiM']['file_version'] + file_version = tables.metadata["SLiM"]["file_version"] if file_version != slim_file_version: - warnings.warn("This is a version {} SLiM tree sequence.".format(file_version) + - " If you write this out to a file, " + - "it will be converted to version {}.".format(slim_file_version)) + warnings.warn( + "This is a version {} SLiM tree sequence.".format(file_version) + + " If you write this out to a file, " + + "it will be converted to version {}.".format(slim_file_version) + ) # the only tables to have metadata schema changed thus far # are nodes, populations, individuals, mutations, and top-level: @@ -1242,16 +1208,16 @@ def update_tables(tables): if old_schema is not None: md = tables.metadata new_schema = slim_metadata_schemas["tree_sequence"] - new_properties = new_schema.asdict()['properties']['SLiM']['required'] + new_properties = new_schema.asdict()["properties"]["SLiM"]["required"] tables.metadata_schema = new_schema defaults = default_slim_metadata("tree_sequence") for k in new_properties: - if k not in md['SLiM']: + if k not in md["SLiM"]: if k == "tick": - md['SLiM']['tick'] = md['SLiM']['generation'] - md['SLiM']['cycle'] = md['SLiM']['generation'] + md["SLiM"]["tick"] = md["SLiM"]["generation"] + md["SLiM"]["cycle"] = md["SLiM"]["generation"] else: - md['SLiM'][k] = defaults['SLiM'][k] + md["SLiM"][k] = defaults["SLiM"][k] tables.metadata = md old_schema = _old_metadata_schema("node", file_version) @@ -1273,16 +1239,18 @@ def update_tables(tables): for n in nodes: md = n.metadata if len(md) > 0: - md['is_vacant'] = yes_vacant if md['is_null'] else not_vacant - if not md['is_null']: + md["is_vacant"] = yes_vacant if md["is_null"] else not_vacant + if not md["is_null"]: if gt is None: - gt = md['genome_type'] + gt = md["genome_type"] else: - assert md['genome_type'] == gt, ("Inconsistent tables: " - f"mismatching genome types {gt} and " - f"{md['genome_type']} in node metadata.") - del md['is_null'] - del md['genome_type'] + assert md["genome_type"] == gt, ( + "Inconsistent tables: " + f"mismatching genome types {gt} and " + f"{md['genome_type']} in node metadata." + ) + del md["is_null"] + del md["genome_type"] tables.nodes.append(n.replace(metadata=md)) # flags for node genome type pre-0.9: # confusingly and sub-optimally, these were redundant: @@ -1292,22 +1260,24 @@ def update_tables(tables): GENOME_TYPE_X = 1 GENOME_TYPE_Y = 2 top_md = tables.metadata - i = top_md['SLiM']['this_chromosome']['index'] + i = top_md["SLiM"]["this_chromosome"]["index"] # 'chromosomes' is not required so won't be inserted, # so we won't update it also - assert "chromosomes" not in top_md['SLiM']['this_chromosome'], ("" - "This is an unexpected result: if you hit this, " - "please file a bug at " - "https://github.com/tskit-dev/pyslim.") + assert "chromosomes" not in top_md["SLiM"]["this_chromosome"], ( + "" + "This is an unexpected result: if you hit this, " + "please file a bug at " + "https://github.com/tskit-dev/pyslim." + ) if gt == GENOME_TYPE_X: - top_md['SLiM']['this_chromosome']['type'] = "X" - top_md['SLiM']['this_chromosome']['symbol'] = "X" + top_md["SLiM"]["this_chromosome"]["type"] = "X" + top_md["SLiM"]["this_chromosome"]["symbol"] = "X" # if "chromosomes" in tables.metadata['SLiM']: # top_md['SLiM']['chromosomes'][i]['type'] = "X" # top_md['SLiM']['chromosomes'][i]['symbol'] = "X" elif gt == GENOME_TYPE_Y: - top_md['SLiM']['this_chromosome']['type'] = "-Y" - top_md['SLiM']['this_chromosome']['symbol'] = "Y" + top_md["SLiM"]["this_chromosome"]["type"] = "-Y" + top_md["SLiM"]["this_chromosome"]["symbol"] = "Y" # top_md['SLiM']['chromosomes'][i]['type'] = "Y" # top_md['SLiM']['chromosomes'][i]['symbol'] = "Y" else: @@ -1352,47 +1322,49 @@ def update_tables(tables): tables.mutations.metadata_schema = slim_metadata_schemas["mutation"] for mut in muts: md = mut.metadata - for ml in md['mutation_list']: - ml['nucleotide'] = -1 + for ml in md["mutation_list"]: + ml["nucleotide"] = -1 tables.mutations.append(mut.replace(metadata=md)) if file_version == "0.1": # shift times - slim_generation = tables.metadata['SLiM']['tick'] + slim_generation = tables.metadata["SLiM"]["tick"] node_times = tables.nodes.time + slim_generation tables.nodes.set_columns( - flags=tables.nodes.flags, - time=node_times, - population=tables.nodes.population, - individual=tables.nodes.individual, - metadata=tables.nodes.metadata, - metadata_offset=tables.nodes.metadata_offset) + flags=tables.nodes.flags, + time=node_times, + population=tables.nodes.population, + individual=tables.nodes.individual, + metadata=tables.nodes.metadata, + metadata_offset=tables.nodes.metadata_offset, + ) migration_times = tables.migrations.time + slim_generation tables.migrations.set_columns( - left=tables.migrations.left, - right=tables.migrations.right, - node=tables.migrations.node, - source=tables.migrations.source, - dest=tables.migrations.dest, - time=migration_times) + left=tables.migrations.left, + right=tables.migrations.right, + node=tables.migrations.node, + source=tables.migrations.source, + dest=tables.migrations.dest, + time=migration_times, + ) new_record = { - "schema_version": "1.0.0", - "software": { - "name": "pyslim", - "version": pyslim_version, - }, - "parameters": { - "command": ["updrade_tables"], - "old_file_version": file_version, - "new_file_version": slim_file_version, - }, - "environment": get_environment(), - } + "schema_version": "1.0.0", + "software": { + "name": "pyslim", + "version": pyslim_version, + }, + "parameters": { + "command": ["updrade_tables"], + "old_file_version": file_version, + "new_file_version": slim_file_version, + }, + "environment": get_environment(), + } tskit.validate_provenance(new_record) tables.provenances.add_row(json.dumps(new_record)) set_metadata_schemas(tables) md = tables.metadata - md['SLiM']['file_version'] = slim_file_version + md["SLiM"]["file_version"] = slim_file_version tables.metadata = md diff --git a/pyslim/slim_tree_sequence.py b/pyslim/slim_tree_sequence.py index 3ae04523..95de0333 100644 --- a/pyslim/slim_tree_sequence.py +++ b/pyslim/slim_tree_sequence.py @@ -1,19 +1,17 @@ -import msprime -import tskit -import json -import warnings import numpy as np +import tskit -from ._version import * -from .slim_metadata import _old_metadata_schema from pyslim import NUCLEOTIDES +from ._version import * # noqa F403 + + def load(*args, **kwargs): raise RuntimeError("This method has been removed: use tskit.load( ) instead.") def mutation_at(ts, node, position, time=None): - ''' + """ Finds the mutation present in the genome of ``node`` at ``position``, returning -1 if there is no such mutation recorded in the tree sequence. Warning: if ``node`` is not actually in the tree sequence @@ -28,7 +26,7 @@ def mutation_at(ts, node, position, time=None): in which case the ``time`` of ``node`` is used. :returns: Index of the mutation in question, or -1 if none. - ''' + """ if position < 0 or position >= ts.sequence_length: raise ValueError("Position {} not valid.".format(position)) if node < 0 or node >= ts.num_nodes: @@ -56,12 +54,13 @@ def mutation_at(ts, node, position, time=None): for mut in site.mutations: if mut.node == n and mut.time >= time: # BUG: this can fail if a mutation has two children - assert(out == tskit.NULL or out == mut.parent) + assert out == tskit.NULL or out == mut.parent out = mut.id return out + def nucleotide_at(ts, node, position, time=None): - ''' + """ Finds the nucleotide present in the genome of ``node`` at ``position``. Warning: if ``node`` is not actually in the tree sequence (e.g., not ancestral to any samples) at ``position``, then this function will @@ -76,7 +75,7 @@ def nucleotide_at(ts, node, position, time=None): in which case the ``time`` of ``node`` is used. :returns: Index of the nucleotide in ``NUCLEOTIDES`` (0=A, 1=C, 2=G, 3=T). - ''' + """ if not ts.has_reference_sequence(): raise ValueError("This tree sequence has no reference sequence.") mut_id = mutation_at(ts, node, position, time) diff --git a/pyslim/spatial.py b/pyslim/spatial.py index 653448c6..d4abc4d2 100644 --- a/pyslim/spatial.py +++ b/pyslim/spatial.py @@ -1,13 +1,12 @@ -import msprime -import tskit import warnings + import numpy as np -from .methods import individual_ages, individuals_alive_at +from .methods import individual_ages def _in_location_bin(locations, x0, x1, y0, y1): - ''' + """ Takes the locations of individuals and tests if each is within [x0, x1) and [y0, y1). Returns a list the same length as the number of individuals with True if the corresponding individual is within the bounds and False @@ -20,20 +19,15 @@ def _in_location_bin(locations, x0, x1, y0, y1): :param float x1: The upper x coordinate boundary. :param float y0: The lower y coordinate boundary. :param float y1: The upper y coordinate boundary. - ''' + """ return np.logical_and( - np.logical_and( - locations[:,0] < x1, - locations[:,0] >= x0), - np.logical_and( - locations[:,1] < y1, - locations[:,1] >= y0 - ) - ) + np.logical_and(locations[:, 0] < x1, locations[:, 0] >= x0), + np.logical_and(locations[:, 1] < y1, locations[:, 1] >= y0), + ) def _average_time_alive(birth_times, death_times, t0, t1): - ''' + """ Calculates the average population size in the time interval [`t0`, `t1`) from birth times and death times of individuals. This is a helper function for `population_size`, and may change or be removed in the future. @@ -63,15 +57,15 @@ def _average_time_alive(birth_times, death_times, t0, t1): :param float t0: Lower time endpoint. :param float t1: Upper time endpoint. t1 is greater than t0. - ''' + """ # length of the segment of time in [t0, t1) that the individual # was alive for, i.e., of the intersection with [birth, death]. - a = np.maximum(0, np.minimum(t1, 1 + birth_times) - np.maximum(t0, death_times)) - return sum(a)/(t1-t0) + a = np.maximum(0, np.minimum(t1, 1 + birth_times) - np.maximum(t0, death_times)) + return sum(a) / (t1 - t0) -def population_size(ts, x_bins, y_bins, time_bins, stage='late', remembered_stage=None): - ''' +def population_size(ts, x_bins, y_bins, time_bins, stage="late", remembered_stage=None): + """ Calculates the population size in each of the spatial bins defined by grid lines at ``x_bins`` and ``y_bins``, averaged over each of the time intervals separated by ``time_bins``. To obtain actual (census) sizes, the tree sequence must contain @@ -100,38 +94,39 @@ def population_size(ts, x_bins, y_bins, time_bins, stage='late', remembered_stag :param str remembered_stage: The stage in the SLiM life cycle during which individuals were Remembered (defaults to the stage the tree sequence was recorded at, stored in metadata). - ''' + """ # TODO: make a helper function to do this if stage not in ("late", "early"): - raise ValueError(f"Unknown stage '{stage}': " - "should be either 'early' or 'late'.") + raise ValueError(f"Unknown stage '{stage}': should be either 'early' or 'late'.") if remembered_stage is None: - remembered_stage = ts.metadata['SLiM']['stage'] + remembered_stage = ts.metadata["SLiM"]["stage"] if remembered_stage not in ("late", "early"): - raise ValueError(f"Unknown remembered_stage '{remembered_stage}': " - "should be either 'early' or 'late'.") - if remembered_stage != ts.metadata['SLiM']['stage']: - warnings.warn(f"Provided remembered_stage '{remembered_stage}' does not" - " match the stage at which the tree sequence was saved" - f" ('{ts.metadata['SLiM']['stage']}'). This is not necessarily" - " an error, but mismatched stages will lead to inconsistencies:" - " make sure you know what you're doing.") + raise ValueError( + f"Unknown remembered_stage '{remembered_stage}': " + "should be either 'early' or 'late'." + ) + if remembered_stage != ts.metadata["SLiM"]["stage"]: + warnings.warn( + f"Provided remembered_stage '{remembered_stage}' does not" + " match the stage at which the tree sequence was saved" + f" ('{ts.metadata['SLiM']['stage']}'). This is not necessarily" + " an error, but mismatched stages will lead to inconsistencies:" + " make sure you know what you're doing." + ) # see individuals_alive_at for explanation - if stage == "early" and ts.metadata['SLiM']['model_type'] == "WF": + if stage == "early" and ts.metadata["SLiM"]["model_type"] == "WF": birth_offset = 1 else: birth_offset = 0 birth_times = ts.individuals_time - birth_offset - if (ts.metadata['SLiM']['model_type'] == "WF" - or stage == remembered_stage): + if ts.metadata["SLiM"]["model_type"] == "WF" or stage == remembered_stage: age_offset = 0 else: - if (remembered_stage == "early" - and stage == "late"): + if remembered_stage == "early" and stage == "late": age_offset = -1 else: age_offset = 1 @@ -157,10 +152,10 @@ def population_size(ts, x_bins, y_bins, time_bins, stage='late', remembered_stag for k in np.arange(ntbins): t0, t1 = time_breaks[k], time_breaks[k + 1] popsize[i, j, k] = _average_time_alive( - birth_times[in_bin], - death_times[in_bin], - t0, - t1, + birth_times[in_bin], + death_times[in_bin], + t0, + t1, ) return popsize diff --git a/pyslim/util.py b/pyslim/util.py index c4f58d22..759abdef 100644 --- a/pyslim/util.py +++ b/pyslim/util.py @@ -1,8 +1,10 @@ import warnings + import numpy as np + def unique_labels_by_group(group, label, minlength=0): - ''' + """ Given an array of integers ("group") from -1 and up and an array of integer "labels" of the same length, returns a logical value for each distinct value of ``group``, except for -1, indicating if all the entries of @@ -11,18 +13,18 @@ def unique_labels_by_group(group, label, minlength=0): In other words, if the result is ``x``, then ``x[j]`` is ``len(set(label[group == j])) <= 1``. - ''' + """ warnings.warn( - "The unique_labels_by_group( ) method is no longer used in pyslim, " - "so is now deprecated. Please copy the source code for your own use " - "if you wish to keep using it.", - FutureWarning, + "The unique_labels_by_group( ) method is no longer used in pyslim, " + "so is now deprecated. Please copy the source code for your own use " + "if you wish to keep using it.", + FutureWarning, ) w = label.astype("float64") n = np.bincount(1 + group, minlength=minlength + 1) x = np.bincount(1 + group, weights=w, minlength=minlength + 1) - with np.errstate(divide='ignore', invalid='ignore'): - xm = x/n + with np.errstate(divide="ignore", invalid="ignore"): + xm = x / n xm[n == 0] = 0 w -= xm[1 + group] gw = np.bincount(1 + group, weights=np.abs(w), minlength=minlength + 1)[1:] diff --git a/tests/__init__.py b/tests/__init__.py index 56c4e424..0996d1a3 100644 --- a/tests/__init__.py +++ b/tests/__init__.py @@ -1,33 +1,33 @@ """ Common code for the pyslim test cases. """ -import os + import json +import os import random import warnings -import pyslim -import tskit import msprime -import pytest import numpy as np +import pytest +import tskit + +import pyslim class PyslimTestCase: - ''' + """ Base class for test cases in pyslim. - ''' + """ def verify_haplotype_equality(self, ts, slim_ts): assert ts.num_sites == slim_ts.num_sites - for j, v1, v2 in zip(range(ts.num_sites), ts.variants(), - slim_ts.variants()): + for j, v1, v2 in zip(range(ts.num_sites), ts.variants(), slim_ts.variants()): g1 = [v1.alleles[x] for x in v1.genotypes] g2 = [v2.alleles[x] for x in v2.genotypes] assert np.array_equal(g1, g2) - - def assertTablesEqual(self, t1, t2, label=''): + def assertTablesEqual(self, t1, t2, label=""): # make it easy to see what's wrong if hasattr(t1, "metadata_schema"): if t1.metadata_schema != t2.metadata_schema: @@ -70,11 +70,11 @@ def verify_trees_equal(self, ts1, ts2): map1 = {} for j, n in enumerate(ts1.nodes()): if n.metadata is not None: - map1[n.metadata['slim_id']] = j + map1[n.metadata["slim_id"]] = j map2 = {} for j, n in enumerate(ts2.nodes()): if n.metadata is not None: - map2[n.metadata['slim_id']] = j + map2[n.metadata["slim_id"]] = j assert set(map1.keys()) == set(map2.keys()) print(ts1) print(map1) @@ -100,22 +100,35 @@ def verify_trees_equal(self, ts1, ts2): a, b = random.choices(sids, k=2) print(a, b, map1[a], map1[b], map2[a], map2[b]) print(t1) - print('a', t1.time(map1[a])) - print('b', t1.time(map1[b])) - print('1', t1.tmrca(map1[a], map1[b])) - print('2', t2.tmrca(map2[a], map2[b])) + print("a", t1.time(map1[a])) + print("b", t1.time(map1[b])) + print("1", t1.tmrca(map1[a], map1[b])) + print("2", t2.tmrca(map2[a], map2[b])) assert t1.tmrca(map1[a], map1[b]) == t2.tmrca(map2[a], map2[b]) - def assertTableCollectionsEqual(self, t1, t2, - skip_provenance=False, check_metadata_schema=True, - reordered_individuals=False): + def assertTableCollectionsEqual( + self, + t1, + t2, + skip_provenance=False, + check_metadata_schema=True, + reordered_individuals=False, + ): if isinstance(t1, tskit.TreeSequence): t1 = t1.dump_tables() if isinstance(t2, tskit.TreeSequence): t2 = t2.dump_tables() - t1_samples = [(n.metadata['slim_id'], j) for j, n in enumerate(t1.nodes) if (n.flags & tskit.NODE_IS_SAMPLE)] + t1_samples = [ + (n.metadata["slim_id"], j) + for j, n in enumerate(t1.nodes) + if (n.flags & tskit.NODE_IS_SAMPLE) + ] t1_samples.sort() - t2_samples = [(n.metadata['slim_id'], j) for j, n in enumerate(t2.nodes) if (n.flags & tskit.NODE_IS_SAMPLE)] + t2_samples = [ + (n.metadata["slim_id"], j) + for j, n in enumerate(t2.nodes) + if (n.flags & tskit.NODE_IS_SAMPLE) + ] t2_samples.sort() t1.simplify([j for (_, j) in t1_samples], record_provenance=False) t2.simplify([j for (_, j) in t2_samples], record_provenance=False) @@ -129,13 +142,25 @@ def assertTableCollectionsEqual(self, t1, t2, if check_metadata_schema: # this is redundant now, but will help diagnose if things go wrong assert t1.metadata_schema.schema == t2.metadata_schema.schema - assert t1.populations.metadata_schema.schema == t2.populations.metadata_schema.schema - assert t1.individuals.metadata_schema.schema == t2.individuals.metadata_schema.schema + assert ( + t1.populations.metadata_schema.schema + == t2.populations.metadata_schema.schema + ) + assert ( + t1.individuals.metadata_schema.schema + == t2.individuals.metadata_schema.schema + ) assert t1.nodes.metadata_schema.schema == t2.nodes.metadata_schema.schema assert t1.edges.metadata_schema.schema == t2.edges.metadata_schema.schema assert t1.sites.metadata_schema.schema == t2.sites.metadata_schema.schema - assert t1.mutations.metadata_schema.schema == t2.mutations.metadata_schema.schema - assert t1.migrations.metadata_schema.schema == t2.migrations.metadata_schema.schema + assert ( + t1.mutations.metadata_schema.schema + == t2.mutations.metadata_schema.schema + ) + assert ( + t1.migrations.metadata_schema.schema + == t2.migrations.metadata_schema.schema + ) if not check_metadata_schema: # need to pull out metadata to compare as dicts before zeroing the schema m1 = t1.metadata @@ -150,14 +175,14 @@ def assertTableCollectionsEqual(self, t1, t2, t.sites.metadata_schema = ms t.mutations.metadata_schema = ms t.migrations.metadata_schema = ms - t1.metadata = b'' - t2.metadata = b'' + t1.metadata = b"" + t2.metadata = b"" assert m1 == m2 if reordered_individuals: - ind1 = {i.metadata['pedigree_id']: j for j, i in enumerate(t1.individuals)} - ind2 = {i.metadata['pedigree_id']: j for j, i in enumerate(t2.individuals)} + ind1 = {i.metadata["pedigree_id"]: j for j, i in enumerate(t1.individuals)} + ind2 = {i.metadata["pedigree_id"]: j for j, i in enumerate(t2.individuals)} for pid in ind1: - if not pid in ind2: + if pid not in ind2: print("not in t2:", ind1[pid]) assert pid in ind2 if t1.individuals[ind1[pid]] != t2.individuals[ind2[pid]]: @@ -165,7 +190,7 @@ def assertTableCollectionsEqual(self, t1, t2, print("t2:", t2.individuals[ind2[pid]]) assert t1.individuals[ind1[pid]] == t2.individuals[ind2[pid]] for pid in ind2: - if not pid in ind1: + if pid not in ind1: print("not in t1:", ind2[pid]) assert pid in ind1 t1.individuals.clear() @@ -192,7 +217,6 @@ def assertTableCollectionsEqual(self, t1, t2, def do_recapitate(self, ts, *args, **kwargs): with warnings.catch_warnings(): - warnings.simplefilter('ignore', msprime.TimeUnitsMismatchWarning) + warnings.simplefilter("ignore", msprime.TimeUnitsMismatchWarning) recap = pyslim.recapitate(ts, *args, **kwargs) return recap - diff --git a/tests/conftest.py b/tests/conftest.py index 001c9497..0a3fa875 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,15 +1,16 @@ -from collections import namedtuple +import json import os -import pytest -import random import subprocess +from collections import namedtuple +import msprime +import pytest +import tskit from filelock import FileLock -import json -import tskit, msprime from .recipe_specs import recipe_specs + class Outfiles: """ Simple wrapper for a list of Outfile items: these specify a file path that SLiM can @@ -17,13 +18,14 @@ class Outfiles: recipe, a function to apply to the path to create an object for the unit test to access and a "name" (key) in the dictionary to access that object in the unit test. """ + Outfile = namedtuple("Outfile", "path, slim_name, post_process, key") @staticmethod def read_dictionary(fname): # reads in the json-written dictionary assert os.path.isfile(fname) - with open(fname, "r") as f: + with open(fname) as f: out = json.load(f) return out @@ -37,9 +39,16 @@ def parse_pedigree_info(fname): # not alive for) assert os.path.isfile(fname) out = {} - with open(fname, 'r') as f: + with open(fname) as f: header = f.readline().split() - assert header == ['generation', 'stage', 'individual', 'age', 'parent1', 'parent2'] + assert header == [ + "generation", + "stage", + "individual", + "age", + "parent1", + "parent2", + ] for line in f: gen, stage, ind, age, p1, p2 = line.split() gen = int(gen) @@ -47,20 +56,17 @@ def parse_pedigree_info(fname): age = int(age) parents = tuple([int(p) for p in (p1, p2) if p != "-1"]) if ind not in out: - out[ind] = { - "parents" : parents, - "age" : {} - } + out[ind] = {"parents": parents, "age": {}} else: for p in parents: - assert p in out[ind]['parents'] - out[ind]['age'][(gen, stage)] = age + assert p in out[ind]["parents"] + out[ind]["age"][(gen, stage)] = age return out def load_ts(self, path): out = {} if os.path.isfile(path): - out['default'] = tskit.load(path) + out["default"] = tskit.load(path) elif os.path.isdir(path): chroms = os.listdir(path) for cfile in os.listdir(path): @@ -97,43 +103,44 @@ def __getitem__(self, index): def __len__(self, index): return len(self._outfiles) - + def results(self): res = {"path": {}} for o in self._outfiles: res["path"][o.key] = o.path if os.path.isfile(o.path) or os.path.isdir(o.path): assert o.key not in res - res[o.key] = o.post_process(o.path) + res[o.key] = o.post_process(o.path) return res class MultiOutfiles(Outfiles): - def __init__(self, out_dir, species): # Note: the 'key' below cannot match a 'key' in recipe_specs self._outfiles = [] for sp in species: - self._outfiles.extend([ - self.Outfile( - path=os.path.join(out_dir, f"{sp}_out.trees"), - slim_name=f"TREES_FILE_{sp}", # The var containing the path name for SLiM output - post_process=tskit.load, # function applied on path to create returned obj - key=f"ts_{sp}", # The key to use for the post-processed item in the returned dict - ), - self.Outfile( - path=os.path.join(out_dir, f"{sp}_out.pedigree"), - slim_name=f"PEDIGREE_FILE_{sp}", - post_process=self.parse_pedigree_info, - key=f"info_{sp}", - ), - self.Outfile( - path=os.path.join(out_dir, f"{sp}_out_mutations.json"), - slim_name=f"MUTATIONS_FILE_{sp}", - post_process=self.read_dictionary, - key=f"mutation_info_{sp}", - ), - ]) + self._outfiles.extend( + [ + self.Outfile( + path=os.path.join(out_dir, f"{sp}_out.trees"), + slim_name=f"TREES_FILE_{sp}", # The var containing the path name for SLiM output + post_process=tskit.load, # function applied on path to create returned obj + key=f"ts_{sp}", # The key to use for the post-processed item in the returned dict + ), + self.Outfile( + path=os.path.join(out_dir, f"{sp}_out.pedigree"), + slim_name=f"PEDIGREE_FILE_{sp}", + post_process=self.parse_pedigree_info, + key=f"info_{sp}", + ), + self.Outfile( + path=os.path.join(out_dir, f"{sp}_out_mutations.json"), + slim_name=f"MUTATIONS_FILE_{sp}", + post_process=self.read_dictionary, + key=f"mutation_info_{sp}", + ), + ] + ) def run_slim(recipe, out_dir, recipe_dir="test_recipes", species=None, **kwargs): @@ -154,26 +161,28 @@ def run_slim(recipe, out_dir, recipe_dir="test_recipes", species=None, **kwargs) for o in outfiles: if o.slim_name != "": # for happy windows filepaths - tmp_str = o.path.replace('\\', '\\\\') - slim_vars += ["-d", f"{o.slim_name}=\"{tmp_str}\""] + tmp_str = o.path.replace("\\", "\\\\") + slim_vars += ["-d", f'{o.slim_name}="{tmp_str}"'] for k in kwargs: x = kwargs[k] if x is not None: - if isinstance(x, str) and x[:10] != 'Dictionary': + if isinstance(x, str) and x[:10] != "Dictionary": # for happy windows filepaths - x = x.replace('\\', '\\\\') + x = x.replace("\\", "\\\\") x = f"'{x}'" if isinstance(x, bool): - x = 'T' if x else 'F' + x = "T" if x else "F" slim_vars += ["-d", f"{k}={x}"] cmd = ["slim", "-s", "23"] + slim_vars + [full_recipe] - print(f"Running {' '.join(cmd)}, outputting errors etc. to '{out_dir}/SLiM_run_output.log'") + print( + f"Running {' '.join(cmd)}, outputting errors etc. to '{out_dir}/SLiM_run_output.log'" + ) with open(os.path.join(out_dir, "SLiM_run_output.log"), "w") as out: retval = subprocess.call(cmd, stderr=subprocess.STDOUT, stdout=out) if retval != 0: errmsg = f"Could not run {' '.join(cmd)}" errline = False - with open(os.path.join(out_dir, "SLiM_run_output.log"), "r") as err: + with open(os.path.join(out_dir, "SLiM_run_output.log")) as err: for line in err: if line[:5] == "ERROR" or line[:5] == "Error": errline = True @@ -190,20 +199,26 @@ def _obj_to_eidos(x): elif isinstance(x, dict): out = _dict_to_eidos(x) elif x is None: - out = 'NULL' + out = "NULL" else: out = x return out def _dict_to_eidos(d): - txt = "Dictionary(" + ", ".join([f"\"{a}\", {_obj_to_eidos(b)}" for a, b in d.items()]) + ")" + txt = ( + "Dictionary(" + + ", ".join([f'"{a}", {_obj_to_eidos(b)}' for a, b in d.items()]) + + ")" + ) return txt class HelperFunctions: @classmethod - def run_slim_restart(cls, in_ts, recipe, out_dir, multichrom, subpop_map=None, **kwargs): + def run_slim_restart( + cls, in_ts, recipe, out_dir, multichrom, subpop_map=None, **kwargs + ): # Saves out the tree sequence to a trees file and run the SLiM recipe # on it, saving to files in out_dir. assert isinstance(in_ts, dict) @@ -216,22 +231,24 @@ def run_slim_restart(cls, in_ts, recipe, out_dir, multichrom, subpop_map=None, * os.mkdir(infile) for chrom, ts in in_ts.items(): ts.dump(os.path.join(infile, f"{chrom}.trees")) - # for happy windows filepaths - infile_str = infile.replace('\\', '\\\\') - kwargs['TREES_IN'] = infile - if 'STAGE' not in kwargs: - kwargs['STAGE'] = ts.metadata['SLiM']['stage'] + # for happy windows filepaths + infile_str = infile.replace("\\", "\\\\") + kwargs["TREES_IN"] = infile + if "STAGE" not in kwargs: + kwargs["STAGE"] = ts.metadata["SLiM"]["stage"] if subpop_map is not None: # subpopMap argument has entries like { "p1" : 2 }, # meaning that when loaded in, subpop p1 will be the second row # in the population table spm = _dict_to_eidos(subpop_map) - kwargs['SUBPOP_MAP'] = spm + kwargs["SUBPOP_MAP"] = spm results = run_slim(recipe, out_dir, **kwargs) return results["ts"] @classmethod - def run_multispecies_slim_restart(cls, in_ts, recipe, out_dir, subpop_map=None, **kwargs): + def run_multispecies_slim_restart( + cls, in_ts, recipe, out_dir, subpop_map=None, **kwargs + ): # in_ts should now be a dictionary with keys corresponding to species names infiles = {} for sp in in_ts: @@ -240,17 +257,17 @@ def run_multispecies_slim_restart(cls, in_ts, recipe, out_dir, subpop_map=None, infiles_str_dict = {} for k, v in infiles.items(): # for happy windows filepaths - infiles_str_dict[k] = v.replace('\\', '\\\\') - kwargs['TREES_IN'] = _dict_to_eidos(infiles_str_dict) - if 'STAGE' not in kwargs: - kwargs['STAGE'] = in_ts[sp].metadata['SLiM']['stage'] + infiles_str_dict[k] = v.replace("\\", "\\\\") + kwargs["TREES_IN"] = _dict_to_eidos(infiles_str_dict) + if "STAGE" not in kwargs: + kwargs["STAGE"] = in_ts[sp].metadata["SLiM"]["stage"] if subpop_map is not None: # subpopMap argument has entries like { "p1" : 2 }, # meaning that when loaded in, subpop p1 will be the second row # in the population table - kwargs['SUBPOP_MAP'] = _dict_to_eidos(subpop_map) + kwargs["SUBPOP_MAP"] = _dict_to_eidos(subpop_map) results = run_slim(recipe, out_dir, species=list(in_ts.keys()), **kwargs) - out = { sp: results[f"ts_{sp}"] for sp in in_ts } + out = {sp: results[f"ts_{sp}"] for sp in in_ts} return out @classmethod @@ -277,18 +294,16 @@ def get_msprime_examples(): for n in [2, 20]: for recrate in [0.0, 0.01]: ts = msprime.sim_ancestry( - n, - recombination_rate=recrate, - population_size=10, - sequence_length=200, - random_seed=seed, - model="dtwf" + n, + recombination_rate=recrate, + population_size=10, + sequence_length=200, + random_seed=seed, + model="dtwf", ) yield ts mts = msprime.sim_mutations( - ts, - model=msprime.SLiMMutationModel(type=0), - rate=mutrate + ts, model=msprime.SLiMMutationModel(type=0), rate=mutrate ) yield mts seed += 1 @@ -297,17 +312,15 @@ def get_msprime_examples(): demography.add_population(name="B", initial_size=30) demography.add_population(name="C", initial_size=10) demography.add_population_split( - time=5, - derived=["A", "B"], - ancestral="C" + time=5, derived=["A", "B"], ancestral="C" ) ts = msprime.sim_ancestry( - {"A": n, "B": n}, - demography=demography, - recombination_rate=recrate, - sequence_length=250, - random_seed=seed, - model="dtwf" + {"A": n, "B": n}, + demography=demography, + recombination_rate=recrate, + sequence_length=250, + random_seed=seed, + model="dtwf", ) yield ts seed += 1 @@ -337,6 +350,6 @@ def recipe(request, tmp_path_factory, worker_id): else: os.makedirs(out_dir, exist_ok=True) ret = run_slim(recipe=recipe_name, out_dir=out_dir) - + ret.update(recipe_specs[recipe_name]) return ret diff --git a/tests/extra_recipes/Recipe 17.10 - Adding a neutral burn-in after simulation with recapitation II.py b/tests/extra_recipes/Recipe 17.10 - Adding a neutral burn-in after simulation with recapitation II.py index afba9a27..263da8a8 100644 --- a/tests/extra_recipes/Recipe 17.10 - Adding a neutral burn-in after simulation with recapitation II.py +++ b/tests/extra_recipes/Recipe 17.10 - Adding a neutral burn-in after simulation with recapitation II.py @@ -1,18 +1,21 @@ # Keywords: Python, tree-sequence recording, tree sequence recording -import tskit, pyslim -import numpy as np import matplotlib.pyplot as plt +import numpy as np +import tskit + +import pyslim # Load the .trees file -ts = tskit.load("recipe_17.10_decap.trees") # no simplify! +ts = tskit.load("recipe_17.10_decap.trees") # no simplify! + # Calculate tree heights, giving uncoalesced sites the maximum time def tree_heights(ts): heights = np.zeros(ts.num_trees + 1) for tree in ts.trees(): if tree.num_roots > 1: # not fully coalesced - heights[tree.index] = ts.metadata['SLiM']['tick'] + heights[tree.index] = ts.metadata["SLiM"]["tick"] else: children = tree.children(tree.root) real_root = tree.root if len(children) > 1 else children[0] @@ -20,10 +23,11 @@ def tree_heights(ts): heights[-1] = heights[-2] # repeat the last entry for plotting with step return heights + # Plot tree heights before recapitation breakpoints = list(ts.breakpoints()) heights = tree_heights(ts) -plt.step(breakpoints, heights, where='post') +plt.step(breakpoints, heights, where="post") plt.show() # Recapitate! @@ -33,6 +37,5 @@ def tree_heights(ts): # Plot the tree heights after recapitation breakpoints = list(recap.breakpoints()) heights = tree_heights(recap) -plt.step(breakpoints, heights, where='post') +plt.step(breakpoints, heights, where="post") plt.show() - diff --git a/tests/extra_recipes/Recipe 17.2 - Overlaying neutral mutations.py b/tests/extra_recipes/Recipe 17.2 - Overlaying neutral mutations.py index 61266fdb..d19494a1 100644 --- a/tests/extra_recipes/Recipe 17.2 - Overlaying neutral mutations.py +++ b/tests/extra_recipes/Recipe 17.2 - Overlaying neutral mutations.py @@ -2,7 +2,8 @@ # This is a Python recipe, to be run after the section 17.1 recipe -import tskit, msprime +import msprime +import tskit ts = tskit.load("./recipe_17.1.trees") ts = ts.simplify() @@ -11,7 +12,9 @@ asserted = False try: for t in ts.trees(): - assert t.num_roots == 1, "not coalesced! on segment {} to {}".format(t.interval[0], t.interval[1]) + assert t.num_roots == 1, "not coalesced! on segment {} to {}".format( + t.interval[0], t.interval[1] + ) except AssertionError: asserted = True diff --git a/tests/extra_recipes/Recipe 17.4 - Detecting the dip in diversity (analyzing tree heights in Python) II.py b/tests/extra_recipes/Recipe 17.4 - Detecting the dip in diversity (analyzing tree heights in Python) II.py index c28e28b0..8feee8b1 100644 --- a/tests/extra_recipes/Recipe 17.4 - Detecting the dip in diversity (analyzing tree heights in Python) II.py +++ b/tests/extra_recipes/Recipe 17.4 - Detecting the dip in diversity (analyzing tree heights in Python) II.py @@ -2,9 +2,9 @@ # This is a Python recipe; note that it runs the SLiM model internally, below -import subprocess, tskit import matplotlib.pyplot as plt import numpy as np +import tskit # Run the SLiM model and load the resulting .trees # subprocess.check_output(["slim", "-m", "-s", "0", "./recipe_17.4.slim"]) @@ -16,11 +16,15 @@ for tree in ts.trees(): mean_height = np.mean([tree.time(root) for root in tree.roots]) left, right = map(int, tree.interval) - height_for_pos[left: right] = mean_height + height_for_pos[left:right] = mean_height # Convert heights along chromosome into heights at distances from gene height_for_pos = height_for_pos - np.min(height_for_pos) -L, L0, L1 = int(1e8), int(200e3), int(1e3) # total length, length between genes, gene length +L, L0, L1 = ( + int(1e8), + int(200e3), + int(1e3), +) # total length, length between genes, gene length gene_starts = np.arange(L0, L - (L0 + L1) + 1, L0 + L1) gene_ends = gene_starts + L1 - 1 max_d = L0 // 4 diff --git a/tests/extra_recipes/Recipe 17.5 - Mapping admixture (analyzing ancestry in Python) II.py b/tests/extra_recipes/Recipe 17.5 - Mapping admixture (analyzing ancestry in Python) II.py index 4e7a6eb4..e1db48a1 100644 --- a/tests/extra_recipes/Recipe 17.5 - Mapping admixture (analyzing ancestry in Python) II.py +++ b/tests/extra_recipes/Recipe 17.5 - Mapping admixture (analyzing ancestry in Python) II.py @@ -2,12 +2,12 @@ # This is a Python recipe; note that it runs the SLiM model internally, below -import subprocess, tskit import matplotlib.pyplot as plt import numpy as np +import tskit # Run the SLiM model and load the resulting .trees file -#subprocess.check_output(["slim", "-m", "-s", "0", "./recipe_17.5.slim"]) +# subprocess.check_output(["slim", "-m", "-s", "0", "./recipe_17.5.slim"]) ts = tskit.load("./recipe_17.5.trees") # Load the .trees file and assess true local ancestry @@ -16,7 +16,9 @@ for tree in ts.trees(): subpop_sum, subpop_weights = 0, 0 for root in tree.roots: - leaves_count = tree.num_samples(root) - 1 # subtract one for the root, which is a sample + leaves_count = ( + tree.num_samples(root) - 1 + ) # subtract one for the root, which is a sample subpop_sum += tree.population(root) * leaves_count subpop_weights += leaves_count breaks[tree.index] = tree.interval[0] diff --git a/tests/extra_recipes/Recipe 17.8 - Starting a hermaphroditic WF model with a coalescent history I.py b/tests/extra_recipes/Recipe 17.8 - Starting a hermaphroditic WF model with a coalescent history I.py index f6db0c83..3029e0f7 100644 --- a/tests/extra_recipes/Recipe 17.8 - Starting a hermaphroditic WF model with a coalescent history I.py +++ b/tests/extra_recipes/Recipe 17.8 - Starting a hermaphroditic WF model with a coalescent history I.py @@ -1,8 +1,11 @@ # Keywords: Python, tree-sequence recording, tree sequence recording -import msprime, pyslim +import msprime -ts = msprime.sim_ancestry(samples=5000, population_size=5000, sequence_length=1e8, - recombination_rate=1e-8) +import pyslim + +ts = msprime.sim_ancestry( + samples=5000, population_size=5000, sequence_length=1e8, recombination_rate=1e-8 +) slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) slim_ts.dump("recipe_17.8.trees") diff --git a/tests/extra_recipes/Recipe 17.9 - Starting a sexual nonWF model with a coalescent history I.py b/tests/extra_recipes/Recipe 17.9 - Starting a sexual nonWF model with a coalescent history I.py index fe256517..9374e178 100644 --- a/tests/extra_recipes/Recipe 17.9 - Starting a sexual nonWF model with a coalescent history I.py +++ b/tests/extra_recipes/Recipe 17.9 - Starting a sexual nonWF model with a coalescent history I.py @@ -1,9 +1,15 @@ # Keywords: Python, nonWF, non-Wright-Fisher, tree-sequence recording, tree sequence recording -import msprime, pyslim, random +import random + +import msprime import numpy as np -ts = msprime.sim_ancestry(samples=5000, population_size=5000, sequence_length=1e8, recombination_rate=1e-8) +import pyslim + +ts = msprime.sim_ancestry( + samples=5000, population_size=5000, sequence_length=1e8, recombination_rate=1e-8 +) tables = ts.dump_tables() pyslim.annotate_tables(tables, model_type="nonWF", tick=1) @@ -11,35 +17,39 @@ # add sexes and ages individual_metadata = [ind.metadata for ind in tables.individuals] for md in individual_metadata: - md["sex"] = random.choice([pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE]) + md["sex"] = random.choice( + [pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE] + ) md["age"] = random.choice([0, 1, 2, 3, 4]) ims = tables.individuals.metadata_schema tables.individuals.packset_metadata( - [ims.validate_and_encode_row(md) for md in individual_metadata]) + [ims.validate_and_encode_row(md) for md in individual_metadata] +) # add selected mutation mut_ind_id = random.choice(range(tables.individuals.num_rows)) mut_node_id = random.choice(np.where(tables.nodes.individual == mut_ind_id)[0]) mut_node = tables.nodes[mut_node_id] mut_metadata = { - "mutation_list": [ - { - "mutation_type": 2, - "selection_coeff": 0.1, - "subpopulation": mut_node.population, - "slim_time": int(tables.metadata['SLiM']['tick'] - mut_node.time), - "nucleotide": -1 - } - ] - } -site_num = tables.sites.add_row(position=5000, ancestral_state='') + "mutation_list": [ + { + "mutation_type": 2, + "selection_coeff": 0.1, + "subpopulation": mut_node.population, + "slim_time": int(tables.metadata["SLiM"]["tick"] - mut_node.time), + "nucleotide": -1, + } + ] +} +site_num = tables.sites.add_row(position=5000, ancestral_state="") tables.mutations.add_row( - node=mut_node_id, - site=site_num, - derived_state='1', - time=mut_node.time, - metadata=mut_metadata) + node=mut_node_id, + site=site_num, + derived_state="1", + time=mut_node.time, + metadata=mut_metadata, +) slim_ts = tables.tree_sequence() slim_ts.dump("recipe_17.9.trees") diff --git a/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models II.py b/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models II.py index 6c6a8d4e..e1812358 100644 --- a/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models II.py +++ b/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models II.py @@ -1,7 +1,9 @@ # Keywords: Python, nucleotide-based, nucleotide sequence, sequence-based mutation rate -import tskit, pyslim import numpy as np +import tskit + +import pyslim ts = tskit.load("recipe_nucleotides.trees") @@ -15,11 +17,11 @@ parent_nuc = pyslim.NUCLEOTIDES.index(acgt) else: parent_mut = ts.mutation(mut.parent) - assert(parent_mut.site == mut.site) + assert parent_mut.site == mut.site parent_nuc = parent_mut.metadata["mutation_list"][0]["nucleotide"] M[parent_nuc][derived_nuc] += 1 -print("{}\t{}\t{}".format('ancestral', 'derived', 'count')) +print("{}\t{}\t{}".format("ancestral", "derived", "count")) for j, a in enumerate(pyslim.NUCLEOTIDES): for k, b in enumerate(pyslim.NUCLEOTIDES): print("{}\t{}\t{}".format(a, b, M[j][k])) diff --git a/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models III.py b/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models III.py index 62171da2..195ca57f 100644 --- a/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models III.py +++ b/tests/extra_recipes/Recipe 18.13 - Tree-sequence recording and nucleotide-based models III.py @@ -1,28 +1,31 @@ # Keywords: Python, nucleotide-based, nucleotide sequence, sequence-based mutation rate -import tskit, pyslim import numpy as np +import tskit + +import pyslim ts = tskit.load("recipe_nucleotides.trees") slim_gen = ts.metadata["SLiM"]["tick"] -M = np.zeros((4,4,4,4), dtype='int') +M = np.zeros((4, 4, 4, 4), dtype="int") for mut in ts.mutations(): - pos = ts.site(mut.site).position + pos = ts.site(mut.site).position # skip mutations at the end of the sequence if pos > 0 and pos < ts.sequence_length - 1: mut_list = mut.metadata["mutation_list"] k = np.argmax([u["slim_time"] for u in mut_list]) derived_nuc = mut_list[k]["nucleotide"] - left_nuc = pyslim.nucleotide_at(ts, mut.node, pos - 1, time = mut.time + 1.0) - right_nuc = pyslim.nucleotide_at(ts, mut.node, pos + 1, time = mut.time + 1.0) - parent_nuc = pyslim.nucleotide_at(ts, mut.node, pos, time = mut.time + 1.0) + left_nuc = pyslim.nucleotide_at(ts, mut.node, pos - 1, time=mut.time + 1.0) + right_nuc = pyslim.nucleotide_at(ts, mut.node, pos + 1, time=mut.time + 1.0) + parent_nuc = pyslim.nucleotide_at(ts, mut.node, pos, time=mut.time + 1.0) M[left_nuc, parent_nuc, right_nuc, derived_nuc] += 1 -print("{}\t{}\t{}".format('ancestral', 'derived', 'count')) +print("{}\t{}\t{}".format("ancestral", "derived", "count")) for j0, a0 in enumerate(pyslim.NUCLEOTIDES): for j1, a1 in enumerate(pyslim.NUCLEOTIDES): for j2, a2 in enumerate(pyslim.NUCLEOTIDES): for k, b in enumerate(pyslim.NUCLEOTIDES): - print("{}{}{}\t{}{}{}\t{}".format(a0, a1, a2, a0, b, a2, - M[j0, j1, j2, k])) + print( + "{}{}{}\t{}{}{}\t{}".format(a0, a1, a2, a0, b, a2, M[j0, j1, j2, k]) + ) diff --git a/tests/extra_recipes/check_trees.py b/tests/extra_recipes/check_trees.py index d157828e..cab529e5 100755 --- a/tests/extra_recipes/check_trees.py +++ b/tests/extra_recipes/check_trees.py @@ -1,10 +1,13 @@ #!/usr/bin/env python3 import sys + import tskit -treefile = sys.argv[1] +treefile = sys.argv[1] ts = tskit.load(treefile) -print(f"The file '{treefile}' has {ts.num_trees} trees relating {ts.num_individuals} individuals " - f"with {ts.num_mutations} mutations at {ts.num_sites} sites.") +print( + f"The file '{treefile}' has {ts.num_trees} trees relating {ts.num_individuals} individuals " + f"with {ts.num_mutations} mutations at {ts.num_sites} sites." +) diff --git a/tests/recipe_specs.py b/tests/recipe_specs.py index 0c632822..283daff1 100644 --- a/tests/recipe_specs.py +++ b/tests/recipe_specs.py @@ -1,7 +1,5 @@ """specify which tests to run on each of the recipes in ./test_recipes""" -import os - # possible attributes to simulation scripts are # (the script name itself, to specify a particular one) # WF, nonWF @@ -18,47 +16,179 @@ # (chromosome type) # All files are of the form `tests/test_recipes/{key}` recipe_specs = { - "recipe_nonWF.slim": {"nonWF": True, "pedigree": True}, - "recipe_nonWF_X.slim": {"nonWF": True, "pedigree": True, "X": True}, - "recipe_nonWF_Y.slim": {"nonWF": True, "pedigree": True, "Y": True}, - "recipe_nonWF_H.slim": {"nonWF": True, "pedigree": True, "H": True}, - "recipe_WF_X.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "X": True}, - "recipe_WF_Y.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "Y": True}, - "recipe_WF_H.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "H": True}, - "recipe_WF_Z.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "Z": True}, - "recipe_WF_W.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "W": True}, - "recipe_WF_HF.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "HF": True}, - "recipe_WF_HM.slim": {"WF": True, "pedigree": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True, "HM": True}, - "recipe_long_nonWF.slim": {"nonWF": True, "long": True}, - "recipe_old_nonWF.slim": {"nonWF": True, "remembered_first": True}, - "recipe_WF.slim": {"WF": True, "pedigree": True}, - "recipe_long_WF.slim": {"WF": True, "long": True}, - "recipe_WF_migration.slim": {"WF": True, "pedigree": True, "multipop": True}, - "recipe_nucleotides_WF.slim": {"WF": True, "pedigree": True, "nucleotides": True}, - "recipe_nucleotides_nonWF.slim": {"nonWF": True, "pedigree": True, "nucleotides": True}, - "recipe_nucleotides_plus_others.slim": {"WF": True, "pedigree": True, "nucleotides": True, "non-nucleotides": True, "adds_mutations": True}, - "recipe_long_nucleotides.slim": {"WF": True, "nucleotides": True, "long": True, "nucleotides": True}, - "recipe_mutation_spectrum.slim": {"WF": True, "nucleotides": True, "mutation_spectrum": True, "nucleotides": True}, - "recipe_roots.slim": {"WF": True, "pedigree": True, "long": True}, - "recipe_starts_later.slim": {"nonWF": True, "starts_later": True}, - "recipe_nonWF_selfing.slim": {"nonWF": True, "pedigree": True}, - "recipe_nonWF_nonstacked.slim": {"nonWF": True, "nonstacked": True}, - "recipe_init_mutated_WF.slim": {"WF": True, "init_mutated": True}, - "recipe_init_mutated_nonWF.slim": {"nonWF": True, "init_mutated": True}, - "recipe_with_metadata.slim": {"user_metadata": True}, - "recipe_resettable_WF.slim": {"WF": True, "resettable": True, "user_metadata": True}, - "recipe_resettable_nonWF.slim": {"nonWF": True, "resettable": True, "user_metadata": True}, - "recipe_retain_everyone_WF_late.slim": {"WF": True, "pedigree": True, "retained": True}, - "recipe_retain_sometimes_WF_late.slim": {"WF": True, "pedigree": True, "retained": True}, - "recipe_retain_unary_WF_late.slim": {"WF": True, "pedigree": True, "retained": True, "retainCoalescentOnly": False}, - "recipe_retain_everyone_nonWF_late.slim": {"nonWF": True, "pedigree": True, "retained": True}, - "recipe_retain_sometimes_nonWF_late.slim": {"nonWF": True, "pedigree": True, "retained": True}, - "recipe_retain_unary_nonWF_late.slim": {"nonWF": True, "pedigree": True, "retained": True, "retainCoalescentOnly": False}, - "recipe_remember_and_retain.slim": {"nonWF": True, "pedigree": True, "retained": True}, - "recipe_all_the_chromosome_types.slim": {"nonWF": True, "pedigree": True, "multichrom": True, "nucleotides": True, "X": True, "Y": True, "H": True, "Z": True, "W": True, "HF": True, "FL": True, "HM": True, "ML": True, "Y-": True}, - "recipe_chromosomes_adds_muts.slim": {"WF": True, "pedigree": True, "multichrom": True, "adds_mutations": True, "nucleotides": True, "non-nucleotides": True}, - "recipe_many_chromosomes.slim": {"nonWF": True, "pedigree": True, "multichrom": True}, - "recipe_H-_chromosome.slim": {"nonWF": True, "pedigree": True, "multichrom": True, "H-": True}, + "recipe_nonWF.slim": {"nonWF": True, "pedigree": True}, + "recipe_nonWF_X.slim": {"nonWF": True, "pedigree": True, "X": True}, + "recipe_nonWF_Y.slim": {"nonWF": True, "pedigree": True, "Y": True}, + "recipe_nonWF_H.slim": {"nonWF": True, "pedigree": True, "H": True}, + "recipe_WF_X.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "X": True, + }, + "recipe_WF_Y.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "Y": True, + }, + "recipe_WF_H.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "H": True, + }, + "recipe_WF_Z.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "Z": True, + }, + "recipe_WF_W.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "W": True, + }, + "recipe_WF_HF.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "HF": True, + }, + "recipe_WF_HM.slim": { + "WF": True, + "pedigree": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + "HM": True, + }, + "recipe_long_nonWF.slim": {"nonWF": True, "long": True}, + "recipe_old_nonWF.slim": {"nonWF": True, "remembered_first": True}, + "recipe_WF.slim": {"WF": True, "pedigree": True}, + "recipe_long_WF.slim": {"WF": True, "long": True}, + "recipe_WF_migration.slim": {"WF": True, "pedigree": True, "multipop": True}, + "recipe_nucleotides_WF.slim": {"WF": True, "pedigree": True, "nucleotides": True}, + "recipe_nucleotides_nonWF.slim": { + "nonWF": True, + "pedigree": True, + "nucleotides": True, + }, + "recipe_nucleotides_plus_others.slim": { + "WF": True, + "pedigree": True, + "nucleotides": True, + "non-nucleotides": True, + "adds_mutations": True, + }, + "recipe_long_nucleotides.slim": { + "WF": True, + "nucleotides": True, + "long": True, + }, + "recipe_mutation_spectrum.slim": { + "WF": True, + "nucleotides": True, + "mutation_spectrum": True, + }, + "recipe_roots.slim": {"WF": True, "pedigree": True, "long": True}, + "recipe_starts_later.slim": {"nonWF": True, "starts_later": True}, + "recipe_nonWF_selfing.slim": {"nonWF": True, "pedigree": True}, + "recipe_nonWF_nonstacked.slim": {"nonWF": True, "nonstacked": True}, + "recipe_init_mutated_WF.slim": {"WF": True, "init_mutated": True}, + "recipe_init_mutated_nonWF.slim": {"nonWF": True, "init_mutated": True}, + "recipe_with_metadata.slim": {"user_metadata": True}, + "recipe_resettable_WF.slim": {"WF": True, "resettable": True, "user_metadata": True}, + "recipe_resettable_nonWF.slim": { + "nonWF": True, + "resettable": True, + "user_metadata": True, + }, + "recipe_retain_everyone_WF_late.slim": { + "WF": True, + "pedigree": True, + "retained": True, + }, + "recipe_retain_sometimes_WF_late.slim": { + "WF": True, + "pedigree": True, + "retained": True, + }, + "recipe_retain_unary_WF_late.slim": { + "WF": True, + "pedigree": True, + "retained": True, + "retainCoalescentOnly": False, + }, + "recipe_retain_everyone_nonWF_late.slim": { + "nonWF": True, + "pedigree": True, + "retained": True, + }, + "recipe_retain_sometimes_nonWF_late.slim": { + "nonWF": True, + "pedigree": True, + "retained": True, + }, + "recipe_retain_unary_nonWF_late.slim": { + "nonWF": True, + "pedigree": True, + "retained": True, + "retainCoalescentOnly": False, + }, + "recipe_remember_and_retain.slim": { + "nonWF": True, + "pedigree": True, + "retained": True, + }, + "recipe_all_the_chromosome_types.slim": { + "nonWF": True, + "pedigree": True, + "multichrom": True, + "nucleotides": True, + "X": True, + "Y": True, + "H": True, + "Z": True, + "W": True, + "HF": True, + "FL": True, + "HM": True, + "ML": True, + "Y-": True, + }, + "recipe_chromosomes_adds_muts.slim": { + "WF": True, + "pedigree": True, + "multichrom": True, + "adds_mutations": True, + "nucleotides": True, + "non-nucleotides": True, + }, + "recipe_many_chromosomes.slim": { + "nonWF": True, + "pedigree": True, + "multichrom": True, + }, + "recipe_H-_chromosome.slim": { + "nonWF": True, + "pedigree": True, + "multichrom": True, + "H-": True, + }, } for x in ("first", "early", "late"): @@ -87,6 +217,7 @@ for k in recipe_specs: recipe_specs[k][k] = True + def recipe_eq(*keys, exclude=None): """ Return an iterator over those recipes whose spec contains the specified keys. @@ -96,26 +227,32 @@ def recipe_eq(*keys, exclude=None): if isinstance(exclude, str) or exclude is None: exclude = [exclude] return ( - k for k, v in recipe_specs.items() + k + for k, v in recipe_specs.items() if (all(u not in v for u in exclude) and all(kk in v for kk in keys)) ) + # These SLiM scripts read in an existing trees file; the "input" gives a key in the # recipe_specs array that will produce a "ts" file suitable for input restarted_recipe_specs = { - "restart_nucleotides_WF.slim": { + "restart_nucleotides_WF.slim": { "recipe_nucleotides_WF.slim": {"WF": True, "nucleotides": True, "no_op": True}, }, - "restart_nucleotides_nonWF.slim": { - "recipe_nucleotides_nonWF.slim": {"nonWF": True, "nucleotides": True, "no_op": True}, + "restart_nucleotides_nonWF.slim": { + "recipe_nucleotides_nonWF.slim": { + "nonWF": True, + "nucleotides": True, + "no_op": True, + }, }, - "restart_and_run_WF.slim": { - "recipe_init_mutated_WF.slim": {"WF": True}, + "restart_and_run_WF.slim": { + "recipe_init_mutated_WF.slim": {"WF": True}, }, "restart_and_run_nonWF.slim": { "recipe_init_mutated_nonWF.slim": {"nonWF": True}, }, - "restart_and_remove_subpop_nonWF.slim": { + "restart_and_remove_subpop_nonWF.slim": { "recipe_init_mutated_nonWF.slim": {"nonWF": True, "remove_subpop": True}, }, # recipes that read in and write out immediately ("no_op") @@ -125,7 +262,11 @@ def recipe_eq(*keys, exclude=None): }, "restart_nonWF.slim": { "recipe_nonWF.slim": {"nonWF": True, "no_op": True}, - "recipe_resettable_nonWF.slim": {"nonWF": True, "no_op": True, "resettable": True}, + "recipe_resettable_nonWF.slim": { + "nonWF": True, + "no_op": True, + "resettable": True, + }, }, } @@ -136,6 +277,7 @@ def recipe_eq(*keys, exclude=None): d[k] = True d[j] = True + def restarted_recipe_eq(*keys): """ Return an iterator over a tuple of (restarted_recipe_name, input_recipe_name) giving @@ -147,4 +289,3 @@ def restarted_recipe_eq(*keys): if all(kk in iv for kk in keys): assert ik in recipe_specs # we need a valid input recipe yield (k, ik) - diff --git a/tests/test_annotation.py b/tests/test_annotation.py index 47ec450a..3db584c2 100644 --- a/tests/test_annotation.py +++ b/tests/test_annotation.py @@ -1,20 +1,23 @@ """ Test cases for the metadata reading/writing of pyslim. """ + +import contextlib import json -import numpy as np -import pytest import random -import warnings -import contextlib +import sys import msprime +import numpy as np +import pytest import tskit import pyslim import tests + from .recipe_specs import restarted_recipe_eq + def mutcontext(ts): if ts.num_mutations > 0: handler = pytest.warns(Warning, match="already has.*metadata") @@ -22,6 +25,7 @@ def mutcontext(ts): handler = contextlib.nullcontext() return handler + def verify_slim_restart_equality(in_ts_dict, out_ts_dict, check_prov=True): """ Check for equality, in everything but the last provenance. @@ -38,16 +42,20 @@ def verify_slim_restart_equality(in_ts_dict, out_ts_dict, check_prov=True): out_tables.sort() in_tables.assert_equals(out_tables, ignore_provenance=True) + +# This skipping is overly broad, but the output is *very* verbose and +# it's hard to track down exactly what's failing in CI. +@pytest.mark.skipif(sys.platform == "win32", reason="Issue #412") class TestAnnotate(tests.PyslimTestCase): - ''' + """ Tests for tools to annotate existing msprime-derived tree sequences. - ''' + """ def verify_annotated_tables(self, ts1, ts2, check_alleles=True): - ''' + """ Verify that the tables returned after annotation are equal, up to the expected forgetting of metadata, flags, and other things. - ''' + """ assert pyslim.is_current_version(ts2) tables1 = ts1.dump_tables() tables2 = ts2.dump_tables() @@ -60,22 +68,30 @@ def verify_annotated_tables(self, ts1, ts2, check_alleles=True): # compare sites assert np.array_equal(tables1.sites.position, tables2.sites.position) if check_alleles: - assert np.array_equal(tables1.sites.ancestral_state, tables2.sites.ancestral_state) - assert np.array_equal(tables1.sites.ancestral_state_offset, - tables2.sites.ancestral_state_offset) + assert np.array_equal( + tables1.sites.ancestral_state, tables2.sites.ancestral_state + ) + assert np.array_equal( + tables1.sites.ancestral_state_offset, + tables2.sites.ancestral_state_offset, + ) # compare mutations assert np.array_equal(tables1.mutations.site, tables2.mutations.site) assert np.array_equal(tables1.mutations.node, tables2.mutations.node) assert np.array_equal(tables1.mutations.time, tables2.mutations.time) if check_alleles: - assert np.array_equal(tables1.mutations.derived_state, tables2.mutations.derived_state) - assert np.array_equal(tables1.mutations.derived_state_offset, - tables2.mutations.derived_state_offset) + assert np.array_equal( + tables1.mutations.derived_state, tables2.mutations.derived_state + ) + assert np.array_equal( + tables1.mutations.derived_state_offset, + tables2.mutations.derived_state_offset, + ) def verify_annotated_trees(self, ts1, ts2): - ''' + """ Verify the *trees* returned before and after annotation are equal. - ''' + """ assert ts1.num_trees == ts2.num_trees for t1, t2 in zip(ts1.trees(), ts2.trees()): assert t1.length == t2.length @@ -83,14 +99,14 @@ def verify_annotated_trees(self, ts1, ts2): assert t1.total_branch_length == t2.total_branch_length def verify_defaults(self, ts): - ''' + """ Verify the default values have been entered into metadata. - ''' + """ do_pops = [False for _ in ts.populations()] for m in ts.mutations(): md = m.metadata - assert isinstance(md['mutation_list'], list) - for mdl in md['mutation_list']: + assert isinstance(md["mutation_list"], list) + for mdl in md["mutation_list"]: assert mdl["mutation_type"] == 0 assert mdl["selection_coeff"] == 0.0 assert mdl["subpopulation"] == tskit.NULL @@ -130,11 +146,11 @@ def verify_provenance(self, ts): def verify_remapping(self, ts, rts, subpop_map): # below we assume the restart has not done additional simulation - do_remap = (subpop_map is not None) + do_remap = subpop_map is not None if not do_remap: - subpop_map = { f"p{k}" : k for k in range(ts.num_populations) } - fwd_map = {-1 : -1} - rev_map = {-1 : -1} + subpop_map = {f"p{k}": k for k in range(ts.num_populations)} + fwd_map = {-1: -1} + rev_map = {-1: -1} for pk in subpop_map: # keys are requried to be of the form "pK" rts_k = int(pk[1:]) @@ -165,11 +181,11 @@ def verify_remapping(self, ts, rts, subpop_map): assert rts_md is None else: if do_remap and ( - ts_md['name'] == f"p{ts_pop.id}" - or ts_md['name'] == f"pop_{ts_pop.id}" + ts_md["name"] == f"p{ts_pop.id}" + or ts_md["name"] == f"pop_{ts_pop.id}" ): - ts_md['name'] = f"p{rts_pop.id}" - assert ts_md['name'] == rts_md['name'] + ts_md["name"] = f"p{rts_pop.id}" + assert ts_md["name"] == rts_md["name"] if "slim_id" not in ts_md: assert ts_md == rts_md else: @@ -183,8 +199,8 @@ def verify_remapping(self, ts, rts, subpop_map): if k in ts_md and k in rts_md: assert len(ts_md[k]) == len(rts_md[k]) for x, y in zip(ts_md[k], rts_md[k]): - assert x['migration_rate'] == y['migration_rate'] - assert fwd_map[x['source_subpop']] == y['source_subpop'] + assert x["migration_rate"] == y["migration_rate"] + assert fwd_map[x["source_subpop"]] == y["source_subpop"] # check other tables have been remapped # (uses the fact that no additional simulation has been done) @@ -206,19 +222,18 @@ def verify_remapping(self, ts, rts, subpop_map): for m, rm in zip(ts.mutations(), rts.mutations()): md = m.metadata rmd = rm.metadata - assert len(md['mutation_list']) == len(rmd['mutation_list']) - for x, y in zip(md['mutation_list'], rmd['mutation_list']): - x['subpopulation'] = fwd_map[x['subpopulation']] + assert len(md["mutation_list"]) == len(rmd["mutation_list"]) + for x, y in zip(md["mutation_list"], rmd["mutation_list"]): + x["subpopulation"] = fwd_map[x["subpopulation"]] assert x == y assert ts.num_individuals == rts.num_individuals for i, ri in zip(ts.individuals(), rts.individuals()): md = i.metadata rmd = ri.metadata - md['subpopulation'] = fwd_map[md['subpopulation']] + md["subpopulation"] = fwd_map[md["subpopulation"]] assert md == rmd - def test_annotate_errors(self, helper_functions): for ts in helper_functions.get_msprime_examples(): with pytest.raises(ValueError): @@ -236,10 +251,10 @@ def test_annotate_errors(self, helper_functions): assert "individuals" in str(except_info) # non-integer positions ts = msprime.sim_mutations( - msprime.sim_ancestry(4, random_seed=8), - rate=10, - discrete_genome=False, - random_seed=9, + msprime.sim_ancestry(4, random_seed=8), + rate=10, + discrete_genome=False, + random_seed=9, ) with pytest.raises(ValueError) as except_info: _ = pyslim.annotate(ts, model_type="WF", tick=1) @@ -247,70 +262,67 @@ def test_annotate_errors(self, helper_functions): def test_warns_overwriting_mutations(self, helper_functions): ts = msprime.sim_ancestry( - 4, - population_size=10, - sequence_length=10, - recombination_rate=0.01, - random_seed=100, + 4, + population_size=10, + sequence_length=10, + recombination_rate=0.01, + random_seed=100, ) ts = msprime.sim_mutations( - ts, - rate=1, - random_seed=12, - model=msprime.SLiMMutationModel(type=1) + ts, rate=1, random_seed=12, model=msprime.SLiMMutationModel(type=1) ) assert ts.num_mutations > 0 with pytest.warns(Warning, match="already has.*metadata"): - slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) + slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) def test_warns_and_overwrites_node_metadata(self, helper_functions): ts = msprime.sim_ancestry( - 4, - population_size=10, - sequence_length=10, - recombination_rate=0.01, - random_seed=100, + 4, + population_size=10, + sequence_length=10, + recombination_rate=0.01, + random_seed=100, ) tables = ts.dump_tables() tables.nodes.clear() for n in ts.nodes(): - tables.nodes.append(n.replace(metadata=b'abc')) + tables.nodes.append(n.replace(metadata=b"abc")) ts = tables.tree_sequence() with pytest.warns(Warning, match="already has.*metadata"): - slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) + slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) for n in slim_ts.nodes(): assert n.is_sample() or n.metadata is None def test_warns_and_overwrites_individual_metadata(self, helper_functions): ts = msprime.sim_ancestry( - 4, - population_size=10, - sequence_length=10, - recombination_rate=0.01, - random_seed=100, + 4, + population_size=10, + sequence_length=10, + recombination_rate=0.01, + random_seed=100, ) tables = ts.dump_tables() tables.individuals.clear() for n in ts.individuals(): - tables.individuals.append(n.replace(metadata=b'abc')) + tables.individuals.append(n.replace(metadata=b"abc")) ts = tables.tree_sequence() with pytest.warns(Warning, match="already has.*metadata"): - slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) + slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) for ind in slim_ts.individuals(): assert slim_ts.node(ind.nodes[0]).is_sample() or ind.metadata is None def test_just_simulate(self, helper_functions, tmp_path): ts = msprime.sim_ancestry( - 4, - population_size=10, - sequence_length=10, - recombination_rate=0.01, - random_seed=100, + 4, + population_size=10, + sequence_length=10, + recombination_rate=0.01, + random_seed=100, ) ts = msprime.sim_mutations(ts, rate=0.1, random_seed=11) - slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) + slim_ts = pyslim.annotate(ts, model_type="WF", tick=1) loaded_ts = helper_functions.run_msprime_restart( - {"default": slim_ts}, tmp_path, multichrom=False, WF=True + {"default": slim_ts}, tmp_path, multichrom=False, WF=True )["default"] self.verify_annotated_trees(ts, loaded_ts) @@ -326,18 +338,23 @@ def test_basic_annotation(self, helper_functions, tmp_path): handler = contextlib.nullcontext() with handler: slim_ts = pyslim.annotate( - ts, model_type="WF", - tick=tick, - cycle=cycle, - stage=stage, - annotate_mutations=do_mutations, + ts, + model_type="WF", + tick=tick, + cycle=cycle, + stage=stage, + annotate_mutations=do_mutations, ) - assert slim_ts.metadata['SLiM']['model_type'] == 'WF' - assert slim_ts.metadata['SLiM']['tick'] == tick - assert slim_ts.metadata['SLiM']['cycle'] == cycle - assert slim_ts.metadata['SLiM']['stage'] == stage - assert slim_ts.metadata['SLiM']['file_version'] == pyslim.slim_file_version - self.verify_annotated_tables(ts, slim_ts, check_alleles=(not do_mutations)) + assert slim_ts.metadata["SLiM"]["model_type"] == "WF" + assert slim_ts.metadata["SLiM"]["tick"] == tick + assert slim_ts.metadata["SLiM"]["cycle"] == cycle + assert slim_ts.metadata["SLiM"]["stage"] == stage + assert ( + slim_ts.metadata["SLiM"]["file_version"] == pyslim.slim_file_version + ) + self.verify_annotated_tables( + ts, slim_ts, check_alleles=(not do_mutations) + ) self.verify_annotated_trees(ts, slim_ts) if not do_mutations: self.verify_haplotype_equality(ts, slim_ts) @@ -345,7 +362,7 @@ def test_basic_annotation(self, helper_functions, tmp_path): self.verify_provenance(slim_ts) # try loading this into SLiM loaded_ts = helper_functions.run_msprime_restart( - {"default": slim_ts}, tmp_path, multichrom=False, WF=True + {"default": slim_ts}, tmp_path, multichrom=False, WF=True )["default"] self.verify_annotated_tables(loaded_ts, slim_ts) self.verify_annotated_trees(loaded_ts, slim_ts) @@ -354,9 +371,7 @@ def test_basic_annotation(self, helper_functions, tmp_path): def test_annotate_refseq(self): ts = msprime.sim_ancestry(2, sequence_length=10, random_seed=77) refseq = "A" * int(ts.sequence_length) - ats = pyslim.annotate( - ts, model_type="nonWF", tick=5, reference_sequence=refseq - ) + ats = pyslim.annotate(ts, model_type="nonWF", tick=5, reference_sequence=refseq) assert ats.reference_sequence.data == refseq def test_annotate_individuals(self, helper_functions, tmp_path): @@ -366,24 +381,28 @@ def test_annotate_individuals(self, helper_functions, tmp_path): slim_ts = pyslim.annotate(ts, model_type="nonWF", tick=1, stage="early") tables = slim_ts.dump_tables() top_md = tables.metadata - top_md['SLiM']['separate_sexes'] = True + top_md["SLiM"]["separate_sexes"] = True tables.metadata = top_md metadata = [ind.metadata for ind in tables.individuals] - sexes = [random.choice([pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE]) - for _ in metadata] + sexes = [ + random.choice( + [pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE] + ) + for _ in metadata + ] for j in range(len(metadata)): metadata[j]["sex"] = sexes[j] ims = tables.individuals.metadata_schema tables.individuals.packset_metadata( - [ims.validate_and_encode_row(r) for r in metadata] + [ims.validate_and_encode_row(r) for r in metadata] ) pop_metadata = [p.metadata for p in tables.populations] for j, md in enumerate(pop_metadata): # nonWF models always have this - md['sex_ratio'] = 0.0 + md["sex_ratio"] = 0.0 pms = tables.populations.metadata_schema tables.populations.packset_metadata( - [pms.validate_and_encode_row(r) for r in pop_metadata] + [pms.validate_and_encode_row(r) for r in pop_metadata] ) new_ts = tables.tree_sequence() for j, ind in enumerate(new_ts.individuals()): @@ -394,7 +413,7 @@ def test_annotate_individuals(self, helper_functions, tmp_path): self.verify_haplotype_equality(new_ts, slim_ts) # try loading this into SLiM loaded_ts = helper_functions.run_msprime_restart( - {"default": new_ts}, tmp_path, multichrom=False, sex="A" + {"default": new_ts}, tmp_path, multichrom=False, sex="A" )["default"] self.verify_trees_equal(new_ts, loaded_ts) @@ -412,7 +431,7 @@ def test_annotate_nodes(self, helper_functions): md["slim_id"] = sid nms = tables.nodes.metadata_schema tables.nodes.packset_metadata( - [nms.validate_and_encode_row(r) for r in metadata] + [nms.validate_and_encode_row(r) for r in metadata] ) new_ts = tables.tree_sequence() for x, sid in zip(new_ts.nodes(), sids): @@ -428,15 +447,15 @@ def test_annotate_mutations(self, helper_functions): metadata = [m.metadata for m in tables.mutations] selcoefs = [random.uniform(0, 1) for _ in metadata] for j in range(len(metadata)): - metadata[j]['mutation_list'][0]["selection_coeff"] = selcoefs[j] + metadata[j]["mutation_list"][0]["selection_coeff"] = selcoefs[j] ms = tables.mutations.metadata_schema tables.mutations.packset_metadata( - [ms.validate_and_encode_row(r) for r in metadata] + [ms.validate_and_encode_row(r) for r in metadata] ) new_ts = tables.tree_sequence() for j, x in enumerate(new_ts.mutations()): md = x.metadata - assert np.isclose(md['mutation_list'][0]["selection_coeff"], selcoefs[j]) + assert np.isclose(md["mutation_list"][0]["selection_coeff"], selcoefs[j]) def test_dont_annotate_mutations(self): # Test the option to not overwrite mutation annotations @@ -445,12 +464,7 @@ def test_dont_annotate_mutations(self): assert ts.num_mutations > 0 tables = ts.dump_tables() pre_mutations = tables.mutations.copy() - pyslim.annotate_tables( - tables, - model_type="WF", - tick=1, - annotate_mutations=False - ) + pyslim.annotate_tables(tables, model_type="WF", tick=1, annotate_mutations=False) # this is necessary because b'' actually is decoded to # an empty mutation_list by the schema pre_mutations.metadata_schema = tables.mutations.metadata_schema @@ -458,203 +472,220 @@ def test_dont_annotate_mutations(self): def test_annotate_empty(self): t = tskit.TableCollection(sequence_length=10) - at = pyslim.annotate_tables(t, model_type='nonWF', tick=1) - assert t.metadata_schema == pyslim.slim_metadata_schemas['tree_sequence'] + at = pyslim.annotate_tables(t, model_type="nonWF", tick=1) + assert t.metadata_schema == pyslim.slim_metadata_schemas["tree_sequence"] for x in ("population", "individual", "node", "site", "mutation"): assert getattr(t, x + "s").metadata_schema == pyslim.slim_metadata_schemas[x] def test_no_populations_errors(self, helper_functions, tmp_path): # test SLiM errors when individuals are in non-SLiM populations - ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=456) + ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=456 + ) t = ts.dump_tables() - p = t.populations.add_row(metadata={'name': '', 'description': ''}) + p = t.populations.add_row(metadata={"name": "", "description": ""}) i = t.individuals.add_row() t.nodes.add_row(time=0.0, flags=tskit.NODE_IS_SAMPLE, individual=i) t.nodes.add_row(time=0.0, flags=tskit.NODE_IS_SAMPLE, individual=i) - pyslim.annotate_tables(t, model_type='nonWF', tick=1, stage="late") + pyslim.annotate_tables(t, model_type="nonWF", tick=1, stage="late") pop = t.populations[-1] - t.populations[-1] = pop.replace(metadata = {'name' : 'not_slim', 'description' : ''}) + t.populations[-1] = pop.replace(metadata={"name": "not_slim", "description": ""}) ind = t.individuals[-1] md = ind.metadata - md['subpopulation'] = (t.populations.num_rows - 1) + md["subpopulation"] = t.populations.num_rows - 1 t.individuals[-1] = ind.replace(metadata=md) ts = t.tree_sequence() - with pytest.raises(RuntimeError, match='individual has a subpopulation id .1.'): + with pytest.raises(RuntimeError, match="individual has a subpopulation id .1."): _ = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - WF=False, - multichrom=False, + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + WF=False, + multichrom=False, ) def test_empty_populations_errors(self, helper_functions, tmp_path): # test SLiM errors on having empty populations in a WF model - ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=455) - ts = pyslim.annotate(ts, model_type='WF', tick=1, stage="late") + ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=455 + ) + ts = pyslim.annotate(ts, model_type="WF", tick=1, stage="late") # first make sure does not error without the empty pops rts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - multichrom=False, - WF=True, + {"default": ts}, + "restart_WF.slim", + tmp_path, + multichrom=False, + WF=True, )["default"] assert rts.num_populations == 1 # now add empty subpops t = ts.dump_tables() for k in range(5): - md = pyslim.default_slim_metadata('population') - md['slim_id'] = k + 1 - md['name'] = f"new_pop_num_{k}" + md = pyslim.default_slim_metadata("population") + md["slim_id"] = k + 1 + md["name"] = f"new_pop_num_{k}" t.populations.add_row(metadata=md) ts = t.tree_sequence() for p in ts.populations(): assert "slim_id" in p.metadata - with pytest.raises(RuntimeError, match='subpopulation.*empty'): + with pytest.raises(RuntimeError, match="subpopulation.*empty"): _ = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - WF=True, - multichrom=False, + {"default": ts}, + "restart_WF.slim", + tmp_path, + WF=True, + multichrom=False, ) def test_empty_populations(self, helper_functions, tmp_path): # test SLiM doesn't error on having empty populations in a nonWF model # however, it may rewrite the metadata - ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=456) - ts = pyslim.annotate(ts, model_type='nonWF', tick=1) + ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=456 + ) + ts = pyslim.annotate(ts, model_type="nonWF", tick=1) t = ts.dump_tables() for k in range(5): - md = pyslim.default_slim_metadata('population') - md['slim_id'] = k + 1 - md['name'] = f"new_pop_num_{k}" - md['description'] = f"the {k}-th added pop" + md = pyslim.default_slim_metadata("population") + md["slim_id"] = k + 1 + md["name"] = f"new_pop_num_{k}" + md["description"] = f"the {k}-th added pop" t.populations.add_row(metadata=md) ts = t.tree_sequence() for subpop_map in ( - None, - {"p0": 0, "p1": 1, "p2": 2, "p3": 3, "p4": 4, "p5": 5}, - {"p0": 0, "p2": 1, "p1": 2, "p9": 3, "p4": 4, "p6": 5}, - {"p10": 0, "p2": 1, "p1": 2, "p9": 3, "p4": 4, "p6": 5}, - ): + None, + {"p0": 0, "p1": 1, "p2": 2, "p3": 3, "p4": 4, "p5": 5}, + {"p0": 0, "p2": 1, "p1": 2, "p9": 3, "p4": 4, "p6": 5}, + {"p10": 0, "p2": 1, "p1": 2, "p9": 3, "p4": 4, "p6": 5}, + ): sts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - WF=False, - subpop_map=subpop_map, - multichrom=False, + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + WF=False, + subpop_map=subpop_map, + multichrom=False, )["default"] self.verify_remapping(ts, sts, subpop_map) def test_many_populations(self, helper_functions, tmp_path): # test we can add more than one population and that names are preserved - ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=455) + ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=455 + ) t = ts.dump_tables() for k in range(1, 6): - md = pyslim.default_slim_metadata('population') - md['name'] = f"new_pop_num_{k}" - md['description'] = f"the {k}-th added pop" - md['slim_id'] = k + md = pyslim.default_slim_metadata("population") + md["name"] = f"new_pop_num_{k}" + md["description"] = f"the {k}-th added pop" + md["slim_id"] = k t.populations.add_row(metadata=md) i = t.individuals.add_row() for _ in range(2): t.nodes.add_row(flags=1, time=0.0, individual=i, population=k) ts = t.tree_sequence() - ts = pyslim.annotate(ts, model_type='WF', tick=1) + ts = pyslim.annotate(ts, model_type="WF", tick=1) for ind in ts.individuals(): assert ind.flags == pyslim.INDIVIDUAL_ALIVE sts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - WF=True, - multichrom=False, + {"default": ts}, + "restart_WF.slim", + tmp_path, + WF=True, + multichrom=False, )["default"] for k in range(1, 6): md = sts.population(k).metadata - assert md['name'] == f"new_pop_num_{k}" + assert md["name"] == f"new_pop_num_{k}" def test_many_species_errors(self, helper_functions, tmp_path): # should error when there are population conflicts between species - fox_ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=455) - fox_ts = pyslim.annotate(fox_ts, model_type='WF', tick=1) - mouse_ts = msprime.sim_ancestry(5, population_size=20, sequence_length=1000, random_seed=234) - mouse_ts = pyslim.annotate(mouse_ts, model_type='WF', tick=1) - with pytest.raises(RuntimeError, match='p0 has been used already'): + fox_ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=455 + ) + fox_ts = pyslim.annotate(fox_ts, model_type="WF", tick=1) + mouse_ts = msprime.sim_ancestry( + 5, population_size=20, sequence_length=1000, random_seed=234 + ) + mouse_ts = pyslim.annotate(mouse_ts, model_type="WF", tick=1) + with pytest.raises(RuntimeError, match="p0 has been used already"): _ = helper_functions.run_multispecies_slim_restart( - {'fox': fox_ts, 'mouse': mouse_ts}, - 'restart_multispecies_WF.slim', - tmp_path, - WF=True, + {"fox": fox_ts, "mouse": mouse_ts}, + "restart_multispecies_WF.slim", + tmp_path, + WF=True, ) - with pytest.raises(RuntimeError, match='p1 has been used already'): + with pytest.raises(RuntimeError, match="p1 has been used already"): _ = helper_functions.run_multispecies_slim_restart( - {'fox': fox_ts, 'mouse': mouse_ts}, - 'restart_multispecies_WF.slim', - tmp_path, - WF=True, - subpop_map={'fox': {'p1': 0}, 'mouse': {'p1': 0}}, + {"fox": fox_ts, "mouse": mouse_ts}, + "restart_multispecies_WF.slim", + tmp_path, + WF=True, + subpop_map={"fox": {"p1": 0}, "mouse": {"p1": 0}}, ) def test_many_species(self, helper_functions, tmp_path): # verify we can load more than one species for wf in (True, False): - fox_ts = msprime.sim_ancestry(5, population_size=10, sequence_length=100, random_seed=455) - mouse_ts = msprime.sim_ancestry(5, population_size=20, sequence_length=1000, random_seed=234) + fox_ts = msprime.sim_ancestry( + 5, population_size=10, sequence_length=100, random_seed=455 + ) + mouse_ts = msprime.sim_ancestry( + 5, population_size=20, sequence_length=1000, random_seed=234 + ) fox_ts = pyslim.annotate(fox_ts, model_type="WF" if wf else "nonWF", tick=1) - mouse_ts = pyslim.annotate(mouse_ts, model_type="WF" if wf else "nonWF", tick=1) + mouse_ts = pyslim.annotate( + mouse_ts, model_type="WF" if wf else "nonWF", tick=1 + ) for subpop_map in ( - {'fox' : None, 'mouse' : {'p1' : 0}}, - {'fox' : {'p1' : 0}, 'mouse' : None}, - {'fox' : {'p3' : 0}, 'mouse' : {'p0' : 0}}, - ): + {"fox": None, "mouse": {"p1": 0}}, + {"fox": {"p1": 0}, "mouse": None}, + {"fox": {"p3": 0}, "mouse": {"p0": 0}}, + ): tsd = helper_functions.run_multispecies_slim_restart( - {'fox': fox_ts, 'mouse': mouse_ts}, - 'restart_multispecies_WF.slim' if wf else 'restart_multispecies_nonWF.slim', - tmp_path, - WF=wf, - subpop_map = subpop_map, + {"fox": fox_ts, "mouse": mouse_ts}, + "restart_multispecies_WF.slim" + if wf + else "restart_multispecies_nonWF.slim", + tmp_path, + WF=wf, + subpop_map=subpop_map, ) - self.verify_remapping(fox_ts, tsd['fox'], subpop_map['fox']) - self.verify_remapping(mouse_ts, tsd['mouse'], subpop_map['mouse']) + self.verify_remapping(fox_ts, tsd["fox"], subpop_map["fox"]) + self.verify_remapping(mouse_ts, tsd["mouse"], subpop_map["mouse"]) def test_keeps_extra_populations(self, helper_functions, tmp_path): # test that non-SLiM metadata is not removed d = msprime.Demography() d.add_population(initial_size=10, name="A", extra_metadata={"pi": 3.1415}) - md = pyslim.default_slim_metadata('population') - del md['name'] - del md['description'] - md['slim_id'] = 1 + md = pyslim.default_slim_metadata("population") + del md["name"] + del md["description"] + md["slim_id"] = 1 d.add_population(initial_size=10, name="B", extra_metadata=md) d.add_population(initial_size=10, name="C", extra_metadata={"abc": 123}) ts = msprime.sim_ancestry( - samples={"B": 5}, - demography=d, - sequence_length=100, - random_seed=455 + samples={"B": 5}, demography=d, sequence_length=100, random_seed=455 ) - ts = pyslim.annotate(ts, model_type='WF', tick=1) + ts = pyslim.annotate(ts, model_type="WF", tick=1) sts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - multichrom=False, - WF=True, + {"default": ts}, + "restart_WF.slim", + tmp_path, + multichrom=False, + WF=True, )["default"] assert sts.num_populations == 3 assert np.all(ts.tables.nodes.population == 1) p = sts.population(0) - assert p.metadata['name'] == "A" - assert p.metadata['pi'] == 3.1415 + assert p.metadata["name"] == "A" + assert p.metadata["pi"] == 3.1415 p = sts.population(1) - assert p.metadata['name'] == "B" + assert p.metadata["name"] == "B" p = sts.population(2) - assert p.metadata['name'] == "C" - assert p.metadata['abc'] == 123 + assert p.metadata["name"] == "C" + assert p.metadata["abc"] == 123 def test_remapping_errors(self, helper_functions, tmp_path): d = msprime.Demography() @@ -663,54 +694,56 @@ def test_remapping_errors(self, helper_functions, tmp_path): d.add_population(initial_size=10, name="A") d.add_population_split(time=1.0, derived=["p0", "p1"], ancestral="A") ts = msprime.sim_ancestry( - {"p0": 5, "p1": 5}, - demography=d, - sequence_length=100, - random_seed=455, + {"p0": 5, "p1": 5}, + demography=d, + sequence_length=100, + random_seed=455, ) - ts = pyslim.annotate(ts, model_type='nonWF', tick=1, stage="late") + ts = pyslim.annotate(ts, model_type="nonWF", tick=1, stage="late") # test must refer to all subpopulations - with pytest.raises(RuntimeError, match='subpopulation id 2 is used.*but is not remapped'): + with pytest.raises( + RuntimeError, match="subpopulation id 2 is used.*but is not remapped" + ): _ = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - multichrom=False, - WF=False, - subpop_map = { - "p0" : 0, - "p1" : 1, - } + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + multichrom=False, + WF=False, + subpop_map={ + "p0": 0, + "p1": 1, + }, ) # test can't map the same subpop to two different pops - with pytest.raises(RuntimeError, match='subpopMap value .0. is not unique'): + with pytest.raises(RuntimeError, match="subpopMap value .0. is not unique"): _ = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - multichrom=False, - WF=False, - subpop_map = { - "p0" : 0, - "p1" : 0, - "p2" : 1, - "p3" : 2, - } + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + multichrom=False, + WF=False, + subpop_map={ + "p0": 0, + "p1": 0, + "p2": 1, + "p3": 2, + }, ) # test errors if it refers to non-existing subpop with pytest.raises(RuntimeError): _ = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - multichrom=False, - WF=False, - subpop_map = { - "p0" : 0, - "p1" : 1, - "p2" : 2, - "p3" : 3, - } + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + multichrom=False, + WF=False, + subpop_map={ + "p0": 0, + "p1": 1, + "p2": 2, + "p3": 3, + }, ) def test_remapping_empty_pops(self, helper_functions, tmp_path): @@ -718,16 +751,16 @@ def test_remapping_empty_pops(self, helper_functions, tmp_path): d = msprime.Demography() d.add_population(initial_size=10, name="p0") d.add_population(initial_size=10, name="p1") - d.add_population(initial_size=10, name="p2") # unused + d.add_population(initial_size=10, name="p2") # unused d.add_population(initial_size=10, name="A") d.add_population_split(time=1.0, derived=["p0", "p1"], ancestral="A") ts = msprime.sim_ancestry( - {"p0": 5, "p1": 5}, - demography=d, - sequence_length=100, - random_seed=456, + {"p0": 5, "p1": 5}, + demography=d, + sequence_length=100, + random_seed=456, ) - ts = pyslim.annotate(ts, model_type='nonWF', tick=1, stage="late") + ts = pyslim.annotate(ts, model_type="nonWF", tick=1, stage="late") t = ts.dump_tables() r = t.populations[2].replace(metadata=None) # make both pop 2 and 4 empty @@ -735,16 +768,16 @@ def test_remapping_empty_pops(self, helper_functions, tmp_path): t.populations.append(r) ts = t.tree_sequence() for subpop_map in ( - {"p0" : 0, "p1" : 1, "p2" : 2, "p3" : 3, "p4" : 4}, - {"p0" : 0, "p1" : 1, "p3": 3}, - ): + {"p0": 0, "p1": 1, "p2": 2, "p3": 3, "p4": 4}, + {"p0": 0, "p1": 1, "p3": 3}, + ): rts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_nonWF.slim", - tmp_path, - multichrom=False, - WF=False, - subpop_map = subpop_map + {"default": ts}, + "restart_nonWF.slim", + tmp_path, + multichrom=False, + WF=False, + subpop_map=subpop_map, )["default"] self.verify_remapping(ts, rts, subpop_map) @@ -753,28 +786,28 @@ def test_remapping(self, helper_functions, tmp_path): # pop 0 d.add_population(initial_size=10, name="A", extra_metadata={"pi": 3.1415}) # pop 1 - md = pyslim.default_slim_metadata('population') - del md['name'] - del md['description'] - md['slim_id'] = 1 - md['migration_records'] = [ + md = pyslim.default_slim_metadata("population") + del md["name"] + del md["description"] + md["slim_id"] = 1 + md["migration_records"] = [ { - "migration_rate" : 0.1, - "source_subpop" : 3, + "migration_rate": 0.1, + "source_subpop": 3, } ] d.add_population(initial_size=10, name="pop_1", extra_metadata=md) # pop 2 d.add_population(initial_size=10, name="pop_2", extra_metadata={"abc": 123}) # pop 3 - md = pyslim.default_slim_metadata('population') - del md['name'] - del md['description'] - md['slim_id'] = 3 - md['migration_records'] = [ + md = pyslim.default_slim_metadata("population") + del md["name"] + del md["description"] + md["slim_id"] = 3 + md["migration_records"] = [ { - "migration_rate" : 0.9, - "source_subpop" : 1, + "migration_rate": 0.9, + "source_subpop": 1, } ] d.add_population(initial_size=10, name="D", extra_metadata=md) @@ -782,32 +815,32 @@ def test_remapping(self, helper_functions, tmp_path): d.add_population(initial_size=10, name="XYZ", extra_metadata={"abc": 5123}) d.add_population_split(time=1.0, derived=["pop_1", "D"], ancestral="A") ts = msprime.sim_ancestry( - samples={"pop_1": 5, "D": 5}, - demography=d, - sequence_length=100, - random_seed=455 + samples={"pop_1": 5, "D": 5}, + demography=d, + sequence_length=100, + random_seed=455, ) - ts = pyslim.annotate(ts, model_type='WF', tick=1) + ts = pyslim.annotate(ts, model_type="WF", tick=1) ts = msprime.sim_mutations( - ts, - rate=1e-2, - random_seed=9, - model=msprime.SLiMMutationModel(type=1), + ts, + rate=1e-2, + random_seed=9, + model=msprime.SLiMMutationModel(type=1), ) assert ts.num_mutations > 0 for subpop_map in ( - None, - {"p0" : 0, "p1" : 1, "p2" : 2, "p3" : 3, "p4" : 4}, - {"p0" : 1, "p1" : 0, "p2" : 2, "p3" : 3, "p4" : 4}, - {"p5" : 0, "p0" : 1, "p7" : 2, "p2" : 3, "p9" : 4}, + None, + {"p0": 0, "p1": 1, "p2": 2, "p3": 3, "p4": 4}, + {"p0": 1, "p1": 0, "p2": 2, "p3": 3, "p4": 4}, + {"p5": 0, "p0": 1, "p7": 2, "p2": 3, "p9": 4}, ): rts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - multichrom=False, - WF=True, - subpop_map = subpop_map, + {"default": ts}, + "restart_WF.slim", + tmp_path, + multichrom=False, + WF=True, + subpop_map=subpop_map, )["default"] self.verify_remapping(ts, rts, subpop_map) @@ -821,33 +854,34 @@ def test_remaps_migration_table(self, helper_functions, tmp_path): d.set_migration_rate(0, 1, 0.1) d.set_migration_rate(1, 0, 0.1) ts = msprime.sim_ancestry( - {"p0": 5, "p1": 5}, - demography=d, - sequence_length=100, - random_seed=455, - record_migrations=True + {"p0": 5, "p1": 5}, + demography=d, + sequence_length=100, + random_seed=455, + record_migrations=True, ) - ts = pyslim.annotate(ts, model_type='WF', tick=1, stage="late") + ts = pyslim.annotate(ts, model_type="WF", tick=1, stage="late") assert ts.num_migrations > 0 rts = helper_functions.run_slim_restart( - {"default": ts}, - "restart_WF.slim", - tmp_path, - multichrom=False, - WF=True, - subpop_map = {"p5" : 0, "p2" : 1, "p0" : 2 }, + {"default": ts}, + "restart_WF.slim", + tmp_path, + multichrom=False, + WF=True, + subpop_map={"p5": 0, "p2": 1, "p0": 2}, )["default"] self.verify_remapping(ts, rts, subpop_map) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("remove_subpop"), indirect=["recipe"]) + "restart_name, recipe", restarted_recipe_eq("remove_subpop"), indirect=["recipe"] + ) def test_keep_slim_names(self, restart_name, recipe, helper_functions, tmp_path): # test that SLiM retains names of SLiM populations # even when those populations are removed in_ts = recipe["ts"] # this recipe moves everyone to subpop 0 out_ts = helper_functions.run_slim_restart( - in_ts, restart_name, tmp_path, "multichrom" in recipe + in_ts, restart_name, tmp_path, "multichrom" in recipe ) assert in_ts.keys() == out_ts.keys() for k in in_ts: @@ -858,43 +892,39 @@ def test_keep_slim_names(self, restart_name, recipe, helper_functions, tmp_path) for j in range(1, it.num_populations): in_md = it.population(j).metadata out_md = ot.population(j).metadata - assert in_md['name'] == out_md['name'] + assert in_md["name"] == out_md["name"] @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op"), indirect=["recipe"]) - def test_reload_recapitate( - self, restart_name, recipe, helper_functions, tmp_path - ): + "restart_name, recipe", restarted_recipe_eq("no_op"), indirect=["recipe"] + ) + def test_reload_recapitate(self, restart_name, recipe, helper_functions, tmp_path): # Test the ability of SLiM to load our files after recapitation. in_ts = {} for chrom, ts in recipe["ts"].items(): # recapitate, reload in_ts[chrom] = self.do_recapitate( - ts, recombination_rate=1e-2, ancestral_Ne=10, random_seed=25 + ts, recombination_rate=1e-2, ancestral_Ne=10, random_seed=25 ) # put it through SLiM (which just reads in and writes out) out_ts = helper_functions.run_slim_restart( - in_ts, - restart_name, - tmp_path, - "multichrom" in recipe, - WF=False, + in_ts, + restart_name, + tmp_path, + "multichrom" in recipe, + WF=False, ) # check for equality, in everything but the last provenance verify_slim_restart_equality(in_ts, out_ts) # test for restarting with a subpop map ex_in_ts = list(in_ts.values())[0] for j, k in [(1, 7), (5, 7)]: - subpop_map = { - f"p{i * j % k}" : i - for i in range(ex_in_ts.num_populations) - } + subpop_map = {f"p{i * j % k}": i for i in range(ex_in_ts.num_populations)} out_ts = helper_functions.run_slim_restart( - in_ts, - restart_name, - tmp_path, - "multichrom" in recipe, - subpop_map=subpop_map + in_ts, + restart_name, + tmp_path, + "multichrom" in recipe, + subpop_map=subpop_map, ) assert in_ts.keys() == out_ts.keys() for k in in_ts: @@ -903,51 +933,51 @@ def test_reload_recapitate( self.verify_remapping(it, ot, subpop_map) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op"), indirect=["recipe"]) - def test_reload_annotate( - self, restart_name, recipe, helper_functions, tmp_path - ): + "restart_name, recipe", restarted_recipe_eq("no_op"), indirect=["recipe"] + ) + def test_reload_annotate(self, restart_name, recipe, helper_functions, tmp_path): # Test the ability of SLiM to load our files after annotation. in_ts = {} for chrom, ts in recipe["ts"].items(): tables = ts.dump_tables() metadata = [m.metadata for m in tables.mutations] - has_nucleotides = tables.metadata['SLiM']['nucleotide_based'] + has_nucleotides = tables.metadata["SLiM"]["nucleotide_based"] if has_nucleotides: nucs = [random.choice([0, 1, 2, 3]) for _ in metadata] refseq = "".join( - random.choices( - pyslim.NUCLEOTIDES, - k = int(ts.sequence_length), - ), + random.choices( + pyslim.NUCLEOTIDES, + k=int(ts.sequence_length), + ), ) for n, md in zip(nucs, metadata): - for m in md['mutation_list']: + for m in md["mutation_list"]: m["nucleotide"] = n tables.reference_sequence.data = refseq for md in metadata: - for m in md['mutation_list']: + for m in md["mutation_list"]: m["selection_coeff"] = random.random() ms = tables.mutations.metadata_schema tables.mutations.packset_metadata( - [ms.validate_and_encode_row(r) for r in metadata] + [ms.validate_and_encode_row(r) for r in metadata] ) in_ts[chrom] = tables.tree_sequence() # put it through SLiM (which just reads in and writes out) out_ts = helper_functions.run_slim_restart( - in_ts, restart_name, tmp_path, "multichrom" in recipe + in_ts, restart_name, tmp_path, "multichrom" in recipe ) # check for equality, in everything but the last provenance verify_slim_restart_equality(in_ts, out_ts) class TestReload(tests.PyslimTestCase): - ''' + """ Tests for basic things related to reloading with SLiM - ''' + """ @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op"), indirect=["recipe"]) + "restart_name, recipe", restarted_recipe_eq("no_op"), indirect=["recipe"] + ) def test_load_without_provenance( self, restart_name, recipe, helper_functions, tmp_path ): @@ -958,31 +988,35 @@ def test_load_without_provenance( in_tables.sort() cleared_ts[chrom] = in_tables.tree_sequence() out_ts = helper_functions.run_slim_restart( - cleared_ts, restart_name, tmp_path, "multichrom" in recipe + cleared_ts, restart_name, tmp_path, "multichrom" in recipe ) verify_slim_restart_equality(recipe["ts"], cleared_ts, check_prov=False) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op", "nucleotides"), indirect=["recipe"]) + "restart_name, recipe", + restarted_recipe_eq("no_op", "nucleotides"), + indirect=["recipe"], + ) def test_reload_reference_sequence( self, restart_name, recipe, helper_functions, tmp_path ): in_ts = recipe["ts"] out_ts = helper_functions.run_slim_restart( - in_ts, restart_name, tmp_path, "multichrom" in recipe + in_ts, restart_name, tmp_path, "multichrom" in recipe ) assert in_ts.keys() == out_ts.keys() for k in in_ts: it = in_ts[k] ot = out_ts[k] - assert it.metadata['SLiM']['nucleotide_based'] is True - assert ot.metadata['SLiM']['nucleotide_based'] is True + assert it.metadata["SLiM"]["nucleotide_based"] is True + assert ot.metadata["SLiM"]["nucleotide_based"] is True assert it.has_reference_sequence() == ot.has_reference_sequence() if it.has_reference_sequence(): it.reference_sequence.assert_equals(ot.reference_sequence) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq(), indirect=["recipe"]) + "restart_name, recipe", restarted_recipe_eq(), indirect=["recipe"] + ) def test_restarts_and_runs_simplified( self, restart_name, recipe, helper_functions, tmp_path ): @@ -991,15 +1025,14 @@ def test_restarts_and_runs_simplified( n = None for chrom, ts in in_ts.items(): if n is None: - inds = np.where(ts.individuals_flags & pyslim.INDIVIDUAL_ALIVE > 0)[0][:2] + inds = np.where(ts.individuals_flags & pyslim.INDIVIDUAL_ALIVE > 0)[0][ + :2 + ] n = [u for i in inds for u in ts.individual(i).nodes] n.sort() py_ts[chrom] = ts.simplify(n, filter_populations=False) out_ts = helper_functions.run_slim_restart( - py_ts, - restart_name, - tmp_path, - "multichrom" in recipe + py_ts, restart_name, tmp_path, "multichrom" in recipe ) assert in_ts.keys() == out_ts.keys() for k in in_ts: diff --git a/tests/test_metadata.py b/tests/test_metadata.py index 688d91b5..b0a44336 100644 --- a/tests/test_metadata.py +++ b/tests/test_metadata.py @@ -1,25 +1,23 @@ """ Test cases for the metadata reading/writing of pyslim. """ -import os import numpy as np import pytest -import msprime import tskit -import pyslim +import pyslim import tests + from .recipe_specs import recipe_eq class TestMetadataSchemas(tests.PyslimTestCase): - def validate_table_metadata(self, table): ms = table.metadata_schema for j, row in enumerate(table): a = table.metadata_offset[j] - b = table.metadata_offset[j+1] + b = table.metadata_offset[j + 1] raw_md = table.metadata[a:b] # this checks to make sure metadata follows the schema enc_md = ms.validate_and_encode_row(row.metadata) @@ -28,8 +26,15 @@ def validate_table_metadata(self, table): def test_slim_metadata(self, recipe): for ts in recipe["ts"].values(): tables = ts.dump_tables() - for t in (tables.populations, tables.individuals, tables.nodes, tables.edges, - tables.sites, tables.mutations, tables.migrations): + for t in ( + tables.populations, + tables.individuals, + tables.nodes, + tables.edges, + tables.sites, + tables.mutations, + tables.migrations, + ): self.validate_table_metadata(t) def test_default_metadata_errors(self): @@ -42,7 +47,7 @@ def test_default_metadata(self): entry = pyslim.default_slim_metadata(k) sd = schema.asdict() if sd is not None: - for p in sd['properties']: + for p in sd["properties"]: assert p in entry encoded = schema.validate_and_encode_row(entry) decoded = schema.decode_row(encoded) @@ -52,13 +57,13 @@ def test_default_metadata(self): assert entry == decoded schema = pyslim.slim_metadata_schemas["mutation"] entry = pyslim.default_slim_metadata("mutation") - entry['mutation_list'].append( + entry["mutation_list"].append( pyslim.default_slim_metadata("mutation_list_entry") ) encoded = schema.validate_and_encode_row(entry) decoded = schema.decode_row(encoded) assert entry == decoded - entry['mutation_list'].append( + entry["mutation_list"].append( pyslim.default_slim_metadata("mutation_list_entry") ) encoded = schema.validate_and_encode_row(entry) @@ -69,20 +74,30 @@ def test_slim_metadata_schema_equality(self, recipe): num_chromosomes = len(recipe["ts"]) for ts in recipe["ts"].values(): t = ts.dump_tables() - assert t.metadata_schema == pyslim.slim_metadata_schemas['tree_sequence'] - assert t.edges.metadata_schema == pyslim.slim_metadata_schemas['edge'] - assert t.sites.metadata_schema == pyslim.slim_metadata_schemas['site'] - assert t.mutations.metadata_schema == pyslim.slim_metadata_schemas['mutation'] - node_schema = pyslim.slim_metadata_schemas['node'].asdict() - node_schema['properties']['is_vacant']['length'] = int((num_chromosomes + 7)/8) + assert t.metadata_schema == pyslim.slim_metadata_schemas["tree_sequence"] + assert t.edges.metadata_schema == pyslim.slim_metadata_schemas["edge"] + assert t.sites.metadata_schema == pyslim.slim_metadata_schemas["site"] + assert ( + t.mutations.metadata_schema == pyslim.slim_metadata_schemas["mutation"] + ) + node_schema = pyslim.slim_metadata_schemas["node"].asdict() + node_schema["properties"]["is_vacant"]["length"] = int( + (num_chromosomes + 7) / 8 + ) assert t.nodes.metadata_schema.asdict() == node_schema - assert t.individuals.metadata_schema == pyslim.slim_metadata_schemas['individual'] - assert t.populations.metadata_schema == pyslim.slim_metadata_schemas['population'] + assert ( + t.individuals.metadata_schema + == pyslim.slim_metadata_schemas["individual"] + ) + assert ( + t.populations.metadata_schema + == pyslim.slim_metadata_schemas["population"] + ) def test_node_schema(self): s = pyslim.slim_node_metadata_schema() sd = s.asdict() - assert sd['properties']['is_vacant']['length'] == 1 + assert sd["properties"]["is_vacant"]["length"] == 1 s1 = pyslim.slim_node_metadata_schema(num_chromosomes=1) assert s == s1 s8 = pyslim.slim_node_metadata_schema(num_chromosomes=8) @@ -90,9 +105,9 @@ def test_node_schema(self): for nc in [7, 12, 25, 32]: sx = pyslim.slim_node_metadata_schema(num_chromosomes=nc) sxd = sx.asdict() - n = sxd['properties']['is_vacant']['length'] + n = sxd["properties"]["is_vacant"]["length"] assert n - 1 < nc / 8 and nc / 8 <= n - sxd['properties']['is_vacant']['length'] = 1 + sxd["properties"]["is_vacant"]["length"] = 1 assert sxd == sd @@ -102,20 +117,20 @@ class TestTreeSequenceMetadata(tests.PyslimTestCase): def validate_slim_metadata(self, t): # t could be tables or a tree sequence schema = t.metadata_schema.schema - assert 'SLiM' in schema['properties'] - assert 'SLiM' in t.metadata - for k in pyslim.default_slim_metadata('tree_sequence')['SLiM']: - assert k in schema['properties']['SLiM']['properties'] - assert k in t.metadata['SLiM'] + assert "SLiM" in schema["properties"] + assert "SLiM" in t.metadata + for k in pyslim.default_slim_metadata("tree_sequence")["SLiM"]: + assert k in schema["properties"]["SLiM"]["properties"] + assert k in t.metadata["SLiM"] def validate_model_type(self, tsdict, model_type): for _, ts in tsdict.items(): - assert ts.metadata['SLiM']['file_version'] == pyslim.slim_file_version - assert ts.metadata['SLiM']['model_type'] == model_type - assert ts.metadata['SLiM']['tick'] > 0 - assert ts.metadata['SLiM']['tick'] >= np.max(ts.tables.nodes.time) + assert ts.metadata["SLiM"]["file_version"] == pyslim.slim_file_version + assert ts.metadata["SLiM"]["model_type"] == model_type + assert ts.metadata["SLiM"]["tick"] > 0 + assert ts.metadata["SLiM"]["tick"] >= np.max(ts.tables.nodes.time) - @pytest.mark.parametrize('recipe', arbitrary_recipe, indirect=True) + @pytest.mark.parametrize("recipe", arbitrary_recipe, indirect=True) def test_set_tree_sequence_metadata_errors(self, recipe): for _, ts in recipe["ts"].items(): tables = ts.dump_tables() @@ -124,18 +139,18 @@ def test_set_tree_sequence_metadata_errors(self, recipe): with pytest.raises(ValueError): pyslim.set_tree_sequence_metadata(tables, "nonWF", 0) - @pytest.mark.parametrize('recipe', arbitrary_recipe, indirect=True) + @pytest.mark.parametrize("recipe", arbitrary_recipe, indirect=True) def test_set_tree_sequence_metadata_keeps(self, recipe): # make sure doesn't overwrite other stuff ts = list(recipe["ts"].values())[0] - for x in [{}, { 'properties': { 'abc': { 'type': 'string' } } }]: + for x in [{}, {"properties": {"abc": {"type": "string"}}}]: schema_dict = { - 'codec': 'json', - 'type': 'object', + "codec": "json", + "type": "object", } schema_dict.update(x) dummy_schema = tskit.MetadataSchema(schema_dict) - dummy_metadata = { 'abc': 'foo' } + dummy_metadata = {"abc": "foo"} tables = ts.dump_tables() tables.metadata_schema = dummy_schema tables.metadata = dummy_metadata @@ -143,48 +158,49 @@ def test_set_tree_sequence_metadata_keeps(self, recipe): schema = tables.metadata_schema.schema for k in dummy_metadata: if len(x) > 0: - assert k in schema['properties'] + assert k in schema["properties"] assert k in tables.metadata assert tables.metadata[k] == dummy_metadata[k] self.validate_slim_metadata(tables) - assert tables.metadata['SLiM']['model_type'] == "nonWF" - assert tables.metadata['SLiM']['tick'] == 0 + assert tables.metadata["SLiM"]["model_type"] == "nonWF" + assert tables.metadata["SLiM"]["tick"] == 0 - @pytest.mark.parametrize('recipe', arbitrary_recipe, indirect=True) + @pytest.mark.parametrize("recipe", arbitrary_recipe, indirect=True) def test_set_tree_sequence_metadata(self, recipe): ts = list(recipe["ts"].values())[0] tables = ts.dump_tables() pyslim.set_tree_sequence_metadata( - tables, - "WF", - tick=99, - cycle=40, - stage="early", - spatial_dimensionality='xy', - spatial_periodicity='y', - separate_sexes=False, - nucleotide_based=True + tables, + "WF", + tick=99, + cycle=40, + stage="early", + spatial_dimensionality="xy", + spatial_periodicity="y", + separate_sexes=False, + nucleotide_based=True, ) self.validate_slim_metadata(tables) - assert tables.metadata['SLiM']['model_type'] == "WF" - assert tables.metadata['SLiM']['tick'] == 99 - assert tables.metadata['SLiM']['cycle'] == 40 - assert tables.metadata['SLiM']['stage'] == 'early' - assert tables.metadata['SLiM']['spatial_dimensionality'] == 'xy' - assert tables.metadata['SLiM']['spatial_periodicity'] == 'y' - assert tables.metadata['SLiM']['separate_sexes'] == False - assert tables.metadata['SLiM']['nucleotide_based'] == True - - @pytest.mark.parametrize('recipe', recipe_eq("WF"), indirect=True) + assert tables.metadata["SLiM"]["model_type"] == "WF" + assert tables.metadata["SLiM"]["tick"] == 99 + assert tables.metadata["SLiM"]["cycle"] == 40 + assert tables.metadata["SLiM"]["stage"] == "early" + assert tables.metadata["SLiM"]["spatial_dimensionality"] == "xy" + assert tables.metadata["SLiM"]["spatial_periodicity"] == "y" + assert tables.metadata["SLiM"]["separate_sexes"] == False + assert tables.metadata["SLiM"]["nucleotide_based"] == True + + @pytest.mark.parametrize("recipe", recipe_eq("WF"), indirect=True) def test_WF_model_type(self, recipe): self.validate_model_type(recipe["ts"], "WF") - @pytest.mark.parametrize('recipe', recipe_eq("nonWF"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("nonWF"), indirect=True) def test_nonWF_model_type(self, recipe): self.validate_model_type(recipe["ts"], "nonWF") @pytest.mark.parametrize( - 'recipe', recipe_eq(exclude=["user_metadata", "multichrom"]), indirect=True) + "recipe", recipe_eq(exclude=["user_metadata", "multichrom"]), indirect=True + ) def test_recover_metadata(self, recipe): # msprime <=0.7.5 discards metadata, but we can recover it from provenance # HOWEVER: multichromosome information is not saved @@ -192,45 +208,46 @@ def test_recover_metadata(self, recipe): for _, ts in recipe["ts"].items(): tables = ts.dump_tables() tables.metadata_schema = tskit.MetadataSchema(None) - tables.metadata = b'' + tables.metadata = b"" pyslim.update_tables(tables) md = tables.metadata - assert 'SLiM' in md - for k in ts.metadata['SLiM']: + assert "SLiM" in md + for k in ts.metadata["SLiM"]: if k in ("chromosomes", "this_chromosome"): continue # TODO: see https://github.com/MesserLab/SLiM/issues/520 - assert k in md['SLiM'] + assert k in md["SLiM"] # slim does not write out empty descriptions - if k != 'description' or ts.metadata['SLiM'][k] != "": - assert ts.metadata['SLiM'][k] == md['SLiM'][k] + if k != "description" or ts.metadata["SLiM"][k] != "": + assert ts.metadata["SLiM"][k] == md["SLiM"][k] - @pytest.mark.parametrize('recipe', recipe_eq("recipe_with_metadata.slim"), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq("recipe_with_metadata.slim"), indirect=True + ) def test_user_metadata(self, recipe): for _, ts in recipe["ts"].items(): md = ts.metadata["SLiM"] assert "user_metadata" in md - assert md['user_metadata'] == { - "hello" : ["world"], - "pi" : [3, 1, 4, 1, 5, 9] - } + assert md["user_metadata"] == {"hello": ["world"], "pi": [3, 1, 4, 1, 5, 9]} - @pytest.mark.parametrize('recipe', recipe_eq("recipe_with_metadata.slim"), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq("recipe_with_metadata.slim"), indirect=True + ) def test_population_names(self, recipe): for _, ts in recipe["ts"].items(): md = ts.metadata["SLiM"] assert ts.num_populations == 4 p = ts.population(1) - assert p.metadata['name'] == "first_population" - assert p.metadata['description'] == "i'm the first population" + assert p.metadata["name"] == "first_population" + assert p.metadata["description"] == "i'm the first population" p = ts.population(3) - assert p.metadata['name'] == "other_population" - assert p.metadata['description'] == "i'm the other population" + assert p.metadata["name"] == "other_population" + assert p.metadata["description"] == "i'm the other population" class TestAlleles(tests.PyslimTestCase): - ''' + """ Test nothing got messed up with haplotypes. - ''' + """ def test_haplotypes(self, recipe): for _, slim_ts in recipe["ts"].items(): @@ -240,45 +257,44 @@ def test_haplotypes(self, recipe): class TestNucleotides(tests.PyslimTestCase): - ''' + """ Test nucleotide support - ''' + """ def test_nucleotides(self, recipe): - ''' + """ Check that nucleotides are all valid, i.e., -1, 0, 1, 2, or 3. - ''' + """ for _, ts in recipe["ts"].items(): for mut in ts.mutations(): - for u in mut.metadata['mutation_list']: + for u in mut.metadata["mutation_list"]: assert u["nucleotide"] >= -1 assert u["nucleotide"] <= 3 class TestMultichrom(tests.PyslimTestCase): - ''' + """ Test multichromosome metadata - ''' + """ - @pytest.mark.parametrize('recipe', recipe_eq("multichrom"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("multichrom"), indirect=True) def test_chromosome_types(self, recipe): chroms = recipe["ts"] chrom_info = {} chrom_list = None # check 'chromosomes' identical for all for chrom, ts in chroms.items(): - md = ts.metadata['SLiM'] - chrom_info[chrom] = md['this_chromosome'] + md = ts.metadata["SLiM"] + chrom_info[chrom] = md["this_chromosome"] # optional but should be there for all these examples - assert 'chromosomes' in md + assert "chromosomes" in md if chrom_list is None: - chrom_list = md['chromosomes'] + chrom_list = md["chromosomes"] else: - assert chrom_list == md['chromosomes'] + assert chrom_list == md["chromosomes"] # check 'this_chromosome' matches entry in 'chromosomes' - chrom_list_d = { f"chromosome_{x['symbol']}" : x for x in chrom_list } + chrom_list_d = {f"chromosome_{x['symbol']}": x for x in chrom_list} for chrom in chroms.keys(): assert chrom in chrom_list_d assert chrom_list_d[chrom] == chrom_info[chrom] - diff --git a/tests/test_provenance.py b/tests/test_provenance.py index 997900fc..d95b275d 100644 --- a/tests/test_provenance.py +++ b/tests/test_provenance.py @@ -1,23 +1,24 @@ """ Test cases for provenance handling. """ + import json import os import random -import tskit import numpy as np import pytest -import msprime -import pyslim +import tskit +import pyslim import tests -from .recipe_specs import recipe_specs, recipe_eq + +from .recipe_specs import recipe_eq # *Note:* it is now deprecated to extract information from provenance, # but we still need to do it, to be able to load old file versions. -_slim_v3_3_1_example = r''' +_slim_v3_3_1_example = r""" { "environment": { "os": { @@ -64,10 +65,10 @@ "name": "SLiM", "version": "3.3.1" } -} -''' +} +""" -_slim_v3_1_example = r''' +_slim_v3_1_example = r""" { "environment": { "os": { @@ -112,79 +113,81 @@ "version": "3.1" } } -''' +""" -_slim_v3_0_example = ''' +_slim_v3_0_example = """ {"program": "SLiM", "version": "3.0", "file_version": "0.1", "model_type": "WF", "generation": 10, "remembered_node_count": 0} -''' +""" old_provenance_examples = [_slim_v3_0_example, _slim_v3_1_example, _slim_v3_3_1_example] class TestProvenance(tests.PyslimTestCase): script_dir = os.path.dirname(os.path.realpath(__file__)) - + def get_0_1_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.0.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.0.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.0.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.0.trees"), ]: yield tskit.load(filename) def get_0_2_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.2.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.2.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.2.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.2.trees"), ]: yield tskit.load(filename) def get_0_3_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.3.1.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.3.1.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.3.1.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.3.1.trees"), ]: yield tskit.load(filename) def get_0_4_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.4.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.4.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.4.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.4.trees"), ]: yield tskit.load(filename) def get_0_5_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.5.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.5.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.5.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.5.trees"), ]: yield tskit.load(filename) def get_0_6_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.6.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.6.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.6.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.6.trees"), ]: yield tskit.load(filename) def get_0_7_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.7.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v3.7.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v3.7.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v3.7.trees"), ]: yield tskit.load(filename) def get_0_8_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v4.2.2.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF_X.v4.2.2.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF_Y.v4.2.2.trees'), - os.path.join(self.script_dir, 'test_recipes', 'recipe_nonWF.v4.2.2.trees'), + os.path.join(self.script_dir, "test_recipes", "recipe_WF.v4.2.2.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_WF_X.v4.2.2.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_WF_Y.v4.2.2.trees"), + os.path.join(self.script_dir, "test_recipes", "recipe_nonWF.v4.2.2.trees"), ]: yield tskit.load(filename) def get_mixed_slim_examples(self): for filename in [ - os.path.join(self.script_dir, 'test_recipes', 'recipe_WF.v3.5_and_v3.6.trees'), + os.path.join( + self.script_dir, "test_recipes", "recipe_WF.v3.5_and_v3.6.trees" + ), ]: yield tskit.load(filename) @@ -197,11 +200,11 @@ def verify_upgrade(self, ts): # (since this isn't tested on load) tables = ts.tables for t in [ - tables.populations, - tables.individuals, - tables.nodes, - tables.mutations - ]: + tables.populations, + tables.individuals, + tables.nodes, + tables.mutations, + ]: ms = t.metadata_schema for x in t: _ = ms.validate_and_encode_row(x.metadata) @@ -218,9 +221,9 @@ def test_convert_0_1_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['generation'] == pts.metadata['SLiM']["tick"] + assert "SLiM" in pts.metadata + assert record["model_type"] == pts.metadata["SLiM"]["model_type"] + assert record["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -244,9 +247,11 @@ def test_convert_0_2_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']["tick"] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -270,9 +275,11 @@ def test_convert_0_3_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']["tick"] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -298,9 +305,11 @@ def test_convert_0_4_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -324,9 +333,11 @@ def test_convert_0_5_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -350,9 +361,11 @@ def test_convert_0_6_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -376,9 +389,11 @@ def test_convert_0_7_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -402,20 +417,22 @@ def test_convert_0_8_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['tick'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["tick"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) genome_type = None for n in samples: md = ts.node(n).metadata - if not md['is_null']: - genome_type = md['genome_type'] + if not md["is_null"]: + genome_type = md["genome_type"] break assert genome_type is not None - chromosome_type = pts.metadata['SLiM']['this_chromosome']['type'] + chromosome_type = pts.metadata["SLiM"]["this_chromosome"]["type"] GENOME_TYPE_AUTOSOME = 0 GENOME_TYPE_X = 1 GENOME_TYPE_Y = 2 @@ -445,9 +462,11 @@ def test_convert_mixed_files(self): assert ts.provenance(0).record == pts.provenance(0).record record = json.loads(ts.provenance(0).record) assert isinstance(pts.metadata, dict) - assert 'SLiM' in pts.metadata - assert record['parameters']['model_type'] == pts.metadata['SLiM']['model_type'] - assert record['slim']['generation'] == pts.metadata['SLiM']['tick'] + assert "SLiM" in pts.metadata + assert ( + record["parameters"]["model_type"] == pts.metadata["SLiM"]["model_type"] + ) + assert record["slim"]["generation"] == pts.metadata["SLiM"]["tick"] assert list(ts.samples()) == list(pts.samples()) assert np.array_equal(ts.tables.nodes.flags, pts.tables.nodes.flags) samples = list(ts.samples()) @@ -459,10 +478,10 @@ def test_convert_mixed_files(self): if t.parent(u) != tskit.NULL: assert t.branch_length(u) == pt.branch_length(u) - @pytest.mark.parametrize('recipe', [next(recipe_eq())], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq())], indirect=True) def test_current_format(self, recipe): for _, ts in recipe["ts"].items(): - uts = pyslim.update(ts) + uts = pyslim.update(ts) ts.tables.assert_equals(uts.tables) def test_file_warnings(self): diff --git a/tests/test_recipes/make_v3_test_additions.py b/tests/test_recipes/make_v3_test_additions.py index 39363949..6ec164c7 100644 --- a/tests/test_recipes/make_v3_test_additions.py +++ b/tests/test_recipes/make_v3_test_additions.py @@ -1,4 +1,6 @@ -import tskit, pyslim +import tskit + +import pyslim """ Takes an old tree sequence and update the metadata *without* properly updating @@ -9,12 +11,12 @@ tables = ts.dump_tables() tables.populations.clear() -tables.populations.metadata_schema = pyslim.slim_metadata_schemas['population'] +tables.populations.metadata_schema = pyslim.slim_metadata_schemas["population"] for p in ts.populations(): tables.populations.append(p) tables.individuals.clear() -tables.individuals.metadata_schema = pyslim.slim_metadata_schemas['individual'] +tables.individuals.metadata_schema = pyslim.slim_metadata_schemas["individual"] d = pyslim.default_slim_metadata("individual") for i in ts.individuals(): d.update(i.metadata) @@ -22,7 +24,7 @@ tables.individuals.append(ii) tables.mutations.clear() -tables.mutations.metadata_schema = pyslim.slim_metadata_schemas['mutation'] +tables.mutations.metadata_schema = pyslim.slim_metadata_schemas["mutation"] d = pyslim.default_slim_metadata("mutation") for m in ts.mutations(): tables.mutations.append(m) diff --git a/tests/test_spatial.py b/tests/test_spatial.py index 829a8e9b..ddd0b564 100644 --- a/tests/test_spatial.py +++ b/tests/test_spatial.py @@ -1,26 +1,23 @@ """ Test cases for tree sequences. """ -import random -import os import numpy as np import pytest import tskit -import msprime -import pyslim +import pyslim import tests from .recipe_specs import recipe_eq -class TestPopulationSize(tests.PyslimTestCase): +class TestPopulationSize(tests.PyslimTestCase): def population_size_simple(self, ts, x_bins, y_bins, time_bins, **kwargs): - ''' - Calculates population size in each location bin averaged over each time_bin. - ''' - + """ + Calculates population size in each location bin averaged over each time_bin. + """ + # Want to return # [[[px0y0t0, px0y0t1, ...], [px0y1t0, px0y1t1, ...], ...], # [[px1y0t0, px0y0t1, ...], [px1y1t0, px1y1t1, ...], ...], @@ -28,7 +25,7 @@ def population_size_simple(self, ts, x_bins, y_bins, time_bins, **kwargs): # where pxiyjtk is the population size in [x_breaks[i], x_breaks[i + 1]) and [y_breaks[j], x_breaks[j + 1]), # averaged over each time point in [t[k], t[k + 1]) # different offsets for different stages, from pyslim.individuals_alive_at code - + time_breaks = time_bins x_breaks = x_bins y_breaks = y_bins @@ -56,10 +53,15 @@ def population_size_simple(self, ts, x_bins, y_bins, time_bins, **kwargs): for t in np.arange(np.ceil(t0), t1): for ind_id in pyslim.individuals_alive_at(ts, t, **kwargs): ind = ts.individual(ind_id) - if (ind.location[0] < x1 and ind.location[0] >= x0 and ind.location[1] < y1 and ind.location[1] >= y0): - alive += 1/(t1-t0) - popsize[i, j, k] = alive - return(popsize) + if ( + ind.location[0] < x1 + and ind.location[0] >= x0 + and ind.location[1] < y1 + and ind.location[1] >= y0 + ): + alive += 1 / (t1 - t0) + popsize[i, j, k] = alive + return popsize def make_bins(self, ts): locs = ts.individuals_location @@ -67,33 +69,53 @@ def make_bins(self, ts): for nx in np.arange(1, 20, 10): for ny in np.arange(1, 20, 10): for nt in np.arange(1, 60, 30): - yield [np.linspace(0, round(max(locs[:,0])), nx + 1), - np.linspace(0, round(max(locs[:,1])), ny + 1), - np.round(np.linspace(0, max(nt, max_time), nt + 1))] + yield [ + np.linspace(0, round(max(locs[:, 0])), nx + 1), + np.linspace(0, round(max(locs[:, 1])), ny + 1), + np.round(np.linspace(0, max(nt, max_time), nt + 1)), + ] def verify(self, ts, remembered_stage): for bins in self.make_bins(ts): - for stage in ('early', 'late'): + for stage in ("early", "late"): x_bins, y_bins, time_bins = bins # as computed by pyslim - popsize0 = pyslim.population_size(ts, x_bins, y_bins, time_bins, stage=stage, remembered_stage=remembered_stage) + popsize0 = pyslim.population_size( + ts, + x_bins, + y_bins, + time_bins, + stage=stage, + remembered_stage=remembered_stage, + ) # as computed in a simple way - popsize1 = self.population_size_simple(ts, x_bins, y_bins, time_bins, stage=stage, remembered_stage=remembered_stage) - assert(np.allclose(popsize1, popsize0)) - - @pytest.mark.parametrize('recipe', [next(recipe_eq("everyone"))], indirect=True) + popsize1 = self.population_size_simple( + ts, + x_bins, + y_bins, + time_bins, + stage=stage, + remembered_stage=remembered_stage, + ) + assert np.allclose(popsize1, popsize0) + + @pytest.mark.parametrize("recipe", [next(recipe_eq("everyone"))], indirect=True) def test_errors(self, recipe): for _, ts in recipe["ts"].items(): x_bins = [0, 1.0] y_bins = [0, 1.0] time_bins = [0, 10.0] - for stage in ['abcd', 10, []]: + for stage in ["abcd", 10, []]: with pytest.raises(ValueError): pyslim.population_size(ts, x_bins, y_bins, time_bins, stage=stage) with pytest.raises(ValueError): - pyslim.population_size(ts, x_bins, y_bins, time_bins, remembered_stage=stage) + pyslim.population_size( + ts, x_bins, y_bins, time_bins, remembered_stage=stage + ) - @pytest.mark.parametrize('recipe', [next(recipe_eq("pedigree", "WF"))], indirect=True) + @pytest.mark.parametrize( + "recipe", [next(recipe_eq("pedigree", "WF"))], indirect=True + ) def test_mismatched_remembered_stage(self, recipe): for _, ts in recipe["ts"].items(): x_bins = [0, 1.0] @@ -102,42 +124,47 @@ def test_mismatched_remembered_stage(self, recipe): info = recipe["info"] if "remembered_early" in recipe: with pytest.warns(UserWarning): - pyslim.population_size(ts, x_bins, y_bins, time_bins, remembered_stage="late") + pyslim.population_size( + ts, x_bins, y_bins, time_bins, remembered_stage="late" + ) else: with pytest.warns(UserWarning): - pyslim.population_size(ts, x_bins, y_bins, time_bins, remembered_stage="early") + pyslim.population_size( + ts, x_bins, y_bins, time_bins, remembered_stage="early" + ) @pytest.mark.skip("Waiting on next tskit release.") - @pytest.mark.parametrize('recipe', recipe_eq("everyone"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("everyone"), indirect=True) def test_population_size(self, recipe): # compare output to the right answer for _, ts in recipe["ts"].items(): - remembered_stage = 'early' if 'remembered_early' in recipe else 'late' + remembered_stage = "early" if "remembered_early" in recipe else "late" self.verify(ts, remembered_stage=remembered_stage) def test_known_answer(self): # a simple example to make sure we've got the edge cases right tables = tskit.TableCollection(sequence_length=1) - pyslim.set_tree_sequence_metadata(tables, model_type='nonWF', tick=0) + pyslim.set_tree_sequence_metadata(tables, model_type="nonWF", tick=0) pyslim.set_metadata_schemas(tables) - locs = [[0, 0], # alive at 0, 1 - [0, 1], # alive at 0, 1, 2 - [2, 0], # alive at 0, 1, 2 - [1, 1], # alive at 0, 1, 2 - [0, 0], # alive at 1 - [0.5, 1], # alive at 1 - [2, 2], # alive at 1 - [3, 2] # alive at 0, 1, 2, 3 + locs = [ + [0, 0], # alive at 0, 1 + [0, 1], # alive at 0, 1, 2 + [2, 0], # alive at 0, 1, 2 + [1, 1], # alive at 0, 1, 2 + [0, 0], # alive at 1 + [0.5, 1], # alive at 1 + [2, 2], # alive at 1 + [3, 2], # alive at 0, 1, 2, 3 ] births = [1, 2, 2, 2, 1, 1, 1, 3] ages = [1, 2, 2, 2, 0, 0, 0, 3] x_bins = [0, 1, 3] for xy, a in zip(locs, ages): - md = pyslim.default_slim_metadata('individual') - md['age'] = a + md = pyslim.default_slim_metadata("individual") + md["age"] = a tables.individuals.add_row( - location=xy + [np.nan], - metadata=md, + location=xy + [np.nan], + metadata=md, ) for j, b in enumerate(births): @@ -146,63 +173,42 @@ def test_known_answer(self): ts = tables.tree_sequence() # check we've got this right - for k, n in enumerate([ - [0, 1, 2, 3, 7], - [0, 1, 2, 3, 4, 5, 6, 7], - [1, 2, 3, 7], - [7]]): - np.testing.assert_array_equal( - n, - pyslim.individuals_alive_at(ts, k) - ) + for k, n in enumerate( + [[0, 1, 2, 3, 7], [0, 1, 2, 3, 4, 5, 6, 7], [1, 2, 3, 7], [7]] + ): + np.testing.assert_array_equal(n, pyslim.individuals_alive_at(ts, k)) # no-one counts = pyslim.population_size( - ts, - x_bins=np.arange(10), - y_bins=np.arange(10), - time_bins=[100, 200, 300], + ts, + x_bins=np.arange(10), + y_bins=np.arange(10), + time_bins=[100, 200, 300], ) np.testing.assert_array_equal( - counts, - np.zeros((9, 9, 2)), + counts, + np.zeros((9, 9, 2)), ) # everyone at the start counts = pyslim.population_size( - ts, - x_bins=[0, 10], - y_bins=[0, 10], - time_bins=[0, 1], - ) - np.testing.assert_array_equal( - counts, - [[[5]]] + ts, + x_bins=[0, 10], + y_bins=[0, 10], + time_bins=[0, 1], ) + np.testing.assert_array_equal(counts, [[[5]]]) # should omit the last one counts = pyslim.population_size( - ts, - x_bins=[0, 3], - y_bins=[0, 3], - time_bins=[0, 1] - ) - np.testing.assert_array_equal( - counts, - [[[4]]] + ts, x_bins=[0, 3], y_bins=[0, 3], time_bins=[0, 1] ) + np.testing.assert_array_equal(counts, [[[4]]]) # now should omit the ones at the boundaries counts = pyslim.population_size( - ts, - x_bins=[0, 1, 2], - y_bins=[0, 1, 2], - time_bins=[0, 1, 2, 5] + ts, x_bins=[0, 1, 2], y_bins=[0, 1, 2], time_bins=[0, 1, 2, 5] ) np.testing.assert_array_equal( - counts, - [[[1, 2, 0], - [1, 2, 1/3]], - [[0, 0, 0], - [1, 1, 1/3]]] + counts, [[[1, 2, 0], [1, 2, 1 / 3]], [[0, 0, 0], [1, 1, 1 / 3]]] ) diff --git a/tests/test_tree_sequence.py b/tests/test_tree_sequence.py index 09a11b12..309f0a5a 100644 --- a/tests/test_tree_sequence.py +++ b/tests/test_tree_sequence.py @@ -1,16 +1,17 @@ """ Test cases for tree sequences. """ -import random -import numpy as np -import os + import json +import random +import sys +import msprime +import numpy as np import pytest import tskit -import msprime -import pyslim +import pyslim import tests from .recipe_specs import recipe_eq, restarted_recipe_eq @@ -44,57 +45,65 @@ def naive_mutation_at(ts, node, pos, time=None): class TestSlimTime(tests.PyslimTestCase): # Tests for slim_time() - @pytest.mark.parametrize('recipe', recipe_eq(exclude="long"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq(exclude="long"), indirect=True) def test_slim_time(self, recipe): for _, ts in recipe["ts"].items(): if "init_mutated" not in recipe: for mut in ts.mutations(): - mut_time = max([x['slim_time'] for x in mut.metadata['mutation_list']]) + mut_time = max( + [x["slim_time"] for x in mut.metadata["mutation_list"]] + ) assert mut_time == pyslim.slim_time(ts, mut.time) # the mutations in "init_mutated" examples have mutations that are *added* # in *early*, and so their times match in that stage. else: for mut in ts.mutations(): - mut_time = max([x['slim_time'] for x in mut.metadata['mutation_list']]) + mut_time = max( + [x["slim_time"] for x in mut.metadata["mutation_list"]] + ) assert mut_time == pyslim.slim_time(ts, mut.time, stage="early") class TestNextMutationID(tests.PyslimTestCase): - ''' + """ Tests for the function that returns the largest SLiM mutation ID. - ''' + """ + def test_next_id(self, recipe): for _, ts in recipe["ts"].items(): - mt_ids_str = ','.join( - tskit.unpack_strings(ts.tables.mutations.derived_state, - ts.tables.mutations.derived_state_offset) + mt_ids_str = ",".join( + tskit.unpack_strings( + ts.tables.mutations.derived_state, + ts.tables.mutations.derived_state_offset, + ) ) - mt_ids = [int(i or 0) for i in mt_ids_str.split(',')] + mt_ids = [int(i or 0) for i in mt_ids_str.split(",")] max_mt_id = max(mt_ids) assert max_mt_id + 1 == pyslim.next_slim_mutation_id(ts) + @pytest.mark.skipif(sys.platform == "win32", reason="Issue #412") @pytest.mark.parametrize( - 'recipe', - recipe_eq("adds_mutations", exclude="multichrom"), # <-- TODO - indirect=True + "recipe", + recipe_eq("adds_mutations", exclude="multichrom"), # <-- TODO + indirect=True, ) def test_reload_slim(self, recipe, helper_functions, tmp_path): recapped = {} for chrom, ts in recipe["ts"].items(): rts = self.do_recapitate( - ts, - recombination_rate=1e-8, - ancestral_Ne=100, - random_seed=875, - keep_vacant=True, + ts, + recombination_rate=1e-8, + ancestral_Ne=100, + random_seed=875, + keep_vacant=True, ) next_id = pyslim.next_slim_mutation_id(rts) mts = msprime.sim_mutations( - rts, - rate=6e-4, - keep=True, - model=msprime.SLiMMutationModel(type=1, next_id=next_id), - random_seed=135, + rts, + rate=6e-4, + keep=True, + model=msprime.SLiMMutationModel(type=1, next_id=next_id), + random_seed=135, ) assert mts.num_mutations > rts.num_mutations recapped[chrom] = mts @@ -105,12 +114,12 @@ def test_reload_slim(self, recipe, helper_functions, tmp_path): chrom_type = ts.metadata["SLiM"]["this_chromosome"]["type"] slimfile = "restart_nucleotides_WF.slim" rrts = helper_functions.run_slim_restart( - recapped, - slimfile, - tmp_path, - multichrom, - WF=False, - CHROM_TYPE=chrom_type, + recapped, + slimfile, + tmp_path, + multichrom, + WF=False, + CHROM_TYPE=chrom_type, ) for chrom, ts in rrts.items(): # nothing should change @@ -118,57 +127,58 @@ def test_reload_slim(self, recipe, helper_functions, tmp_path): assert pyslim.next_slim_mutation_id(mts) == pyslim.next_slim_mutation_id(ts) assert ts.num_mutations == recapped[chrom].num_mutations a = ts.metadata - a['SLiM'].pop("user_metadata", None) + a["SLiM"].pop("user_metadata", None) b = recipe["ts"][chrom].metadata - b['SLiM'].pop("user_metadata", None) + b["SLiM"].pop("user_metadata", None) assert a == b def test_invalid_derived_state(self): ts = msprime.sim_ancestry( - 4, - sequence_length=10, - population_size=10, - random_seed=10, + 4, + sequence_length=10, + population_size=10, + random_seed=10, ) mts = msprime.sim_mutations( - ts, - model="jc69", - rate=0.5, - random_seed=23, + ts, + model="jc69", + rate=0.5, + random_seed=23, ) with pytest.raises(ValueError, match="values coercible to int"): pyslim.next_slim_mutation_id(mts) + class TestRecapitate(tests.PyslimTestCase): - ''' + """ Tests for recapitation. - ''' + """ def check_recap_consistency(self, ts, recap, with_ancestral_Ne=True): - assert ts.metadata['SLiM']['tick'] == recap.metadata['SLiM']['tick'] - assert ts.metadata['SLiM']['cycle'] == recap.metadata['SLiM']['cycle'] - assert ts.metadata['SLiM']['stage'] == recap.metadata['SLiM']['stage'] - assert ts.metadata['SLiM']['name'] == recap.metadata['SLiM']['name'] + assert ts.metadata["SLiM"]["tick"] == recap.metadata["SLiM"]["tick"] + assert ts.metadata["SLiM"]["cycle"] == recap.metadata["SLiM"]["cycle"] + assert ts.metadata["SLiM"]["stage"] == recap.metadata["SLiM"]["stage"] + assert ts.metadata["SLiM"]["name"] == recap.metadata["SLiM"]["name"] assert all(tree.num_roots == 1 for tree in recap.trees()) assert ts.has_reference_sequence() == recap.has_reference_sequence() if ts.has_reference_sequence(): assert ts.reference_sequence.data == recap.reference_sequence.data - root_times = list(set([ - ts.node(n).time for t in ts.trees(root_threshold=2) for n in t.roots - ])) + root_times = list( + set([ts.node(n).time for t in ts.trees(root_threshold=2) for n in t.roots]) + ) assert len(root_times) == 1 if with_ancestral_Ne: # check that time recorded in provenance is correct assert recap.num_provenances == 2 recap_prov = json.loads(recap.provenance(1).record) - recap_events = recap_prov['parameters']['demography']['events'] + recap_events = recap_prov["parameters"]["demography"]["events"] assert len(recap_events) == 1 - recap_time = recap_events[0]['time'] + recap_time = recap_events[0]["time"] assert np.allclose(recap_time, root_times[0]) # the oldest nodes in all trees with SLiM provenance should be at that time - if recap.num_nodes <= 500: # takes a long time otherwise + if recap.num_nodes <= 500: # takes a long time otherwise for t in recap.trees(): for n in t.nodes(): rn = recap.node(n) @@ -182,9 +192,9 @@ def check_recap_consistency(self, ts, recap, with_ancestral_Ne=True): n1 = recap.node(u) assert n1.individual >= 0 i1 = recap.individual(n1.individual) - remembered = ((pyslim.INDIVIDUAL_REMEMBERED & i1.flags) > 0) - retained = ((pyslim.INDIVIDUAL_RETAINED & i1.flags) > 0) - alive = ((pyslim.INDIVIDUAL_ALIVE & i1.flags) > 0) + remembered = (pyslim.INDIVIDUAL_REMEMBERED & i1.flags) > 0 + retained = (pyslim.INDIVIDUAL_RETAINED & i1.flags) > 0 + alive = (pyslim.INDIVIDUAL_ALIVE & i1.flags) > 0 assert alive or remembered or retained assert u in ts_samples n2 = ts.node(u) @@ -201,29 +211,33 @@ def check_recap_consistency(self, ts, recap, with_ancestral_Ne=True): # find ancestral pop in which recapitation happens tables = ts.tables # note: this next one assumes the tick hasn't been set to something other than 1 - anc_nodes = np.where(tables.nodes.time > ts.metadata['SLiM']['tick'])[0] + anc_nodes = np.where(tables.nodes.time > ts.metadata["SLiM"]["tick"])[0] if len(anc_nodes) > 0: for pop in ts.populations(): - if pop.metadata is not None and pop.metadata['name'] == "ancestral": + if pop.metadata is not None and pop.metadata["name"] == "ancestral": break - assert pop.metadata['name'] == "ancestral" + assert pop.metadata["name"] == "ancestral" assert np.all(tables.nodes.population[anc_nodes] == pop.id) # Just test on the first recipe - @pytest.mark.parametrize('recipe', [next(recipe_eq())], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq())], indirect=True) def test_recapitate_errors(self, recipe): ts = list(recipe["ts"].values())[0] - with pytest.raises(ValueError, match="cannot specify both `demography` and `ancestral_Ne`"): + with pytest.raises( + ValueError, match="cannot specify both `demography` and `ancestral_Ne`" + ): _ = self.do_recapitate( - ts, - recombination_rate=0.0, - demography=msprime.Demography.from_tree_sequence(ts), - ancestral_Ne=10, - random_seed=123, + ts, + recombination_rate=0.0, + demography=msprime.Demography.from_tree_sequence(ts), + ancestral_Ne=10, + random_seed=123, ) def test_root_mismatch_error(self): - ts = msprime.sim_ancestry(4, sequence_length=10, random_seed=12, recombination_rate=0.1) + ts = msprime.sim_ancestry( + 4, sequence_length=10, random_seed=12, recombination_rate=0.1 + ) assert ts.num_trees > 1 recap_time = 100 assert ts.node(ts.first().roots[0]).time < recap_time @@ -244,7 +258,7 @@ def test_unique_names(self): t.populations.add_row(metadata=md) ts = t.tree_sequence() rts = self.do_recapitate(ts, ancestral_Ne=10) - names = [pop.metadata['name'] for pop in rts.populations()] + names = [pop.metadata["name"] for pop in rts.populations()] assert len(set(names)) == len(names) assert names[0] == "ancestral" assert names[-2] == "ancestral_ancestral" @@ -253,10 +267,7 @@ def test_recapitation(self, recipe): for _, ts in recipe["ts"].items(): recomb_rate = 1.0 / ts.sequence_length recap = self.do_recapitate( - ts, - recombination_rate=recomb_rate, - ancestral_Ne=10, - random_seed=5 + ts, recombination_rate=recomb_rate, ancestral_Ne=10, random_seed=5 ) # there should be no new mutations assert ts.num_mutations == recap.num_mutations @@ -264,63 +275,67 @@ def test_recapitation(self, recipe): assert list(ts.tables.sites.position) == list(recap.tables.sites.position) self.check_recap_consistency(ts, recap) - if ts.metadata['SLiM']['tick'] < 200: + if ts.metadata["SLiM"]["tick"] < 200: old_root_time = np.max(ts.tables.nodes.time) for t in recap.trees(): assert t.num_roots == 1 assert recap.node(t.root).time >= old_root_time - @pytest.mark.parametrize('recipe', recipe_eq(exclude="long"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq(exclude="long"), indirect=True) def test_with_recomb_map(self, recipe): for _, ts in recipe["ts"].items(): recomb_rate = 1.0 / ts.sequence_length recombination_map = msprime.RateMap( - position = [0.0, ts.sequence_length], - rate = [recomb_rate] + position=[0.0, ts.sequence_length], rate=[recomb_rate] ) recap = self.do_recapitate( - ts, - recombination_rate=recombination_map, - ancestral_Ne=1e-6, - random_seed=875, + ts, + recombination_rate=recombination_map, + ancestral_Ne=1e-6, + random_seed=875, ) self.check_recap_consistency(ts, recap) - @pytest.mark.parametrize('recipe', recipe_eq("multipop"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("multipop"), indirect=True) def test_with_demography(self, recipe): for _, ts in recipe["ts"].items(): recomb_rate = 1.0 / ts.sequence_length demography = msprime.Demography.from_tree_sequence(ts) for pop in demography.populations: - pop.initial_size=100.0 + pop.initial_size = 100.0 demography.add_population( - initial_size=10, - name='ancestral', - extra_metadata={"slim_id": ts.num_populations}, + initial_size=10, + name="ancestral", + extra_metadata={"slim_id": ts.num_populations}, ) demography.add_population_split( - time=ts.metadata["SLiM"]["tick"] + 20.0, # assumes tick hasn't been changed - derived=[p.name for p in demography.populations if p.name != "ancestral"], - ancestral="ancestral", + time=ts.metadata["SLiM"]["tick"] + + 20.0, # assumes tick hasn't been changed + derived=[ + p.name for p in demography.populations if p.name != "ancestral" + ], + ancestral="ancestral", ) recap = self.do_recapitate( - ts, - demography=demography, - recombination_rate=recomb_rate, - random_seed=333, + ts, + demography=demography, + recombination_rate=recomb_rate, + random_seed=333, ) self.check_recap_consistency(ts, recap, with_ancestral_Ne=False) - @pytest.mark.parametrize('recipe', recipe_eq(exclude=["long", "starts_later"]), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq(exclude=["long", "starts_later"]), indirect=True + ) def test_first_gen_nodes(self, recipe): # check that all the roots of the trees are present # (note this will fail if some populations were started at different # times than others or if the tick has been changed) for _, ts in recipe["ts"].items(): - root_time = ts.metadata['SLiM']['tick'] - is_wf = (ts.metadata['SLiM']['model_type'] == 'WF') - remembered_stage = ts.metadata['SLiM']['stage'] - if (not is_wf) or (remembered_stage != 'late'): + root_time = ts.metadata["SLiM"]["tick"] + is_wf = ts.metadata["SLiM"]["model_type"] == "WF" + remembered_stage = ts.metadata["SLiM"]["stage"] + if (not is_wf) or (remembered_stage != "late"): root_time -= 1 if (not is_wf) and ("begun_first" in recipe): root_time += 1 @@ -330,17 +345,19 @@ def test_first_gen_nodes(self, recipe): root_time -= 1 for t in ts.trees(): for u in t.roots: - assert (pyslim.node_is_vacant(ts, ts.node(u)) - or ts.node(u).time == root_time) + assert ( + pyslim.node_is_vacant(ts, ts.node(u)) + or ts.node(u).time == root_time + ) class TestIndividualAges(tests.PyslimTestCase): # tests for individuals_alive_at and individual_ages_at - @pytest.mark.parametrize('recipe', [next(recipe_eq("everyone"))], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq("everyone"))], indirect=True) def test_errors(self, recipe): for _, ts in recipe["ts"].items(): - for stage in ['abcd', 10, []]: + for stage in ["abcd", 10, []]: with pytest.raises(ValueError): pyslim.individuals_alive_at(ts, 0, stage=stage) with pytest.raises(ValueError): @@ -348,7 +365,9 @@ def test_errors(self, recipe): with pytest.raises(ValueError): pyslim.individual_ages_at(ts, 0, stage=stage) - @pytest.mark.parametrize('recipe', [next(recipe_eq("pedigree", "WF"))], indirect=True) + @pytest.mark.parametrize( + "recipe", [next(recipe_eq("pedigree", "WF"))], indirect=True + ) def test_mismatched_remembered_stage(self, recipe): for _, ts in recipe["ts"].items(): if "remembered_early" in recipe: @@ -358,7 +377,9 @@ def test_mismatched_remembered_stage(self, recipe): with pytest.warns(UserWarning): pyslim.individuals_alive_at(ts, 0, remembered_stage="early") - @pytest.mark.parametrize('recipe', recipe_eq("multipop", exclude="remembered_early"), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq("multipop", exclude="remembered_early"), indirect=True + ) def test_population(self, recipe): for _, ts in recipe["ts"].items(): individual_populations = ts.individuals_population @@ -372,20 +393,35 @@ def test_population(self, recipe): sub_inds = pyslim.individuals_alive_at(ts, 0, population=np.arange(p)) assert set(sub_inds) == set(all_inds[individual_populations != p]) - @pytest.mark.parametrize('recipe', recipe_eq("nonWF", exclude="remembered_early"), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq("nonWF", exclude="remembered_early"), indirect=True + ) def test_samples_only(self, recipe): for _, ts in recipe["ts"].items(): all_inds = pyslim.individuals_alive_at(ts, 0) - assert set(all_inds) == set(pyslim.individuals_alive_at(ts, 0, samples_only=False)) - sub_inds = np.random.choice(all_inds, size=min(len(all_inds), 4), replace=False) - flags = np.array([n.flags & (tskit.NODE_IS_SAMPLE * n.individual in sub_inds) - for n in ts.nodes()], dtype=np.uint32) + assert set(all_inds) == set( + pyslim.individuals_alive_at(ts, 0, samples_only=False) + ) + sub_inds = np.random.choice( + all_inds, size=min(len(all_inds), 4), replace=False + ) + flags = np.array( + [ + n.flags & (tskit.NODE_IS_SAMPLE * n.individual in sub_inds) + for n in ts.nodes() + ], + dtype=np.uint32, + ) tables = ts.dump_tables() tables.nodes.flags = flags new_ts = tables.tree_sequence() - assert set(sub_inds) == set(pyslim.individuals_alive_at(new_ts, 0, samples_only=True)) + assert set(sub_inds) == set( + pyslim.individuals_alive_at(new_ts, 0, samples_only=True) + ) - @pytest.mark.parametrize('recipe', recipe_eq(exclude=("remembered_early", "long")), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq(exclude=("remembered_early", "long")), indirect=True + ) def test_after_simplify(self, recipe): for _, ts in recipe["ts"].items(): sts = ts.simplify() @@ -400,73 +436,67 @@ def test_after_simplify(self, recipe): if n.flags & tskit.NODE_IS_SAMPLE: assert slim_id in sdict - @pytest.mark.parametrize('recipe', recipe_eq("pedigree"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("pedigree"), indirect=True) def test_ages(self, recipe): for _, ts in recipe["ts"].items(): info = recipe["info"] - remembered_stage = 'late' - if 'remembered_first' in recipe: - remembered_stage = 'first' - elif 'remembered_early' in recipe: - remembered_stage = 'early' - assert remembered_stage == ts.metadata['SLiM']['stage'] - max_time_ago = ts.metadata['SLiM']['tick'] - if remembered_stage in ('first', 'early'): + remembered_stage = "late" + if "remembered_first" in recipe: + remembered_stage = "first" + elif "remembered_early" in recipe: + remembered_stage = "early" + assert remembered_stage == ts.metadata["SLiM"]["stage"] + max_time_ago = ts.metadata["SLiM"]["tick"] + if remembered_stage in ("first", "early"): max_time_ago -= 1 for time in range(0, max_time_ago): - slim_tick = ts.metadata['SLiM']['tick'] - time - check_stages = ('first', 'early', 'late') + slim_tick = ts.metadata["SLiM"]["tick"] - time + check_stages = ("first", "early", "late") if time == 0: - if remembered_stage == 'first': + if remembered_stage == "first": # if we remember in first we don't know who's still there # in later stages of that time step - check_stages = ('first', ) - elif remembered_stage == 'early': - check_stages = ('first', 'early') + check_stages = ("first",) + elif remembered_stage == "early": + check_stages = ("first", "early") if time == max_time_ago: - if remembered_stage == 'early': + if remembered_stage == "early": # if we set up the population in early there aren't individuals in first # of the very first time step - check_stages = ('early', 'late') - elif remembered_stage == 'late': + check_stages = ("early", "late") + elif remembered_stage == "late": # similarly for late - check_stages = ('late', ) + check_stages = ("late",) for stage in check_stages: alive = pyslim.individuals_alive_at( - ts, - time, - stage=stage, - remembered_stage=remembered_stage + ts, time, stage=stage, remembered_stage=remembered_stage ) ages = pyslim.individual_ages_at( - ts, - time, - stage=stage, - remembered_stage=remembered_stage + ts, time, stage=stage, remembered_stage=remembered_stage ) for ind in ts.individuals(): ind_time = ts.node(ind.nodes[0]).time # bad things can happen for the very first individuals # depending on when the subpops are created - if (('everyone' in recipe or ind_time == 0) and - (remembered_stage == "early" or ind_time < max_time_ago)): + if ("everyone" in recipe or ind_time == 0) and ( + remembered_stage == "early" or ind_time < max_time_ago + ): slim_id = ind.metadata["pedigree_id"] assert slim_id in info - slim_alive = (slim_tick, stage) in info[slim_id]['age'] + slim_alive = (slim_tick, stage) in info[slim_id]["age"] pyslim_alive = ind.id in alive assert slim_alive == pyslim_alive if slim_alive: - slim_age = info[slim_id]['age'][(slim_tick, stage)] + slim_age = info[slim_id]["age"][(slim_tick, stage)] if ts.metadata["SLiM"]["model_type"] == "WF": # SLiM records -1 but we return 0 in late and 1 in early - slim_age = 0 + (stage in ('first', 'early')) + slim_age = 0 + (stage in ("first", "early")) assert ages[ind.id] == slim_age else: assert np.isnan(ages[ind.id]) class TestHasIndividualParents(tests.PyslimTestCase): - def verify_has_parents(self, ts): right_answer = np.repeat(True, ts.num_individuals) node_indivs = ts.tables.nodes.individual @@ -527,9 +557,9 @@ def get_first_gen(self, ts): root_time = np.max(nodes.time) first_gen = set(nodes.individual[nodes.time == root_time]) first_gen.discard(tskit.NULL) - return np.array(list(first_gen), dtype='int') + return np.array(list(first_gen), dtype="int") - @pytest.mark.parametrize('recipe', recipe_eq("everyone"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("everyone"), indirect=True) def test_everyone(self, recipe): # since everyone is recorded, only the initial individuals should # not have parents @@ -543,43 +573,47 @@ def test_everyone(self, recipe): assert np.array_equal(right_answer, has_parents) self.verify_has_parents(ts) - @pytest.mark.parametrize('recipe', recipe_eq("everyone"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("everyone"), indirect=True) def test_post_recap(self, recipe): # the same should be true after recapitation for _, ts in recipe["ts"].items(): right_answer = np.repeat(True, ts.num_individuals) first_gen = self.get_first_gen(ts) right_answer[first_gen] = False - assert(ts.num_populations <= 2) - ts = self.do_recapitate(ts, recombination_rate=0.01, ancestral_Ne=10, random_seed=11) + assert ts.num_populations <= 2 + ts = self.do_recapitate( + ts, recombination_rate=0.01, ancestral_Ne=10, random_seed=11 + ) with pytest.warns(FutureWarning): has_parents = pyslim.has_individual_parents(ts) assert np.array_equal(right_answer, has_parents) self.verify_has_parents(ts) - @pytest.mark.parametrize('recipe', recipe_eq("everyone"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("everyone"), indirect=True) def test_post_simplify(self, recipe): for _, ts in recipe["ts"].items(): rng = np.random.default_rng(seed=3) individual_times = ts.individuals_time keep_indivs = rng.choice( - # assumes tick hasn't been changed - np.where(individual_times < ts.metadata['SLiM']['tick'] - 1)[0], - size=30, - replace=False + # assumes tick hasn't been changed + np.where(individual_times < ts.metadata["SLiM"]["tick"] - 1)[0], + size=30, + replace=False, ) keep_nodes = [] for i in keep_indivs: keep_nodes.extend(ts.individual(i).nodes) - ts = ts.simplify(samples=keep_nodes, filter_individuals=True, keep_input_roots=True) - assert(ts.num_populations <= 2) + ts = ts.simplify( + samples=keep_nodes, filter_individuals=True, keep_input_roots=True + ) + assert ts.num_populations <= 2 ts = self.do_recapitate(ts, recombination_rate=0.01, ancestral_Ne=10) with pytest.warns(FutureWarning): has_parents = pyslim.has_individual_parents(ts) assert sum(has_parents) > 0 self.verify_has_parents(ts) - @pytest.mark.parametrize('recipe', recipe_eq("everyone"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("everyone"), indirect=True) def test_pedigree_parents_everyone(self, recipe): # We can only guarantee to correctly reconstruct parents when everyone is remembered: # for instance, A selfs to produce B who selfs to produce C; if A and C are present @@ -597,7 +631,7 @@ def test_pedigree_parents_everyone(self, recipe): for ind in ts.individuals(): slim_map[ind.metadata["pedigree_id"]] = ind.id ts_to_slim = {sid: [] for sid in slim_map} - for (pa, ch) in parents: + for pa, ch in parents: assert pa >= 0 and pa < ts.num_individuals assert ch >= 0 and pa < ts.num_individuals pa_ind = ts.individual(pa).metadata["pedigree_id"] @@ -616,7 +650,9 @@ def test_pedigree_parents_everyone(self, recipe): # TODO: excluding multichrom because there's a great-grandparent who makes this # test fail in recipe_all_the_chromosome_types.slim - @pytest.mark.parametrize('recipe', recipe_eq("pedigree", exclude="multichrom"), indirect=True) + @pytest.mark.parametrize( + "recipe", recipe_eq("pedigree", exclude="multichrom"), indirect=True + ) def test_pedigree_parents(self, recipe): # Less strict test for consistency only: see caveats above in test_pedigree_parents_everyone. # In particular, we are only guaranteed to have whole genomes for ALIVE @@ -631,14 +667,17 @@ def test_pedigree_parents(self, recipe): for ind in ts.individuals(): slim_map[ind.metadata["pedigree_id"]] = ind.id ts_to_slim = {sid: [] for sid in slim_map} - for (pa, ch) in parents: + for pa, ch in parents: assert pa >= 0 and pa < ts.num_individuals assert ch >= 0 and pa < ts.num_individuals pa_ind = ts.individual(pa).metadata["pedigree_id"] ch_ind = ts.individual(ch).metadata["pedigree_id"] ts_to_slim[ch_ind].append(pa_ind) for hasp, ind in zip(has_parents, ts.individuals()): - all_there = (ind.flags & (pyslim.INDIVIDUAL_ALIVE | pyslim.INDIVIDUAL_REMEMBERED) > 0) + all_there = ( + ind.flags & (pyslim.INDIVIDUAL_ALIVE | pyslim.INDIVIDUAL_REMEMBERED) + > 0 + ) if all_there: for n in ind.nodes: assert ts.node(n).is_sample() @@ -663,11 +702,11 @@ def test_pedigree_parents(self, recipe): class TestReferenceSequence(tests.PyslimTestCase): - ''' + """ Test for operations involving the reference sequence - ''' + """ - @pytest.mark.parametrize('recipe', recipe_eq(exclude="long"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq(exclude="long"), indirect=True) def test_reference_sequence(self, recipe): for _, ts in recipe["ts"].items(): if ts.num_mutations > 0: @@ -676,7 +715,7 @@ def test_reference_sequence(self, recipe): if not has_nucleotides: assert not ts.has_reference_sequence() else: - assert type(ts.reference_sequence.data) == type('') + assert type(ts.reference_sequence.data) == str assert len(ts.reference_sequence.data) == ts.sequence_length for u in ts.reference_sequence.data: assert u in pyslim.NUCLEOTIDES @@ -721,27 +760,20 @@ def test_mutation_at(self, recipe): c = pyslim.mutation_at(ts, node, pos, ts.node(parent).time) assert b == c rtime = max([ts.node(r).time for r in tree.roots]) - ut = ( - ts.node(node).time + - (rtime - ts.node(node).time) * rng.random() - ) + ut = ts.node(node).time + (rtime - ts.node(node).time) * rng.random() for time in [None, ts.node(node).time, ut]: a = pyslim.mutation_at(ts, node, pos, time=time) b = naive_mutation_at(ts, node, pos, time=time) - assert a== b + assert a == b for _ in range(min(10, int(ts.sequence_length - ts.num_sites))): - pos = rng.choice(list( - set(range(int(ts.sequence_length))) - - set(ts.sites_position)) + pos = rng.choice( + list(set(range(int(ts.sequence_length))) - set(ts.sites_position)) ) tree = ts.at(pos) for _ in range(10): node = rng.randint(0, ts.num_nodes - 1) rtime = max([ts.node(r).time for r in tree.roots]) - ut = ( - ts.node(node).time + - (rtime - ts.node(node).time) * rng.random() - ) + ut = ts.node(node).time + (rtime - ts.node(node).time) * rng.random() for time in [None, ts.node(node).time, ut]: assert naive_mutation_at(ts, node, pos, time=time) == -1 @@ -750,7 +782,7 @@ def test_nucleotide_at(self, recipe): for _, ts in recipe["ts"].items(): if ts.num_mutations > 0: mut_md = ts.mutation(0).metadata - has_nucleotides = (mut_md["mutation_list"][0]["nucleotide"] >= 0) + has_nucleotides = mut_md["mutation_list"][0]["nucleotide"] >= 0 if has_nucleotides: assert ts.has_reference_sequence() assert len(ts.reference_sequence.data) == ts.sequence_length @@ -773,7 +805,7 @@ def test_nucleotide_at(self, recipe): b = mut.metadata["mutation_list"][0]["nucleotide"] assert a == b - @pytest.mark.parametrize('recipe', recipe_eq("mutation_spectrum"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("mutation_spectrum"), indirect=True) def test_nucleotide_spectrum(self, recipe): # this is modified from Recipe 18.13 # Also note that we are comparing to "truth" in a recipe where @@ -783,24 +815,35 @@ def test_nucleotide_spectrum(self, recipe): for _, ts in recipe["ts"].items(): mutation_spectrum = recipe["mutation_info"] M = { - a + b + c + "," + d : 0 - for a in pyslim.NUCLEOTIDES - for b in pyslim.NUCLEOTIDES - for c in pyslim.NUCLEOTIDES - for d in pyslim.NUCLEOTIDES + a + b + c + "," + d: 0 + for a in pyslim.NUCLEOTIDES + for b in pyslim.NUCLEOTIDES + for c in pyslim.NUCLEOTIDES + for d in pyslim.NUCLEOTIDES } nmuts = 0 for mut in ts.mutations(): - pos = ts.site(mut.site).position + pos = ts.site(mut.site).position if pos > 0 and pos < ts.sequence_length - 1: nmuts += 1 mut_list = mut.metadata["mutation_list"] k = np.argmax([u["slim_time"] for u in mut_list]) derived_nuc = mut_list[k]["nucleotide"] - left_nuc = pyslim.nucleotide_at(ts, mut.node, pos - 1, time = mut.time + 1.0) - right_nuc = pyslim.nucleotide_at(ts, mut.node, pos + 1, time = mut.time + 1.0) - parent_nuc = pyslim.nucleotide_at(ts, mut.node, pos, time = mut.time + 1.0) - context = "".join([pyslim.NUCLEOTIDES[k] for k in (left_nuc, parent_nuc, right_nuc)]) + left_nuc = pyslim.nucleotide_at( + ts, mut.node, pos - 1, time=mut.time + 1.0 + ) + right_nuc = pyslim.nucleotide_at( + ts, mut.node, pos + 1, time=mut.time + 1.0 + ) + parent_nuc = pyslim.nucleotide_at( + ts, mut.node, pos, time=mut.time + 1.0 + ) + context = "".join( + [ + pyslim.NUCLEOTIDES[k] + for k in (left_nuc, parent_nuc, right_nuc) + ] + ) key = context + "," + pyslim.NUCLEOTIDES[derived_nuc] M[key] += 1 if key == "ACA,T" or key == "CCA,T": @@ -816,9 +859,9 @@ def test_nucleotide_spectrum(self, recipe): class TestConvertNucleotides(tests.PyslimTestCase): - ''' + """ Test for operations involving the converting and generating nucleotides - ''' + """ def last_slim_mutations(self, ts): # iterator over mutations, returning for each mutation in ts a tuple @@ -827,24 +870,30 @@ def last_slim_mutations(self, ts): # is possible that this is ambiguous. for mut in ts.mutations(): slim_muts = { - k : v for k, v in zip( - mut.derived_state.split(","), - mut.metadata['mutation_list'] - ) + k: v + for k, v in zip( + mut.derived_state.split(","), mut.metadata["mutation_list"] + ) } if mut.parent == tskit.NULL: parent_slim_ids = [] else: parent_mut = ts.mutation(mut.parent) parent_slim_ids = parent_mut.derived_state.split(",") - max_time = max([md['slim_time'] for md in slim_muts.values()]) - any_new = any([k not in parent_slim_ids for k in slim_muts.keys() - if slim_muts[k]['slim_time'] == max_time]) - maybe_these = [k for k in slim_muts.keys() - if slim_muts[k]["slim_time"] == max_time - and ((k not in parent_slim_ids) - or (not any_new)) - ] + max_time = max([md["slim_time"] for md in slim_muts.values()]) + any_new = any( + [ + k not in parent_slim_ids + for k in slim_muts.keys() + if slim_muts[k]["slim_time"] == max_time + ] + ) + maybe_these = [ + k + for k in slim_muts.keys() + if slim_muts[k]["slim_time"] == max_time + and ((k not in parent_slim_ids) or (not any_new)) + ] k = max(maybe_these) yield k, slim_muts[k] @@ -857,13 +906,15 @@ def verify_converted_nucleotides(self, ts, cts): assert s.position == ns.position assert s.metadata == ns.metadata assert ns.ancestral_state == ts.reference_sequence.data[int(s.position)] - for m, cm, (_, sm) in zip(ts.mutations(), cts.mutations(), self.last_slim_mutations(ts)): + for m, cm, (_, sm) in zip( + ts.mutations(), cts.mutations(), self.last_slim_mutations(ts) + ): assert m.site == cm.site assert m.node == cm.node assert m.parent == cm.parent assert m.time == cm.time assert m.metadata == cm.metadata - nuc = sm['nucleotide'] + nuc = sm["nucleotide"] assert nuc in [0, 1, 2, 3] assert cm.derived_state == pyslim.NUCLEOTIDES[nuc] # should not have changed anything else @@ -886,12 +937,9 @@ def scramble_mutations(self, ts): for m in ts.mutations(): a = np.array(m.derived_state.split(",")) ii = rng.permutation(len(a)) - ml = [m.metadata['mutation_list'][i] for i in ii] + ml = [m.metadata["mutation_list"][i] for i in ii] t.mutations.append( - m.replace( - derived_state=",".join(a[ii]), - metadata={'mutation_list': ml} - ) + m.replace(derived_state=",".join(a[ii]), metadata={"mutation_list": ml}) ) t.compute_mutation_parents() return t.tree_sequence() @@ -903,19 +951,18 @@ def test_convert_alleles_errors(self): ts = pyslim.annotate(ts, model_type="nonWF", tick=1) with pytest.raises(ValueError, match="must have a valid reference sequence"): _ = pyslim.convert_alleles(ts) - mts = msprime.sim_mutations(ts, - model=msprime.SLiMMutationModel(type=1), - rate=0.1, - random_seed=23) + mts = msprime.sim_mutations( + ts, model=msprime.SLiMMutationModel(type=1), rate=0.1, random_seed=23 + ) assert mts.num_mutations > 0 mtt = mts.dump_tables() - mtt.reference_sequence.data = 'A' * int(mts.sequence_length) + mtt.reference_sequence.data = "A" * int(mts.sequence_length) mts = mtt.tree_sequence() with pytest.raises(ValueError, match="must be nucleotide mutations"): _ = pyslim.convert_alleles(mts) @pytest.mark.parametrize( - 'recipe', recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True + "recipe", recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True ) def test_convert_alleles(self, recipe): for _, ts in recipe["ts"].items(): @@ -934,7 +981,7 @@ def test_convert_alleles(self, recipe): self.verify_converted_nucleotides(ts, cts) @pytest.mark.parametrize( - 'recipe', recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True + "recipe", recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True ) def test_convert_alleles_scrambled(self, recipe): for _, ts in recipe["ts"].items(): @@ -943,7 +990,7 @@ def test_convert_alleles_scrambled(self, recipe): self.verify_converted_nucleotides(ts, cts) @pytest.mark.parametrize( - 'recipe', recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True + "recipe", recipe_eq("nucleotides", exclude="non-nucleotides"), indirect=True ) def test_keeps_reference_sequence(self, recipe): for _, ts in recipe["ts"].items(): @@ -953,40 +1000,39 @@ def test_keeps_reference_sequence(self, recipe): assert ts.reference_sequence == nts.reference_sequence def test_generate_nucleotides_errors(self): - ts = msprime.sim_ancestry(4, sequence_length=10, population_size=10, random_seed=777) + ts = msprime.sim_ancestry( + 4, sequence_length=10, population_size=10, random_seed=777 + ) with pytest.raises(ValueError, match="must have length equal"): _ = pyslim.generate_nucleotides(ts, reference_sequence="AAA") with pytest.raises(ValueError, match="must have length equal"): _ = pyslim.generate_nucleotides(ts, reference_sequence=[1, 2, 3]) with pytest.raises(ValueError, match="must be a string of"): _ = pyslim.generate_nucleotides( - ts, - reference_sequence="X" * int(ts.sequence_length) + ts, reference_sequence="X" * int(ts.sequence_length) ) with pytest.raises(ValueError, match="must be a string of"): _ = pyslim.generate_nucleotides( - ts, - reference_sequence=np.arange(int(ts.sequence_length)), + ts, + reference_sequence=np.arange(int(ts.sequence_length)), ) def verify_generate_nucleotides(self, ts, check_transitions=False): # if check_transitions is True, verify that derived states differ # from parental states - which we try to do but is not guaranteed, # for instance, if keep=True or in other weird situations. - assert ts.metadata['SLiM']['nucleotide_based'] + assert ts.metadata["SLiM"]["nucleotide_based"] assert len(ts.reference_sequence.data) == ts.sequence_length muts = {} ts_muts = { - j : v['nucleotide'] - for j, (_, v) in enumerate(self.last_slim_mutations(ts)) + j: v["nucleotide"] for j, (_, v) in enumerate(self.last_slim_mutations(ts)) } for mut in ts.mutations(): aa = ts.reference_sequence.data[int(ts.site(mut.site).position)] for i, md in zip( - mut.derived_state.split(","), - mut.metadata['mutation_list'] - ): - nuc = md['nucleotide'] + mut.derived_state.split(","), mut.metadata["mutation_list"] + ): + nuc = md["nucleotide"] assert nuc in [0, 1, 2, 3] if i in muts: assert muts[i] == nuc @@ -1002,22 +1048,21 @@ def test_generate_nucleotides(self, recipe): for _, ts in recipe["ts"].items(): nts = pyslim.generate_nucleotides(ts, keep=False, seed=5) self.verify_generate_nucleotides( - nts, - check_transitions=("adds_mutations" not in recipe), + nts, + check_transitions=("adds_mutations" not in recipe), ) def test_generate_nucleotides_refseq(self): ts = msprime.sim_ancestry( - 4, - sequence_length=10, - population_size=10, - random_seed=10, + 4, + sequence_length=10, + population_size=10, + random_seed=10, + ) + ts = pyslim.annotate(ts, model_type="nonWF", tick=1) + mts = msprime.sim_mutations( + ts, model=msprime.SLiMMutationModel(type=1), rate=0.5, random_seed=23 ) - ts = pyslim.annotate(ts, model_type='nonWF', tick=1) - mts = msprime.sim_mutations(ts, - model=msprime.SLiMMutationModel(type=1), - rate=0.5, - random_seed=23) refseq = "A" * int(mts.sequence_length) nts = pyslim.generate_nucleotides(mts, reference_sequence=refseq, seed=6) self.verify_generate_nucleotides(nts, check_transitions=True) @@ -1025,61 +1070,63 @@ def test_generate_nucleotides_refseq(self): def test_generate_nucleotides_keep(self): ts = msprime.sim_ancestry(4, sequence_length=10, population_size=10) - ts = pyslim.annotate(ts, model_type='nonWF', tick=1) - mts1 = msprime.sim_mutations(ts, - model=msprime.SLiMMutationModel(type=1), - rate=0.1, - random_seed=23) + ts = pyslim.annotate(ts, model_type="nonWF", tick=1) + mts1 = msprime.sim_mutations( + ts, model=msprime.SLiMMutationModel(type=1), rate=0.1, random_seed=23 + ) mts1.dump("out.trees") nts1 = pyslim.generate_nucleotides(mts1, seed=10, keep=False) assert nts1.num_mutations > 0 self.verify_generate_nucleotides(nts1, check_transitions=False) - mts2 = msprime.sim_mutations(nts1, - model=msprime.SLiMMutationModel( - type=2, - next_id=nts1.num_mutations, - ), - rate=0.1, - random_seed=24, + mts2 = msprime.sim_mutations( + nts1, + model=msprime.SLiMMutationModel( + type=2, + next_id=nts1.num_mutations, + ), + rate=0.1, + random_seed=24, ) # keep defaults to True nts2 = pyslim.generate_nucleotides(mts2, seed=12) assert nts2.num_mutations > nts1.num_mutations muts1 = {} for mut in nts1.mutations(): - for i, md in zip(mut.derived_state.split(","), mut.metadata['mutation_list']): - muts1[i] = md['nucleotide'] + for i, md in zip( + mut.derived_state.split(","), mut.metadata["mutation_list"] + ): + muts1[i] = md["nucleotide"] for mut in nts2.mutations(): - for i, md in zip(mut.derived_state.split(","), mut.metadata['mutation_list']): - if md['mutation_type'] == 1: + for i, md in zip( + mut.derived_state.split(","), mut.metadata["mutation_list"] + ): + if md["mutation_type"] == 1: assert i in muts1 - assert muts1[i] == md['nucleotide'] + assert muts1[i] == md["nucleotide"] else: - assert md['nucleotide'] in [0, 1, 2, 3] + assert md["nucleotide"] in [0, 1, 2, 3] nts3 = pyslim.generate_nucleotides(mts2, keep=False, seed=15) self.verify_generate_nucleotides(nts3, check_transitions=False) - @pytest.mark.parametrize( - 'recipe', ["recipe_long_nonWF.slim"], indirect=True - ) + @pytest.mark.parametrize("recipe", ["recipe_long_nonWF.slim"], indirect=True) def test_generate_and_convert(self, recipe, helper_functions, tmp_path): for _, ts in recipe["ts"].items(): nts = pyslim.generate_nucleotides(ts, seed=123) cts = pyslim.convert_alleles(nts) self.verify_converted_nucleotides(nts, cts) helper_functions.run_slim_restart( - {"default": nts}, - "restart_nucleotides_nonWF.slim", - tmp_path, - multichrom=False, - WF=False, + {"default": nts}, + "restart_nucleotides_nonWF.slim", + tmp_path, + multichrom=False, + WF=False, ) class TestDeprecations(tests.PyslimTestCase): # test on one arbitrary recipe @pytest.mark.skip(reason="TODO") - @pytest.mark.parametrize('recipe', [next(recipe_eq())], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq())], indirect=True) def test_slim_tree_sequence(self, recipe): ts = list(recipe["ts"].values())[0] with pytest.warns(FutureWarning): @@ -1087,12 +1134,11 @@ def test_slim_tree_sequence(self, recipe): class TestVacancy(tests.PyslimTestCase): - def vacancy_values(self, node): if node.metadata is None: out = None else: - b = node.metadata['is_vacant'] + b = node.metadata["is_vacant"] out = [] powers = [1, 2, 4, 8, 16, 32, 64, 128] for bb in b: @@ -1115,19 +1161,21 @@ def verify_remove_vacant(self, ts, rts): vacant_samples = self.get_vacant_samples(ts) for node in rts.nodes(): assert not (pyslim.node_is_vacant(rts, node) and (node.is_sample() == 1)) - assert (node.id in vacant_samples) == (node.flags & pyslim.NODE_IS_VACANT_SAMPLE > 0) + assert (node.id in vacant_samples) == ( + node.flags & pyslim.NODE_IS_VACANT_SAMPLE > 0 + ) def verify_restore_vacant(self, ts, rrts): vacant_samples = self.get_vacant_samples(ts) rr_vacant_samples = self.get_vacant_samples(rrts) assert np.all(vacant_samples == rr_vacant_samples) ts.tables.assert_equals( - rrts.tables, - ignore_ts_metadata=True, - ignore_provenance=True, + rrts.tables, + ignore_ts_metadata=True, + ignore_provenance=True, ) - @pytest.mark.parametrize('recipe', [next(recipe_eq())], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq())], indirect=True) def test_chromosome_index_errors(self, recipe): ts = list(recipe["ts"].values())[0] # no SLiM > this_chromosome key @@ -1135,7 +1183,7 @@ def test_chromosome_index_errors(self, recipe): md = tables.metadata del md["SLiM"]["this_chromosome"] tables.metadata_schema = tskit.MetadataSchema( - {"codec": "json", "type": "object"} + {"codec": "json", "type": "object"} ) tables.metadata = md with pytest.raises(ValueError, match="in top-level metadata"): @@ -1146,7 +1194,7 @@ def test_chromosome_index_errors(self, recipe): with pytest.raises(ValueError, match="in top-level metadata"): pyslim.remove_vacant(tables.tree_sequence()) - @pytest.mark.parametrize('recipe', [next(recipe_eq("Y"))], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq("Y"))], indirect=True) def test_restore_vacant_bad_nodes(self, recipe): ts = pyslim.remove_vacant(list(recipe["ts"].values())[0]) tables = ts.dump_tables() @@ -1167,7 +1215,9 @@ def test_restore_vacant_bad_nodes(self, recipe): with pytest.raises(ValueError, match="has no metadata"): _ = pyslim.restore_vacant(tables.tree_sequence()) - @pytest.mark.parametrize('recipe', [next(recipe_eq("multichrom", "X", "Y"))], indirect=True) + @pytest.mark.parametrize( + "recipe", [next(recipe_eq("multichrom", "X", "Y"))], indirect=True + ) def test_multiple_remove_vacant_warning(self, recipe): done = 0 for ts in recipe["ts"].values(): @@ -1188,15 +1238,15 @@ def test_has_vacant_samples(self, recipe): def test_has_vacant_msprime(self): ts = msprime.sim_ancestry( - 4, - sequence_length=10, - population_size=10, - random_seed=10, + 4, + sequence_length=10, + population_size=10, + random_seed=10, ) with pytest.raises(ValueError, match="top-level metadata"): _ = pyslim.has_vacant_samples(ts) tables = ts.dump_tables() - tables.metadata_schema = tskit.MetadataSchema({'codec': 'json'}) + tables.metadata_schema = tskit.MetadataSchema({"codec": "json"}) tables.metadata = {} with pytest.raises(ValueError, match="top-level metadata"): _ = pyslim.has_vacant_samples(ts) @@ -1233,11 +1283,11 @@ def test_recapitate_keeps_vacant(self, recipe): for chrom, ts in recipe["ts"].items(): before = pyslim.has_vacant_samples(ts) recap_ts = self.do_recapitate( - ts, - recombination_rate=1e-8, - ancestral_Ne=100, - random_seed=875, - keep_vacant=True, + ts, + recombination_rate=1e-8, + ancestral_Ne=100, + random_seed=875, + keep_vacant=True, ) assert before == pyslim.has_vacant_samples(recap_ts) # now check we can remove and restore @@ -1246,7 +1296,7 @@ def test_recapitate_keeps_vacant(self, recipe): rrts = pyslim.restore_vacant(rts) self.verify_restore_vacant(recap_ts, rrts) - @pytest.mark.parametrize('recipe', recipe_eq("multichrom"), indirect=True) + @pytest.mark.parametrize("recipe", recipe_eq("multichrom"), indirect=True) def test_remove_restore_vacant_tables(self, recipe): for _, ts in recipe["ts"].items(): rtables = ts.dump_tables() @@ -1255,7 +1305,7 @@ def test_remove_restore_vacant_tables(self, recipe): pyslim.restore_vacant_tables(rtables) self.verify_restore_vacant(ts, rtables.tree_sequence()) - @pytest.mark.parametrize('recipe', [next(recipe_eq("multichrom"))], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq("multichrom"))], indirect=True) def test_multiple_restore_vacant(self, recipe): # restore_vacant( ) should be idempotent for _, ts in recipe["ts"].items(): @@ -1268,21 +1318,24 @@ def test_multiple_restore_vacant(self, recipe): class TestFlags(tests.PyslimTestCase): - def test_flags_types(self): # they should be unsigned so this should be true assert ~pyslim.INDIVIDUAL_ALIVE > 0 assert ~pyslim.INDIVIDUAL_REMEMBERED > 0 assert ~pyslim.INDIVIDUAL_RETAINED > 0 - @pytest.mark.parametrize('recipe', [next(recipe_eq("multichrom"))], indirect=True) + @pytest.mark.parametrize("recipe", [next(recipe_eq("multichrom"))], indirect=True) def test_alive_not_alive(self, recipe): - for flag in (pyslim.INDIVIDUAL_ALIVE, pyslim.INDIVIDUAL_REMEMBERED, pyslim.INDIVIDUAL_RETAINED): + for flag in ( + pyslim.INDIVIDUAL_ALIVE, + pyslim.INDIVIDUAL_REMEMBERED, + pyslim.INDIVIDUAL_RETAINED, + ): yes = None no = None for _, ts in recipe["ts"].items(): - this_yes, = np.where(ts.individuals_flags & flag > 0) - this_no, = np.where(ts.individuals_flags & ~flag > 0) + (this_yes,) = np.where(ts.individuals_flags & flag > 0) + (this_no,) = np.where(ts.individuals_flags & ~flag > 0) if yes is None: yes = this_yes else: @@ -1294,23 +1347,22 @@ def test_alive_not_alive(self, recipe): class TestSetInitialState(tests.PyslimTestCase): - def verify_reset(self, its, ots, time=0, individuals=None): # we're writing out the tree sequences unchanged if individuals is None: - individuals = [ind.id for ind in its.individuals() - if ind.flags & pyslim.INDIVIDUAL_ALIVE > 0] - slim_ids = [ - its.individual(k).metadata["pedigree_id"] - for k in individuals - ] + individuals = [ + ind.id + for ind in its.individuals() + if ind.flags & pyslim.INDIVIDUAL_ALIVE > 0 + ] + slim_ids = [its.individual(k).metadata["pedigree_id"] for k in individuals] for ind in ots.individuals(): sid = ind.metadata["pedigree_id"] if sid in slim_ids: assert ind.flags & pyslim.INDIVIDUAL_ALIVE > 0 else: assert ind.flags & pyslim.INDIVIDUAL_ALIVE == 0 - assert its.metadata['SLiM']['tick'] == ots.metadata['SLiM']['tick'] + time + assert its.metadata["SLiM"]["tick"] == ots.metadata["SLiM"]["tick"] + time assert np.allclose( its.mutations_time, ots.mutations_time + time, @@ -1325,63 +1377,71 @@ def verify_reset(self, its, ots, time=0, individuals=None): ) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op"), indirect=["recipe"]) + "restart_name, recipe", restarted_recipe_eq("no_op"), indirect=["recipe"] + ) def test_no_change(self, restart_name, recipe, helper_functions, tmp_path): in_ts = {} for chrom, ts in recipe["ts"].items(): in_ts[chrom] = pyslim.set_slim_state(ts) # put it through SLiM (which just reads in and writes out) out_ts = helper_functions.run_slim_restart( - in_ts, - restart_name, - tmp_path, - "multichrom" in recipe, - WF="WF" in recipe, + in_ts, + restart_name, + tmp_path, + "multichrom" in recipe, + WF="WF" in recipe, ) for chrom, ts in recipe["ts"].items(): self.verify_reset(ts, out_ts[chrom]) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op"), indirect=["recipe"]) + "restart_name, recipe", restarted_recipe_eq("no_op"), indirect=["recipe"] + ) def test_shift_time(self, restart_name, recipe, helper_functions, tmp_path): in_ts = {} time = 3 for chrom, ts in recipe["ts"].items(): in_ts[chrom] = pyslim.set_slim_state(ts, time=time) out_ts = helper_functions.run_slim_restart( - in_ts, - restart_name, - tmp_path, - "multichrom" in recipe, - WF="WF" in recipe, + in_ts, + restart_name, + tmp_path, + "multichrom" in recipe, + WF="WF" in recipe, ) for chrom, ts in recipe["ts"].items(): self.verify_reset(ts, out_ts[chrom], time=time) @pytest.mark.parametrize( - 'restart_name, recipe', restarted_recipe_eq("no_op", 'resettable'), indirect=["recipe"]) - @pytest.mark.parametrize('num_indivs', [2, 100]) - @pytest.mark.parametrize('time', [0, None]) - def test_set_individuals(self, restart_name, recipe, num_indivs, time, helper_functions, tmp_path): + "restart_name, recipe", + restarted_recipe_eq("no_op", "resettable"), + indirect=["recipe"], + ) + @pytest.mark.parametrize("num_indivs", [2, 100]) + @pytest.mark.parametrize("time", [0, None]) + def test_set_individuals( + self, restart_name, recipe, num_indivs, time, helper_functions, tmp_path + ): in_ts = {} ts = list(recipe["ts"].values())[0] - assert ('user_metadata' in ts.metadata['SLiM'] and - 'reset_tick' in ts.metadata['SLiM']['user_metadata']), "Simulation not set up for this test." - reset_tick = ts.metadata['SLiM']['user_metadata']['reset_tick'][0] + assert ( + "user_metadata" in ts.metadata["SLiM"] + and "reset_tick" in ts.metadata["SLiM"]["user_metadata"] + ), "Simulation not set up for this test." + reset_tick = ts.metadata["SLiM"]["user_metadata"]["reset_tick"][0] if time is None: - for time in range(ts.metadata['SLiM']['tick'] + 1): + for time in range(ts.metadata["SLiM"]["tick"] + 1): if pyslim.slim_time(ts, time) == reset_tick: break individuals = pyslim.individuals_alive_at(ts, time)[:num_indivs] for chrom, ts in recipe["ts"].items(): in_ts[chrom] = pyslim.set_slim_state(ts, time=time, individuals=individuals) out_ts = helper_functions.run_slim_restart( - in_ts, - restart_name, - tmp_path, - "multichrom" in recipe, - WF="WF" in recipe, + in_ts, + restart_name, + tmp_path, + "multichrom" in recipe, + WF="WF" in recipe, ) for chrom, ts in recipe["ts"].items(): self.verify_reset(ts, out_ts[chrom], time=time, individuals=individuals) - diff --git a/tests/test_util.py b/tests/test_util.py index a78068e5..12bf739b 100644 --- a/tests/test_util.py +++ b/tests/test_util.py @@ -1,14 +1,14 @@ """ Test cases for utility functions. 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