From e905aa2e43d7d9a7c9b6c9bb6f201969f9072eed Mon Sep 17 00:00:00 2001 From: Oliver Ruebel Date: Mon, 5 Apr 2021 12:21:58 -0700 Subject: [PATCH] Add icephys meta (#1349) Declare SweepTable as deprecated on init Add TimeSeriesReferenceVectorData Container class Add simple test for TimeSeriesReferenceVectorData Update nwb-schema branch Add icephys metadata container classes Update NWBFile to support icephys metadata tables Add unit tests for icephys metadata tables Update imports and fix SweepTable integration tests Fix test available namespaces testcase Update SweepTable tutorial and declare as deprecated Add new icephys tutorial using the new hierarchical metadata tables Add IntracellularRecordingsTable illustration Fix flake8 issues Remove use of HierarchiclaDynamicTableMixin use for now Add source PowerPoint file for icephys docs add doc for TimeIntervals (#1352) * add doc for TimeIntervals * add allensdk back Fix make clean command for docs to also clean sphinx-gallery files Updated CHANGELOG to describe changes from this PR Add thumbnails for domain-specfic tutorials Add thumbnaisl for general tutorials Update changelog Remove ic_filtering/icephys_filtering duplicate and fix test Fix description of ExperimentalConditionsTable Use HDMF 2.5.0 (#1354) DOC: make template less puzzling in how to fill out ;-) (#1336) Co-authored-by: Ryan Ly Add ReadTheDocs badge to README (#1311) Co-authored-by: Ryan Ly Update to use upcoming HDMF 2.5.1 (#1355) Revert breaking changes to scratch API (#1356) Use HDMF 2.5.2 (#1360) Add `DfOverF` to docs (#1351) Co-authored-by: Ryan Ly docs/gallery/general/file.py: Fix argument count in documentation add strain optional arg to Subject (#1241) * remove validate_core_schema. You can check the core schema with e.g. * Update Subject unit test * Fix Subject unit test, add check for date_of_birth Co-authored-by: Ryan Ly add source channels to DecompSeries add option to include source_channels for DecompositionSeries (#1258) * add option to include source_channels for DecompositionSeries and include round trip test * Use latest schema * Add unit test Add optional link to Device in ImageSeries (#1265) * Add optional link to Device in ImageSeries * Add support for device in ImageSeries subclasses * Update ImageMaskSeries docstring * Update schema add continuity optional arg to TimeSeries.__init__ (#1226) * add continuity optional arg to TimeSeries.__init__ * use new enum feature of hdmf to check against controlled vocabulary * Fix flake8 * Add integration test * Fix flake8 * Add correct mapping for data.continuity Co-authored-by: Ryan Ly Add support for ElectricalSeries.filtering dataset (#1270) Set fixed value for IZeroClampSeries stimulus description Fix test Update changelog Add note about allensdk py3.8 incompatibility Add workaround for validation against cached hdmf-experimental Update CI to avoid click8 incompatibility Use HDMF 2.5.5 Address comments, improve doc Fix docs, add citation info, update repo infra (#1362) Use latest HDMF, raise min pandas, dissociate req-min and setup reqs (#1363) Use nwb schema branch for icephys meta Ensure start_index and count are set to -1 if TimeSeries is None Add test for conversion of start_index and index_count vals Fix flake8 in __compute_index docstring Fix icephys metadata roundtrip NWBFile test base on update DynamicTableRegion behavior Update schema (updated version to 1.4.0-alpha) improve extensions documentation (#1350) * improve extensions documentation * adjustments to extensions.rst * add tips to extension docs * create multi-part extensions tutorial * move API building docs to chapter 5 of extensions guide * restructure and fix up some spots * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/6_documenting_extension.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/4_auto_api.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Oliver Ruebel * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Oliver Ruebel * remove detailed GroupSpec API instructions from tutorial * remove instructions for generated the directory structure, and instead focus on generating the HTML and filling in the missing pieces. * add link to ndx catalog * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/4_auto_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/5_custom_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/4_auto_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/4_auto_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/4_auto_api.rst * Update docs/source/extensions_tutorial/3_spec_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/5_custom_api.rst Co-authored-by: Ryan Ly * Update docs/source/extensions_tutorial/5_custom_api.rst Co-authored-by: Ryan Ly * Update extensions_tutorial_home.rst * Minor text fixes * Minor text fixes * Minor text fixes Co-authored-by: Oliver Ruebel Co-authored-by: Ryan Ly Set language for code block to fix readthedocs Add RRID for PyNWB Add RRID to README Update changelog make MotionCorrection test (#1374) * attempt to make MotionCorrection test. I don't understand why it's failing * Fix CorrectedImageStack nwbfields * Fix tests * Fix test * Fix flake8 * Fix test Co-authored-by: Ryan Ly Add unique electrode id check (#1344) Co-authored-by: Ryan Ly Fix integration tests with invalid test data that will be caught by future hdmf validator version (#1366) Co-authored-by: Ryan Ly Improve documentation and test for CorrectedImageStack (#1306) Fix test for validator update (#1376) Update changelog Allow h5py 3 so that this can work with hdmf rc/3.0.0 Move SweepTable DeprectationWarning to the constructor of SweepTable to clean up code Suppress SweepTable Deprecation warning in icephys integration test Ignore and assert deprecation warning for SweepTable during SweepTable roundtrip tests Merge branch 'rc/2.0.0' into add/icephys_meta Fix falke8 on icephys tutorial galleries --- .circleci/config.yml | 145 +- .coveragerc | 6 + .github/ISSUE_TEMPLATE/bug_report.md | 7 +- .github/PULL_REQUEST_TEMPLATE.md | 7 +- .github/PULL_REQUEST_TEMPLATE/release.md | 26 + .github/workflows/workflow.yml | 4 +- .gitignore | 3 + CHANGELOG.md | 71 +- Legal.txt | 2 +- MANIFEST.in | 2 +- README.rst | 21 +- azure-pipelines-nightly.yml | 66 +- azure-pipelines.yml | 33 +- docs/Makefile | 2 +- docs/gallery/domain/brain_observatory.py | 7 +- docs/gallery/domain/ecephys.py | 8 +- docs/gallery/domain/icephys.py | 26 +- docs/gallery/domain/ophys.py | 7 +- docs/gallery/domain/plot_icephys.py | 632 +++++++ docs/gallery/general/add_remove_containers.py | 1 + docs/gallery/general/advanced_hdf5_io.py | 1 + docs/gallery/general/extensions.py | 1 + docs/gallery/general/file.py | 56 +- docs/gallery/general/iterative_write.py | 1 + docs/gallery/general/linking_data.py | 2 +- docs/gallery/general/object_id.py | 1 + docs/gallery/general/scratch.py | 1 + docs/make.bat | 1 + docs/source/building_api.rst | 193 --- docs/source/conf.py | 11 +- docs/source/extensions.rst | 404 ----- .../2_create_extension_spec_walkthrough.rst | 141 ++ .../source/extensions_tutorial/3_spec_api.rst | 183 +++ .../source/extensions_tutorial/4_auto_api.rst | 67 + .../extensions_tutorial/5_custom_api.rst | 282 ++++ .../6_documenting_extension.rst | 40 + .../extensions_tutorial_home.rst | 17 + docs/source/figures/gallery_thumbnails.pptx | Bin 0 -> 2258651 bytes ...llery_thumbnails_add_remove_containers.png | Bin 0 -> 77100 bytes .../gallery_thumbnails_advnaced_hdf5_io.png | Bin 0 -> 49409 bytes ...llery_thumbnails_allenbrainobservatory.png | Bin 0 -> 361272 bytes .../figures/gallery_thumbnails_ecephys.png | Bin 0 -> 565631 bytes .../figures/gallery_thumbnails_extensions.png | Bin 0 -> 155405 bytes .../figures/gallery_thumbnails_file.png | Bin 0 -> 88991 bytes .../figures/gallery_thumbnails_icephys.png | Bin 0 -> 232265 bytes .../gallery_thumbnails_icephys_sweeptable.png | Bin 0 -> 116892 bytes .../gallery_thumbnails_iterative_write.png | Bin 0 -> 168736 bytes .../gallery_thumbnails_linking_data.png | Bin 0 -> 72354 bytes .../figures/gallery_thumbnails_objectid.png | Bin 0 -> 141983 bytes .../figures/gallery_thumbnails_ophys.png | Bin 0 -> 335259 bytes .../figures/gallery_thumbnails_scratch.png | Bin 0 -> 98604 bytes docs/source/figures/plot_icephys_figures.pptx | Bin 0 -> 521005 bytes ...icephys_intracellular_recordings_table.png | Bin 0 -> 294698 bytes .../figures/plot_icephys_table_hierarchy.png | Bin 0 -> 258505 bytes docs/source/getting_started.rst | 2 +- docs/source/index.rst | 8 +- docs/source/overview_citing.rst | 61 + docs/source/software_process.rst | 19 +- docs/source/update_requirements.rst | 2 +- license.txt | 2 +- requirements-dev.txt | 16 +- requirements-doc.txt | 3 +- requirements-min.txt | 9 +- requirements.txt | 10 +- setup.cfg | 16 +- setup.py | 15 +- src/pynwb/__init__.py | 24 +- src/pynwb/_due.py | 74 + src/pynwb/base.py | 34 +- src/pynwb/core.py | 32 +- src/pynwb/ecephys.py | 13 +- src/pynwb/file.py | 349 +++- src/pynwb/icephys.py | 559 ++++++- src/pynwb/image.py | 21 +- src/pynwb/io/base.py | 1 + src/pynwb/io/file.py | 8 +- src/pynwb/io/icephys.py | 24 +- src/pynwb/misc.py | 19 +- src/pynwb/nwb-schema | 2 +- src/pynwb/ophys.py | 16 +- src/pynwb/validate.py | 16 +- test.h5 | Bin 2448 -> 0 bytes test.py | 29 +- tests/back_compat/test_read.py | 14 +- tests/coloredtestrunner.py | 498 ------ tests/integration/hdf5/test_base.py | 3 +- tests/integration/hdf5/test_ecephys.py | 27 +- tests/integration/hdf5/test_icephys.py | 55 +- tests/integration/hdf5/test_image.py | 49 +- tests/integration/hdf5/test_misc.py | 71 +- tests/integration/hdf5/test_nwbfile.py | 7 +- tests/integration/hdf5/test_ophys.py | 151 +- tests/integration/test_io.py | 13 +- tests/unit/test_base.py | 20 +- tests/unit/test_core.py | 3 +- tests/unit/test_ecephys.py | 14 +- tests/unit/test_epoch.py | 2 +- tests/unit/test_extension.py | 29 +- tests/unit/test_file.py | 22 +- tests/unit/test_icephys.py | 26 +- tests/unit/test_icephys_metadata_tables.py | 1458 +++++++++++++++++ tests/unit/test_image.py | 18 +- tests/unit/test_misc.py | 33 +- tests/unit/test_ophys.py | 43 +- tests/validation/test_validate.py | 16 +- tox.ini | 64 +- 106 files changed, 4900 insertions(+), 1598 deletions(-) create mode 100644 .github/PULL_REQUEST_TEMPLATE/release.md create mode 100644 docs/gallery/domain/plot_icephys.py delete mode 100644 docs/source/building_api.rst delete mode 100644 docs/source/extensions.rst create mode 100644 docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst create mode 100644 docs/source/extensions_tutorial/3_spec_api.rst create mode 100644 docs/source/extensions_tutorial/4_auto_api.rst create mode 100644 docs/source/extensions_tutorial/5_custom_api.rst create mode 100644 docs/source/extensions_tutorial/6_documenting_extension.rst create mode 100644 docs/source/extensions_tutorial/extensions_tutorial_home.rst create mode 100644 docs/source/figures/gallery_thumbnails.pptx create mode 100644 docs/source/figures/gallery_thumbnails_add_remove_containers.png create mode 100644 docs/source/figures/gallery_thumbnails_advnaced_hdf5_io.png create mode 100644 docs/source/figures/gallery_thumbnails_allenbrainobservatory.png create mode 100644 docs/source/figures/gallery_thumbnails_ecephys.png create mode 100644 docs/source/figures/gallery_thumbnails_extensions.png create mode 100644 docs/source/figures/gallery_thumbnails_file.png create mode 100644 docs/source/figures/gallery_thumbnails_icephys.png create mode 100644 docs/source/figures/gallery_thumbnails_icephys_sweeptable.png create mode 100644 docs/source/figures/gallery_thumbnails_iterative_write.png create mode 100644 docs/source/figures/gallery_thumbnails_linking_data.png create mode 100644 docs/source/figures/gallery_thumbnails_objectid.png create mode 100644 docs/source/figures/gallery_thumbnails_ophys.png create mode 100644 docs/source/figures/gallery_thumbnails_scratch.png create mode 100644 docs/source/figures/plot_icephys_figures.pptx create mode 100644 docs/source/figures/plot_icephys_intracellular_recordings_table.png create mode 100644 docs/source/figures/plot_icephys_table_hierarchy.png create mode 100644 docs/source/overview_citing.rst create mode 100644 src/pynwb/_due.py delete mode 100644 test.h5 delete mode 100644 tests/coloredtestrunner.py create mode 100644 tests/unit/test_icephys_metadata_tables.py diff --git a/.circleci/config.yml b/.circleci/config.yml index 3f0575d44..aae6c58f1 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -38,13 +38,6 @@ references: username: hdmf password: $DOCKERHUB_PASSWORD - py36: &py36 - docker: - - image: circleci/python:3.6.13-buster - auth: - username: hdmf - password: $DOCKERHUB_PASSWORD - conda-image: &conda-image docker: - image: continuumio/miniconda3:4.9.2 @@ -161,14 +154,6 @@ jobs: - run: <<: *run-style-check - python36: - <<: *py36 - environment: - - TEST_TOX_ENV: "py36" - - BUILD_TOX_ENV: "build-py36" - - TEST_WHEELINSTALL_ENV: "wheelinstall" - <<: *ci-steps - python37: <<: *py37 environment: @@ -183,7 +168,6 @@ jobs: - TEST_TOX_ENV: "py38" - BUILD_TOX_ENV: "build-py38" - TEST_WHEELINSTALL_ENV: "wheelinstall" - - UPLOAD_WHEELS: "true" <<: *ci-steps python39: @@ -192,41 +176,33 @@ jobs: - TEST_TOX_ENV: "py39" - BUILD_TOX_ENV: "build-py39" - TEST_WHEELINSTALL_ENV: "wheelinstall" + - UPLOAD_WHEELS: "true" # upload distributions from only this job to pypi <<: *ci-steps - python38-upgrade-dev: - <<: *py38 + python39-upgrade-dev: + <<: *py39 environment: - - TEST_TOX_ENV: "py38-upgrade-dev" - - BUILD_TOX_ENV: "build-py38-upgrade-dev" + - TEST_TOX_ENV: "py39-upgrade-dev" + - BUILD_TOX_ENV: "build-py39-upgrade-dev" - TEST_WHEELINSTALL_ENV: "wheelinstall" <<: *ci-steps - python38-upgrade-dev-pre: - <<: *py38 + python39-upgrade-dev-pre: + <<: *py39 environment: - - TEST_TOX_ENV: "py38-upgrade-dev-pre" - - BUILD_TOX_ENV: "build-py38-upgrade-dev-pre" + - TEST_TOX_ENV: "py39-upgrade-dev-pre" + - BUILD_TOX_ENV: "build-py39-upgrade-dev-pre" - TEST_WHEELINSTALL_ENV: "wheelinstall" <<: *ci-steps - python36-min-req: - <<: *py36 + python37-min-req: + <<: *py37 environment: - - TEST_TOX_ENV: "py36-min-req" - - BUILD_TOX_ENV: "build-py36-min-req" + - TEST_TOX_ENV: "py37-min-req" + - BUILD_TOX_ENV: "build-py37-min-req" - TEST_WHEELINSTALL_ENV: "wheelinstall" <<: *ci-steps - miniconda36: - <<: *conda-image - environment: - - CONDA_PYTHON_VER: "3.6.*=*_cpython" # avoid using pypy compiler - - TEST_TOX_ENV: "py36" - - BUILD_TOX_ENV: "build-py36" - - TEST_WHEELINSTALL_ENV: "wheelinstall" - <<: *conda-steps - miniconda37: <<: *conda-image environment: @@ -254,12 +230,6 @@ jobs: - TEST_WHEELINSTALL_ENV: "wheelinstall" <<: *conda-steps - gallery36: - <<: *py36 - environment: - - TEST_TOX_ENV: "gallery-py36" - <<: *gallery-steps - gallery37: <<: *py37 environment: @@ -278,26 +248,26 @@ jobs: - TEST_TOX_ENV: "gallery-py39" <<: *gallery-steps - gallery38-upgrade-dev: - <<: *py38 + gallery39-upgrade-dev: + <<: *py39 environment: - - TEST_TOX_ENV: "gallery-py38-upgrade-dev" + - TEST_TOX_ENV: "gallery-py39-upgrade-dev" <<: *gallery-steps - gallery38-upgrade-dev-pre: - <<: *py38 + gallery39-upgrade-dev-pre: + <<: *py39 environment: - - TEST_TOX_ENV: "gallery-py38-upgrade-dev-pre" + - TEST_TOX_ENV: "gallery-py39-upgrade-dev-pre" <<: *gallery-steps - gallery36-min-req: - <<: *py36 + gallery37-min-req: + <<: *py37 environment: - - TEST_TOX_ENV: "gallery-py36-min-req" + - TEST_TOX_ENV: "gallery-py37-min-req" <<: *gallery-steps test-validation: - <<: *py38 + <<: *py39 steps: - checkout - run: git submodule sync @@ -309,13 +279,13 @@ jobs: command: | . ../venv/bin/activate pip install tox - tox -e validation-py38 + tox -e validation-py39 # Install is expected to be quick. Increase timeout in case there are some network issues. # While pip installing tox does not output by default. Circle thinks task is dead after 10 min. no_output_timeout: 30m deploy-dev: - <<: *py38 + <<: *py39 steps: - checkout - attach_workspace: @@ -336,7 +306,7 @@ jobs: --exit-success-if-missing-token deploy-release: - <<: *py38 + <<: *py39 steps: - attach_workspace: at: ./ @@ -354,7 +324,8 @@ jobs: command: | python -m venv ../venv . ../venv/bin/activate - pip install githubrelease + # use click<8 until https://github.com/j0057/github-release/issues/62 is resolved + pip install "click<8" githubrelease githubrelease release $CIRCLE_PROJECT_USERNAME/$CIRCLE_PROJECT_REPONAME \ create $CIRCLE_TAG --name $CIRCLE_TAG \ --publish ./dist/* @@ -365,27 +336,27 @@ workflows: jobs: - flake8: <<: *no_filters - - python38: + - python37-min-req: <<: *no_filters - - python36-min-req: + - python39: <<: *no_filters - - miniconda36: + - miniconda37: <<: *no_filters - - miniconda38: + - miniconda39: <<: *no_filters - - gallery38: + - gallery37-min-req: <<: *no_filters - - gallery36-min-req: + - gallery38: # TODO replace with gallery39 after allensdk support py39 <<: *no_filters - deploy-dev: requires: - flake8 - - python38 - - python36-min-req - - miniconda36 - - miniconda38 - - gallery38 - - gallery36-min-req + - python37-min-req + - python39 + - miniconda37 + - miniconda39 + - gallery37-min-req + - gallery38 # gallery39 filters: tags: ignore: @@ -399,12 +370,12 @@ workflows: - deploy-release: requires: - flake8 - - python38 - - python36-min-req - - miniconda36 - - miniconda38 - - gallery38 - - gallery36-min-req + - python37-min-req + - python39 + - miniconda37 + - miniconda39 + - gallery37-min-req + - gallery38 # gallery39 filters: tags: only: /^[0-9]+(\.[0-9]+)*(\.post[0-9]+)?$/ @@ -423,19 +394,17 @@ workflows: jobs: - flake8: <<: *no_filters - - python36: - <<: *no_filters - python37: <<: *no_filters + - python37-min-req: + <<: *no_filters - python38: <<: *no_filters - python39: <<: *no_filters - - python38-upgrade-dev: - <<: *no_filters - - python36-min-req: + - python39-upgrade-dev: <<: *no_filters - - miniconda36: + - python39-upgrade-dev-pre: <<: *no_filters - miniconda37: <<: *no_filters @@ -443,21 +412,15 @@ workflows: <<: *no_filters - miniconda39: <<: *no_filters - - gallery36: - <<: *no_filters - gallery37: <<: *no_filters + - gallery37-min-req: + <<: *no_filters - gallery38: <<: *no_filters - gallery39: <<: *no_filters - - gallery38-upgrade-dev: - <<: *no_filters - - gallery36-min-req: - <<: *no_filters - - python38-upgrade-dev-pre: - <<: *no_filters - - gallery38-upgrade-dev-pre: + - gallery39-upgrade-dev: <<: *no_filters - - test-validation: + - gallery39-upgrade-dev-pre: <<: *no_filters diff --git a/.coveragerc b/.coveragerc index 70e985016..3e659c1f4 100644 --- a/.coveragerc +++ b/.coveragerc @@ -3,4 +3,10 @@ branch = True source = src/ omit = src/pynwb/_version.py + src/pynwb/_due.py src/pynwb/testing/* + +[report] +exclude_lines = + pragma: no cover + @abstract diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md index e8559d83d..14f7796b1 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.md +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -20,13 +20,14 @@ assignees: '' Python Executable: Conda or Python - Python Version: Python 3.5, 3.6, or 3.7 + Python Version: Python 3.7, 3.8, or 3.9 Operating System: Windows, macOS or Linux - HDMF Version: Version of PyNWB used + HDMF Version: + PyNWB Version: ## Checklist -- [ ] Have you ensured the feature or change was not already [reported](https://github.com/NeurodataWithoutBorders/pynwb/issues)? +- [ ] Have you ensured the bug was not already [reported](https://github.com/NeurodataWithoutBorders/pynwb/issues)? - [ ] Have you included a brief and descriptive title? - [ ] Have you included a clear description of the problem you are trying to solve? - [ ] Have you included a minimal code snippet that reproduces the issue you are encountering? diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md index d3b9783b1..3542c3f8c 100644 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -4,13 +4,14 @@ What was the reasoning behind this change? Please explain the changes briefly. ## How to test the behavior? ``` -Show here how to reproduce the new behavior (can be a bug fix or a new feature) +Show how to reproduce the new behavior (can be a bug fix or a new feature) ``` ## Checklist +- [ ] Did you update CHANGELOG.md with your changes? - [ ] Have you checked our [Contributing](https://github.com/NeurodataWithoutBorders/pynwb/blob/dev/docs/CONTRIBUTING.rst) document? -- [ ] Have you ensured the PR description clearly describes problem and the solution? +- [ ] Have you ensured the PR clearly describes the problem and the solution? - [ ] Is your contribution compliant with our coding style? This can be checked running `flake8` from the source directory. - [ ] Have you checked to ensure that there aren't other open [Pull Requests](https://github.com/NeurodataWithoutBorders/pynwb/pulls) for the same change? -- [ ] Have you included the relevant issue number using `#XXX` notation where `XXX` is the issue number? +- [ ] Have you included the relevant issue number using "Fix #XXX" notation where XXX is the issue number? By including "Fix #XXX" you allow GitHub to close issue #XXX when the PR is merged. diff --git a/.github/PULL_REQUEST_TEMPLATE/release.md b/.github/PULL_REQUEST_TEMPLATE/release.md new file mode 100644 index 000000000..698263510 --- /dev/null +++ b/.github/PULL_REQUEST_TEMPLATE/release.md @@ -0,0 +1,26 @@ +Prepare for release of PyNWB [version] + +### Before merging: +- [ ] Major and minor releases: Update package versions in `requirements.txt`, `requirements-dev.txt`, + `requirements-doc.txt`, `requirements-min.txt`, `setup.py` as needed + See https://requires.io/github/NeurodataWithoutBorders/pynwb/requirements/?branch=dev +- [ ] Check legal file dates and information in `Legal.txt`, `license.txt`, `README.rst`, `docs/source/conf.py`, + and any other locations as needed +- [ ] Update `setup.py` as needed +- [ ] Update `README.rst` as needed +- [ ] Update `src/pynwb/nwb-schema` submodule as needed. Check the version number and commit SHA manually +- [ ] Update changelog (set release date) in `CHANGELOG.md` and any other docs as needed +- [ ] Run tests locally including gallery tests and validation tests, and inspect all warnings and outputs + (`python test.py -v > out.txt`) +- [ ] Test docs locally (`make apidoc`, `make html`) +- [ ] Push changes to this PR and make sure all PRs to be included in this release have been merged +- [ ] Check that the readthedocs build for this PR succeeds (build latest to pull the new branch, then activate and + build docs for new branch): https://readthedocs.org/projects/pynwb/builds/ + +### After merging: +1. Create release by following steps in `docs/source/make_a_release.rst` or use alias `git pypi-release [tag]` if set up +2. After the CI bot creates the new release (wait ~10 min), update the release notes on the + [GitHub releases page](https://github.com/NeurodataWithoutBorders/pynwb/releases) with the changelog +3. Check that the readthedocs "latest" and "stable" builds run and succeed +4. Update [conda-forge/pynwb-feedstock](https://github.com/conda-forge/pynwb-feedstock) with the latest version number + and SHA256 retrieved from PyPI > PyNWB > Download Files > View hashes for the `.tar.gz` file. Re-render as needed diff --git a/.github/workflows/workflow.yml b/.github/workflows/workflow.yml index c0cfcc234..70eb5695c 100644 --- a/.github/workflows/workflow.yml +++ b/.github/workflows/workflow.yml @@ -15,7 +15,7 @@ jobs: os: [ubuntu-latest, macos-latest, windows-latest] env: OS: ${{ matrix.os }} - PYTHON: '3.8' + PYTHON: '3.9' steps: - name: Cancel Workflow Action uses: styfle/cancel-workflow-action@0.6.0 @@ -27,7 +27,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v2 with: - python-version: 3.8 + python-version: 3.9 - name: Install dependencies run: | python -m pip install --upgrade pip diff --git a/.gitignore b/.gitignore index d2565814b..db7652720 100644 --- a/.gitignore +++ b/.gitignore @@ -59,6 +59,9 @@ docs/tmpl.index.rst tests/coverage/htmlcov .coverage +# duecredit output +.duecredit.p + # tox .tox diff --git a/CHANGELOG.md b/CHANGELOG.md index ef834b660..220366650 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,18 +2,77 @@ ## PyNWB 2.0.0 (Upcoming) -### Breaking changes: -- The 'notes' and 'table_description' arguments of `NWBFile.add_scratch(...)` are now replaced by a 'description' - argument that is required when a scalar, numpy.ndarray, list, tuple, or pandas.DataFrame is added to scratch. The - 'notes' argument of `ScratchData.__init__(...)` is now replaced by the required 'description' argument for - consistency. Previously, 'notes' had a default value of empty string, which is not recommended. @rly (#1309) +### New features +- +- +- +- + +### Internal improvements +- +- +- +- + +### Bug fixes +- +- +- +- + +## PyNWB 1.5.1 (May 24, 2021) + +## Bug fix: +- Raise minimum version of pandas from 0.23 to 1.0.5 to be compatible with numpy 1.20, and raise minimum version of + HDMF to use the corresponding change in HDMF. @rly (#1363) +- Update documentation and update structure of requirements files. @rly (#1363) + +## PyNWB 1.5.0 (May 17, 2021) ### New features: - `NWBFile.add_scratch(...)` and `ScratchData.__init__(...)` now accept scalar data in addition to the currently accepted types. @rly (#1309) - Support `pathlib.Path` paths when opening files with `NWBHDF5IO`. @dsleiter (#1314) -- Use HDMF 2.4.0. See the [HDMF 2.4.0 release notes](https://github.com/hdmf-dev/hdmf/releases/tag/2.4.0) for details. +- Use HDMF 2.5.1. See the [HDMF release notes](https://github.com/hdmf-dev/hdmf/releases/tag/2.5.1) for details. - Support `driver='ros3'` in `NWBHDF5IO` for streaming NWB files directly from s3. @bendichter (#1331) +- Update documentation, CI GitHub processes. @oruebel @yarikoptic, @bendichter, @TomDonoghue, @rly + (#1311, #1336, #1351, #1352, #1345, #1340, #1327) +- Set default `neurodata_type_inc` for `NWBGroupSpec`, `NWBDatasetSpec`. @rly (#1295) +- Block usage of h5py 3+ for now. h5py>=2.9, <3 is supported. (#1355) +- Fix incompatibility issue with downstream github-release tool used to deploy releases to GitHub. @rly (#1245) +- Fix issue with Sphinx gallery. @rly +- Add citation information to documentation and support for duecredit tool. @rly +- Remove use of ColoredTestRunner for more readable verbose test output. @rly +- Add support for nwb-schema 2.3.0. @rly (#1245, #1330) + - Add optional `waveforms` column to the `Units` table. + - Add optional `strain` field to `Subject`. + - Add to `DecompositionSeries` an optional `DynamicTableRegion` called `source_channels`. + - Add to `ImageSeries` an optional link to `Device`. + - Add optional `continuity` field to `TimeSeries`. + - Add optional `filtering` attribute to `ElectricalSeries`. + - Clarify documentation for electrode impedance and filtering. + - Set the `stimulus_description` for `IZeroCurrentClamp` to have the fixed value "N/A". + - See https://nwb-schema.readthedocs.io/en/latest/format_release_notes.html for full schema release notes. +- Add support for HDMF 2.5.5 and upgrade HDMF requirement from 2.1.0 to 2.5.5. @rly @ajtritt + (#1325, #1355, #1360, #1245, #1287). This includes several relevant features and bug fixes, including: + - Fix issue where dependencies of included types were not being loaded in namespaces / extensions. + - Add `HDF5IO.get_namespaces(path=path, file=file)` method which returns a dict of namespace name mapped to the + namespace version (the largest one if there are multiple) for each namespace cached in the given HDF5 file. + - Add methods for automatic creation of `MultiContainerInterface` classes. + - Add ability to specify a custom class for new columns to a `DynamicTable` that are not `VectorData`, + `DynamicTableRegion`, or `VocabData` using `DynamicTable.__columns__` or `DynamicTable.add_column(...)`. + - Add support for creating and specifying multi-index columns in a `DynamicTable` using `add_column(...)`. + - Add capability to add a row to a column after IO. + - Add method `AbstractContainer.get_fields_conf`. + - Add functionality for storing external resource references. + - Add method `hdmf.utils.get_docval_macro` to get a tuple of the current values for a docval_macro, e.g., 'array_data' + and 'scalar_data'. + - `DynamicTable` can be automatically generated using `get_class`. Now the HDMF API can read files with extensions + that contain a DynamicTable without needing to import the extension first. + - Add `EnumData` type for storing data that comes from a fixed set of values. + - Add `AlignedDynamicTable` type which defines a DynamicTable that supports storing a collection of subtables. + - Allow `np.bool_` as a valid `bool` dtype when validating. + - See https://github.com/hdmf-dev/hdmf/releases for full HDMF release notes. ## PyNWB 1.4.0 (August 12, 2020) diff --git a/Legal.txt b/Legal.txt index b1ba29e92..88f40f34d 100644 --- a/Legal.txt +++ b/Legal.txt @@ -1,4 +1,4 @@ -“pynwb” Copyright (c) 2017-2020, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. +“pynwb” Copyright (c) 2017-2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation & Partnerships Office at IPO@lbl.gov. diff --git a/MANIFEST.in b/MANIFEST.in index 9fa9268fe..1b9053bf2 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,4 +1,4 @@ -include license.txt Legal.txt versioneer.py src/pynwb/_version.py +include license.txt Legal.txt versioneer.py src/pynwb/_version.py src/pynwb/_due.py include requirements.txt requirements-dev.txt requirements-doc.txt requirements-min.txt include test.py tox.ini diff --git a/README.rst b/README.rst index f5f29a007..42a168b0a 100644 --- a/README.rst +++ b/README.rst @@ -37,6 +37,9 @@ Build Status Overall Health ============== +.. image:: https://github.com/NeurodataWithoutBorders/pynwb/workflows/Run%20coverage/badge.svg + :target: https://github.com/NeurodataWithoutBorders/pynwb/actions?query=workflow%3A%22Run+coverage%22 + .. image:: https://codecov.io/gh/NeurodataWithoutBorders/pynwb/branch/dev/graph/badge.svg :target: https://codecov.io/gh/NeurodataWithoutBorders/pynwb @@ -44,6 +47,14 @@ Overall Health :target: https://requires.io/github/NeurodataWithoutBorders/pynwb/requirements/?branch=dev :alt: Requirements Status +.. image:: https://readthedocs.org/projects/pynwb/badge/?version=latest + :target: https://pynwb.readthedocs.io/en/latest/?badge=latest + :alt: Documentation Status + +.. image:: https://img.shields.io/pypi/l/pynwb.svg + :target: https://github.com/neurodatawithoutborders/pynwb/blob/dev/license.txt + :alt: PyPI - License + NWB Format API ============== @@ -74,10 +85,16 @@ Contributing For details on how to contribute to PyNWB see our `contribution guidelines `_. +Citing NWB +========== + +* **Manuscript:** Oliver Rübel, Andrew Tritt, Ryan Ly, Benjamin K. Dichter, Satrajit Ghosh, Lawrence Niu, Ivan Soltesz, Karel Svoboda, Loren Frank, Kristofer E. Bouchard, "The Neurodata Without Borders ecosystem for neurophysiological data science", bioRxiv 2021.03.13.435173, March 15, 2021, doi: https://doi.org/10.1101/2021.03.13.435173 +* **RRID:** (PyNWB, RRID:SCR_017452) + LICENSE ======= -"pynwb" Copyright (c) 2017-2019, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. +"pynwb" Copyright (c) 2017-2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: (1) Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. @@ -93,7 +110,7 @@ You are under no obligation whatsoever to provide any bug fixes, patches, or upg COPYRIGHT ========= -"pynwb" Copyright (c) 2017-2020, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. +"pynwb" Copyright (c) 2017-2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation & Partnerships Office at IPO@lbl.gov. NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so. diff --git a/azure-pipelines-nightly.yml b/azure-pipelines-nightly.yml index 552d1bcd3..c0a79b9d2 100644 --- a/azure-pipelines-nightly.yml +++ b/azure-pipelines-nightly.yml @@ -19,23 +19,21 @@ jobs: imageName: 'macos-10.15' pythonVersion: '3.9' testToxEnv: 'py39' - coverageToxEnv: '' buildToxEnv: 'build-py39' testWheelInstallEnv: 'wheelinstall' - macOS-py3.8-upgrade-dev-pre: + macOS-py3.9-upgrade-dev-pre: imageName: 'macos-10.15' - pythonVersion: '3.8' - testToxEnv: 'py38-upgrade-dev-pre' - coverageToxEnv: '' - buildToxEnv: 'build-py38-upgrade-dev-pre' + pythonVersion: '3.9' + testToxEnv: 'py39-upgrade-dev-pre' + buildToxEnv: 'build-py39-upgrade-dev-pre' testWheelInstallEnv: 'wheelinstall' - macOS-py3.8-upgrade-dev: + macOS-py3.9-upgrade-dev: imageName: 'macos-10.15' - pythonVersion: '3.8' - testToxEnv: 'py38-upgrade-dev' - buildToxEnv: 'build-py38-upgrade-dev' + pythonVersion: '3.9' + testToxEnv: 'py39-upgrade-dev' + buildToxEnv: 'build-py39-upgrade-dev' testWheelInstallEnv: 'wheelinstall' macOS-py3.8: @@ -52,41 +50,32 @@ jobs: buildToxEnv: 'build-py37' testWheelInstallEnv: 'wheelinstall' - macOS-py3.6: + macOS-py3.7-min-req: imageName: 'macos-10.15' - pythonVersion: '3.6' - testToxEnv: 'py36' - buildToxEnv: 'build-py36' - testWheelInstallEnv: 'wheelinstall' - - macOS-py3.6-min-req: - imageName: 'macos-10.15' - pythonVersion: '3.6' - testToxEnv: 'py36-min-req' - buildToxEnv: 'build-py36-min-req' + pythonVersion: '3.7' + testToxEnv: 'py37-min-req' + buildToxEnv: 'build-py37-min-req' testWheelInstallEnv: 'wheelinstall' Windows-py3.9: imageName: 'vs2017-win2016' pythonVersion: '3.9' testToxEnv: 'py39' - coverageToxEnv: '' buildToxEnv: 'build-py39' testWheelInstallEnv: 'wheelinstall' - Windows-py3.8-upgrade-dev-pre: + Windows-py3.9-upgrade-dev-pre: imageName: 'vs2017-win2016' - pythonVersion: '3.8' - testToxEnv: 'py38-upgrade-dev-pre' - coverageToxEnv: '' - buildToxEnv: 'build-py38-upgrade-dev-pre' + pythonVersion: '3.9' + testToxEnv: 'py39-upgrade-dev-pre' + buildToxEnv: 'build-py39-upgrade-dev-pre' testWheelInstallEnv: 'wheelinstall' - Windows-py3.8-upgrade-dev: + Windows-py3.9-upgrade-dev: imageName: 'vs2017-win2016' - pythonVersion: '3.8' - testToxEnv: 'py38-upgrade-dev' - buildToxEnv: 'build-py38-upgrade-dev' + pythonVersion: '3.9' + testToxEnv: 'py39-upgrade-dev' + buildToxEnv: 'build-py39-upgrade-dev' testWheelInstallEnv: 'wheelinstall' Windows-py3.8: @@ -103,18 +92,11 @@ jobs: buildToxEnv: 'build-py37' testWheelInstallEnv: 'wheelinstall' - Windows-py3.6: + Windows-py3.7-min-req: imageName: 'vs2017-win2016' - pythonVersion: '3.6' - testToxEnv: 'py36' - buildToxEnv: 'build-py36' - testWheelInstallEnv: 'wheelinstall' - - Windows-py3.6-min-req: - imageName: 'vs2017-win2016' - pythonVersion: '3.6' - testToxEnv: 'py36-min-req' - buildToxEnv: 'build-py36-min-req' + pythonVersion: '3.7' + testToxEnv: 'py37-min-req' + buildToxEnv: 'build-py37-min-req' testWheelInstallEnv: 'wheelinstall' pool: diff --git a/azure-pipelines.yml b/azure-pipelines.yml index b43eeb0a4..a720e78bd 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -8,39 +8,38 @@ jobs: strategy: matrix: - macOS-py3.8: + macOS-py3.9: imageName: 'macos-10.15' - pythonVersion: '3.8' - testToxEnv: 'py38' - buildToxEnv: 'build-py38' + pythonVersion: '3.9' + testToxEnv: 'py39' + buildToxEnv: 'build-py39' testWheelInstallEnv: 'wheelinstall' - macOS-py3.6-min-req: + macOS-py3.7-min-req: imageName: 'macos-10.15' - pythonVersion: '3.6' - testToxEnv: 'py36-min-req' - buildToxEnv: 'build-py36-min-req' + pythonVersion: '3.7' + testToxEnv: 'py37-min-req' + buildToxEnv: 'build-py37-min-req' testWheelInstallEnv: 'wheelinstall' - Windows-py3.8: + Windows-py3.9: imageName: 'vs2017-win2016' - pythonVersion: '3.8' - testToxEnv: 'py38' - buildToxEnv: 'build-py38' + pythonVersion: '3.9' + testToxEnv: 'py39' + buildToxEnv: 'build-py39' testWheelInstallEnv: 'wheelinstall' - Windows-py3.6-min-req: + Windows-py3.7-min-req: imageName: 'vs2017-win2016' - pythonVersion: '3.6' - testToxEnv: 'py36-min-req' - buildToxEnv: 'build-py36-min-req' + pythonVersion: '3.7' + testToxEnv: 'py37-min-req' + buildToxEnv: 'build-py37-min-req' testWheelInstallEnv: 'wheelinstall' pool: vmImage: $(imageName) steps: - - checkout: self submodules: true diff --git a/docs/Makefile b/docs/Makefile index ece536eae..4cb0b9d41 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -45,7 +45,7 @@ help: @echo " apidoc to build RST from source code" clean: - -rm -rf $(BUILDDIR)/* $(RSTDIR)/$(PKGNAME)*.rst + -rm -rf $(BUILDDIR)/* $(RSTDIR)/$(PKGNAME)*.rst $(RSTDIR)/tutorials html: $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html diff --git a/docs/gallery/domain/brain_observatory.py b/docs/gallery/domain/brain_observatory.py index 6347864ba..11e490251 100644 --- a/docs/gallery/domain/brain_observatory.py +++ b/docs/gallery/domain/brain_observatory.py @@ -16,6 +16,7 @@ # .. raw:: html # :url: https://gist.githubusercontent.com/nicain/82e6b3d8f9ff5b85ef01a582e41e2389/raw/ +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_allenbrainobservatory.png' from datetime import datetime from dateutil.tz import tzlocal @@ -142,9 +143,9 @@ ) ######################################## -# The Allen Institute does not include the raw imaging signal, as this data would make the file too large. Instead, these -# data are preprocessed, and a dF/F fluorescence signal extracted for each region-of-interest (ROI). To store the chain -# of computations necessary to describe this data processing pipeline, pynwb provides a "processing module" with +# The Allen Institute does not include the raw imaging signal, as this data would make the file too large. Instead, +# these data are preprocessed, and a dF/F fluorescence signal extracted for each region-of-interest (ROI). To store the +# chain of computations necessary to describe this data processing pipeline, pynwb provides a "processing module" with # interfaces that simplify and standardize the process of adding the steps in this provenance chain to the file: ophys_module = nwbfile.create_processing_module( name='ophys_module', diff --git a/docs/gallery/domain/ecephys.py b/docs/gallery/domain/ecephys.py index fd9bcf931..54f493ddf 100644 --- a/docs/gallery/domain/ecephys.py +++ b/docs/gallery/domain/ecephys.py @@ -5,13 +5,8 @@ Extracellular electrophysiology data ============================================ -The following examples will reference variables that may not be defined within the block they are used in. For -clarity, we define them here: ''' - -import numpy as np - ####################### # Creating and Writing NWB files # ------------------------------ @@ -19,6 +14,9 @@ # When creating a NWB file, the first step is to create the :py:class:`~pynwb.file.NWBFile`. The first # argument is the name of the NWB file, and the second argument is a brief description of the dataset. +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_ecephys.png' + +import numpy as np from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile diff --git a/docs/gallery/domain/icephys.py b/docs/gallery/domain/icephys.py index 9cad32b4a..e096edac8 100644 --- a/docs/gallery/domain/icephys.py +++ b/docs/gallery/domain/icephys.py @@ -2,11 +2,17 @@ ''' .. _icephys_tutorial: -Intracellular electrophysiology data -============================================ +Intracellular electrophysiology data using SweepTable +===================================================== -The following examples will reference variables that may not be defined within the block they are used in. For -clarity, we define them here: +The following tutorial describes storage of intracellular electrophysiology data in NWB using the +SweepTable to manage recordings. + +.. note:: + The use of SweepTable has been deprecated as of PyNWB >v1.4 in favor of the new hierarchical + intracellular electrophysiology metadata tables to allow for a more complete description of + intracellular electrophysiology experiments. See the :doc:`Intracellular electrophysiology ` + tutorial for details. ''' ####################### @@ -16,6 +22,7 @@ # When creating a NWB file, the first step is to create the :py:class:`~pynwb.file.NWBFile`. The first # argument is is a brief description of the dataset. +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_icephys_sweeptable.png' from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile @@ -76,7 +83,7 @@ ccss = CurrentClampStimulusSeries( name="ccss", data=[1, 2, 3, 4, 5], starting_time=123.6, rate=10e3, electrode=elec, gain=0.02, sweep_number=0) -nwbfile.add_stimulus(ccss) +nwbfile.add_stimulus(ccss, use_sweep_table=True) ####################### # We now add another stimulus series but from a different sweep. TimeSeries @@ -87,7 +94,7 @@ vcss = VoltageClampStimulusSeries( name="vcss", data=[2, 3, 4, 5, 6], starting_time=234.5, rate=10e3, electrode=elec, gain=0.03, sweep_number=1) -nwbfile.add_stimulus(vcss) +nwbfile.add_stimulus(vcss, use_sweep_table=True) ####################### # Here, we will use :py:class:`~pynwb.icephys.CurrentClampSeries` to store current clamp @@ -102,7 +109,7 @@ electrode=elec, gain=0.02, bias_current=1e-12, bridge_balance=70e6, capacitance_compensation=1e-12, sweep_number=0) -nwbfile.add_acquisition(ccs) +nwbfile.add_acquisition(ccs, use_sweep_table=True) ####################### # And voltage clamp data from the second sweep using @@ -116,7 +123,7 @@ electrode=elec, gain=0.02, capacitance_slow=100e-12, resistance_comp_correction=70.0, sweep_number=1) -nwbfile.add_acquisition(vcs) +nwbfile.add_acquisition(vcs, use_sweep_table=True) #################### # .. _icephys_writing: @@ -183,7 +190,8 @@ # PatchClampSeries which belongs to a certain sweep number via # :py:meth:`~pynwb.icephys.SweepTable.get_series`. # -# The following call will return the voltage clamp data, two timeseries +# The following call will return the voltage clamp data, of two timeseries # consisting of acquisition and stimulus, from sweep 1. series = nwbfile.sweep_table.get_series(1) +print("hello world") diff --git a/docs/gallery/domain/ophys.py b/docs/gallery/domain/ophys.py index dc9ace87c..ed1a1aecb 100644 --- a/docs/gallery/domain/ophys.py +++ b/docs/gallery/domain/ophys.py @@ -17,6 +17,7 @@ clarity, we define them here: ''' +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_ophys.png' from datetime import datetime from dateutil.tz import tzlocal @@ -133,6 +134,10 @@ #################### +# .. tip:: +# You can also store dF/F data using the :py:class:`~pynwb.ophys.DfOverF` class, which works the same way as +# :py:class:`~pynwb.ophys.Fluorescence`. +# # Because this data stores information about specific ROIs, you will need to provide a reference to the ROIs # that you will be storing data for. This is done using a :py:class:`~pynwb.core.DynamicTableRegion`, which can be # created with :py:func:`~pynwb.ophys.PlaneSegmentation.create_roi_table_region`. @@ -227,8 +232,6 @@ # one's life much simpler. NWB currently does not have the ability to read and parse native image formats. It # is up to downstream users to read these file formats. # -# .. [#] You can also store dF/F data using the :py:class:`~pynwb.ophys.DfOverF` class. -# # .. [#] Neurodata sets can be *very* large, so individual components of the dataset are only loaded into memory when # you request them. This functionality is only possible if closing of the :py:class:`~pynwb.NWBHDF5IO` # object is handled by the user. diff --git a/docs/gallery/domain/plot_icephys.py b/docs/gallery/domain/plot_icephys.py new file mode 100644 index 000000000..b1adcc247 --- /dev/null +++ b/docs/gallery/domain/plot_icephys.py @@ -0,0 +1,632 @@ +# -*- coding: utf-8 -*- +''' +.. _icephys_tutorial_new: + +Intracellular electrophysiology +================================================================== + +The following tutorial describes storage of intracellular electrophysiology data in NWB. +NWB supports storage of the time series describing the stimulus and response, information +about the electrode and device used, as well as metadata about the organization of the +experiment. + +.. note:: For a video tutorial on intracellular electrophysiology in NWB see also the + `Intracellular electrophysiology basics in NWB `_ + and `Intracellular electrophysiology structured metadata in NWB `_ + tutorials as part of the `NWB Course at the INCF Training Space `_. + + +To describe the organization of intracellular experiments the metadata is organized +hierarchically in a sequence of tables. All of the tables are so-called DynamicTables +enabling users to add columns for custom metadata. + +.. figure:: ../../figures/plot_icephys_table_hierarchy.png + :width: 700 + :alt: Intracellular electrophysiology metadata table hierarchy + + Illustration of the hierarchy of metadata tables used to describe the organization of + intracellular electrophysiology experiments. + +- :py:class:`~pynwb.icephys.IntracellularRecordingsTable` relates electrode, stimulus + and response pairs and describes metadata specific to individual recordings. +- :py:class:`~pynwb.icephys.SimultaneousRecordingsTable` groups intracellular + recordings from the :py:class:`~pynwb.icephys.IntracellularRecordingsTable` + together that were recorded simultaneously from different electrodes and/or cells + and describes metadata that is constant across the simultaneous recordings. + In practice a simultaneous recording is often also referred to as a sweep. +- :py:class:`~pynwb.icephys.SequentialRecordingsTable` groups simultaneously + recorded intracellular recordings from the + :py:class:`~pynwb.icephys.SimultaneousRecordingsTable` together and describes + metadata that is constant across the simultaneous recordings. In practice a + sequential recording is often also referred to as a sweep sequence. A common + use of sequential recordings is to group together simultaneous recordings + where a sequence of stimuli of the same type with varying parameters + have been presented in a sequence (e.g., a sequence of square waveforms with + varying amplitude). +- :py:class:`~pynwb.icephys.RepetitionsTable` groups sequential recordings from + the :py:class:`~pynwb.icephys.SequentialRecordingsTable`. In practice a + repetition is often also referred to a run. A typical use of the + py:class:`~pynwb.icephys.RepetitionsTable` is to group sets of different stimuli + that are applied in sequence that may be repeated. +- :py:class:`~pynwb.icephys.ExperimentalConditionsTable` groups repetitions of + intracellular recording from the :py:class:`~pynwb.icephys.RepetitionsTable` + together that belong to the same experimental conditions. +''' + +####################### +# Imports used in the tutorial +# ------------------------------ + +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_icephys.png' +# Standard Python imports +from datetime import datetime +from dateutil.tz import tzlocal +import numpy as np +import pandas +pandas.set_option("display.max_colwidth", 30) # Set Pandas rendering option to avoid very wide cells + +# Import main NWB file class +from pynwb import NWBFile +# Import icephys TimeSeries types used +from pynwb.icephys import VoltageClampStimulusSeries, VoltageClampSeries +# Import I/O class used for reading and writing NWB files +from pynwb import NWBHDF5IO +# Import additional core datatypes used in the example +from pynwb.core import DynamicTable, VectorData + +####################### +# A brief example script +# ------------------------------ +# +# The following shows a brief example script, providing a brief overview of the +# main steps to create and NWB icephys file. A more detailed dicussion of the +# various steps is then provided afterwards. To avoid collisions between this +# example script and the more detailed discussion we prefix +# all variables in the example script with ``ex_``. + +# Create an ICEphysFile +ex_nwbfile = NWBFile(session_description='my first recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal())) + +# Add a device +ex_device = ex_nwbfile.create_device(name='Heka ITC-1600') + +# Add an intracellular electrode +ex_electrode = ex_nwbfile.create_icephys_electrode( + name="elec0", + description='a mock intracellular electrode', + device=ex_device) + +# Create an ic-ephys stimulus +ex_stimulus = VoltageClampStimulusSeries(name="stimulus", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=ex_electrode, + gain=0.02) + +# Create an ic-response +ex_response = VoltageClampSeries(name='response', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=ex_electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0) + +# (A) Add an intracellular recording to the file +# NOTE: We can optionally define time-ranges for the stimulus/response via +# the corresponding option _start_index and _index_count parameters. +# NOTE: It is allowed to add a recording with just a stimulus or a response +# NOTE: We can add custom columns to any of our tables in steps (A)-(E) +ex_ir_index = ex_nwbfile.add_intracellular_recording(electrode=ex_electrode, + stimulus=ex_stimulus, + response=ex_response) + +# (B) Add a list of sweeps to the sweeps table +ex_sweep_index = ex_nwbfile.add_icephys_simultaneous_recording(recordings=[ex_ir_index, ]) + +# (C) Add a list of simultaneous recordings table indices as a sequential recording +ex_sequence_index = ex_nwbfile.add_icephys_sequential_recording( + simultaneous_recordings=[ex_sweep_index, ], + stimulus_type='square') + +# (D) Add a list of sequential recordings table indices as a repetition +run_index = ex_nwbfile.add_icephys_repetition(sequential_recordings=[ex_sequence_index, ]) + +# (E) Add a list of repetition table indices as a experimental condition +ex_nwbfile.add_icephys_experimental_condition(repetitions=[run_index, ]) + +# Write our test file +ex_testpath = "ex_test_icephys_file.h5" +with NWBHDF5IO(ex_testpath, 'w') as io: + io.write(ex_nwbfile) + +# Read the data back in +with NWBHDF5IO(ex_testpath, 'r') as io: + infile = io.read() + +# Optionally plot the organization of our example NWB file +try: + from hdmf_docutils.doctools.render import NXGraphHierarchyDescription, HierarchyDescription + import matplotlib.pyplot as plt + ex_file_hierarchy = HierarchyDescription.from_hdf5(ex_testpath) + ex_file_graph = NXGraphHierarchyDescription(ex_file_hierarchy) + ex_fig = ex_file_graph.draw(show_plot=False, figsize=(12, 16), label_offset=(0.0, 0.0065), label_font_size=10) + plt.show() +except ImportError: # ignore in case hdmf_docutils is not installed + pass + +####################### +# Now that we have seen a brief example, we are going to start from the beginning and +# go through each of the steps in more detail in the following sections. + + +####################### +# Creating an icephys NWB file +# ------------------------------ +# +# When creating an NWB file, the first step is to create the :py:class:`~pynwb.file.NWBFile`. The first +# argument is is a brief description of the dataset. + +# Create the file +nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + +####################### +# Device metadata +# ^^^^^^^^^^^^^^^ +# +# Device metadata is represented by :py:class:`~pynwb.device.Device` objects. +# To create a device, you can use the :py:class:`~pynwb.device.Device` instance method +# :py:meth:`~pynwb.file.NWBFile.create_device`. + +device = nwbfile.create_device(name='Heka ITC-1600') + +####################### +# Electrode metadata +# ^^^^^^^^^^^^^^^^^^ +# +# Intracellular electrode metadata is represented by :py:class:`~pynwb.icephys.IntracellularElectrode` objects. +# To create an electrode group, you can use the :py:class:`~pynwb.file.NWBFile` instance method +# :py:meth:`~pynwb.file.NWBFile.create_icephys_electrode`. + +electrode = nwbfile.create_icephys_electrode(name="elec0", + description='a mock intracellular electrode', + device=device) + +####################### +# Stimulus and response data +# ^^^^^^^^^^^^^^^^^^^^^^^^^^ +# +# Intracellular stimulus and response data are represented with subclasses of +# :py:class:`~pynwb.icephys.PatchClampSeries`. A stimulus is described by a +# time series representing voltage or current stimulation with a particular +# set of parameters. There are two classes for representing stimulus data: +# +# - :py:class:`~pynwb.icephys.VoltageClampStimulusSeries` +# - :py:class:`~pynwb.icephys.CurrentClampStimulusSeries` +# +# The response is then described by a time series representing voltage or current +# recorded from a single cell using a single intracellular electrode via one of +# the following classes: +# +# - :py:class:`~pynwb.icephys.VoltageClampSeries` +# - :py:class:`~pynwb.icephys.CurrentClampSeries` +# - :py:class:`~pynwb.icephys.IZeroClampSeries` +# +# Below we create a simple example stimulus/response recording data pair. + +# Create an example icephys stimulus. +stimulus = VoltageClampStimulusSeries(name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=electrode, + gain=0.02, + sweep_number=np.uint64(15)) + +# Create and icephys response +response = VoltageClampSeries(name='vcs', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0, + sweep_number=np.uint64(15)) + +####################### +# Adding an intracellular recording +# --------------------------------- +# +# As mentioned earlier, intracellular recordings are organized in the +# :py:class:`~pynwb.icephys.IntracellularRecordingsTable` which relates electrode, stimulus +# and response pairs and describes metadata specific to individual recordings. +# +# .. figure:: ../../figures/plot_icephys_intracellular_recordings_table.png +# :width: 700 +# :alt: IntracellularRecordingsTabl +# +# Illustration of the structure of the IntracellularRecordingsTable +# +# We can add an intracellular recording to the file via :py:meth:`~pynwb.file.NWBFile.add_intracellular_recording`. +# The function will record the data in the :py:class:`~pynwb.icephys.IntracellularRecordingsTable` +# and add the given electrode, stimulus, or response to the NWBFile object if necessary. +# Any time we add a row to one of our tables, the corresponding add function (here +# :py:meth:`~pynwb.file.NWBFile.add_intracellular_recording`) returns the integer index of the +# newly created row. The ``rowindex`` is used in subsequent tables that reference rows in our table. + +rowindex = nwbfile.add_intracellular_recording(electrode=electrode, + stimulus=stimulus, + response=response, + id=10) + +####################### +# .. note:: All of the above mentioned metadata tables are optional and are created automatically +# by the :py:class:`~pynwb.file.NWBFile` class the first time data is being +# added to a table via the corresponding add functions. +# +# .. note:: Since :py:meth:`~pynwb.file.NWBFile.add_intracellular_recording` can automatically add +# the objects to the NWBFile we do not need to separately call +# :py:meth:`~pynwb.file.NWBFile.add_stimulus` and :py:meth:`~pynwb.file.NWBFile.add_acquistion` +# to add our stimulus and response, but it is still fine to do so. +# +# .. note:: The ``id`` parameter in the call is optional and if the ``id`` is omitted then PyNWB will +# automatically number recordings in sequences (i.e., id is the same as the rowindex) +# +# .. note:: The IntracellularRecordigns, SimultaneousRecordings, SequentialRecordingsTable, +# RepetitionsTable and ExperimentalConditionsTable tables all enforce unique ids +# when adding rows. I.e., adding an intracellular recording with the same id twice +# results in a ValueError. +# + +####################### +# .. note:: We may optionally also specify the relevant time range for a stimulus and/or response as part of +# the intracellular_recording. This is useful, e.g., in case where the recording of the stimulus +# and response do not align (e.g., in case that recording of the response started before +# the recording of the stimulus). + +rowindex2 = nwbfile.add_intracellular_recording(electrode=electrode, + stimulus=stimulus, + stimulus_start_index=1, + stimulus_index_count=3, + response=response, + response_start_index=2, + response_index_count=3, + id=11) + +####################### +# .. note:: A recording may optionally also consist of just an electrode and stimulus or electrode +# and response, but at least one of stimulus or response are required. If either stimulus or response +# are missing, then the stimulus and response are internally set ot the same TimeSeries and the +# start_index and index_count for the missing parameter are set to -1 + +rowindex3 = nwbfile.add_intracellular_recording(electrode=electrode, + response=response, + id=12) + +####################### +# .. warning:: For brevity we reused in the above example the same response and stimulus in +# all rows of the intracellular_recordings. While this is allowed, in most practical +# cases the stimulus and response will change between intracellular_recordings. + +####################### +# Adding custom columns to the intracellular recordings table +# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +# +# We can add a column to the main intracellular recordings table as follows + +nwbfile.intracellular_recordings.add_column( + name='recording_tag', + data=['A1', 'A2', 'A3'], + description='String with a recording tag') + +####################### +# Similarly, we can also add custom columns to any of the subcategory tables, i.e., +# the electrodes, stimuli, and responses tables. All we need to do is indicate +# the name of the category we want to add the column to. +# + +nwbfile.intracellular_recordings.add_column( + name='voltage_threshold', + data=[0.1, 0.12, 0.13], + description='Just and example filter on the electrode', + category='electrodes') + +####################### +# The :py:class:`~pynwb.icephys.IntracellularRecordingsTable` table is not just a ``DynamicTable`` +# but an ``AlignedDynamicTable`. The ``AlignedDynamicTable` type is itself a ``DynamicTable`` +# that may contain an arbitrary number of additional ``DynamicTable``, each of which defines +# a "category". This is similar to a table with "sub-headings". In the case of the +# :py:class:`~pynwb.icephys.IntracellularRecordingsTable` we have three predefined categories, +# i.e., electrodes, stimuli, and responses. We can now also dynamically add new categories to +# the table. As each category corresponds to a DynamicTable this means we have to create a +# new DynamicTable and add it to our table. + +# Create a new DynamicTable for our category +lab_category = DynamicTable( + name='recording_lab_data', + description='category table for lab-specific recording metadata', + colnames=['location', ], + columns=[VectorData(name='location', + data=['Mordor', 'Gondor', 'Rohan'], + description='Recording location in Middle Earth')]) +# Add the table as a new category to our intracellular_recordings +nwbfile.intracellular_recordings.add_category(category=lab_category) +# Note, the name of the category is name of the table, i.e. recording_lab_data + +####################### +# .. note:: In an ``AlignedDynamicTable`` all category tables MUST align with the master table, +# i.e., all tables must have the same number of rows and rows are expected to +# correspond to each other by index + + +####################### +# Add a simultaneous recording +# --------------------------------- +# +# Before adding a simultaneous recording, we will take a brief discourse to illustrate +# how we can add custom columns to tables before and after we have populated the table with data +# +# Define a custom column for a simultaneous recording before populating the table +# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +# +# Before we add a simultaneous recording, let's create a custom data column in our +# :py:class:`~pynwb.icephys.SimultaneousRecordingsTable`. We can create columns at the +# beginning (i.e., before we populate the table with rows/data) or we can add columns +# after we have already populated the table with rows. Here we will show the former. +# For this, we first need to get access to our table. + +print(nwbfile.icephys_simultaneous_recordings) + +####################### +# The :py:class:`~pynwb.icephys.SimultaneousRecordingsTable` is optional, and since we have +# not populated it with any data yet, we can see that the table does not actually exist yet. +# In order to make sure the table is being created we can use +# :py:meth:`~pynwb.file.NWBFile.get_icephys_simultaneous_recordings` instead, which ensures +# that the table is being created if it does not exist yet. + +icephys_simultaneous_recordings = nwbfile.get_icephys_simultaneous_recordings() +icephys_simultaneous_recordings.add_column(name='simultaneous_recording_tag', + description='A custom tag for simultaneous_recordings') +print(icephys_simultaneous_recordings.colnames) + +####################### +# As we can see, we now have succesfully created a new custom column +# +# .. note:: The same process applies to all our other tables as well. Here we use the +# corresponding :py:meth:`~pynwb.file.NWBFile.get_intracelluar_recordings`, +# :py:meth:`~pynwb.file.NWBFile.get_icephys_sequential_recordings`, +# :py:meth:`~pynwb.file.NWBFile.get_icephys_repetitions`, and +# :py:meth:`~pynwb.file.NWBFile.get_icephys_conditions` functions intead. +# In general, we can always use the get functions instead of accessing the property +# of the file. +# + +####################### +# Add a simultaneous recording +# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +# +# Add a single simultaneous recording consisting of a set of intracellular recordings. +# Again, setting the id for a simultaneous recording is optional. The recordings +# argument of the :py:meth:`~pynwb.file.NWBFile.add_simultaneous_recording` function +# here is simply a list of ints with the indices of the corresponding rows in +# the :py:class:`~pynwb.icephys.IntracellularRecordingsTable` +# +# .. note:: Since we created our custom ``simultaneous_recording_tag column`` earlier +# we now also need to populate this custom field for every row we add to +# the :py:class:`~pynwb.icephys.SimultaneousRecordingsTable`. +# + +rowindex = nwbfile.add_icephys_simultaneous_recording(recordings=[rowindex, rowindex2, rowindex3], + id=12, + simultaneous_recording_tag='LabTag1') + +####################### +# .. note:: The ``recordings`` argument is the list of indices of the rows in the +# :py:class:`~pynwb.icephys.IntracellularRecordingsTable` that we want +# to reference. The indices are determined by the order in which we +# added the elements to the table. If we don't know the row indicies, +# but only the ids of the relevant intracellular recordings, then +# we can search for them as follows: + +temp_row_indicies = (nwbfile.intracellular_recordings.id == [10, 11]) +print(temp_row_indicies) + +####################### +# .. note:: The same is true for our other tables as well, i.e., referencing is +# done always by indices of rows (NOT ids). If we only know ids then we +# can search for them in the same manner on the other tables as well, +# e.g,. via ``nwbfile.simultaneous_recordings.id == 15``. In the search +# we can use a list of integer ids or a single int. + +####################### +# Define a custom column for a simultaneous recording after adding rows +# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +# +# Depending on the lab workflow, it may be useful to add complete columns to a table +# after we have already populated the table with rows. We can do this the same way as +# before, only now we need to provide a data array to populate the values for +# the existing rows. E.g.: + +nwbfile.icephys_simultaneous_recordings.add_column( + name='simultaneous_recording_type', + description='Description of the type of simultaneous_recording', + data=['SimultaneousRecordingType1', ]) + +####################### +# Add a sequential recording +# -------------------------- +# +# Add a single sequential recording consisting of a set of simultaneous recordings. +# Again, setting the id for a sequential recording is optional. Also this table is +# optional and will be created automatically by NWBFile. The ``simultaneous_recordings`` +# argument of the :py:meth:`~pynwb.file.NWBFile.add_sequential_recording` function +# here is simply a list of ints with the indices of the corresponding rows in +# the :py:class:`~pynwb.icephys.SimultaneousRecordingsTable`. + +rowindex = nwbfile.add_icephys_sequential_recording( + simultaneous_recordings=[0], + stimulus_type='square', + id=15) + +####################### +# Add a repetition +# ---------------- +# +# Add a single repetition consisting of a set of sequential recordings. Again, setting +# the id for a repetition is optional. Also this table is optional and will be created +# automatically by NWBFile. The ``sequential_recordings argument`` of the +# :py:meth:`~pynwb.file.NWBFile.add_sequential_recording` function here is simply +# a list of ints with the indices of the corresponding rows in +# the :py:class:`~pynwb.icephys.SequentialRecordingsTable`. + +rowindex = nwbfile.add_icephys_repetition(sequential_recordings=[0], id=17) + + +####################### +# Add an experimental condition +# ----------------------------- +# +# Add a single experimental condition consisting of a set of repetitions. Again, +# setting the id for a condition is optional. Also this table is optional and +# will be created automatically by NWBFile. The ``repetitions`` argument of +# the :py:meth:`~pynwb.file.NWBFile.add_icephys_condition` function again is +# simply a list of ints with the indices of the correspondingto rows in the +# :py:class:`~pynwb.icephys.RepetitionsTable`. + +rowindex = nwbfile.add_icephys_experimental_condition(repetitions=[0], id=19) + +####################### +# As mentioned earlier, to add additonal columns to any of the tables, we can +# use the ``.add_column`` function on the corresponding table after they have +# been created. + +nwbfile.icephys_experimental_conditions.add_column( + name='tag', + data=np.arange(1), + description='integer tag for a experimental condition') + +####################### +# When we add new items then we now also need to set the values for the new column, e.g.: + +rowindex = nwbfile.add_icephys_experimental_condition( + repetitions=[0], + id=21, + tag=3) + +####################### +# Read/write the NWBFile +# ----------------------------- +# + +# Write our test file +testpath = "test_icephys_file.h5" +with NWBHDF5IO(testpath, 'w') as io: + io.write(nwbfile) + +# Read the data back in +with NWBHDF5IO(testpath, 'r') as io: + infile = io.read() + + +####################### +# Accessing the tables +# ----------------------------- +# +# All of the icephys metadata tables are available as attributes on the NWBFile object. +# Below we simply convert the tables to Pandas dataframes to show their content. + +nwbfile.intracellular_recordings.to_dataframe() + +####################### +# + +# optionally we can ignore the id columns of the category subtables +nwbfile.intracellular_recordings.to_dataframe(ignore_category_ids=True) + +####################### +# +nwbfile.icephys_simultaneous_recordings.to_dataframe() + +####################### +# + +nwbfile.icephys_sequential_recordings.to_dataframe() + +####################### +# + +nwbfile.icephys_repetitions.to_dataframe() + +####################### +# + +nwbfile.icephys_experimental_conditions.to_dataframe() + +####################### +# .. note:: As the tables in the hierarchy are optional, a given NWBFile may +# contain, e.g., a ``experimental_conditions`` table. To provide a consistent +# interface for users, and to avoid having to manually check which tables exist +# in a given file in order to find the "top-most" table in the hierarchy, +# NWBFile provides the ``:py:meth:`~pynwb.file.NWBFile.get_icephys_meta_parent_table`` +# function. With this we can retrieve the highest table in the icephys metadata +# hierarchy that actually exists in the file. For example: + +top_table = nwbfile.get_icephys_meta_parent_table() +print(top_table.neurodata_type) + + +####################### +# Validate data +# ^^^^^^^^^^^^^ +# +# This section is primarily for internal testing purpose to validate that the roundtrip +# of the data (i.e., generate --> write --> read) produces the correct results. + +# Read the data back in +with NWBHDF5IO(testpath, 'r') as io: + infile = io.read() + + # assert intracellular_recordings + assert np.all(infile.intracellular_recordings.id[:] == nwbfile.intracellular_recordings.id[:]) + + # Assert that the ids and the VectorData, VectorIndex, and table target of the recordings column of the Sweeps table are correct + assert np.all(infile.icephys_simultaneous_recordings.id[:] == nwbfile.icephys_simultaneous_recordings.id[:]) + assert np.all(infile.icephys_simultaneous_recordings['recordings'].target.data[:] == nwbfile.icephys_simultaneous_recordings['recordings'].target.data[:]) + assert np.all(infile.icephys_simultaneous_recordings['recordings'].data[:] == nwbfile.icephys_simultaneous_recordings['recordings'].data[:]) + assert infile.icephys_simultaneous_recordings['recordings'].target.table.name == nwbfile.icephys_simultaneous_recordings['recordings'].target.table.name + + # Assert that the ids and the VectorData, VectorIndex, and table target of the simultaneous recordings column of the SweepSequences table are correct + assert np.all(infile.icephys_sequential_recordings.id[:] == nwbfile.icephys_sequential_recordings.id[:]) + assert np.all(infile.icephys_sequential_recordings['simultaneous_recordings'].target.data[:] == nwbfile.icephys_sequential_recordings['simultaneous_recordings'].target.data[:]) + assert np.all(infile.icephys_sequential_recordings['simultaneous_recordings'].data[:] == nwbfile.icephys_sequential_recordings['simultaneous_recordings'].data[:]) + assert infile.icephys_sequential_recordings['simultaneous_recordings'].target.table.name == nwbfile.icephys_sequential_recordings['simultaneous_recordings'].target.table.name + + # Assert that the ids and the VectorData, VectorIndex, and table target of the sequential_recordings column of the Repetitions table are correct + assert np.all(infile.icephys_repetitions.id[:] == nwbfile.icephys_repetitions.id[:]) + assert np.all(infile.icephys_repetitions['sequential_recordings'].target.data[:] == nwbfile.icephys_repetitions['sequential_recordings'].target.data[:]) + assert np.all(infile.icephys_repetitions['sequential_recordings'] .data[:] == nwbfile.icephys_repetitions['sequential_recordings'].data[:]) + assert infile.icephys_repetitions['sequential_recordings'].target.table.name == nwbfile.icephys_repetitions['sequential_recordings'].target.table.name + + # Assert that the ids and the VectorData, VectorIndex, and table target of the repetitions column of the Conditions table are correct + assert np.all(infile.icephys_experimental_conditions.id[:] == nwbfile.icephys_experimental_conditions.id[:]) + assert np.all(infile.icephys_experimental_conditions['repetitions'].target.data[:] == nwbfile.icephys_experimental_conditions['repetitions'].target.data[:]) + assert np.all(infile.icephys_experimental_conditions['repetitions'] .data[:] == nwbfile.icephys_experimental_conditions['repetitions'].data[:]) + assert infile.icephys_experimental_conditions['repetitions'].target.table.name == nwbfile.icephys_experimental_conditions['repetitions'].target.table.name + assert np.all(infile.icephys_experimental_conditions['tag'][:] == nwbfile.icephys_experimental_conditions['tag'][:]) diff --git a/docs/gallery/general/add_remove_containers.py b/docs/gallery/general/add_remove_containers.py index b03f3dd4f..33c23cf53 100644 --- a/docs/gallery/general/add_remove_containers.py +++ b/docs/gallery/general/add_remove_containers.py @@ -22,6 +22,7 @@ # # For example: +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_add_remove_containers.png' from pynwb import NWBFile, NWBHDF5IO, TimeSeries import datetime import numpy as np diff --git a/docs/gallery/general/advanced_hdf5_io.py b/docs/gallery/general/advanced_hdf5_io.py index f2d72d406..c4092b416 100644 --- a/docs/gallery/general/advanced_hdf5_io.py +++ b/docs/gallery/general/advanced_hdf5_io.py @@ -18,6 +18,7 @@ # Before we get started, lets create an NWBFile for testing so that we can add our data to it. # +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_advnaced_hdf5_io.png' from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile diff --git a/docs/gallery/general/extensions.py b/docs/gallery/general/extensions.py index c87d291c0..027d07644 100644 --- a/docs/gallery/general/extensions.py +++ b/docs/gallery/general/extensions.py @@ -30,6 +30,7 @@ # to this namespace. Finally, # it calls :py:meth:`~hdmf.spec.write.NamespaceBuilder.export` to save the extensions to disk for downstream use. +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_extensions.png' from pynwb.spec import NWBNamespaceBuilder, NWBGroupSpec, NWBAttributeSpec ns_path = "mylab.namespace.yaml" diff --git a/docs/gallery/general/file.py b/docs/gallery/general/file.py index 288dceecb..615898c0e 100644 --- a/docs/gallery/general/file.py +++ b/docs/gallery/general/file.py @@ -13,8 +13,8 @@ # The NWB file # ------------ # -# +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_file.png' from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile @@ -294,25 +294,13 @@ nwbfile.processing['behavior'].add(position) #################### -# .. _basic_epochs: -# -# Epochs -# ------ +# Time Intervals +# -------------- # -# Epochs can be added to an NWB file using the method :py:meth:`~pynwb.file.NWBFile.add_epoch`. -# The first and second arguments are the start time and stop times, respectively. -# The third argument is one or more tags for labeling the epoch, and the fifth argument is a -# list of all the :py:class:`~pynwb.base.TimeSeries` that the epoch applies -# to. - -nwbfile.add_epoch(2.0, 4.0, ['first', 'example'], [test_ts, ]) -nwbfile.add_epoch(6.0, 8.0, ['second', 'example'], [test_ts, ]) - -#################### # .. _basic_trials: # # Trials -# ------ +# ~~~~~~~~~~~~~~~~~~~~~~ # # Trials can be added to an NWB file using the methods :py:meth:`~pynwb.file.NWBFile.add_trial` # and :py:meth:`~pynwb.file.NWBFile.add_trial_column`. Together, these methods maintains a @@ -347,6 +335,42 @@ # 1 3.0 5.0 ocean # 2 6.0 8.0 desert # +# .. _basic_epochs: +# +# Epochs +# ~~~~~~~~~~~~~~~~~~~~~~ +# +# Epochs can be added to an NWB file using the method :py:meth:`~pynwb.file.NWBFile.add_epoch`. +# The first and second arguments are the start time and stop times, respectively. +# The third argument is one or more tags for labeling the epoch, and the fourth argument is a +# list of all the :py:class:`~pynwb.base.TimeSeries` that the epoch applies +# to. + +nwbfile.add_epoch(2.0, 4.0, ['first', 'example'], [test_ts, ]) +nwbfile.add_epoch(6.0, 8.0, ['second', 'example'], [test_ts, ]) + +#################### +# Other time intervals +# ~~~~~~~~~~~~~~~~~~~~~~ +# Both ``epochs`` and ``trials`` are of of data type :py:class:`~pynwb.epoch.TimeIntervals`, which is a type of +# ``DynamicTable`` for storing information about time intervals. ``"epochs"`` and ``"trials"`` +# are the two default names for :py:class:`~pynwb.base.TimeIntervals` objects, but you can also add your own + +from pynwb.epoch import TimeIntervals + +sleep_stages = TimeIntervals( + name="sleep_stages", + description="intervals for each sleep stage as determined by EEG", +) + +sleep_stages.add_column(name="stage", description="stage of sleep") +sleep_stages.add_column(name="confidence", description="confidence in stage (0-1)") + +sleep_stages.add_row(start_time=0.3, stop_time=0.5, stage=1, confidence=.5) +sleep_stages.add_row(start_time=0.7, stop_time=0.9, stage=2, confidence=.99) +sleep_stages.add_row(start_time=1.3, stop_time=3.0, stage=3, confidence=0.7) + +nwbfile.add_time_intervals(sleep_stages) #################### # .. _basic_units: diff --git a/docs/gallery/general/iterative_write.py b/docs/gallery/general/iterative_write.py index e17a5e7b8..e9ea8a6c7 100644 --- a/docs/gallery/general/iterative_write.py +++ b/docs/gallery/general/iterative_write.py @@ -100,6 +100,7 @@ # simple helper function first to write a simple NWBFile containing a single timeseries to # avoid repetition of the same code and to allow us to focus on the important parts of this tutorial. +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_iterative_write.png' from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile, TimeSeries diff --git a/docs/gallery/general/linking_data.py b/docs/gallery/general/linking_data.py index 7f9bcbc8f..6c2e005e8 100644 --- a/docs/gallery/general/linking_data.py +++ b/docs/gallery/general/linking_data.py @@ -56,7 +56,7 @@ # In the following we are creating two :py:meth:`~pynwb.base.TimeSeries` each written to a separate file. # We then show how we can integrate these files into a single NWBFile. - +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_linking_data.png' from datetime import datetime from dateutil.tz import tzlocal from pynwb import NWBFile diff --git a/docs/gallery/general/object_id.py b/docs/gallery/general/object_id.py index f6b49a9dc..1c7c332b6 100644 --- a/docs/gallery/general/object_id.py +++ b/docs/gallery/general/object_id.py @@ -16,6 +16,7 @@ """ +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_objectid.png' from pynwb import NWBFile, TimeSeries from datetime import datetime from dateutil.tz import tzlocal diff --git a/docs/gallery/general/scratch.py b/docs/gallery/general/scratch.py index 2627a3cfe..306dbc65f 100644 --- a/docs/gallery/general/scratch.py +++ b/docs/gallery/general/scratch.py @@ -27,6 +27,7 @@ # To demonstrate linking and scratch space, lets assume we are starting with some acquired data. # +# sphinx_gallery_thumbnail_path = 'figures/gallery_thumbnails_scratch.png' from pynwb import NWBFile, TimeSeries, NWBHDF5IO from datetime import datetime from dateutil.tz import tzlocal diff --git a/docs/make.bat b/docs/make.bat index b50d10f3a..1e2a19ff4 100644 --- a/docs/make.bat +++ b/docs/make.bat @@ -50,6 +50,7 @@ if "%1" == "clean" ( for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i del /q /s %BUILDDIR%\* del /q %RSTDIR%\%PKGNAME%*.rst + rmdir /q /s %RSTDIR%\tutorials goto end ) diff --git a/docs/source/building_api.rst b/docs/source/building_api.rst deleted file mode 100644 index 5270e6b48..000000000 --- a/docs/source/building_api.rst +++ /dev/null @@ -1,193 +0,0 @@ -Building API classes -==================== - -After you have written an extension, you will need a Pythonic way to interact with the data model. To do this, -you will need to write some classes that represent the data you defined in your specification extensions. -The :py:mod:`pynwb.core` module has various tools to make it easier to write classes that behave like -the rest of the PyNWB API. - -The :py:mod:`pynwb.core` defines two base classes that represent the primitive structures supported by -the schema. :py:class:`~pynwb.core.NWBData` represents datasets and :py:class:`~pynwb.core.NWBContainer` -represents groups. Additionally, :py:mod:`pynwb.core` offers subclasses of these two classes for -writing classes that come with more functionality. - -``register_class`` ------------------- - -When defining a class that represents a *neurodata_type* (i.e. anything that has a *neurodata_type_def*) -from your extension, you can tell PyNWB which *neurodata_type* it represents using the function -:py:func:`~pynwb.register_class`. This class can be called on its own, or used as a class decorator. The -first argument should be the *neurodata_type* and the second argument should be the *namespace* name. - -The following example demonstrates how to register a class as the Python class representation of the -*neurodata_type* "MyContainer" from the *namespace* "my_ns". - -.. code-block:: python - - from pynwb import register_class - from pynwb.core import NWBContainer - - class MyContainer(NWBContainer): - ... - - regitser_class('MyContainer', 'my_ns', MyContainer) - - -Alternatively, you can use :py:func:`~pynwb.register_class` as a decorator. - -.. code-block:: python - - from pynwb import register_class - from pynwb.core import NWBContainer - - @regitser_class('MyContainer', 'my_ns') - class MyContainer(NWBContainer): - ... - -:py:func:`~pynwb.register_class` is used with :py:class:`~pynwb.core.NWBData` the same way it is used with -:py:class:`~pynwb.core.NWBContainer`. - - -``__nwbfields__`` ------------------ - -When subclassing :py:class:`~pynwb.core.NWBData` or :py:class:`~pynwb.core.NWBContainer`, you might want to -define some properties on your class. This can be done using the ``__nwbfields__`` class property. This -class property should be a tuple of strings that name the properties. Adding a property using this functionality -will create a property than can be set *only once*. - -For example, the following class definition will create the ``MyContainer`` class that has the properties ``foo`` -and ``bar``. - -.. code-block:: python - - from pynwb import register_class - from pynwb.core import NWBContainer - - - class MyContainer(NWBContainer): - - __nwbfields__ = ('foo', 'bar') - - ... - - -``NWBData`` ------------ - -:py:class:`~pynwb.core.NWBData` should be used to represent datasets with a *neurodata_type_def*. This section - will discuss the available :py:class:`~pynwb.core.NWBData` subclasses for representing common dataset specifications. - -``NWBTable`` -^^^^^^^^^^^^ - -If your specification extension contains a table definition i.e. a dataset with a compound data type, you should use -the :py:class:`~pynwb.core.NWBTable` class to represent this specification. Since :py:class:`~pynwb.core.NWBTable` -subclasses :py:class:`~pynwb.core.NWBData` you can still use ``__nwbfields__``. In addition, you can use the -``__columns__`` class property to specify the columns of the table. ``__columns__`` should be a list or a tuple of -:py:func:`~hdmf.utils.docval`-like dictionaries. - -The following example demonstrates how to define a table with the columns ``foo`` and ``bar`` that are of type -str and int, respectively. We also register the class as the representation of the *neurodata_type* "MyTable" -from the *namespace* "my_ns". - -.. code-block:: python - - from pynwb import register_class - from pynwb.core import NWBTable - - - @register_class('MyTable', 'my_ns') - class MyTable(NWBTable): - - __columns__ = [ - {'name': 'foo', 'type': str, 'doc': 'the foo column'}, - {'name': 'bar', 'type': int, 'doc': 'the bar column'}, - ] - - ... - -``NWBTableRegion`` -^^^^^^^^^^^^^^^^^^ - -:py:class:`~pynwb.core.NWBTableRegion` should be used to represent datasets that store a region reference. The constructor -for :py:class:`~pynwb.core.NWBTableRegion`. When subclassing this class, make sure you provide a way to pass in the required -arguments for the :py:class:`~pynwb.core.NWBTableRegion` constructor--the *name* of the dataset, the *table* that the region -applies to, and the *region* itself. - - -``NWBContainer`` ----------------- - -:py:class:`~pynwb.core.NWBContainer` -should be used to represent groups with a *neurodata_type_def*. This section -will discuss the available :py:class:`~pynwb.core.NWBContainer` subclasses for representing common group specifications. - -``NWBDataInterface`` -^^^^^^^^^^^^^^^^^^^^ - -The NWB schema users the neurodata type *NWBDataInterface* for specifying containers that contain data that is not -considered metadata. For example, *NWBDataInterface* is a parent neurodata type to *ElectricalSeries* data, -but not a parent to *ElectrodeGroup*. - -There are no requirements for using :py:class:`~pynwb.core.NWBDataInterface` in addition to those inherited from -:py:class:`~pynwb.core.NWBContainer`. - -``MultiContainerInterface`` -^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -Throughout the NWB schema, there are multiple *NWBDataInterface* specifications that include one or more or zero -or more of a certain neurodata type. For example, the *LFP* neurodata type contains one or more *ElectricalSeries*. -If your extension follows this pattern, you can use :py:class:`~pynwb.core.MultiContainerInterface` for defining -the representative class. - -:py:class:`~pynwb.core.MultiContainerInterface` provides a way of automatically generating setters, getters, and -properties for your class. These methods are autogenerated based on a configuration provided using the class property -``__clsconf__``. ``__clsconf__`` should be a dict or a list of dicts. A single dict should be used if your -specification contains a single neurodata type. A list of dicts should be used if your specification contains -multiple neurodata types that will exist as one or more or zero or more. The contents of the dict are described -in the following table. - -=========== =========================================================== ================ - Key Attribute Required? -=========== =========================================================== ================ -``type`` the type of the Container Yes -``attr`` the property name that holds the Containers Yes -``add`` the name of the method for adding a Container Yes -``create`` the name of the method for creating a Container No -``get`` the name of the method for getting a Container by name Yes -=========== =========================================================== ================ - - -The ``type`` key provides a way for the setters to check for type. The property under the name given by the. -``attr`` key will be a :py:class:`~pynwb.core.LabelledDict`. If your class uses a single dict, -a ``__getitem__`` method will be autogenerated for indexing into this :py:class:`~pynwb.core.LabelledDict`. -Finally, a constructor will also be autogenerated if you do not provide one in the class definition. - -The following code block demonstrates using :py:class:`~pynwb.core.MultiContainerInterface` to build a class -that represents the neurodata type "MyDataInterface" from the namespace "my_ns". It contains one or more containers -with neurodata type "MyContainer". - -.. code-block:: python - - from pynwb import register_class - from pynwb.core import MultiContainerInterface - - - @register_class("MyDataInterface", "my_ns") - class MyDataInterface(MultiContainerInterface): - - __clsconf__ = { - 'type': MyContainer, - 'attr': 'containers', - 'add': 'add_container', - 'create': 'create_container', - 'get': 'get_container', - } - ... - - -This class will have the methods ``add_container``, ``create_container``, and ``get_container``. It will also have -the property ``containers``. The ``add_container`` method will check to make sure that either an object of type -``MyContainer`` or a list/dict/tuple of objects of type ``MyContainer`` is passed in. ``create_container`` will -accept the exact same arguments that the ``MyContainer`` class constructor accepts. diff --git a/docs/source/conf.py b/docs/source/conf.py index 6cbe0e752..63923cff0 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -65,17 +65,16 @@ 'gallery_dirs': ['tutorials'], 'subsection_order': ExplicitOrder(['../gallery/general', '../gallery/domain']), 'backreferences_dir': 'gen_modules/backreferences', - 'download_section_examples': False, 'min_reported_time': 5 } intersphinx_mapping = { 'python': ('https://docs.python.org/3.8', None), - 'numpy': ('https://docs.scipy.org/doc/numpy/', None), + 'numpy': ('https://numpy.org/doc/stable/objects.inv', None), 'matplotlib': ('https://matplotlib.org', None), - 'h5py': ('http://docs.h5py.org/en/latest/', None), + 'h5py': ('https://docs.h5py.org/en/latest/', None), 'hdmf': ('https://hdmf.readthedocs.io/en/latest/', None), - 'pandas': ('http://pandas.pydata.org/pandas-docs/stable/', None) + 'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None) } # Add any paths that contain templates here, relative to this directory. @@ -93,7 +92,7 @@ # General information about the project. project = u'PyNWB' -copyright = u'2017-2020, Neurodata Without Borders' +copyright = u'2017-2021, Neurodata Without Borders' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the @@ -326,5 +325,5 @@ def skip(app, what, name, obj, skip, options): def setup(app): app.connect('builder-inited', run_apidoc) - app.add_stylesheet("theme_overrides.css") # overrides for wide tables in RTD theme + app.add_css_file("theme_overrides.css") # overrides for wide tables in RTD theme app.connect("autodoc-skip-member", skip) diff --git a/docs/source/extensions.rst b/docs/source/extensions.rst deleted file mode 100644 index 7799afa3a..000000000 --- a/docs/source/extensions.rst +++ /dev/null @@ -1,404 +0,0 @@ -.. _extending-nwb: - -Extending NWB -============= - -The following page will discuss how to extend NWB using PyNWB. - -.. note:: - - A simple example demonstrating the creation and use of a custom extension is available as part of the - tutorial :ref:`tutorial-extending-nwb`. - -.. _creating-extensions: - -Creating new Extensions ------------------------ - -The NWB specification is designed to be extended. Extension for the NWB format can be done so using classes provided in the :py:mod:`pynwb.spec` module. -The classes :py:class:`~pynwb.spec.NWBGroupSpec`, :py:class:`~pynwb.spec.NWBDatasetSpec`, :py:class:`~pynwb.spec.NWBAttributeSpec`, and :py:class:`~pynwb.spec.NWBLinkSpec` -can be used to define custom types. - -Attribute Specifications -^^^^^^^^^^^^^^^^^^^^^^^^ - -Specifying attributes is done with :py:class:`~pynwb.spec.NWBAttributeSpec`. - -.. code-block:: python - - from pynwb.spec import NWBAttributeSpec - - spec = NWBAttributeSpec('bar', 'a value for bar', 'float') - -Dataset Specifications -^^^^^^^^^^^^^^^^^^^^^^ - -Specifying datasets is done with :py:class:`~pynwb.spec.NWBDatasetSpec`. - -.. code-block:: python - - from pynwb.spec import NWBDatasetSpec - - spec = NWBDatasetSpec('A custom NWB type', - name='qux', - attribute=[ - NWBAttributeSpec('baz', 'a value for baz', 'text'), - ], - shape=(None, None)) - - -Using datasets to specify tables -++++++++++++++++++++++++++++++++ - -Tables can be specified using :py:class:`~pynwb.spec.NWBDtypeSpec`. To specify a table, provide a -list of :py:class:`~pynwb.spec.NWBDtypeSpec` objects to the *dtype* argument. - -.. code-block:: python - - from pynwb.spec import NWBDatasetSpec, NWBDtypeSpec - - spec = NWBDatasetSpec('A custom NWB type', - name='qux', - attribute=[ - NWBAttributeSpec('baz', 'a value for baz', 'text'), - ], - dtype=[ - NWBDtypeSpec('foo', 'column for foo', 'int'), - NWBDtypeSpec('bar', 'a column for bar', 'float') - ]) - -Group Specifications -^^^^^^^^^^^^^^^^^^^^ - -Specifying groups is done with the :py:class:`~pynwb.spec.NWBGroupSpec` class. - -.. code-block:: python - - from pynwb.spec import NWBGroupSpec - - spec = NWBGroupSpec('A custom NWB type', - name='quux', - attributes=[...], - datasets=[...], - groups=[...]) - -Neurodata Type Specifications -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -:py:class:`~pynwb.spec.NWBGroupSpec` and :py:class:`~pynwb.spec.NWBDatasetSpec` use the arguments `neurodata_type_inc` and `neurodata_type_def` for -declaring new types and extending existing types. New types are specified by setting the argument `neurodata_type_def`. New types can extend an existing type -by specifying the argument `neurodata_type_inc`. - -Create a new type - -.. code-block:: python - - from pynwb.spec import NWBGroupSpec - - # A list of NWBAttributeSpec objects to specify new attributes - addl_attributes = [...] - # A list of NWBDatasetSpec objects to specify new datasets - addl_datasets = [...] - # A list of NWBDatasetSpec objects to specify new groups - addl_groups = [...] - spec = NWBGroupSpec('A custom NWB type', - attributes=addl_attributes, - datasets=addl_datasets, - groups=addl_groups, - neurodata_type_def='MyNewNWBType') - -Extend an existing type - -.. code-block:: python - - from pynwb.spec import NWBGroupSpec - - # A list of NWBAttributeSpec objects to specify additional attributes or attributes to be overridden - addl_attributes = [...] - # A list of NWBDatasetSpec objects to specify additional datasets or datasets to be overridden - addl_datasets = [...] - # A list of NWBGroupSpec objects to specify additional groups or groups to be overridden - addl_groups = [...] - spec = NWBGroupSpec('An extended NWB type', - attributes=addl_attributes, - datasets=addl_datasets, - groups=addl_groups, - neurodata_type_inc='SpikeEventSeries', - neurodata_type_def='MyExtendedSpikeEventSeries') - -Existing types can be instantiated by specifying `neurodata_type_inc` alone. - -.. code-block:: python - - from pynwb.spec import NWBGroupSpec - - # use another NWBGroupSpec object to specify that a group of type - # ElectricalSeries should be present in the new type defined below - addl_groups = [ NWBGroupSpec('An included ElectricalSeries instance', - neurodata_type_inc='ElectricalSeries') ] - - spec = NWBGroupSpec('An extended NWB type', - groups=addl_groups, - neurodata_type_inc='SpikeEventSeries', - neurodata_type_def='MyExtendedSpikeEventSeries') - - -Datasets can be extended in the same manner (with regard to `neurodata_type_inc` and `neurodata_type_def`, -by using the class :py:class:`~pynwb.spec.NWBDatasetSpec`. - -.. _saving-extensions: - -Saving Extensions ------------------ - -Extensions are used by including them in a loaded namespace. Namespaces and extensions need to be saved to file -for downstream use. The class :py:class:`~pynwb.spec.NWBNamespaceBuilder` can be used to create new namespace and -specification files. - -.. note:: - - When using :py:class:`~pynwb.spec.NWBNamespaceBuilder`, the core NWB namespace is automatically included - -Create a new namespace with extensions - -.. code-block:: python - - from pynwb.spec import NWBGroupSpec, NWBNamespaceBuilder - - # create a builder for the namespace - ns_builder = NWBNamespaceBuilder("Extension for use in my laboratory", "mylab", version='0.1.0', ...) - - # create extensions - ext1 = NWBGroupSpec('A custom SpikeEventSeries interface', - attributes=[...], - datasets=[...], - groups=[...], - neurodata_type_inc='SpikeEventSeries', - neurodata_type_def='MyExtendedSpikeEventSeries') - - ext2 = NWBGroupSpec('A custom EventDetection interface', - attributes=[...], - datasets=[...], - groups=[...], - neurodata_type_inc='EventDetection', - neurodata_type_def='MyExtendedEventDetection') - - - # add the extension - ext_source = 'mylab.specs.yaml' - ns_builder.add_spec(ext_source, ext1) - ns_builder.add_spec(ext_source, ext2) - - # include an existing namespace - this will include all specifications in that namespace - ns_builder.include_namespace('collab_ns') - - # save the namespace and extensions - ns_path = 'mylab.namespace.yaml' - ns_builder.export(ns_path) - - -.. tip:: - - Using the API to generate extensions (rather than writing YAML sources directly) helps avoid errors in the specification - (e.g., due to missing required keys or invalid values) and ensure compliance of the extension definition with the - NWB specification language. It also helps with maintenance of extensions, e.g., if extensions have to be ported to - newer versions of the `specification language `_ - in the future. - -.. _incorporating-extensions: - -Incorporating extensions ------------------------- - -The NWB file format supports extending existing data types (See :ref:`extending-nwb` for more details on creating extensions). -Extensions must be registered with PyNWB to be used for reading and writing of custom neurodata types. - -The following code demonstrates how to load custom namespaces. - -.. code-block:: python - - from pynwb import load_namespaces - namespace_path = 'my_namespace.yaml' - load_namespaces(namespace_path) - -.. note:: - - This will register all namespaces defined in the file ``'my_namespace.yaml'``. - -NWBContainer : Representing custom data -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -To read and write custom data, corresponding :py:class:`~pynwb.core.NWBContainer` classes must be associated with their respective specifications. -:py:class:`~pynwb.core.NWBContainer` classes are associated with their respective specification using the decorator :py:func:`~pynwb.register_class`. - -The following code demonstrates how to associate a specification with the :py:class:`~pynwb.core.NWBContainer` class that represents it. - -.. code-block:: python - - from pynwb import register_class - @register_class('MyExtension', 'my_namespace') - class MyExtensionContainer(NWBContainer): - ... - -:py:func:`~pynwb.register_class` can also be used as a function. - -.. code-block:: python - - from pynwb import register_class - class MyExtensionContainer(NWBContainer): - ... - register_class('my_namespace', 'MyExtension', MyExtensionContainer) - -If you do not have an :py:class:`~pynwb.core.NWBContainer` subclass to associate with your extension specification, -a dynamically created class is created by default. - -To use the dynamic class, you will need to retrieve the class object using the function :py:func:`~pynwb.get_class`. -Once you have retrieved the class object, you can use it just like you would a statically defined class. - -.. code-block:: python - - from pynwb import get_class - MyExtensionContainer = get_class('my_namespace', 'MyExtension') - my_ext_inst = MyExtensionContainer(...) - - -If using iPython, you can access documentation for the class's constructor using the help command. - -ObjectMapper : Customizing the mapping between NWBContainer and the Spec -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -If your :py:class:`~pynwb.core.NWBContainer` extension requires custom mapping of the -:py:class:`~pynwb.core.NWBContainer` -class for reading and writing, you will need to implement and register a custom -:py:class:`~hdmf.build.objectmapper.ObjectMapper`. - -:py:class:`~hdmf.build.objectmapper.ObjectMapper` extensions are registered with the decorator -:py:func:`~pynwb.register_map`. - -.. code-block:: python - - from pynwb import register_map - from hdmf.build import ObjectMapper - - @register_map(MyExtensionContainer) - class MyExtensionMapper(ObjectMapper) - ... - -:py:func:`~pynwb.register_map` can also be used as a function. - -.. code-block:: python - - from pynwb import register_map - from hdmf.build import ObjectMapper - - class MyExtensionMapper(ObjectMapper) - ... - - register_map(MyExtensionContainer, MyExtensionMapper) - -.. tip:: - - ObjectMappers allow you to customize how objects in the spec are mapped to attributes of your NWBContainer in - Python. This is useful, e.g., in cases where you want to customize the default mapping. For example in - TimeSeries the attribute ``unit`` which is defined on the dataset ``data`` (i.e., ``data.unit``) would - by default be mapped to the attribute ``data_unit`` on :py:class:`~pynwb.base.TimeSeries`. The ObjectMapper - :py:class:`~pynwb.io.base.TimeSeriesMap` then changes this mapping to map ``data.unit`` to the attribute ``unit`` - on :py:class:`~pynwb.base.TimeSeries` . ObjectMappers also allow you to customize how constructor arguments - for your ``NWBContainer`` are constructed. E.g., in TimeSeries instead of explicit ``timestamps`` we - may only have a ``starting_time`` and ``rate``. In the ObjectMapper we could then construct ``timestamps`` - from this data on data load to always have ``timestamps`` available for the user. - For an overview of the concepts of containers, spec, builders, object mappers in PyNWB see also - :ref:`software-architecture` - - -.. _documenting-extensions: - -Documenting Extensions ----------------------- - -Using the same tools used to generate the documentation for the `NWB-N core format `_ -one can easily generate documentation in HTML, PDF, ePub and many other format for extensions as well. - -Code to generate this documentation is maintained in a separate repo: https://github.com/hdmf-dev/hdmf-docutils. To use these utilities, install the package with pip: - -.. code-block:: text - - pip install hdmf-docutils - -For the purpose of this example, we assume that our current directory has the following structure. - - -.. code-block:: text - - - my_extension/ - - my_extension_source/ - - mylab.namespace.yaml - - mylab.specs.yaml - - ... - - docs/ (Optional) - - mylab_description.rst - - mylab_release_notes.rst - -In addition to Python 3.x, you will also need ``sphinx`` (including the ``sphinx-quickstart`` tool) installed. -Sphinx is available here http://www.sphinx-doc.org/en/stable/install.html . - -We can now create the sources of our documentation as follows: - -.. code-block:: text - - python3 nwb_init_sphinx_extension_doc \ - --project test \ - --author "Dr. Master Expert" \ - --version "1.2.3" \ - --release alpha \ - --output my_extension_docs \ - --spec_dir my_extension_source \ - --namespace_filename mylab.namespace.yaml \ - --default_namespace mylab - --external_description my_extension_source/docs/mylab_description.rst \ (Optional) - --external_release_notes my_extension_source/docs/mylab_release_notes.rst \ (Optional) - -To automatically generate the RST documentation files from the YAML (or JSON) sources of the extension simply run: - -.. code-block:: text - - cd my_extension_docs - make apidoc - -Finally, to generate the HTML version of the docs run: - -.. code-block:: text - - make html - -.. tip:: - - Additional instructions for how to use and customize the extension documentations are also available - in the ``Readme.md`` file that ``init_sphinx_extension_doc.py`` automatically adds to the docs. - -.. tip:: - - See ``make help`` for a list of available options for building the documentation in many different - output formats (e.g., PDF, ePub, LaTeX, etc.). - -.. tip:: - - See ``python3 init_sphinx_extension_doc.py --help`` for a complete list of option to customize the documentation - directly during initialization. - -.. tip:: - - The above example included additional description and release note docs as part of the specification. These are - included in the docs via ``.. include`` commands so that changes in those files are automatically picked up - when rebuilding to docs. Alternatively, we can also add custom documentation directly to the docs. - In this case the options ``--custom_description format_description.rst`` - and ``--custom_release_notes format_release_notes.rst`` of the ``init_sphinx_extension_doc.py`` script are useful - to automatically generate the basic setup for those files so that one can easily start to add content directly - without having to worry about the additional setup. - - -Further Reading ---------------- - -* **Using Extensions:** See :ref:`extending-nwb` for an example on how to use extensions during read and write. -* **Specification Language:** For a detailed overview of the specification language itself see https://schema-language.readthedocs.io/en/latest/ diff --git a/docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst b/docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst new file mode 100644 index 000000000..a158ecdec --- /dev/null +++ b/docs/source/extensions_tutorial/2_create_extension_spec_walkthrough.rst @@ -0,0 +1,141 @@ +Creating an extension +===================== + +Using ndx-template +~~~~~~~~~~~~~~~~~~ +Extensions should be created in their own repository, not alongside data conversion code. This facilitates sharing +and editing of the extension separately from the code that uses it. When starting a new extension, we highly +recommend using the `ndx-template `_ repository, which automatically +generates a repository with the appropriate directory structure. + +After you finish the instructions `here `_, +you should have a directory structure that looks like this + +.. code-block:: c + + ├── LICENSE.txt + ├── MANIFEST.in + ├── NEXTSTEPS.md + ├── README.md + ├── docs + │   ├── Makefile + │   ├── README.md + │   ├── make.bat + │   └── source + │   ├── _static + │   │   └── theme_overrides.css + │   ├── conf.py + │   ├── conf_doc_autogen.py + │   ├── credits.rst + │   ├── description.rst + │   ├── format.rst + │   ├── index.rst + │   └── release_notes.rst + ├── requirements.txt + ├── setup.cfg + ├── setup.py + ├── spec + │   ├── ndx-example.extensions.yaml + │   └── ndx-example.namespace.yaml + └── src + ├── matnwb + │   └── README.md + ├── pynwb + │   ├── README.md + │   ├── ndx_example + │   │   └── __init__.py + │   └── tests + │   ├── __init__.py + │   └── test_tetrodeseries.py + └── spec + └── create_extension_spec.py + +At its core, an NWB extension consists of YAML text files, such as those generated in the `spec` +folder. While you can write these YAML extension files by hand, PyNWB provides a convenient API +via the :py:mod:`~pynwb.spec` module for creating extensions. + +Open ``src/spec/create_extension_spec.py``. You will be +modifying this script to create your own NWB extension. Let's first walk through each piece. + +Creating a namespace +~~~~~~~~~~~~~~~~~~~~ +NWB organizes types into namespaces. You must define a new namespace before creating any new types. After following +the instructions from `ndx-template `_, you should have a file +``ndx-my-ext/src/spec/create_extension_spec.py``. The beginning of this file should look like + +.. code-block:: python + + from pynwb.spec import NWBNamespaceBuilder, export_spec, NWBGroupSpec, NWBAttributeSpec + # TODO: import the following spec classes as needed + # from pynwb.spec import NWBDatasetSpec, NWBLinkSpec, NWBDtypeSpec, NWBRefSpec + + + def main(): + # these arguments were auto-generated from your cookiecutter inputs + ns_builder = NWBNamespaceBuilder( + doc="my description", + name="ndx-my-ext", + version="0.1.0", + author="John Doe", + contact="contact@gmail.com" + ) + +Here, after the initial imports, we are defining meta-data of the extension. +Pay particular attention to ``version``. If you make changes to your extension +after the initial release, you should increase the numbers in your version +number, so that you can keep track of what exact version of the extension was +used for each file. We recommend using a `semantic versioning approach `_. + +Including types +~~~~~~~~~~~~~~~ + +Next, we need to include types from the core schemas. This is analogous to +importing classes in Python. The generated file includes some example imports. + +.. code-block:: python + + ns_builder.include_type('ElectricalSeries', namespace='core') + ns_builder.include_type('TimeSeries', namespace='core') + ns_builder.include_type('NWBDataInterface', namespace='core') + ns_builder.include_type('NWBContainer', namespace='core') + ns_builder.include_type('DynamicTableRegion', namespace='hdmf-common') + ns_builder.include_type('VectorData', namespace='hdmf-common') + ns_builder.include_type('Data', namespace='hdmf-common') + +Neuroscience-specific data types are defined in the namespace ``'core'`` +(which means core NWB). More general organizational data types that are not +specific to neuroscience and are relevant across scientific fields are defined +in ``'hdmf-common'``. You can see which types are defined in which namespace by +exploring the `NWB schema documentation `_ +and hdmf-common schema documentation `_. + +Defining new neurodata types +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +Next, the ``create_extension_spec.py`` file declares an example extension +for a new neurodata type called ``TetrodeSeries``, which extends the :py:class:`~pynwb.ecephys.ElectricalSeries` +type. Then it creates a list of all new data types. + +.. code-block:: python + + tetrode_series = NWBGroupSpec( + neurodata_type_def='TetrodeSeries', + neurodata_type_inc='ElectricalSeries', + doc=('An extension of ElectricalSeries to include the tetrode ID for ' + 'each time series.'), + attributes=[ + NWBAttributeSpec( + name='trode_id', + doc='The tetrode ID.', + dtype='int32' + ) + ], + ) + + # TODO: add all of your new data types to this list + new_data_types = [tetrode_series] + +The remainder of the file is to generate the YAML files from the spec definition, and should not be changed. + +After you make changes to this file, you should run it to re-generate the ``ndx-[name].extensions.yaml`` and +``ndx-[name].namespace.yaml`` files. In the next section, we will go into more detail into how to create neurodata +types. diff --git a/docs/source/extensions_tutorial/3_spec_api.rst b/docs/source/extensions_tutorial/3_spec_api.rst new file mode 100644 index 000000000..54df0cca0 --- /dev/null +++ b/docs/source/extensions_tutorial/3_spec_api.rst @@ -0,0 +1,183 @@ +The Spec API +------------ + +The `NWB Specification Language `_ defines a structure for +data and metadata using Groups, Datasets, Attributes, and Links. These structures are mapped onto +:py:class:`~pynwb.spec.NWBGroupSpec`, :py:class:`~pynwb.spec.NWBDatasetSpec`, +:py:class:`~pynwb.spec.NWBAttributeSpec`, and :py:class:`~pynwb.spec.NWBLinkSpec`, respectively. Here, we describe in +detail each of these classes, and demonstrate how to use them to create custom neurodata types. + +Group Specifications +^^^^^^^^^^^^^^^^^^^^ + +Most neurodata types are Groups, which act like a directory or folder within the NWB file. A Group can have +within it Datasets, Attributes, Links, and/or other Groups. Groups are specified with the +:py:class:`~pynwb.spec.NWBGroupSpec` class, which provides a python API for specifying the structure for an +`NWB Group `_ . + +.. code-block:: python + + from pynwb.spec import NWBGroupSpec + + spec = NWBGroupSpec( + neurodata_type_def='MyType', + neurodata_type_inc='NWBDataInterface', + doc='A custom NWB type', + name='quux', + attributes=[...], + datasets=[...], + groups=[...], + links=[...] + ) + +``neurodata_type_def`` and ``neurodata_type_inc`` define the neurodata type with the following rules: + +- ``neurodata_type_def`` declares the name of the neurodata type. +- ``neurodata_type_inc`` indicates what data type you are extending (Groups must extend Groups, and Datasets must extend Datasets). +- To define a new neurodata type that does not extend an existing type, use + ``neurodata_type_inc=NWBContainer`` for a group or ``neurodata_type_inc=NWBData`` for a dataset. + ``NWBContainer`` and ``NWBData`` are base types for NWB. +- To use a type that has already been defined, use ``neurodata_type_inc`` and not ``neurodata_type_def``. +- You can define a group that is not a neurodata type by omitting both ``neurodata_type_def`` and ``neurodata_type_inc``. + +.. tip:: + Although you have the option not to, there are several advantages to defining new groups and neurodata types. + Neurodata types can be reused in multiple places in the schema, and can be linked to, while groups that are not + neurodata types cannot. You can also have multiple neurodata type groups of the same type in the same group, + whereas groups that are not neurodata types are limited to 0 or 1. Most of the time, we would recommend making a + group a neurodata type. It is also generally better to extend your neurodata type from an existing type. Look + through the `NWB schema `_ to see if a core neurodata type would + work as a base for your new type. If no existing type works, consider extending + :py:class:`~pynwb.base.NWBDataInterface``, which allows you to add the object to a processing module. + +.. tip:: + New neurodata types should always be declared at the top level of the schema rather than nesting type + definitions. I.e., when creating a new neurodata type it should be placed at the top level of your schema + and then included at the appropriate location via ``neurodata_type_inc``. This approach greatly simplifies + management of types. + +For more information about the options available when specifying a Group, see the +`API docs for NWBGroupSpec `_. + +Dataset Specifications +^^^^^^^^^^^^^^^^^^^^^^ + +All larger blocks of numeric or text data should be stored in Datasets. Specifying datasets is done with +:py:class:`~pynwb.spec.NWBDatasetSpec`. + +.. code-block:: python + + from pynwb.spec import NWBDatasetSpec + + spec = NWBDatasetSpec( + doc='A custom NWB type', + name='qux', + shape=(None, None), + attributes=[...] + ) + +``neurodata_type_def``, ``neurodata_type_inc``, ``doc``, ``name``, ``default_name``, ``linkable``, ``quantity``, and +``attributes`` all work the same as they do in :py:class:`~pynwb.spec.NWBGroupSpec`, described in the previous section. + +``dtype`` defines the type of the data, which can be a basic type, compound type, or reference type. +See a list of options `here `_. +Basic types can be defined as string objects and more complex types via :py:class:`~pynwb.spec.NWBDtypeSpec` and `RefSpec `_. + + +``shape`` is a specification defining the allowable shapes for the dataset. See the shape specification +`here `_. ``None`` is +mapped to ``null``. Is no shape is provided, it is assumed that the dataset is only a single element. + +If the dataset is a single element (scalar) that represents meta-data, consider using an Attribute (see +below) to store the data more efficiently instead. However, note that a Dataset can have Attributes, +whereas an Attribute cannot have Attributes of its own. +``dims`` provides labels for each dimension of ``shape``. + +Using datasets to specify tables +++++++++++++++++++++++++++++++++ + +Row-based tables can be specified using :py:class:`~pynwb.spec.NWBDtypeSpec`. To specify a table, provide a +list of :py:class:`~pynwb.spec.NWBDtypeSpec` objects to the ``dtype`` argument. + +.. code-block:: python + + from pynwb.spec import NWBDatasetSpec, NWBDtypeSpec + + spec = NWBDatasetSpec( + doc='A custom NWB type', + name='qux', + attribute=[ + NWBAttributeSpec('baz', 'a value for baz', 'text'), + ], + dtype=[ + NWBDtypeSpec('foo', 'column for foo', 'int'), + NWBDtypeSpec('bar', 'a column for bar', 'float') + ] + ) + +.. tip:: + Column-based tables are also possible and more flexible. See the documentation for `DynamicTable `_. + +Attribute Specifications +^^^^^^^^^^^^^^^^^^^^^^^^ + +Attributes are small metadata objects describing the nature and/or intended usage of a Group or Dataset. Attributes are +defined in the ``attributes`` field of a :py:class:`~pynwb.spec.NWBGroupSpec` or +:py:class:`~pynwb.spec.NWBDatasetSpec`. ``attributes`` takes a list of :py:class:`~pynwb.spec.NWBAttributeSpec` objects. + +.. code-block:: python + + from pynwb.spec import NWBAttributeSpec + + spec = NWBAttributeSpec( + name='bar', + doc='a value for bar', + dtype='float' + ) + +:py:class:`~pynwb.spec.NWBAttributeSpec` has arguments very similar to :py:class:`~pynwb.spec.NWBDatasetSpec`. A key difference is that an attribute cannot be a +neurodata type, i.e., the ``neurodata_type_def`` and ``neurodata_type_inc`` keys are not allowed. The only way to match an object with a spec is through the name of the attribute so ``name`` is +required. You cannot have multiple attributes on a single group/dataset that correspond to the same +:py:class:`~pynwb.spec.NWBAttributeSpec`, since these would have to have the same name. Therefore, instead of +specifying number of ``quantity``, you have a ``required`` field which takes a boolean value. Another +key difference between datasets and attributes is that attributes cannot have attributes of their own. + +.. tip:: + Dataset or Attribute? It is often possible to store data as either a Dataset or an Attribute. Our best advice is + to keep Attributes small. In HDF5 the typical size limit for attributes is 64Kbytes. If an attribute is going to + store more than 64Kbyte, then make it a Dataset. Attributes are also more efficient for storing very + small data, such as scalars. However, attributes cannot have attributes of their own, and in HDF5, + I/O filters, such as compression and chunking, cannot apply to attributes. + + +Link Specifications +^^^^^^^^^^^^^^^^^^^ + +You can store an object in one place and reference that object in another without copying the object using +`Links `_, which +can be defined using :py:class:`~pynwb.spec.NWBLinkSpec` objects. + +.. code-block:: python + + from pynwb.spec import NWBLinkSpec + + spec = NWBLinkSpec( + doc='my link', + target_type='ElectricalSeries', + quantity='?' + ) + +``doc``, ``quantity``, and ``name`` work similarly to :py:class:`~pynwb.spec.NWBDatasetSpec`. + +``target_type`` indicates the neurodata type that can be referenced. + +.. tip:: + In case you need to store large collections of links, it can be more efficient to create a dataset for storing + the links via object references. In NWB, this is used, e.g., in py:class:`~pynwb.epoch.TimeIntervals` to store + collections of references to TimeSeries objects. + +Using these functions in ``create_extension_spec.py`` and then running that file will generate YAML files that define +your extension. If you are a MATLAB user, you are now ready to switch over to MATLAB. Just run +``generateExtension ('path/to/ndx_name.extension.yaml')`` and the extension will be automatically generated for you. If +you are a Python user, you need to do a little more work to make a Python API that allows you to read and write data +according to this extension. The next two sections will teach you how to create this Python API. diff --git a/docs/source/extensions_tutorial/4_auto_api.rst b/docs/source/extensions_tutorial/4_auto_api.rst new file mode 100644 index 000000000..971f87a7c --- /dev/null +++ b/docs/source/extensions_tutorial/4_auto_api.rst @@ -0,0 +1,67 @@ +Automatically generating a PyNWB API for an extension +----------------------------------------------------- + +Now that we have created the extension specification, we need to create the Python interface. These classes will be +used just like the PyNWB API to read and write NWB files using Python. There are two ways to do this: you can +automatically generate the API classes based on the schema, or you can manually create the API classes. Here, we will +show you how to automatically generate the API. In the next section we will discuss why and how to create custom API +classes. + +.. note:: + In MatNWB there is only one method: automatically generating the API. Simply call + ``generateExtension("path/to/extension.yaml")``; + + +Open up ``ndx-example/src/pynwb/ndx_example/__init__.py``, and notice the last line: + +.. code-block:: python + + TetrodeSeries = get_class('TetrodeSeries', 'ndx-example') + +:py:func:`~pynwb.get_class` is a function that automatically creates a Python API object by parsing the extension +YAML. If you create more neurodata types, simply go down the line creating each one. This is the same object that is +created when you use the ``load_namespaces`` flag on :py:func:`~pynwb.NWBHDF5IO.__init__`. + +Customizing automatically generated APIs +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Once these classes are generated, you can customize them by dynamically adding or replacing attributes/methods (a.k.a., monkey patching). + +A typical example is adding methods. Let's say you wanted a method that could +return data from only the first channel. You could add that method like this: + +.. code-block:: python + + def data_from_first_chan(self): + return self.data[:, 0] + + TetrodeSeries.data_from_first_chan = data_from_first_chan + +You can also alter existing methods by overwriting them. Lets suppose you wanted to ensure that the +``trode_id`` field is never less than 0 for the ``TetrodeSeries`` constructor. You can do this by creating a new +``__init__`` function and assigning it to the class. + +.. code-block:: python + + from hdmf.utils import docval, get_docval + from hdmf.common.table import DynamicTableRegion + + @docval(get_docval(TetrodeSeries.__init__)) + def new_init(self, **kwargs): + assert kwargs['trode_id'] >=0, f"`trode_id` must be greater than or equal to 0." + TetrodeSeries.__init__(self, **kwargs) + + TetrodeSeries.__init__ = new_init + +The above code creates a ``new_init`` method that runs a validation step and then calls the original ``__init__``. +Then the class ``__init__`` is overwritten by the new method. Here we also use ``docval``, which is described in the +next section. + + +.. tip:: + This approach is easy, but note your API will be locked to your specification. If you make changes to your + specification there will be corresponding changes to the API, and this is likely to break existing code. + Also, monkey patches can be very confusing to someone who is not aware of them. Differences + between the installed module and the actual behavior of the source code can lead to frustrated + developers. As such, this approach should be used with great care. In the + next section we will show you how to create your own custom API that is more robust. diff --git a/docs/source/extensions_tutorial/5_custom_api.rst b/docs/source/extensions_tutorial/5_custom_api.rst new file mode 100644 index 000000000..e691838ea --- /dev/null +++ b/docs/source/extensions_tutorial/5_custom_api.rst @@ -0,0 +1,282 @@ +Building a custom API for an extension +====================================== + +Creating custom extensions is recommended if you want a stable API that can remain the same even as you make changes +to the internal data organization. The :py:mod:`pynwb.core` module has various tools to make it easier to write +classes that behave like the rest of the PyNWB API. + +The :py:mod:`pynwb.core` defines two base classes that represent the primitive structures supported by +the schema. :py:class:`~pynwb.core.NWBData` represents datasets and :py:class:`~pynwb.core.NWBContainer` +represents groups. Additionally, :py:mod:`pynwb.core` offers subclasses of these two classes for +writing classes that come with more functionality. + +Docval +------ +docval is a library within PyNWB and HDMF that performs input validation and automatic documentation generation. Using +the ``docval`` decorator is recommended for methods of custom API classes. + +This decorator takes a list of dictionaries that specify the method parameters. These +dictionaries are used for enforcing type and building a Sphinx docstring. +The first arguments are dictionaries that specify the positional +arguments and keyword arguments of the decorated function. These dictionaries +must contain the following keys: ``'name'``, ``'type'``, and ``'doc'``. This will define a +positional argument. To define a keyword argument, specify a default value +using the key ``'default'``. To validate the dimensions of an input array +add the optional ``'shape'`` parameter. + +The decorated method must take ``self`` and ``**kwargs`` as arguments. + +When using this decorator, the functions :py:func:`getargs` and +:py:func:`popargs` can be used for easily extracting arguments from +kwargs. + +The following code example demonstrates the use of this decorator: + +.. code-block:: python + + @docval({'name': 'arg1':, 'type': str, 'doc': 'this is the first positional argument'}, + {'name': 'arg2':, 'type': int, 'doc': 'this is the second positional argument'}, + {'name': 'kwarg1':, 'type': (list, tuple), 'doc': 'this is a keyword argument', 'default': list()}, + returns='foo object', rtype='Foo') + def foo(self, **kwargs): + arg1, arg2, kwarg1 = getargs('arg1', 'arg2', 'kwarg1', **kwargs) + ... + + +The ``'shape'`` parameter is a tuple that follows the same logic as the `shape parameter in the specification +language `_. It can take the form of a tuple +with integers or ``None`` in each dimension. ``None`` indicates that this dimension can take any value. For +instance, ``(3, None)`` means the data must be a 2D matrix with a length of 3 and any width. ``'shape'`` can also +take a value that is a tuple of tuples, in which case any one of those tuples can match the spec. For instance, +``"shape": ((3, 3), (4, 4, 4))`` would indicate that the shape of this data could either be 3x3 or 4x4x4. + +The ``'type'`` argument can take a class or a tuple of classes. We also define special strings that are macros which +encompass a number of similar types, and can be used in place of a class, on its own, or within a tuple. ``'array_data'`` +allows the data to be of type ``np.ndarray``, ``list``, ``tuple``, or ``h5py.Dataset``; and ``'scalar_data'`` allows +the data to be ``str``, ``int``, ``float``, ``bytes``, or ``bool``. + +Registering classes +------------------- + +When defining a class that represents a *neurodata_type* (i.e. anything that has a *neurodata_type_def*) +from your extension, you can tell PyNWB which *neurodata_type* it represents using the function +:py:func:`~pynwb.register_class`. This class can be called on its own, or used as a class decorator. The +first argument should be the *neurodata_type* and the second argument should be the *namespace* name. + +The following example demonstrates how to register a class as the Python class representation of the +*neurodata_type* "MyContainer" from the *namespace* "my_ns". + +.. code-block:: python + + from pynwb import register_class + from pynwb.core import NWBContainer + + class MyContainer(NWBContainer): + ... + + regitser_class('MyContainer', 'my_ns', MyContainer) + + +Alternatively, you can use :py:func:`~pynwb.register_class` as a decorator. + +.. code-block:: python + + from pynwb import register_class + from pynwb.core import NWBContainer + + @regitser_class('MyContainer', 'my_ns') + class MyContainer(NWBContainer): + ... + +:py:func:`~pynwb.register_class` is used with :py:class:`~pynwb.core.NWBData` the same way it is used with +:py:class:`~pynwb.core.NWBContainer`. + + +Nwbfields +--------- + +When creating a new neurodata type, you need to define the new properties on your class, which is done by defining +them in the ``__nwbfields__`` class property. This class property should be a tuple of strings that name the new +properties. Adding a property using this functionality will create a property than can be set *only once*. Any +new properties of the class should be defined here. + +For example, the following class definition will create the ``MyContainer`` class that has the properties ``foo`` +and ``bar``. + +.. code-block:: python + + from pynwb import register_class + from pynwb.core import NWBContainer + + + class MyContainer(NWBContainer): + + __nwbfields__ = ('foo', 'bar') + + ... + + +NWBContainer +------------- + +:py:class:`~pynwb.core.NWBContainer` should be used to represent groups with a *neurodata_type_def*. This section +will discuss the available :py:class:`~pynwb.core.NWBContainer` subclasses for representing common group specifications. + +NWBDataInterface +^^^^^^^^^^^^^^^^ + +The NWB schema uses the neurodata type ``NWBDataInterface`` for specifying containers that contain data that is not +considered metadata. For example, ``NWBDataInterface`` is a parent neurodata type to ``ElectricalSeries`` data, +but not a parent to ``ElectrodeGroup``. + +There are no requirements for using :py:class:`~pynwb.core.NWBDataInterface` in addition to those inherited from +:py:class:`~pynwb.core.NWBContainer`. + +MultiContainerInterface +^^^^^^^^^^^^^^^^^^^^^^^^ + +Throughout the NWB schema, there are multiple ``NWBDataInterface`` specifications that include one or more or zero +or more of a certain neurodata type. For example, the ``LFP`` neurodata type contains one or more ``ElectricalSeries``. +If your extension follows this pattern, you can use :py:class:`~pynwb.core.MultiContainerInterface` for defining +the representative class. + +:py:class:`~pynwb.core.MultiContainerInterface` provides a way of automatically generating setters, getters, and +properties for your class. These methods are autogenerated based on a configuration provided using the class property +``__clsconf__``. ``__clsconf__`` should be a dict or a list of dicts. A single dict should be used if your +specification contains a single neurodata type. A list of dicts should be used if your specification contains +multiple neurodata types that will exist as one or more or zero or more. The contents of the dict are described +in the following table. + +=========== =========================================================== ================ + Key Attribute Required? +=========== =========================================================== ================ +``type`` the type of the Container Yes +``attr`` the property name that holds the Containers Yes +``add`` the name of the method for adding a Container Yes +``create`` the name of the method for creating a Container No +``get`` the name of the method for getting a Container by name Yes +=========== =========================================================== ================ + + +The ``type`` key provides a way for the setters to check for type. The property under the name given by the. +``attr`` key will be a :py:class:`~pynwb.core.LabelledDict`. If your class uses a single dict, +a ``__getitem__`` method will be autogenerated for indexing into this :py:class:`~pynwb.core.LabelledDict`. +Finally, a constructor will also be autogenerated if you do not provide one in the class definition. + +The following code block demonstrates using :py:class:`~pynwb.core.MultiContainerInterface` to build a class +that represents the neurodata type "MyDataInterface" from the namespace "my_ns". It contains one or more containers +with neurodata type "MyContainer". + +.. code-block:: python + + from pynwb import register_class + from pynwb.core import MultiContainerInterface + + + @register_class("MyDataInterface", "my_ns") + class MyDataInterface(MultiContainerInterface): + + __clsconf__ = { + 'type': MyContainer, + 'attr': 'containers', + 'add': 'add_container', + 'create': 'create_container', + 'get': 'get_container', + } + ... + + +This class will have the methods ``add_container``, ``create_container``, and ``get_container``. It will also have +the property ``containers``. The ``add_container`` method will check to make sure that either an object of type +``MyContainer`` or a list/dict/tuple of objects of type ``MyContainer`` is passed in. ``create_container`` will +accept the exact same arguments that the ``MyContainer`` class constructor accepts. + +NWBData +-------- + +:py:class:`~pynwb.core.NWBData` should be used to represent datasets with a *neurodata_type_def*. This section +will discuss the available :py:class:`~pynwb.core.NWBData` subclasses for representing common dataset specifications. + +NWBTable +^^^^^^^^^ + +If your specification extension contains a table definition i.e. a dataset with a compound data type, you should use +the :py:class:`~pynwb.core.NWBTable` class to represent this specification. Since :py:class:`~pynwb.core.NWBTable` +subclasses :py:class:`~pynwb.core.NWBData`, you can still use ``__nwbfields__``. In addition, you can use the +``__columns__`` class property to specify the columns of the table. ``__columns__`` should be a list or a tuple of +:py:func:`~hdmf.utils.docval`-like dictionaries. + +The following example demonstrates how to define a table with the columns ``foo`` and ``bar`` that are of type +str and int, respectively. We also register the class as the representation of the *neurodata_type* "MyTable" +from the *namespace* "my_ns". + +.. code-block:: python + + from pynwb import register_class + from pynwb.core import NWBTable + + + @register_class('MyTable', 'my_ns') + class MyTable(NWBTable): + + __columns__ = [ + {'name': 'foo', 'type': str, 'doc': 'the foo column'}, + {'name': 'bar', 'type': int, 'doc': 'the bar column'}, + ] + + ... + +NWBTableRegion +^^^^^^^^^^^^^^ + +:py:class:`~pynwb.core.NWBTableRegion` should be used to represent datasets that store a region reference. +When subclassing this class, make sure you provide a way to pass in the required +arguments for the :py:class:`~pynwb.core.NWBTableRegion` constructor--the *name* of the dataset, the *table* that the region +applies to, and the *region* itself. + + +ObjectMapper: Customizing the mapping between NWBContainer and the Spec +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If your :py:class:`~pynwb.core.NWBContainer` extension requires custom mapping of the +:py:class:`~pynwb.core.NWBContainer` +class for reading and writing, you will need to implement and register a custom +:py:class:`~hdmf.build.objectmapper.ObjectMapper`. + +:py:class:`~hdmf.build.objectmapper.ObjectMapper` extensions are registered with the decorator +:py:func:`~pynwb.register_map`. + +.. code-block:: python + + from pynwb import register_map + from hdmf.build import ObjectMapper + + @register_map(MyExtensionContainer) + class MyExtensionMapper(ObjectMapper) + ... + +:py:func:`~pynwb.register_map` can also be used as a function. + +.. code-block:: python + + from pynwb import register_map + from hdmf.build import ObjectMapper + + class MyExtensionMapper(ObjectMapper) + ... + + register_map(MyExtensionContainer, MyExtensionMapper) + +.. tip:: + + ObjectMappers allow you to customize how objects in the spec are mapped to attributes of your NWBContainer in + Python. This is useful, e.g., in cases where you want to customize the default mapping. For example in + ``TimeSeries``, the attribute ``unit``, which is defined on the dataset ``data`` (i.e., ``data.unit``), would + by default be mapped to the attribute ``data__unit`` on :py:class:`~pynwb.base.TimeSeries`. The ObjectMapper + :py:class:`~pynwb.io.base.TimeSeriesMap` then changes this mapping to map ``data.unit`` to the attribute ``unit`` + on :py:class:`~pynwb.base.TimeSeries` . ObjectMappers also allow you to customize how constructor arguments + for your ``NWBContainer`` are constructed. For example, in ``TimeSeries`` instead of explicit ``timestamps`` we + may only have a ``starting_time`` and ``rate``. In the ObjectMapper, we could then construct ``timestamps`` + from this data on data load to always have ``timestamps`` available for the user. + For an overview of the concepts of containers, spec, builders, and object mappers in PyNWB, see also + :ref:`software-architecture`. diff --git a/docs/source/extensions_tutorial/6_documenting_extension.rst b/docs/source/extensions_tutorial/6_documenting_extension.rst new file mode 100644 index 000000000..87a252479 --- /dev/null +++ b/docs/source/extensions_tutorial/6_documenting_extension.rst @@ -0,0 +1,40 @@ +Documenting Extensions +---------------------- + +Using the same tools used to generate the documentation for the `NWB core format `_, +one can easily generate documentation in HTML, PDF, ePub and many other formats for extensions. + +If you used ndx-template, then your repository is already pre-configured to automatically generate documentation for +your extension. The ``docs`` directory structure should look like this. + +.. code-block:: text + + ndx-my-extension/ + docs/ + source/ + credits.rst + description.rst + release_notes.rst + ... + + +To generate the HTML documentation files from the YAML (or JSON) sources of the extension, simply run: + +.. code-block:: text + + cd docs/source + make html + +The generated documentation will be available in ``build/html``. To view, open ``build/html/index.html`` in your browser. +These pages contain diagrams of your extension. Note that there are several places where information needs to be +added. For instance, the Overview section says: + +.. note:: + + Add the description of your extension here + +Within ``docs/source``, edit ``credits.rst``, ``description.rst``, and ``release_notes.rst``, then rerun ``make html``. + +Now that you have created documentation for your extension, it is time to learn how to publish in the NDX catalog. + +See published extensions and learn how to share your extension on the `NDX Catalog website `_. diff --git a/docs/source/extensions_tutorial/extensions_tutorial_home.rst b/docs/source/extensions_tutorial/extensions_tutorial_home.rst new file mode 100644 index 000000000..6fec63b01 --- /dev/null +++ b/docs/source/extensions_tutorial/extensions_tutorial_home.rst @@ -0,0 +1,17 @@ +Extending NWB +============= + +Neurophysiology is always changing as new technologies are developed. While the core NWB schema supports many of the +most common data types in neurophysiology, we need a way to accommodate new technologies and unique metadata needs. +Neurodata extensions (NDX) allow us to define new data types. These data types can extend core types, contain core +types, or can be entirely new. These extensions are formally defined with a collection of YAML files following +the `NWB Specification Language `_. + +.. toctree:: + :maxdepth: 2 + + 2_create_extension_spec_walkthrough + 3_spec_api + 4_auto_api + 5_custom_api + 6_documenting_extension diff --git a/docs/source/figures/gallery_thumbnails.pptx b/docs/source/figures/gallery_thumbnails.pptx new file mode 100644 index 0000000000000000000000000000000000000000..d94f17ac5b6bbc876e3fd1dde094e469e770a7e9 GIT binary patch literal 2258651 zcmeFYV~}lImo1vMZQFM4v~AnAZSS;g+qQPv_DC-J+GqTy?<42{+J`y znsY_0-lLD!+GwK>c`0BJ6aX*)2mk;8LV&{Ngh)yt0041B003kF2p}yXJ6mTHTW39G z4|@|Q9XfX#Yk~q0Ac{PI@0b4n>%VgbhSH{NHyB|2uYsT7LTiMo+BQ0B!WRa8W#1^{ zt^k!YB^K8c2pBc)p9(Ko7=h@2B4c+9#hWDHOGKdYwtI~?>ccKeR2!m&7@_$~I#VqX znfl@N#M-Lw%9kk{YYI%V?XGS;TxO0Bj`%~1YqqD+B2LjB(`g9OX_vuLWTabVLKo%h z*b^t1)dTpl;_2NBQ-g#M(>T|i{-&NBrW)McfZnPR7taFKt2l;IVniM>Wq_g*0R6cFrm$nox<$@tV-dP{B52PlPSSzU^(=eS&)qL} z4YINg`NM;}?N;_?jaz`_DR#G)O7wHW@OLkrs4rCEJjB&wu@3e_4~=EVhOYW>`O&uJ 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PyNWB. -#. Python 3.5, 3.6, or 3.7 +#. Python 3.7, 3.8, or 3.9 #. pip ------------ diff --git a/docs/source/index.rst b/docs/source/index.rst index 8f7f13392..7bc457e07 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -9,12 +9,12 @@ NWB for Python PyNWB is a Python package for working with NWB files. It provides a high-level API for efficiently working with Neurodata stored in the `NWB format `_. -`Neurodata Without Borders: Neurophysiology (NWB:N) `_ is a project to develop a +`Neurodata Without Borders (NWB) `_ is a project to develop a unified data format for cellular-based neurophysiology data, focused on the dynamics of groups of neurons measured under a large range of experimental conditions. -The NWB:N team consists of neuroscientists and software developers +The NWB team consists of neuroscientists and software developers who recognize that adoption of a unified data format is an important step toward breaking down the barriers to data sharing in neuroscience. @@ -33,14 +33,14 @@ breaking down the barriers to data sharing in neuroscience. overview_intro overview_software_architecture overview_nwbfile + overview_citing .. toctree:: :maxdepth: 2 :caption: Resources tutorials/index - extensions - building_api + extensions_tutorial/extensions_tutorial_home validation api_docs software_process diff --git a/docs/source/overview_citing.rst b/docs/source/overview_citing.rst new file mode 100644 index 000000000..6618de345 --- /dev/null +++ b/docs/source/overview_citing.rst @@ -0,0 +1,61 @@ +.. _citing: + +Citing PyNWB +============ + +BibTeX entry +------------ + +If you use PyNWB in your research, please use the following citation: + +.. code-block:: bibtex + + @article {R{\"u}bel2021.03.13.435173, + author = {R{\"u}bel, Oliver and Tritt, Andrew and Ly, Ryan and Dichter, Benjamin K. and Ghosh, Satrajit and Niu, Lawrence and Soltesz, Ivan and Svoboda, Karel and Frank, Loren and Bouchard, Kristofer E.}, + title = {The Neurodata Without Borders ecosystem for neurophysiological data science}, + elocation-id = {2021.03.13.435173}, + year = {2021}, + doi = {10.1101/2021.03.13.435173}, + publisher = {Cold Spring Harbor Laboratory}, + abstract = {The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB{\textquoteright}s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.Competing Interest StatementThe authors have declared no competing interest.}, + URL = {https://www.biorxiv.org/content/early/2021/03/15/2021.03.13.435173}, + eprint = {https://www.biorxiv.org/content/early/2021/03/15/2021.03.13.435173.full.pdf}, + journal = {bioRxiv} + } + +Using RRID +---------- + +* ResourceID: `SCR_017452 `_ +* Proper Citation: **(PyNWB, RRID:SCR_017452)** + + +Using duecredit +--------------- + +Citations can be generated using duecredit_. To install duecredit, run ``pip install duecredit``. + +You can obtain a list of citations for your Python script, e.g., ``yourscript.py``, using: + +.. code-block:: bash + + cd /path/to/your/module + python -m duecredit yourscript.py + +Alternatively, you can set the environment variable ``DUECREDIT_ENABLE=yes`` + +.. code-block:: bash + + DUECREDIT-ENABLE=yes python yourscript.py + +Citations will be saved in a hidden file (``.duecredit.p``) in the current directory. You can then use the duecredit_ +command line tool to export the citations to different formats. For example, you can display your citations in +BibTeX format using: + +.. code-block:: bash + + duecredit summary --format=bibtex + +For more information on using duecredit, please consult its `homepage `_. + +.. _duecredit: https://github.com/duecredit/duecredit diff --git a/docs/source/software_process.rst b/docs/source/software_process.rst index 6182fd3a4..0a4beb4ab 100644 --- a/docs/source/software_process.rst +++ b/docs/source/software_process.rst @@ -43,27 +43,24 @@ lines are covered by the tests. Requirement Specifications -------------------------- -There are 4 kinds of requirements specification in PyNWB. - -Setup.py Dependencies ---------------------- - -There are 4 kinds of requirements specification in PyNWB. +There are 5 kinds of requirements specification in PyNWB. The first one is the requirements-min.txt_ file, which lists the package dependencies and their minimum versions for -installing PyNWB. These dependencies are read by setup.py_ into the `install_requires` key, with the adjustment that -the `'=='` listed in `requirements-min.txt` are replaced with `'>='` to reflect that they are minimum versions. +installing PyNWB. -The second one is requirements.txt_ which contain a list of pinned (concrete) dependencies to reproduce +The second one is requirements.txt_, which lists the pinned (concrete) dependencies to reproduce an entire development environment to use PyNWB. -The third one is requirements-dev.txt_ which contain a list of pinned (concrete) dependencies to reproduce +The third one is requirements-dev.txt_, which lists the pinned (concrete) dependencies to reproduce an entire development environment to use PyNWB, run PyNWB tests, check code style, compute coverage, and create test environments. -The final one is requirements-doc.txt_ which contain a list of dependencies to generate the documentation for PyNWB. +The fourth one is requirements-doc.txt_, which lists the dependencies to generate the documentation for PyNWB. Both this file and `requirements.txt` are used by ReadTheDocs_ to initialize the local environment for Sphinx to run. +The final one is within setup.py_, which contains a list of package dependencies and their version ranges allowed for +running PyNWB. + In order to check the status of the required packages, requires.io_ is used to create a badge on the project README_. If all the required packages are up to date, a green badge appears. diff --git a/docs/source/update_requirements.rst b/docs/source/update_requirements.rst index 991c74712..1ef434d6d 100644 --- a/docs/source/update_requirements.rst +++ b/docs/source/update_requirements.rst @@ -46,7 +46,7 @@ the following scripts: cd pynwb - # Set the requirements file to update + # Set the requirements file to update: requirements-dev.txt or requirements-doc.txt target_requirements=requirements-dev.txt mkvirtualenv pynwb-requirements diff --git a/license.txt b/license.txt index a0a700803..2fc29210c 100644 --- a/license.txt +++ b/license.txt @@ -1,4 +1,4 @@ -“pynwb” Copyright (c) 2017-2020, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. +“pynwb” Copyright (c) 2017-2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: diff --git a/requirements-dev.txt b/requirements-dev.txt index f5a4edb2d..27b099d30 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -1,7 +1,9 @@ -codecov==2.1.8 -coverage==5.2 -flake8==3.8.3 -flake8-debugger==3.1.0 -flake8-print==3.1.4 -importlib-metadata<2 -tox==3.17.1 +# pinned dependencies to reproduce an entire development environment to use PyNWB, run PyNWB tests, check code style, +# compute coverage, and create test environments +codecov==2.1.11 +coverage==5.5 +flake8==3.9.2 +flake8-debugger==4.0.0 +flake8-print==4.0.0 +importlib-metadata==4.6.1 +tox==3.23.1 diff --git a/requirements-doc.txt b/requirements-doc.txt index ff0b741c4..5f7ceff81 100644 --- a/requirements-doc.txt +++ b/requirements-doc.txt @@ -1,5 +1,6 @@ +# dependencies to generate the documentation for PyNWB sphinx matplotlib sphinx_rtd_theme sphinx-gallery -allensdk +allensdk # note that as of allensdk 2.10.0, python 3.8 is not supported diff --git a/requirements-min.txt b/requirements-min.txt index 03b08d65b..9b9d14bd3 100644 --- a/requirements-min.txt +++ b/requirements-min.txt @@ -1,6 +1,7 @@ -# these minimum requirements specify '==' for testing; setup.py replaces '==' with '>=' -h5py==2.9 # support for setting attrs to lists of utf-8 added in 2.9 -hdmf==2.4 +# minimum versions of package dependencies for installing PyNWB +h5py==2.10 # support for selection of datasets with list of indices added in 2.10 +hdmf==3.0.1 numpy==1.16 -pandas==0.23 +pandas==1.0.5 python-dateutil==2.7 +setuptools diff --git a/requirements.txt b/requirements.txt index 7f4c5c04b..ba1493ad7 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,7 @@ -h5py==2.10.0 -hdmf==2.4.0 -numpy==1.18.5 -pandas==0.25.3 +# pinned dependencies to reproduce an entire development environment to use PyNWB +h5py==3.3.0 +hdmf==3.0.1 +numpy==1.21.0 +pandas==1.3.0 python-dateutil==2.8.1 +setuptools==57.1.0 diff --git a/setup.cfg b/setup.cfg index 1b3b3aa0e..d20424c74 100644 --- a/setup.cfg +++ b/setup.cfg @@ -15,18 +15,26 @@ exclude = .git, .tox, __pycache__, - docs/_build/, + build/, dist/, src/pynwb/nwb-schema/ + docs/_build/, docs/source/conf.py - versioneer.py + docs/source/tutorials/ + versioneer.py, + src/pynwb/_version.py + src/pynwb/_due.py per-file-ignores = - docs/gallery/*:E402, - docs/source/tutorials/*:E402 + docs/gallery/*:E402,T001 + docs/source/tutorials/*:E402,T001 src/pynwb/io/__init__.py:F401 src/pynwb/legacy/io/__init__.py:F401 tests/integration/__init__.py:F401 src/pynwb/testing/__init__.py:F401 + src/pynwb/validate.py:T001 + setup.py:T001 + test.py:T001 + scripts/*:T001 [metadata] description-file = README.rst diff --git a/setup.py b/setup.py index 5a2dcce91..f862c3446 100755 --- a/setup.py +++ b/setup.py @@ -12,10 +12,14 @@ schema_dir = 'nwb-schema/core' -with open('requirements-min.txt', 'r') as fp: - # replace == with >= and remove trailing comments and spaces - reqs = [x.replace('==', '>=').split('#')[0].strip() for x in fp] - reqs = [x for x in reqs if x] # remove empty strings +reqs = [ + 'h5py>=2.9,<4', + 'hdmf>=3.0.1,<4', + 'numpy>=1.16,<1.22', + 'pandas>=1.0.5,<2', + 'python-dateutil>=2.7,<3', + 'setuptools' +] print(reqs) @@ -36,10 +40,9 @@ 'package_data': {'pynwb': ["%s/*.yaml" % schema_dir, "%s/*.json" % schema_dir]}, 'classifiers': [ "Programming Language :: Python", - "Programming Language :: Python :: 3.5", - "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", "License :: OSI Approved :: BSD License", "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", diff --git a/src/pynwb/__init__.py b/src/pynwb/__init__.py index b98b05157..f91ffc0d7 100644 --- a/src/pynwb/__init__.py +++ b/src/pynwb/__init__.py @@ -41,10 +41,8 @@ def _get_resources(): __NS_CATALOG = NamespaceCatalog(NWBGroupSpec, NWBDatasetSpec, NWBNamespace) hdmf_typemap = hdmf.common.get_type_map() -__NS_CATALOG.merge(hdmf_typemap.namespace_catalog) - __TYPE_MAP = TypeMap(__NS_CATALOG) -__TYPE_MAP.merge(hdmf_typemap) +__TYPE_MAP.merge(hdmf_typemap, ns_catalog=True) @docval({'name': 'extensions', 'type': (str, TypeMap, list), @@ -185,7 +183,7 @@ def get_sum(self, a, b): """ neurodata_type, namespace = getargs('neurodata_type', 'namespace', kwargs) - return __TYPE_MAP.get_container_cls(namespace, neurodata_type) + return __TYPE_MAP.get_dt_container_cls(neurodata_type, namespace) @docval({'name': 'io', 'type': HDMFIO, 'doc': 'the HDMFIO object to read from'}, @@ -281,3 +279,21 @@ def export(self, **kwargs): from ._version import get_versions # noqa: E402 __version__ = get_versions()['version'] del get_versions + +from ._due import due, BibTeX # noqa: E402 +due.cite(BibTeX(""" +@article {R{\"u}bel2021.03.13.435173, + author = {R{\"u}bel, Oliver and Tritt, Andrew and Ly, Ryan and Dichter, Benjamin K. and Ghosh, Satrajit and Niu, Lawrence and Soltesz, Ivan and Svoboda, Karel and Frank, Loren and Bouchard, Kristofer E.}, + title = {The Neurodata Without Borders ecosystem for neurophysiological data science}, + elocation-id = {2021.03.13.435173}, + year = {2021}, + doi = {10.1101/2021.03.13.435173}, + publisher = {Cold Spring Harbor Laboratory}, + abstract = {The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB{\textquoteright}s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.Competing Interest StatementThe authors have declared no competing interest.}, + URL = {https://www.biorxiv.org/content/early/2021/03/15/2021.03.13.435173}, + eprint = {https://www.biorxiv.org/content/early/2021/03/15/2021.03.13.435173.full.pdf}, + journal = {bioRxiv} +} +"""), description="The Neurodata Without Borders ecosystem for neurophysiological data science", # noqa: E501 + path="pynwb/", version=__version__, cite_module=True) +del due, BibTeX diff --git a/src/pynwb/_due.py b/src/pynwb/_due.py new file mode 100644 index 000000000..9a1c4dd08 --- /dev/null +++ b/src/pynwb/_due.py @@ -0,0 +1,74 @@ +# emacs: at the end of the file +# ex: set sts=4 ts=4 sw=4 et: +# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### # +""" + +Stub file for a guaranteed safe import of duecredit constructs: if duecredit +is not available. + +To use it, place it into your project codebase to be imported, e.g. copy as + + cp stub.py /path/tomodule/module/due.py + +Note that it might be better to avoid naming it duecredit.py to avoid shadowing +installed duecredit. + +Then use in your code as + + from .due import due, Doi, BibTeX, Text + +See https://github.com/duecredit/duecredit/blob/master/README.md for examples. + +Origin: Originally a part of the duecredit +Copyright: 2015-2019 DueCredit developers +License: BSD-2 +""" + +__version__ = '0.0.8' + + +class InactiveDueCreditCollector(object): + """Just a stub at the Collector which would not do anything""" + def _donothing(self, *args, **kwargs): + """Perform no good and no bad""" + pass + + def dcite(self, *args, **kwargs): + """If I could cite I would""" + def nondecorating_decorator(func): + return func + return nondecorating_decorator + + active = False + activate = add = cite = dump = load = _donothing + + def __repr__(self): + return self.__class__.__name__ + '()' + + +def _donothing_func(*args, **kwargs): + """Perform no good and no bad""" + pass + + +try: + from duecredit import due, BibTeX, Doi, Url, Text + if 'due' in locals() and not hasattr(due, 'cite'): + raise RuntimeError( + "Imported due lacks .cite. DueCredit is now disabled") +except Exception as e: + if not isinstance(e, ImportError): + import logging + logging.getLogger("duecredit").error( + "Failed to import duecredit due to %s" % str(e)) + # Initiate due stub + due = InactiveDueCreditCollector() + BibTeX = Doi = Url = Text = _donothing_func + +# Emacs mode definitions +# Local Variables: +# mode: python +# py-indent-offset: 4 +# tab-width: 4 +# indent-tabs-mode: nil +# End: diff --git a/src/pynwb/base.py b/src/pynwb/base.py index fceb6776e..81e71fdcd 100644 --- a/src/pynwb/base.py +++ b/src/pynwb/base.py @@ -1,8 +1,8 @@ from warnings import warn from collections.abc import Iterable -from hdmf.utils import docval, getargs, popargs, call_docval_func -from hdmf.common import DynamicTable +from hdmf.utils import docval, getargs, popargs, call_docval_func, get_docval +from hdmf.common import DynamicTable, VectorData from . import register_class, CORE_NAMESPACE @@ -92,7 +92,8 @@ class TimeSeries(NWBDataInterface): "rate", "starting_time_unit", "control", - "control_description") + "control_description", + "continuity") __time_unit = "seconds" @@ -119,10 +120,19 @@ class TimeSeries(NWBDataInterface): {'name': 'control', 'type': Iterable, 'doc': 'Numerical labels that apply to each element in data', 'default': None}, {'name': 'control_description', 'type': Iterable, 'doc': 'Description of each control value', - 'default': None}) + 'default': None}, + {'name': 'continuity', 'type': str, 'default': None, 'enum': ["continuous", "instantaneous", "step"], + 'doc': 'Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or' + '"step". For example, a voltage trace would be "continuous", because samples are recorded from a ' + 'continuous process. An array of lick times would be "instantaneous", because the data represents ' + 'distinct moments in time. Times of image presentations would be "step" because the picture ' + 'remains the same until the next time-point. This field is optional, but is useful in providing ' + 'information about the underlying data. It may inform the way this data is interpreted, the way it ' + 'is visualized, and what analysis methods are applicable.'}) def __init__(self, **kwargs): """Create a TimeSeries object """ + call_docval_func(super(TimeSeries, self).__init__, kwargs) keys = ("resolution", "comments", @@ -130,7 +140,8 @@ def __init__(self, **kwargs): "conversion", "unit", "control", - "control_description") + "control_description", + "continuity") for key in keys: val = kwargs.get(key) if val is not None: @@ -271,3 +282,16 @@ def __init__(self, **kwargs): super(Images, self).__init__(name, **kwargs) self.description = description self.images = images + + +@register_class('TimeSeriesReferenceVectorData', CORE_NAMESPACE) +class TimeSeriesReferenceVectorData(VectorData): + """ + Column storing references to a TimeSeries (rows). For each TimeSeries this VectorData + column stores the start_index and count to indicate the range in time to be selected + as well as an object reference to the TimeSeries. + """ + + @docval(*get_docval(VectorData.__init__)) + def __init__(self, **kwargs): + call_docval_func(super().__init__, kwargs) diff --git a/src/pynwb/core.py b/src/pynwb/core.py index 2a5dc9dc5..317dd1281 100644 --- a/src/pynwb/core.py +++ b/src/pynwb/core.py @@ -1,4 +1,5 @@ import numpy as np +from warnings import warn from hdmf import Container, Data from hdmf.container import AbstractContainer, MultiContainerInterface as hdmf_MultiContainerInterface, Table @@ -88,14 +89,39 @@ def extend(self, arg): @register_class('ScratchData', CORE_NAMESPACE) class ScratchData(NWBData): - __nwbfields__ = ('description',) + __nwbfields__ = ('description', ) @docval({'name': 'name', 'type': str, 'doc': 'the name of this container'}, {'name': 'data', 'type': ('scalar_data', 'array_data', 'data', Data), 'doc': 'the source of the data'}, - {'name': 'description', 'type': str, 'doc': 'description of the data'}) + {'name': 'notes', 'type': str, + 'doc': 'notes about the data. This argument will be deprecated. Use description instead', 'default': ''}, + {'name': 'description', 'type': str, 'doc': 'notes about the data', 'default': None}) def __init__(self, **kwargs): call_docval_func(super().__init__, kwargs) - self.description = getargs('description', kwargs) + notes, description = getargs('notes', 'description', kwargs) + if notes != '': + warn('The `notes` argument of ScratchData.__init__ will be deprecated. Use description instead.', + PendingDeprecationWarning) + if notes != '' and description != '': + raise ValueError('Cannot provide both notes and description to ScratchData.__init__. The description ' + 'argument is recommended.') + description = notes + if not description: + warn('ScratchData.description will be required in a future major release of PyNWB.', + PendingDeprecationWarning) + self.description = description + + @property + def notes(self): + warn('Use of ScratchData.notes will be deprecated. Use ScratchData.description instead.', + PendingDeprecationWarning) + return self.description + + @notes.setter + def notes(self, value): + warn('Use of ScratchData.notes will be deprecated. Use ScratchData.description instead.', + PendingDeprecationWarning) + self.description = value class NWBTable(Table): diff --git a/src/pynwb/ecephys.py b/src/pynwb/ecephys.py index bb9ee7344..91160753d 100644 --- a/src/pynwb/ecephys.py +++ b/src/pynwb/ecephys.py @@ -49,7 +49,8 @@ class ElectricalSeries(TimeSeries): __nwbfields__ = ({'name': 'electrodes', 'required_name': 'electrodes', 'doc': 'the electrodes that generated this electrical series', 'child': True}, - 'channel_conversion') + 'channel_conversion', + 'filtering') @docval(*get_docval(TimeSeries.__init__, 'name'), # required {'name': 'data', 'type': ('array_data', 'data', TimeSeries), # required @@ -66,13 +67,21 @@ class ElectricalSeries(TimeSeries): "to support the storage of electrical recordings as native values generated by data acquisition systems. " "If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all" " channels.", 'default': None}, + {'name': 'filtering', 'type': str, 'doc': + "Filtering applied to all channels of the data. For example, if this ElectricalSeries represents " + "high-pass-filtered data (also known as AP Band), then this value could be 'High-pass 4-pole Bessel " + "filter at 500 Hz'. If this ElectricalSeries represents low-pass-filtered LFP data and the type of " + "filter is unknown, then this value could be 'Low-pass filter at 300 Hz'. If a non-standard filter " + "type is used, provide as much detail about the filter properties as possible.", 'default': None}, *get_docval(TimeSeries.__init__, 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', 'description', 'control', 'control_description')) def __init__(self, **kwargs): - name, electrodes, data, channel_conversion = popargs('name', 'electrodes', 'data', 'channel_conversion', kwargs) + name, electrodes, data, channel_conversion, filtering = popargs('name', 'electrodes', 'data', + 'channel_conversion', 'filtering', kwargs) super(ElectricalSeries, self).__init__(name, data, 'volts', **kwargs) self.electrodes = electrodes self.channel_conversion = channel_conversion + self.filtering = filtering @register_class('SpikeEventSeries', CORE_NAMESPACE) diff --git a/src/pynwb/file.py b/src/pynwb/file.py index 296adab0f..107c71710 100644 --- a/src/pynwb/file.py +++ b/src/pynwb/file.py @@ -7,14 +7,16 @@ import numpy as np import pandas as pd -from hdmf.utils import docval, getargs, call_docval_func, get_docval +from hdmf.utils import docval, getargs, call_docval_func, get_docval, popargs from . import register_class, CORE_NAMESPACE from .base import TimeSeries, ProcessingModule from .device import Device from .epoch import TimeIntervals from .ecephys import ElectrodeGroup -from .icephys import IntracellularElectrode, SweepTable, PatchClampSeries +from .icephys import (IntracellularElectrode, SweepTable, PatchClampSeries, IntracellularRecordingsTable, + SimultaneousRecordingsTable, SequentialRecordingsTable, RepetitionsTable, + ExperimentalConditionsTable) from .ophys import ImagingPlane from .ogen import OptogeneticStimulusSite from .misc import Units @@ -44,18 +46,33 @@ class Subject(NWBContainer): 'species', 'subject_id', 'weight', - 'date_of_birth' + 'date_of_birth', + 'strain' ) - @docval({'name': 'age', 'type': str, 'doc': 'the age of the subject', 'default': None}, - {'name': 'description', 'type': str, 'doc': 'a description of the subject', 'default': None}, - {'name': 'genotype', 'type': str, 'doc': 'the genotype of the subject', 'default': None}, - {'name': 'sex', 'type': str, 'doc': 'the sex of the subject', 'default': None}, - {'name': 'species', 'type': str, 'doc': 'the species of the subject', 'default': None}, - {'name': 'subject_id', 'type': str, 'doc': 'a unique identifier for the subject', 'default': None}, - {'name': 'weight', 'type': str, 'doc': 'the weight of the subject', 'default': None}, + @docval({'name': 'age', 'type': str, + 'doc': ('The age of the subject. The ISO 8601 Duration format is recommended, e.g., "P90D" for ' + '90 days old.'), 'default': None}, + {'name': 'description', 'type': str, + 'doc': 'A description of the subject, e.g., "mouse A10".', 'default': None}, + {'name': 'genotype', 'type': str, + 'doc': 'The genotype of the subject, e.g., "Sst-IRES-Cre/wt;Ai32(RCL-ChR2(H134R)_EYFP)/wt".', + 'default': None}, + {'name': 'sex', 'type': str, + 'doc': ('The sex of the subject. Using "F" (female), "M" (male), "U" (unknown), or "O" (other) ' + 'is recommended.'), 'default': None}, + {'name': 'species', 'type': str, + 'doc': ('The species of the subject. The formal latin binomal name is recommended, e.g., "Mus musculus"'), + 'default': None}, + {'name': 'subject_id', 'type': str, 'doc': 'A unique identifier for the subject, e.g., "A10"', + 'default': None}, + {'name': 'weight', 'type': (float, str), + 'doc': ('The weight of the subject, including units. Using kilograms is recommended. e.g., "0.02 kg". ' + 'If a float is provided, then the weight will be stored as "[value] kg".'), + 'default': None}, {'name': 'date_of_birth', 'type': datetime, 'default': None, - 'doc': 'datetime of date of birth. May be supplied instead of age.'}) + 'doc': 'The datetime of the date of birth. May be supplied instead of age.'}, + {'name': 'strain', 'type': str, 'doc': 'The strain of the subject, e.g., "C57BL/6J"', 'default': None}) def __init__(self, **kwargs): kwargs['name'] = 'subject' call_docval_func(super(Subject, self).__init__, kwargs) @@ -65,7 +82,11 @@ def __init__(self, **kwargs): self.sex = getargs('sex', kwargs) self.species = getargs('species', kwargs) self.subject_id = getargs('subject_id', kwargs) - self.weight = getargs('weight', kwargs) + weight = getargs('weight', kwargs) + if isinstance(weight, float): + weight = str(weight) + ' kg' + self.weight = weight + self.strain = getargs('strain', kwargs) date_of_birth = getargs('date_of_birth', kwargs) if date_of_birth and date_of_birth.tzinfo is None: self.date_of_birth = _add_missing_timezone(date_of_birth) @@ -198,8 +219,36 @@ class NWBFile(MultiContainerInterface): {'name': 'sweep_table', 'child': True, 'required_name': 'sweep_table'}, {'name': 'invalid_times', 'child': True, 'required_name': 'invalid_times'}, 'epoch_tags', - {'name': 'icephys_filtering', 'settable': False}) - # icephys_filtering is temporary. /intracellular_ephys/filtering dataset will be deprecated + # icephys_filtering is temporary. /intracellular_ephys/filtering dataset will be deprecated + {'name': 'icephys_filtering', 'settable': False}, + {'name': 'intracellular_recordings', 'child': True, + 'required_name': 'intracellular_recordings', + 'doc': 'IntracellularRecordingsTable table to group together a stimulus and response ' + 'from a single intracellular electrode and a single simultaneous recording.'}, + {'name': 'icephys_simultaneous_recordings', + 'child': True, + 'required_name': 'simultaneous_recordings', + 'doc': 'SimultaneousRecordingsTable table for grouping different intracellular recordings from' + 'the IntracellularRecordingsTable table together that were recorded simultaneously ' + 'from different electrodes'}, + {'name': 'icephys_sequential_recordings', + 'child': True, + 'required_name': 'sequential_recordings', + 'doc': 'A table for grouping different simultaneous intracellular recording from the ' + 'SimultaneousRecordingsTable table together. This is typically used to group ' + 'together simultaneous recordings where the a sequence of stimuli of the same ' + 'type with varying parameters have been presented in a sequence.'}, + {'name': 'icephys_repetitions', + 'child': True, + 'required_name': 'repetitions', + 'doc': 'A table for grouping different intracellular recording sequential recordings together.' + 'With each SweepSequence typically representing a particular type of stimulus, the ' + 'RepetitionsTable table is typically used to group sets of stimuli applied in sequence.'}, + {'name': 'icephys_experimental_conditions', + 'child': True, + 'required_name': 'experimental_conditions', + 'doc': 'A table for grouping different intracellular recording repetitions together that ' + 'belong to the same experimental experimental_conditions.'}) @docval({'name': 'session_description', 'type': str, 'doc': 'a description of the session where this data was generated'}, @@ -291,7 +340,19 @@ class NWBFile(MultiContainerInterface): {'name': 'scratch', 'type': (list, tuple), 'doc': 'scratch data', 'default': None}, {'name': 'icephys_electrodes', 'type': (list, tuple), - 'doc': 'IntracellularElectrodes that belong to this NWBFile.', 'default': None}) + 'doc': 'IntracellularElectrodes that belong to this NWBFile.', 'default': None}, + {'name': 'icephys_filtering', 'type': str, 'default': None, + 'doc': '[DEPRECATED] Use IntracellularElectrode.filtering instead. Description of filtering used.'}, + {'name': 'intracellular_recordings', 'type': IntracellularRecordingsTable, 'default': None, + 'doc': 'the IntracellularRecordingsTable table that belongs to this NWBFile'}, + {'name': 'icephys_simultaneous_recordings', 'type': SimultaneousRecordingsTable, 'default': None, + 'doc': 'the SimultaneousRecordingsTable table that belongs to this NWBFile'}, + {'name': 'icephys_sequential_recordings', 'type': SequentialRecordingsTable, 'default': None, + 'doc': 'the SequentialRecordingsTable table that belongs to this NWBFile'}, + {'name': 'icephys_repetitions', 'type': RepetitionsTable, 'default': None, + 'doc': 'the RepetitionsTable table that belongs to this NWBFile'}, + {'name': 'icephys_experimental_conditions', 'type': ExperimentalConditionsTable, 'default': None, + 'doc': 'the ExperimentalConditionsTable table that belongs to this NWBFile'}) def __init__(self, **kwargs): kwargs['name'] = 'root' call_docval_func(super(NWBFile, self).__init__, kwargs) @@ -351,6 +412,12 @@ def __init__(self, **kwargs): 'surgery', 'virus', 'stimulus_notes', + 'icephys_filtering', # DEPRECATION warning will be raised in the setter when calling setattr in the loop + 'intracellular_recordings', + 'icephys_simultaneous_recordings', + 'icephys_sequential_recordings', + 'icephys_repetitions', + 'icephys_experimental_conditions' ] for attr in fieldnames: setattr(self, attr, kwargs.get(attr, None)) @@ -420,6 +487,17 @@ def ic_electrodes(self): warn("NWBFile.ic_electrodes has been replaced by NWBFile.icephys_electrodes.", DeprecationWarning) return self.icephys_electrodes + @property + def icephys_filtering(self): + return self.fields.get('icephys_filtering') + + @icephys_filtering.setter + def icephys_filtering(self, val): + if val is not None: + warn("Use of icephys_filtering is deprecated. Use the IntracellularElectrode.filtering field instead", + DeprecationWarning) + self.fields['icephys_filtering'] = val + def add_ic_electrode(self, *args, **kwargs): """ This method is deprecated and will be removed in future versions. Please @@ -508,6 +586,8 @@ def add_electrode_column(self, **kwargs): {'name': 'rel_z', 'type': 'float', 'doc': 'the z coordinate within the electrode group', 'default': None}, {'name': 'reference', 'type': str, 'doc': 'Description of the reference used for this electrode.', 'default': None}, + {'name': 'enforce_unique_id', 'type': bool, 'doc': 'enforce that the id in the table must be unique', + 'default': True}, allow_extra=True) def add_electrode(self, **kwargs): """ @@ -655,48 +735,245 @@ def _update_sweep_table(self, nwbdata): self._check_sweep_table() self.sweep_table.add_entry(nwbdata) - @docval({'name': 'nwbdata', 'type': (NWBDataInterface, DynamicTable)}) - def add_acquisition(self, nwbdata): + @docval({'name': 'nwbdata', 'type': (NWBDataInterface, DynamicTable)}, + {'name': 'use_sweep_table', 'type': bool, 'default': False, 'doc': 'Use the deprecated SweepTable'}) + def add_acquisition(self, **kwargs): + nwbdata = popargs('nwbdata', kwargs) self._add_acquisition_internal(nwbdata) - self._update_sweep_table(nwbdata) - - @docval({'name': 'timeseries', 'type': TimeSeries}) - def add_stimulus(self, timeseries): + use_sweep_table = popargs('use_sweep_table', kwargs) + if use_sweep_table: + self._update_sweep_table(nwbdata) + + @docval({'name': 'timeseries', 'type': TimeSeries}, + {'name': 'use_sweep_table', 'type': bool, 'default': False, 'doc': 'Use the deprecated SweepTable'}) + def add_stimulus(self, **kwargs): + timeseries = popargs('timeseries', kwargs) self._add_stimulus_internal(timeseries) - self._update_sweep_table(timeseries) - - @docval({'name': 'timeseries', 'type': TimeSeries}) - def add_stimulus_template(self, timeseries): + use_sweep_table = popargs('use_sweep_table', kwargs) + if use_sweep_table: + self._update_sweep_table(timeseries) + + @docval({'name': 'timeseries', 'type': TimeSeries}, + {'name': 'use_sweep_table', 'type': bool, 'default': False, 'doc': 'Use the deprecated SweepTable'}) + def add_stimulus_template(self, **kwargs): + timeseries = popargs('timeseries', kwargs) self._add_stimulus_template_internal(timeseries) - self._update_sweep_table(timeseries) + use_sweep_table = popargs('use_sweep_table', kwargs) + if use_sweep_table: + self._update_sweep_table(timeseries) + + @docval(returns='The NWBFile.intracellular_recordings table', rtype=IntracellularRecordingsTable) + def get_intracellular_recordings(self): + """ + Get the NWBFile.intracellular_recordings table. + + In contrast to NWBFile.intracellular_recordings, this function will create the + IntracellularRecordingsTable table if not yet done, whereas NWBFile.intracellular_recordings + will return None if the table is currently not being used. + """ + if self.intracellular_recordings is None: + self.intracellular_recordings = IntracellularRecordingsTable() + return self.intracellular_recordings + + @docval(*get_docval(IntracellularRecordingsTable.add_recording), + returns='Integer index of the row that was added to IntracellularRecordingsTable', + rtype=int, + allow_extra=True) + def add_intracellular_recording(self, **kwargs): + """ + Add a intracellular recording to the intracellular_recordings table. If the + electrode, stimulus, and/or response do not exsist yet in the NWBFile, then + they will be added to this NWBFile before adding them to the table. + + Note: For more complex organization of intracellular recordings you may also be + interested in the related SimultaneousRecordingsTable, SequentialRecordingsTable, + RepetitionsTable, and ExperimentalConditionsTable tables an the related function + of NWBFile: add_icephsy_simultaneous_recording, add_icephys_sequential_recording, + add_icephys_repetition, and add_icephys_condition. + """ + # Add the stimulus, response, and electrode to the file if they don't exist yet + stimulus, response, electrode = getargs('stimulus', 'response', 'electrode', kwargs) + if (stimulus is not None and + (stimulus.name not in self.stimulus and + stimulus.name not in self.stimulus_template)): + self.add_stimulus(stimulus, use_sweep_table=False) + if response is not None and response.name not in self.acquisition: + self.add_acquisition(response, use_sweep_table=False) + if electrode is not None and electrode.name not in self.icephys_electrodes: + self.add_icephys_electrode(electrode) + # make sure the intracellular recordings table exists and if not create it using get_intracellular_recordings + # Add the recoding to the intracellular_recordings table + return call_docval_func(self.get_intracellular_recordings().add_recording, kwargs) + + @docval(returns='The NWBFile.icephys_simultaneous_recordings table', rtype=SimultaneousRecordingsTable) + def get_icephys_simultaneous_recordings(self): + """ + Get the NWBFile.icephys_simultaneous_recordings table. + + In contrast to NWBFile.icephys_simultaneous_recordings, this function will create the + SimultaneousRecordingsTable table if not yet done, whereas NWBFile.icephys_simultaneous_recordings + will return None if the table is currently not being used. + """ + if self.icephys_simultaneous_recordings is None: + self.icephys_simultaneous_recordings = SimultaneousRecordingsTable(self.get_intracellular_recordings()) + return self.icephys_simultaneous_recordings + + @docval(*get_docval(SimultaneousRecordingsTable.add_simultaneous_recording), + returns='Integer index of the row that was added to SimultaneousRecordingsTable', + rtype=int, + allow_extra=True) + def add_icephys_simultaneous_recording(self, **kwargs): + """ + Add a new simultaneous recording to the icephys_simultaneous_recordings table + """ + return call_docval_func(self.get_icephys_simultaneous_recordings().add_simultaneous_recording, kwargs) + + @docval(returns='The NWBFile.icephys_sequential_recordings table', rtype=SequentialRecordingsTable) + def get_icephys_sequential_recordings(self): + """ + Get the NWBFile.icephys_sequential_recordings table. + + In contrast to NWBFile.icephys_sequential_recordings, this function will create the + IntracellularRecordingsTable table if not yet done, whereas NWBFile.icephys_sequential_recordings + will return None if the table is currently not being used. + """ + if self.icephys_sequential_recordings is None: + self.icephys_sequential_recordings = SequentialRecordingsTable(self.get_icephys_simultaneous_recordings()) + return self.icephys_sequential_recordings + + @docval(*get_docval(SequentialRecordingsTable.add_sequential_recording), + returns='Integer index of the row that was added to SequentialRecordingsTable', + rtype=int, + allow_extra=True) + def add_icephys_sequential_recording(self, **kwargs): + """ + Add a new sequential recording to the icephys_sequential_recordings table + """ + self.get_icephys_sequential_recordings() + return call_docval_func(self.icephys_sequential_recordings.add_sequential_recording, kwargs) + + @docval(returns='The NWBFile.icephys_repetitions table', rtype=RepetitionsTable) + def get_icephys_repetitions(self): + """ + Get the NWBFile.icephys_repetitions table. + + In contrast to NWBFile.icephys_repetitions, this function will create the + RepetitionsTable table if not yet done, whereas NWBFile.icephys_repetitions + will return None if the table is currently not being used. + """ + if self.icephys_repetitions is None: + self.icephys_repetitions = RepetitionsTable(self.get_icephys_sequential_recordings()) + return self.icephys_repetitions + + @docval(*get_docval(RepetitionsTable.add_repetition), + returns='Integer index of the row that was added to RepetitionsTable', + rtype=int, + allow_extra=True) + def add_icephys_repetition(self, **kwargs): + """ + Add a new repetition to the RepetitionsTable table + """ + return call_docval_func(self.get_icephys_repetitions().add_repetition, kwargs) + + @docval(returns='The NWBFile.icephys_experimental_conditions table', rtype=ExperimentalConditionsTable) + def get_icephys_experimental_conditions(self): + """ + Get the NWBFile.icephys_experimental_conditions table. + + In contrast to NWBFile.icephys_experimental_conditions, this function will create the + RepetitionsTable table if not yet done, whereas NWBFile.icephys_experimental_conditions + will return None if the table is currently not being used. + """ + if self.icephys_experimental_conditions is None: + self.icephys_experimental_conditions = ExperimentalConditionsTable(self.get_icephys_repetitions()) + return self.icephys_experimental_conditions + + @docval(*get_docval(ExperimentalConditionsTable.add_experimental_condition), + returns='Integer index of the row that was added to ExperimentalConditionsTable', + rtype=int, + allow_extra=True) + def add_icephys_experimental_condition(self, **kwargs): + """ + Add a new condition to the ExperimentalConditionsTable table + """ + return call_docval_func(self.get_icephys_experimental_conditions().add_experimental_condition, kwargs) + + def get_icephys_meta_parent_table(self): + """ + Get the top-most table in the intracellular ephys metadata table hierarchy that exists in this NWBFile. + + The intracellular ephys metadata consists of a hierarchy of DynamicTables, i.e., + experimental_conditions --> repetitions --> sequential_recordings --> + simultaneous_recordings --> intracellular_recordings etc. + In a given NWBFile not all tables may exist. This convenience functions returns the top-most + table that exists in this file. E.g., if the file contains only the simultaneous_recordings + and intracellular_recordings tables then the function would return the simultaneous_recordings table. + Similarly, if the file contains all tables then it will return the experimental_conditions table. + + :returns: DynamicTable object or None + """ + if self.icephys_experimental_conditions is not None: + return self.icephys_experimental_conditions + elif self.icephys_repetitions is not None: + return self.icephys_repetitions + elif self.icephys_sequential_recordings is not None: + return self.icephys_sequential_recordings + elif self.icephys_simultaneous_recordings is not None: + return self.icephys_simultaneous_recordings + elif self.intracellular_recordings is not None: + return self.intracellular_recordings + else: + return None @docval({'name': 'data', 'type': ('scalar_data', np.ndarray, list, tuple, pd.DataFrame, DynamicTable, NWBContainer, ScratchData), 'doc': 'The data to add to the scratch space.'}, {'name': 'name', 'type': str, - 'doc': ('The name of the data. Required only when passing in a scalar, numpy.ndarray, ' - 'list, tuple, or pandas.DataFrame'), + 'doc': 'The name of the data. Required only when passing in a scalar, numpy.ndarray, list, or tuple', + 'default': None}, + {'name': 'notes', 'type': str, + 'doc': ('Notes to add to the data. Only used when passing in numpy.ndarray, list, or tuple. This ' + 'argument is not recommended. Use the `description` argument instead.'), 'default': None}, + {'name': 'table_description', 'type': str, + 'doc': ('Description for the internal DynamicTable used to store a pandas.DataFrame. This ' + 'argument is not recommended. Use the `description` argument instead.'), + 'default': ''}, {'name': 'description', 'type': str, 'doc': ('Description of the data. Required only when passing in a scalar, numpy.ndarray, ' 'list, tuple, or pandas.DataFrame. Ignored when passing in an NWBContainer, ' 'DynamicTable, or ScratchData object.'), 'default': None}) def add_scratch(self, **kwargs): - '''Add data to the scratch space.''' - data, name, description = getargs('data', 'name', 'description', kwargs) + '''Add data to the scratch space''' + data, name, notes, table_description, description = getargs('data', 'name', 'notes', 'table_description', + 'description', kwargs) + if notes is not None or table_description != '': + warn('Use of the `notes` or `table_description` argument will be removed in a future version of PyNWB. ' + 'Use the `description` argument instead.', PendingDeprecationWarning) + if description is not None: + raise ValueError('Cannot call add_scratch with (notes or table_description) and description') + if isinstance(data, (str, int, float, bytes, np.ndarray, list, tuple, pd.DataFrame)): if name is None: msg = ('A name is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, ' 'list, tuple, or pandas.DataFrame as scratch data.') raise ValueError(msg) - if description is None: - msg = ('A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, ' - 'list, tuple, or pandas.DataFrame as scratch data.') - raise ValueError(msg) if isinstance(data, pd.DataFrame): + if table_description != '': + description = table_description # remove after deprecation + if description is None: + msg = ('A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, ' + 'list, tuple, or pandas.DataFrame as scratch data.') + raise ValueError(msg) data = DynamicTable.from_dataframe(df=data, name=name, table_description=description) else: + if notes is not None: + description = notes # remove after deprecation + if description is None: + msg = ('A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, ' + 'list, tuple, or pandas.DataFrame as scratch data.') + raise ValueError(msg) data = ScratchData(name=name, data=data, description=description) else: if name is not None: @@ -707,8 +984,8 @@ def add_scratch(self, **kwargs): 'DynamicTable to scratch.') return self._add_scratch(data) - @docval({'name': 'name', 'type': str, 'help': 'the name of the object to get'}, - {'name': 'convert', 'type': bool, 'help': 'return the original data, not the NWB object', 'default': True}) + @docval({'name': 'name', 'type': str, 'doc': 'the name of the object to get'}, + {'name': 'convert', 'type': bool, 'doc': 'return the original data, not the NWB object', 'default': True}) def get_scratch(self, **kwargs): '''Get data from the scratch space''' name, convert = getargs('name', 'convert', kwargs) diff --git a/src/pynwb/icephys.py b/src/pynwb/icephys.py index 156c97c04..f76c72d00 100644 --- a/src/pynwb/icephys.py +++ b/src/pynwb/icephys.py @@ -1,12 +1,28 @@ import warnings -from hdmf.common import DynamicTable -from hdmf.utils import docval, popargs, call_docval_func, get_docval +from hdmf.common import DynamicTable, AlignedDynamicTable +from hdmf.utils import docval, popargs, call_docval_func, get_docval, getargs from . import register_class, CORE_NAMESPACE -from .base import TimeSeries +from .base import TimeSeries, TimeSeriesReferenceVectorData from .core import NWBContainer from .device import Device +from copy import copy +import numpy as np + + +def ensure_unit(self, name, current_unit, unit, nwb_version): + """A helper to ensure correct unit used. + + Issues a warning with details if `current_unit` is to be ignored, and + `unit` to be used instead. + """ + if current_unit != unit: + warnings.warn( + "Unit '%s' for %s '%s' is ignored and will be set to '%s' " + "as per NWB %s." + % (current_unit, self.__class__.__name__, name, unit, nwb_version)) + return unit @register_class('IntracellularElectrode', CORE_NAMESPACE) @@ -71,7 +87,7 @@ class PatchClampSeries(TimeSeries): 'doc': 'IntracellularElectrode group that describes the electrode that was used to apply ' 'or record this data.'}, {'name': 'gain', 'type': 'float', 'doc': 'Units: Volt/Amp (v-clamp) or Volt/Volt (c-clamp)'}, # required - {'name': 'stimulus_description', 'type': str, 'doc': 'the stimulus name/protocol', 'default': "NA"}, + {'name': 'stimulus_description', 'type': str, 'doc': 'the stimulus name/protocol', 'default': "N/A"}, *get_docval(TimeSeries.__init__, 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', 'description', 'control', 'control_description'), {'name': 'sweep_number', 'type': (int, 'uint32', 'uint64'), @@ -138,7 +154,11 @@ class IZeroClampSeries(CurrentClampSeries): @docval(*get_docval(CurrentClampSeries.__init__, 'name', 'data', 'electrode'), # required {'name': 'gain', 'type': 'float', 'doc': 'Units: Volt/Volt'}, # required - *get_docval(CurrentClampSeries.__init__, 'stimulus_description', 'resolution', 'conversion', 'timestamps', + {'name': 'stimulus_description', 'type': str, + 'doc': ('The stimulus name/protocol. Setting this to a value other than "N/A" is deprecated as of ' + 'NWB 2.3.0.'), + 'default': 'N/A'}, + *get_docval(CurrentClampSeries.__init__, 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', 'description', 'control', 'control_description', 'sweep_number'), {'name': 'unit', 'type': str, 'doc': "The base unit of measurement (must be 'volts')", @@ -146,9 +166,25 @@ class IZeroClampSeries(CurrentClampSeries): def __init__(self, **kwargs): name, data, electrode, gain = popargs('name', 'data', 'electrode', 'gain', kwargs) bias_current, bridge_balance, capacitance_compensation = (0.0, 0.0, 0.0) + stimulus_description = popargs('stimulus_description', kwargs) + stimulus_description = self._ensure_stimulus_description(name, stimulus_description, 'N/A', '2.3.0') + kwargs['stimulus_description'] = stimulus_description super().__init__(name, data, electrode, gain, bias_current, bridge_balance, capacitance_compensation, **kwargs) + def _ensure_stimulus_description(self, name, current_stim_desc, stim_desc, nwb_version): + """A helper to ensure correct stimulus_description used. + + Issues a warning with details if `current_stim_desc` is to be ignored, and + `stim_desc` to be used instead. + """ + if current_stim_desc != stim_desc: + warnings.warn( + "Stimulus description '%s' for %s '%s' is ignored and will be set to '%s' " + "as per NWB %s." + % (current_stim_desc, self.__class__.__name__, name, stim_desc, nwb_version)) + return stim_desc + @register_class('CurrentClampStimulusSeries', CORE_NAMESPACE) class CurrentClampStimulusSeries(PatchClampSeries): @@ -258,6 +294,9 @@ class SweepTable(DynamicTable): 'default': "A sweep table groups different PatchClampSeries together."}, *get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) def __init__(self, **kwargs): + warnings.warn("Use of SweepTable is deprecated. Use the IntracellularRecordingsTable " + "instead. See also the NWBFile.add_intracellular_recordings function.", + DeprecationWarning) call_docval_func(super().__init__, kwargs) @docval({'name': 'pcs', 'type': PatchClampSeries, @@ -299,15 +338,505 @@ def __get_row_ids(self, sweep_number): return [index for index, elem in enumerate(self['sweep_number'].data) if elem == sweep_number] -def ensure_unit(self, name, current_unit, unit, nwb_version): - """A helper to ensure correct unit used. +@register_class('IntracellularElectrodesTable', CORE_NAMESPACE) +class IntracellularElectrodesTable(DynamicTable): + """ + Table for storing intracellular electrode related metadata' + """ + __columns__ = ( + {'name': 'electrode', + 'description': 'Column for storing the reference to the intracellular electrode', + 'required': True, + 'index': False, + 'table': False}, + ) - Issues a warning with details if `current_unit` is to be ignored, and - `unit` to be used instead. + @docval(*get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + # Define defaultb name and description settings + kwargs['name'] = 'electrodes' + kwargs['description'] = ('Table for storing intracellular electrode related metadata') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + + +@register_class('IntracellularStimuliTable', CORE_NAMESPACE) +class IntracellularStimuliTable(DynamicTable): """ - if current_unit != unit: - warnings.warn( - "Unit '%s' for %s '%s' is ignored and will be set to '%s' " - "as per NWB %s." - % (current_unit, self.__class__.__name__, name, unit, nwb_version)) - return unit + Table for storing intracellular electrode related metadata' + """ + __columns__ = ( + {'name': 'stimulus', + 'description': 'Column storing the reference to the recorded stimulus for the recording (rows)', + 'required': True, + 'index': False, + 'table': False, + 'class': TimeSeriesReferenceVectorData}, + ) + + @docval(*get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + # Define defaultb name and description settings + kwargs['name'] = 'stimuli' + kwargs['description'] = ('Table for storing intracellular stimulus related metadata') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + + +@register_class('IntracellularResponsesTable', CORE_NAMESPACE) +class IntracellularResponsesTable(DynamicTable): + """ + Table for storing intracellular electrode related metadata' + """ + __columns__ = ( + {'name': 'response', + 'description': 'Column storing the reference to the recorded response for the recording (rows)', + 'required': True, + 'index': False, + 'table': False, + 'class': TimeSeriesReferenceVectorData}, + ) + + @docval(*get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + # Define defaultb name and description settings + kwargs['name'] = 'responses' + kwargs['description'] = ('Table for storing intracellular response related metadata') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + + +@register_class('IntracellularRecordingsTable', CORE_NAMESPACE) +class IntracellularRecordingsTable(AlignedDynamicTable): + """ + A table to group together a stimulus and response from a single electrode and + a single simultaneous_recording. Each row in the table represents a single recording consisting + typically of a stimulus and a corresponding response. + """ + @docval(*get_docval(AlignedDynamicTable.__init__, 'id', 'columns', 'colnames', 'category_tables', 'categories')) + def __init__(self, **kwargs): + kwargs['name'] = 'intracellular_recordings' + kwargs['description'] = ('A table to group together a stimulus and response from a single electrode ' + 'and a single simultaneous recording and for storing metadata about the ' + 'intracellular recording.') + in_category_tables = getargs('category_tables', kwargs) + if in_category_tables is None or len(in_category_tables) == 0: + kwargs['category_tables'] = [IntracellularElectrodesTable(), + IntracellularStimuliTable(), + IntracellularResponsesTable()] + kwargs['categories'] = None + else: + # Check if our required data tables are supplied, otherwise add them to the list + required_dynamic_table_given = [-1 for i in range(3)] # The first three are our required tables + for i, tab in enumerate(in_category_tables): + if isinstance(tab, IntracellularElectrodesTable): + required_dynamic_table_given[0] = i + elif isinstance(tab, IntracellularStimuliTable): + required_dynamic_table_given[1] = i + elif isinstance(tab, IntracellularResponsesTable): + required_dynamic_table_given[2] = i + # Check if the supplied tables contain data but not all required tables have been supplied + required_dynamic_table_missing = np.any(np.array(required_dynamic_table_given[0:3]) < 0) + if len(in_category_tables[0]) != 0 and required_dynamic_table_missing: + raise ValueError("IntracellularElectrodeTable, IntracellularStimuliTable, and " + "IntracellularResponsesTable are required when adding custom, non-empty " + "tables to IntracellularRecordingsTable as the missing data for the required " + "tables cannot be determined automatically") + # Compile the complete list of tables + dynamic_table_arg = copy(in_category_tables) + categories_arg = [] if getargs('categories', kwargs) is None else copy(getargs('categories', kwargs)) + if required_dynamic_table_missing: + if required_dynamic_table_given[2] < 0: + dynamic_table_arg.append(IntracellularResponsesTable) + if not dynamic_table_arg[-1].name in categories_arg: + categories_arg.insert(0, dynamic_table_arg[-1].name) + if required_dynamic_table_given[1] < 0: + dynamic_table_arg.append(IntracellularStimuliTable()) + if not dynamic_table_arg[-1].name in categories_arg: + categories_arg.insert(0, dynamic_table_arg[-1].name) + if required_dynamic_table_given[0] < 0: + dynamic_table_arg.append(IntracellularElectrodesTable()) + if not dynamic_table_arg[-1].name in categories_arg: + categories_arg.insert(0, dynamic_table_arg[-1].name) + kwargs['category_tables'] = dynamic_table_arg + kwargs['categories'] = categories_arg + + call_docval_func(super().__init__, kwargs) + + @docval({'name': 'electrode', 'type': IntracellularElectrode, 'doc': 'The intracellular electrode used'}, + {'name': 'stimulus_start_index', 'type': 'int', 'doc': 'Start index of the stimulus', 'default': -1}, + {'name': 'stimulus_index_count', 'type': 'int', 'doc': 'Stop index of the stimulus', 'default': -1}, + {'name': 'stimulus', 'type': TimeSeries, + 'doc': 'The TimeSeries (usually a PatchClampSeries) with the stimulus', + 'default': None}, + {'name': 'response_start_index', 'type': 'int', 'doc': 'Start index of the response', 'default': -1}, + {'name': 'response_index_count', 'type': 'int', 'doc': 'Stop index of the response', 'default': -1}, + {'name': 'response', 'type': TimeSeries, + 'doc': 'The TimeSeries (usually a PatchClampSeries) with the response', + 'default': None}, + {'name': 'electrode_metadata', 'type': dict, + 'doc': 'Additional electrode metadata to be stored in the electrodes table', 'default': None}, + {'name': 'stimulus_metadata', 'type': dict, + 'doc': 'Additional stimulus metadata to be stored in the stimuli table', 'default': None}, + {'name': 'response_metadata', 'type': dict, + 'doc': 'Additional resposnse metadata to be stored in the responses table', 'default': None}, + returns='Integer index of the row that was added to this table', + rtype=int, + allow_extra=True) + def add_recording(self, **kwargs): + """ + Add a single recording to the IntracellularRecordingsTable table. + + Typically, both stimulus and response are expected. However, in some cases only a stimulus + or a resposne may be recodred as part of a recording. In this case, None, may be given + for either stimulus or response, but not both. Internally, this results in both stimulus + and response pointing to the same timeseries, while the start_index and index_count for + the invalid series will both be set to -1. + """ + # Get the input data + stimulus_start_index, stimulus_index_count, stimulus = popargs('stimulus_start_index', + 'stimulus_index_count', + 'stimulus', + kwargs) + response_start_index, response_index_count, response = popargs('response_start_index', + 'response_index_count', + 'response', + kwargs) + electrode = popargs('electrode', kwargs) + # Confirm that we have at least a valid stimulus or response + if stimulus is None and response is None: + raise ValueError("stimulus and response cannot both be None.") + + # Compute the start and stop index if necessary + stimulus_start_index, stimulus_index_count = self.__compute_index(stimulus_start_index, + stimulus_index_count, + stimulus, 'stimulus') + response_start_index, response_index_count = self.__compute_index(response_start_index, + response_index_count, + response, 'response') + # If either stimulus or response are None, then set them to the same TimeSeries to keep the I/O happy + response = response if response is not None else stimulus + stimulus = stimulus if stimulus is not None else response + + # Make sure the types are compatible + if ((response.neurodata_type.startswith("CurrentClamp") and + stimulus.neurodata_type.startswith("VoltageClamp")) or + (response.neurodata_type.startswith("VoltageClamp") and + stimulus.neurodata_type.startswith("CurrentClamp"))): + raise ValueError("Incompatible types given for 'stimulus' and 'response' parameters. " + "'stimulus' is of type %s and 'response' is of type %s." % + (stimulus.neurodata_type, response.neurodata_type)) + if response.neurodata_type == 'IZeroClampSeries': + if stimulus is not None: + raise ValueError("stimulus should usually be None for IZeroClampSeries response") + if isinstance(response, PatchClampSeries) and isinstance(stimulus, PatchClampSeries): + # # We could also check sweep_number, but since it is mostly relevant to the deprecated SweepTable + # # we don't really need to enforce it here + # if response.sweep_number != stimulus.sweep_number: + # warnings.warn("sweep_number are usually expected to be the same for PatchClampSeries type " + # "stimulus and response pairs in an intracellular recording.") + if response.electrode != stimulus.electrode: + raise ValueError("electrodes are usually expected to be the same for PatchClampSeries type " + "stimulus and response pairs in an intracellular recording.") + + # Compile the electrodes table data + electrodes = copy(popargs('electrode_metadata', kwargs)) + if electrodes is None: + electrodes = {} + electrodes['electrode'] = electrode + + # Compile the stimuli table data + stimuli = copy(popargs('stimulus_metadata', kwargs)) + if stimuli is None: + stimuli = {} + stimuli['stimulus'] = (stimulus_start_index, stimulus_index_count, stimulus) + + # Compile the reponses table data + responses = copy(popargs('response_metadata', kwargs)) + if responses is None: + responses = {} + responses['response'] = (response_start_index, response_index_count, response) + + _ = super().add_row(enforce_unique_id=True, + electrodes=electrodes, + responses=responses, + stimuli=stimuli, + **kwargs) + return len(self) - 1 + + @staticmethod + def __compute_index(start_index, index_count, time_series, name): + """ + Internal helper function to compute the start_index and index_count + to use for the stimulus and response column + + :param start_index: The start_index provided by the user + :param index_count: The index count provided by the user + :param time_series: The timeseries object to reference. May be None. + :param name: Name of the table. Used only to enhance error reporting + + :raises IndexError: If index_count cannot be determined or start_index+index_count + are outside of the range of the timeseries. + + :returns: A tuple of integers with the start_index and index_count to use + """ + if time_series is None: + return -1, -1 + start_index = start_index if start_index >= 0 else 0 + num_samples = time_series.num_samples + index_count = (index_count + if index_count >= 0 + else ((num_samples - start_index) + if num_samples is not None + else None)) + if index_count is None: + raise IndexError("Invalid %s_index_count cannot be determined from %s data." % (name, name)) + if num_samples is not None: + if start_index >= num_samples: + raise IndexError("%s_start_index out of range" % name) + if (start_index + index_count) > num_samples: + raise IndexError("%s_start_index + %s_index_count out of range" % (name, name)) + return start_index, index_count + + @docval(*get_docval(AlignedDynamicTable.to_dataframe, 'ignore_category_ids'), + {'name': 'electrode_refs_as_objectids', 'type': bool, + 'doc': 'replace object references in the electrode column with object_ids', + 'default': False}, + {'name': 'stimulus_refs_as_objectids', 'type': bool, + 'doc': 'replace object references in the stimulus column with object_ids', + 'default': False}, + {'name': 'response_refs_as_objectids', 'type': bool, + 'doc': 'replace object references in the response column with object_ids', + 'default': False} + ) + def to_dataframe(self, **kwargs): + """Convert the collection of tables to a single pandas DataFrame""" + res = super().to_dataframe(ignore_category_ids=getargs('ignore_category_ids', kwargs)) + if getargs('electrode_refs_as_objectids', kwargs): + res[('electrodes', 'electrode')] = [e.object_id for e in res[('electrodes', 'electrode')]] + if getargs('stimulus_refs_as_objectids', kwargs): + res[('stimuli', 'stimulus')] = [(e[0], e[1], e[2].object_id) for e in res[('stimuli', 'stimulus')]] + if getargs('response_refs_as_objectids', kwargs): + res[('responses', 'response')] = [(e[0], e[1], e[2].object_id) for e in res[('responses', 'response')]] + return res + + +@register_class('SimultaneousRecordingsTable', CORE_NAMESPACE) +class SimultaneousRecordingsTable(DynamicTable): + """ + A table for grouping different intracellular recordings from the + IntracellularRecordingsTable table together that were recorded simultaneously + from different electrodes. + """ + + __columns__ = ( + {'name': 'recordings', + 'description': 'Column with a references to one or more rows in the IntracellularRecordingsTable table', + 'required': True, + 'index': True, + 'table': True}, + ) + + @docval({'name': 'intracellular_recordings_table', + 'type': IntracellularRecordingsTable, + 'doc': 'the IntracellularRecordingsTable table that the recordings column indexes. May be None when ' + 'reading the Container from file as the table attribute is already populated in this case ' + 'but otherwise this is required.', + 'default': None}, + *get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + intracellular_recordings_table = popargs('intracellular_recordings_table', kwargs) + # Define default name and description settings + kwargs['name'] = 'simultaneous_recordings' + kwargs['description'] = ('A table for grouping different intracellular recordings from the' + 'IntracellularRecordingsTable table together that were recorded simultaneously ' + 'from different electrodes.') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + if self['recordings'].target.table is None: + if intracellular_recordings_table is not None: + self['recordings'].target.table = intracellular_recordings_table + else: + raise ValueError("intracellular_recordings constructor argument required") + + @docval({'name': 'recordings', + 'type': 'array_data', + 'doc': 'the indices of the recordings belonging to this simultaneous recording'}, + returns='Integer index of the row that was added to this table', + rtype=int, + allow_extra=True) + def add_simultaneous_recording(self, **kwargs): + """ + Add a single Sweep consisting of one-or-more recordings and associated custom + SimultaneousRecordingsTable metadata to the table. + """ + _ = super().add_row(enforce_unique_id=True, **kwargs) + return len(self.id) - 1 + + +@register_class('SequentialRecordingsTable', CORE_NAMESPACE) +class SequentialRecordingsTable(DynamicTable): + """ + A table for grouping different intracellular recording simultaneous_recordings from the + SimultaneousRecordingsTable table together. This is typically used to group together simultaneous_recordings + where the a sequence of stimuli of the same type with varying parameters + have been presented in a sequence. + """ + + __columns__ = ( + {'name': 'simultaneous_recordings', + 'description': 'Column with a references to one or more rows in the SimultaneousRecordingsTable table', + 'required': True, + 'index': True, + 'table': True}, + {'name': 'stimulus_type', + 'description': 'Column storing the type of stimulus used for the sequential recording', + 'required': True, + 'index': False, + 'table': False} + ) + + @docval({'name': 'simultaneous_recordings_table', + 'type': SimultaneousRecordingsTable, + 'doc': 'the SimultaneousRecordingsTable table that the simultaneous_recordings ' + 'column indexes. May be None when reading the Container from file as the ' + 'table attribute is already populated in this case but otherwise this is required.', + 'default': None}, + *get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + simultaneous_recordings_table = popargs('simultaneous_recordings_table', kwargs) + # Define defaultb name and description settings + kwargs['name'] = 'sequential_recordings' + kwargs['description'] = ('A table for grouping different intracellular recording simultaneous_recordings ' + 'from the SimultaneousRecordingsTable table together. This is typically used to ' + 'group together simultaneous_recordings where the a sequence of stimuli of the ' + 'same type with varying parameters have been presented in a sequence.') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + if self['simultaneous_recordings'].target.table is None: + if simultaneous_recordings_table is not None: + self['simultaneous_recordings'].target.table = simultaneous_recordings_table + else: + raise ValueError('simultaneous_recordings_table constructor argument required') + + @docval({'name': 'stimulus_type', + 'type': str, + 'doc': 'the type of stimulus used for the sequential recording'}, + {'name': 'simultaneous_recordings', + 'type': 'array_data', + 'doc': 'the indices of the simultaneous_recordings belonging to this sequential recording'}, + returns='Integer index of the row that was added to this table', + rtype=int, + allow_extra=True) + def add_sequential_recording(self, **kwargs): + """ + Add a sequential recording (i.e., one row) consisting of one-or-more recording simultaneous_recordings + and associated custom sequential recording metadata to the table. + """ + _ = super().add_row(enforce_unique_id=True, **kwargs) + return len(self.id) - 1 + + +@register_class('RepetitionsTable', CORE_NAMESPACE) +class RepetitionsTable(DynamicTable): + """ + A table for grouping different intracellular recording sequential recordings together. + With each SweepSequence typically representing a particular type of stimulus, the + RepetitionsTable table is typically used to group sets of stimuli applied in sequence. + """ + + __columns__ = ( + {'name': 'sequential_recordings', + 'description': 'Column with a references to one or more rows in the SequentialRecordingsTable table', + 'required': True, + 'index': True, + 'table': True}, + ) + + @docval({'name': 'sequential_recordings_table', + 'type': SequentialRecordingsTable, + 'doc': 'the SequentialRecordingsTable table that the sequential_recordings column indexes. May ' + 'be None when reading the Container from file as the table attribute is already populated ' + 'in this case but otherwise this is required.', + 'default': None}, + *get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + sequential_recordings_table = popargs('sequential_recordings_table', kwargs) + # Define default name and description settings + kwargs['name'] = 'repetitions' + kwargs['description'] = ('A table for grouping different intracellular recording sequential recordings ' + 'together. With each SimultaneousRecording typically representing a particular type ' + 'of stimulus, the RepetitionsTable table is typically used to group sets ' + 'of stimuli applied in sequence.') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + if self['sequential_recordings'].target.table is None: + if sequential_recordings_table is not None: + self['sequential_recordings'].target.table = sequential_recordings_table + else: + raise ValueError('sequential_recordings_table constructor argument required') + + @docval({'name': 'sequential_recordings', + 'type': 'array_data', + 'doc': 'the indices of the sequential recordings belonging to this repetition', + 'default': None}, + returns='Integer index of the row that was added to this table', + rtype=int, + allow_extra=True) + def add_repetition(self, **kwargs): + """ + Add a repetition (i.e., one row) consisting of one-or-more recording sequential recordings + and associated custom repetition metadata to the table. + """ + _ = super().add_row(enforce_unique_id=True, **kwargs) + return len(self.id) - 1 + + +@register_class('ExperimentalConditionsTable', CORE_NAMESPACE) +class ExperimentalConditionsTable(DynamicTable): + """ + A table for grouping different intracellular recording repetitions together that + belong to the same experimental conditions. + """ + + __columns__ = ( + {'name': 'repetitions', + 'description': 'Column with a references to one or more rows in the RepetitionsTable table', + 'required': True, + 'index': True, + 'table': True}, + ) + + @docval({'name': 'repetitions_table', + 'type': RepetitionsTable, + 'doc': 'the RepetitionsTable table that the repetitions column indexes', + 'default': None}, + *get_docval(DynamicTable.__init__, 'id', 'columns', 'colnames')) + def __init__(self, **kwargs): + repetitions_table = popargs('repetitions_table', kwargs) + # Define default name and description settings + kwargs['name'] = 'experimental_conditions' + kwargs['description'] = ('A table for grouping different intracellular recording repetitions together that ' + 'belong to the same experimental conditions.') + # Initialize the DynamicTable + call_docval_func(super().__init__, kwargs) + if self['repetitions'].target.table is None: + if repetitions_table is not None: + self['repetitions'].target.table = repetitions_table + else: + raise ValueError('repetitions_table constructor argument required') + + @docval({'name': 'repetitions', + 'type': 'array_data', + 'doc': 'the indices of the repetitions belonging to this condition', + 'default': None}, + returns='Integer index of the row that was added to this table', + rtype=int, + allow_extra=True) + def add_experimental_condition(self, **kwargs): + """ + Add a condition (i.e., one row) consisting of one-or-more recording repetitions of sequential recordings + and associated custom experimental_conditions metadata to the table. + """ + _ = super().add_row(enforce_unique_id=True, **kwargs) + return len(self.id) - 1 diff --git a/src/pynwb/image.py b/src/pynwb/image.py index ad7af3761..666177296 100644 --- a/src/pynwb/image.py +++ b/src/pynwb/image.py @@ -5,6 +5,7 @@ from . import register_class, CORE_NAMESPACE from .base import TimeSeries, Image +from .device import Device @register_class('ImageSeries', CORE_NAMESPACE) @@ -17,7 +18,8 @@ class ImageSeries(TimeSeries): __nwbfields__ = ('dimension', 'external_file', 'starting_frame', - 'format') + 'format', + 'device') @docval(*get_docval(TimeSeries.__init__, 'name'), # required {'name': 'data', 'type': ('array_data', 'data', TimeSeries), 'shape': ([None] * 3, [None] * 4), @@ -40,10 +42,12 @@ class ImageSeries(TimeSeries): {'name': 'dimension', 'type': Iterable, 'doc': 'Number of pixels on x, y, (and z) axes.', 'default': None}, *get_docval(TimeSeries.__init__, 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', - 'comments', 'description', 'control', 'control_description')) + 'comments', 'description', 'control', 'control_description'), + {'name': 'device', 'type': Device, + 'doc': 'Device used to capture the images/video.', 'default': None},) def __init__(self, **kwargs): - bits_per_pixel, dimension, external_file, starting_frame, format = popargs( - 'bits_per_pixel', 'dimension', 'external_file', 'starting_frame', 'format', kwargs) + bits_per_pixel, dimension, external_file, starting_frame, format, device = popargs( + 'bits_per_pixel', 'dimension', 'external_file', 'starting_frame', 'format', 'device', kwargs) call_docval_func(super(ImageSeries, self).__init__, kwargs) if external_file is None and self.data is None: raise ValueError("Must supply either external_file or data to %s '%s'." @@ -56,6 +60,7 @@ def __init__(self, **kwargs): else: self.starting_frame = None self.format = format + self.device = device @property def bits_per_pixel(self): @@ -111,7 +116,11 @@ class ImageMaskSeries(ImageSeries): 'doc': 'Link to ImageSeries that mask is applied to.'}, *get_docval(ImageSeries.__init__, 'format', 'external_file', 'starting_frame', 'bits_per_pixel', 'dimension', 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', - 'description', 'control', 'control_description')) + 'description', 'control', 'control_description'), + {'name': 'device', 'type': Device, + 'doc': ('Device used to capture the mask data. This field will likely not be needed. ' + 'The device used to capture the masked ImageSeries data should be stored in the ImageSeries.'), + 'default': None},) def __init__(self, **kwargs): masked_imageseries = popargs('masked_imageseries', kwargs) super(ImageMaskSeries, self).__init__(**kwargs) @@ -146,7 +155,7 @@ class OpticalSeries(ImageSeries): 'Must also specify frame of reference.'}, *get_docval(ImageSeries.__init__, 'external_file', 'starting_frame', 'bits_per_pixel', 'dimension', 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', - 'description', 'control', 'control_description')) + 'description', 'control', 'control_description', 'device')) def __init__(self, **kwargs): distance, field_of_view, orientation = popargs('distance', 'field_of_view', 'orientation', kwargs) super(OpticalSeries, self).__init__(**kwargs) diff --git a/src/pynwb/io/base.py b/src/pynwb/io/base.py index dd5f499d2..b1aaa940b 100644 --- a/src/pynwb/io/base.py +++ b/src/pynwb/io/base.py @@ -29,6 +29,7 @@ def __init__(self, spec): self.map_spec('unit', data_spec.get_attribute('unit')) self.map_spec('resolution', data_spec.get_attribute('resolution')) self.map_spec('conversion', data_spec.get_attribute('conversion')) + self.map_spec('continuity', data_spec.get_attribute('continuity')) timestamps_spec = self.spec.get_dataset('timestamps') self.map_spec('timestamps_unit', timestamps_spec.get_attribute('unit')) diff --git a/src/pynwb/io/file.py b/src/pynwb/io/file.py index 2c629ab7d..ccff9c5b6 100644 --- a/src/pynwb/io/file.py +++ b/src/pynwb/io/file.py @@ -47,12 +47,18 @@ def __init__(self, spec): general_spec = self.spec.get_group('general') self.unmap(general_spec) + # map icephys metadata structures and tables icephys_spec = general_spec.get_group('intracellular_ephys') self.unmap(icephys_spec) self.map_spec('icephys_electrodes', icephys_spec.get_neurodata_type('IntracellularElectrode')) self.map_spec('sweep_table', icephys_spec.get_neurodata_type('SweepTable')) + self.map_spec('intracellular_recordings', icephys_spec.get_neurodata_type('IntracellularRecordingsTable')) + self.map_spec('icephys_simultaneous_recordings', icephys_spec.get_neurodata_type('SimultaneousRecordingsTable')) + self.map_spec('icephys_sequential_recordings', icephys_spec.get_neurodata_type('SequentialRecordingsTable')) + self.map_spec('icephys_repetitions', icephys_spec.get_neurodata_type('RepetitionsTable')) + self.map_spec('icephys_experimental_conditions', icephys_spec.get_neurodata_type('ExperimentalConditionsTable')) - # 'filtering' will be deprecated. add this mapping in the meantime + # 'filtering' has been deprecated. add this mapping in the meantime icephys_filtering_spec = icephys_spec.get_dataset('filtering') self.unmap(icephys_filtering_spec) self.map_spec('icephys_filtering', icephys_filtering_spec) diff --git a/src/pynwb/io/icephys.py b/src/pynwb/io/icephys.py index 308f869fe..0ed1a2c3b 100644 --- a/src/pynwb/io/icephys.py +++ b/src/pynwb/io/icephys.py @@ -1,7 +1,8 @@ from .. import register_map -from pynwb.icephys import SweepTable, VoltageClampSeries +from pynwb.icephys import SweepTable, VoltageClampSeries, IntracellularRecordingsTable from hdmf.common.io.table import DynamicTableMap +from hdmf.common.io.alignedtable import AlignedDynamicTableMap from .base import TimeSeriesMap @@ -26,3 +27,24 @@ def __init__(self, spec): for field in fields_with_unit: field_spec = self.spec.get_dataset(field) self.map_spec('%s__unit' % field, field_spec.get_attribute('unit')) + + +@register_map(IntracellularRecordingsTable) +class IntracellularRecordingsTableMap(AlignedDynamicTableMap): + """ + Customize the mapping for AlignedDynamicTable + """ + def __init__(self, spec): + super().__init__(spec) + + @DynamicTableMap.object_attr('electrodes') + def electrodes(self, container, manager): + return container.category_tables.get('electrodes', None) + + @DynamicTableMap.object_attr('stimuli') + def stimuli(self, container, manager): + return container.category_tables.get('stimuli', None) + + @DynamicTableMap.object_attr('responses') + def responses(self, container, manager): + return container.category_tables.get('responses', None) diff --git a/src/pynwb/misc.py b/src/pynwb/misc.py index 18222bbd8..31303edf1 100644 --- a/src/pynwb/misc.py +++ b/src/pynwb/misc.py @@ -7,7 +7,7 @@ from . import register_class, CORE_NAMESPACE from .base import TimeSeries -from hdmf.common import DynamicTable +from hdmf.common import DynamicTable, DynamicTableRegion @register_class('AnnotationSeries', CORE_NAMESPACE) @@ -251,6 +251,7 @@ class DecompositionSeries(TimeSeries): __nwbfields__ = ('metric', {'name': 'source_timeseries', 'child': False, 'doc': 'the input TimeSeries from this analysis'}, + {'name': 'source_channels', 'child': True, 'doc': 'the channels that provided the source data'}, {'name': 'bands', 'doc': 'the bands that the signal is decomposed into', 'child': True}) @@ -267,15 +268,23 @@ class DecompositionSeries(TimeSeries): 'doc': 'a table for describing the frequency bands that the signal was decomposed into', 'default': None}, {'name': 'source_timeseries', 'type': TimeSeries, 'doc': 'the input TimeSeries from this analysis', 'default': None}, + {'name': 'source_channels', 'type': DynamicTableRegion, + 'doc': ('The channels that provided the source data. In the case of electrical recordings this is ' + 'typically a DynamicTableRegion pointing to the electrodes table at NWBFile.electrodes, ' + 'similar to ElectricalSeries.electrodes.'), + 'default': None}, *get_docval(TimeSeries.__init__, 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', 'comments', 'control', 'control_description')) def __init__(self, **kwargs): - metric, source_timeseries, bands = popargs('metric', 'source_timeseries', 'bands', kwargs) + metric, source_timeseries, bands, source_channels = popargs('metric', 'source_timeseries', 'bands', + 'source_channels', kwargs) super(DecompositionSeries, self).__init__(**kwargs) self.source_timeseries = source_timeseries - if self.source_timeseries is None: - warnings.warn("It is best practice to set `source_timeseries` if it is present to document " - "where the DecompositionSeries was derived from. (Optional)") + self.source_channels = source_channels + if self.source_timeseries is None and self.source_channels is None: + warnings.warn("Neither source_timeseries nor source_channels is present in DecompositionSeries. It is " + "recommended to indicate the source timeseries if it is present, or else to link to the " + "corresponding source_channels. (Optional)") self.metric = metric if bands is None: bands = DynamicTable("bands", "data about the frequency bands that the signal was decomposed into") diff --git a/src/pynwb/nwb-schema b/src/pynwb/nwb-schema index aa7702e1c..fcbca7a57 160000 --- a/src/pynwb/nwb-schema +++ b/src/pynwb/nwb-schema @@ -1 +1 @@ -Subproject commit aa7702e1cc5be2b85f19206e0d1d50bc4bd7e296 +Subproject commit fcbca7a57dcb7d7d738e591ddfb2c9c946c7fdaf diff --git a/src/pynwb/ophys.py b/src/pynwb/ophys.py index 2dd329749..97e3b2468 100644 --- a/src/pynwb/ophys.py +++ b/src/pynwb/ophys.py @@ -142,7 +142,7 @@ class TwoPhotonSeries(ImageSeries): 'default': None}, *get_docval(ImageSeries.__init__, 'external_file', 'starting_frame', 'bits_per_pixel', 'dimension', 'resolution', 'conversion', 'timestamps', 'starting_time', 'rate', - 'comments', 'description', 'control', 'control_description')) + 'comments', 'description', 'control', 'control_description', 'device')) def __init__(self, **kwargs): field_of_view, imaging_plane, pmt_gain, scan_line_rate = popargs( 'field_of_view', 'imaging_plane', 'pmt_gain', 'scan_line_rate', kwargs) @@ -161,19 +161,19 @@ class CorrectedImageStack(NWBDataInterface): assumed to be 2-D (has only x & y dimensions). """ - __nwbfields__ = ({'name': 'corrected', 'child': True}, - {'name': 'xy_translation', 'child': True}, + __nwbfields__ = ({'name': 'corrected', 'child': True, 'required_name': 'corrected'}, + {'name': 'xy_translation', 'child': True, 'required_name': 'xy_translation'}, 'original') @docval({'name': 'name', 'type': str, 'doc': 'The name of this CorrectedImageStack container', 'default': 'CorrectedImageStack'}, {'name': 'corrected', 'type': ImageSeries, - 'doc': 'Image stack with frames shifted to the common coordinates.'}, + 'doc': 'Image stack with frames shifted to the common coordinates. This must have the name "corrected".'}, {'name': 'original', 'type': ImageSeries, 'doc': 'Link to image series that is being registered.'}, {'name': 'xy_translation', 'type': TimeSeries, 'doc': 'Stores the x,y delta necessary to align each frame to the common coordinates, ' - 'for example, to align each frame to a reference image.'}) + 'for example, to align each frame to a reference image. This must have the name "xy_translation".'}) def __init__(self, **kwargs): corrected, original, xy_translation = popargs('corrected', 'original', 'xy_translation', kwargs) call_docval_func(super(CorrectedImageStack, self).__init__, kwargs) @@ -193,7 +193,7 @@ class MotionCorrection(MultiContainerInterface): 'get': 'get_corrected_image_stack', 'create': 'create_corrected_image_stack', 'type': CorrectedImageStack, - 'attr': 'corrected_images_stacks' + 'attr': 'corrected_image_stacks' } @@ -267,8 +267,8 @@ def pixel_to_image(pixel_mask): """Converts a 2D pixel_mask of a ROI into an image_mask.""" image_matrix = np.zeros(np.shape(pixel_mask)) npmask = np.asarray(pixel_mask) - x_coords = npmask[:, 0].astype(np.int) - y_coords = npmask[:, 1].astype(np.int) + x_coords = npmask[:, 0].astype(np.int32) + y_coords = npmask[:, 1].astype(np.int32) weights = npmask[:, -1] image_matrix[y_coords, x_coords] = weights return image_matrix diff --git a/src/pynwb/validate.py b/src/pynwb/validate.py index 2e62eecfb..f3f127b19 100644 --- a/src/pynwb/validate.py +++ b/src/pynwb/validate.py @@ -26,7 +26,7 @@ def _validate_helper(**kwargs): return (errors is not None and len(errors) > 0) -def main(): +def main(): # noqa: C901 ep = """ use --nspath to validate against an extension. If --ns is not specified, @@ -73,6 +73,9 @@ def main(): s = set(ns_deps.keys()) # determine which namespaces are the most for k in ns_deps: # specific (i.e. extensions) and validate s -= ns_deps[k].keys() # against those + # TODO remove this workaround for issue https://github.com/NeurodataWithoutBorders/pynwb/issues/1357 + if 'hdmf-experimental' in s: + s.remove('hdmf-experimental') # remove validation of hdmf-experimental for now namespaces = list(sorted(s)) if len(namespaces) > 0: tm = TypeMap(catalog) @@ -108,15 +111,22 @@ def main(): if args.ns: if args.ns in namespaces: namespaces = [args.ns] + elif args.cached_namespace and args.ns in ns_deps: # validating against a dependency + for k in ns_deps: + if args.ns in ns_deps[k]: + print(("The namespace '{}' is included by the namespace '{}'. Please validate against " + "that namespace instead.").format(args.ns, k), file=sys.stderr) + ret = 1 + continue else: - print("The namespace {} could not be found in {} as only {} is present.".format( + print("The namespace '{}' could not be found in {} as only {} is present.".format( args.ns, specloc, namespaces), file=sys.stderr) ret = 1 continue with NWBHDF5IO(path, mode='r', manager=manager) as io: for ns in namespaces: - print("Validating {} against {} using namespace {}.".format(path, specloc, ns)) + print("Validating {} against {} using namespace '{}'.".format(path, specloc, ns)) ret = ret or _validate_helper(io=io, namespace=ns) sys.exit(ret) diff --git a/test.h5 b/test.h5 deleted file mode 100644 index 840f8b8d51aa51892574b92ed9ebfb42d036c9ee..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 2448 zcmeIyw@$<`7{GDoC<;hOz=T-f5qJcUICK*rU|@rj=)L#eJ4f%m_uhNwO?V9WC$SeM z1|$Y9r=RV7PVDn1JDrZmC_mp|UtwIjES z@e?9Q#slQ|-=9l}v)ctvs_|7VUlZY8R!dg_cm1z2;IK!;8VgR8t5&=8UG6iLj1*^y z(`c*x=ujQ*`d2cb32!U6GQpZW*_vhrQsgYE_Tao5J^mbAPqQ!7EWLzo#%(s6`Jyhz z@zCfnFPEIbx(k$HBN+0rkR(Kd)$zw=d~{5t@r6_0r7&xefBdi9)4Mb9vkVyLG!2*?7kS7>0SZxsVw9j1Whh4lDp7@M)Swo1s7C`D(S&BSpcQRsM+Z95g>Lkq z7k%i53j-L$5QZ^=QH)_66PUylrZIzA%wZl2Si};Rv4T~sVI3RT#1^)(gI(-l9|t(Z h5sq 1: - runner = ColoredTestRunner(verbosity=verbose) - else: - runner = unittest.TextTestRunner(verbosity=verbose, resultclass=ColoredTestResult) + runner = unittest.TextTestRunner(verbosity=verbose, resultclass=SuccessRecordingResult) test_result = runner.run(unittest.TestLoader().discover(directory)) TOTAL += test_result.testsRun diff --git a/tests/back_compat/test_read.py b/tests/back_compat/test_read.py index 731895c7d..c9ccd51ce 100644 --- a/tests/back_compat/test_read.py +++ b/tests/back_compat/test_read.py @@ -7,6 +7,17 @@ class TestReadOldVersions(TestCase): + expected_errors = { + '1.0.2_str_experimenter.nwb': [("root/general/experimenter (general/experimenter): incorrect shape - expected " + "an array of shape '[None]', got non-array data 'one experimenter'")], + '1.0.3_str_experimenter.nwb': [("root/general/experimenter (general/experimenter): incorrect shape - expected " + "an array of shape '[None]', got non-array data 'one experimenter'")], + '1.0.2_str_pub.nwb': [("root/general/related_publications (general/related_publications): incorrect shape " + "- expected an array of shape '[None]', got non-array data 'one publication'")], + '1.0.3_str_pub.nwb': [("root/general/related_publications (general/related_publications): incorrect shape " + "- expected an array of shape '[None]', got non-array data 'one publication'")], + } + def test_read(self): """ Attempt to read and validate all NWB files in the same folder as this file. The folder should contain NWB files @@ -21,6 +32,7 @@ def test_read(self): io.read() if errors: for e in errors: - warnings.warn('%s: %s' % (f.name, e)) + if f.name in self.expected_errors and str(e) not in self.expected_errors[f.name]: + warnings.warn('%s: %s' % (f.name, e)) # TODO uncomment below when validation errors have been fixed # raise Exception('%d validation error(s). See warnings.' % len(errors)) diff --git a/tests/coloredtestrunner.py b/tests/coloredtestrunner.py deleted file mode 100644 index e6fcb272f..000000000 --- a/tests/coloredtestrunner.py +++ /dev/null @@ -1,498 +0,0 @@ -# -*- coding: utf-8 -*- -""" -A ColoredTestRunner for use with the Python unit testing framework. It -generates a tabular report to show the result at a glance, with COLORS. - -coloredtestrunner.py was modified from code written by Vinícius Dantas and posted -as a gist: https://gist.github.com/viniciusd/73e6eccd39dea5e714b1464e3c47e067 -and demonstrated here: -https://stackoverflow.com/questions/17162682/display-python-unittest-results-in-nice-tabular-form/31665827#31665827 - -The code linked above is based on HTMLTestRunner -written by Wai Yip Tung. The BSD-3-Clause license covering HTMLTestRunner is below. - ------------------------------------------------------------------------- -Copyright (c) 2004-2007, Wai Yip Tung -All rights reserved. - -Redistribution and use in source and binary forms, with or without -modification, are permitted provided that the following conditions are -met: - -* Redistributions of source code must retain the above copyright notice, - this list of conditions and the following disclaimer. -* Redistributions in binary form must reproduce the above copyright - notice, this list of conditions and the following disclaimer in the - documentation and/or other materials provided with the distribution. -* Neither the name Wai Yip Tung nor the names of its contributors may be - used to endorse or promote products derived from this software without - specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS -IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED -TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A -PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER -OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR -PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF -LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING -NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS -SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -""" -import datetime -try: - from StringIO import StringIO -except ImportError: - from io import StringIO -import sys -import re -import unittest -import textwrap - - -# ------------------------------------------------------------------------ -# The redirectors below are used to capture output during testing. Output -# sent to sys.stdout and sys.stderr are automatically captured. However -# in some cases sys.stdout is already cached before HTMLTestRunner is -# invoked (e.g. calling logging.basicConfig). In order to capture those -# output, use the redirectors for the cached stream. -# -# e.g. -# >>> logging.basicConfig(stream=HTMLTestRunner.stdout_redirector) -# >>> - -class OutputRedirector(object): - """ Wrapper to redirect stdout or stderr """ - def __init__(self, fp): - self.fp = fp - - def write(self, s): - self.fp.write(s) - - def writelines(self, lines): - self.fp.writelines(lines) - - def flush(self): - self.fp.flush() - - -class Table(object): - - def __init__(self, padding='', allow_newlines=False): - self.__columnSize__ = [] - self.__rows__ = [] - self.__titles__ = None - self.padding = padding - self.allow_newlines = allow_newlines - - def __len__(self, x): - return len(re.sub(r"\033\[[0-9];[0-9];[0-9]{1,2}m", "", x)) - - def addRow(self, row): - rows = [[''] for i in range(len(row))] - maxrows = 0 - for i, x in enumerate(row): - for j, y in enumerate(x.split("\n")): - if len(y) == 0 and not self.allow_newlines: - continue - try: - self.__columnSize__[i] = max(self.__columnSize__[i], self.__len__(y)) - except IndexError: - self.__columnSize__.append(self.__len__(y)) - rows[i].append(y) - maxrows = max(j, maxrows) - for i in range(len(rows)): - rows[i] += (maxrows-len(rows[i])+2)*[''] - for i in range(maxrows + 1): - self.__rows__.append([rows[j][i+1] for j in range(len(row))]) - - def addTitles(self, titles): - for i, x in enumerate(titles): - try: - self.__columnSize__[i] = max(self.__columnSize__[i], self.__len__(x)) - except IndexError: - self.__columnSize__.append(self.__len__(x)) - self.__titles__ = titles - - def __repr__(self): - hline = self.padding+"+" - for x in self.__columnSize__: - hline += (x+2)*'-'+'+' - rows = [] - if self.__titles__ is None: - title = "" - else: - if len(self.__titles__) < len(self.__columnSize__): - self.__titles__ += ((len(self.__columnSize__)-len(self.__titles__))*['']) - for i, x in enumerate(self.__titles__): - self.__titles__[i] = x.center(self.__columnSize__[i]) - title = self.padding+"| "+" | ".join(self.__titles__)+" |\n"+hline+"\n" - for x in self.__rows__: - if len(x) < len(self.__columnSize__): - x += ((len(self.__columnSize__)-len(x))*['']) - for i, c in enumerate(x): - x[i] = c.ljust(self.__columnSize__[i])+(len(c)-self.__len__(c)-3)*' ' - rows.append(self.padding+"| "+" | ".join(x)+" |") - return hline+"\n"+title+"\n".join(rows)+"\n"+hline+"\n" - - -class bcolors(object): - FORMAT = { - 'Regular': '0', - 'Bold': '1', - 'Underline': '4', - 'High Intensity': '0', # +60 on color - 'BoldHighIntensity': '1', # +60 on color - } - START = "\033[" - COLOR = { - 'black': "0;30m", - 'red': "0;31m", - 'green': "0;32m", - 'yellow': "0;33m", - 'blue': "0;34m", - 'purple': "0;35m", - 'cyan': "0;36m", - 'white': "0;37m", - 'end': "0m", - } - - def __getattr__(self, name): - def handlerFunction(*args, **kwargs): - return self.START+self.FORMAT['Regular']+";"+self.COLOR[name.lower()] - return handlerFunction(name=name) - - -# ---------------------------------------------------------------------- -# Template - -class Template_mixin(object): - bc = bcolors() - - STATUS = { - 0: bc.GREEN+'pass'+bc.END, - 1: bc.PURPLE+'fail'+bc.END, - 2: bc.RED+'error'+bc.END, - } - - # ------------------------------------------------------------------------ - # Report - REPORT_TEST_WITH_OUTPUT_TMPL = r""" - %(desc)s - - %(status)s - - %(script)s - -""" # variables: (tid, Class, style, desc, status) - - REPORT_TEST_NO_OUTPUT_TMPL = r""" - %(desc)s - %(status)s -""" # variables: (tid, Class, style, desc, status) - - REPORT_TEST_OUTPUT_TMPL = r""" -%(output)s -""" # variables: (id, output) - - -class ColoredTestResult(unittest.TextTestResult): - - stdout_redirector = OutputRedirector(sys.stdout) - stderr_redirector = OutputRedirector(sys.stderr) - - def __init__(self, stream, descriptions, verbosity=1): - super(ColoredTestResult, self).__init__(stream, descriptions, verbosity) - self.stdout0 = None - self.stderr0 = None - self.success_count = 0 - self.failure_count = 0 - self.error_count = 0 - self.skip_count = 0 - self.verbosity = verbosity - - # deny TextTestResult showAll functionality - self.showAll = False - - # result is a list of result in 4 tuple - # ( - # result code (0: success; 1: fail; 2: error), - # TestCase object, - # Test output (byte string), - # stack trace, - # ) - self.result = [] - - def startTest(self, test): - super(ColoredTestResult, self).startTest(test) - # just one buffer for both stdout and stderr - self.outputBuffer = StringIO() - self.stdout_redirector.fp = self.outputBuffer - self.stderr_redirector.fp = self.outputBuffer - self.stdout0 = sys.stdout - self.stderr0 = sys.stderr - sys.stdout = self.stdout_redirector - sys.stderr = self.stderr_redirector - - def complete_output(self): - """ - Disconnect output redirection and return buffer. - Safe to call multiple times. - """ - if self.stdout0: - sys.stdout = self.stdout0 - sys.stderr = self.stderr0 - self.stdout0 = None - self.stderr0 = None - return self.outputBuffer.getvalue() - - def stopTest(self, test): - # Usually one of addSuccess, addError or addFailure would have been called. - # But there are some path in unittest that would bypass this. - # We must disconnect stdout in stopTest(), which is guaranteed to be called. - self.complete_output() - - def addSuccess(self, test): - self.success_count += 1 - super(ColoredTestResult, self).addSuccess(test) - output = self.complete_output() - self.result.append((0, test, output, '')) - if self.verbosity > 1: - sys.stdout.write('.') - sys.stdout.flush() - - if not hasattr(self, 'successes'): - self.successes = [test] - else: - self.successes.append(test) - - def addError(self, test, err): - self.error_count += 1 - super(ColoredTestResult, self).addError(test, err) - output = self.complete_output() - _, _exc_str = self.errors[-1] - self.result.append((2, test, output, _exc_str)) - if self.verbosity > 1: - sys.stdout.write('E') - sys.stdout.flush() - - def addFailure(self, test, err): - self.failure_count += 1 - super(ColoredTestResult, self).addFailure(test, err) - output = self.complete_output() - _, _exc_str = self.failures[-1] - self.result.append((1, test, output, _exc_str)) - if self.verbosity > 1: - sys.stdout.write('F') - sys.stdout.flush() - - def addSubTest(self, test, subtest, err): - if err is not None: - if issubclass(err[0], test.failureException): - self.addFailure(subtest, err) - else: - self.addError(subtest, err) - - def addSkip(self, test, reason): - self.skip_count += 1 - super(ColoredTestResult, self).addSkip(test, reason) - self.complete_output() - if self.verbosity > 1: - sys.stdout.write('s') - sys.stdout.flush() - - def get_all_cases_run(self): - '''Return a list of each test case which failed or succeeded - ''' - cases = [] - if hasattr(self, 'successes'): - cases.extend(self.successes) - cases.extend([failure[0] for failure in self.failures]) - return cases - - -class ColoredTestRunner(Template_mixin): - - def __init__(self, stream=sys.stdout, verbosity=1, title=None, description=None): - self.stream = stream - self.verbosity = verbosity - if title is None: - self.title = '' - else: - self.title = title - if description is None: - self.description = '' - else: - self.description = description - - self.startTime = datetime.datetime.now() - self.bc = bcolors() - self.desc_width = 40 - self.output_width = 60 - - def run(self, test): - "Run the given test case or test suite." - result = ColoredTestResult(stream=self.stream, descriptions=True, verbosity=self.verbosity) - test(result) - self.stopTime = datetime.datetime.now() - self.generateReport(test, result) - return result - - def sortResult(self, result_list): - # unittest does not seems to run in any particular order. - # Here at least we want to group them together by class. - rmap = {} - classes = [] - for n, test, output, error in result_list: - testClass = test.__class__ - if testClass not in rmap: - rmap[testClass] = [] - classes.append(testClass) - rmap[testClass].append((n, test, output, error)) - r = [(testClass, rmap[testClass]) for testClass in classes] - return r - - def getReportAttributes(self, result): - """ - Return report attributes as a list of (name, value). - Override this to add custom attributes. - """ - startTime = str(self.startTime)[:19] - duration = str(self.stopTime - self.startTime) - status = [] - padding = 4 * ' ' - if result.success_count: - status.append(padding + self.bc.GREEN + 'Pass:' + self.bc.END + ' %s\n' % result.success_count) - if result.failure_count: - status.append(padding + self.bc.PURPLE + 'Failure:' + self.bc.END + ' %s\n' % result.failure_count) - if result.error_count: - status.append(padding + self.bc.RED + 'Error:' + self.bc.END + ' %s\n' % result.error_count) - if status: - status = '\n'+''.join(status) - else: - status = 'none' - return [ - ('Start Time', startTime), - ('Duration', duration), - ('Status', status), - ] - - def generateReport(self, test, result): - report_attrs = self.getReportAttributes(result) - heading = self._generate_heading(report_attrs) - report = self._generate_report(result) - output = "\n" + self.title.rjust(30) + "\n" + heading + report - try: - self.stream.write(output.encode('utf8')) - except TypeError: - self.stream.write(output) - - def _generate_heading(self, report_attrs): - a_lines = [] - for name, value in report_attrs: - line = self.bc.CYAN + name + ": " + self.bc.END + value + "\n" - a_lines.append(line) - heading = ''.join(a_lines) + self.bc.CYAN + "Description:" + self.bc.END + self.description + "\n" - return heading - - def _generate_report(self, result): - sortedResult = self.sortResult(result.result) - padding = 4 * ' ' - table = Table(padding=padding, allow_newlines=True) - table.addTitles(["Test group/Test case", "Count", "Pass", "Fail", "Error"]) - tests = '' - for cid, (testClass, classResults) in enumerate(sortedResult): # Iterate over the test cases - classTable = Table(padding=2*padding) - classTable.addTitles(["Test name", "Output", "Status"]) - # subtotal for a class - np = nf = ne = 0 - for n, test, output, error in classResults: - if n == 0: - np += 1 - elif n == 1: - nf += 1 - else: - ne += 1 - - # format class description - if testClass.__module__ == "__main__": - name = testClass.__name__ - else: - name = "%s.%s" % (testClass.__module__, testClass.__name__) - tests += padding + name + "\n" - doc = testClass.__doc__ and testClass.__doc__.split("\n")[0] or "" - if doc: - doc = self._indent(self._wrap_text(doc, width=self.output_width - 4), 4) - desc = doc and ('%s:\n%s' % (name, doc)) or name - - table.addRow([self._wrap_text(desc, width=self.desc_width), str(np + nf + ne), str(np), str(nf), str(ne)]) - for tid, (n, test, output, error) in enumerate(classResults): # Iterate over the unit tests - classTable.addRow(self._generate_report_test(cid, tid, n, test, output, error)) - tests += str(classTable) - - for tid, (n, test, output, error) in enumerate(classResults): # Iterate over the unit tests - if error: - tests += self._indent(self.bc.RED + "ERROR in test %s:" % test + self.bc.END, 2) - tests += "\n" + self._indent(error, 2) + "\n" - - table.addRow([self.desc_width * '-', '----', '----', '----', '----']) - table.addRow(["Total", str(result.success_count + result.failure_count + result.error_count), - str(result.success_count), str(result.failure_count), str(result.error_count)]) - report = self.bc.CYAN + "Summary: " + self.bc.END + "\n" + str(table) + tests - return report - - def _generate_report_test(self, cid, tid, n, test, output, error): - name = test.id().split('.')[-1] - doc = test.shortDescription() or "" - if doc: - doc = self._indent(self._wrap_text(doc, width=self.output_width - 4), 4) - desc = doc and ('%s:\n%s' % (name, doc)) or name - - # o and e should be byte string because they are collected from stdout and stderr? - if isinstance(output, str): - # TODO: some problem with 'string_escape': it escape \n and mess up formating - # uo = unicode(o.encode('string_escape')) - try: - uo = output.decode('latin-1') - except AttributeError: - uo = output - else: - uo = output - if isinstance(error, str): - # TODO: some problem with 'string_escape': it escape \n and mess up formating - # ue = unicode(e.encode('string_escape')) - try: - ue = error.decode('latin-1') - except AttributeError: - ue = error - else: - ue = error - - # just print the last line of any error - if "\n" in ue: - ue = ue.splitlines()[-1] - - script = self.REPORT_TEST_OUTPUT_TMPL % dict( - output=self._wrap_text(uo, width=self.output_width) + self._wrap_text(ue, width=self.output_width), - ) - row = [desc, script, self.STATUS[n]] - return row - - @staticmethod - def _wrap_text(text, width): - """Wrap text to a given width but preserve line breaks - """ - # https://stackoverflow.com/a/26538082 - return '\n'.join(['\n'.join(textwrap.wrap(line, width, break_long_words=False, replace_whitespace=False)) - for line in text.splitlines() if line.strip() != '']) - - @staticmethod - def _indent(text, amount): - """Indent text by a particular number of spaces on each line - """ - try: - return textwrap.indent(text, amount * ' ') - except AttributeError: # undefined function (indent wasn't added until Python 3.3) - return ''.join((amount * ' ') + line for line in text.splitlines(True)) diff --git a/tests/integration/hdf5/test_base.py b/tests/integration/hdf5/test_base.py index 3a7c06221..a13ffe7ff 100644 --- a/tests/integration/hdf5/test_base.py +++ b/tests/integration/hdf5/test_base.py @@ -15,7 +15,8 @@ def setUpContainer(self): data=list(range(1000)), unit='SIunit', timestamps=np.arange(1000.), - resolution=0.1 + resolution=0.1, + continuity='continuous', ) diff --git a/tests/integration/hdf5/test_ecephys.py b/tests/integration/hdf5/test_ecephys.py index 392f9375c..cc70ee9dc 100644 --- a/tests/integration/hdf5/test_ecephys.py +++ b/tests/integration/hdf5/test_ecephys.py @@ -40,7 +40,7 @@ def make_electrode_table(self): location='tetrode location', device=self.dev1) for i in range(4): - self.table.add_row(x=i, y=2.0, z=3.0, imp=-1.0, location='CA1', filtering='none', group=self.group, + self.table.add_row(x=float(i), y=2.0, z=3.0, imp=-1.0, location='CA1', filtering='none', group=self.group, group_name='tetrode1') def setUpContainer(self): @@ -52,11 +52,16 @@ def setUpContainer(self): table=self.table) data = list(zip(range(10), range(10, 20))) timestamps = list(map(lambda x: x/10., range(10))) - es = ElectricalSeries(name='test_eS', - data=data, - electrodes=region, - channel_conversion=[4., .4], - timestamps=timestamps) + channel_conversion = [1., 2., 3., 4.] + filtering = 'Low-pass filter at 300 Hz' + es = ElectricalSeries( + name='test_eS', + data=data, + electrodes=region, + channel_conversion=channel_conversion, + filtering=filtering, + timestamps=timestamps + ) return es def addContainer(self, nwbfile): @@ -145,6 +150,11 @@ def roundtripContainer(self, cache_spec=False): with self.assertWarnsWith(DeprecationWarning, 'use pynwb.misc.Units or NWBFile.units instead'): return super().roundtripContainer(cache_spec) + def roundtripExportContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the Clustering object from file + with self.assertWarnsWith(DeprecationWarning, 'use pynwb.misc.Units or NWBFile.units instead'): + return super().roundtripExportContainer(cache_spec) + class EventWaveformConstructor(AcquisitionH5IOMixin, TestCase): @@ -195,6 +205,11 @@ def roundtripContainer(self, cache_spec=False): with self.assertWarnsWith(DeprecationWarning, 'use pynwb.misc.Units or NWBFile.units instead'): return super().roundtripContainer(cache_spec) + def roundtripExportContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the Clustering object from file + with self.assertWarnsWith(DeprecationWarning, 'use pynwb.misc.Units or NWBFile.units instead'): + return super().roundtripExportContainer(cache_spec) + class FeatureExtractionConstructor(AcquisitionH5IOMixin, TestCase): diff --git a/tests/integration/hdf5/test_icephys.py b/tests/integration/hdf5/test_icephys.py index 564f0a342..490b06d68 100644 --- a/tests/integration/hdf5/test_icephys.py +++ b/tests/integration/hdf5/test_icephys.py @@ -6,6 +6,7 @@ VoltageClampSeries, IZeroClampSeries) from pynwb.device import Device from pynwb.testing import NWBH5IOMixin, AcquisitionH5IOMixin, TestCase +import warnings class TestIntracellularElectrode(NWBH5IOMixin, TestCase): @@ -128,7 +129,14 @@ def setUpContainer(self): self.pcs = PatchClampSeries(name="pcs", data=[1, 2, 3, 4, 5], unit='A', starting_time=123.6, rate=10e3, electrode=self.elec, gain=0.126, stimulus_description="gotcha ya!", sweep_number=np.uint(4711)) - return SweepTable(name='sweep_table') + # Create the SweepTable but ignore the DeprecationWarning + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('ignore', DeprecationWarning) + sweeptable = SweepTable(name='sweep_table') + # Reissue any other warnings that may have occured + for i in w: + warnings.warn(i.message, i.category) + return sweeptable def addContainer(self, nwbfile): """ @@ -137,12 +145,26 @@ def addContainer(self, nwbfile): nwbfile.sweep_table = self.container nwbfile.add_device(self.device) nwbfile.add_icephys_electrode(self.elec) - nwbfile.add_acquisition(self.pcs) + nwbfile.add_acquisition(self.pcs, use_sweep_table=True) def getContainer(self, nwbfile): """ Return the test SweepTable from the given NWBFile """ return nwbfile.sweep_table + def roundtripContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the SweepTable object from file + with self.assertWarnsWith(DeprecationWarning, + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable instead. " + "See also the NWBFile.add_intracellular_recordings function."): + return super().roundtripContainer(cache_spec) + + def roundtripExportContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the SweepTable object from file + with self.assertWarnsWith(DeprecationWarning, + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable instead. " + "See also the NWBFile.add_intracellular_recordings function."): + return super().roundtripExportContainer(cache_spec) + def test_container(self): """ Test properties of the SweepTable read from file """ description = 'a file to test writing and reading a %s' % self.container_type @@ -178,7 +200,14 @@ def setUpContainer(self): starting_time=123.6, rate=10e3, electrode=self.elec, gain=0.126, stimulus_description="gotcha ya!", sweep_number=np.uint(4712)) - return SweepTable(name='sweep_table') + # Create the SweepTable but ignore the DeprecationWarning + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('ignore', DeprecationWarning) + sweeptable = SweepTable(name='sweep_table') + # Reissue any other warnings that may have occured + for i in w: + warnings.warn(i.message, i.category) + return sweeptable def addContainer(self, nwbfile): """ @@ -188,14 +217,28 @@ def addContainer(self, nwbfile): nwbfile.add_device(self.device) nwbfile.add_icephys_electrode(self.elec) - nwbfile.add_acquisition(self.pcs1) - nwbfile.add_stimulus_template(self.pcs2a) - nwbfile.add_stimulus(self.pcs2b) + nwbfile.add_acquisition(self.pcs1, use_sweep_table=True) + nwbfile.add_stimulus_template(self.pcs2a, use_sweep_table=True) + nwbfile.add_stimulus(self.pcs2b, use_sweep_table=True) def getContainer(self, nwbfile): """ Return the test SweepTable from the given NWBFile """ return nwbfile.sweep_table + def roundtripContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the SweepTable object from file + with self.assertWarnsWith(DeprecationWarning, + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable instead. " + "See also the NWBFile.add_intracellular_recordings function."): + return super().roundtripContainer(cache_spec) + + def roundtripExportContainer(self, cache_spec=False): + # catch the DeprecationWarning raised when reading the SweepTable object from file + with self.assertWarnsWith(DeprecationWarning, + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable instead. " + "See also the NWBFile.add_intracellular_recordings function."): + return super().roundtripExportContainer(cache_spec) + def test_container(self): """ Test properties of the SweepTable read from file """ description = 'a file to test writing and reading a %s' % self.container_type diff --git a/tests/integration/hdf5/test_image.py b/tests/integration/hdf5/test_image.py index 558fb3c98..d10770f83 100644 --- a/tests/integration/hdf5/test_image.py +++ b/tests/integration/hdf5/test_image.py @@ -1,25 +1,54 @@ import numpy as np -from pynwb.image import OpticalSeries -from pynwb.testing import NWBH5IOMixin, TestCase +from pynwb.device import Device +from pynwb.image import ImageSeries, OpticalSeries +from pynwb.testing import AcquisitionH5IOMixin, NWBH5IOMixin, TestCase + + +class TestImageSeriesIO(AcquisitionH5IOMixin, TestCase): + + def setUpContainer(self): + """ Return a test ImageSeries to read/write """ + self.dev1 = Device('dev1') + iS = ImageSeries( + name='test_iS', + data=np.ones((3, 3, 3)), + unit='unit', + external_file=['external_file'], + starting_frame=[1, 2, 3], + format='tiff', + timestamps=list(), + device=self.dev1, + ) + return iS + + def addContainer(self, nwbfile): + """ Add the test ElectrodeGroup to the given NWBFile """ + nwbfile.add_device(self.dev1) + super().addContainer(nwbfile) class TestOpticalSeriesIO(NWBH5IOMixin, TestCase): def setUpContainer(self): """ Return a test OpticalSeries to read/write """ - self.optical_series = OpticalSeries(name='OpticalSeries', - distance=8., - field_of_view=(4., 5.), - orientation='upper left', - data=np.ones((10, 3, 3)), - unit='m', - format='raw', - timestamps=np.arange(10.)) + self.dev1 = Device('dev1') + self.optical_series = OpticalSeries( + name='OpticalSeries', + distance=8., + field_of_view=(4., 5.), + orientation='upper left', + data=np.ones((10, 3, 3)), + unit='m', + format='raw', + timestamps=np.arange(10.), + device=self.dev1, + ) return self.optical_series def addContainer(self, nwbfile): """ Add the test OpticalSeries to the given NWBFile """ + nwbfile.add_device(self.dev1) nwbfile.add_stimulus(self.optical_series) def getContainer(self, nwbfile): diff --git a/tests/integration/hdf5/test_misc.py b/tests/integration/hdf5/test_misc.py index 396985993..3bfa42a33 100644 --- a/tests/integration/hdf5/test_misc.py +++ b/tests/integration/hdf5/test_misc.py @@ -1,9 +1,12 @@ import numpy as np -from hdmf.common import DynamicTable, VectorData +from hdmf.common import DynamicTable, VectorData, DynamicTableRegion from pynwb import TimeSeries from pynwb.misc import Units, DecompositionSeries from pynwb.testing import NWBH5IOMixin, AcquisitionH5IOMixin, TestCase +from pynwb.ecephys import ElectrodeGroup +from pynwb.device import Device +from pynwb.file import ElectrodeTable as get_electrode_table class TestUnitsIO(AcquisitionH5IOMixin, TestCase): @@ -12,7 +15,7 @@ class TestUnitsIO(AcquisitionH5IOMixin, TestCase): def setUpContainer(self): """ Return the test Units to read/write """ ut = Units(name='UnitsTest', description='a simple table for testing Units') - ut.add_unit(spike_times=[0, 1, 2], obs_intervals=[[0, 1], [2, 3]], + ut.add_unit(spike_times=[0., 1., 2.], obs_intervals=[[0., 1.], [2., 3.]], waveform_mean=[1., 2., 3.], waveform_sd=[4., 5., 6.], waveforms=[ [ # elec 1 @@ -25,7 +28,7 @@ def setUpContainer(self): [1, 2, 3] ] ]) - ut.add_unit(spike_times=[3, 4, 5], obs_intervals=[[2, 5], [6, 7]], + ut.add_unit(spike_times=[3., 4., 5.], obs_intervals=[[2., 5.], [6., 7.]], waveform_mean=[1., 2., 3.], waveform_sd=[4., 5., 6.], waveforms=np.array([ [ # elec 1 @@ -53,19 +56,19 @@ def test_get_spike_times(self): """ Test whether the Units spike times read from file are what was written """ ut = self.roundtripContainer() received = ut.get_unit_spike_times(0) - self.assertTrue(np.array_equal(received, [0, 1, 2])) + self.assertTrue(np.array_equal(received, [0., 1., 2.])) received = ut.get_unit_spike_times(1) - self.assertTrue(np.array_equal(received, [3, 4, 5])) - self.assertTrue(np.array_equal(ut['spike_times'][:], [[0, 1, 2], [3, 4, 5]])) + self.assertTrue(np.array_equal(received, [3., 4., 5.])) + self.assertTrue(np.array_equal(ut['spike_times'][:], [[0., 1., 2.], [3., 4., 5.]])) def test_get_obs_intervals(self): """ Test whether the Units observation intervals read from file are what was written """ ut = self.roundtripContainer() received = ut.get_unit_obs_intervals(0) - self.assertTrue(np.array_equal(received, [[0, 1], [2, 3]])) + self.assertTrue(np.array_equal(received, [[0., 1.], [2., 3.]])) received = ut.get_unit_obs_intervals(1) - self.assertTrue(np.array_equal(received, [[2, 5], [6, 7]])) - self.assertTrue(np.array_equal(ut['obs_intervals'][:], [[[0, 1], [2, 3]], [[2, 5], [6, 7]]])) + self.assertTrue(np.array_equal(received, [[2., 5.], [6., 7.]])) + self.assertTrue(np.array_equal(ut['obs_intervals'][:], [[[0., 1.], [2., 3.]], [[2., 5.], [6., 7.]]])) class TestUnitsFileIO(NWBH5IOMixin, TestCase): @@ -134,3 +137,53 @@ def addContainer(self, nwbfile): def getContainer(self, nwbfile): """ Return the test DecompositionSeries from the given NWBFile """ return nwbfile.processing['test_mod']['LFPSpectralAnalysis'] + + +class TestDecompositionSeriesWithSourceChannelsIO(AcquisitionH5IOMixin, TestCase): + + @staticmethod + def make_electrode_table(self): + """ Make an electrode table, electrode group, and device """ + self.table = get_electrode_table() + self.dev1 = Device(name='dev1') + self.group = ElectrodeGroup(name='tetrode1', + description='tetrode description', + location='tetrode location', + device=self.dev1) + for i in range(4): + self.table.add_row(x=float(i), y=2.0, z=3.0, imp=-1.0, location='CA1', filtering='none', group=self.group, + group_name='tetrode1') + + def setUpContainer(self): + """ Return the test ElectricalSeries to read/write """ + self.make_electrode_table(self) + region = DynamicTableRegion(name='source_channels', + data=[0, 2], + description='the first and third electrodes', + table=self.table) + data = np.random.randn(100, 2, 30) + timestamps = np.arange(100)/100 + ds = DecompositionSeries(name='test_DS', + data=data, + source_channels=region, + timestamps=timestamps, + metric='amplitude') + return ds + + def addContainer(self, nwbfile): + """ Add the test ElectricalSeries and related objects to the given NWBFile """ + nwbfile.add_device(self.dev1) + nwbfile.add_electrode_group(self.group) + nwbfile.set_electrode_table(self.table) + nwbfile.add_acquisition(self.container) + + def test_eg_ref(self): + """ + Test that the electrode DynamicTableRegion references of the read ElectricalSeries have a group that + correctly resolves to ElectrodeGroup instances. + """ + read = self.roundtripContainer() + row1 = read.source_channels[0] + row2 = read.source_channels[1] + self.assertIsInstance(row1.iloc[0]['group'], ElectrodeGroup) + self.assertIsInstance(row2.iloc[0]['group'], ElectrodeGroup) diff --git a/tests/integration/hdf5/test_nwbfile.py b/tests/integration/hdf5/test_nwbfile.py index f9168b642..70909c029 100644 --- a/tests/integration/hdf5/test_nwbfile.py +++ b/tests/integration/hdf5/test_nwbfile.py @@ -203,14 +203,15 @@ class TestSubjectIO(NWBH5IOMixin, TestCase): def setUpContainer(self): """ Return the test Subject """ - return Subject(age='12 mo', + return Subject(age='P90D', description='An unfortunate rat', genotype='WT', sex='M', species='Rattus norvegicus', subject_id='RAT123', - weight='2 lbs', - date_of_birth=datetime(1970, 1, 1, 12, tzinfo=tzutc())) + weight='2 kg', + date_of_birth=datetime(1970, 1, 1, 12, tzinfo=tzutc()), + strain='my_strain') def addContainer(self, nwbfile): """ Add the test Subject to the given NWBFile """ diff --git a/tests/integration/hdf5/test_ophys.py b/tests/integration/hdf5/test_ophys.py index dec550a84..6507efccf 100644 --- a/tests/integration/hdf5/test_ophys.py +++ b/tests/integration/hdf5/test_ophys.py @@ -1,5 +1,6 @@ -from copy import deepcopy from abc import ABCMeta +from copy import deepcopy +import numpy as np from pynwb.ophys import ( ImagingPlane, @@ -7,13 +8,39 @@ PlaneSegmentation, ImageSegmentation, TwoPhotonSeries, - RoiResponseSeries + RoiResponseSeries, + MotionCorrection, + CorrectedImageStack, ) +from pynwb.base import TimeSeries from pynwb.image import ImageSeries from pynwb.device import Device from pynwb.testing import NWBH5IOMixin, AcquisitionH5IOMixin, TestCase +def make_imaging_plane(): + """ Make an ImagingPlane and related objects """ + device = Device(name='dev1') + optical_channel = OpticalChannel( + name='optchan1', + description='a fake OpticalChannel', + emission_lambda=500. + ) + imaging_plane = ImagingPlane( + name='imgpln1', + optical_channel=optical_channel, + description='a fake ImagingPlane', + device=device, + excitation_lambda=600., + imaging_rate=300., + indicator='GFP', + location='somewhere in the brain', + reference_frame='unknown' + ) + + return device, optical_channel, imaging_plane + + class TestImagingPlaneIO(NWBH5IOMixin, TestCase): def setUpContainer(self): @@ -50,31 +77,69 @@ def getContainer(self, nwbfile): return nwbfile.get_imaging_plane(self.container.name) -class TestTwoPhotonSeriesIO(AcquisitionH5IOMixin, TestCase): +class TestMotionCorrection(NWBH5IOMixin, TestCase): - def make_imaging_plane(self): - """ Make an ImagingPlane and related objects """ - self.device = Device(name='dev1') - self.optical_channel = OpticalChannel( - name='optchan1', - description='a fake OpticalChannel', - emission_lambda=500. + def setUpContainer(self): + """ Return the test ImagingPlane to read/write """ + + self.device, self.optical_channel, self.imaging_plane = make_imaging_plane() + + self.two_photon_series = TwoPhotonSeries( + name='TwoPhotonSeries', + data=np.ones((1000, 100, 100)), + imaging_plane=self.imaging_plane, + rate=1.0, + unit='normalized amplitude' ) - self.imaging_plane = ImagingPlane( - name='imgpln1', - optical_channel=self.optical_channel, - description='a fake ImagingPlane', - device=self.device, - excitation_lambda=600., - imaging_rate=300., - indicator='GFP', - location='somewhere in the brain', - reference_frame='unknown' + + corrected = ImageSeries( + name='corrected', + data=np.ones((1000, 100, 100)), + unit='na', + format='raw', + starting_time=0.0, + rate=1.0 + ) + + xy_translation = TimeSeries( + name='xy_translation', + data=np.ones((1000, 2)), + unit='pixels', + starting_time=0.0, + rate=1.0, + ) + + corrected_image_stack = CorrectedImageStack( + corrected=corrected, + original=self.two_photon_series, + xy_translation=xy_translation, ) + return MotionCorrection(corrected_image_stacks=[corrected_image_stack]) + + def addContainer(self, nwbfile): + """ Add the test ImagingPlane and Device to the given NWBFile """ + + nwbfile.add_device(self.device) + nwbfile.add_imaging_plane(self.imaging_plane) + nwbfile.add_acquisition(self.two_photon_series) + + ophys_module = nwbfile.create_processing_module( + name='ophys', + description='optical physiology processed data' + ) + ophys_module.add(self.container) + + def getContainer(self, nwbfile): + """ Return the test ImagingPlane from the given NWBFile """ + return nwbfile.processing['ophys'].data_interfaces['MotionCorrection'] + + +class TestTwoPhotonSeriesIO(AcquisitionH5IOMixin, TestCase): + def setUpContainer(self): """ Return the test TwoPhotonSeries to read/write """ - self.make_imaging_plane() + self.device, self.optical_channel, self.imaging_plane = make_imaging_plane() data = [[[1., 1.] * 2] * 2] timestamps = list(map(lambda x: x/10, range(10))) fov = [2.0, 2.0, 5.0] @@ -257,3 +322,47 @@ def addContainer(self, nwbfile): description='a plain module for testing') mod.add(img_seg) super().addContainer(nwbfile) + + +class TestCorrectedImageStackIO(AcquisitionH5IOMixin, TestCase): + + def setUpContainer(self): + """Return the test CorrectedImageStack to read/write.""" + data = np.ones((2, 2, 2)), + timestamps = [1., 2.] + + corrected_is = ImageSeries( + name='corrected', + data=data, + unit='unit', + external_file=['external_file'], + starting_frame=[1, 2, 3], + format='tiff', + timestamps=timestamps + ) + self.original_is = ImageSeries( + name='original_is', + data=data, + unit='unit', + external_file=['external_file'], + starting_frame=[1, 2, 3], + format='tiff', + timestamps=timestamps + ) + tstamps = [1., 2., 3.] + ts = TimeSeries( + name='xy_translation', + data=list(range(len(tstamps))), + unit='unit', + timestamps=tstamps + ) + return CorrectedImageStack( + corrected=corrected_is, + original=self.original_is, + xy_translation=ts + ) + + def addContainer(self, nwbfile): + """Add the test CorrectedImageStack and the original ImageSeries in acquisition.""" + nwbfile.add_acquisition(self.original_is) + super().addContainer(nwbfile) diff --git a/tests/integration/test_io.py b/tests/integration/test_io.py index d9bd26fe1..30e939c9b 100644 --- a/tests/integration/test_io.py +++ b/tests/integration/test_io.py @@ -275,8 +275,17 @@ def test_append(self): self.assertIs(nwb.processing['test_proc_mod']['LFP'].electrical_series['test_es'].electrodes, nwb.acquisition['timeseries2'].electrodes) errors = validate(io) - for e in errors: - print('ERROR', e) # noqa: T001 + self.assertEqual(len(errors), 0, errors) + + def test_electrode_id_uniqueness(self): + device = self.nwbfile.create_device(name='test_device') + e_group = self.nwbfile.create_electrode_group(name='test_electrode_group', + description='', + location='', + device=device) + self.nwbfile.add_electrode(id=0, x=0.0, y=0.0, z=0.0, imp=np.nan, location='', filtering='', group=e_group) + with self.assertRaises(ValueError): + self.nwbfile.add_electrode(id=0, x=0.0, y=0.0, z=0.0, imp=np.nan, location='', filtering='', group=e_group) class TestH5DataIO(TestCase): diff --git a/tests/unit/test_base.py b/tests/unit/test_base.py index 99dfce1d1..a67d5b2f8 100644 --- a/tests/unit/test_base.py +++ b/tests/unit/test_base.py @@ -1,6 +1,6 @@ import numpy as np -from pynwb.base import ProcessingModule, TimeSeries, Images, Image +from pynwb.base import ProcessingModule, TimeSeries, Images, Image, TimeSeriesReferenceVectorData from pynwb.testing import TestCase from hdmf.data_utils import DataChunkIterator from hdmf.backends.hdf5 import H5DataIO @@ -124,6 +124,18 @@ def test_timestamps_timeseries(self): 'grams', timestamps=ts1) self.assertEqual(ts2.timestamps, [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]) + def test_good_continuity_timeseries(self): + ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5], + 'grams', timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5], + continuity='continuous') + self.assertEqual(ts1.continuity, 'continuous') + + def test_bad_continuity_timeseries(self): + with self.assertRaises(ValueError): + TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5], + 'grams', timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5], + continuity='wrong') + def test_nodata(self): ts1 = TimeSeries('test_ts1', starting_time=0.0, rate=0.1) with self.assertWarns(UserWarning): @@ -209,3 +221,9 @@ def test_images(self): image = Image(name='test_image', data=np.ones((10, 10))) image2 = Image(name='test_image2', data=np.ones((10, 10))) Images(name='images_name', images=[image, image2]) + + +class TestTimeSeriesReferenceVectorData(TestCase): + + def test_init(self): + TimeSeriesReferenceVectorData(name='test', description='test') diff --git a/tests/unit/test_core.py b/tests/unit/test_core.py index 1cd19781e..0a9d74f85 100644 --- a/tests/unit/test_core.py +++ b/tests/unit/test_core.py @@ -2,6 +2,7 @@ from dateutil.tz import tzlocal from hdmf.utils import docval, call_docval_func +from hdmf import __version__ as hdmfversion from pynwb import NWBFile, TimeSeries, available_namespaces from pynwb.core import NWBContainer @@ -81,4 +82,4 @@ def test_print_file(self): class TestAvailableNamespaces(TestCase): def test_available_namespaces(self): - self.assertEqual(available_namespaces(), ('hdmf-common', 'core')) + self.assertEqual(available_namespaces(), ('hdmf-common', 'hdmf-experimental', 'core')) diff --git a/tests/unit/test_ecephys.py b/tests/unit/test_ecephys.py index d8b2682b3..e9048da6c 100644 --- a/tests/unit/test_ecephys.py +++ b/tests/unit/test_ecephys.py @@ -29,12 +29,24 @@ class ElectricalSeriesConstructor(TestCase): def test_init(self): data = list(range(10)) ts = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0] + channel_conversion = [2., 6.3] + filtering = 'Low-pass filter at 300 Hz' table = make_electrode_table() region = DynamicTableRegion('electrodes', [0, 2], 'the first and third electrodes', table) - eS = ElectricalSeries('test_eS', data, region, channel_conversion=[2., 6.3], timestamps=ts) + eS = ElectricalSeries( + name='test_eS', + data=data, + electrodes=region, + channel_conversion=channel_conversion, + filtering=filtering, + timestamps=ts + ) self.assertEqual(eS.name, 'test_eS') self.assertEqual(eS.data, data) + self.assertEqual(eS.electrodes, region) self.assertEqual(eS.timestamps, ts) + self.assertEqual(eS.channel_conversion, [2., 6.3]) + self.assertEqual(eS.filtering, filtering) def test_link(self): table = make_electrode_table() diff --git a/tests/unit/test_epoch.py b/tests/unit/test_epoch.py index 774edc41f..64278130d 100644 --- a/tests/unit/test_epoch.py +++ b/tests/unit/test_epoch.py @@ -11,7 +11,7 @@ class TimeIntervalsTest(TestCase): def test_init(self): - tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float) + tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float64) ts = TimeSeries("test_ts", list(range(len(tstamps))), 'unit', timestamps=tstamps) ept = TimeIntervals('epochs', "TimeIntervals unittest") self.assertEqual(ept.name, 'epochs') diff --git a/tests/unit/test_extension.py b/tests/unit/test_extension.py index 6259fba60..abfe96bf5 100644 --- a/tests/unit/test_extension.py +++ b/tests/unit/test_extension.py @@ -49,7 +49,7 @@ def test_load_namespace(self): def test_get_class(self): self.test_export() type_map = get_type_map(extensions=os.path.join(self.tempdir, self.ns_path)) - type_map.get_container_cls(self.prefix, 'TetrodeSeries') + type_map.get_dt_container_cls('TetrodeSeries', self.prefix) def test_load_namespace_with_reftype_attribute(self): ns_builder = NWBNamespaceBuilder('Extension for use in my Lab', self.prefix, version='0.1.0') @@ -74,7 +74,7 @@ def test_load_namespace_with_reftype_attribute_check_autoclass_const(self): ns_builder.add_spec(self.ext_source, test_ds_ext) ns_builder.export(self.ns_path, outdir=self.tempdir) type_map = get_type_map(extensions=os.path.join(self.tempdir, self.ns_path)) - my_new_type = type_map.get_container_cls(self.prefix, 'my_new_type') + my_new_type = type_map.get_dt_container_cls('my_new_type', self.prefix) docval = None for tmp in get_docval(my_new_type.__init__): if tmp['name'] == 'target_ds': @@ -169,28 +169,3 @@ def test_catch_dup_name(self): ns_builder2.export(self.ns_path2, outdir=self.tempdir) type_map = get_type_map(extensions=os.path.join(self.tempdir, self.ns_path1)) type_map.load_namespaces(os.path.join(self.tempdir, self.ns_path2)) - - -class TestCatchDuplicateSpec(TestCase): - - def setUp(self): - self.prefix = id_generator() - self.ext_source = '%s_extension3.yaml' % self.prefix - - def tearDown(self): - pass - - def test_catch_duplicate_spec(self): - spec1 = NWBGroupSpec("This is my new group 1", - "Group1", - neurodata_type_inc="NWBDataInterface", - neurodata_type_def="Group1") - spec2 = NWBGroupSpec("This is my new group 2", - "Group2", - groups=[spec1], - neurodata_type_inc="NWBDataInterface", - neurodata_type_def="Group2") - ns_builder = NWBNamespaceBuilder("Example namespace", "pynwb_test_ext", version='0.1.0') - ns_builder.add_spec(self.ext_source, spec1) - with self.assertRaises(ValueError): - ns_builder.add_spec(self.ext_source, spec2) diff --git a/tests/unit/test_file.py b/tests/unit/test_file.py index 8476914f5..c68ff5589 100644 --- a/tests/unit/test_file.py +++ b/tests/unit/test_file.py @@ -130,7 +130,7 @@ def test_access_processing(self): def test_epoch_tags(self): tags1 = ['t1', 't2'] tags2 = ['t3', 't4'] - tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float) + tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float64) ts = TimeSeries("test_ts", list(range(len(tstamps))), 'unit', timestamps=tstamps) expected_tags = tags1 + tags2 self.nwbfile.add_epoch(0.0, 1.0, tags1, ts) @@ -417,14 +417,15 @@ def test_multi_publications(self): class SubjectTest(TestCase): def setUp(self): - self.subject = Subject(age='12 mo', + self.subject = Subject(age='P90D', description='An unfortunate rat', genotype='WT', sex='M', species='Rattus norvegicus', subject_id='RAT123', - weight='2 lbs', - date_of_birth=datetime(2017, 5, 1, 12, tzinfo=tzlocal())) + weight='2 kg', + date_of_birth=datetime(2017, 5, 1, 12, tzinfo=tzlocal()), + strain='my_strain') self.start = datetime(2017, 5, 1, 12, tzinfo=tzlocal()) self.path = 'nwbfile_test.h5' self.nwbfile = NWBFile('a test session description for a test NWBFile', @@ -438,17 +439,26 @@ def setUp(self): subject=self.subject) def test_constructor(self): - self.assertEqual(self.subject.age, '12 mo') + self.assertEqual(self.subject.age, 'P90D') self.assertEqual(self.subject.description, 'An unfortunate rat') self.assertEqual(self.subject.genotype, 'WT') self.assertEqual(self.subject.sex, 'M') self.assertEqual(self.subject.species, 'Rattus norvegicus') self.assertEqual(self.subject.subject_id, 'RAT123') - self.assertEqual(self.subject.weight, '2 lbs') + self.assertEqual(self.subject.weight, '2 kg') + self.assertEqual(self.subject.date_of_birth, datetime(2017, 5, 1, 12, tzinfo=tzlocal())) + self.assertEqual(self.subject.strain, 'my_strain') def test_nwbfile_constructor(self): self.assertIs(self.nwbfile.subject, self.subject) + def test_weight_float(self): + subject = Subject( + subject_id='RAT123', + weight=2.3, + ) + self.assertEqual(subject.weight, '2.3 kg') + class TestCacheSpec(TestCase): diff --git a/tests/unit/test_icephys.py b/tests/unit/test_icephys.py index 5610a613e..bc5b43c98 100644 --- a/tests/unit/test_icephys.py +++ b/tests/unit/test_icephys.py @@ -1,7 +1,7 @@ import numpy as np -from pynwb.icephys import PatchClampSeries, CurrentClampSeries, IZeroClampSeries, CurrentClampStimulusSeries, \ - VoltageClampSeries, VoltageClampStimulusSeries, IntracellularElectrode +from pynwb.icephys import (PatchClampSeries, CurrentClampSeries, IZeroClampSeries, CurrentClampStimulusSeries, + VoltageClampSeries, VoltageClampStimulusSeries, IntracellularElectrode, SweepTable) from pynwb.device import Device from pynwb.testing import TestCase from pynwb.file import NWBFile # Needed to test icephys functionality defined on NWBFile @@ -29,6 +29,17 @@ class NWBFileICEphys(TestCase): def setUp(self): self.icephys_electrode = GetElectrode() + def test_sweep_table_depractation_warn(self): + msg = ("Use of SweepTable is deprecated. Use the IntracellularRecordingsTable " + "instead. See also the NWBFile.add_intracellular_recordings function.") + with self.assertWarnsWith(DeprecationWarning, msg): + _ = NWBFile( + session_description='NWBFile icephys test', + identifier='NWB123', # required + session_start_time=datetime(2017, 4, 3, 11, tzinfo=tzlocal()), + ic_electrodes=[self.icephys_electrode, ], + sweep_table=SweepTable()) + def test_ic_electrodes_parameter_deprecation(self): # Make sure we warn when using the ic_electrodes parameter on NWBFile msg = "Use of the ic_electrodes parameter is deprecated. Use the icephys_electrodes parameter instead" @@ -225,6 +236,7 @@ def test_init(self): self.assertEqual(iZCS.bias_current, 0.0) self.assertEqual(iZCS.bridge_balance, 0.0) self.assertEqual(iZCS.capacitance_compensation, 0.0) + self.assertEqual(iZCS.stimulus_description, 'N/A') def test_unit_warning(self): electrode_name = GetElectrode() @@ -234,6 +246,16 @@ def test_unit_warning(self): iZCS = IZeroClampSeries('test_iZCS', list(), electrode_name, 1.0, timestamps=list(), unit='unit') self.assertEqual(iZCS.unit, 'volts') + def test_stim_desc_warning(self): + electrode_name = GetElectrode() + + msg = ("Stimulus description 'desc' for IZeroClampSeries 'test_iZCS' is ignored and will be set to 'N/A' " + "as per NWB 2.3.0.") + with self.assertWarnsWith(UserWarning, msg): + iZCS = IZeroClampSeries('test_iZCS', list(), electrode_name, 1.0, timestamps=list(), + stimulus_description='desc') + self.assertEqual(iZCS.stimulus_description, 'N/A') + class CurrentClampStimulusSeriesConstructor(TestCase): diff --git a/tests/unit/test_icephys_metadata_tables.py b/tests/unit/test_icephys_metadata_tables.py new file mode 100644 index 000000000..1fd67cc33 --- /dev/null +++ b/tests/unit/test_icephys_metadata_tables.py @@ -0,0 +1,1458 @@ +""" +Module for testing of the intracellular electrophysiology experiment metadata +tables originally created as part of the ndx-icephy-meta extension. These +are tested in this separate module to avoid crowding of the main test_icephys +test module and to allow us to test the main experiment metadata structures +separately. +""" +import numpy as np +from datetime import datetime +from dateutil.tz import tzlocal +from pandas.testing import assert_frame_equal +from numpy.testing import assert_array_equal +import warnings +import h5py + + +from pynwb.testing import TestCase, remove_test_file +from pynwb.file import NWBFile +from pynwb.icephys import (VoltageClampStimulusSeries, VoltageClampSeries, CurrentClampStimulusSeries, + IZeroClampSeries, IntracellularRecordingsTable, SimultaneousRecordingsTable, + SequentialRecordingsTable, RepetitionsTable, ExperimentalConditionsTable) +from pynwb import NWBHDF5IO +from hdmf.utils import docval, popargs + + +class ICEphysMetaTestBase(TestCase): + """ + Base helper class for setting up tests for the ndx-icephys-meta extension. + + Here we use the base NWBFile class for read/write (rather than our custom ICEphysFile) + to make sure tests of the individual tables do not depend on our custom class. We are testing + ICEphysFile separately. + """ + @classmethod + def create_stimulus_and_response(cls, sweep_number, electrode, randomize_data): + """ + Internal helper function to construct a dummy stimulus and reponse pair representing an + instracellular recording: + + :param sweep_number: Integer sweep number of the recording + :param electrode: Intracellular electrode used + :param randomize_data: Randomize data values in the stimulus and response + + :returns: Tuple of VoltageClampStimulusSeries with the stimulus and VoltageClampSeries with the response. + """ + stimulus = VoltageClampStimulusSeries( + name="ccss_"+str(sweep_number), + data=[1, 2, 3, 4, 5] if not randomize_data else np.random.rand(10), + starting_time=123.6 if not randomize_data else (np.random.rand() * 100), + rate=10e3 if not randomize_data else int(np.random.rand()*10) * 1000 + 1000., + electrode=electrode, + gain=0.1 if not randomize_data else np.random.rand(), + sweep_number=sweep_number) + # Create and ic-response + response = VoltageClampSeries( + name='vcs_'+str(sweep_number), + data=[0.1, 0.2, 0.3, 0.4, 0.5] if not randomize_data else np.random.rand(10), + conversion=1e-12, + resolution=np.nan, + starting_time=123.6 if not randomize_data else (np.random.rand() * 100), + rate=20e3 if not randomize_data else int(np.random.rand() * 20) * 1000. + 1000., + electrode=electrode, + gain=0.02 if not randomize_data else np.random.rand(), + capacitance_slow=100e-12, + resistance_comp_correction=70.0 if not randomize_data else 70.0 + np.random.rand(), + sweep_number=sweep_number) + return stimulus, response + + @classmethod + def create_icephs_meta_testfile(cls, filename=None, add_custom_columns=True, randomize_data=True): + """ + Create a small but relatively complex icephys test file that + we can use for testing of queries. + + :param filename: The name of the output file to be generated. If set to None then the file is not written + but only created in memory + :type filename: str, None + :param add_custom_colums: Add custom metadata columns to each table + :type add_custom_colums: bool + :param randomize_data: Randomize data values in the stimulus and response + :type randomize_data: bool + + :returns: ICEphysFile NWBFile object + :rtype: ICEphysFile + """ + nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + # Add a device + device = nwbfile.create_device(name='Heka ITC-1600') + # Add an intracellular electrode + electrode0 = nwbfile.create_icephys_electrode( + name="elec0", + description='a mock intracellular electrode', + device=device) + # Add an intracellular electrode + electrode1 = nwbfile.create_icephys_electrode( + name="elec1", + description='another mock intracellular electrode', + device=device) + # Add the intracelluar recordings + for sweep_number in range(20): + elec = (electrode0 if (sweep_number % 2 == 0) else electrode1) + stim, resp = cls.create_stimulus_and_response(sweep_number=np.uint64(sweep_number), + electrode=elec, + randomize_data=randomize_data) + nwbfile.add_intracellular_recording(electrode=elec, + stimulus=stim, + response=resp, + id=sweep_number) + nwbfile.intracellular_recordings.add_column(name='recording_tags', + data=['A1', 'A2', + 'B1', 'B2', + 'C1', 'C2', 'C3', + 'D1', 'D2', 'D3', + 'A1', 'A2', + 'B1', 'B2', + 'C1', 'C2', 'C3', + 'D1', 'D2', 'D3'], + description='String with a set of recording tags') + # Add simultaneous_recordings + nwbfile.add_icephys_simultaneous_recording(recordings=[0, 1], id=np.int64(100)) + nwbfile.add_icephys_simultaneous_recording(recordings=[2, 3], id=np.int64(101)) + nwbfile.add_icephys_simultaneous_recording(recordings=[4, 5, 6], id=np.int64(102)) + nwbfile.add_icephys_simultaneous_recording(recordings=[7, 8, 9], id=np.int64(103)) + nwbfile.add_icephys_simultaneous_recording(recordings=[10, 11], id=np.int64(104)) + nwbfile.add_icephys_simultaneous_recording(recordings=[12, 13], id=np.int64(105)) + nwbfile.add_icephys_simultaneous_recording(recordings=[14, 15, 16], id=np.int64(106)) + nwbfile.add_icephys_simultaneous_recording(recordings=[17, 18, 19], id=np.int64(107)) + if add_custom_columns: + nwbfile.icephys_simultaneous_recordings.add_column( + name='tag', + data=np.arange(8), + description='some integer tag for a sweep') + + # Add sequential recordings + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[0, 1], + id=np.int64(1000), + stimulus_type="StimType_1") + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[2, ], + id=np.int64(1001), + stimulus_type="StimType_2") + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[3, ], + id=np.int64(1002), + stimulus_type="StimType_3") + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[4, 5], + id=np.int64(1003), + stimulus_type="StimType_1") + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[6, ], + id=np.int64(1004), + stimulus_type="StimType_2") + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[7, ], + id=np.int64(1005), + stimulus_type="StimType_3") + if add_custom_columns: + nwbfile.icephys_sequential_recordings.add_column( + name='type', + data=['T1', 'T2', 'T3', 'T1', 'T2', 'T3'], + description='type of the sequential recording') + + # Add repetitions + nwbfile.add_icephys_repetition(sequential_recordings=[0, ], id=np.int64(10000)) + nwbfile.add_icephys_repetition(sequential_recordings=[1, 2], id=np.int64(10001)) + nwbfile.add_icephys_repetition(sequential_recordings=[3, ], id=np.int64(10002)) + nwbfile.add_icephys_repetition(sequential_recordings=[4, 5], id=np.int64(10003)) + if add_custom_columns: + nwbfile.icephys_repetitions.add_column( + name='type', + data=['R1', 'R2', 'R1', 'R2'], + description='some repetition type indicator') + + # Add experimental_conditions + nwbfile.add_icephys_experimental_condition(repetitions=[0, 1], id=np.int64(100000)) + nwbfile.add_icephys_experimental_condition(repetitions=[2, 3], id=np.int64(100001)) + if add_custom_columns: + nwbfile.icephys_experimental_conditions.add_column( + name='temperature', + data=[32., 24.], + description='Temperatur in C') + + # Write our test file + if filename is not None: + with NWBHDF5IO(filename, 'w') as io: + io.write(nwbfile) + + # Return our in-memory NWBFile + return nwbfile + + def setUp(self): + # Create an example nwbfile with a device, intracellular electrode, stimulus, and response + self.nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + self.device = self.nwbfile.create_device(name='Heka ITC-1600') + self.electrode = self.nwbfile.create_icephys_electrode(name="elec0", + description='a mock intracellular electrode', + device=self.device) + self.stimulus = VoltageClampStimulusSeries(name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=self.electrode, + gain=0.02, + sweep_number=np.uint64(15)) + self.nwbfile.add_stimulus(self.stimulus) + self.response = VoltageClampSeries(name='vcs', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=self.electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0, + sweep_number=np.uint64(15)) + self.nwbfile.add_acquisition(self.response) + self.path = 'test_icephys_meta_intracellularrecording.h5' + + def tearDown(self): + remove_test_file(self.path) + + @docval({'name': 'ir', + 'type': IntracellularRecordingsTable, + 'doc': 'Intracellular recording to be added to the file before write', + 'default': None}, + {'name': 'sw', + 'type': SimultaneousRecordingsTable, + 'doc': 'SimultaneousRecordingsTable table to be added to the file before write', + 'default': None}, + {'name': 'sws', + 'type': SequentialRecordingsTable, + 'doc': 'SequentialRecordingsTable table to be added to the file before write', + 'default': None}, + {'name': 'repetitions', + 'type': RepetitionsTable, + 'doc': 'RepetitionsTable table to be added to the file before write', + 'default': None}, + {'name': 'cond', + 'type': ExperimentalConditionsTable, + 'doc': 'ExperimentalConditionsTable table to be added to the file before write', + 'default': None}) + def write_test_helper(self, **kwargs): + """ + Internal helper function to roundtrip an ICEphys file with the given set of ICEphys tables + """ + ir, sw, sws, repetitions, cond = popargs('ir', 'sw', 'sws', 'repetitions', 'cond', kwargs) + + if ir is not None: + self.nwbfile.intracellular_recordings = ir + if sw is not None: + self.nwbfile.icephys_simultaneous_recordings = sw + if sws is not None: + self.nwbfile.icephys_sequential_recordings = sws + if repetitions is not None: + self.nwbfile.icephys_repetitions = repetitions + if cond is not None: + self.nwbfile.icephys_experimental_conditions = cond + + # Write our test file + with NWBHDF5IO(self.path, 'w') as io: + io.write(self.nwbfile) + + # Test that we can read the file + with NWBHDF5IO(self.path, 'r') as io: + infile = io.read() + if ir is not None: + in_ir = infile.intracellular_recordings + self.assertIsNotNone(in_ir) + to_dataframe_kwargs = dict(electrode_refs_as_objectids=True, + stimulus_refs_as_objectids=True, + response_refs_as_objectids=True) + assert_frame_equal(ir.to_dataframe(**to_dataframe_kwargs), in_ir.to_dataframe(**to_dataframe_kwargs)) + if sw is not None: + in_sw = infile.icephys_simultaneous_recordings + self.assertIsNotNone(in_sw) + self.assertListEqual(in_sw['recordings'].target.data[:].tolist(), sw['recordings'].target.data[:]) + self.assertEqual(in_sw['recordings'].target.table.object_id, sw['recordings'].target.table.object_id) + if sws is not None: + in_sws = infile.icephys_sequential_recordings + self.assertIsNotNone(in_sws) + self.assertListEqual(in_sws['simultaneous_recordings'].target.data[:].tolist(), + sws['simultaneous_recordings'].target.data[:]) + self.assertEqual(in_sws['simultaneous_recordings'].target.table.object_id, + sws['simultaneous_recordings'].target.table.object_id) + if repetitions is not None: + in_repetitions = infile.icephys_repetitions + self.assertIsNotNone(in_repetitions) + self.assertListEqual(in_repetitions['sequential_recordings'].target.data[:].tolist(), + repetitions['sequential_recordings'].target.data[:]) + self.assertEqual(in_repetitions['sequential_recordings'].target.table.object_id, + repetitions['sequential_recordings'].target.table.object_id) + if cond is not None: + in_cond = infile.icephys_experimental_conditions + self.assertIsNotNone(in_cond) + self.assertListEqual(in_cond['repetitions'].target.data[:].tolist(), + cond['repetitions'].target.data[:]) + self.assertEqual(in_cond['repetitions'].target.table.object_id, + cond['repetitions'].target.table.object_id) + + +class IntracellularElectrodesTableTests(TestCase): + """ + The IntracellularElectrodesTable is covered by the + IntracellularRecordingsTableTests as this table is part of that table. + """ + def setUp(self): + pass + + def tearDown(self): + pass + + +class IntracellularStimuliTableTests(TestCase): + """ + The IntracellularStimuliTable is covered by the + IntracellularRecordingsTableTests as this table is part of that table. + """ + def setUp(self): + pass + + def tearDown(self): + pass + + +class IntracellularResponsesTableTests(TestCase): + """ + The IntracellularResponsesTable is covered by the + IntracellularRecordingsTableTests as this table is part of that table. + """ + def setUp(self): + pass + + def tearDown(self): + pass + + +class IntracellularRecordingsTableTests(ICEphysMetaTestBase): + """ + Class for testing the IntracellularRecordingsTable Container + """ + + def test_init(self): + _ = IntracellularRecordingsTable() + self.assertTrue(True) + + def test_add_row(self): + # Add a row to our IR table + ir = IntracellularRecordingsTable() + + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + # test that we get the correct row index back + self.assertEqual(row_index, 0) + # read our first (and only) row and assert that it is correct + res = ir[0] + # Confirm that slicing one row give the same result as converting the whole table, which has only one row + assert_frame_equal(ir.to_dataframe(), res) + # Check the row id + self.assertEqual(res.index[0], 10) + # Check electrodes + self.assertIs(res[('electrodes', 'electrode')].iloc[0], self.electrode) + # Check the stimulus + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], (0, 5, self.stimulus)) + # Check the response + self.assertTupleEqual(res[('responses', 'response')].iloc[0], (0, 5, self.response)) + # test writing out ir table + self.write_test_helper(ir) + + def test_add_row_incompatible_types(self): + # Add a row that mixes CurrentClamp and VoltageClamp data + sweep_number = 15 + local_stimulus = CurrentClampStimulusSeries( + name="ccss_"+str(sweep_number), + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=self.electrode, + gain=0.1, + sweep_number=np.uint64(sweep_number)) + ir = IntracellularRecordingsTable() + with self.assertRaises(ValueError): + _ = ir.add_recording(electrode=self.electrode, + stimulus=local_stimulus, + response=self.response, + id=np.int64(10)) + + def test_warn_if_IZeroClampSeries_with_stimulus(self): + local_response = IZeroClampSeries( + name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=self.electrode, + gain=0.02, + sweep_number=np.uint64(100000)) + ir = IntracellularRecordingsTable() + with self.assertRaises(ValueError): + _ = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=local_response, + id=np.int64(10)) + + def test_inconsistent_PatchClampSeries(self): + local_electrode = self.nwbfile.create_icephys_electrode(name="elec1", + description='a mock intracellular electrode', + device=self.device) + local_stimulus = VoltageClampStimulusSeries(name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=local_electrode, + gain=0.02, + sweep_number=np.uint64(100000)) + ir = IntracellularRecordingsTable() + with self.assertRaises(ValueError): + _ = ir.add_recording(electrode=self.electrode, + stimulus=local_stimulus, + response=self.response, + id=np.int64(10)) + + def test_add_row_no_response(self): + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=None, + id=np.int64(10)) + res = ir[0] + # Check the ID + self.assertEqual(row_index, 0) + self.assertEqual(res.index[0], 10) + # Check the row id + self.assertEqual(res.index[0], 10) + # Check electrodes + self.assertIs(res[('electrodes', 'electrode')].iloc[0], self.electrode) + # Check the stimulus + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], (0, 5, self.stimulus)) + # Check the response + self.assertTupleEqual(res[('responses', 'response')].iloc[0], (-1, -1, self.stimulus)) + # test writing out ir table + self.write_test_helper(ir) + + def test_add_row_no_stimulus(self): + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=None, + response=self.response, + id=np.int64(10)) + res = ir[0] + # Check the ID + self.assertEqual(row_index, 0) + self.assertEqual(res.index[0], 10) + # Check the row id + self.assertEqual(res.index[0], 10) + # Check electrodes + self.assertIs(res[('electrodes', 'electrode')].iloc[0], self.electrode) + # Check the stimulus + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], (-1, -1, self.response)) + # Check the response + self.assertTupleEqual(res[('responses', 'response')].iloc[0], (0, 5, self.response)) + # test writing out ir table + self.write_test_helper(ir) + + def test_add_row_check_start_index_and_index_count_are_fixed(self): + # Make sure -1 values are converted + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_start_index=-1, # assert this is fixed to 0 + stimulus_index_count=-1, # assert this is fixed to len(stimulus) + response=None, + response_start_index=0, # assert this is fixed to -1 + response_index_count=10, # assert this is fixed to -1 + id=np.int64(10)) + res = ir[0] + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], + (0, len(self.stimulus.data), self.stimulus)) + self.assertTupleEqual(res[('responses', 'response')].iloc[0], + (-1, -1, self.stimulus)) + # Make sure single -1 values are converted + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_start_index=2, + id=np.int64(10)) + res = ir[0] + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], + (2, len(self.stimulus.data)-2, self.stimulus)) + # Make sure single -1 values are converted + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_index_count=2, + id=np.int64(10)) + res = ir[0] + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], + (0, 2, self.stimulus)) + + def test_add_row_index_out_of_range(self): + + # Stimulus/Response start_index to large + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_start_index=10, + response=self.response, + id=np.int64(10)) + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response_start_index=10, + response=self.response, + id=np.int64(10)) + # Stimulus/Reponse index count too large + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_index_count=10, + response=self.response, + id=np.int64(10)) + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response_index_count=10, + response=self.response, + id=np.int64(10)) + # Stimulus/Reponse start+count combination too large + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + stimulus_start_index=3, + stimulus_index_count=4, + response=self.response, + id=np.int64(10)) + with self.assertRaises(IndexError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response_start_index=3, + response_index_count=4, + response=self.response, + id=np.int64(10)) + + def test_add_row_no_stimulus_and_response(self): + with self.assertRaises(ValueError): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=None, + response=None) + + def test_add_column(self): + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + ir.add_column(name='test', description='test column', data=np.arange(1)) + self.assertTupleEqual(ir.colnames, ('test',)) + + def test_enforce_unique_id(self): + """ + Test to ensure that unique ids are enforced on RepetitionsTable table + """ + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + with self.assertRaises(ValueError): + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + + def test_basic_write(self): + """ + Populate, write, and read the SimultaneousRecordingsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + ir.add_column(name='test', description='test column', data=np.arange(1)) + self.write_test_helper(ir=ir) + + def test_round_trip_container_no_data(self): + """Test read and write the container by itself""" + curr = IntracellularRecordingsTable() + with NWBHDF5IO(self.path, 'w') as io: + io.write(curr) + with NWBHDF5IO(self.path, 'r') as io: + incon = io.read() + self.assertListEqual(incon.categories, curr.categories) + for n in curr.categories: + # empty columns from file have dtype int64 or float64 but empty in-memory columns have dtype object + assert_frame_equal(incon[n], curr[n], check_dtype=False, check_index_type=False) + + def test_write_with_stimulus_template(self): + """ + Populate, write, and read the SimultaneousRecordingsTable container and other required containers + """ + local_nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + # Add a device + local_device = local_nwbfile.create_device(name='Heka ITC-1600') + local_electrode = local_nwbfile.create_icephys_electrode( + name="elec0", + description='a mock intracellular electrode', + device=local_device) + local_stimulus = VoltageClampStimulusSeries(name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=local_electrode, + gain=0.02, + sweep_number=np.uint64(15)) + local_response = VoltageClampSeries(name='vcs', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=local_electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0, + sweep_number=np.uint64(15)) + local_nwbfile.add_stimulus_template(local_stimulus) + row_index = local_nwbfile.add_intracellular_recording(electrode=local_electrode, + stimulus=local_stimulus, + response=local_response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + # Write our test file + with NWBHDF5IO(self.path, 'w') as io: + io.write(local_nwbfile) + + +class SimultaneousRecordingsTableTests(ICEphysMetaTestBase): + """ + Test class for testing the SimultaneousRecordingsTable Container class + """ + + def test_init(self): + """ + Test __init__ to make sure we can instantiate the SimultaneousRecordingsTable container + """ + ir = IntracellularRecordingsTable() + _ = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + self.assertTrue(True) + + def test_missing_intracellular_recordings_on_init(self): + """ + Test that ValueError is raised when intracellular_recordings is missing. This is + allowed only on read where the intracellular_recordings table is already set + from the file. + """ + with self.assertRaises(ValueError): + _ = SimultaneousRecordingsTable() + + def test_add_simultaneous_recording(self): + """ + Populate, write, and read the SimultaneousRecordingsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + self.assertEqual(len(ir), 1) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + row_index = sw.add_simultaneous_recording(recordings=[row_index], id=100) + self.assertEqual(row_index, 0) + self.assertListEqual(sw.id[:], [100]) + self.assertListEqual(sw['recordings'].data, [1]) + self.assertListEqual(sw['recordings'].target.data[:], [0]) + + def test_basic_write(self): + """ + Populate, write, and read the SimultaneousRecordingsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + self.assertEqual(len(ir), 1) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + row_index = sw.add_simultaneous_recording(recordings=[row_index]) + self.assertEqual(row_index, 0) + self.write_test_helper(ir=ir, sw=sw) + + def test_enforce_unique_id(self): + """ + Test to ensure that unique ids are enforced on RepetitionsTable table + """ + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sw.add_simultaneous_recording(recordings=[0], id=np.int64(10)) + with self.assertRaises(ValueError): + sw.add_simultaneous_recording(recordings=[0], id=np.int64(10)) + + +class SequentialRecordingsTableTests(ICEphysMetaTestBase): + """ + Test class for testing the SequentialRecordingsTable Container class + """ + + def test_init(self): + """ + Test __init__ to make sure we can instantiate the SequentialRecordingsTable container + """ + ir = IntracellularRecordingsTable() + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + _ = SequentialRecordingsTable(simultaneous_recordings_table=sw) + self.assertTrue(True) + + def test_missing_simultaneous_recordings_on_init(self): + """ + Test that ValueError is raised when simultaneous_recordings is missing. This is + allowed only on read where the simultaneous_recordings table is already set + from the file. + """ + with self.assertRaises(ValueError): + _ = SequentialRecordingsTable() + + def test_basic_write(self): + """ + Populate, write, and read the SequentialRecordingsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + row_index = sw.add_simultaneous_recording(recordings=[0]) + self.assertEqual(row_index, 0) + sws = SequentialRecordingsTable(sw) + row_index = sws.add_sequential_recording(simultaneous_recordings=[0, ], stimulus_type='MyStimStype') + self.assertEqual(row_index, 0) + self.write_test_helper(ir=ir, sw=sw, sws=sws) + + def test_enforce_unique_id(self): + """ + Test to ensure that unique ids are enforced on RepetitionsTable table + """ + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sw.add_simultaneous_recording(recordings=[0]) + sws = SequentialRecordingsTable(sw) + sws.add_sequential_recording(simultaneous_recordings=[0, ], id=np.int64(10), stimulus_type='MyStimStype') + with self.assertRaises(ValueError): + sws.add_sequential_recording(simultaneous_recordings=[0, ], id=np.int64(10), stimulus_type='MyStimStype') + + +class RepetitionsTableTests(ICEphysMetaTestBase): + """ + Test class for testing the RepetitionsTable Container class + """ + + def test_init(self): + """ + Test __init__ to make sure we can instantiate the RepetitionsTable container + """ + ir = IntracellularRecordingsTable() + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sws = SequentialRecordingsTable(simultaneous_recordings_table=sw) + _ = RepetitionsTable(sequential_recordings_table=sws) + self.assertTrue(True) + + def test_missing_sequential_recordings_on_init(self): + """ + Test that ValueError is raised when sequential_recordings is missing. This is + allowed only on read where the sequential_recordings table is already set + from the file. + """ + with self.assertRaises(ValueError): + _ = RepetitionsTable() + + def test_basic_write(self): + """ + Populate, write, and read the RepetitionsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + row_index = sw.add_simultaneous_recording(recordings=[0]) + self.assertEqual(row_index, 0) + sws = SequentialRecordingsTable(sw) + row_index = sws.add_sequential_recording(simultaneous_recordings=[0, ], stimulus_type='MyStimStype') + self.assertEqual(row_index, 0) + repetitions = RepetitionsTable(sequential_recordings_table=sws) + repetitions.add_repetition(sequential_recordings=[0, ]) + self.write_test_helper(ir=ir, sw=sw, sws=sws, repetitions=repetitions) + + def test_enforce_unique_id(self): + """ + Test to ensure that unique ids are enforced on RepetitionsTable table + """ + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sw.add_simultaneous_recording(recordings=[0]) + sws = SequentialRecordingsTable(sw) + sws.add_sequential_recording(simultaneous_recordings=[0, ], stimulus_type='MyStimStype') + repetitions = RepetitionsTable(sequential_recordings_table=sws) + repetitions.add_repetition(sequential_recordings=[0, ], id=np.int64(10)) + with self.assertRaises(ValueError): + repetitions.add_repetition(sequential_recordings=[0, ], id=np.int64(10)) + + +class ExperimentalConditionsTableTests(ICEphysMetaTestBase): + """ + Test class for testing the ExperimentalConditionsTable Container class + """ + + def test_init(self): + """ + Test __init__ to make sure we can instantiate the ExperimentalConditionsTable container + """ + ir = IntracellularRecordingsTable() + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sws = SequentialRecordingsTable(simultaneous_recordings_table=sw) + repetitions = RepetitionsTable(sequential_recordings_table=sws) + _ = ExperimentalConditionsTable(repetitions_table=repetitions) + self.assertTrue(True) + + def test_missing_repetitions_on_init(self): + """ + Test that ValueError is raised when repetitions is missing. This is + allowed only on read where the repetitions table is already set + from the file. + """ + with self.assertRaises(ValueError): + _ = ExperimentalConditionsTable() + + def test_basic_write(self): + """ + Populate, write, and read the ExperimentalConditionsTable container and other required containers + """ + ir = IntracellularRecordingsTable() + row_index = ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + self.assertEqual(row_index, 0) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + row_index = sw.add_simultaneous_recording(recordings=[0]) + self.assertEqual(row_index, 0) + sws = SequentialRecordingsTable(sw) + row_index = sws.add_sequential_recording(simultaneous_recordings=[0, ], stimulus_type='MyStimStype') + self.assertEqual(row_index, 0) + repetitions = RepetitionsTable(sequential_recordings_table=sws) + row_index = repetitions.add_repetition(sequential_recordings=[0, ]) + self.assertEqual(row_index, 0) + cond = ExperimentalConditionsTable(repetitions_table=repetitions) + row_index = cond.add_experimental_condition(repetitions=[0, ]) + self.assertEqual(row_index, 0) + self.write_test_helper(ir=ir, sw=sw, sws=sws, repetitions=repetitions, cond=cond) + + def test_enforce_unique_id(self): + """ + Test to ensure that unique ids are enforced on RepetitionsTable table + """ + ir = IntracellularRecordingsTable() + ir.add_recording(electrode=self.electrode, + stimulus=self.stimulus, + response=self.response, + id=np.int64(10)) + sw = SimultaneousRecordingsTable(intracellular_recordings_table=ir) + sw.add_simultaneous_recording(recordings=[0]) + sws = SequentialRecordingsTable(sw) + sws.add_sequential_recording(simultaneous_recordings=[0, ], stimulus_type='MyStimStype') + repetitions = RepetitionsTable(sequential_recordings_table=sws) + repetitions.add_repetition(sequential_recordings=[0, ]) + cond = ExperimentalConditionsTable(repetitions_table=repetitions) + cond.add_experimental_condition(repetitions=[0, ], id=np.int64(10)) + with self.assertRaises(ValueError): + cond.add_experimental_condition(repetitions=[0, ], id=np.int64(10)) + + +# TODO: Move these tests from ICEPhys to NWBFile proper +class NWBFileTests(TestCase): + """ + Test class for testing the NWBFileTests Container class + """ + def setUp(self): + warnings.simplefilter("always") # Trigger all warnings + self.path = 'test_icephys_meta_intracellularrecording.h5' + + def tearDown(self): + remove_test_file(self.path) + + def __get_icephysfile(self): + """ + Create a dummy NWBFile instance + """ + icefile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + return icefile + + def __add_device(self, icefile): + return icefile.create_device(name='Heka ITC-1600') + + def __add_electrode(self, icefile, device): + return icefile.create_icephys_electrode(name="elec0", + description='a mock intracellular electrode', + device=device) + + def __get_stimuls(self, electrode): + """ + Create a dummy VoltageClampStimulusSeries + """ + return VoltageClampStimulusSeries( + name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=electrode, + gain=0.02, + sweep_number=np.uint64(15)) + + def __get_response(self, electrode): + """ + Create a dummy VoltageClampSeries + """ + return VoltageClampSeries( + name='vcs', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0, + sweep_number=np.uint64(15)) + + def test_init(self): + """ + Test __init__ to make sure we can instantiate the NWBFileTests container + """ + _ = self.__get_icephysfile() + + def test_deprecate_simultaneous_recordings_on_add_stimulus(self): + """ + Test that warnings are raised if the user tries to use a simultaneous_recordings table + """ + nwbfile = self.__get_icephysfile() + device = self.__add_device(nwbfile) + electrode = self.__add_electrode(nwbfile, device) + stimulus = self.__get_stimuls(electrode=electrode) + responce = self.__get_response(electrode=electrode) + # Make sure we warn if sweeptable is added on add_stimulus + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") # Trigger all warnings + nwbfile.add_stimulus(stimulus, use_sweep_table=True) + self.assertEqual(len(w), 1) + assert issubclass(w[-1].category, DeprecationWarning) + # make sure we don't trigger the same deprecation warning twice + nwbfile.add_acquisition(responce, use_sweep_table=True) + self.assertEqual(len(w), 1) + + def test_deprecate_sweeptable_on_add_stimulus_template(self): + """ + Make sure we warn when using the sweep-table + """ + nwbfile = self.__get_icephysfile() + local_electrode = nwbfile.create_icephys_electrode( + name="elec0", + description='a mock intracellular electrode', + device=nwbfile.create_device(name='Heka ITC-1600')) + local_stimulus = VoltageClampStimulusSeries( + name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=local_electrode, + gain=0.02, + sweep_number=np.uint64(15)) + local_stimulus2 = VoltageClampStimulusSeries( + name="ccss2", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=local_electrode, + gain=0.02, + sweep_number=np.uint64(15)) + with warnings.catch_warnings(record=True) as w: + nwbfile.add_stimulus_template(local_stimulus, use_sweep_table=True) + self.assertEqual(len(w), 1) + assert issubclass(w[-1].category, DeprecationWarning) + self.assertEqual(str(w[-1].message), + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable " + "instead. See also the NWBFile.add_intracellular_recordings function.") + # make sure we don't trigger the same deprecation warning twice + nwbfile.add_stimulus_template(local_stimulus2, use_sweep_table=True) + self.assertEqual(len(w), 1) + + def test_deprecate_sweepstable_on_add_acquistion(self): + """ + Test that warnings are raised if the user tries to use a sweeps table + """ + nwbfile = self.__get_icephysfile() + device = self.__add_device(nwbfile) + electrode = self.__add_electrode(nwbfile, device) + stimulus = self.__get_stimuls(electrode=electrode) + responce = self.__get_response(electrode=electrode) + # Make sure we warn if sweeptable is added on add_stimulus + with warnings.catch_warnings(record=True) as w: + nwbfile.add_acquisition(responce, use_sweep_table=True) + self.assertEqual(len(w), 1) + assert issubclass(w[-1].category, DeprecationWarning) + self.assertEqual(str(w[-1].message), + "Use of SweepTable is deprecated. Use the IntracellularRecordingsTable " + "instead. See also the NWBFile.add_intracellular_recordings function.") + # make sure we don't trigger the same deprecation warning twice + nwbfile.add_stimulus(stimulus, use_sweep_table=True) + self.assertEqual(len(w), 1) + + def test_deprecate_sweepstable_on_init(self): + """ + Test that warnings are raised if the user tries to use a sweeps table + """ + from pynwb.icephys import SweepTable + with warnings.catch_warnings(record=True) as w: + nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN', + sweep_table=SweepTable()) + device = self.__add_device(nwbfile) + electrode = self.__add_electrode(nwbfile, device) + stimulus = self.__get_stimuls(electrode=electrode) + self.assertEqual(len(w), 1) + assert issubclass(w[-1].category, DeprecationWarning) + # make sure we don't trigger the same deprecation warning twice + nwbfile.add_stimulus(stimulus, use_sweep_table=True) + self.assertEqual(len(w), 1) + + def test_deprectation_icephys_filtering_on_init(self): + with warnings.catch_warnings(record=True) as w: + nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN', + icephys_filtering='test filtering') + assert issubclass(w[-1].category, DeprecationWarning) + self.assertEqual(nwbfile.icephys_filtering, 'test filtering') + + def test_icephys_filtering_roundtrip(self): + # create the base file + nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + # set the icephys_filtering attribute and make sure we get a deprectation warning + with warnings.catch_warnings(record=True) as w: + nwbfile.icephys_filtering = 'test filtering' + assert issubclass(w[-1].category, DeprecationWarning) + # write the test fil + with NWBHDF5IO(self.path, 'w') as io: + io.write(nwbfile) + # read the test file and confirm icephys_filtering has been written + with NWBHDF5IO(self.path, 'r') as io: + with warnings.catch_warnings(record=True) as w: + infile = io.read() + self.assertEqual(len(w), 1) # make sure a warning is being raised + assert issubclass(w[0].category, DeprecationWarning) # make sure it is a deprecation warning + self.assertEqual(infile.icephys_filtering, 'test filtering') # make sure the value is set + + def test_get_icephys_meta_parent_table(self): + """ + Create the table hierarchy step-by-step and check that as we add tables the get_icephys_meta_parent_table + returns the expected top table + """ + local_nwbfile = NWBFile( + session_description='my first synthetic recording', + identifier='EXAMPLE_ID', + session_start_time=datetime.now(tzlocal()), + experimenter='Dr. Bilbo Baggins', + lab='Bag End Laboratory', + institution='University of Middle Earth at the Shire', + experiment_description='I went on an adventure with thirteen dwarves to reclaim vast treasures.', + session_id='LONELYMTN') + # Add a device + local_device = local_nwbfile.create_device(name='Heka ITC-1600') + local_electrode = local_nwbfile.create_icephys_electrode( + name="elec0", + description='a mock intracellular electrode', + device=local_device) + local_stimulus = VoltageClampStimulusSeries(name="ccss", + data=[1, 2, 3, 4, 5], + starting_time=123.6, + rate=10e3, + electrode=local_electrode, + gain=0.02, + sweep_number=np.uint64(15)) + local_response = VoltageClampSeries(name='vcs', + data=[0.1, 0.2, 0.3, 0.4, 0.5], + conversion=1e-12, + resolution=np.nan, + starting_time=123.6, + rate=20e3, + electrode=local_electrode, + gain=0.02, + capacitance_slow=100e-12, + resistance_comp_correction=70.0, + sweep_number=np.uint64(15)) + local_nwbfile.add_stimulus_template(local_stimulus) + # Check that none of the table exist yet + self.assertIsNone(local_nwbfile.get_icephys_meta_parent_table()) + # Add a recording and confirm that intracellular_recordings is the top table + _ = local_nwbfile.add_intracellular_recording(electrode=local_electrode, + stimulus=local_stimulus, + response=local_response, + id=np.int64(10)) + self.assertIsInstance(local_nwbfile.get_icephys_meta_parent_table(), + IntracellularRecordingsTable) + # Add a sweep and check that the simultaneous_recordings table is the top table + _ = local_nwbfile.add_icephys_simultaneous_recording(recordings=[0]) + self.assertIsInstance(local_nwbfile.get_icephys_meta_parent_table(), + SimultaneousRecordingsTable) + # Add a sweep_sequence and check that it is now our top table + _ = local_nwbfile.add_icephys_sequential_recording(simultaneous_recordings=[0], stimulus_type="MyStimulusType") + self.assertIsInstance(local_nwbfile.get_icephys_meta_parent_table(), + SequentialRecordingsTable) + # Add a repetition and check that it is now our top table + _ = local_nwbfile.add_icephys_repetition(sequential_recordings=[0]) + self.assertIsInstance(local_nwbfile.get_icephys_meta_parent_table(), + RepetitionsTable) + # Add a condition and check that it is now our top table + _ = local_nwbfile.add_icephys_experimental_condition(repetitions=[0]) + self.assertIsInstance(local_nwbfile.get_icephys_meta_parent_table(), + ExperimentalConditionsTable) + + def test_add_icephys_meta_full_roundtrip(self): + """ + This test adds all data and then constructs step-by-step the full table structure + Returns: + + """ + #################################### + # Create our file and timeseries + ################################### + nwbfile = self.__get_icephysfile() + device = self.__add_device(nwbfile) + electrode = self.__add_electrode(nwbfile, device) + # Add the data using standard methods from NWBFile + stimulus = self.__get_stimuls(electrode=electrode) + nwbfile.add_stimulus(stimulus) + # Check that the deprecated sweep table has indeed not been created + self.assertIsNone(nwbfile.sweep_table) + response = self.__get_response(electrode=electrode) + nwbfile.add_acquisition(response) + # Check that the deprecated sweep table has indeed not been created + self.assertIsNone(nwbfile.sweep_table) + + ############################################# + # Test adding IntracellularRecordingsTable + ############################################# + # Check that our IntracellularRecordingsTable table does not yet exists + self.assertIsNone(nwbfile.intracellular_recordings) + # Add an intracellular recording + intracellular_recording_ids = [np.int64(10), np.int64(11)] + nwbfile.add_intracellular_recording(electrode=electrode, + stimulus=stimulus, + response=response, + id=intracellular_recording_ids[0]) + nwbfile.add_intracellular_recording(electrode=electrode, + stimulus=stimulus, + response=response, + id=intracellular_recording_ids[1]) + # Check that the table has been created + self.assertIsNotNone(nwbfile.intracellular_recordings) + # Check that the values in our row are correct + self.assertEqual(len(nwbfile.intracellular_recordings), 2) + res = nwbfile.intracellular_recordings[0] + # Check the ID + self.assertEqual(res.index[0], intracellular_recording_ids[0]) + # Check electrodes + self.assertIs(res[('electrodes', 'electrode')].iloc[0], electrode) + # Check the stimulus + self.assertTupleEqual(res[('stimuli', 'stimulus')].iloc[0], (0, 5, stimulus)) + # Check the response + self.assertTupleEqual(res[('responses', 'response')].iloc[0], (0, 5, response)) + + ############################################# + # Test adding SimultaneousRecordingsTable + ############################################# + # Confirm that our SimultaneousRecordingsTable table does not yet exist + self.assertIsNone(nwbfile.icephys_simultaneous_recordings) + # Add a sweep + simultaneous_recordings_id = np.int64(12) + recordings_indices = [0, 1] + nwbfile.add_icephys_simultaneous_recording(recordings=recordings_indices, id=simultaneous_recordings_id) + # Check that the SimultaneousRecordingsTable table has been added + self.assertIsNotNone(nwbfile.icephys_simultaneous_recordings) + # Check that the values for our icephys_simultaneous_recordings table are correct + self.assertListEqual(nwbfile.icephys_simultaneous_recordings.id[:], [simultaneous_recordings_id]) + self.assertListEqual(nwbfile.icephys_simultaneous_recordings['recordings'].data, [2]) + self.assertListEqual(nwbfile.icephys_simultaneous_recordings['recordings'].target.data[:], [0, 1]) + res = nwbfile.icephys_simultaneous_recordings[0] + # check the id value + self.assertEqual(res.index[0], simultaneous_recordings_id) + # Check that our simultaneous recording contains 2 IntracellularRecording + assert_array_equal(res.loc[simultaneous_recordings_id]['recordings'], + recordings_indices) + + ############################################# + # Test adding a SweepSequence + ############################################# + # Confirm that our SequentialRecordingsTable table does not yet exist + self.assertIsNone(nwbfile.icephys_sequential_recordings) + # Add a sweep + sequential_recording_id = np.int64(15) + simultaneous_recordings_indices = [0] + nwbfile.add_icephys_sequential_recording(simultaneous_recordings=simultaneous_recordings_indices, + id=sequential_recording_id, + stimulus_type="MyStimulusType") + # Check that the SimultaneousRecordingsTable table has been added + self.assertIsNotNone(nwbfile.icephys_sequential_recordings) + # Check that the values for our SimultaneousRecordingsTable table are correct + res = nwbfile.icephys_sequential_recordings[0] + # check the id value + self.assertEqual(res.index[0], sequential_recording_id) + # Check that our sequential recording containts 1 simultaneous recording + assert_array_equal(res.loc[sequential_recording_id]['simultaneous_recordings'], + simultaneous_recordings_indices) + + ############################################# + # Test adding a Run + ############################################# + # Confirm that our RepetitionsTable table does not yet exist + self.assertIsNone(nwbfile.icephys_repetitions) + # Add a repetition + sequential_recordings_indices = [0] + repetition_id = np.int64(17) + nwbfile.add_icephys_repetition(sequential_recordings=sequential_recordings_indices, id=repetition_id) + # Check that the SimultaneousRecordingsTable table has been added + self.assertIsNotNone(nwbfile.icephys_repetitions) + # Check that the values for our RepetitionsTable table are correct + res = nwbfile.icephys_repetitions[0] + # check the id value + self.assertEqual(res.index[0], repetition_id) + # Check that our repetition contains 1 SweepSequence + assert_array_equal(res.loc[repetition_id]['sequential_recordings'], + sequential_recordings_indices) + + ############################################# + # Test adding a Condition + ############################################# + # Confirm that our RepetitionsTable table does not yet exist + self.assertIsNone(nwbfile.icephys_experimental_conditions) + # Add a condition + repetitions_indices = [0] + experiment_id = np.int64(19) + nwbfile.add_icephys_experimental_condition(repetitions=repetitions_indices, id=experiment_id) + # Check that the ExperimentalConditionsTable table has been added + self.assertIsNotNone(nwbfile.icephys_experimental_conditions) + # Check that the values for our ExperimentalConditionsTable table are correct + res = nwbfile.icephys_experimental_conditions[0] + # check the id value + self.assertEqual(res.index[0], experiment_id) + # Check that our repetition contains 1 repetition + assert_array_equal(res.loc[experiment_id]['repetitions'], + repetitions_indices) + + ############################################# + # Test writing the file to disk + ############################################# + # Write our file to disk + # Write our test file + with NWBHDF5IO(self.path, 'w') as nwbio: + # # Uncomment the following lines to enable profiling for write + # import cProfile, pstats, io + # from pstats import SortKey + # pr = cProfile.Profile() + # pr.enable() + nwbio.write(nwbfile) + # pr.disable() + # s = io.StringIO() + # sortby = SortKey.CUMULATIVE + # ps = pstats.Stats(pr, stream=s).sort_stats(sortby) + # ps.print_stats() + # print(s.getvalue()) + + ################################################################# + # Confirm that the low-level data has been written as expected + # using h5py to confirm all id values. We do this before we try + # to read the file back to confirm that data is correct on disk. + ################################################################# + with h5py.File(self.path, 'r') as io: + assert_array_equal(io['/general']['intracellular_ephys']['intracellular_recordings']['id'][:], + intracellular_recording_ids) + default_ids = [0, 1] + assert_array_equal(io['/general']['intracellular_ephys']['intracellular_recordings']['electrodes']['id'][:], + default_ids) + assert_array_equal(io['/general']['intracellular_ephys']['intracellular_recordings']['stimuli']['id'][:], + default_ids) + assert_array_equal(io['/general']['intracellular_ephys']['intracellular_recordings']['responses']['id'][:], + default_ids) + assert_array_equal(io['/general']['intracellular_ephys']['simultaneous_recordings']['id'][:], + [simultaneous_recordings_id, ]) + assert_array_equal(io['/general']['intracellular_ephys']['sequential_recordings']['id'][:], + [sequential_recording_id, ]) + assert_array_equal(io['/general']['intracellular_ephys']['repetitions']['id'][:], + [repetition_id, ]) + assert_array_equal(io['/general']['intracellular_ephys']['experimental_conditions']['id'][:], + [experiment_id, ]) + + ############################################# + # Test reading the file back from disk + ############################################# + with NWBHDF5IO(self.path, 'r') as nwbio: + # # Uncomment the following lines to enable profiling for read + # import cProfile, pstats, io + # from pstats import SortKey + # pr = cProfile.Profile() + # pr.enable() + infile = nwbio.read() + # pr.disable() + # s = io.StringIO() + # sortby = SortKey.CUMULATIVE + # ps = pstats.Stats(pr, stream=s).sort_stats(sortby) + # ps.print_stats() + # print(s.getvalue()) + + ############################################################################ + # Test that the IntracellularRecordingsTable table has been written correctly + ############################################################################ + self.assertIsNotNone(infile.intracellular_recordings) + self.assertEqual(len(infile.intracellular_recordings), 2) + res = infile.intracellular_recordings[0] + # Check the ID + self.assertEqual(res.index[0], 10) + # Check the stimulus + self.assertEqual(res[('stimuli', 'stimulus')].iloc[0][0], 0) + self.assertEqual(res[('stimuli', 'stimulus')].iloc[0][1], 5) + self.assertEqual(res[('stimuli', 'stimulus')].iloc[0][2].object_id, stimulus.object_id) + # Check the response + self.assertEqual(res[('responses', 'response')].iloc[0][0], 0) + self.assertEqual(res[('responses', 'response')].iloc[0][1], 5) + self.assertEqual(res[('responses', 'response')].iloc[0][2].object_id, + nwbfile.get_acquisition('vcs').object_id) + # Check the Intracellular electrode + self.assertEqual(res[('electrodes', 'electrode')].iloc[0].object_id, electrode.object_id) + + ############################################################################ + # Test that the SimultaneousRecordingsTable table has been written correctly + ############################################################################ + self.assertIsNotNone(infile.icephys_simultaneous_recordings) + self.assertEqual(len(infile.icephys_simultaneous_recordings), 1) + res = infile.icephys_simultaneous_recordings[0] + # Check the ID and len of the intracellular_recordings column + self.assertEqual(res.index[0], simultaneous_recordings_id) + assert_array_equal(res.loc[simultaneous_recordings_id]['recordings'], recordings_indices) + + ############################################################################ + # Test that the SequentialRecordingsTable table has been written correctly + ############################################################################ + self.assertIsNotNone(infile.icephys_sequential_recordings) + self.assertEqual(len(infile.icephys_sequential_recordings), 1) + res = infile.icephys_sequential_recordings[0] + # Check the ID and len of the simultaneous_recordings column + self.assertEqual(res.index[0], sequential_recording_id) + assert_array_equal(res.loc[sequential_recording_id]['simultaneous_recordings'], + simultaneous_recordings_indices) + + ############################################################################ + # Test that the RepetitionsTable table has been written correctly + ############################################################################ + self.assertIsNotNone(infile.icephys_repetitions) + self.assertEqual(len(infile.icephys_repetitions), 1) + res = infile.icephys_repetitions[0] + # Check the ID and len of the simultaneous_recordings column + self.assertEqual(res.index[0], repetition_id) + assert_array_equal(res.loc[repetition_id]['sequential_recordings'], sequential_recordings_indices) + + ############################################################################ + # Test that the ExperimentalConditionsTable table has been written correctly + ############################################################################ + self.assertIsNotNone(infile.icephys_experimental_conditions) + self.assertEqual(len(infile.icephys_experimental_conditions), 1) + res = infile.icephys_experimental_conditions[0] + # Check the ID and len of the simultaneous_recordings column + self.assertEqual(res.index[0], experiment_id) + assert_array_equal(res.loc[experiment_id]['repetitions'], repetitions_indices) diff --git a/tests/unit/test_image.py b/tests/unit/test_image.py index 063cbea9e..c79a7b0d5 100644 --- a/tests/unit/test_image.py +++ b/tests/unit/test_image.py @@ -1,21 +1,31 @@ import numpy as np from pynwb import TimeSeries -from pynwb.image import ImageSeries, IndexSeries, ImageMaskSeries, OpticalSeries, \ - GrayscaleImage, RGBImage, RGBAImage +from pynwb.device import Device +from pynwb.image import ImageSeries, IndexSeries, ImageMaskSeries, OpticalSeries, GrayscaleImage, RGBImage, RGBAImage from pynwb.testing import TestCase class ImageSeriesConstructor(TestCase): def test_init(self): - iS = ImageSeries(name='test_iS', data=np.ones((3, 3, 3)), unit='unit', - external_file=['external_file'], starting_frame=[1, 2, 3], format='tiff', timestamps=list()) + dev = Device('test_device') + iS = ImageSeries( + name='test_iS', + data=np.ones((3, 3, 3)), + unit='unit', + external_file=['external_file'], + starting_frame=[1, 2, 3], + format='tiff', + timestamps=list(), + device=dev, + ) self.assertEqual(iS.name, 'test_iS') self.assertEqual(iS.unit, 'unit') self.assertEqual(iS.external_file, ['external_file']) self.assertEqual(iS.starting_frame, [1, 2, 3]) self.assertEqual(iS.format, 'tiff') + self.assertIs(iS.device, dev) # self.assertEqual(iS.bits_per_pixel, np.nan) def test_no_data_no_file(self): diff --git a/tests/unit/test_misc.py b/tests/unit/test_misc.py index 3417af97e..4412063ce 100644 --- a/tests/unit/test_misc.py +++ b/tests/unit/test_misc.py @@ -1,9 +1,9 @@ import numpy as np -from hdmf.common import DynamicTable, VectorData +from hdmf.common import DynamicTable, VectorData, DynamicTableRegion from pynwb.misc import AnnotationSeries, AbstractFeatureSeries, IntervalSeries, Units, DecompositionSeries -from pynwb.file import TimeSeries +from pynwb.file import TimeSeries, ElectrodeTable as get_electrode_table from pynwb.device import Device from pynwb.ecephys import ElectrodeGroup from pynwb.testing import TestCase @@ -74,6 +74,35 @@ def test_init_delayed_bands(self): self.assertEqual(spec_anal.source_timeseries, timeseries) self.assertEqual(spec_anal.metric, 'amplitude') + @staticmethod + def make_electrode_table(self): + """ Make an electrode table, electrode group, and device """ + self.table = get_electrode_table() + self.dev1 = Device(name='dev1') + self.group = ElectrodeGroup(name='tetrode1', + description='tetrode description', + location='tetrode location', + device=self.dev1) + for i in range(4): + self.table.add_row(x=i, y=2.0, z=3.0, imp=-1.0, location='CA1', filtering='none', group=self.group, + group_name='tetrode1') + + def test_init_with_source_channels(self): + self.make_electrode_table(self) + region = DynamicTableRegion(name='source_channels', + data=[0, 2], + description='the first and third electrodes', + table=self.table) + data = np.random.randn(100, 2, 30) + timestamps = np.arange(100)/100 + ds = DecompositionSeries(name='test_DS', + data=data, + source_channels=region, + timestamps=timestamps, + metric='amplitude') + + self.assertIs(ds.source_channels, region) + class IntervalSeriesConstructor(TestCase): def test_init(self): diff --git a/tests/unit/test_ophys.py b/tests/unit/test_ophys.py index 2757a854e..024c081cb 100644 --- a/tests/unit/test_ophys.py +++ b/tests/unit/test_ophys.py @@ -200,13 +200,47 @@ def test_init(self): class MotionCorrectionConstructor(TestCase): def test_init(self): - MotionCorrection(list()) + corrected = ImageSeries( + name='corrected', + data=np.ones((1000, 100, 100)), + unit='na', + format='raw', + starting_time=0.0, + rate=1.0 + ) + + xy_translation = TimeSeries( + name='xy_translation', + data=np.ones((1000, 2)), + unit='pixels', + starting_time=0.0, + rate=1.0, + ) + + ip = create_imaging_plane() + + image_series = TwoPhotonSeries( + name='TwoPhotonSeries1', + data=np.ones((1000, 100, 100)), + imaging_plane=ip, + rate=1.0, + unit='normalized amplitude' + ) + + corrected_image_stack = CorrectedImageStack( + corrected=corrected, + original=image_series, + xy_translation=xy_translation, + ) + + motion_correction = MotionCorrection(corrected_image_stacks=[corrected_image_stack]) + self.assertEqual(motion_correction.corrected_image_stacks['CorrectedImageStack'], corrected_image_stack) class CorrectedImageStackConstructor(TestCase): def test_init(self): is1 = ImageSeries( - name='is1', + name='corrected', data=np.ones((2, 2, 2)), unit='unit', external_file=['external_file'], @@ -216,16 +250,15 @@ def test_init(self): ) is2 = ImageSeries( name='is2', - data=np.ones((2, 2, 2)), unit='unit', external_file=['external_file'], starting_frame=[1, 2, 3], format='tiff', timestamps=[1., 2.] ) - tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float) + tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float64) ts = TimeSeries( - name="test_ts", + name='xy_translation', data=list(range(len(tstamps))), unit='unit', timestamps=tstamps diff --git a/tests/validation/test_validate.py b/tests/validation/test_validate.py index cf946aa0d..d491fff47 100644 --- a/tests/validation/test_validate.py +++ b/tests/validation/test_validate.py @@ -39,7 +39,8 @@ def test_validate_file_no_cache_bad_ns(self): r"warnings.warn\(msg\)\s*" r"The file tests/back_compat/1\.0\.2_nwbfile\.nwb has no cached namespace information\. " r"Falling back to pynwb namespace information\.\s*" - r"The namespace 'notfound' could not be found in pynwb namespace information\.\s*" + r"The namespace 'notfound' could not be found in pynwb namespace information as only " + r"\['core'\] is present\.\s*" ) self.assertRegex(result.stderr.decode('utf-8'), stderr_regex) @@ -63,7 +64,8 @@ def test_validate_file_cached_bad_ns(self): capture_output=True) stderr_regex = re.compile( - r"The namespace 'notfound' could not be found in cached namespace information\.\s*" + r"The namespace 'notfound' could not be found in cached namespace information as only " + r"\['core'\] is present\.\s*" ) self.assertRegex(result.stderr.decode('utf-8'), stderr_regex) @@ -75,17 +77,11 @@ def test_validate_file_cached_hdmf_common(self): capture_output=True) stderr_regex = re.compile( - r".*ValueError: data type \'NWBFile\' not found in namespace hdmf-common.\s*", - re.DOTALL + r"The namespace 'hdmf-common' is included by the namespace 'core'\. Please validate against that " + r"namespace instead\.\s*", ) self.assertRegex(result.stderr.decode('utf-8'), stderr_regex) - stdout_regex = re.compile( - r"Validating tests/back_compat/1.1.2_nwbfile.nwb against cached namespace information using namespace " - r"'hdmf-common'.\s*" - ) - self.assertRegex(result.stdout.decode('utf-8'), stdout_regex) - def test_validate_file_cached_ignore(self): """Test that validating a file with cached spec against the core namespace succeeds.""" result = subprocess.run("python -m pynwb.validate tests/back_compat/1.1.2_nwbfile.nwb --no-cached-namespace", diff --git a/tox.ini b/tox.ini index 5c76ec964..81ed4fcd2 100644 --- a/tox.ini +++ b/tox.ini @@ -4,7 +4,7 @@ # and then run "tox" from this directory. [tox] -envlist = py36, py37, py38, py39 +envlist = py37, py38, py39 [testenv] usedevelop = True @@ -22,32 +22,32 @@ commands = # Env to create coverage report locally [testenv:localcoverage] -basepython = python3.8 +basepython = python3.9 commands = python -m coverage run test.py --pynwb coverage html -d tests/coverage/htmlcov -# Test with python 3.8, pinned dev reqs, and upgraded run requirements -[testenv:py38-upgrade-dev] -basepython = python3.8 +# Test with python 3.9, pinned dev reqs, and upgraded run requirements +[testenv:py39-upgrade-dev] +basepython = python3.9 install_command = pip install -U -e . {opts} {packages} deps = -rrequirements-dev.txt commands = {[testenv]commands} -# Test with python 3.8, pinned dev reqs, and pre-release run requirements -[testenv:py38-upgrade-dev-pre] -basepython = python3.8 +# Test with python 3.9, pinned dev reqs, and pre-release run requirements +[testenv:py39-upgrade-dev-pre] +basepython = python3.9 install_command = pip install -U --pre -e . {opts} {packages} deps = -rrequirements-dev.txt commands = {[testenv]commands} -# Test with python 3.6, pinned dev reqs, and minimum run requirements -[testenv:py36-min-req] -basepython = python3.6 +# Test with python 3.7, pinned dev reqs, and minimum run requirements +[testenv:py37-min-req] +basepython = python3.7 deps = -rrequirements-dev.txt -rrequirements-min.txt @@ -59,10 +59,6 @@ commands = python setup.py sdist python setup.py bdist_wheel -[testenv:build-py36] -basepython = python3.6 -commands = {[testenv:build]commands} - [testenv:build-py37] basepython = python3.7 commands = {[testenv:build]commands} @@ -75,24 +71,24 @@ commands = {[testenv:build]commands} basepython = python3.9 commands = {[testenv:build]commands} -[testenv:build-py38-upgrade-dev] -basepython = python3.8 +[testenv:build-py39-upgrade-dev] +basepython = python3.9 install_command = pip install -U -e . {opts} {packages} deps = -rrequirements-dev.txt commands = {[testenv:build]commands} -[testenv:build-py38-upgrade-dev-pre] -basepython = python3.8 +[testenv:build-py39-upgrade-dev-pre] +basepython = python3.9 install_command = pip install -U --pre -e . {opts} {packages} deps = -rrequirements-dev.txt commands = {[testenv:build]commands} -[testenv:build-py36-min-req] -basepython = python3.6 +[testenv:build-py37-min-req] +basepython = python3.7 deps = -rrequirements-dev.txt -rrequirements-min.txt @@ -116,11 +112,6 @@ deps = commands = python test.py --example -[testenv:gallery-py36] -basepython = python3.6 -deps = {[testenv:gallery]deps} -commands = {[testenv:gallery]commands} - [testenv:gallery-py37] basepython = python3.7 deps = {[testenv:gallery]deps} @@ -136,32 +127,37 @@ basepython = python3.9 deps = {[testenv:gallery]deps} commands = {[testenv:gallery]commands} -[testenv:gallery-py38-upgrade-dev] -basepython = python3.8 +# Test with python 3.9, pinned dev and doc reqs, and upgraded run requirements +[testenv:gallery-py39-upgrade-dev] +basepython = python3.9 install_command = pip install -U -e . {opts} {packages} deps = -rrequirements-dev.txt + -rrequirements-doc.txt commands = {[testenv:gallery]commands} -[testenv:gallery-py38-upgrade-dev-pre] -basepython = python3.8 +# Test with python 3.9, pinned dev and doc reqs, and pre-release run requirements +[testenv:gallery-py39-upgrade-dev-pre] +basepython = python3.9 install_command = pip install -U --pre -e . {opts} {packages} deps = -rrequirements-dev.txt + -rrequirements-doc.txt commands = {[testenv:gallery]commands} -[testenv:gallery-py36-min-req] -basepython = python3.6 +# Test with python 3.7, pinned dev reqs, and minimum run requirements +[testenv:gallery-py37-min-req] +basepython = python3.7 deps = -rrequirements-dev.txt -rrequirements-min.txt -rrequirements-doc.txt commands = {[testenv:gallery]commands} -[testenv:validation-py37] -basepython = python3.7 +[testenv:validation-py39] +basepython = python3.9 install_command = pip install -U {opts} {packages} deps =

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