mirror of
https://github.com/p2p-ld/nwb-linkml.git
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testing nwb file, and experimenting with yaml format
This commit is contained in:
parent
0e4058520a
commit
b555ccb199
GPG key ID:
6DCB96EF1E4D232D
5 changed files with 655 additions and 49 deletions
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@ -5,7 +5,7 @@
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groups = ["default", "dev", "plot", "tests"]
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strategy = ["inherit_metadata"]
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lock_version = "4.5.0"
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content_hash = "sha256:f219083028bd024c53bc55626c8b6088d6eb5c2ade56bd694a7a112098aa9bfc"
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content_hash = "sha256:aaf3c34a5f39fc7db0c5dce91a0693eb78358a255d6b0a72f2e1f988eb7e899f"
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[[metadata.targets]]
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requires_python = ">=3.10,<3.13"
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@ -549,7 +549,7 @@ name = "h5py"
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version = "3.11.0"
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requires_python = ">=3.8"
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summary = "Read and write HDF5 files from Python"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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dependencies = [
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"numpy>=1.17.3",
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]
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@ -580,6 +580,26 @@ files = [
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{file = "hbreader-0.9.1.tar.gz", hash = "sha256:d2c132f8ba6276d794c66224c3297cec25c8079d0a4cf019c061611e0a3b94fa"},
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]
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[[package]]
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name = "hdmf"
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version = "3.14.3"
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requires_python = ">=3.8"
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summary = "A hierarchical data modeling framework for modern science data standards"
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groups = ["dev", "tests"]
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dependencies = [
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"h5py>=2.10",
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"importlib-resources; python_version < \"3.9\"",
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"jsonschema>=2.6.0",
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"numpy>=1.18",
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"pandas>=1.0.5",
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"ruamel-yaml>=0.16",
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"scipy>=1.4",
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]
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files = [
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{file = "hdmf-3.14.3-py3-none-any.whl", hash = "sha256:1417ccc0d336d535192b7a3db4c7354cbc15123f1ccb3cdd82e363308e78f9bc"},
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{file = "hdmf-3.14.3.tar.gz", hash = "sha256:e9548fc7bdbb534a2750092b6b9819df2ce50e27430866c3c32061a2306271cc"},
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]
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[[package]]
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name = "idna"
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version = "3.8"
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@ -751,7 +771,7 @@ name = "jsonschema"
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version = "4.23.0"
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requires_python = ">=3.8"
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summary = "An implementation of JSON Schema validation for Python"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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dependencies = [
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"attrs>=22.2.0",
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"importlib-resources>=1.4.0; python_version < \"3.9\"",
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@ -770,7 +790,7 @@ name = "jsonschema-specifications"
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version = "2023.12.1"
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requires_python = ">=3.8"
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summary = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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dependencies = [
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"importlib-resources>=1.4.0; python_version < \"3.9\"",
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"referencing>=0.31.0",
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@ -984,45 +1004,36 @@ files = [
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[[package]]
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name = "numpy"
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version = "2.1.0"
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requires_python = ">=3.10"
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version = "1.26.4"
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requires_python = ">=3.9"
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summary = "Fundamental package for array computing in Python"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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files = [
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{file = "numpy-2.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6326ab99b52fafdcdeccf602d6286191a79fe2fda0ae90573c5814cd2b0bc1b8"},
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{file = "numpy-2.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0937e54c09f7a9a68da6889362ddd2ff584c02d015ec92672c099b61555f8911"},
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{file = "numpy-2.1.0-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:30014b234f07b5fec20f4146f69e13cfb1e33ee9a18a1879a0142fbb00d47673"},
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{file = "numpy-2.1.0-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:899da829b362ade41e1e7eccad2cf274035e1cb36ba73034946fccd4afd8606b"},
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{file = "numpy-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:08801848a40aea24ce16c2ecde3b756f9ad756586fb2d13210939eb69b023f5b"},
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{file = "numpy-2.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:398049e237d1aae53d82a416dade04defed1a47f87d18d5bd615b6e7d7e41d1f"},
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{file = "numpy-2.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0abb3916a35d9090088a748636b2c06dc9a6542f99cd476979fb156a18192b84"},
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{file = "numpy-2.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:f505264735ee074250a9c78247ee8618292091d9d1fcc023290e9ac67e8f1afa"},
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{file = "numpy-2.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:76368c788ccb4f4782cf9c842b316140142b4cbf22ff8db82724e82fe1205dce"},
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{file = "numpy-2.1.0-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:f8e93a01a35be08d31ae33021e5268f157a2d60ebd643cfc15de6ab8e4722eb1"},
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{file = "numpy-2.1.0-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:9523f8b46485db6939bd069b28b642fec86c30909cea90ef550373787f79530e"},
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{file = "numpy-2.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:54139e0eb219f52f60656d163cbe67c31ede51d13236c950145473504fa208cb"},
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{file = "numpy-2.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5ebbf9fbdabed208d4ecd2e1dfd2c0741af2f876e7ae522c2537d404ca895c3"},
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{file = "numpy-2.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:0af3a5987f59d9c529c022c8c2a64805b339b7ef506509fba7d0556649b9714b"},
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{file = "numpy-2.1.0-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:dd94ce596bda40a9618324547cfaaf6650b1a24f5390350142499aa4e34e53d1"},
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{file = "numpy-2.1.0-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:b47c551c6724960479cefd7353656498b86e7232429e3a41ab83be4da1b109e8"},
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{file = "numpy-2.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0756a179afa766ad7cb6f036de622e8a8f16ffdd55aa31f296c870b5679d745"},
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{file = "numpy-2.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24003ba8ff22ea29a8c306e61d316ac74111cebf942afbf692df65509a05f111"},
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{file = "numpy-2.1.0-cp312-cp312-win32.whl", hash = "sha256:c4cd94dfefbefec3f8b544f61286584292d740e6e9d4677769bc76b8f41deb02"},
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{file = "numpy-2.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:a0cdef204199278f5c461a0bed6ed2e052998276e6d8ab2963d5b5c39a0500bc"},
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{file = "numpy-2.1.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:15ef8b2177eeb7e37dd5ef4016f30b7659c57c2c0b57a779f1d537ff33a72c7b"},
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{file = "numpy-2.1.0-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:e5f0642cdf4636198a4990de7a71b693d824c56a757862230454629cf62e323d"},
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{file = "numpy-2.1.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f15976718c004466406342789f31b6673776360f3b1e3c575f25302d7e789575"},
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{file = "numpy-2.1.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:6c1de77ded79fef664d5098a66810d4d27ca0224e9051906e634b3f7ead134c2"},
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{file = "numpy-2.1.0.tar.gz", hash = "sha256:7dc90da0081f7e1da49ec4e398ede6a8e9cc4f5ebe5f9e06b443ed889ee9aaa2"},
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{file = "numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f"},
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{file = "numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2"},
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{file = "numpy-1.26.4-cp311-cp311-win_amd64.whl", hash = "sha256:cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2"},
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{file = "numpy-1.26.4-cp312-cp312-win_amd64.whl", hash = "sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818"},
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{file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"},
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]
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[[package]]
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@ -1102,7 +1113,7 @@ name = "pandas"
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version = "2.2.2"
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requires_python = ">=3.9"
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summary = "Powerful data structures for data analysis, time series, and statistics"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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dependencies = [
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"numpy>=1.22.4; python_version < \"3.11\"",
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"numpy>=1.23.2; python_version == \"3.11\"",
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@ -1350,6 +1361,24 @@ files = [
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{file = "PyJSG-0.11.10.tar.gz", hash = "sha256:4bd6e3ff2833fa2b395bbe803a2d72a5f0bab5b7285bccd0da1a1bc0aee88bfa"},
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]
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[[package]]
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name = "pynwb"
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version = "2.8.1"
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requires_python = ">=3.8"
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summary = "Package for working with Neurodata stored in the NWB format."
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groups = ["dev", "tests"]
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dependencies = [
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"h5py>=2.10",
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"hdmf>=3.14.0",
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"numpy<2.0,>=1.18",
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"pandas>=1.1.5",
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"python-dateutil>=2.7.3",
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]
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files = [
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{file = "pynwb-2.8.1-py3-none-any.whl", hash = "sha256:f3c392652b26396e135cf6f1abd570d413c9eb7bf5bdb1a89d899852338fdf6c"},
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{file = "pynwb-2.8.1.tar.gz", hash = "sha256:498e4bc46a7b0a1331a0f754bac72ea7f9d10d1bba35af3c7be78a61bb1d104b"},
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]
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[[package]]
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name = "pyparsing"
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version = "3.1.4"
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@ -1469,7 +1498,7 @@ name = "python-dateutil"
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version = "2.9.0.post0"
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requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
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summary = "Extensions to the standard Python datetime module"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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dependencies = [
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"six>=1.5",
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]
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@ -1506,7 +1535,7 @@ files = [
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name = "pytz"
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version = "2024.1"
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summary = "World timezone definitions, modern and historical"
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groups = ["default"]
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groups = ["default", "dev", "tests"]
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files = [
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|
||||
|
|
@ -1597,7 +1626,7 @@ name = "referencing"
|
|||
version = "0.35.1"
|
||||
requires_python = ">=3.8"
|
||||
summary = "JSON Referencing + Python"
|
||||
groups = ["default"]
|
||||
groups = ["default", "dev", "tests"]
|
||||
dependencies = [
|
||||
"attrs>=22.2.0",
|
||||
"rpds-py>=0.7.0",
|
||||
|
|
@ -1701,7 +1730,7 @@ name = "rpds-py"
|
|||
version = "0.20.0"
|
||||
requires_python = ">=3.8"
|
||||
summary = "Python bindings to Rust's persistent data structures (rpds)"
|
||||
groups = ["default"]
|
||||
groups = ["default", "dev", "tests"]
|
||||
files = [
|
||||
{file = "rpds_py-0.20.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:3ad0fda1635f8439cde85c700f964b23ed5fc2d28016b32b9ee5fe30da5c84e2"},
|
||||
{file = "rpds_py-0.20.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9bb4a0d90fdb03437c109a17eade42dfbf6190408f29b2744114d11586611d6f"},
|
||||
|
|
@ -1762,7 +1791,7 @@ name = "ruamel-yaml"
|
|||
version = "0.18.6"
|
||||
requires_python = ">=3.7"
|
||||
summary = "ruamel.yaml is a YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order"
|
||||
groups = ["default"]
|
||||
groups = ["default", "dev", "tests"]
|
||||
dependencies = [
|
||||
"ruamel-yaml-clib>=0.2.7; platform_python_implementation == \"CPython\" and python_version < \"3.13\"",
|
||||
]
|
||||
|
|
@ -1776,7 +1805,7 @@ name = "ruamel-yaml-clib"
|
|||
version = "0.2.8"
|
||||
requires_python = ">=3.6"
|
||||
summary = "C version of reader, parser and emitter for ruamel.yaml derived from libyaml"
|
||||
groups = ["default"]
|
||||
groups = ["default", "dev", "tests"]
|
||||
marker = "platform_python_implementation == \"CPython\" and python_version < \"3.13\""
|
||||
files = [
|
||||
{file = "ruamel.yaml.clib-0.2.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b42169467c42b692c19cf539c38d4602069d8c1505e97b86387fcf7afb766e1d"},
|
||||
|
|
@ -1833,6 +1862,43 @@ files = [
|
|||
{file = "ruff-0.6.2.tar.gz", hash = "sha256:239ee6beb9e91feb8e0ec384204a763f36cb53fb895a1a364618c6abb076b3be"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "scipy"
|
||||
version = "1.14.1"
|
||||
requires_python = ">=3.10"
|
||||
summary = "Fundamental algorithms for scientific computing in Python"
|
||||
groups = ["dev", "tests"]
|
||||
dependencies = [
|
||||
"numpy<2.3,>=1.23.5",
|
||||
]
|
||||
files = [
|
||||
{file = "scipy-1.14.1-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:b28d2ca4add7ac16ae8bb6632a3c86e4b9e4d52d3e34267f6e1b0c1f8d87e389"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:d0d2821003174de06b69e58cef2316a6622b60ee613121199cb2852a873f8cf3"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:8bddf15838ba768bb5f5083c1ea012d64c9a444e16192762bd858f1e126196d0"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:97c5dddd5932bd2a1a31c927ba5e1463a53b87ca96b5c9bdf5dfd6096e27efc3"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ff0a7e01e422c15739ecd64432743cf7aae2b03f3084288f399affcefe5222d"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8e32dced201274bf96899e6491d9ba3e9a5f6b336708656466ad0522d8528f69"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8426251ad1e4ad903a4514712d2fa8fdd5382c978010d1c6f5f37ef286a713ad"},
|
||||
{file = "scipy-1.14.1-cp310-cp310-win_amd64.whl", hash = "sha256:a49f6ed96f83966f576b33a44257d869756df6cf1ef4934f59dd58b25e0327e5"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:2da0469a4ef0ecd3693761acbdc20f2fdeafb69e6819cc081308cc978153c675"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:c0ee987efa6737242745f347835da2cc5bb9f1b42996a4d97d5c7ff7928cb6f2"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:3a1b111fac6baec1c1d92f27e76511c9e7218f1695d61b59e05e0fe04dc59617"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:8475230e55549ab3f207bff11ebfc91c805dc3463ef62eda3ccf593254524ce8"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:278266012eb69f4a720827bdd2dc54b2271c97d84255b2faaa8f161a158c3b37"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fef8c87f8abfb884dac04e97824b61299880c43f4ce675dd2cbeadd3c9b466d2"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b05d43735bb2f07d689f56f7b474788a13ed8adc484a85aa65c0fd931cf9ccd2"},
|
||||
{file = "scipy-1.14.1-cp311-cp311-win_amd64.whl", hash = "sha256:716e389b694c4bb564b4fc0c51bc84d381735e0d39d3f26ec1af2556ec6aad94"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:631f07b3734d34aced009aaf6fedfd0eb3498a97e581c3b1e5f14a04164a456d"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:af29a935803cc707ab2ed7791c44288a682f9c8107bc00f0eccc4f92c08d6e07"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:2843f2d527d9eebec9a43e6b406fb7266f3af25a751aa91d62ff416f54170bc5"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:eb58ca0abd96911932f688528977858681a59d61a7ce908ffd355957f7025cfc"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:30ac8812c1d2aab7131a79ba62933a2a76f582d5dbbc695192453dae67ad6310"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f9ea80f2e65bdaa0b7627fb00cbeb2daf163caa015e59b7516395fe3bd1e066"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:edaf02b82cd7639db00dbff629995ef185c8df4c3ffa71a5562a595765a06ce1"},
|
||||
{file = "scipy-1.14.1-cp312-cp312-win_amd64.whl", hash = "sha256:2ff38e22128e6c03ff73b6bb0f85f897d2362f8c052e3b8ad00532198fbdae3f"},
|
||||
{file = "scipy-1.14.1.tar.gz", hash = "sha256:5a275584e726026a5699459aa72f828a610821006228e841b94275c4a7c08417"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "setuptools"
|
||||
version = "74.0.0"
|
||||
|
|
@ -2023,7 +2089,7 @@ name = "tzdata"
|
|||
version = "2024.1"
|
||||
requires_python = ">=2"
|
||||
summary = "Provider of IANA time zone data"
|
||||
groups = ["default"]
|
||||
groups = ["default", "dev", "tests"]
|
||||
files = [
|
||||
{file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
|
||||
{file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
|
||||
|
|
|
|||
|
|
@ -44,6 +44,7 @@ tests = [
|
|||
"pytest-cov<5.0.0,>=4.1.0",
|
||||
"sybil>=6.0.3",
|
||||
"requests-cache>=1.2.1",
|
||||
"pynwb>=2.8.1",
|
||||
]
|
||||
dev = [
|
||||
"nwb-linkml[tests]",
|
||||
|
|
|
|||
78
nwb_linkml/tests/data/test_nwb.yaml
Normal file
78
nwb_linkml/tests/data/test_nwb.yaml
Normal file
|
|
@ -0,0 +1,78 @@
|
|||
# manually transcribed target version of nwb-linkml dataset
|
||||
# matching the one created by fixtures.py:nwb_file
|
||||
---
|
||||
id: my_dataset
|
||||
|
||||
prefixes:
|
||||
nwbfile:
|
||||
- path: "test_nwb.nwb"
|
||||
- hash: "blake2b:blahblahblahblah"
|
||||
|
||||
imports:
|
||||
core:
|
||||
as: nwb
|
||||
version: "2.7.0"
|
||||
from:
|
||||
- pypi:
|
||||
package: nwb-models
|
||||
---
|
||||
|
||||
hdmf-common:
|
||||
as: hdmf
|
||||
version: "1.8.0"
|
||||
from:
|
||||
- pypi:
|
||||
package: nwb-models
|
||||
---
|
||||
|
||||
extracellular_ephys: &ecephys
|
||||
electrodes:
|
||||
group:
|
||||
- @shank{{i}}
|
||||
- @shank{{i}}
|
||||
- @shank{{i}}
|
||||
# could have expression here like { range(3) } => i
|
||||
# - ... { range(3) } => i
|
||||
# or blank ... implies use expression from outer scope
|
||||
- ...
|
||||
shank{{i}}:
|
||||
device: @general.devices.array
|
||||
...: { range(3) } => i
|
||||
|
||||
# expands to
|
||||
extracellular_ephys:
|
||||
electrodes:
|
||||
group:
|
||||
- @shank0
|
||||
- @shank0
|
||||
- @shank0
|
||||
- @shank1
|
||||
- # etc.
|
||||
shank0:
|
||||
device: @general.devices.array
|
||||
shank1:
|
||||
device: @general.devices.array
|
||||
# etc.
|
||||
|
||||
data: !{{ nwb.NWBFile }} <== :nwbfile
|
||||
file_create_date: [ 2024-01-01 ]
|
||||
identifier: "1111-1111-1111-1111"
|
||||
session_description: All that you touch, you change.
|
||||
session_start_time: 2024-01-01T01:01:01
|
||||
general:
|
||||
devices:
|
||||
- Heka ITC-1600:
|
||||
- Microscope:
|
||||
- array:
|
||||
description: old reliable
|
||||
manufacturer: diy
|
||||
extracellular_ephys: *ecephys
|
||||
|
||||
experiment_description: All that you change, changes you.
|
||||
experimenter: [ "Lauren Oya Olamina" ]
|
||||
institution: Earthseed Research Institute
|
||||
keywords:
|
||||
- behavior
|
||||
- belief
|
||||
related_publications: doi:10.1016/j.neuron.2016.12.011
|
||||
|
||||
|
|
@ -1,9 +1,12 @@
|
|||
import shutil
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime
|
||||
from itertools import product
|
||||
from pathlib import Path
|
||||
from types import ModuleType
|
||||
from typing import Dict, Optional
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
from linkml_runtime.dumpers import yaml_dumper
|
||||
from linkml_runtime.linkml_model import (
|
||||
|
|
@ -13,6 +16,24 @@ from linkml_runtime.linkml_model import (
|
|||
SlotDefinition,
|
||||
TypeDefinition,
|
||||
)
|
||||
from pynwb import NWBHDF5IO, NWBFile, TimeSeries
|
||||
from pynwb.base import TimeSeriesReference, TimeSeriesReferenceVectorData
|
||||
from pynwb.behavior import Position, SpatialSeries
|
||||
from pynwb.core import DynamicTable, VectorData
|
||||
from pynwb.ecephys import LFP, ElectricalSeries
|
||||
from pynwb.file import Subject
|
||||
from pynwb.icephys import VoltageClampSeries, VoltageClampStimulusSeries
|
||||
from pynwb.image import ImageSeries
|
||||
from pynwb.ophys import (
|
||||
CorrectedImageStack,
|
||||
Fluorescence,
|
||||
ImageSegmentation,
|
||||
MotionCorrection,
|
||||
OnePhotonSeries,
|
||||
OpticalChannel,
|
||||
RoiResponseSeries,
|
||||
TwoPhotonSeries,
|
||||
)
|
||||
|
||||
from nwb_linkml.adapters.namespaces import NamespacesAdapter
|
||||
from nwb_linkml.io import schema as io
|
||||
|
|
@ -27,6 +48,7 @@ __all__ = [
|
|||
"linkml_schema",
|
||||
"linkml_schema_bare",
|
||||
"nwb_core_fixture",
|
||||
"nwb_file",
|
||||
"nwb_schema",
|
||||
"tmp_output_dir",
|
||||
"tmp_output_dir_func",
|
||||
|
|
@ -314,3 +336,425 @@ def nwb_schema() -> NWBSchemaTest:
|
|||
],
|
||||
)
|
||||
return NWBSchemaTest(datasets={"image": image}, groups={"images": images})
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def nwb_file(tmp_output_dir) -> Path:
|
||||
"""
|
||||
NWB File created with pynwb that uses all the weird language features
|
||||
|
||||
Borrowing code from pynwb docs in one humonogous fixture function
|
||||
since there's not really a reason to
|
||||
"""
|
||||
generator = np.random.default_rng()
|
||||
|
||||
nwb_path = tmp_output_dir / "test_nwb.nwb"
|
||||
|
||||
nwbfile = NWBFile(
|
||||
session_description="All that you touch, you change.", # required
|
||||
identifier="1111-1111-1111-1111", # required
|
||||
session_start_time=datetime(year=2024, month=1, day=1), # required
|
||||
session_id="session_1234", # optional
|
||||
experimenter=[
|
||||
"Lauren Oya Olamina",
|
||||
], # optional
|
||||
institution="Earthseed Research Institute", # optional
|
||||
experiment_description="All that you change, changes you.", # optional
|
||||
keywords=["behavior", "belief"], # optional
|
||||
related_publications="doi:10.1016/j.neuron.2016.12.011", # optional
|
||||
)
|
||||
subject = Subject(
|
||||
subject_id="001",
|
||||
age="P90D",
|
||||
description="mouse 5",
|
||||
species="Mus musculus",
|
||||
sex="M",
|
||||
)
|
||||
nwbfile.subject = subject
|
||||
|
||||
data = np.arange(100, 200, 10)
|
||||
timestamps = np.arange(10.0)
|
||||
time_series_with_timestamps = TimeSeries(
|
||||
name="test_timeseries",
|
||||
description="an example time series",
|
||||
data=data,
|
||||
unit="m",
|
||||
timestamps=timestamps,
|
||||
)
|
||||
nwbfile.add_acquisition(time_series_with_timestamps)
|
||||
|
||||
position_data = np.array([np.linspace(0, 10, 50), np.linspace(0, 8, 50)]).T
|
||||
position_timestamps = np.linspace(0, 50).astype(float) / 200
|
||||
|
||||
spatial_series_obj = SpatialSeries(
|
||||
name="SpatialSeries",
|
||||
description="(x,y) position in open field",
|
||||
data=position_data,
|
||||
timestamps=position_timestamps,
|
||||
reference_frame="(0,0) is bottom left corner",
|
||||
)
|
||||
# name is set to "Position" by default
|
||||
position_obj = Position(spatial_series=spatial_series_obj)
|
||||
behavior_module = nwbfile.create_processing_module(
|
||||
name="behavior", description="processed behavioral data"
|
||||
)
|
||||
behavior_module.add(position_obj)
|
||||
|
||||
nwbfile.add_trial_column(
|
||||
name="correct",
|
||||
description="whether the trial was correct",
|
||||
)
|
||||
nwbfile.add_trial(start_time=1.0, stop_time=5.0, correct=True)
|
||||
nwbfile.add_trial(start_time=6.0, stop_time=10.0, correct=False)
|
||||
|
||||
# --------------------------------------------------
|
||||
# Extracellular Ephys
|
||||
# https://pynwb.readthedocs.io/en/latest/tutorials/domain/ecephys.html
|
||||
# --------------------------------------------------
|
||||
device = nwbfile.create_device(name="array", description="old reliable", manufacturer="diy")
|
||||
nwbfile.add_electrode_column(name="label", description="label of electrode")
|
||||
|
||||
nshanks = 4
|
||||
nchannels_per_shank = 3
|
||||
electrode_counter = 0
|
||||
|
||||
for ishank in range(nshanks):
|
||||
# create an electrode group for this shank
|
||||
electrode_group = nwbfile.create_electrode_group(
|
||||
name=f"shank{ishank}",
|
||||
description=f"electrode group for shank {ishank}",
|
||||
device=device,
|
||||
location="brain area",
|
||||
)
|
||||
# add electrodes to the electrode table
|
||||
for ielec in range(nchannels_per_shank):
|
||||
nwbfile.add_electrode(
|
||||
group=electrode_group,
|
||||
label=f"shank{ishank}elec{ielec}",
|
||||
location="brain area",
|
||||
)
|
||||
electrode_counter += 1
|
||||
all_table_region = nwbfile.create_electrode_table_region(
|
||||
region=list(range(electrode_counter)), # reference row indices 0 to N-1
|
||||
description="all electrodes",
|
||||
)
|
||||
raw_data = generator.standard_normal((50, 12))
|
||||
raw_electrical_series = ElectricalSeries(
|
||||
name="ElectricalSeries",
|
||||
description="Raw acquisition traces",
|
||||
data=raw_data,
|
||||
electrodes=all_table_region,
|
||||
starting_time=0.0,
|
||||
# timestamp of the first sample in seconds relative to the session start time
|
||||
rate=20000.0, # in Hz
|
||||
)
|
||||
nwbfile.add_acquisition(raw_electrical_series)
|
||||
|
||||
# --------------------------------------------------
|
||||
# LFP
|
||||
# --------------------------------------------------
|
||||
lfp_data = generator.standard_normal((50, 12))
|
||||
lfp_electrical_series = ElectricalSeries(
|
||||
name="ElectricalSeries",
|
||||
description="LFP data",
|
||||
data=lfp_data,
|
||||
electrodes=all_table_region,
|
||||
starting_time=0.0,
|
||||
rate=200.0,
|
||||
)
|
||||
lfp = LFP(electrical_series=lfp_electrical_series)
|
||||
ecephys_module = nwbfile.create_processing_module(
|
||||
name="ecephys", description="processed extracellular electrophysiology data"
|
||||
)
|
||||
ecephys_module.add(lfp)
|
||||
|
||||
# Spike Times
|
||||
nwbfile.add_unit_column(name="quality", description="sorting quality")
|
||||
firing_rate = 20
|
||||
n_units = 10
|
||||
res = 1000
|
||||
duration = 20
|
||||
for _ in range(n_units):
|
||||
spike_times = np.where(generator.random(res * duration) < (firing_rate / res))[0] / res
|
||||
nwbfile.add_unit(spike_times=spike_times, quality="good")
|
||||
|
||||
# --------------------------------------------------
|
||||
# Intracellular ephys
|
||||
# --------------------------------------------------
|
||||
device = nwbfile.create_device(name="Heka ITC-1600")
|
||||
electrode = nwbfile.create_icephys_electrode(
|
||||
name="elec0", description="a mock intracellular electrode", device=device
|
||||
)
|
||||
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),
|
||||
)
|
||||
# we can also add stimulus template data as follows
|
||||
rowindex = nwbfile.add_intracellular_recording(
|
||||
electrode=electrode, stimulus=stimulus, response=response, id=10
|
||||
)
|
||||
|
||||
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,
|
||||
)
|
||||
rowindex3 = nwbfile.add_intracellular_recording(electrode=electrode, response=response, id=12)
|
||||
|
||||
nwbfile.intracellular_recordings.add_column(
|
||||
name="recording_tag",
|
||||
data=["A1", "A2", "A3"],
|
||||
description="String with a recording tag",
|
||||
)
|
||||
location_column = VectorData(
|
||||
name="location",
|
||||
data=["Mordor", "Gondor", "Rohan"],
|
||||
description="Recording location in Middle Earth",
|
||||
)
|
||||
|
||||
lab_category = DynamicTable(
|
||||
name="recording_lab_data",
|
||||
description="category table for lab-specific recording metadata",
|
||||
colnames=[
|
||||
"location",
|
||||
],
|
||||
columns=[
|
||||
location_column,
|
||||
],
|
||||
)
|
||||
# Add the table as a new category to our intracellular_recordings
|
||||
nwbfile.intracellular_recordings.add_category(category=lab_category)
|
||||
nwbfile.intracellular_recordings.add_column(
|
||||
name="voltage_threshold",
|
||||
data=[0.1, 0.12, 0.13],
|
||||
description="Just an example column on the electrodes category table",
|
||||
category="electrodes",
|
||||
)
|
||||
stimulus_template = VoltageClampStimulusSeries(
|
||||
name="ccst",
|
||||
data=[0, 1, 2, 3, 4],
|
||||
starting_time=0.0,
|
||||
rate=10e3,
|
||||
electrode=electrode,
|
||||
gain=0.02,
|
||||
)
|
||||
nwbfile.add_stimulus_template(stimulus_template)
|
||||
|
||||
nwbfile.intracellular_recordings.add_column(
|
||||
name="stimulus_template",
|
||||
data=[
|
||||
TimeSeriesReference(0, 5, stimulus_template),
|
||||
# (start_index, index_count, stimulus_template)
|
||||
TimeSeriesReference(1, 3, stimulus_template),
|
||||
TimeSeriesReference.empty(stimulus_template),
|
||||
],
|
||||
# if there was no data for that recording, use empty reference
|
||||
description=(
|
||||
"Column storing the reference to the stimulus template for the recording (rows)."
|
||||
),
|
||||
category="stimuli",
|
||||
col_cls=TimeSeriesReferenceVectorData,
|
||||
)
|
||||
|
||||
icephys_simultaneous_recordings = nwbfile.get_icephys_simultaneous_recordings()
|
||||
icephys_simultaneous_recordings.add_column(
|
||||
name="simultaneous_recording_tag",
|
||||
description="A custom tag for simultaneous_recordings",
|
||||
)
|
||||
simultaneous_index = nwbfile.add_icephys_simultaneous_recording(
|
||||
recordings=[rowindex, rowindex2, rowindex3],
|
||||
id=12,
|
||||
simultaneous_recording_tag="LabTag1",
|
||||
)
|
||||
repetition_index = nwbfile.add_icephys_repetition(
|
||||
sequential_recordings=[simultaneous_index], id=17
|
||||
)
|
||||
nwbfile.add_icephys_experimental_condition(repetitions=[repetition_index], id=19)
|
||||
nwbfile.icephys_experimental_conditions.add_column(
|
||||
name="tag",
|
||||
data=np.arange(1),
|
||||
description="integer tag for a experimental condition",
|
||||
)
|
||||
|
||||
# --------------------------------------------------
|
||||
# Calcium Imaging
|
||||
# https://pynwb.readthedocs.io/en/latest/tutorials/domain/ophys.html
|
||||
# --------------------------------------------------
|
||||
device = nwbfile.create_device(
|
||||
name="Microscope",
|
||||
description="My two-photon microscope",
|
||||
manufacturer="The best microscope manufacturer",
|
||||
)
|
||||
optical_channel = OpticalChannel(
|
||||
name="OpticalChannel",
|
||||
description="an optical channel",
|
||||
emission_lambda=500.0,
|
||||
)
|
||||
imaging_plane = nwbfile.create_imaging_plane(
|
||||
name="ImagingPlane",
|
||||
optical_channel=optical_channel,
|
||||
imaging_rate=30.0,
|
||||
description="a very interesting part of the brain",
|
||||
device=device,
|
||||
excitation_lambda=600.0,
|
||||
indicator="GFP",
|
||||
location="V1",
|
||||
grid_spacing=[0.01, 0.01],
|
||||
grid_spacing_unit="meters",
|
||||
origin_coords=[1.0, 2.0, 3.0],
|
||||
origin_coords_unit="meters",
|
||||
)
|
||||
one_p_series = OnePhotonSeries(
|
||||
name="OnePhotonSeries",
|
||||
description="Raw 1p data",
|
||||
data=np.ones((1000, 100, 100)),
|
||||
imaging_plane=imaging_plane,
|
||||
rate=1.0,
|
||||
unit="normalized amplitude",
|
||||
)
|
||||
nwbfile.add_acquisition(one_p_series)
|
||||
two_p_series = TwoPhotonSeries(
|
||||
name="TwoPhotonSeries",
|
||||
description="Raw 2p data",
|
||||
data=np.ones((1000, 100, 100)),
|
||||
imaging_plane=imaging_plane,
|
||||
rate=1.0,
|
||||
unit="normalized amplitude",
|
||||
)
|
||||
|
||||
nwbfile.add_acquisition(two_p_series)
|
||||
|
||||
corrected = ImageSeries(
|
||||
name="corrected", # this must be named "corrected"
|
||||
description="A motion corrected image stack",
|
||||
data=np.ones((1000, 100, 100)),
|
||||
unit="na",
|
||||
format="raw",
|
||||
starting_time=0.0,
|
||||
rate=1.0,
|
||||
)
|
||||
|
||||
xy_translation = TimeSeries(
|
||||
name="xy_translation",
|
||||
description="x,y translation in pixels",
|
||||
data=np.ones((1000, 2)),
|
||||
unit="pixels",
|
||||
starting_time=0.0,
|
||||
rate=1.0,
|
||||
)
|
||||
|
||||
corrected_image_stack = CorrectedImageStack(
|
||||
corrected=corrected,
|
||||
original=one_p_series,
|
||||
xy_translation=xy_translation,
|
||||
)
|
||||
|
||||
motion_correction = MotionCorrection(corrected_image_stacks=[corrected_image_stack])
|
||||
|
||||
ophys_module = nwbfile.create_processing_module(
|
||||
name="ophys", description="optical physiology processed data"
|
||||
)
|
||||
|
||||
ophys_module.add(motion_correction)
|
||||
|
||||
img_seg = ImageSegmentation()
|
||||
|
||||
ps = img_seg.create_plane_segmentation(
|
||||
name="PlaneSegmentation",
|
||||
description="output from segmenting my favorite imaging plane",
|
||||
imaging_plane=imaging_plane,
|
||||
reference_images=one_p_series, # optional
|
||||
)
|
||||
|
||||
ophys_module.add(img_seg)
|
||||
|
||||
for _ in range(30):
|
||||
image_mask = np.zeros((100, 100))
|
||||
|
||||
# randomly generate example image masks
|
||||
x = generator.integers(0, 95)
|
||||
y = generator.integers(0, 95)
|
||||
image_mask[x : x + 5, y : y + 5] = 1
|
||||
|
||||
# add image mask to plane segmentation
|
||||
ps.add_roi(image_mask=image_mask)
|
||||
|
||||
ps2 = img_seg.create_plane_segmentation(
|
||||
name="PlaneSegmentation2",
|
||||
description="output from segmenting my favorite imaging plane",
|
||||
imaging_plane=imaging_plane,
|
||||
reference_images=one_p_series, # optional
|
||||
)
|
||||
|
||||
for _ in range(30):
|
||||
# randomly generate example starting points for region
|
||||
x = generator.integers(0, 95)
|
||||
y = generator.integers(0, 95)
|
||||
|
||||
# define an example 4 x 3 region of pixels of weight '1'
|
||||
pixel_mask = [(ix, iy, 1) for ix in range(x, x + 4) for iy in range(y, y + 3)]
|
||||
|
||||
# add pixel mask to plane segmentation
|
||||
ps2.add_roi(pixel_mask=pixel_mask)
|
||||
|
||||
ps3 = img_seg.create_plane_segmentation(
|
||||
name="PlaneSegmentation3",
|
||||
description="output from segmenting my favorite imaging plane",
|
||||
imaging_plane=imaging_plane,
|
||||
reference_images=one_p_series, # optional
|
||||
)
|
||||
|
||||
for _ in range(30):
|
||||
# randomly generate example starting points for region
|
||||
x = generator.integers(0, 95)
|
||||
y = generator.integers(0, 95)
|
||||
z = generator.integers(0, 15)
|
||||
|
||||
# define an example 4 x 3 x 2 voxel region of weight '0.5'
|
||||
voxel_mask = []
|
||||
for ix, iy, iz in product(range(x, x + 4), range(y, y + 3), range(z, z + 2)):
|
||||
voxel_mask.append((ix, iy, iz, 0.5))
|
||||
|
||||
# add voxel mask to plane segmentation
|
||||
ps3.add_roi(voxel_mask=voxel_mask)
|
||||
rt_region = ps.create_roi_table_region(region=[0, 1], description="the first of two ROIs")
|
||||
roi_resp_series = RoiResponseSeries(
|
||||
name="RoiResponseSeries",
|
||||
description="Fluorescence responses for two ROIs",
|
||||
data=np.ones((50, 2)), # 50 samples, 2 ROIs
|
||||
rois=rt_region,
|
||||
unit="lumens",
|
||||
rate=30.0,
|
||||
)
|
||||
fl = Fluorescence(roi_response_series=roi_resp_series)
|
||||
ophys_module.add(fl)
|
||||
|
||||
with NWBHDF5IO(nwb_path, "w") as io:
|
||||
io.write(nwbfile)
|
||||
|
||||
return nwb_path
|
||||
|
|
|
|||
17
nwb_linkml/tests/test_io/test_io_nwb.py
Normal file
17
nwb_linkml/tests/test_io/test_io_nwb.py
Normal file
|
|
@ -0,0 +1,17 @@
|
|||
"""
|
||||
Placeholder test module to test reading from pynwb-generated NWB file
|
||||
"""
|
||||
|
||||
|
||||
def test_read_from_nwbfile(nwb_file):
|
||||
"""
|
||||
Read data from a pynwb HDF5 NWB file
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
def test_read_from_yaml(nwb_file):
|
||||
"""
|
||||
Read data from a yaml-fied NWB file
|
||||
"""
|
||||
pass
|
||||
Loading…
Reference in a new issue