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rly/xarray_reading_nwb_hdf5_via_zarr_rfs.ipynb

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xarray_reading_nwb_hdf5_via_zarr_rfs.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "b7ad12b5-62d9-4d7d-8da4-761b5e7dcc26",
"metadata": {},
"outputs": [],
"source": [
"import lindi\n",
"from pynwb import NWBHDF5IO\n",
"from pynwb.testing.mock.ecephys import mock_ElectricalSeries\n",
"from pynwb.testing.mock.file import mock_NWBFile\n",
"import numpy as np\n",
"import json\n",
"import warnings\n",
"\n",
"warnings.simplefilter(\"always\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a7cb5cfc",
"metadata": {},
"outputs": [],
"source": [
"es_data = np.arange(50).reshape(10, 5)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "b3ab778e-72a1-4f37-8a1e-d443c94cf1ac",
"metadata": {},
"outputs": [],
"source": [
"nwb_file_path = \"example.nwb\"\n",
"nwbfile = mock_NWBFile()\n",
"es = mock_ElectricalSeries(\n",
" name=\"ElectricalSeries\",\n",
" timestamps=np.arange(10.),\n",
" rate=None,\n",
" nwbfile=nwbfile,\n",
" data=es_data,\n",
" conversion=10.,\n",
" offset=1.,\n",
")\n",
"# mock data has shape (10, 5) and is all ones\n",
"\n",
"with NWBHDF5IO(nwb_file_path, \"w\") as io:\n",
" io.write(nwbfile)\n",
"\n",
"# Create a read-only Zarr store as a wrapper for the h5 file\n",
"# Set url to the local file reference for local read\n",
"store = lindi.LindiH5ZarrStore.from_file(nwb_file_path, url=nwb_file_path)\n",
"\n",
"# Generate a reference file system\n",
"rfs = store.to_reference_file_system()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "5dd8cc3f-8f8c-4a84-a581-8257d37881af",
"metadata": {},
"outputs": [],
"source": [
"with NWBHDF5IO(nwb_file_path, \"r\") as io:\n",
" nwbfile = io.read()\n",
" data = nwbfile.acquisition[\"ElectricalSeries\"].data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d5065a57-f012-4423-bee7-6bf8bfdf422b",
"metadata": {},
"outputs": [],
"source": [
"def adjust_array(rfs, dset_name, dims):\n",
" # TODO handle consolidated metadata\n",
" zattrs = json.loads(rfs[\"refs\"][f\"{dset_name}/.zattrs\"])\n",
" # write special xarray attributes for automatic scaling and units\n",
" if \"unit\" in zattrs:\n",
" zattrs[\"units\"] = zattrs[\"unit\"]\n",
" if \"conversion\" in zattrs:\n",
" zattrs[\"scale_factor\"] = zattrs[\"conversion\"]\n",
" if \"offset\" in zattrs:\n",
" zattrs[\"add_offset\"] = zattrs[\"offset\"]\n",
" zattrs[\"_ARRAY_DIMENSIONS\"] = dims\n",
" rfs[\"refs\"][f\"{dset_name}/.zattrs\"] = json.dumps(zattrs)\n",
" \n",
" zarray = json.loads(rfs[\"refs\"][f\"{dset_name}/.zarray\"])\n",
" # workaround for https://github.com/pydata/xarray/issues/5475\n",
" # to use scale_factor and add_offset without converting all\n",
" # values that equal fill_value to NaN\n",
" if zarray[\"fill_value\"] in (0, 0.0, False):\n",
" zarray[\"fill_value\"] = None\n",
" rfs[\"refs\"][f\"{dset_name}/.zarray\"] = json.dumps(zarray)\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "df58686c-e2df-418a-8621-496c935d90c2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"version\": 1,\n",
" \"refs\": {\n",
" \".zgroup\": \"{\\\"zarr_format\\\":2}\",\n",
" \".zattrs\": \"{\\\"comments\\\":\\\"no comments\\\",\\\"description\\\":\\\"description\\\",\\\"filtering\\\":\\\"filtering\\\",\\\"namespace\\\":\\\"core\\\",\\\"neurodata_type\\\":\\\"ElectricalSeries\\\",\\\"object_id\\\":\\\"f7696ed3-2c80-4fb4-b284-5469e2c11a6c\\\"}\",\n",
" \"data/.zattrs\": \"{\\\"conversion\\\": 10.0, \\\"offset\\\": 1.0, \\\"resolution\\\": -1.0, \\\"unit\\\": \\\"volts\\\", \\\"units\\\": \\\"volts\\\", \\\"scale_factor\\\": 10.0, \\\"add_offset\\\": 1.0, \\\"_ARRAY_DIMENSIONS\\\": [\\\"timestamps\\\", \\\"electrodes\\\"]}\",\n",
" \"data/.zarray\": \"{\\\"chunks\\\": [10, 5], \\\"compressor\\\": null, \\\"dtype\\\": \\\"<i8\\\", \\\"fill_value\\\": null, \\\"filters\\\": null, \\\"order\\\": \\\"C\\\", \\\"shape\\\": [10, 5], \\\"zarr_format\\\": 2}\",\n",
" \"data/0.0\": [\n",
" \"example.nwb\",\n",
" 3464,\n",
" 400\n",
" ],\n",
" \"electrodes/.zattrs\": \"{\\\"description\\\": \\\"the first and third electrodes\\\", \\\"namespace\\\": \\\"hdmf-common\\\", \\\"neurodata_type\\\": \\\"DynamicTableRegion\\\", \\\"object_id\\\": \\\"65b98b43-3cfc-4774-bf05-ca342c9c624a\\\", \\\"table\\\": {\\\"_REFERENCE\\\": {\\\"object_id\\\": \\\"5307b610-47dc-43cb-b6b4-02dbfb98bcf0\\\", \\\"path\\\": \\\"/general/extracellular_ephys/electrodes\\\", \\\"source\\\": \\\".\\\", \\\"source_object_id\\\": \\\"fe8ec11f-9737-4368-b87b-6fcf24c256f6\\\"}}, \\\"_ARRAY_DIMENSIONS\\\": [\\\"electrodes\\\"]}\",\n",
" \"electrodes/.zarray\": \"{\\\"chunks\\\": [5], \\\"compressor\\\": null, \\\"dtype\\\": \\\"<i8\\\", \\\"fill_value\\\": null, \\\"filters\\\": null, \\\"order\\\": \\\"C\\\", \\\"shape\\\": [5], \\\"zarr_format\\\": 2}\",\n",
" \"electrodes/0\": [\n",
" \"example.nwb\",\n",
" 10008,\n",
" 40\n",
" ],\n",
" \"timestamps/.zattrs\": \"{\\\"interval\\\": 1, \\\"unit\\\": \\\"seconds\\\", \\\"units\\\": \\\"seconds\\\", \\\"_ARRAY_DIMENSIONS\\\": [\\\"timestamps\\\"]}\",\n",
" \"timestamps/.zarray\": \"{\\\"chunks\\\": [10], \\\"compressor\\\": null, \\\"dtype\\\": \\\"<f8\\\", \\\"fill_value\\\": null, \\\"filters\\\": null, \\\"order\\\": \\\"C\\\", \\\"shape\\\": [10], \\\"zarr_format\\\": 2}\",\n",
" \"timestamps/0\": [\n",
" \"example.nwb\",\n",
" 10048,\n",
" 80\n",
" ]\n",
" }\n",
"}\n"
]
}
],
"source": [
"# create a new RFS JSON that contains only datasets in acquisition/ElectricalSeries\n",
"new_refs = {k.replace(\"acquisition/ElectricalSeries/\", \"\"): v for k, v in rfs[\"refs\"].items() if k.startswith('acquisition/ElectricalSeries/')}\n",
"rfs_electrical_series_only = {\n",
" 'version': 1,\n",
" 'refs': {\n",
" '.zgroup': '{\"zarr_format\":2}',\n",
" }\n",
"}\n",
"rfs_electrical_series_only[\"refs\"].update(new_refs)\n",
"\n",
"adjust_array(rfs_electrical_series_only, \"data\", [\"timestamps\", \"electrodes\"])\n",
"adjust_array(rfs_electrical_series_only, \"timestamps\", [\"timestamps\"])\n",
"adjust_array(rfs_electrical_series_only, \"electrodes\", [\"electrodes\"])\n",
"print(json.dumps(rfs_electrical_series_only, indent=2))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "677c3999-92ac-49b3-b300-ebe03dd7a357",
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"def read_xarray_from_zarr_metadata(zm: dict, remote_protocol: str = \"file\"):\n",
" ds = xr.open_dataset(\n",
" \"reference://\",\n",
" engine=\"zarr\",\n",
" backend_kwargs={\n",
" \"storage_options\": dict(\n",
" fo=zm,\n",
" remote_protocol=remote_protocol,\n",
" ),\n",
" \"consolidated\": False\n",
" },\n",
" # decode_cf=False,\n",
" # mask_and_scale=False,\n",
" )\n",
" return ds\n",
"\n",
"dset = read_xarray_from_zarr_metadata(rfs_electrical_series_only)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "f98f557d-b082-4d50-b6dc-b6d69c2f0e84",
"metadata": {},
"outputs": [
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 520B\n",
"Dimensions: (timestamps: 10, electrodes: 5)\n",
"Coordinates:\n",
" * electrodes (electrodes) int64 40B 0 1 2 3 4\n",
" * timestamps (timestamps) timedelta64[ns] 80B 00:00:00 00:00:01 ... 00:00:09\n",
"Data variables:\n",
" data (timestamps, electrodes) float64 400B ...\n",
"Attributes:\n",
" comments: no comments\n",
" description: description\n",
" filtering: filtering\n",
" namespace: core\n",
" neurodata_type: ElectricalSeries\n",
" object_id: f7696ed3-2c80-4fb4-b284-5469e2c11a6c</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d03e5f1a-dc53-4340-a842-67060ced9b29' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d03e5f1a-dc53-4340-a842-67060ced9b29' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>timestamps</span>: 10</li><li><span class='xr-has-index'>electrodes</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f8538712-1a2d-4697-8b76-25c7fc8888cc' class='xr-section-summary-in' type='checkbox' checked><label for='section-f8538712-1a2d-4697-8b76-25c7fc8888cc' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>electrodes</span></div><div class='xr-var-dims'>(electrodes)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-c861e7cb-6b0b-4582-89da-948367379172' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c861e7cb-6b0b-4582-89da-948367379172' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d077244-9750-45b0-b509-6b7815850c19' class='xr-var-data-in' type='checkbox'><label for='data-0d077244-9750-45b0-b509-6b7815850c19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>the first and third electrodes</dd><dt><span>namespace :</span></dt><dd>hdmf-common</dd><dt><span>neurodata_type :</span></dt><dd>DynamicTableRegion</dd><dt><span>object_id :</span></dt><dd>65b98b43-3cfc-4774-bf05-ca342c9c624a</dd><dt><span>table :</span></dt><dd>{&#x27;_REFERENCE&#x27;: {&#x27;object_id&#x27;: &#x27;5307b610-47dc-43cb-b6b4-02dbfb98bcf0&#x27;, &#x27;path&#x27;: &#x27;/general/extracellular_ephys/electrodes&#x27;, &#x27;source&#x27;: &#x27;.&#x27;, &#x27;source_object_id&#x27;: &#x27;fe8ec11f-9737-4368-b87b-6fcf24c256f6&#x27;}}</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>timestamps</span></div><div class='xr-var-dims'>(timestamps)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00 00:00:01 ... 00:00:09</div><input id='attrs-e73c1e50-4bef-42e3-b075-b12f2598b0c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e73c1e50-4bef-42e3-b075-b12f2598b0c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66cfce00-4d8b-4c93-b6d9-6d4893e673e6' class='xr-var-data-in' type='checkbox'><label for='data-66cfce00-4d8b-4c93-b6d9-6d4893e673e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>interval :</span></dt><dd>1</dd><dt><span>unit :</span></dt><dd>seconds</dd></dl></div><div class='xr-var-data'><pre>array([ 0, 1000000000, 2000000000, 3000000000, 4000000000, 5000000000,\n",
" 6000000000, 7000000000, 8000000000, 9000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-82229590-eee1-4ca5-9809-8e88ff22eac4' class='xr-section-summary-in' type='checkbox' checked><label for='section-82229590-eee1-4ca5-9809-8e88ff22eac4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(timestamps, electrodes)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c5194ea7-35a1-4d43-b0e5-c98777146ad6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5194ea7-35a1-4d43-b0e5-c98777146ad6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-771d3ea4-40b2-4e36-a971-afe14c2e7668' class='xr-var-data-in' type='checkbox'><label for='data-771d3ea4-40b2-4e36-a971-afe14c2e7668' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>conversion :</span></dt><dd>10.0</dd><dt><span>offset :</span></dt><dd>1.0</dd><dt><span>resolution :</span></dt><dd>-1.0</dd><dt><span>unit :</span></dt><dd>volts</dd><dt><span>units :</span></dt><dd>volts</dd></dl></div><div class='xr-var-data'><pre>[50 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fadf812-e364-43c9-ad6f-129eb5d3f879' class='xr-section-summary-in' type='checkbox' ><label for='section-3fadf812-e364-43c9-ad6f-129eb5d3f879' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>electrodes</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ddfdb7d3-c007-4c12-9484-76c8bea16107' class='xr-index-data-in' type='checkbox'/><label for='index-ddfdb7d3-c007-4c12-9484-76c8bea16107' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;electrodes&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>timestamps</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-08c573a4-8276-4668-ad64-b447d27168b0' class='xr-index-data-in' type='checkbox'/><label for='index-08c573a4-8276-4668-ad64-b447d27168b0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(TimedeltaIndex([&#x27;0 days 00:00:00&#x27;, &#x27;0 days 00:00:01&#x27;, &#x27;0 days 00:00:02&#x27;,\n",
" &#x27;0 days 00:00:03&#x27;, &#x27;0 days 00:00:04&#x27;, &#x27;0 days 00:00:05&#x27;,\n",
" &#x27;0 days 00:00:06&#x27;, &#x27;0 days 00:00:07&#x27;, &#x27;0 days 00:00:08&#x27;,\n",
" &#x27;0 days 00:00:09&#x27;],\n",
" dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;timestamps&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-52585101-a6c2-471f-8ffd-01a7a6419e07' class='xr-section-summary-in' type='checkbox' checked><label for='section-52585101-a6c2-471f-8ffd-01a7a6419e07' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>comments :</span></dt><dd>no comments</dd><dt><span>description :</span></dt><dd>description</dd><dt><span>filtering :</span></dt><dd>filtering</dd><dt><span>namespace :</span></dt><dd>core</dd><dt><span>neurodata_type :</span></dt><dd>ElectricalSeries</dd><dt><span>object_id :</span></dt><dd>f7696ed3-2c80-4fb4-b284-5469e2c11a6c</dd></dl></div></li></ul></div></div>"
],
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"<xarray.Dataset> Size: 520B\n",
"Dimensions: (timestamps: 10, electrodes: 5)\n",
"Coordinates:\n",
" * electrodes (electrodes) int64 40B 0 1 2 3 4\n",
" * timestamps (timestamps) timedelta64[ns] 80B 00:00:00 00:00:01 ... 00:00:09\n",
"Data variables:\n",
" data (timestamps, electrodes) float64 400B ...\n",
"Attributes:\n",
" comments: no comments\n",
" description: description\n",
" filtering: filtering\n",
" namespace: core\n",
" neurodata_type: ElectricalSeries\n",
" object_id: f7696ed3-2c80-4fb4-b284-5469e2c11a6c"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
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"source": [
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},
{
"cell_type": "code",
"execution_count": 9,
"id": "055a06b8-c3db-4199-8732-97ecd98841aa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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" 'compressor': None,\n",
" 'filters': None,\n",
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]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
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"source": [
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{
"cell_type": "code",
"execution_count": 10,
"id": "e2ea94c2-c0d5-4e37-88b6-513441e4dd32",
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{
"data": {
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"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
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"source": [
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{
"cell_type": "code",
"execution_count": 11,
"id": "5029b467",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 1., 11., 21., 31., 41.],\n",
" [ 51., 61., 71., 81., 91.],\n",
" [101., 111., 121., 131., 141.],\n",
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]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"with NWBHDF5IO(nwb_file_path, \"r\") as io:\n",
" nwb = io.read()\n",
" es_data_read = nwb.acquisition[\"ElectricalSeries\"].get_data_in_units()\n",
"es_data_read"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "733f4aaf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
" [ True, True, True, True, True],\n",
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]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"dset.data.data == es_data_read"
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},
{
"cell_type": "code",
"execution_count": 13,
"id": "41ad0abf-8d88-48db-b4e4-d2ebd098314e",
"metadata": {},
"outputs": [
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"\n",
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".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
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"\n",
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"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
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"\n",
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"\n",
".xr-var-dims {\n",
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"\n",
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"\n",
".xr-index-preview {\n",
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"\n",
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".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
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" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
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".xr-var-data,\n",
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"\n",
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"\n",
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".xr-attrs dd {\n",
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"\n",
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"\n",
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"\n",
".xr-icon-database,\n",
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".xr-no-icon {\n",
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"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;electrodes&#x27; (electrodes: 5)&gt; Size: 40B\n",
"array([0, 1, 2, 3, 4])\n",
"Coordinates:\n",
" * electrodes (electrodes) int64 40B 0 1 2 3 4\n",
"Attributes:\n",
" description: the first and third electrodes\n",
" namespace: hdmf-common\n",
" neurodata_type: DynamicTableRegion\n",
" object_id: 65b98b43-3cfc-4774-bf05-ca342c9c624a\n",
" table: {&#x27;_REFERENCE&#x27;: {&#x27;object_id&#x27;: &#x27;5307b610-47dc-43cb-b6b4-02...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'electrodes'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>electrodes</span>: 5</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-57313175-5b6c-43e4-a4b0-cf8d5427c75e' class='xr-array-in' type='checkbox' checked><label for='section-57313175-5b6c-43e4-a4b0-cf8d5427c75e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0 1 2 3 4</span></div><div class='xr-array-data'><pre>array([0, 1, 2, 3, 4])</pre></div></div></li><li class='xr-section-item'><input id='section-4619128f-5643-44e9-9f76-990507889445' class='xr-section-summary-in' type='checkbox' checked><label for='section-4619128f-5643-44e9-9f76-990507889445' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>electrodes</span></div><div class='xr-var-dims'>(electrodes)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-7d1b1c24-e3d0-4398-b871-cffdcc1b38db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d1b1c24-e3d0-4398-b871-cffdcc1b38db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4050641-c3cd-4065-a73c-de83d000a04e' class='xr-var-data-in' type='checkbox'><label for='data-a4050641-c3cd-4065-a73c-de83d000a04e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>the first and third electrodes</dd><dt><span>namespace :</span></dt><dd>hdmf-common</dd><dt><span>neurodata_type :</span></dt><dd>DynamicTableRegion</dd><dt><span>object_id :</span></dt><dd>65b98b43-3cfc-4774-bf05-ca342c9c624a</dd><dt><span>table :</span></dt><dd>{&#x27;_REFERENCE&#x27;: {&#x27;object_id&#x27;: &#x27;5307b610-47dc-43cb-b6b4-02dbfb98bcf0&#x27;, &#x27;path&#x27;: &#x27;/general/extracellular_ephys/electrodes&#x27;, &#x27;source&#x27;: &#x27;.&#x27;, &#x27;source_object_id&#x27;: &#x27;fe8ec11f-9737-4368-b87b-6fcf24c256f6&#x27;}}</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd02c243-c6f4-42c0-8f55-6ea2a8c757ce' class='xr-section-summary-in' type='checkbox' ><label for='section-cd02c243-c6f4-42c0-8f55-6ea2a8c757ce' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>electrodes</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9933a363-bd7d-41fa-be9b-3de81e4d363c' class='xr-index-data-in' type='checkbox'/><label for='index-9933a363-bd7d-41fa-be9b-3de81e4d363c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;electrodes&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e5b4129-0f72-46cd-b012-d685be84416a' class='xr-section-summary-in' type='checkbox' checked><label for='section-2e5b4129-0f72-46cd-b012-d685be84416a' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>the first and third electrodes</dd><dt><span>namespace :</span></dt><dd>hdmf-common</dd><dt><span>neurodata_type :</span></dt><dd>DynamicTableRegion</dd><dt><span>object_id :</span></dt><dd>65b98b43-3cfc-4774-bf05-ca342c9c624a</dd><dt><span>table :</span></dt><dd>{&#x27;_REFERENCE&#x27;: {&#x27;object_id&#x27;: &#x27;5307b610-47dc-43cb-b6b4-02dbfb98bcf0&#x27;, &#x27;path&#x27;: &#x27;/general/extracellular_ephys/electrodes&#x27;, &#x27;source&#x27;: &#x27;.&#x27;, &#x27;source_object_id&#x27;: &#x27;fe8ec11f-9737-4368-b87b-6fcf24c256f6&#x27;}}</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'electrodes' (electrodes: 5)> Size: 40B\n",
"array([0, 1, 2, 3, 4])\n",
"Coordinates:\n",
" * electrodes (electrodes) int64 40B 0 1 2 3 4\n",
"Attributes:\n",
" description: the first and third electrodes\n",
" namespace: hdmf-common\n",
" neurodata_type: DynamicTableRegion\n",
" object_id: 65b98b43-3cfc-4774-bf05-ca342c9c624a\n",
" table: {'_REFERENCE': {'object_id': '5307b610-47dc-43cb-b6b4-02..."
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dset.electrodes"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "62fa724a-6a92-420c-82bc-3120d7a10c12",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 3, 4])"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import zarr\n",
"storage_opts = {\n",
" \"fo\": rfs_electrical_series_only,\n",
"}\n",
"z = zarr.open(\"reference://\", storage_options=storage_opts)\n",
"z[\"electrodes\"][:]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f7164d0f-d3c0-4cab-b3b5-631bc19fd30c",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
}
},
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"nbformat_minor": 5
}
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