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jhamman/sample-zarr-for-viz-discussion.ipynb

Created November 12, 2020 17:00
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sample-zarr-for-viz-discussion.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import zarr\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"ds = xr.open_rasterio(\n",
" 'https://carbonplan.blob.core.windows.net/carbonplan-data/raw/nftd/conus_foresttype/250m/raster.tif',\n",
" chunks={'x': 256, 'y': 256}).to_dataset(name='nftd')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (band: 1, x: 18493, y: 11658)\n",
"Coordinates:\n",
" * band (band) int64 1\n",
" * y (y) float64 3.177e+06 3.177e+06 3.177e+06 ... 2.634e+05 2.631e+05\n",
" * x (x) float64 -2.36e+06 -2.36e+06 -2.359e+06 ... 2.263e+06 2.263e+06\n",
"Data variables:\n",
" nftd (band, y, x) uint16 dask.array&lt;chunksize=(1, 256, 256), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><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-e75bf353-92b0-4a9b-b838-bc636c430a95' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e75bf353-92b0-4a9b-b838-bc636c430a95' 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'>band</span>: 1</li><li><span class='xr-has-index'>x</span>: 18493</li><li><span class='xr-has-index'>y</span>: 11658</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ff005929-b749-411b-9854-2b180be34812' class='xr-section-summary-in' type='checkbox' checked><label for='section-ff005929-b749-411b-9854-2b180be34812' class='xr-section-summary' >Coordinates: <span>(3)</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'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-894441c3-a8b3-4119-a6c1-66e1a4b17a2c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-894441c3-a8b3-4119-a6c1-66e1a4b17a2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb65fabd-2fab-4845-b81a-d76a18f220c7' class='xr-var-data-in' type='checkbox'><label for='data-fb65fabd-2fab-4845-b81a-d76a18f220c7' 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'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.177e+06 3.177e+06 ... 2.631e+05</div><input id='attrs-bf65eaa4-4ca9-4374-bbaa-d66244b09a53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf65eaa4-4ca9-4374-bbaa-d66244b09a53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c80c1a1-6c8e-481a-b569-135908016cdf' class='xr-var-data-in' type='checkbox'><label for='data-2c80c1a1-6c8e-481a-b569-135908016cdf' 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'></dl></div><div class='xr-var-data'><pre>array([3177375., 3177125., 3176875., ..., 263625., 263375., 263125.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.36e+06 -2.36e+06 ... 2.263e+06</div><input id='attrs-d8f53fff-065d-47f6-b9c5-9c24c34ff81c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8f53fff-065d-47f6-b9c5-9c24c34ff81c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1edd399f-288c-41ec-af18-50f126e4dc39' class='xr-var-data-in' type='checkbox'><label for='data-1edd399f-288c-41ec-af18-50f126e4dc39' 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'></dl></div><div class='xr-var-data'><pre>array([-2359875., -2359625., -2359375., ..., 2262625., 2262875., 2263125.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5871e1b1-e389-4be8-a89d-e2371d31435f' class='xr-section-summary-in' type='checkbox' checked><label for='section-5871e1b1-e389-4be8-a89d-e2371d31435f' 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>nftd</span></div><div class='xr-var-dims'>(band, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 256, 256), meta=np.ndarray&gt;</div><input id='attrs-baf7f586-2869-41a5-a82d-0730bc9ce124' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baf7f586-2869-41a5-a82d-0730bc9ce124' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63f7d459-da24-410f-843a-41a364bbd653' class='xr-var-data-in' type='checkbox'><label for='data-63f7d459-da24-410f-843a-41a364bbd653' 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>transform :</span></dt><dd>(250.00000000000003, 0.0, -2360000.0, 0.0, -250.00000000000003, 3177500.0)</dd><dt><span>crs :</span></dt><dd>+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=23 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD27 +units=m +no_defs=True</dd><dt><span>res :</span></dt><dd>(250.00000000000003, 250.00000000000003)</dd><dt><span>is_tiled :</span></dt><dd>1</dd><dt><span>nodatavals :</span></dt><dd>(nan,)</dd><dt><span>scales :</span></dt><dd>(1.0,)</dd><dt><span>offsets :</span></dt><dd>(0.0,)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Layer_1&#x27;,)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>OVR_RESAMPLING_ALG :</span></dt><dd>NEAREST</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
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" <thead>\n",
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr><th> Bytes </th><td> 431.18 MB </td> <td> 131.07 kB </td></tr>\n",
" <tr><th> Shape </th><td> (1, 11658, 18493) </td> <td> (1, 256, 256) </td></tr>\n",
" <tr><th> Count </th><td> 3359 Tasks </td><td> 3358 Chunks </td></tr>\n",
" <tr><th> Type </th><td> uint16 </td><td> numpy.ndarray </td></tr>\n",
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],
"text/plain": [
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"Dimensions: (band: 1, x: 18493, y: 11658)\n",
"Coordinates:\n",
" * band (band) int64 1\n",
" * y (y) float64 3.177e+06 3.177e+06 3.177e+06 ... 2.634e+05 2.631e+05\n",
" * x (x) float64 -2.36e+06 -2.36e+06 -2.359e+06 ... 2.263e+06 2.263e+06\n",
"Data variables:\n",
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]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.backends.zarr.ZarrStore at 0x7f3cbd9234d0>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"store = zarr.storage.ABSStore(\n",
" 'carbonplan-share',\n",
" prefix='zarr-demo',\n",
" account_name=\"carbonplan\",\n",
" account_key=os.environ[\"BLOB_ACCOUNT_KEY\"],\n",
")\n",
"\n",
"ds.to_zarr(store, mode='w', encoding={k: {'compressor': None} for k in ds.variables}, consolidated=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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" \"metadata\": {\n",
" \".zattrs\": {},\n",
" \".zgroup\": {\n",
" \"zarr_format\": 2\n",
" },\n",
" \"band/.zarray\": {\n",
" \"chunks\": [\n",
" 1\n",
" ],\n",
" \"compressor\": null,\n",
" \"dtype\": \"<i8\",\n",
" \"fill_value\": null,\n",
" \"filters\": null,\n",
" \"order\": \"C\",\n",
" \"shape\": [\n",
" 1\n",
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" \"zarr_format\": 2\n",
" },\n",
" \"band/.zattrs\": {\n",
" \"_ARRAY_DIMENSIONS\": [\n",
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" },\n",
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" \"chunks\": [\n",
" 1,\n",
" 256,\n",
" 256\n",
" ],\n",
" \"compressor\": null,\n",
" \"dtype\": \"<u2\",\n",
" \"fill_value\": null,\n",
" \"filters\": null,\n",
" \"order\": \"C\",\n",
" \"shape\": [\n",
" 1,\n",
" 11658,\n",
" 18493\n",
" ],\n",
" \"zarr_format\": 2\n",
" },\n",
" \"nftd/.zattrs\": {\n",
" \"AREA_OR_POINT\": \"Area\",\n",
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" \"_ARRAY_DIMENSIONS\": [\n",
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" \"Layer_1\"\n",
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" \"is_tiled\": 1,\n",
" \"nodatavals\": [\n",
" NaN\n",
" ],\n",
" \"offsets\": [\n",
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" \"res\": [\n",
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" -250.00000000000003,\n",
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" ]\n",
" },\n",
" \"x/.zarray\": {\n",
" \"chunks\": [\n",
" 18493\n",
" ],\n",
" \"compressor\": null,\n",
" \"dtype\": \"<f8\",\n",
" \"fill_value\": \"NaN\",\n",
" \"filters\": null,\n",
" \"order\": \"C\",\n",
" \"shape\": [\n",
" 18493\n",
" ],\n",
" \"zarr_format\": 2\n",
" },\n",
" \"x/.zattrs\": {\n",
" \"_ARRAY_DIMENSIONS\": [\n",
" \"x\"\n",
" ]\n",
" },\n",
" \"y/.zarray\": {\n",
" \"chunks\": [\n",
" 11658\n",
" ],\n",
" \"compressor\": null,\n",
" \"dtype\": \"<f8\",\n",
" \"fill_value\": \"NaN\",\n",
" \"filters\": null,\n",
" \"order\": \"C\",\n",
" \"shape\": [\n",
" 11658\n",
" ],\n",
" \"zarr_format\": 2\n",
" },\n",
" \"y/.zattrs\": {\n",
" \"_ARRAY_DIMENSIONS\": [\n",
" \"y\"\n",
" ]\n",
" }\n",
" },\n",
" \"zarr_consolidated_format\": 1\n",
"}\n"
]
}
],
"source": [
"print(store['.zmetadata'].decode())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.8"
}
},
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}
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