sparse_mat_in_xarray.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Xarray sparse matrix example\n",
    "\n",
    "This is an example of add a sparse matrix variable to an Xarray. This can be done via the `sparse` module. Not this module is a wrapper of `scipy.sparse`. Inspired by the [unit test of Xarray](https://github.com/pydata/xarray/blob/main/xarray/tests/test_sparse.py).\n",
    "\n",
    "Although `xarray` support support a data variable, it does not support writing it into Zarr. So the sparse matrix need to be converted into a dense array when writing.\n",
    "\n",
    "This example is considered useful if we need to host several sparse arrays simutanouesly in memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "%load_ext memory_profiler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare the test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set data cube dimension\n",
    "n_azimuth=2000\n",
    "n_range=1000\n",
    "n_time=4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7fb0ef8d50f0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x300 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# signal\n",
    "signal = np.zeros((n_time,n_azimuth,n_range))\n",
    "signal[0,:,:] = np.tile(np.linspace(0,np.pi,num=n_range), (n_azimuth,1))\n",
    "for i in range(1,n_time):\n",
    "    signal[i,:,:] = signal[0,:,:]+i\n",
    "\n",
    "# noise\n",
    "np.random.seed(0)\n",
    "noise = np.random.rand(n_time,n_azimuth,n_range)*2*np.pi\n",
    "\n",
    "# obs\n",
    "obs = signal + noise\n",
    "\n",
    "# visualize\n",
    "fig, ax = plt.subplots(1,n_time)\n",
    "fig.set_size_inches(9,3)\n",
    "for i in range(n_time):\n",
    "    im = ax[i].imshow(obs[i], vmin=0, vmax=12)\n",
    "plt.colorbar(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.Dataset(\n",
    "    data_vars=dict(\n",
    "        obs=([\"time\", \"azimuth\", \"range\"], obs),\n",
    "    ),\n",
    "    coords=dict(\n",
    "        azimuth=np.arange(n_azimuth),\n",
    "        range=np.arange(n_range),\n",
    "        time=np.arange(n_time),\n",
    "    ),\n",
    ")\n",
    "\n",
    "ds_pointset = ds.stack(points=('azimuth', 'range'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a subsetted pointset\n",
    "mask = ds.obs.std(axis=0)<0.5\n",
    "ds_masked = ds.where(mask)\n",
    "pointset = ds_masked.stack(points=('azimuth', 'range'))\n",
    "pointset = pointset.dropna('points', subset=['obs'])\n",
    "pointset['obs1'] = pointset.obs+100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Update the original DataSet with a sparse array\n",
    "\n",
    "Original DataSet: `ds_pointset`.\n",
    "\n",
    "Processed DataSet: `pointset`.\n",
    "\n",
    "There is a new variable `obs1` in `pointset`. We would like to save this variable as a sparse matrix first. Then add this sparse matrix as a new variable to `ds_pointset`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 4, points: 2000000)&gt;\n",
       "&lt;COO: shape=(4, 2000000), dtype=float64, nnz=139540, fill_value=0.0&gt;\n",
       "Coordinates:\n",
       "  * time     (time) int64 0 1 2 3\n",
       "  * points   (points) object MultiIndex\n",
       "  * azimuth  (points) int64 0 0 0 0 0 0 0 ... 1999 1999 1999 1999 1999 1999 1999\n",
       "  * range    (points) int64 0 1 2 3 4 5 6 7 ... 992 993 994 995 996 997 998 999</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'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4</li><li><span class='xr-has-index'>points</span>: 2000000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1812c4c5-3bf2-4f45-a27e-dbdfa6ed5669' class='xr-array-in' type='checkbox' checked><label for='section-1812c4c5-3bf2-4f45-a27e-dbdfa6ed5669' 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>&lt;COO: nnz=139540, fill_value=0.0&gt;</span></div><div class='xr-array-data'><table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">coo</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(4, 2000000)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">139540</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.0174425</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">3.2M</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">0.1</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-3535bc6d-2677-43cc-af41-1342b61b2518' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3535bc6d-2677-43cc-af41-1342b61b2518' class='xr-section-summary' >Coordinates: <span>(4)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-c0899de9-441a-49dd-b2ae-b984f8bf06fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0899de9-441a-49dd-b2ae-b984f8bf06fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4bf4aa7-053f-4ecf-9b03-f1bbdfc002c5' class='xr-var-data-in' type='checkbox'><label for='data-c4bf4aa7-053f-4ecf-9b03-f1bbdfc002c5' 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([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>points</span></div><div class='xr-var-dims'>(points)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-56590a68-9dd8-4295-8dfc-a285b8b29f4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56590a68-9dd8-4295-8dfc-a285b8b29f4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d8609fa-c32b-4822-983b-ace51b538fc6' class='xr-var-data-in' type='checkbox'><label for='data-7d8609fa-c32b-4822-983b-ace51b538fc6' 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([(0, 0), (0, 1), (0, 2), ..., (1999, 997), (1999, 998), (1999, 999)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>azimuth</span></div><div class='xr-var-dims'>(points)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 ... 1999 1999 1999 1999</div><input id='attrs-3978a2ed-a69d-4886-8358-9ec964a3f8e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3978a2ed-a69d-4886-8358-9ec964a3f8e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3a71e93-00ec-48d7-ad55-d66f9712b9fd' class='xr-var-data-in' type='checkbox'><label for='data-b3a71e93-00ec-48d7-ad55-d66f9712b9fd' 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([   0,    0,    0, ..., 1999, 1999, 1999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(points)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-ea2ffd5b-d616-4156-9c96-5b974c457d41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea2ffd5b-d616-4156-9c96-5b974c457d41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541b2b73-f446-475c-a868-81314c19da73' class='xr-var-data-in' type='checkbox'><label for='data-541b2b73-f446-475c-a868-81314c19da73' 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([  0,   1,   2, ..., 997, 998, 999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-32e753d8-41e4-4bf6-a429-5a8813773562' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-32e753d8-41e4-4bf6-a429-5a8813773562' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 4, points: 2000000)>\n",
       "<COO: shape=(4, 2000000), dtype=float64, nnz=139540, fill_value=0.0>\n",
       "Coordinates:\n",
       "  * time     (time) int64 0 1 2 3\n",
       "  * points   (points) object MultiIndex\n",
       "  * azimuth  (points) int64 0 0 0 0 0 0 0 ... 1999 1999 1999 1999 1999 1999 1999\n",
       "  * range    (points) int64 0 1 2 3 4 5 6 7 ... 992 993 994 995 996 997 998 999"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sparse\n",
    "\n",
    "da_dense = xr.DataArray(coords=ds_pointset.coords)\n",
    "da_dense.loc[dict(points = pointset.obs1.points)] = pointset.obs1.data\n",
    "\n",
    "\n",
    "dense = da_dense.data\n",
    "dense[np.where(np.isnan(dense))] = 0\n",
    "spm = sparse.COO.from_numpy(da_dense.data, fill_value=dense[0,0])\n",
    "\n",
    "da_sparse= xr.DataArray(data=sparse.COO(da_dense.data), coords=ds_pointset.coords) \n",
    "\n",
    "da_sparse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peak memory: 754.65 MiB, increment: -6.39 MiB\n"
     ]
    },
    {
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       ".xr-icon-database,\n",
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       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 4, azimuth: 2000, range: 1000, points: 2000000)\n",
       "Coordinates:\n",
       "  * azimuth  (azimuth) int64 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n",
       "  * range    (range) int64 0 1 2 3 4 5 6 7 8 ... 992 993 994 995 996 997 998 999\n",
       "  * time     (time) int64 0 1 2 3\n",
       "Dimensions without coordinates: points\n",
       "Data variables:\n",
       "    obs      (time, azimuth, range) float64 3.448 4.497 3.794 ... 8.004 7.702\n",
       "    obs1     (time, points) float64 &lt;COO: nnz=139540, fill_value=0.0&gt;</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-a2b5233e-a147-4ec0-b987-6af69f8e648b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a2b5233e-a147-4ec0-b987-6af69f8e648b' 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'>time</span>: 4</li><li><span class='xr-has-index'>azimuth</span>: 2000</li><li><span class='xr-has-index'>range</span>: 1000</li><li><span>points</span>: 2000000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-51ef3bab-a5fd-4dce-a70a-252e459bf085' class='xr-section-summary-in' type='checkbox'  checked><label for='section-51ef3bab-a5fd-4dce-a70a-252e459bf085' 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'>azimuth</span></div><div class='xr-var-dims'>(azimuth)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1996 1997 1998 1999</div><input id='attrs-105c54c4-4539-4afb-90d1-98d13a1077e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-105c54c4-4539-4afb-90d1-98d13a1077e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dc28258-8c99-41c7-8f63-1e38e8c1949b' class='xr-var-data-in' type='checkbox'><label for='data-7dc28258-8c99-41c7-8f63-1e38e8c1949b' 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([   0,    1,    2, ..., 1997, 1998, 1999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-46029a91-8d94-4d52-9eb4-19548fcbf32f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46029a91-8d94-4d52-9eb4-19548fcbf32f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58149cef-ae10-46bd-b212-5d2590afe15f' class='xr-var-data-in' type='checkbox'><label for='data-58149cef-ae10-46bd-b212-5d2590afe15f' 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([  0,   1,   2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-d41dcc69-0db0-4916-b930-49e92ff53202' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d41dcc69-0db0-4916-b930-49e92ff53202' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3242243-dd5e-4a63-bae2-e28e54fda74c' class='xr-var-data-in' type='checkbox'><label for='data-b3242243-dd5e-4a63-bae2-e28e54fda74c' 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([0, 1, 2, 3])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95148c42-29be-4af8-a9bd-4fbfbec6ac47' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95148c42-29be-4af8-a9bd-4fbfbec6ac47' class='xr-section-summary' >Data variables: <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>obs</span></div><div class='xr-var-dims'>(time, azimuth, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.448 4.497 3.794 ... 8.004 7.702</div><input id='attrs-ff8e2bc6-7ade-4c86-87fe-58edb27e32c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff8e2bc6-7ade-4c86-87fe-58edb27e32c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a9661ed-dacb-411b-946e-fcda2a16a6a9' class='xr-var-data-in' type='checkbox'><label for='data-0a9661ed-dacb-411b-946e-fcda2a16a6a9' 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([[[ 3.44829694,  4.49681206,  3.79356346, ...,  9.03151981,\n",
       "          4.57507657,  7.39619594],\n",
       "        [ 3.72517661,  0.0663768 ,  2.99599364, ...,  6.1519095 ,\n",
       "          7.18396497,  6.29432622],\n",
       "        [ 5.09892093,  2.99446864,  3.2933755 , ...,  5.16862808,\n",
       "          8.25010202,  7.52348846],\n",
       "        ...,\n",
       "        [ 3.34125502,  4.38098714,  5.72962509, ...,  4.82854708,\n",
       "          8.25130125,  3.39594384],\n",
       "        [ 0.25450378,  4.6649426 ,  0.55336375, ...,  4.02672578,\n",
       "          6.53092243,  7.80392371],\n",
       "        [ 0.24206801,  1.64351812,  5.09516528, ...,  8.96835215,\n",
       "          8.74112606,  6.23210474]],\n",
       "\n",
       "       [[ 5.9606289 ,  2.88193543,  6.83138   , ...,  4.39316838,\n",
       "          6.47534806,  8.24814829],\n",
       "        [ 2.66409652,  1.63333252,  2.73078366, ...,  8.61417664,\n",
       "         10.00989683,  8.57412305],\n",
       "        [ 2.6962788 ,  6.58118629,  2.18403771, ...,  8.256945  ,\n",
       "          7.52997796,  4.8261986 ],\n",
       "...\n",
       "        [ 2.36772239,  4.77388107,  8.2387385 , ..., 10.14389545,\n",
       "          5.67037242,  9.7460928 ],\n",
       "        [ 8.26045325,  7.57971541,  5.83871304, ...,  5.34465831,\n",
       "          7.05949158,  6.41340905],\n",
       "        [ 6.40710549,  4.48263662,  7.32040137, ...,  8.00446189,\n",
       "         11.27714477,  5.55382812]],\n",
       "\n",
       "       [[ 6.61671439,  7.55560867,  5.91500093, ...,  9.60518165,\n",
       "          9.71445774,  8.33007131],\n",
       "        [ 7.93328611,  3.9580006 ,  7.00775525, ..., 12.01567133,\n",
       "          6.93834349, 10.48155186],\n",
       "        [ 5.5990042 ,  7.38089291,  6.88236053, ...,  6.63391244,\n",
       "         10.73105173,  7.24717932],\n",
       "        ...,\n",
       "        [ 5.7067881 ,  6.46129211,  4.71339131, ..., 11.25679596,\n",
       "          9.01801673,  9.5019992 ],\n",
       "        [ 4.31148401,  8.61282742,  8.18592285, ...,  6.46978996,\n",
       "          6.26953643, 11.82201566],\n",
       "        [ 8.17263888,  4.14390718,  8.8129008 , ..., 12.27938359,\n",
       "          8.00414491,  7.70171342]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obs1</span></div><div class='xr-var-dims'>(time, points)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>&lt;COO: nnz=139540, fill_value=0.0&gt;</div><input id='attrs-7bc278d2-0483-4fc1-9889-f76f29f8c4f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7bc278d2-0483-4fc1-9889-f76f29f8c4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51718007-5102-41ec-88c9-0926bb72ab72' class='xr-var-data-in' type='checkbox'><label for='data-51718007-5102-41ec-88c9-0926bb72ab72' 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'><table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">coo</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(4, 2000000)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">139540</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.0174425</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">3.2M</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">0.1</td></tr></tbody></table></div></li></ul></div></li><li class='xr-section-item'><input id='section-993b99d6-9558-4a08-91f9-06f6e4038319' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-993b99d6-9558-4a08-91f9-06f6e4038319' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 4, azimuth: 2000, range: 1000, points: 2000000)\n",
       "Coordinates:\n",
       "  * azimuth  (azimuth) int64 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n",
       "  * range    (range) int64 0 1 2 3 4 5 6 7 8 ... 992 993 994 995 996 997 998 999\n",
       "  * time     (time) int64 0 1 2 3\n",
       "Dimensions without coordinates: points\n",
       "Data variables:\n",
       "    obs      (time, azimuth, range) float64 3.448 4.497 3.794 ... 8.004 7.702\n",
       "    obs1     (time, points) float64 <COO: nnz=139540, fill_value=0.0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%memit\n",
    "ds = ds.assign(obs1=da_sparse)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peak memory: 754.84 MiB, increment: 0.18 MiB\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "SparseArray.astype() got an unexpected keyword argument 'order'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m/mnt/c/Users/OuKu/Developments/MobyLe/JupyterNB_examples/sparse_mat_in_xarray.ipynb Cell 9\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      <a href='vscode-notebook-cell://wsl%2Bubuntu-18.04/mnt/c/Users/OuKu/Developments/MobyLe/JupyterNB_examples/sparse_mat_in_xarray.ipynb#X35sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0'>1</a>\u001b[0m get_ipython()\u001b[39m.\u001b[39mrun_line_magic(\u001b[39m'\u001b[39m\u001b[39mmemit\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m      <a href='vscode-notebook-cell://wsl%2Bubuntu-18.04/mnt/c/Users/OuKu/Developments/MobyLe/JupyterNB_examples/sparse_mat_in_xarray.ipynb#X35sdnNjb2RlLXJlbW90ZQ%3D%3D?line=1'>2</a>\u001b[0m \u001b[39m# Update zarr\u001b[39;00m\n\u001b[0;32m----> <a href='vscode-notebook-cell://wsl%2Bubuntu-18.04/mnt/c/Users/OuKu/Developments/MobyLe/JupyterNB_examples/sparse_mat_in_xarray.ipynb#X35sdnNjb2RlLXJlbW90ZQ%3D%3D?line=2'>3</a>\u001b[0m ds\u001b[39m.\u001b[39;49mto_zarr(\u001b[39m\"\u001b[39;49m\u001b[39mdatabase.zarr\u001b[39;49m\u001b[39m\"\u001b[39;49m, mode\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39ma\u001b[39;49m\u001b[39m'\u001b[39;49m)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/core/dataset.py:2060\u001b[0m, in \u001b[0;36mDataset.to_zarr\u001b[0;34m(self, store, chunk_store, mode, synchronizer, group, encoding, compute, consolidated, append_dim, region, safe_chunks, storage_options)\u001b[0m\n\u001b[1;32m   1950\u001b[0m \u001b[39m\"\"\"Write dataset contents to a zarr group.\u001b[39;00m\n\u001b[1;32m   1951\u001b[0m \n\u001b[1;32m   1952\u001b[0m \u001b[39mZarr chunks are determined in the following way:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2056\u001b[0m \u001b[39m    The I/O user guide, with more details and examples.\u001b[39;00m\n\u001b[1;32m   2057\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2058\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39m.\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mbackends\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mapi\u001b[39;00m \u001b[39mimport\u001b[39;00m to_zarr\n\u001b[0;32m-> 2060\u001b[0m \u001b[39mreturn\u001b[39;00m to_zarr(  \u001b[39m# type: ignore\u001b[39;49;00m\n\u001b[1;32m   2061\u001b[0m     \u001b[39mself\u001b[39;49m,\n\u001b[1;32m   2062\u001b[0m     store\u001b[39m=\u001b[39;49mstore,\n\u001b[1;32m   2063\u001b[0m     chunk_store\u001b[39m=\u001b[39;49mchunk_store,\n\u001b[1;32m   2064\u001b[0m     storage_options\u001b[39m=\u001b[39;49mstorage_options,\n\u001b[1;32m   2065\u001b[0m     mode\u001b[39m=\u001b[39;49mmode,\n\u001b[1;32m   2066\u001b[0m     synchronizer\u001b[39m=\u001b[39;49msynchronizer,\n\u001b[1;32m   2067\u001b[0m     group\u001b[39m=\u001b[39;49mgroup,\n\u001b[1;32m   2068\u001b[0m     encoding\u001b[39m=\u001b[39;49mencoding,\n\u001b[1;32m   2069\u001b[0m     compute\u001b[39m=\u001b[39;49mcompute,\n\u001b[1;32m   2070\u001b[0m     consolidated\u001b[39m=\u001b[39;49mconsolidated,\n\u001b[1;32m   2071\u001b[0m     append_dim\u001b[39m=\u001b[39;49mappend_dim,\n\u001b[1;32m   2072\u001b[0m     region\u001b[39m=\u001b[39;49mregion,\n\u001b[1;32m   2073\u001b[0m     safe_chunks\u001b[39m=\u001b[39;49msafe_chunks,\n\u001b[1;32m   2074\u001b[0m )\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/backends/api.py:1637\u001b[0m, in \u001b[0;36mto_zarr\u001b[0;34m(dataset, store, chunk_store, mode, synchronizer, group, encoding, compute, consolidated, append_dim, region, safe_chunks, storage_options)\u001b[0m\n\u001b[1;32m   1635\u001b[0m writer \u001b[39m=\u001b[39m ArrayWriter()\n\u001b[1;32m   1636\u001b[0m \u001b[39m# TODO: figure out how to properly handle unlimited_dims\u001b[39;00m\n\u001b[0;32m-> 1637\u001b[0m dump_to_store(dataset, zstore, writer, encoding\u001b[39m=\u001b[39;49mencoding)\n\u001b[1;32m   1638\u001b[0m writes \u001b[39m=\u001b[39m writer\u001b[39m.\u001b[39msync(compute\u001b[39m=\u001b[39mcompute)\n\u001b[1;32m   1640\u001b[0m \u001b[39mif\u001b[39;00m compute:\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/backends/api.py:1257\u001b[0m, in \u001b[0;36mdump_to_store\u001b[0;34m(dataset, store, writer, encoder, encoding, unlimited_dims)\u001b[0m\n\u001b[1;32m   1254\u001b[0m \u001b[39mif\u001b[39;00m encoder:\n\u001b[1;32m   1255\u001b[0m     variables, attrs \u001b[39m=\u001b[39m encoder(variables, attrs)\n\u001b[0;32m-> 1257\u001b[0m store\u001b[39m.\u001b[39;49mstore(variables, attrs, check_encoding, writer, unlimited_dims\u001b[39m=\u001b[39;49munlimited_dims)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/backends/zarr.py:571\u001b[0m, in \u001b[0;36mZarrStore.store\u001b[0;34m(self, variables, attributes, check_encoding_set, writer, unlimited_dims)\u001b[0m\n\u001b[1;32m    568\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mset_attributes(attributes)\n\u001b[1;32m    569\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mset_dimensions(variables_encoded, unlimited_dims\u001b[39m=\u001b[39munlimited_dims)\n\u001b[0;32m--> 571\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mset_variables(\n\u001b[1;32m    572\u001b[0m     variables_encoded, check_encoding_set, writer, unlimited_dims\u001b[39m=\u001b[39;49munlimited_dims\n\u001b[1;32m    573\u001b[0m )\n\u001b[1;32m    574\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_consolidate_on_close:\n\u001b[1;32m    575\u001b[0m     zarr\u001b[39m.\u001b[39mconsolidate_metadata(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mzarr_group\u001b[39m.\u001b[39mstore)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/backends/zarr.py:650\u001b[0m, in \u001b[0;36mZarrStore.set_variables\u001b[0;34m(self, variables, check_encoding_set, writer, unlimited_dims)\u001b[0m\n\u001b[1;32m    647\u001b[0m     zarr_array\u001b[39m.\u001b[39mresize(new_shape)\n\u001b[1;32m    649\u001b[0m region \u001b[39m=\u001b[39m \u001b[39mtuple\u001b[39m(write_region[dim] \u001b[39mfor\u001b[39;00m dim \u001b[39min\u001b[39;00m dims)\n\u001b[0;32m--> 650\u001b[0m writer\u001b[39m.\u001b[39;49madd(v\u001b[39m.\u001b[39;49mdata, zarr_array, region)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/xarray/backends/common.py:156\u001b[0m, in \u001b[0;36mArrayWriter.add\u001b[0;34m(self, source, target, region)\u001b[0m\n\u001b[1;32m    154\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    155\u001b[0m     \u001b[39mif\u001b[39;00m region:\n\u001b[0;32m--> 156\u001b[0m         target[region] \u001b[39m=\u001b[39m source\n\u001b[1;32m    157\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    158\u001b[0m         target[\u001b[39m.\u001b[39m\u001b[39m.\u001b[39m\u001b[39m.\u001b[39m] \u001b[39m=\u001b[39m source\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:1353\u001b[0m, in \u001b[0;36mArray.__setitem__\u001b[0;34m(self, selection, value)\u001b[0m\n\u001b[1;32m   1351\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mvindex[selection] \u001b[39m=\u001b[39m value\n\u001b[1;32m   1352\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1353\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mset_basic_selection(pure_selection, value, fields\u001b[39m=\u001b[39;49mfields)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:1448\u001b[0m, in \u001b[0;36mArray.set_basic_selection\u001b[0;34m(self, selection, value, fields)\u001b[0m\n\u001b[1;32m   1446\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_set_basic_selection_zd(selection, value, fields\u001b[39m=\u001b[39mfields)\n\u001b[1;32m   1447\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1448\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_set_basic_selection_nd(selection, value, fields\u001b[39m=\u001b[39;49mfields)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:1748\u001b[0m, in \u001b[0;36mArray._set_basic_selection_nd\u001b[0;34m(self, selection, value, fields)\u001b[0m\n\u001b[1;32m   1742\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_set_basic_selection_nd\u001b[39m(\u001b[39mself\u001b[39m, selection, value, fields\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[1;32m   1743\u001b[0m     \u001b[39m# implementation of __setitem__ for array with at least one dimension\u001b[39;00m\n\u001b[1;32m   1744\u001b[0m \n\u001b[1;32m   1745\u001b[0m     \u001b[39m# setup indexer\u001b[39;00m\n\u001b[1;32m   1746\u001b[0m     indexer \u001b[39m=\u001b[39m BasicIndexer(selection, \u001b[39mself\u001b[39m)\n\u001b[0;32m-> 1748\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_set_selection(indexer, value, fields\u001b[39m=\u001b[39;49mfields)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:1800\u001b[0m, in \u001b[0;36mArray._set_selection\u001b[0;34m(self, indexer, value, fields)\u001b[0m\n\u001b[1;32m   1797\u001b[0m                 chunk_value \u001b[39m=\u001b[39m chunk_value[item]\n\u001b[1;32m   1799\u001b[0m         \u001b[39m# put data\u001b[39;00m\n\u001b[0;32m-> 1800\u001b[0m         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_chunk_setitem(chunk_coords, chunk_selection, chunk_value, fields\u001b[39m=\u001b[39;49mfields)\n\u001b[1;32m   1801\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   1802\u001b[0m     lchunk_coords, lchunk_selection, lout_selection \u001b[39m=\u001b[39m \u001b[39mzip\u001b[39m(\u001b[39m*\u001b[39mindexer)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:2062\u001b[0m, in \u001b[0;36mArray._chunk_setitem\u001b[0;34m(self, chunk_coords, chunk_selection, value, fields)\u001b[0m\n\u001b[1;32m   2059\u001b[0m     lock \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_synchronizer[ckey]\n\u001b[1;32m   2061\u001b[0m \u001b[39mwith\u001b[39;00m lock:\n\u001b[0;32m-> 2062\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_chunk_setitem_nosync(chunk_coords, chunk_selection, value,\n\u001b[1;32m   2063\u001b[0m                                fields\u001b[39m=\u001b[39;49mfields)\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:2067\u001b[0m, in \u001b[0;36mArray._chunk_setitem_nosync\u001b[0;34m(self, chunk_coords, chunk_selection, value, fields)\u001b[0m\n\u001b[1;32m   2065\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_chunk_setitem_nosync\u001b[39m(\u001b[39mself\u001b[39m, chunk_coords, chunk_selection, value, fields\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[1;32m   2066\u001b[0m     ckey \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_chunk_key(chunk_coords)\n\u001b[0;32m-> 2067\u001b[0m     cdata \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_process_for_setitem(ckey, chunk_selection, value, fields\u001b[39m=\u001b[39;49mfields)\n\u001b[1;32m   2069\u001b[0m     \u001b[39m# attempt to delete chunk if it only contains the fill value\u001b[39;00m\n\u001b[1;32m   2070\u001b[0m     \u001b[39mif\u001b[39;00m (\u001b[39mnot\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mwrite_empty_chunks) \u001b[39mand\u001b[39;00m all_equal(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfill_value, cdata):\n",
      "File \u001b[0;32m~/miniconda3/envs/mobyle/lib/python3.10/site-packages/zarr/core.py:2091\u001b[0m, in \u001b[0;36mArray._process_for_setitem\u001b[0;34m(self, ckey, chunk_selection, value, fields)\u001b[0m\n\u001b[1;32m   2086\u001b[0m         chunk\u001b[39m.\u001b[39mfill(value)\n\u001b[1;32m   2088\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   2089\u001b[0m \n\u001b[1;32m   2090\u001b[0m         \u001b[39m# ensure array is contiguous\u001b[39;00m\n\u001b[0;32m-> 2091\u001b[0m         chunk \u001b[39m=\u001b[39m value\u001b[39m.\u001b[39;49mastype(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_dtype, order\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_order, copy\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n\u001b[1;32m   2093\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   2094\u001b[0m     \u001b[39m# partially replace the contents of this chunk\u001b[39;00m\n\u001b[1;32m   2096\u001b[0m     \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m   2097\u001b[0m \n\u001b[1;32m   2098\u001b[0m         \u001b[39m# obtain compressed data for chunk\u001b[39;00m\n",
      "\u001b[0;31mTypeError\u001b[0m: SparseArray.astype() got an unexpected keyword argument 'order'"
     ]
    }
   ],
   "source": [
    "%memit\n",
    "# The storage in Zarr has not been supported yet\n",
    "ds.to_zarr(\"database.zarr\", mode='a')"
   ]
  }
 ],
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