margulis_xarray.ipynb

{
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   "source": [
    "import xarray as xr\n",
    "import rioxarray as rxr\n",
    "import numpy as np\n",
    "import hvplot.xarray  # noqa\n",
    "from matplotlib import pyplot as plt"
   ]
  },
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (band: 1, x: 5701, y: 6601)\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -123.3 -123.3 -123.3 ... -117.6 -117.6 -117.6\n",
       "  * y            (y) float64 42.0 42.0 42.0 42.0 42.0 ... 35.4 35.4 35.4 35.4\n",
       "    spatial_ref  int64 0\n",
       "Data variables:\n",
       "    band_data    (band, y, x) float32 nan nan nan nan nan ... nan nan nan nan</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-190c8702-1148-4409-b59b-534f90cf5495' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-190c8702-1148-4409-b59b-534f90cf5495' 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>: 5701</li><li><span class='xr-has-index'>y</span>: 6601</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6beb5fbc-b78f-42dc-a058-2a871ba3df40' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6beb5fbc-b78f-42dc-a058-2a871ba3df40' 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'>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-0c0e0c95-b65d-420a-9be0-51e875114d31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c0e0c95-b65d-420a-9be0-51e875114d31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de48fca5-a9f4-4fb4-989e-9aee3c64e0f3' class='xr-var-data-in' type='checkbox'><label for='data-de48fca5-a9f4-4fb4-989e-9aee3c64e0f3' 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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-123.3 -123.3 ... -117.6 -117.6</div><input id='attrs-9676d709-c4c6-4b21-a470-fa6217693cc6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9676d709-c4c6-4b21-a470-fa6217693cc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb28e7da-e89b-43f4-a549-a0ba0a42bc01' class='xr-var-data-in' type='checkbox'><label for='data-cb28e7da-e89b-43f4-a549-a0ba0a42bc01' 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([-123.2995, -123.2985, -123.2975, ..., -117.6025, -117.6015, -117.6005])</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'>42.0 42.0 42.0 ... 35.4 35.4 35.4</div><input id='attrs-0fb6c29a-00bc-48f3-a501-22b09f8f23d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0fb6c29a-00bc-48f3-a501-22b09f8f23d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b971ae36-e90f-4775-88d4-f63e453f4835' class='xr-var-data-in' type='checkbox'><label for='data-b971ae36-e90f-4775-88d4-f63e453f4835' 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([41.9995, 41.9985, 41.9975, ..., 35.4025, 35.4015, 35.4005])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-66e7d888-ef36-430f-b0f7-87fea631c4e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66e7d888-ef36-430f-b0f7-87fea631c4e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3c8e52d-f31f-4bf1-8688-4a0701b4850b' class='xr-var-data-in' type='checkbox'><label for='data-b3c8e52d-f31f-4bf1-8688-4a0701b4850b' 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>GeoTransform :</span></dt><dd>-123.3 0.0009998245921768116 0.0 42.0 0.0 -0.0009998485078018483</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fe8d478e-95a2-4019-92f6-8348ce23e4ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fe8d478e-95a2-4019-92f6-8348ce23e4ac' 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>band_data</span></div><div class='xr-var-dims'>(band, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5becaa8c-af25-448b-b622-b6aa6e34a6da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5becaa8c-af25-448b-b622-b6aa6e34a6da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-689c9eae-6b6a-4f38-9268-1123b73762ef' class='xr-var-data-in' type='checkbox'><label for='data-689c9eae-6b6a-4f38-9268-1123b73762ef' 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>STATISTICS_MAXIMUM :</span></dt><dd>4361.6544978218</dd><dt><span>STATISTICS_MEAN :</span></dt><dd>2188.8927168701</dd><dt><span>STATISTICS_MINIMUM :</span></dt><dd>1500.0934414576</dd><dt><span>STATISTICS_STDDEV :</span></dt><dd>536.09068152772</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a94f1a9f-d014-4f17-ac30-8ab41c03868e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a94f1a9f-d014-4f17-ac30-8ab41c03868e' 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:      (band: 1, x: 5701, y: 6601)\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -123.3 -123.3 -123.3 ... -117.6 -117.6 -117.6\n",
       "  * y            (y) float64 42.0 42.0 42.0 42.0 42.0 ... 35.4 35.4 35.4 35.4\n",
       "    spatial_ref  int64 0\n",
       "Data variables:\n",
       "    band_data    (band, y, x) float32 nan nan nan nan nan ... nan nan nan nan"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdf5file = \"/Volumes/JT/projects/margulis/static/rasters/SNSR_DEM.tif\"\n",
    "\n",
    "dem = xr.open_dataset(hdf5file, engine=\"rasterio\").load()\n",
    "dem.transpose(\"band\",\"y\",\"x\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "7d32d2b4-6741-4ff4-8a4a-a4c178428bc7",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'numpy' has no attribute 'DataArray'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/7d/61kbxptj5yl29nbrh216cv_40000gn/T/ipykernel_2200/4019963823.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataArray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/miniconda3/envs/test_env/lib/python3.8/site-packages/numpy/__init__.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m    311\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mTester\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 313\u001b[0;31m             raise AttributeError(\"module {!r} has no attribute \"\n\u001b[0m\u001b[1;32m    314\u001b[0m                                  \"{!r}\".format(__name__, attr))\n\u001b[1;32m    315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'DataArray'"
     ]
    }
   ],
   "source": [
    "test = np.DataArray(dem)\n",
    "plt.imshow(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93a71b89-6861-4be0-abf0-fd2788ddb843",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "codemirror_mode": {
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