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kmuehlbauer/InterpolationKDE.ipynb

Created March 22, 2024 07:44
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InterpolationKDE.ipynb
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"### Gage adjustment\n",
"\n",
"-----------------------------------------------------\n",
"---"
]
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"import os\n",
"import math\n",
"import copy\n",
"import warnings\n",
"\n",
"import numpy as np\n",
"import numpy.ma as ma\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import cartopy.crs as ccrs\n",
"import xarray as xr\n",
"\n",
"import wradlib as wrl\n",
"\n",
"try:\n",
" get_ipython().run_line_magic(\"matplotlib inline\")\n",
"except:\n",
" plt.ion()\n",
"\n",
"warnings.filterwarnings('ignore')"
]
},
{
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"source": [
"### **PART 1):** Reading the RADAR file"
]
},
{
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"execution_count": 2,
"id": "837f019d-cbb5-4f15-8ee6-25fd2efd89f1",
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"source": [
"filename = \"CAPPI-2km-Depth-H&V.nc\""
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0407d663-2e5b-4ddd-b4ef-84dcf18ed08c",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 1, x: 500, y: 500, z: 1, nradar: 1)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2022-02-15T21:00:11\n",
" * x (x) float64 -2.5e+05 -2.49e+05 ... 2.5e+05\n",
" * y (y) float64 -2.5e+05 -2.49e+05 ... 2.5e+05\n",
" * z (z) float64 2e+03\n",
"Dimensions without coordinates: nradar\n",
"Data variables: (12/16)\n",
" origin_latitude (time) float64 ...\n",
" origin_longitude (time) float64 ...\n",
" origin_altitude (time) float64 ...\n",
" projection int32 ...\n",
" ProjectionCoordinateSystem int32 ...\n",
" radar_latitude (nradar) float64 ...\n",
" ... ...\n",
" DBZV (time, z, y, x) float32 ...\n",
" UV (time, z, y, x) float32 ...\n",
" UH (time, z, y, x) float32 ...\n",
" DBZH (time, z, y, x) float32 ...\n",
" R_KDP_Corr_h_depth (time, z, y, x) float32 ...\n",
" R_KDP_Corr_v_depth (time, z, y, x) float32 ...\n",
"Attributes: (12/14)\n",
" Conventions: Cf/Radial instrument_parameters radar_parameters\n",
" title: PPIVol\n",
" institution: EEC\n",
" references: EEC\n",
" source: EDGE\n",
" history: original\n",
" ... ...\n",
" site_name: 9921GUA\n",
" n_gates_vary: false\n",
" volume_number: 1\n",
" platform_type: fixed\n",
" instrument_type: radar\n",
" primary_axis: axis_z</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-d8d00b15-07a3-441a-b006-a392e7964a8b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d8d00b15-07a3-441a-b006-a392e7964a8b' 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>: 1</li><li><span class='xr-has-index'>x</span>: 500</li><li><span class='xr-has-index'>y</span>: 500</li><li><span class='xr-has-index'>z</span>: 1</li><li><span>nradar</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0a4ce41c-1596-43e8-b3bd-8749944e3570' class='xr-section-summary-in' type='checkbox' checked><label for='section-0a4ce41c-1596-43e8-b3bd-8749944e3570' 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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-692d5074-4bfc-4b1e-9026-01fc8f935b66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-692d5074-4bfc-4b1e-9026-01fc8f935b66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9869c4e-0953-4de9-b178-186edd829b99' class='xr-var-data-in' type='checkbox'><label for='data-e9869c4e-0953-4de9-b178-186edd829b99' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-02-15T21:00:11.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-dcdf8f61-eb18-4da1-9243-9236791d156a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcdf8f61-eb18-4da1-9243-9236791d156a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6baf2d2-6ead-4278-aeb6-cb93dc4e4c82' class='xr-var-data-in' type='checkbox'><label for='data-e6baf2d2-6ead-4278-aeb6-cb93dc4e4c82' 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>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</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'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-d40b154f-040e-4958-a101-b7745687cd1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d40b154f-040e-4958-a101-b7745687cd1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44f5514b-80c1-49d2-aa8b-5b171cc288c9' class='xr-var-data-in' type='checkbox'><label for='data-44f5514b-80c1-49d2-aa8b-5b171cc288c9' 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>long_name :</span></dt><dd>Y distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-b113b995-67e0-45b2-a8fc-607181538a4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b113b995-67e0-45b2-a8fc-607181538a4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-243fcf68-7613-476f-9b61-522e596929cf' class='xr-var-data-in' type='checkbox'><label for='data-243fcf68-7613-476f-9b61-522e596929cf' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([2000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-56a8d0d3-2719-46bf-b728-230a0c85667b' class='xr-section-summary-in' type='checkbox' ><label for='section-56a8d0d3-2719-46bf-b728-230a0c85667b' class='xr-section-summary' >Data variables: <span>(16)</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>origin_latitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-94c6b2de-5b6f-4459-9014-efae081a5aef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94c6b2de-5b6f-4459-9014-efae081a5aef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51850259-a62a-48f4-bdf1-eac3aa609bbd' class='xr-var-data-in' type='checkbox'><label for='data-51850259-a62a-48f4-bdf1-eac3aa609bbd' 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>long_name :</span></dt><dd>Latitude at grid origin</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>origin_longitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-74e4ba61-1e21-4b4b-b9c8-1cadb220a777' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74e4ba61-1e21-4b4b-b9c8-1cadb220a777' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-020d6870-c26b-47cb-b68b-85798b3134aa' class='xr-var-data-in' type='checkbox'><label for='data-020d6870-c26b-47cb-b68b-85798b3134aa' 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>long_name :</span></dt><dd>Longitude at grid origin</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>origin_altitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd84983d-9efa-43b3-b240-a3a7a190fb02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd84983d-9efa-43b3-b240-a3a7a190fb02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b4f023f-80fb-404e-be35-f99f4f5ac586' class='xr-var-data-in' type='checkbox'><label for='data-9b4f023f-80fb-404e-be35-f99f4f5ac586' 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>long_name :</span></dt><dd>Altitude at grid origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>altitude</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>projection</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-78f7ca00-23f9-4d1a-bb07-b2259f20f69e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78f7ca00-23f9-4d1a-bb07-b2259f20f69e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48b74b62-d9a6-43ba-9364-b73b5ece4e25' class='xr-var-data-in' type='checkbox'><label for='data-48b74b62-d9a6-43ba-9364-b73b5ece4e25' 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>proj :</span></dt><dd>pyart_aeqd</dd><dt><span>_include_lon_0_lat_0 :</span></dt><dd>true</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ProjectionCoordinateSystem</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-054283a3-ac38-453f-9159-83b5d7c6ec88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-054283a3-ac38-453f-9159-83b5d7c6ec88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-545f3cf9-499c-4ff8-9d36-9415cc5c4e75' class='xr-var-data-in' type='checkbox'><label for='data-545f3cf9-499c-4ff8-9d36-9415cc5c4e75' 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>latitude_of_projection_origin :</span></dt><dd>-22.9932804107666</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-43.58795928955078</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>_CoordinateAxes :</span></dt><dd>x y z time</dd><dt><span>_CoordinateAxesTypes :</span></dt><dd>GeoX GeoY Height Time</dd><dt><span>grid_mapping_name :</span></dt><dd>azimuthal_equidistant</dd><dt><span>semi_major_axis :</span></dt><dd>6370997.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.25</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radar_latitude</span></div><div class='xr-var-dims'>(nradar)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fcfa7161-1251-4be0-867a-a3e06d05dca8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcfa7161-1251-4be0-867a-a3e06d05dca8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f11ebe8-1270-44b3-880c-8b318747987a' class='xr-var-data-in' type='checkbox'><label for='data-1f11ebe8-1270-44b3-880c-8b318747987a' 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>long_name :</span></dt><dd>Latitude of radars used to make the grid.</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radar_longitude</span></div><div class='xr-var-dims'>(nradar)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f57c751f-1335-4888-9738-827b3b81b9e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f57c751f-1335-4888-9738-827b3b81b9e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a512212-a00c-4512-9563-40ab63146376' class='xr-var-data-in' type='checkbox'><label for='data-7a512212-a00c-4512-9563-40ab63146376' 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>long_name :</span></dt><dd>Longitude of radars used to make the grid.</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radar_altitude</span></div><div class='xr-var-dims'>(nradar)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b80ad65c-5811-4d5c-9896-cd4e2dc32962' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b80ad65c-5811-4d5c-9896-cd4e2dc32962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b182697-6a6e-4fb1-9699-883a016ce31a' class='xr-var-data-in' type='checkbox'><label for='data-0b182697-6a6e-4fb1-9699-883a016ce31a' 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>long_name :</span></dt><dd>Altitude of radars used to make the grid.</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radar_time</span></div><div class='xr-var-dims'>(nradar)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d5e9bab6-3cf2-4051-b19f-c89f8ecf5ebc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5e9bab6-3cf2-4051-b19f-c89f8ecf5ebc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-603f3f73-db6c-4d47-8a0a-e4319c2b6d48' class='xr-var-data-in' type='checkbox'><label for='data-603f3f73-db6c-4d47-8a0a-e4319c2b6d48' 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>long_name :</span></dt><dd>Time in seconds of the volume start for each radar</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radar_name</span></div><div class='xr-var-dims'>(nradar)</div><div class='xr-var-dtype'>|S7</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-62697fd0-7353-4d0e-945d-5ecee2de164a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62697fd0-7353-4d0e-945d-5ecee2de164a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc4962de-a665-4427-9a33-c287c74a0290' class='xr-var-data-in' type='checkbox'><label for='data-dc4962de-a665-4427-9a33-c287c74a0290' 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>long_name :</span></dt><dd>Name of radar used to make the grid</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S7]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DBZV</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7810f90f-9133-4835-b231-c27312ff676f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7810f90f-9133-4835-b231-c27312ff676f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b96643f6-577d-46a7-817a-724493d1a0c3' class='xr-var-data-in' type='checkbox'><label for='data-b96643f6-577d-46a7-817a-724493d1a0c3' 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>long_name :</span></dt><dd>equivalent_reflectivity_factor_v</dd><dt><span>units :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UV</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-111aa7cf-76b2-45d7-a4c5-c50833a551cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-111aa7cf-76b2-45d7-a4c5-c50833a551cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d36c271-4541-4bf0-9a2f-d116fd032e58' class='xr-var-data-in' type='checkbox'><label for='data-9d36c271-4541-4bf0-9a2f-d116fd032e58' 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>long_name :</span></dt><dd>unfiltered_reflectivity_factor_v</dd><dt><span>units :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UH</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7b06f32f-b285-4406-988e-2b27f0c1054b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b06f32f-b285-4406-988e-2b27f0c1054b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f85ec5f-857b-4706-820f-a178527218b4' class='xr-var-data-in' type='checkbox'><label for='data-0f85ec5f-857b-4706-820f-a178527218b4' 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>long_name :</span></dt><dd>unfiltered_reflectivity_factor_h</dd><dt><span>units :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DBZH</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ca777828-2902-4806-9283-e0a4fe8688fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca777828-2902-4806-9283-e0a4fe8688fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-430177ad-babb-4539-9096-d6e2e3845362' class='xr-var-data-in' type='checkbox'><label for='data-430177ad-babb-4539-9096-d6e2e3845362' 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>long_name :</span></dt><dd>equivalent_reflectivity_factor_h</dd><dt><span>units :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>R_KDP_Corr_h_depth</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-eeb69c8e-43dc-41b0-8237-475401feb5c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eeb69c8e-43dc-41b0-8237-475401feb5c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-238c0c8d-4318-4d42-90c0-822654f914b6' class='xr-var-data-in' type='checkbox'><label for='data-238c0c8d-4318-4d42-90c0-822654f914b6' 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>long_name :</span></dt><dd>Rainfall Depth Horizontal </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:47.362010 Elton</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>R_KDP_Corr_v_depth</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f91063c6-0ed3-409f-9455-0651f8ddd8d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f91063c6-0ed3-409f-9455-0651f8ddd8d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-562f1c5a-7212-48fc-992b-7091f2b255b2' class='xr-var-data-in' type='checkbox'><label for='data-562f1c5a-7212-48fc-992b-7091f2b255b2' 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>long_name :</span></dt><dd>Rainfall Depth Vertical </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Vertical</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Vertical</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:49.284166 Elton</dd></dl></div><div class='xr-var-data'><pre>[250000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80b780bb-e51b-49e2-a067-a03553f37f57' class='xr-section-summary-in' type='checkbox' ><label for='section-80b780bb-e51b-49e2-a067-a03553f37f57' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2d89a9e6-445f-4cdd-b941-4172792ee581' class='xr-index-data-in' type='checkbox'/><label for='index-2d89a9e6-445f-4cdd-b941-4172792ee581' 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(DatetimeIndex([&#x27;2022-02-15 21:00:11&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a126d3f4-5c28-44fd-a7b8-950aa50425c7' class='xr-index-data-in' type='checkbox'/><label for='index-a126d3f4-5c28-44fd-a7b8-950aa50425c7' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c9b3e739-0586-40ce-8e9f-93ed82b267e4' class='xr-index-data-in' type='checkbox'/><label for='index-c9b3e739-0586-40ce-8e9f-93ed82b267e4' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>z</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7a397213-a572-4dec-b91c-cad7c0099978' class='xr-index-data-in' type='checkbox'/><label for='index-7a397213-a572-4dec-b91c-cad7c0099978' 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([2000.0], dtype=&#x27;float64&#x27;, name=&#x27;z&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8264d4cb-089c-47e6-920b-41acd64f57ca' class='xr-section-summary-in' type='checkbox' ><label for='section-8264d4cb-089c-47e6-920b-41acd64f57ca' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>Cf/Radial instrument_parameters radar_parameters</dd><dt><span>title :</span></dt><dd>PPIVol</dd><dt><span>institution :</span></dt><dd>EEC</dd><dt><span>references :</span></dt><dd>EEC</dd><dt><span>source :</span></dt><dd>EDGE</dd><dt><span>history :</span></dt><dd>original</dd><dt><span>comment :</span></dt><dd>PPIVol</dd><dt><span>instrument_name :</span></dt><dd>9921GUA</dd><dt><span>site_name :</span></dt><dd>9921GUA</dd><dt><span>n_gates_vary :</span></dt><dd>false</dd><dt><span>volume_number :</span></dt><dd>1</dd><dt><span>platform_type :</span></dt><dd>fixed</dd><dt><span>instrument_type :</span></dt><dd>radar</dd><dt><span>primary_axis :</span></dt><dd>axis_z</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 1, x: 500, y: 500, z: 1, nradar: 1)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2022-02-15T21:00:11\n",
" * x (x) float64 -2.5e+05 -2.49e+05 ... 2.5e+05\n",
" * y (y) float64 -2.5e+05 -2.49e+05 ... 2.5e+05\n",
" * z (z) float64 2e+03\n",
"Dimensions without coordinates: nradar\n",
"Data variables: (12/16)\n",
" origin_latitude (time) float64 ...\n",
" origin_longitude (time) float64 ...\n",
" origin_altitude (time) float64 ...\n",
" projection int32 ...\n",
" ProjectionCoordinateSystem int32 ...\n",
" radar_latitude (nradar) float64 ...\n",
" ... ...\n",
" DBZV (time, z, y, x) float32 ...\n",
" UV (time, z, y, x) float32 ...\n",
" UH (time, z, y, x) float32 ...\n",
" DBZH (time, z, y, x) float32 ...\n",
" R_KDP_Corr_h_depth (time, z, y, x) float32 ...\n",
" R_KDP_Corr_v_depth (time, z, y, x) float32 ...\n",
"Attributes: (12/14)\n",
" Conventions: Cf/Radial instrument_parameters radar_parameters\n",
" title: PPIVol\n",
" institution: EEC\n",
" references: EEC\n",
" source: EDGE\n",
" history: original\n",
" ... ...\n",
" site_name: 9921GUA\n",
" n_gates_vary: false\n",
" volume_number: 1\n",
" platform_type: fixed\n",
" instrument_type: radar\n",
" primary_axis: axis_z"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"grid = xr.open_dataset(filename)\n",
"display(grid)"
]
},
{
"cell_type": "markdown",
"id": "ea1bb625-d2be-4619-93d4-bd8c044f0d03",
"metadata": {},
"source": [
"### **PART 2):** Reading rain gauges"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "44da5a7e-f705-4699-8269-adcaa500adac",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"(85,)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Load data from text file\n",
"obs = np.loadtxt('obs.txt')\n",
"obs.shape"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "2c114a80-f76a-47d0-a5ad-5dfbe1f9ab0e",
"metadata": {},
"outputs": [],
"source": [
"#obs"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e9ccfd75-acec-42a0-ae89-8dd6fadf51a2",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"(85, 2)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Load coordinate text file data\n",
"obs_coords = np.loadtxt('obs_coords.txt')\n",
"obs_coords.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d2623906-7787-4120-8101-83717f8ca9d7",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"#obs_coords"
]
},
{
"cell_type": "markdown",
"id": "7787a087-d69e-4b1a-84e2-490b70847105",
"metadata": {},
"source": [
"### **PART 3):**Preparing the data"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "7e8b35e5-056f-4a38-86e7-2f87baa23fa5",
"metadata": {},
"outputs": [],
"source": [
"# select base 2d grid\n",
"grid = grid.isel(time=0, z=0)"
]
},
{
"cell_type": "markdown",
"id": "80149167-61a2-476c-92b3-432c36ede4e8",
"metadata": {},
"source": [
"### Radar Horizontal\n",
"\n",
"- create mask\n",
"- fill nan with zero\n",
"- stack xy into radar_obs"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "abca56ce-4fd9-4135-b88c-f8ced9590e6b",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;R_KDP_Corr_h_depth&#x27; (radar_obs: 250000)&gt;\n",
"array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton</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'>'R_KDP_Corr_h_depth'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>radar_obs</span>: 250000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-efcbf3b5-74dc-4d67-89a0-139553543956' class='xr-array-in' type='checkbox' checked><label for='section-efcbf3b5-74dc-4d67-89a0-139553543956' 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>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-0dcbbe2d-b261-4d7e-b524-79b47e5ea574' class='xr-section-summary-in' type='checkbox' checked><label for='section-0dcbbe2d-b261-4d7e-b524-79b47e5ea574' class='xr-section-summary' >Coordinates: <span>(5)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-07ea85ad-209f-4c1e-9b26-247895c13c22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07ea85ad-209f-4c1e-9b26-247895c13c22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f293232-5a4c-4b80-a457-ccb8ec79f2a0' class='xr-var-data-in' type='checkbox'><label for='data-7f293232-5a4c-4b80-a457-ccb8ec79f2a0' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-15T21:00:11.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-0030989e-5ff1-4267-8c55-9a8523cd37ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0030989e-5ff1-4267-8c55-9a8523cd37ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94a2d245-23d5-4d53-8ddd-46ddebe49d90' class='xr-var-data-in' type='checkbox'><label for='data-94a2d245-23d5-4d53-8ddd-46ddebe49d90' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>radar_obs</span></div><div class='xr-var-dims'>(radar_obs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-bd1a9b54-4cdf-495e-b18d-fdf96cf95007' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd1a9b54-4cdf-495e-b18d-fdf96cf95007' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48c0a787-3883-40ea-b6bf-bac326b0bdfc' class='xr-var-data-in' type='checkbox'><label for='data-48c0a787-3883-40ea-b6bf-bac326b0bdfc' 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([(-250000.0, -250000.0), (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795), ..., (250000.0, 247995.99198396795),\n",
" (250000.0, 248997.99599198397), (250000.0, 250000.0)], dtype=object)</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.5e+05 ... 2.5e+05</div><input id='attrs-372d5718-13e9-4b8b-b144-7aea4bb5a117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-372d5718-13e9-4b8b-b144-7aea4bb5a117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6917f4d-53bb-446b-a467-c071090e6f1a' class='xr-var-data-in' type='checkbox'><label for='data-c6917f4d-53bb-446b-a467-c071090e6f1a' 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>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-250000., -250000., -250000., ..., 250000., 250000., 250000.])</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-e2b2a989-b247-4176-aee0-7e5d03efc742' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2b2a989-b247-4176-aee0-7e5d03efc742' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03db8a9b-34ff-4b88-a18a-c348e7204110' class='xr-var-data-in' type='checkbox'><label for='data-03db8a9b-34ff-4b88-a18a-c348e7204110' 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>long_name :</span></dt><dd>Y distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18ec7446-6ac5-4fd5-8938-02dbeed21214' class='xr-section-summary-in' type='checkbox' ><label for='section-18ec7446-6ac5-4fd5-8938-02dbeed21214' 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>radar_obs<br>x<br>y</div></div><div class='xr-index-preview'>PandasMultiIndex</div><div></div><input id='index-0cc14a87-d55c-47cc-b555-8df29a3e4cef' class='xr-index-data-in' type='checkbox'/><label for='index-0cc14a87-d55c-47cc-b555-8df29a3e4cef' 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(MultiIndex([(-250000.0, -250000.0),\n",
" (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795),\n",
" (-250000.0, -246993.9879759519),\n",
" (-250000.0, -245991.98396793587),\n",
" (-250000.0, -244989.97995991984),\n",
" (-250000.0, -243987.97595190382),\n",
" (-250000.0, -242985.97194388777),\n",
" (-250000.0, -241983.96793587174),\n",
" (-250000.0, -240981.96392785572),\n",
" ...\n",
" ( 250000.0, 240981.96392785572),\n",
" ( 250000.0, 241983.96793587174),\n",
" ( 250000.0, 242985.97194388782),\n",
" ( 250000.0, 243987.97595190385),\n",
" ( 250000.0, 244989.97995991987),\n",
" ( 250000.0, 245991.9839679359),\n",
" ( 250000.0, 246993.98797595192),\n",
" ( 250000.0, 247995.99198396795),\n",
" ( 250000.0, 248997.99599198397),\n",
" ( 250000.0, 250000.0)],\n",
" name=&#x27;radar_obs&#x27;, length=250000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba7987d4-1ef6-431f-9b7c-e373cf5645b6' class='xr-section-summary-in' type='checkbox' checked><label for='section-ba7987d4-1ef6-431f-9b7c-e373cf5645b6' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Rainfall Depth Horizontal </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:47.362010 Elton</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'R_KDP_Corr_h_depth' (radar_obs: 250000)>\n",
"array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nanmask_h = xr.where(np.isnan(grid.R_KDP_Corr_h_depth), True, False)\n",
"radar_h = grid.R_KDP_Corr_h_depth.fillna(0)\n",
"radar_h_stack = radar_h.stack(radar_obs=(\"x\", \"y\"))\n",
"display(radar_h_stack)"
]
},
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"source": [
"### Radar Vertical\n",
"- create mask\n",
"- fill nan with zero\n",
"- stack xy into radar_obs"
]
},
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;R_KDP_Corr_v_depth&#x27; (radar_obs: 250000)&gt;\n",
"array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Attributes:\n",
" long_name: Rainfall Depth Vertical \n",
" units: mm\n",
" standard_name: Rainfall Depth Vertical\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Vertical\n",
" institution: IME\n",
" history: 2024-03-21 17:11:49.284166 Elton</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'>'R_KDP_Corr_v_depth'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>radar_obs</span>: 250000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8e50970b-6f0d-474d-9e72-03953eea0e01' class='xr-array-in' type='checkbox' checked><label for='section-8e50970b-6f0d-474d-9e72-03953eea0e01' 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>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-d228619f-d25e-4113-8f07-94c32cc42a4a' class='xr-section-summary-in' type='checkbox' checked><label for='section-d228619f-d25e-4113-8f07-94c32cc42a4a' class='xr-section-summary' >Coordinates: <span>(5)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-734d7b5a-6669-4154-b3e6-f6301e524bec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-734d7b5a-6669-4154-b3e6-f6301e524bec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e2f1844-fe3e-4758-8753-ac1318e17503' class='xr-var-data-in' type='checkbox'><label for='data-5e2f1844-fe3e-4758-8753-ac1318e17503' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-15T21:00:11.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-8d38fe16-d73e-43fe-8dce-206c6ff625ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d38fe16-d73e-43fe-8dce-206c6ff625ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0acdc1dd-c64b-48ce-8556-2c525338bffb' class='xr-var-data-in' type='checkbox'><label for='data-0acdc1dd-c64b-48ce-8556-2c525338bffb' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>radar_obs</span></div><div class='xr-var-dims'>(radar_obs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-06274f2f-0480-4798-be50-e5db5acbb05b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06274f2f-0480-4798-be50-e5db5acbb05b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0739b13a-5d52-44df-811f-f917f587c9a7' class='xr-var-data-in' type='checkbox'><label for='data-0739b13a-5d52-44df-811f-f917f587c9a7' 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([(-250000.0, -250000.0), (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795), ..., (250000.0, 247995.99198396795),\n",
" (250000.0, 248997.99599198397), (250000.0, 250000.0)], dtype=object)</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.5e+05 ... 2.5e+05</div><input id='attrs-1db67f17-eee4-4ab7-8e2c-96909120d12c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1db67f17-eee4-4ab7-8e2c-96909120d12c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17f2812e-acba-4926-90b4-5061f0bb2412' class='xr-var-data-in' type='checkbox'><label for='data-17f2812e-acba-4926-90b4-5061f0bb2412' 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>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-250000., -250000., -250000., ..., 250000., 250000., 250000.])</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-bb82e8ac-6953-44fd-a1e8-e1e0fd1cf820' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb82e8ac-6953-44fd-a1e8-e1e0fd1cf820' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd2b9343-54a1-426a-b3e9-6e67954b52eb' class='xr-var-data-in' type='checkbox'><label for='data-cd2b9343-54a1-426a-b3e9-6e67954b52eb' 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>long_name :</span></dt><dd>Y distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c847c02-f0aa-4b52-9c29-344e29316abc' class='xr-section-summary-in' type='checkbox' ><label for='section-4c847c02-f0aa-4b52-9c29-344e29316abc' 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>radar_obs<br>x<br>y</div></div><div class='xr-index-preview'>PandasMultiIndex</div><div></div><input id='index-c2237066-1e6e-46af-b34d-cf36283a9d23' class='xr-index-data-in' type='checkbox'/><label for='index-c2237066-1e6e-46af-b34d-cf36283a9d23' 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(MultiIndex([(-250000.0, -250000.0),\n",
" (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795),\n",
" (-250000.0, -246993.9879759519),\n",
" (-250000.0, -245991.98396793587),\n",
" (-250000.0, -244989.97995991984),\n",
" (-250000.0, -243987.97595190382),\n",
" (-250000.0, -242985.97194388777),\n",
" (-250000.0, -241983.96793587174),\n",
" (-250000.0, -240981.96392785572),\n",
" ...\n",
" ( 250000.0, 240981.96392785572),\n",
" ( 250000.0, 241983.96793587174),\n",
" ( 250000.0, 242985.97194388782),\n",
" ( 250000.0, 243987.97595190385),\n",
" ( 250000.0, 244989.97995991987),\n",
" ( 250000.0, 245991.9839679359),\n",
" ( 250000.0, 246993.98797595192),\n",
" ( 250000.0, 247995.99198396795),\n",
" ( 250000.0, 248997.99599198397),\n",
" ( 250000.0, 250000.0)],\n",
" name=&#x27;radar_obs&#x27;, length=250000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b1fcede-4642-4946-b758-312e3dc20c1e' class='xr-section-summary-in' type='checkbox' checked><label for='section-2b1fcede-4642-4946-b758-312e3dc20c1e' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Rainfall Depth Vertical </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Vertical</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Vertical</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:49.284166 Elton</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'R_KDP_Corr_v_depth' (radar_obs: 250000)>\n",
"array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Attributes:\n",
" long_name: Rainfall Depth Vertical \n",
" units: mm\n",
" standard_name: Rainfall Depth Vertical\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Vertical\n",
" institution: IME\n",
" history: 2024-03-21 17:11:49.284166 Elton"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nanmask_v = xr.where(np.isnan(grid.R_KDP_Corr_v_depth), True, False)\n",
"radar_v = grid.R_KDP_Corr_v_depth.fillna(0)\n",
"radar_v.plot()\n",
"radar_v_stack = radar_v.stack(radar_obs=(\"x\", \"y\"))\n",
"display(radar_v_stack)"
]
},
{
"cell_type": "markdown",
"id": "79be7194-7a89-402c-b0d2-503cc6534e67",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"### **PART 3): **Adjustment of Rain Gauges**"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5d5048a6-e91b-4dfe-a011-bd4d81d83b77",
"metadata": {},
"outputs": [
{
"data": {
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" grid-column: 2;\n",
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"\n",
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".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
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"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
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" content: '(';\n",
"}\n",
"\n",
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" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
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"\n",
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" font-weight: bold;\n",
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"\n",
".xr-var-list,\n",
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"\n",
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".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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" padding-right: 5px;\n",
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"\n",
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".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
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"\n",
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"\n",
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"\n",
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"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
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"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;x&#x27; (radar_obs: 250000, xy: 2)&gt;\n",
"array([[-250000. , -250000. ],\n",
" [-250000. , -248997.99599198],\n",
" [-250000. , -247995.99198397],\n",
" ...,\n",
" [ 250000. , 247995.99198397],\n",
" [ 250000. , 248997.99599198],\n",
" [ 250000. , 250000. ]])\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Dimensions without coordinates: xy\n",
"Attributes:\n",
" long_name: X distance on the projection plane from the origin\n",
" units: m\n",
" standard_name: projection_x_coordinate\n",
" axis: X</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'>'x'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>radar_obs</span>: 250000</li><li><span>xy</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a5e7bcd9-527c-43ca-9cf6-a99cfc6b890d' class='xr-array-in' type='checkbox' checked><label for='section-a5e7bcd9-527c-43ca-9cf6-a99cfc6b890d' 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>-2.5e+05 -2.5e+05 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05 2.5e+05</span></div><div class='xr-array-data'><pre>array([[-250000. , -250000. ],\n",
" [-250000. , -248997.99599198],\n",
" [-250000. , -247995.99198397],\n",
" ...,\n",
" [ 250000. , 247995.99198397],\n",
" [ 250000. , 248997.99599198],\n",
" [ 250000. , 250000. ]])</pre></div></div></li><li class='xr-section-item'><input id='section-91761a82-24fa-407e-bb63-8189792bf78d' class='xr-section-summary-in' type='checkbox' checked><label for='section-91761a82-24fa-407e-bb63-8189792bf78d' class='xr-section-summary' >Coordinates: <span>(5)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-523b562c-827f-4484-8722-d1d7d35e0dc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-523b562c-827f-4484-8722-d1d7d35e0dc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11c44720-b6fa-4274-957a-404f870db0ec' class='xr-var-data-in' type='checkbox'><label for='data-11c44720-b6fa-4274-957a-404f870db0ec' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-15T21:00:11.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-4b25a308-f7b0-4638-b177-8128302f4f24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b25a308-f7b0-4638-b177-8128302f4f24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-719b052a-728a-459e-a0d0-0ee8248471ad' class='xr-var-data-in' type='checkbox'><label for='data-719b052a-728a-459e-a0d0-0ee8248471ad' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>radar_obs</span></div><div class='xr-var-dims'>(radar_obs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-34095b5e-c00a-4adf-ae10-c8d7a0402eb9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34095b5e-c00a-4adf-ae10-c8d7a0402eb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c361915e-daba-4730-a041-e91535586f31' class='xr-var-data-in' type='checkbox'><label for='data-c361915e-daba-4730-a041-e91535586f31' 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([(-250000.0, -250000.0), (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795), ..., (250000.0, 247995.99198396795),\n",
" (250000.0, 248997.99599198397), (250000.0, 250000.0)], dtype=object)</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.5e+05 ... 2.5e+05</div><input id='attrs-b1c6f732-05e6-4156-b6c4-f749791781ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b1c6f732-05e6-4156-b6c4-f749791781ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-298c81e0-e9cd-42eb-b3b7-4fa2287a6c8c' class='xr-var-data-in' type='checkbox'><label for='data-298c81e0-e9cd-42eb-b3b7-4fa2287a6c8c' 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([-250000., -250000., -250000., ..., 250000., 250000., 250000.])</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'>(radar_obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-b76de459-cf29-4997-856f-00047f890b1b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b76de459-cf29-4997-856f-00047f890b1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa72aacb-3c17-4a59-801a-1626e691037c' class='xr-var-data-in' type='checkbox'><label for='data-aa72aacb-3c17-4a59-801a-1626e691037c' 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([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-acac192b-596b-4a96-a90d-0b612d54b1f8' class='xr-section-summary-in' type='checkbox' ><label for='section-acac192b-596b-4a96-a90d-0b612d54b1f8' 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>radar_obs<br>x<br>y</div></div><div class='xr-index-preview'>PandasMultiIndex</div><div></div><input id='index-315dcbee-bd67-45ed-9eee-ef763bd5b14c' class='xr-index-data-in' type='checkbox'/><label for='index-315dcbee-bd67-45ed-9eee-ef763bd5b14c' 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(MultiIndex([(-250000.0, -250000.0),\n",
" (-250000.0, -248997.99599198397),\n",
" (-250000.0, -247995.99198396795),\n",
" (-250000.0, -246993.9879759519),\n",
" (-250000.0, -245991.98396793587),\n",
" (-250000.0, -244989.97995991984),\n",
" (-250000.0, -243987.97595190382),\n",
" (-250000.0, -242985.97194388777),\n",
" (-250000.0, -241983.96793587174),\n",
" (-250000.0, -240981.96392785572),\n",
" ...\n",
" ( 250000.0, 240981.96392785572),\n",
" ( 250000.0, 241983.96793587174),\n",
" ( 250000.0, 242985.97194388782),\n",
" ( 250000.0, 243987.97595190385),\n",
" ( 250000.0, 244989.97995991987),\n",
" ( 250000.0, 245991.9839679359),\n",
" ( 250000.0, 246993.98797595192),\n",
" ( 250000.0, 247995.99198396795),\n",
" ( 250000.0, 248997.99599198397),\n",
" ( 250000.0, 250000.0)],\n",
" name=&#x27;radar_obs&#x27;, length=250000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fa349fe-96fa-488d-a53f-26f7fa19c598' class='xr-section-summary-in' type='checkbox' checked><label for='section-8fa349fe-96fa-488d-a53f-26f7fa19c598' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'x' (radar_obs: 250000, xy: 2)>\n",
"array([[-250000. , -250000. ],\n",
" [-250000. , -248997.99599198],\n",
" [-250000. , -247995.99198397],\n",
" ...,\n",
" [ 250000. , 247995.99198397],\n",
" [ 250000. , 248997.99599198],\n",
" [ 250000. , 250000. ]])\n",
"Coordinates:\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
" * radar_obs (radar_obs) object MultiIndex\n",
" * x (radar_obs) float64 -2.5e+05 -2.5e+05 ... 2.5e+05 2.5e+05\n",
" * y (radar_obs) float64 -2.5e+05 -2.49e+05 ... 2.49e+05 2.5e+05\n",
"Dimensions without coordinates: xy\n",
"Attributes:\n",
" long_name: X distance on the projection plane from the origin\n",
" units: m\n",
" standard_name: projection_x_coordinate\n",
" axis: X"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# get grid coords\n",
"grid_coords = xr.concat([radar_h_stack.x, radar_h_stack.y], \"xy\").transpose(..., \"xy\")\n",
"display(grid_coords)"
]
},
{
"cell_type": "markdown",
"id": "24fec5b5-393b-40cb-af11-3f5ca03bbc37",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"## AdjustADD with OrdinaryKriging"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "ed96d547-888c-4690-837b-172192adeef3",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"obs: (85,)\n",
"obs_coords: (85, 2)\n",
"radar_h: (500, 500)\n",
"grid_coords: (250000, 2)\n",
"radar_v: (500, 500)\n"
]
}
],
"source": [
"# Estrutura dos seus dados\n",
"print(\"obs:\", obs.shape)\n",
"print(\"obs_coords:\", obs_coords.shape)\n",
"print(\"radar_h:\", radar_h.shape)\n",
"print(\"grid_coords:\", grid_coords.shape)\n",
"print(\"radar_v:\", radar_v.shape)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1f3e392e-2df2-4b6e-ab54-97245c5645b0",
"metadata": {
"editable": true,
"scrolled": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 20.9 s, sys: 243 ms, total: 21.2 s\n",
"Wall time: 21 s\n"
]
}
],
"source": [
"%%time\n",
"# Additive Error Model with OrdinaryKriging Exponential\n",
"# class wradlib.ipol.OrdinaryKriging(src, trg, cov='1.0 Exp(10000.)', nnearest=12)\n",
"addadjuster_ok_exp = wrl.adjust.AdjustAdd(obs_coords, \n",
" grid_coords.values,\n",
" cov = '1.0 Exp(10000.)',\n",
" ipclass=wrl.ipol.OrdinaryKriging)\n",
"addadjusted_ok_exp_values = addadjuster_ok_exp(obs, radar_h_stack.values)"
]
},
{
"cell_type": "markdown",
"id": "29bc952d-f0b8-42d0-b031-44d16e0dbcff",
"metadata": {},
"source": [
"### create DataArray, set values, unstack and transpose"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "d926929e-348b-414e-8d57-a2fa4da78a62",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;R_KDP_Corr_h_depth&#x27; (y: 500, x: 500)&gt;\n",
"array([[0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.5022548 ,\n",
" 0.5022548 ],\n",
" ...,\n",
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" 0.38615127],\n",
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" 0.38615126],\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615133, 0.38615128,\n",
" 0.38615125]])\n",
"Coordinates:\n",
" * x (x) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" * y (y) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton</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'>'R_KDP_Corr_h_depth'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 500</li><li><span class='xr-has-index'>x</span>: 500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-81e009bb-1fa4-4320-ba8c-8aa3a04026d9' class='xr-array-in' type='checkbox' checked><label for='section-81e009bb-1fa4-4320-ba8c-8aa3a04026d9' 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>0.1414 0.1414 0.1414 0.1414 0.1414 ... 0.3357 0.3862 0.3862 0.3862</span></div><div class='xr-array-data'><pre>array([[0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.5022548 ,\n",
" 0.5022548 ],\n",
" ...,\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615136, 0.38615131,\n",
" 0.38615127],\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615134, 0.3861513 ,\n",
" 0.38615126],\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615133, 0.38615128,\n",
" 0.38615125]])</pre></div></div></li><li class='xr-section-item'><input id='section-2475f351-7987-4f9a-bc7a-fbf1426f2480' class='xr-section-summary-in' type='checkbox' checked><label for='section-2475f351-7987-4f9a-bc7a-fbf1426f2480' 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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-0f695f12-0e9e-424e-81b0-ab6062288eae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f695f12-0e9e-424e-81b0-ab6062288eae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5345d30-cfd5-4e1c-952d-c591fef432a9' class='xr-var-data-in' type='checkbox'><label for='data-f5345d30-cfd5-4e1c-952d-c591fef432a9' 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>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</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'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-c3081595-a0b4-4615-b88b-d8a99a6f0927' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3081595-a0b4-4615-b88b-d8a99a6f0927' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d043a4e-e62f-4f65-b1c0-37ca33dfd560' class='xr-var-data-in' type='checkbox'><label for='data-2d043a4e-e62f-4f65-b1c0-37ca33dfd560' 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>long_name :</span></dt><dd>Y distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-22bf998b-c3c4-4394-bbf9-294432a310c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22bf998b-c3c4-4394-bbf9-294432a310c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0d2ef23-8861-4f14-b6e6-e057f039e012' class='xr-var-data-in' type='checkbox'><label for='data-e0d2ef23-8861-4f14-b6e6-e057f039e012' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-15T21:00:11.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-0bbc6a76-9857-4ec1-9ad2-55a7744d3e7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bbc6a76-9857-4ec1-9ad2-55a7744d3e7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-224e67c3-8d3a-4335-9d44-95afee9c4097' class='xr-var-data-in' type='checkbox'><label for='data-224e67c3-8d3a-4335-9d44-95afee9c4097' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2000.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab65498e-0442-47e8-b64b-cb73e220984e' class='xr-section-summary-in' type='checkbox' ><label for='section-ab65498e-0442-47e8-b64b-cb73e220984e' 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>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3be7c175-aedd-48bb-bdde-5511c7908485' class='xr-index-data-in' type='checkbox'/><label for='index-3be7c175-aedd-48bb-bdde-5511c7908485' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-324794eb-36ec-4a4b-b46e-43e5cbc32511' class='xr-index-data-in' type='checkbox'/><label for='index-324794eb-36ec-4a4b-b46e-43e5cbc32511' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6317ecc-6b6a-4a1b-ae6f-f5a3057319ce' class='xr-section-summary-in' type='checkbox' checked><label for='section-f6317ecc-6b6a-4a1b-ae6f-f5a3057319ce' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Rainfall Depth Horizontal </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:47.362010 Elton</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'R_KDP_Corr_h_depth' (y: 500, x: 500)>\n",
"array([[0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.58856927,\n",
" 0.5022548 ],\n",
" [0.14140616, 0.14140616, 0.14140616, ..., 0.58856927, 0.5022548 ,\n",
" 0.5022548 ],\n",
" ...,\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615136, 0.38615131,\n",
" 0.38615127],\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615134, 0.3861513 ,\n",
" 0.38615126],\n",
" [0.25972893, 0.25972893, 0.25972893, ..., 0.38615133, 0.38615128,\n",
" 0.38615125]])\n",
"Coordinates:\n",
" * x (x) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" * y (y) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"addadjusted_ok_exp = xr.zeros_like(radar_h_stack)\n",
"addadjusted_ok_exp.values = addadjusted_ok_exp_values\n",
"addadjusted_ok_exp = addadjusted_ok_exp.unstack().transpose(\"y\", \"x\")\n",
"display(addadjusted_ok_exp)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "de9abb03-f925-4ed4-a809-a421ca2219e4",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1000x350 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# open figure\n",
"fig = plt.figure(figsize=(10, 3.5))\n",
"\n",
"# \"Radar Rainfall: Real\"\n",
"ax = fig.add_subplot(121)\n",
"radar_h.where(~nanmask_h).plot(ax=ax)\n",
"ax.set_title(\"Radar Rainfall: Real\")\n",
"\n",
"# \"Additive Error Model with Nearest\"\n",
"ax = fig.add_subplot(122)\n",
"addadjusted_ok_exp.where(~nanmask_h).plot(ax=ax)\n",
"ax.set_title(\"Additive Error Model with OK EXPl\")\n",
"\n",
"plt.tight_layout()\n",
"# salva figura"
]
},
{
"cell_type": "markdown",
"id": "3b4dcdd8-3c93-4689-860f-6a4adcd70443",
"metadata": {},
"source": [
"## AdjustADD with ExternalDriftKriging"
]
},
{
"cell_type": "markdown",
"id": "7a5090fd-8052-4d35-bf28-9cbdd81143f9",
"metadata": {},
"source": [
"Docstring excerpt:\n",
"\n",
"```python\n",
"src_drift : :class:`numpy:numpy.ndarray`\n",
" ndarray of floats, shape (nsrcpoints, )\n",
" values of the external drift at each source point\n",
"trg_drift : :class:`numpy:numpy.ndarray`\n",
" ndarray of floats, shape (ntrgpoints, )\n",
" values of the external drift at each target point\n",
"```\n",
"\n",
"Not sure, if the now provided values for `src_drift` and `trg_drift` are the correct ones to provide there as `drift`."
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "d26476f6-1e8d-4545-8eca-8f4fb80d65ea",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 22.8 s, sys: 237 ms, total: 23 s\n",
"Wall time: 22.9 s\n"
]
}
],
"source": [
"%%time\n",
"addadjuster_kde_exp = wrl.adjust.AdjustAdd(obs_coords, \n",
" grid_coords.values,\n",
" cov = '1.0 Exp(10000.)',\n",
" nnearest=12,\n",
" src_drift=obs, # need obs values here\n",
" trg_drift=radar_v_stack.values, # need radar v values here\n",
" ipclass=wrl.ipol.ExternalDriftKriging)\n",
"addadjusted_kde_exp_values = addadjuster_kde_exp(obs, radar_h_stack.values)"
]
},
{
"cell_type": "markdown",
"id": "4a664d78-626f-4831-b359-39fcbdf01caa",
"metadata": {},
"source": [
"### create DataArray, set values, unstack and transpose"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "2e50a8a7-9574-46fb-96df-ff8d260cd156",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;R_KDP_Corr_h_depth&#x27; (y: 500, x: 500)&gt;\n",
"array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.]])\n",
"Coordinates:\n",
" * x (x) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" * y (y) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton</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'>'R_KDP_Corr_h_depth'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 500</li><li><span class='xr-has-index'>x</span>: 500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-faf767ed-ab3a-45d3-8a7d-8f177dc64811' class='xr-array-in' type='checkbox' checked><label for='section-faf767ed-ab3a-45d3-8a7d-8f177dc64811' 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>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.]])</pre></div></div></li><li class='xr-section-item'><input id='section-61b89a1a-13e2-4ac1-880c-0bba1ab9507a' class='xr-section-summary-in' type='checkbox' checked><label for='section-61b89a1a-13e2-4ac1-880c-0bba1ab9507a' 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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-73b95013-9743-4af8-b6b7-b892b9ed2807' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73b95013-9743-4af8-b6b7-b892b9ed2807' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c80b01d0-477a-4228-ae38-21cf67d3fba7' class='xr-var-data-in' type='checkbox'><label for='data-c80b01d0-477a-4228-ae38-21cf67d3fba7' 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>long_name :</span></dt><dd>X distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</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'>-2.5e+05 -2.49e+05 ... 2.5e+05</div><input id='attrs-2895d065-7455-441c-80a6-b985027282f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2895d065-7455-441c-80a6-b985027282f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e120a9a7-03ae-40d2-862d-c12e5680bb98' class='xr-var-data-in' type='checkbox'><label for='data-e120a9a7-03ae-40d2-862d-c12e5680bb98' 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>long_name :</span></dt><dd>Y distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-250000. , -248997.995992, -247995.991984, ..., 247995.991984,\n",
" 248997.995992, 250000. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-15T21:00:11</div><input id='attrs-6eaa38a2-00b4-458b-8a6e-bb95dfa69294' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6eaa38a2-00b4-458b-8a6e-bb95dfa69294' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6019498-5046-4143-8ada-2a51ffca9802' class='xr-var-data-in' type='checkbox'><label for='data-e6019498-5046-4143-8ada-2a51ffca9802' 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>long_name :</span></dt><dd>Time of grid</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-15T21:00:11.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+03</div><input id='attrs-af41b589-d07c-4466-9f9a-d854a94b737f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af41b589-d07c-4466-9f9a-d854a94b737f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30610d4b-a4ed-471d-a3cb-a9361e9421f6' class='xr-var-data-in' type='checkbox'><label for='data-30610d4b-a4ed-471d-a3cb-a9361e9421f6' 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>long_name :</span></dt><dd>Z distance on the projection plane from the origin</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_z_coordinate</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2000.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ae460b6a-8275-4101-ba95-6bad5385bd29' class='xr-section-summary-in' type='checkbox' ><label for='section-ae460b6a-8275-4101-ba95-6bad5385bd29' 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>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e9c685d7-06be-4dfc-9f18-b6de0b6ec481' class='xr-index-data-in' type='checkbox'/><label for='index-e9c685d7-06be-4dfc-9f18-b6de0b6ec481' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d2eb5e91-46bb-4bb9-bee5-d1170c418943' class='xr-index-data-in' type='checkbox'/><label for='index-d2eb5e91-46bb-4bb9-bee5-d1170c418943' 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([ -250000.0, -248997.99599198397, -247995.99198396795,\n",
" -246993.9879759519, -245991.98396793587, -244989.97995991984,\n",
" -243987.97595190382, -242985.97194388777, -241983.96793587174,\n",
" -240981.96392785572,\n",
" ...\n",
" 240981.96392785572, 241983.96793587174, 242985.97194388782,\n",
" 243987.97595190385, 244989.97995991987, 245991.9839679359,\n",
" 246993.98797595192, 247995.99198396795, 248997.99599198397,\n",
" 250000.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-78d01330-6215-419b-af59-399349526972' class='xr-section-summary-in' type='checkbox' checked><label for='section-78d01330-6215-419b-af59-399349526972' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Rainfall Depth Horizontal </dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>standard_name :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>title :</span></dt><dd>Rainfall Depth Horizontal</dd><dt><span>institution :</span></dt><dd>IME</dd><dt><span>history :</span></dt><dd>2024-03-21 17:11:47.362010 Elton</dd></dl></div></li></ul></div></div>"
],
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"array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
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"Coordinates:\n",
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" * y (y) float64 -2.5e+05 -2.49e+05 -2.48e+05 ... 2.49e+05 2.5e+05\n",
" time datetime64[ns] 2022-02-15T21:00:11\n",
" z float64 2e+03\n",
"Attributes:\n",
" long_name: Rainfall Depth Horizontal \n",
" units: mm\n",
" standard_name: Rainfall Depth Horizontal\n",
" Conventions: CF-1.7\n",
" title: Rainfall Depth Horizontal\n",
" institution: IME\n",
" history: 2024-03-21 17:11:47.362010 Elton"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"addadjusted_kde_exp = xr.zeros_like(radar_h_stack)\n",
"addadjusted_kde_exp.values = addadjusted_kde_exp_values\n",
"addadjusted_kde_exp = addadjusted_kde_exp.unstack().transpose(\"y\", \"x\")\n",
"display(addadjusted_kde_exp)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "331ece7a-805e-45a8-ae09-664dfb1a04f1",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x350 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# open figure\n",
"fig = plt.figure(figsize=(10, 3.5))\n",
"\n",
"# \"Radar Rainfall: Real\"\n",
"ax = fig.add_subplot(121)\n",
"radar_h.where(~nanmask_h).plot(ax=ax)\n",
"ax.set_title(\"Radar Rainfall: Real\")\n",
"\n",
"# \"Additive Error Model with Nearest\"\n",
"ax = fig.add_subplot(122)\n",
"addadjusted_kde_exp.where(~nanmask_h).plot(ax=ax)\n",
"ax.set_title(\"Additive Error Model with OK EXPl\")\n",
"\n",
"plt.tight_layout()\n",
"# salva figura"
]
}
],
"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": "3.12.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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