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zonca/compare_catalogs.ipynb

Created May 13, 2025 15:32
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compare_catalogs.ipynb
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"source": [
"import h5py\n",
"import numpy as np\n",
"import healpy as hp\n",
"import matplotlib.pyplot as plt"
]
},
{
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"freqs = [\n",
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"output_filename = \"data/websky_high_flux_catalog_1mJy.h5\""
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"text": [
"-rw-rw-r-- 1 azonca azonca 38725282 May 12 22:41 data/websky_high_flux_catalog_1mJy.h5\n"
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}
],
"source": [
"!ls -l $output_filename"
]
},
{
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"-rw-rw-r-- 1 azonca azonca 37M May 12 22:41 data/websky_high_flux_catalog_1mJy.h5\n"
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"source": [
"%ls -lah $output_filename"
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"source": [
"import xarray"
]
},
{
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"source": [
"new_catalog = xarray.open_dataset(output_filename)"
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 39MB\n",
"Dimensions: (index: 372255, power: 5)\n",
"Coordinates:\n",
" * index (index) int64 3MB 27897657 242175600 ... 166742332\n",
" * power (power) int64 40B 4 3 2 1 0\n",
" theta (index) float64 3MB ...\n",
" phi (index) float64 3MB ...\n",
"Data variables:\n",
" logpolycoefflux (index, power) float64 15MB ...\n",
" logpolycoefpolflux (index, power) float64 15MB ...\n",
"Attributes:\n",
" description: Websky catalog of sources with flux &gt; 1 mJy at 100 GHz, fit...</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-dd6ead8b-f74e-4e4a-813c-c046fa825e88' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dd6ead8b-f74e-4e4a-813c-c046fa825e88' 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'>index</span>: 372255</li><li><span class='xr-has-index'>power</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-22c795cc-cac2-4ee7-bb53-84dbb266ad11' class='xr-section-summary-in' type='checkbox' checked><label for='section-22c795cc-cac2-4ee7-bb53-84dbb266ad11' 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'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>27897657 242175600 ... 166742332</div><input id='attrs-9c92fee2-8c92-43c7-ad26-2393f0276775' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9c92fee2-8c92-43c7-ad26-2393f0276775' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dabee5eb-8a9e-4164-8550-7bc59b10b72a' class='xr-var-data-in' type='checkbox'><label for='data-dabee5eb-8a9e-4164-8550-7bc59b10b72a' 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([ 27897657, 242175600, 270516228, ..., 246732122, 263347056, 166742332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>power</span></div><div class='xr-var-dims'>(power)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4 3 2 1 0</div><input id='attrs-867bfddd-605c-4d89-baf1-68afcc98b951' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-867bfddd-605c-4d89-baf1-68afcc98b951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88c4602c-5a5c-44b2-a3f9-3671d49edea2' class='xr-var-data-in' type='checkbox'><label for='data-88c4602c-5a5c-44b2-a3f9-3671d49edea2' 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([4, 3, 2, 1, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-12fb9a86-dd79-47c5-a8dc-db7b48a88686' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12fb9a86-dd79-47c5-a8dc-db7b48a88686' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bac3ac99-27a7-48d9-aae2-0b1777d55ad2' class='xr-var-data-in' type='checkbox'><label for='data-bac3ac99-27a7-48d9-aae2-0b1777d55ad2' 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>units :</span></dt><dd>rad</dd><dt><span>reference_frame :</span></dt><dd>Galactic</dd></dl></div><div class='xr-var-data'><pre>[372255 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phi</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-94639278-2b7e-4565-bb7d-561e68571cb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94639278-2b7e-4565-bb7d-561e68571cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-151c04fa-3607-40de-9eef-b94cd66efb56' class='xr-var-data-in' type='checkbox'><label for='data-151c04fa-3607-40de-9eef-b94cd66efb56' 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>units :</span></dt><dd>rad</dd><dt><span>reference_frame :</span></dt><dd>Galactic</dd></dl></div><div class='xr-var-data'><pre>[372255 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-007e81d7-12eb-47df-9441-8756cb459e0d' class='xr-section-summary-in' type='checkbox' checked><label for='section-007e81d7-12eb-47df-9441-8756cb459e0d' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4f377d01-f42e-4f4a-b42b-2daaf36ea41d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f377d01-f42e-4f4a-b42b-2daaf36ea41d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb1b3dd3-7c9a-4102-aff1-b344ac773fee' class='xr-var-data-in' type='checkbox'><label for='data-cb1b3dd3-7c9a-4102-aff1-b344ac773fee' 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>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>[1861275 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefpolflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8620c57f-0d3f-4228-b600-061f5e183ae1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8620c57f-0d3f-4228-b600-061f5e183ae1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6b0433d-6551-4d91-a712-f8ecab627875' class='xr-var-data-in' type='checkbox'><label for='data-f6b0433d-6551-4d91-a712-f8ecab627875' 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>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>[1861275 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65fb1c1c-8549-4740-a1bf-8549ec338f1c' class='xr-section-summary-in' type='checkbox' ><label for='section-65fb1c1c-8549-4740-a1bf-8549ec338f1c' 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>index</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5e79e005-e888-4a23-97e2-68e79af55c8d' class='xr-index-data-in' type='checkbox'/><label for='index-5e79e005-e888-4a23-97e2-68e79af55c8d' 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([ 27897657, 242175600, 270516228, 276407774, 256213631, 281544643,\n",
" 263719520, 259533227, 251679008, 252717495,\n",
" ...\n",
" 238190295, 145826702, 108046020, 232265270, 174768449, 256408684,\n",
" 236382968, 246732122, 263347056, 166742332],\n",
" dtype=&#x27;int64&#x27;, name=&#x27;index&#x27;, length=372255))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>power</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-94e29ecc-5c41-430b-88fa-51b7764ff056' class='xr-index-data-in' type='checkbox'/><label for='index-94e29ecc-5c41-430b-88fa-51b7764ff056' 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([4, 3, 2, 1, 0], dtype=&#x27;int64&#x27;, name=&#x27;power&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0325eb28-0f04-4821-9221-64d573990689' class='xr-section-summary-in' type='checkbox' checked><label for='section-0325eb28-0f04-4821-9221-64d573990689' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>Websky catalog of sources with flux &gt; 1 mJy at 100 GHz, fitted with a 4th order polynomial in log frequency. Galactic reference frame. Sorted by flux at 100 GHz (descending). The &#x27;index&#x27; coordinate gives the original index in the Websky catalog.</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 39MB\n",
"Dimensions: (index: 372255, power: 5)\n",
"Coordinates:\n",
" * index (index) int64 3MB 27897657 242175600 ... 166742332\n",
" * power (power) int64 40B 4 3 2 1 0\n",
" theta (index) float64 3MB ...\n",
" phi (index) float64 3MB ...\n",
"Data variables:\n",
" logpolycoefflux (index, power) float64 15MB ...\n",
" logpolycoefpolflux (index, power) float64 15MB ...\n",
"Attributes:\n",
" description: Websky catalog of sources with flux > 1 mJy at 100 GHz, fit..."
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_catalog"
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},
{
"cell_type": "code",
"execution_count": 6,
"id": "48",
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"exception": false,
"start_time": "2025-05-10T06:54:52.364083",
"status": "completed"
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"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<HDF5 dataset \"logpolycoefflux\": shape (372255, 5), type \"<f8\">"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import h5py\n",
"f = h5py.File(output_filename, 'r')\n",
"f[\"logpolycoefflux\"]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "49",
"metadata": {
"execution": {
"iopub.execute_input": "2025-05-10T06:54:52.395368Z",
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"exception": false,
"start_time": "2025-05-10T06:54:52.387993",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"b'Jy'"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f[\"logpolycoefflux\"].attrs[\"units\"]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "6d2ff2bb",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/mnt/home/azonca'"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pathlib import Path\n",
"\n",
"home_folder = str(Path.home())\n",
"home_folder"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "85fa5dd5",
"metadata": {},
"outputs": [],
"source": [
"old_catalog= xarray.open_dataset(home_folder + \"/s/pysm-data/websky/0.4/radio_catalog/websky_high_flux_catalog_1mJy.h5\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "77e3103a",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 39MB\n",
"Dimensions: (index: 372255, power: 5)\n",
"Coordinates:\n",
" * index (index) int64 3MB 11253 16428 ... 281755430 281755795\n",
" * power (power) int64 40B 4 3 2 1 0\n",
" theta (index) float64 3MB ...\n",
" phi (index) float64 3MB ...\n",
"Data variables:\n",
" logpolycoefflux (index, power) float64 15MB ...\n",
" logpolycoefpolflux (index, power) float64 15MB ...\n",
"Attributes:\n",
" notes: Catalog of sources where the flux in Jy at any frequency is cal...</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-0b6b1318-69c9-4df4-9f6b-f5a983f7973c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0b6b1318-69c9-4df4-9f6b-f5a983f7973c' 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'>index</span>: 372255</li><li><span class='xr-has-index'>power</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1af219a9-8b56-457c-99df-8951ead6e18e' class='xr-section-summary-in' type='checkbox' checked><label for='section-1af219a9-8b56-457c-99df-8951ead6e18e' 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'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>11253 16428 ... 281755430 281755795</div><input id='attrs-17cd005c-4f6a-419b-bf28-531ebe9cc8dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17cd005c-4f6a-419b-bf28-531ebe9cc8dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27a48085-c944-42be-87d1-8210d4760ca1' class='xr-var-data-in' type='checkbox'><label for='data-27a48085-c944-42be-87d1-8210d4760ca1' 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([ 11253, 16428, 24110, ..., 281755117, 281755430, 281755795])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>power</span></div><div class='xr-var-dims'>(power)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4 3 2 1 0</div><input id='attrs-e4eff832-eba9-4439-8d07-4fef80adcf8b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4eff832-eba9-4439-8d07-4fef80adcf8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50961382-2417-4448-88b7-167fb2bbe4aa' class='xr-var-data-in' type='checkbox'><label for='data-50961382-2417-4448-88b7-167fb2bbe4aa' 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([4, 3, 2, 1, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-897a48e2-a291-430f-8ff8-31630e7a4128' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-897a48e2-a291-430f-8ff8-31630e7a4128' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35153d91-e508-4bd9-b583-98e61fcbe886' class='xr-var-data-in' type='checkbox'><label for='data-35153d91-e508-4bd9-b583-98e61fcbe886' 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>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>[372255 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phi</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e0ad5b43-50f3-4eff-85d5-ef8d7d6b66ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0ad5b43-50f3-4eff-85d5-ef8d7d6b66ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9339581d-2dbb-4b06-866c-370dcd99be7a' class='xr-var-data-in' type='checkbox'><label for='data-9339581d-2dbb-4b06-866c-370dcd99be7a' 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>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>[372255 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d6a2c642-6e79-4498-999a-ed156ecbfdcd' class='xr-section-summary-in' type='checkbox' checked><label for='section-d6a2c642-6e79-4498-999a-ed156ecbfdcd' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7a1dedeb-142f-450d-9871-45d77c86bb01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a1dedeb-142f-450d-9871-45d77c86bb01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bcba05f-44d0-4870-a1d8-dcf2fbc36aa8' class='xr-var-data-in' type='checkbox'><label for='data-2bcba05f-44d0-4870-a1d8-dcf2fbc36aa8' 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>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>[1861275 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefpolflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f67f4b6-8ebb-4ad9-b654-189e94718dc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f67f4b6-8ebb-4ad9-b654-189e94718dc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efd8a6d2-ccfc-452b-81da-799a3cea0925' class='xr-var-data-in' type='checkbox'><label for='data-efd8a6d2-ccfc-452b-81da-799a3cea0925' 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>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>[1861275 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bbc12773-8e71-4375-82e9-c13aed9f3198' class='xr-section-summary-in' type='checkbox' ><label for='section-bbc12773-8e71-4375-82e9-c13aed9f3198' 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>index</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4082e16d-c53b-4a57-9f30-abd2a78db979' class='xr-index-data-in' type='checkbox'/><label for='index-4082e16d-c53b-4a57-9f30-abd2a78db979' 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([ 11253, 16428, 24110, 25342, 26268, 27427,\n",
" 27855, 40649, 43434, 44634,\n",
" ...\n",
" 281751967, 281752822, 281753210, 281753640, 281753799, 281754105,\n",
" 281754532, 281755117, 281755430, 281755795],\n",
" dtype=&#x27;int64&#x27;, name=&#x27;index&#x27;, length=372255))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>power</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-34a032d9-33df-4e68-91e9-6b96c28246fc' class='xr-index-data-in' type='checkbox'/><label for='index-34a032d9-33df-4e68-91e9-6b96c28246fc' 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([4, 3, 2, 1, 0], dtype=&#x27;int64&#x27;, name=&#x27;power&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-52ca8cd7-be06-483f-b6fe-e6ecb3bef304' class='xr-section-summary-in' type='checkbox' checked><label for='section-52ca8cd7-be06-483f-b6fe-e6ecb3bef304' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>notes :</span></dt><dd>Catalog of sources where the flux in Jy at any frequency is calculated with a 5th order polynomial in the logarithm of the frequency in GHz, separately for temperature and polarization.\n",
"The catalog does not contain information about the polarization angle of a source.\n",
"The catalog sorted in descending order based on the source flux at 100 GHz</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 39MB\n",
"Dimensions: (index: 372255, power: 5)\n",
"Coordinates:\n",
" * index (index) int64 3MB 11253 16428 ... 281755430 281755795\n",
" * power (power) int64 40B 4 3 2 1 0\n",
" theta (index) float64 3MB ...\n",
" phi (index) float64 3MB ...\n",
"Data variables:\n",
" logpolycoefflux (index, power) float64 15MB ...\n",
" logpolycoefpolflux (index, power) float64 15MB ...\n",
"Attributes:\n",
" notes: Catalog of sources where the flux in Jy at any frequency is cal..."
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"old_catalog"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "606c20ce",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Indices match: True\n",
"Number of indices in new_catalog: 372255\n",
"Number of indices in old_catalog: 372255\n",
"Indices only in new_catalog: 0\n",
"Indices only in old_catalog: 0\n"
]
}
],
"source": [
"# Compare the index values of new_catalog and old_catalog, ignoring order\n",
"new_indices = set(new_catalog.index.values)\n",
"old_indices = set(old_catalog.index.values)\n",
"\n",
"print(\"Indices match:\", new_indices == old_indices)\n",
"print(\"Number of indices in new_catalog:\", len(new_indices))\n",
"print(\"Number of indices in old_catalog:\", len(old_indices))\n",
"print(\"Indices only in new_catalog:\", len(new_indices - old_indices))\n",
"print(\"Indices only in old_catalog:\", len(old_indices - new_indices))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3c9f110f",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 17,
"id": "7530924e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"logpolycoefflux arrays are equal for all indices: False\n"
]
}
],
"source": [
"import numpy as np\n",
"\n",
"# Ensure both catalogs are aligned by index\n",
"new_sorted = new_catalog.sortby(\"index\")\n",
"old_sorted = old_catalog.sortby(\"index\")\n",
"# Compare logpolycoefflux values for all indices\n",
"coeff_equal = np.allclose(\n",
" new_sorted.logpolycoefflux.values,\n",
" old_sorted.logpolycoefflux.values,\n",
" rtol=1e-6,\n",
" atol=1e-10,\n",
" equal_nan=True,\n",
")\n",
"\n",
"print(\"logpolycoefflux arrays are equal for all indices:\", coeff_equal)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2569363e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 19,
"id": "74cf4056",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total number of differing elements: 0\n"
]
}
],
"source": [
"# Find where the logpolycoefflux arrays differ and by how much\n",
"diff_mask = ~np.isclose(\n",
" new_sorted.logpolycoefflux.values,\n",
" old_sorted.logpolycoefflux.values,\n",
" rtol=1e-4,\n",
" atol=1e-6,\n",
" equal_nan=True,\n",
")\n",
"\n",
"# Get the indices (index, power) where they differ\n",
"diff_indices = np.argwhere(diff_mask)\n",
"\n",
"# Compute absolute differences for all differing elements\n",
"abs_diffs = [\n",
" (\n",
" abs(new_sorted.logpolycoefflux.values[i, p] - old_sorted.logpolycoefflux.values[i, p]),\n",
" i,\n",
" p\n",
" )\n",
" for i, p in diff_indices\n",
"]\n",
"\n",
"# Sort by absolute difference, descending\n",
"abs_diffs_sorted = sorted(abs_diffs, key=lambda x: x[0], reverse=True)\n",
"\n",
"# Show the 10 highest absolute differences\n",
"for abs_diff, i, p in abs_diffs_sorted[:10]:\n",
" new_val = new_sorted.logpolycoefflux.values[i, p]\n",
" old_val = old_sorted.logpolycoefflux.values[i, p]\n",
" print(\n",
" f\"index={new_sorted.index.values[i]}, power={new_sorted.power.values[p]}: \"\n",
" f\"new={new_val}, old={old_val}, abs_diff={abs_diff}\"\n",
" )\n",
" rel_diff = abs_diff / (abs(old_val) if old_val != 0 else 1)\n",
" print(f\" rel_diff={rel_diff}\")\n",
"print(f\"Total number of differing elements: {diff_mask.sum()}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a616770f",
"metadata": {},
"outputs": [],
"source": []
}
],
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"language": "python",
"name": "python3"
},
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"duration": 38459.845197,
"end_time": "2025-05-10T06:54:52.825666",
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