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keewis/tmp_test_notebook.ipynb

Created May 16, 2025 13:55
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tmp_test_notebook.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "0",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import xarray as xr\n",
"import xdggs\n",
"import cdshealpix.nested\n",
"import astropy.coordinates as ac"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "57728701-982a-4cda-9213-713b99c2fa18",
"metadata": {},
"outputs": [],
"source": [
"import shapely"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "1",
"metadata": {},
"outputs": [],
"source": [
"ZOOM = 4\n",
"N = int(10e6)\n",
"da = xr.DataArray(\n",
" data=np.arange(N),\n",
" dims=(\"cell_ids\",),\n",
" coords={\n",
" \"cell_ids\": (\n",
" \"cell_ids\",\n",
" np.arange(N),\n",
" {\"grid_name\": \"healpix\", \"level\": ZOOM, \"indexing_scheme\": \"nested\"},\n",
" )\n",
" },\n",
").dggs.decode()\n",
"\n",
"\n",
"def sel_and_decode(da, cell_ids):\n",
" da = da.copy()\n",
"\n",
" return da.sel(\n",
" cell_ids=cell_ids,\n",
" ).dggs.decode()\n",
"\n",
"\n",
"def get_cell_ids(lon_lat_list: list[tuple[float, float]], zoom: int):\n",
" lon = ac.Longitude(lon_lat_list[:, 0], unit=\"deg\")\n",
" lat = ac.Latitude(lon_lat_list[:, 1], unit=\"deg\")\n",
" cell_ids, _, _ = cdshealpix.nested.polygon_search(lon, lat,\n",
" zoom,\n",
" flat=True,\n",
" )\n",
"\n",
" return cell_ids\n",
"\n",
"\n",
"def lon_lat_to_xyz(lon_lat: tuple[float, float]) -> tuple[float, float, float]:\n",
" # https://en.wikipedia.org/wiki/Spherical_coordinate_system\n",
" r = 1\n",
" lat, lon = lon_lat\n",
" lat = np.radians(lat)\n",
" lon = np.radians(lon)\n",
" x = r * np.cos(lat) * np.cos(lon)\n",
" y = r * np.cos(lat) * np.sin(lon)\n",
" z = r * np.sin(lat)\n",
" return x, y, z\n",
"\n",
"\n",
"def get_aus_bbox():\n",
" return (113.338953078, -43.6345972634, 153.569469029, -10.6681857235)\n",
"\n",
"polygon = shapely.box(*get_aus_bbox()).segmentize(0.1)\n",
"POLYGON = shapely.get_coordinates(polygon)\n",
"\n",
"cells = get_cell_ids(POLYGON, ZOOM)\n",
"cells1 = np.array(\n",
" [\n",
" 1344,\n",
" 1345,\n",
" 1347,\n",
" 1348,\n",
" 1349,\n",
" 1350,\n",
" 2492,\n",
" 2493,\n",
" 2495,\n",
" 2530,\n",
" 2531,\n",
" 2536,\n",
" 2537,\n",
" 2538,\n",
" 2539,\n",
" 2540,\n",
" 2542,\n",
" 2543,\n",
" ],\n",
" dtype=np.uint64,\n",
")\n",
"\n",
"da_truth = sel_and_decode(da, cells)\n",
"da1 = sel_and_decode(da, cells1)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "221ad3ce-648e-4741-87b2-c21c0db2a57b",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (cell_ids: 18)&gt; Size: 144B\n",
"array([1344, 1345, 1347, 1348, 1349, 1350, 2492, 2493, 2495, 2530, 2531,\n",
" 2536, 2537, 2538, 2539, 2540, 2542, 2543])\n",
"Coordinates:\n",
" * cell_ids (cell_ids) int64 144B 1344 1345 1347 1348 ... 2539 2540 2542 2543\n",
"Indexes:\n",
" cell_ids HealpixIndex(level=4, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>cell_ids</span>: 18</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-10f12661-65ff-4865-a91b-db8336424d1d' class='xr-array-in' type='checkbox' checked><label for='section-10f12661-65ff-4865-a91b-db8336424d1d' 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>1344 1345 1347 1348 1349 1350 2492 ... 2537 2538 2539 2540 2542 2543</span></div><div class='xr-array-data'><pre>array([1344, 1345, 1347, 1348, 1349, 1350, 2492, 2493, 2495, 2530, 2531,\n",
" 2536, 2537, 2538, 2539, 2540, 2542, 2543])</pre></div></div></li><li class='xr-section-item'><input id='section-63c36c07-0ac2-4a32-914f-d5b7a8623d4b' class='xr-section-summary-in' type='checkbox' checked><label for='section-63c36c07-0ac2-4a32-914f-d5b7a8623d4b' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cell_ids)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1344 1345 1347 ... 2540 2542 2543</div><input id='attrs-2795aa39-9539-4380-86c4-1dff8a54fdbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2795aa39-9539-4380-86c4-1dff8a54fdbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9b16a96-fd57-4595-8e06-85f9013ca393' class='xr-var-data-in' type='checkbox'><label for='data-b9b16a96-fd57-4595-8e06-85f9013ca393' 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>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>4</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([1344, 1345, 1347, 1348, 1349, 1350, 2492, 2493, 2495, 2530, 2531, 2536,\n",
" 2537, 2538, 2539, 2540, 2542, 2543])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f981f53-0358-4b95-96f7-4612dd0f987b' class='xr-section-summary-in' type='checkbox' ><label for='section-0f981f53-0358-4b95-96f7-4612dd0f987b' 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>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(level=4, indexing_scheme=nested)</div><input type='checkbox' disabled/><label></label><input id='index-a5e5ff5a-ec4d-4b4a-980c-9586b2b3e49b' class='xr-index-data-in' type='checkbox'/><label for='index-a5e5ff5a-ec4d-4b4a-980c-9586b2b3e49b' 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>&lt;xdggs.healpix.HealpixIndex object at 0x7cbfabd01b20&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fe767012-0e2f-4889-b706-96c4ec09cdc8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fe767012-0e2f-4889-b706-96c4ec09cdc8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray (cell_ids: 18)> Size: 144B\n",
"array([1344, 1345, 1347, 1348, 1349, 1350, 2492, 2493, 2495, 2530, 2531,\n",
" 2536, 2537, 2538, 2539, 2540, 2542, 2543])\n",
"Coordinates:\n",
" * cell_ids (cell_ids) int64 144B 1344 1345 1347 1348 ... 2539 2540 2542 2543\n",
"Indexes:\n",
" cell_ids HealpixIndex(level=4, indexing_scheme=nested)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"da1"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "f23d4d3b-6d84-4647-95f3-993a68c4cfb8",
"metadata": {},
"outputs": [],
"source": [
"import lonboard\n",
"import geoarrow.rust.core as geoarrow\n",
"from arro3.core import Array, Schema, Table"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "924b5942-68a2-478a-97b8-b969e8c5fcf3",
"metadata": {},
"outputs": [],
"source": [
"def add_polygon(map, polygon):\n",
" arr = Array.from_arrow(geoarrow.from_shapely(np.array([polygon])))\n",
" arrays = {\"geometry\": arr}\n",
" fields = [array.field.with_name(name) for name, array in arrays.items()]\n",
" schema = Schema(fields)\n",
"\n",
" table = Table.from_arrays(list(arrays.values()), schema=schema)\n",
" layer = lonboard.PolygonLayer(table=table, get_line_width=2, get_line_color=\"red\", get_fill_color=[0, 0, 0, 180])\n",
"\n",
" map.layers = (layer, *map.layers)\n",
" return map\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c7488da0-50b4-4938-b6fe-57bffd45ab4a",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jmagin/.local/opt/mambaforge/envs/cdshealpix/lib/python3.12/site-packages/lonboard/_geoarrow/ops/reproject.py:33: UserWarning: No CRS exists on data. If no data is shown on the map, double check that your CRS is WGS84.\n",
" warn(\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "77ad6fbbb45e4690b46220f6af75440c",
"version_major": 2,
"version_minor": 1
},
"text/plain": [
"Map(custom_attribution='', layers=(PolygonLayer(get_fill_color=[0, 0, 0, 180], get_line_color=(255, 0, 0, 255)…"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"map = da_truth.dggs.explore(alpha=0.7)\n",
"add_polygon(map, polygon)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "3",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jmagin/.local/opt/mambaforge/envs/cdshealpix/lib/python3.12/site-packages/lonboard/_geoarrow/ops/reproject.py:33: UserWarning: No CRS exists on data. If no data is shown on the map, double check that your CRS is WGS84.\n",
" warn(\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5b8e2bb7cc5144d2bf2a5fa1806bd224",
"version_major": 2,
"version_minor": 1
},
"text/plain": [
"Map(custom_attribution='', layers=(PolygonLayer(get_fill_color=[0, 0, 0, 180], get_line_color=(255, 0, 0, 255)…"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"map = da1.dggs.explore()\n",
"add_polygon(map, polygon)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "4a45abf1-98d6-45c2-b806-cec1165d5763",
"metadata": {},
"outputs": [],
"source": [
"import healpix_geo"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "39ddafb9-a86c-43bd-80a9-409ee2d58272",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[153.56946903, -43.63459726],\n",
" [153.56946903, -43.53469905],\n",
" [153.56946903, -43.43480083],\n",
" ...,\n",
" [153.36981386, -43.63459726],\n",
" [153.46964145, -43.63459726],\n",
" [153.56946903, -43.63459726]], shape=(1467, 2))"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"POLYGON"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "b564072a-0417-4913-b129-a167e2cc96c9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"dtype('int64')"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"da[\"cell_ids\"].data"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "74111a36-77ef-41ff-a566-f025fad3f8ca",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[153.56946903, -43.63459726],\n",
" [153.56946903, -43.53469905],\n",
" [153.56946903, -43.43480083],\n",
" ...,\n",
" [153.36981386, -43.63459726],\n",
" [153.46964145, -43.63459726],\n",
" [153.56946903, -43.63459726]], shape=(1467, 2))"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"POLYGON"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "8043174d-3bff-4a3a-b825-9cb8463f9daa",
"metadata": {},
"outputs": [],
"source": [
"box = shapely.box(*get_aus_bbox())\n",
"polygon_ = shapely.get_coordinates(box)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "b0c25090-725d-444a-98cd-71a6ee58c097",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[153.56946903, -43.63459726],\n",
" [153.56946903, -10.66818572],\n",
" [113.33895308, -10.66818572],\n",
" [113.33895308, -43.63459726],\n",
" [153.56946903, -43.63459726]])"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"polygon_"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "20b82cd5-3380-48bf-9dfa-a02cb638733a",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"thread '<unnamed>' panicked at /home/jmagin/.cargo/registry/src/index.crates.io-1949cf8c6b5b557f/cdshealpix-0.7.3/src/special_points_finder.rs:459:3:\n",
"p1: (153.56946902900003, -43.6345972634); p2: (153.56946902900003, -41.810314895778596)\n"
]
},
{
"ename": "PanicException",
"evalue": "p1: (153.56946902900003, -43.6345972634); p2: (153.56946902900003, -41.810314895778596)",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mPanicException\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[29], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mhealpix_geo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mselect\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcells_in_polygon\u001b[49m\u001b[43m(\u001b[49m\u001b[43mda\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcell_ids\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43muint64\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mda\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdggs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgrid_info\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpolygon_\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
"\u001b[0;31mPanicException\u001b[0m: p1: (153.56946902900003, -43.6345972634); p2: (153.56946902900003, -41.810314895778596)"
]
}
],
"source": [
"healpix_geo.select.cells_in_polygon(da[\"cell_ids\"].data.astype(\"uint64\"), da.dggs.grid_info.level, polygon_[:-1, ::-1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a6fd9a1a-f035-4bc6-ad95-a95437c19f46",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.12.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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