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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "provenance": [] | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "TDkiljIpRhpT", | |
| "outputId": "b5bff5df-22b0-48fa-b2f5-2c579113f18e" | |
| }, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Collecting git+https://github.com/DLR-terrabyte/pygeofilter-duckdb.git\n", | |
| " Cloning https://github.com/DLR-terrabyte/pygeofilter-duckdb.git to /tmp/pip-req-build-u30549d1\n", | |
| " Running command git clone --filter=blob:none --quiet https://github.com/DLR-terrabyte/pygeofilter-duckdb.git /tmp/pip-req-build-u30549d1\n", | |
| " Resolved https://github.com/DLR-terrabyte/pygeofilter-duckdb.git to commit aeaaa14fd8e59b688e3cfd32dbd2cc8e3f5ef2eb\n", | |
| " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", | |
| " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", | |
| " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", | |
| "Requirement already satisfied: duckdb==1.0.0 in /usr/local/lib/python3.12/dist-packages (1.0.0)\n", | |
| "Requirement already satisfied: stac-geoparquet in /usr/local/lib/python3.12/dist-packages (0.7.0)\n", | |
| "Requirement already satisfied: ciso8601 in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (2.3.3)\n", | |
| "Requirement already satisfied: deltalake in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (1.1.4)\n", | |
| "Requirement already satisfied: geopandas in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (1.1.1)\n", | |
| "Requirement already satisfied: orjson in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (3.11.2)\n", | |
| "Requirement already satisfied: packaging in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (25.0)\n", | |
| "Requirement already satisfied: pandas in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (2.2.2)\n", | |
| "Requirement already satisfied: pyarrow!=19.0.0,>=16 in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (18.1.0)\n", | |
| "Requirement already satisfied: pyproj in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (3.7.2)\n", | |
| "Requirement already satisfied: pystac in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (1.13.0)\n", | |
| "Requirement already satisfied: shapely in /usr/local/lib/python3.12/dist-packages (from stac-geoparquet) (2.1.1)\n", | |
| "Requirement already satisfied: pygeofilter>=0.2.4 in /usr/local/lib/python3.12/dist-packages (from pygeofilter-duckdb==1.0) (0.3.1)\n", | |
| "Requirement already satisfied: dateparser in /usr/local/lib/python3.12/dist-packages (from pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (1.2.2)\n", | |
| "Requirement already satisfied: lark in /usr/local/lib/python3.12/dist-packages (from pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (1.2.2)\n", | |
| "Requirement already satisfied: pygeoif>=1.0.0 in /usr/local/lib/python3.12/dist-packages (from pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (1.5.1)\n", | |
| "Requirement already satisfied: arro3-core>=0.5.0 in /usr/local/lib/python3.12/dist-packages (from deltalake->stac-geoparquet) (0.6.1)\n", | |
| "Requirement already satisfied: deprecated>=1.2.18 in /usr/local/lib/python3.12/dist-packages (from deltalake->stac-geoparquet) (1.2.18)\n", | |
| "Requirement already satisfied: numpy>=1.24 in /usr/local/lib/python3.12/dist-packages (from geopandas->stac-geoparquet) (2.0.2)\n", | |
| "Requirement already satisfied: pyogrio>=0.7.2 in /usr/local/lib/python3.12/dist-packages (from geopandas->stac-geoparquet) (0.11.1)\n", | |
| "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas->stac-geoparquet) (2.9.0.post0)\n", | |
| "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas->stac-geoparquet) (2025.2)\n", | |
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| "Requirement already satisfied: certifi in /usr/local/lib/python3.12/dist-packages (from pyproj->stac-geoparquet) (2025.8.3)\n", | |
| "Requirement already satisfied: wrapt<2,>=1.10 in /usr/local/lib/python3.12/dist-packages (from deprecated>=1.2.18->deltalake->stac-geoparquet) (1.17.3)\n", | |
| "Requirement already satisfied: typing_extensions in /usr/local/lib/python3.12/dist-packages (from pygeoif>=1.0.0->pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (4.15.0)\n", | |
| "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas->stac-geoparquet) (1.17.0)\n", | |
| "Requirement already satisfied: regex>=2024.9.11 in /usr/local/lib/python3.12/dist-packages (from dateparser->pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (2024.11.6)\n", | |
| "Requirement already satisfied: tzlocal>=0.2 in /usr/local/lib/python3.12/dist-packages (from dateparser->pygeofilter>=0.2.4->pygeofilter-duckdb==1.0) (5.3.1)\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "!pip install duckdb==1.0.0 stac-geoparquet git+https://github.com/DLR-terrabyte/pygeofilter-duckdb.git" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!pip install odc-stac" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "Pwdxq_BbT7DT", | |
| "outputId": "8a2f74f0-cc93-48a0-99fc-0f52d41d35c3" | |
| }, | |
| "execution_count": 20, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Collecting odc-stac\n", | |
| " Downloading odc_stac-0.4.0-py3-none-any.whl.metadata (5.9 kB)\n", | |
| "Collecting affine (from odc-stac)\n", | |
| " Downloading affine-2.4.0-py3-none-any.whl.metadata (4.0 kB)\n", | |
| "Collecting odc-geo>=0.4.7 (from odc-stac)\n", | |
| " Downloading odc_geo-0.4.10-py3-none-any.whl.metadata (6.1 kB)\n", | |
| "Collecting odc-loader>=0.5.1 (from odc-stac)\n", | |
| " Downloading odc_loader-0.5.1-py3-none-any.whl.metadata (1.3 kB)\n", | |
| "Collecting rasterio!=1.3.0,!=1.3.1,>=1.0.0 (from odc-stac)\n", | |
| " Downloading rasterio-1.4.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (9.1 kB)\n", | |
| "Requirement already satisfied: dask[array] in /usr/local/lib/python3.12/dist-packages (from odc-stac) (2025.5.0)\n", | |
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| "Requirement already satisfied: cachetools in /usr/local/lib/python3.12/dist-packages (from odc-geo>=0.4.7->odc-stac) (5.5.2)\n", | |
| "Requirement already satisfied: pyproj>=3.0.0 in /usr/local/lib/python3.12/dist-packages (from odc-geo>=0.4.7->odc-stac) (3.7.2)\n", | |
| "Requirement already satisfied: shapely in /usr/local/lib/python3.12/dist-packages (from odc-geo>=0.4.7->odc-stac) (2.1.1)\n", | |
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| "Requirement already satisfied: attrs in /usr/local/lib/python3.12/dist-packages (from rasterio!=1.3.0,!=1.3.1,>=1.0.0->odc-stac) (25.3.0)\n", | |
| "Requirement already satisfied: certifi in /usr/local/lib/python3.12/dist-packages (from rasterio!=1.3.0,!=1.3.1,>=1.0.0->odc-stac) (2025.8.3)\n", | |
| "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.12/dist-packages (from rasterio!=1.3.0,!=1.3.1,>=1.0.0->odc-stac) (8.2.1)\n", | |
| "Collecting cligj>=0.5 (from rasterio!=1.3.0,!=1.3.1,>=1.0.0->odc-stac)\n", | |
| " Downloading cligj-0.7.2-py3-none-any.whl.metadata (5.0 kB)\n", | |
| "Collecting click-plugins (from rasterio!=1.3.0,!=1.3.1,>=1.0.0->odc-stac)\n", | |
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| "Downloading odc_stac-0.4.0-py3-none-any.whl (44 kB)\n", | |
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| "\u001b[?25hDownloading affine-2.4.0-py3-none-any.whl (15 kB)\n", | |
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| "Downloading click_plugins-1.1.1.2-py2.py3-none-any.whl (11 kB)\n", | |
| "Installing collected packages: cligj, click-plugins, affine, rasterio, odc-geo, odc-loader, odc-stac\n", | |
| "Successfully installed affine-2.4.0 click-plugins-1.1.1.2 cligj-0.7.2 odc-geo-0.4.10 odc-loader-0.5.1 odc-stac-0.4.0 rasterio-1.4.3\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import json\n", | |
| "import pystac\n", | |
| "import duckdb\n", | |
| "from stac_geoparquet.arrow._api import stac_table_to_items\n", | |
| "\n", | |
| "# Install and load DuckDB spatial extension\n", | |
| "duckdb.install_extension('spatial')\n", | |
| "duckdb.load_extension('spatial')\n", | |
| "\n", | |
| "# Use pygeofilter library to convert between CQL2-JSON/Text and SQL query\n", | |
| "from pygeofilter.parsers.cql2_json import parse as json_parse\n", | |
| "from pygeofilter.backends.duckdb import to_sql_where\n", | |
| "from pygeofilter.util import IdempotentDict" | |
| ], | |
| "metadata": { | |
| "id": "4Kj0glUNRouM" | |
| }, | |
| "execution_count": 2, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "minx, miny, maxx, maxy = (132.0, -25.0, 136.0, -20.0)" | |
| ], | |
| "metadata": { | |
| "id": "gp_oaNR0SQQy" | |
| }, | |
| "execution_count": 3, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "url = \"s3://deant-data-public-dev/experimental/for_zhengshu/geoparquet_partitioned.parquet/**/*.parquet\"" | |
| ], | |
| "metadata": { | |
| "id": "f6g5c_KPSefz" | |
| }, | |
| "execution_count": 4, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "start = '2025-01-01T00:00:00Z'\n", | |
| "end = '2025-02-01T23:59:59Z'\n", | |
| "\n", | |
| "cql2_filter = {\n", | |
| " \"op\": \"and\",\n", | |
| " \"args\": [\n", | |
| " # {\n", | |
| " # \"op\": \"between\",\n", | |
| " # \"args\": [\n", | |
| " # {\n", | |
| " # \"property\": \"eo:cloud_cover\"\n", | |
| " # },\n", | |
| " # [0, 21]\n", | |
| " # ]\n", | |
| " # },\n", | |
| " {\n", | |
| " \"op\": \"between\",\n", | |
| " \"args\": [\n", | |
| " {\n", | |
| " \"property\": \"datetime\"\n", | |
| " },\n", | |
| " [start, end]\n", | |
| " ]\n", | |
| " },\n", | |
| " {\n", | |
| " \"op\": \"s_intersects\",\n", | |
| " \"args\": [\n", | |
| " { \"property\": \"geometry\" } ,\n", | |
| " {\n", | |
| " \"type\": \"Polygon\",\n", | |
| " \"coordinates\": [[\n", | |
| " [minx, miny],\n", | |
| " [maxx, miny],\n", | |
| " [maxx, maxy],\n", | |
| " [minx, maxy],\n", | |
| " [minx, miny],\n", | |
| " ]]\n", | |
| " }\n", | |
| " ]\n", | |
| " }\n", | |
| " ]\n", | |
| "}\n", | |
| "\n", | |
| "sql_where = to_sql_where(json_parse(cql2_filter), IdempotentDict())" | |
| ], | |
| "metadata": { | |
| "id": "FSI7hZo_RyCT" | |
| }, | |
| "execution_count": 5, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "%%time\n", | |
| "# Note: union_by_name slows down the query process, but is necessary when there are properties not available in all STAC items\n", | |
| "sql_query = f\"SELECT * FROM read_parquet('{url}', union_by_name=False) WHERE {sql_where}\"\n", | |
| "print(f\"DuckDB Query:\\n{sql_query}\\n\")\n", | |
| "db = duckdb.query(sql_query)" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "rIWgy43OSZ7j", | |
| "outputId": "13eb0a37-1b31-43a2-ac45-4f6d5568f5cb" | |
| }, | |
| "execution_count": 6, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "DuckDB Query:\n", | |
| "SELECT * FROM read_parquet('s3://deant-data-public-dev/experimental/for_zhengshu/geoparquet_partitioned.parquet/**/*.parquet', union_by_name=False) WHERE ((\"datetime\" BETWEEN '2025-01-01T00:00:00Z' AND '2025-02-01T23:59:59Z') AND ST_Intersects(ST_GeomFromWKB(geometry),ST_GeomFromHEXEWKB('01030000000100000005000000000000000080604000000000000039C0000000000000614000000000000039C0000000000000614000000000000034C0000000000080604000000000000034C0000000000080604000000000000039C0')))\n", | |
| "\n", | |
| "CPU times: user 271 ms, sys: 26.1 ms, total: 297 ms\n", | |
| "Wall time: 2.63 s\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "%%time\n", | |
| "## Convert DuckDB result to Arrow table\n", | |
| "table = db.fetch_arrow_table()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 84, | |
| "referenced_widgets": [ | |
| "2696bfc8435643a0809e6b2267067743", | |
| "b7e80444235747e8bdaac5579bb54720", | |
| "689d06677db84c05996a5e20142436c9" | |
| ] | |
| }, | |
| "id": "_89zSiwVSoDL", | |
| "outputId": "1a975478-5241-4c5e-b4c6-5dd1f4dedf83" | |
| }, | |
| "execution_count": 7, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "2696bfc8435643a0809e6b2267067743" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "CPU times: user 1.52 s, sys: 405 ms, total: 1.93 s\n", | |
| "Wall time: 1min 50s\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "%%time\n", | |
| "## Convert Arrow table to List of PyStac-Items\n", | |
| "items = []\n", | |
| "for item in stac_table_to_items(table):\n", | |
| " items.append(pystac.Item.from_dict(item))\n", | |
| "\n", | |
| "print(\"%s items found\\n\" % len(items))" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "C5fyougyStPD", | |
| "outputId": "e78115af-bd99-4e4b-d1b6-c78eeb7e3844" | |
| }, | |
| "execution_count": 9, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "216 items found\n", | |
| "\n", | |
| "CPU times: user 562 ms, sys: 10.5 ms, total: 573 ms\n", | |
| "Wall time: 575 ms\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from odc.stac import load\n", | |
| "data = load(items, bbox=[minx, miny, maxx, maxy], crs=\"utm\", resolution=250, chunks={})\n", | |
| "data" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 536 | |
| }, | |
| "id": "mL5sQ9uUTeVZ", | |
| "outputId": "58e59026-aec9-46c2-d5de-a60d1c6638fa" | |
| }, | |
| "execution_count": 17, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "<xarray.Dataset> Size: 26GB\n", | |
| "Dimensions: (y: 2227, x: 1675, time: 216)\n", | |
| "Coordinates:\n", | |
| " * y (y) float64 18kB 7.788e+06 7.788e+06 ... 7.232e+06\n", | |
| " * x (x) float64 13kB 1.861e+05 1.864e+05 ... 6.046e+05\n", | |
| " spatial_ref int32 4B 32753\n", | |
| " * time (time) datetime64[ns] 2kB 2025-01-04T20:34:27.837...\n", | |
| "Data variables:\n", | |
| " VH_gamma0 (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " VV_gamma0 (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
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| " mask (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
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| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2,\n", | |
| ".xr-no-icon {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n", | |
| ".xr-var-data-in:checked + label > .xr-icon-database,\n", | |
| ".xr-index-data-in:checked + label > .xr-icon-database {\n", | |
| " color: var(--xr-font-color0);\n", | |
| " filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n", | |
| " stroke-width: 0.8px;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 26GB\n", | |
| "Dimensions: (y: 2227, x: 1675, time: 216)\n", | |
| "Coordinates:\n", | |
| " * y (y) float64 18kB 7.788e+06 7.788e+06 ... 7.232e+06\n", | |
| " * x (x) float64 13kB 1.861e+05 1.864e+05 ... 6.046e+05\n", | |
| " spatial_ref int32 4B 32753\n", | |
| " * time (time) datetime64[ns] 2kB 2025-01-04T20:34:27.837...\n", | |
| "Data variables:\n", | |
| " VH_gamma0 (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " VV_gamma0 (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " gamma0_to_beta0_ratio (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " gamma0_to_sigma0_ratio (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " incidence_angle (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " local_incidence_angle (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " mask (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray>\n", | |
| " number_of_looks (time, y, x) float32 3GB dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></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-1c20a018-e08f-46fe-b3e9-8a2fded73515' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1c20a018-e08f-46fe-b3e9-8a2fded73515' 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'>y</span>: 2227</li><li><span class='xr-has-index'>x</span>: 1675</li><li><span class='xr-has-index'>time</span>: 216</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e283587a-e71b-47eb-821f-8e3544829534' class='xr-section-summary-in' type='checkbox' checked><label for='section-e283587a-e71b-47eb-821f-8e3544829534' 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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.788e+06 7.788e+06 ... 7.232e+06</div><input id='attrs-8e822026-72cf-4316-90ba-536075aef496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e822026-72cf-4316-90ba-536075aef496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65d638ed-9c25-4ff9-a864-9720e55271f4' class='xr-var-data-in' type='checkbox'><label for='data-65d638ed-9c25-4ff9-a864-9720e55271f4' 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>metre</dd><dt><span>resolution :</span></dt><dd>-250.0</dd><dt><span>crs :</span></dt><dd>EPSG:32753</dd></dl></div><div class='xr-var-data'><pre>array([7788125., 7787875., 7787625., ..., 7232125., 7231875., 7231625.])</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'>1.861e+05 1.864e+05 ... 6.046e+05</div><input id='attrs-de50da39-0b65-4c41-a4c2-98df97810fd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de50da39-0b65-4c41-a4c2-98df97810fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d316d1f-ff1d-48c1-8125-d965182bd9a1' class='xr-var-data-in' type='checkbox'><label for='data-4d316d1f-ff1d-48c1-8125-d965182bd9a1' 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>metre</dd><dt><span>resolution :</span></dt><dd>250.0</dd><dt><span>crs :</span></dt><dd>EPSG:32753</dd></dl></div><div class='xr-var-data'><pre>array([186125., 186375., 186625., ..., 604125., 604375., 604625.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32753</div><input id='attrs-d02853b4-2ed1-482a-9752-40250a4c913c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d02853b4-2ed1-482a-9752-40250a4c913c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8948f56f-ea2e-4e9f-a6ce-9053774a6c4b' class='xr-var-data-in' type='checkbox'><label for='data-8948f56f-ea2e-4e9f-a6ce-9053774a6c4b' 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>spatial_ref :</span></dt><dd>PROJCRS["WGS 84 / UTM zone 53S",BASEGEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],MEMBER["World Geodetic System 1984 (G2296)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],ID["EPSG",4326]],CONVERSION["UTM zone 53S",METHOD["Transverse Mercator",ID["EPSG",9807]],PARAMETER["Latitude of natural origin",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",135,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["Scale factor at natural origin",0.9996,SCALEUNIT["unity",1],ID["EPSG",8805]],PARAMETER["False easting",500000,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",10000000,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1]],USAGE[SCOPE["Navigation and medium accuracy spatial referencing."],AREA["Between 132°E and 138°E, southern hemisphere between 80°S and equator, onshore and offshore. Australia. Indonesia."],BBOX[-80,132,0,138]],ID["EPSG",32753]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS["WGS 84 / UTM zone 53S",BASEGEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],MEMBER["World Geodetic System 1984 (G2296)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],ID["EPSG",4326]],CONVERSION["UTM zone 53S",METHOD["Transverse Mercator",ID["EPSG",9807]],PARAMETER["Latitude of natural origin",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",135,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["Scale factor at natural origin",0.9996,SCALEUNIT["unity",1],ID["EPSG",8805]],PARAMETER["False easting",500000,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",10000000,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1]],USAGE[SCOPE["Navigation and medium accuracy spatial referencing."],AREA["Between 132°E and 138°E, southern hemisphere between 80°S and equator, onshore and offshore. Australia. Indonesia."],BBOX[-80,132,0,138]],ID["EPSG",32753]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 53S</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>135.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>10000000.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>GeoTransform :</span></dt><dd>186000 250 0 7788250 0 -250</dd></dl></div><div class='xr-var-data'><pre>array(32753, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-01-04T20:34:27.837650 ... 2...</div><input id='attrs-8a4fe1ca-f913-437f-bea0-cddeeb4203f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a4fe1ca-f913-437f-bea0-cddeeb4203f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32a580c5-f185-476b-9fd7-e21e8b458925' class='xr-var-data-in' type='checkbox'><label for='data-32a580c5-f185-476b-9fd7-e21e8b458925' 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(['2025-01-04T20:34:27.837650000', '2025-01-04T20:34:30.596206000',\n", | |
| " '2025-01-04T20:34:31.541762000', ..., '2025-01-28T20:35:10.399997000',\n", | |
| " '2025-01-28T20:35:11.343498000', '2025-01-28T20:35:12.301386000'],\n", | |
| " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3010c63c-b30b-49f8-ba01-deedfaf5fb62' class='xr-section-summary-in' type='checkbox' checked><label for='section-3010c63c-b30b-49f8-ba01-deedfaf5fb62' class='xr-section-summary' >Data variables: <span>(8)</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>VH_gamma0</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-e7b733b7-1f06-4a7a-9602-b51d50d23434' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7b733b7-1f06-4a7a-9602-b51d50d23434' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-131723a7-cc98-4d29-8e18-3a4f2d17d74d' class='xr-var-data-in' type='checkbox'><label for='data-131723a7-cc98-4d29-8e18-3a4f2d17d74d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
| " <svg width=\"172\" height=\"192\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"10\" y1=\"120\" x2=\"32\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"121\" />\n", | |
| " <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"122\" />\n", | |
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| "\n", | |
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| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"100\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
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| " <line x1=\"32\" y1=\"22\" x2=\"122\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"100\" y1=\"0\" x2=\"122\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
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| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"122\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"32\" y1=\"142\" x2=\"122\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"122\" y1=\"22\" x2=\"122\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
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| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"77.732026\" y=\"162.604051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1675</text>\n", | |
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| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VV_gamma0</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-1824dc7a-8bd5-4e7c-a838-d75666fb6f4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1824dc7a-8bd5-4e7c-a838-d75666fb6f4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-302e9830-76ca-4c80-a20f-a8822dc01e0b' class='xr-var-data-in' type='checkbox'><label for='data-302e9830-76ca-4c80-a20f-a8822dc01e0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </tbody>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma0_to_beta0_ratio</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-e8eb46a7-e0be-48f6-805e-3ad18388569a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8eb46a7-e0be-48f6-805e-3ad18388569a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-770376cf-7f45-44dd-89f9-fa7b13a162b2' class='xr-var-data-in' type='checkbox'><label for='data-770376cf-7f45-44dd-89f9-fa7b13a162b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
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| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma0_to_sigma0_ratio</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-9f1d9917-45fd-426f-9a48-c5c9d0afad2d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9f1d9917-45fd-426f-9a48-c5c9d0afad2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9095bdd0-fa6f-4251-bf0e-acab5a0a9a37' class='xr-var-data-in' type='checkbox'><label for='data-9095bdd0-fa6f-4251-bf0e-acab5a0a9a37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>incidence_angle</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-6d50cc73-7b87-4052-ae2d-a1695bdb19ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d50cc73-7b87-4052-ae2d-a1695bdb19ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-083601a5-26d9-4f26-94d5-50c6ae0093a2' class='xr-var-data-in' type='checkbox'><label for='data-083601a5-26d9-4f26-94d5-50c6ae0093a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>local_incidence_angle</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-359b1763-7d35-4e3e-b8ec-7bc57d4dbb3e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-359b1763-7d35-4e3e-b8ec-7bc57d4dbb3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd88e9a7-5171-41c1-be91-d8905a70acaf' class='xr-var-data-in' type='checkbox'><label for='data-fd88e9a7-5171-41c1-be91-d8905a70acaf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
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| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-db13e76c-1cf3-443e-880c-d13fe6672dac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db13e76c-1cf3-443e-880c-d13fe6672dac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-230f918a-e5b9-450a-9757-019d8cff8c53' class='xr-var-data-in' type='checkbox'><label for='data-230f918a-e5b9-450a-9757-019d8cff8c53' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
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| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>number_of_looks</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2227, 1675), meta=np.ndarray></div><input id='attrs-e9a587dd-0082-4f4e-989c-16258defd94d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9a587dd-0082-4f4e-989c-16258defd94d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72b4763b-4f9b-4255-a93a-75679f4bff41' class='xr-var-data-in' type='checkbox'><label for='data-72b4763b-4f9b-4255-a93a-75679f4bff41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 3.00 GiB </td>\n", | |
| " <td> 14.23 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (216, 2227, 1675) </td>\n", | |
| " <td> (1, 2227, 1675) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 216 chunks in 3 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
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| " <text x=\"142.860001\" y=\"82.604051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,142.860001,82.604051)\">2227</text>\n", | |
| " <text x=\"11.302025\" y=\"151.302025\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.302025,151.302025)\">216</text>\n", | |
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| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7954962-f8e8-46ee-ac91-b119f5998376' class='xr-section-summary-in' type='checkbox' ><label for='section-e7954962-f8e8-46ee-ac91-b119f5998376' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5c18cf16-b756-4174-985d-f33bf44b6fd5' class='xr-index-data-in' type='checkbox'/><label for='index-5c18cf16-b756-4174-985d-f33bf44b6fd5' 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([7788125.0, 7787875.0, 7787625.0, 7787375.0, 7787125.0, 7786875.0,\n", | |
| " 7786625.0, 7786375.0, 7786125.0, 7785875.0,\n", | |
| " ...\n", | |
| " 7233875.0, 7233625.0, 7233375.0, 7233125.0, 7232875.0, 7232625.0,\n", | |
| " 7232375.0, 7232125.0, 7231875.0, 7231625.0],\n", | |
| " dtype='float64', name='y', length=2227))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3c97be58-7147-4b7b-8a7e-9b64a3bb9488' class='xr-index-data-in' type='checkbox'/><label for='index-3c97be58-7147-4b7b-8a7e-9b64a3bb9488' 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([186125.0, 186375.0, 186625.0, 186875.0, 187125.0, 187375.0, 187625.0,\n", | |
| " 187875.0, 188125.0, 188375.0,\n", | |
| " ...\n", | |
| " 602375.0, 602625.0, 602875.0, 603125.0, 603375.0, 603625.0, 603875.0,\n", | |
| " 604125.0, 604375.0, 604625.0],\n", | |
| " dtype='float64', name='x', length=1675))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7af00020-2729-484a-ad86-d9e04e397cdf' class='xr-index-data-in' type='checkbox'/><label for='index-7af00020-2729-484a-ad86-d9e04e397cdf' 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(['2025-01-04 20:34:27.837650', '2025-01-04 20:34:30.596206',\n", | |
| " '2025-01-04 20:34:31.541762', '2025-01-04 20:34:33.356818',\n", | |
| " '2025-01-04 20:34:34.300319', '2025-01-04 20:34:35.256152',\n", | |
| " '2025-01-04 20:34:36.115375', '2025-01-04 20:34:37.058875',\n", | |
| " '2025-01-04 20:34:38.014709', '2025-01-04 20:34:38.875987',\n", | |
| " ...\n", | |
| " '2025-01-28 20:35:04.027772', '2025-01-28 20:35:04.880828',\n", | |
| " '2025-01-28 20:35:05.826385', '2025-01-28 20:35:06.788384',\n", | |
| " '2025-01-28 20:35:07.639385', '2025-01-28 20:35:08.584941',\n", | |
| " '2025-01-28 20:35:09.544885', '2025-01-28 20:35:10.399997',\n", | |
| " '2025-01-28 20:35:11.343498', '2025-01-28 20:35:12.301386'],\n", | |
| " dtype='datetime64[ns]', name='time', length=216, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a1e3d6f3-9b5a-4e9f-ac5b-d6acbffc556a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a1e3d6f3-9b5a-4e9f-ac5b-d6acbffc556a' 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>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 17 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "data.VV_gamma0.isel(time=3).plot()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 504 | |
| }, | |
| "id": "o1RuUh_SUMp7", | |
| "outputId": "a1a8c400-3c5c-4871-eefe-20e749944462" | |
| }, | |
| "execution_count": 15, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x7d3cf0b67a70>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 15 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 640x480 with 2 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "LGsSqlthWAAS" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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