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Add NDPointIndex example (#285)
* add NDPointIndex example * add style.css * finalize example * add history.md entry * remove logo-size from style.css
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‎docs/_static/style.css‎

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/*
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Added as suggested by @benbovy to fix issues with dark mode
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*/
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code.literal {
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background-color: unset;
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border: unset;
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}
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.xr-wrap {
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/* workaround when (ipy)widgets are present in output cells
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* https://github.com/xarray-contrib/xarray-indexes/issues/14
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* only rely on pydata-sphinx-theme variables here!
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*/
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--xr-font-color0: var(--pst-color-text-base);
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--xr-font-color2: var(--pst-color-text-base);
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--xr-font-color3: var(--pst-color-text-base);
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--xr-border-color: hsl(from var(--pst-color-text-base) h s calc(l + 40));
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--xr-disabled-color: hsl(from var(--pst-color-text-base) h s calc(l + 40));
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--xr-background-color: var(--pst-color-on-background);
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--xr-background-color-row-even: hsl(
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from var(--pst-color-on-background) h s calc(l - 5)
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);
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--xr-background-color-row-odd: hsl(
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from var(--pst-color-on-background) h s calc(l - 15)
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);
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font-size: 0.9em;
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margin-left: 1.25em;
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}
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html[data-theme="dark"] .xr-wrap {
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--xr-border-color: hsl(from var(--pst-color-text-base) h s calc(l - 40));
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--xr-disabled-color: hsl(from var(--pst-color-text-base) h s calc(l - 40));
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--xr-background-color-row-even: hsl(
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from var(--pst-color-on-background) h s calc(l + 5)
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);
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--xr-background-color-row-odd: hsl(
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from var(--pst-color-on-background) h s calc(l + 15)
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);
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}
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.xr-array-wrap,
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.xr-var-data,
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.xr-var-preview {
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/* font-size: 0.9em; */
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}
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.gp {
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color: darkorange;
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}
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/* workaround Pydata Sphinx theme using light colors for widget cell outputs in dark-mode */
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/* works for many widgets but not for Xarray html reprs */
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/* https://github.com/pydata/pydata-sphinx-theme/issues/2189 */
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html[data-theme="dark"] div.cell_output .text_html:has(div.xr-wrap) {
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background-color: var(--pst-color-on-background) !important;
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color: var(--pst-color-text-base) !important;
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}

‎docs/conf.py‎

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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ["_static"]
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html_css_files = ["style.css"]
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favicons = [
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{

‎docs/history.md‎

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* FIX: Prevent literal timedelta decoding for new xarray versions, fix tests, update pinnings ({pull}`278`) by [@kmuehlbauer](https://github.com/kmuehlbauer).
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* MNT: Package and Documentation cleanup ({issue}`273`), {pull}`284`) by [@kmuehlbauer](https://github.com/kmuehlbauer).
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* ADD: Support Universal Format (UF) ({issue}`275`) ({pull}`276`) by [@kmuehlbauer](https://github.com/kmuehlbauer).
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* ADD: NDPointIndex Notebook example ({pull}`276`) by [@kmuehlbauer](https://github.com/kmuehlbauer).
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## 0.9.0 (2025-02-07)
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‎docs/usage.md‎

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notebooks/Read-plot-Sigmet-data-from-AWS
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notebooks/plot-ppi
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notebooks/angle_reindexing
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notebooks/NDPointIndex.ipynb
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notebooks/Multi-Volume-Concatenation.ipynb
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notebooks/multiple-sweeps-into-volume-scan.ipynb
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notebooks/Transform

‎examples/notebooks/NDPointIndex.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "0",
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"metadata": {},
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"source": [
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"# NDPointIndex\n",
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"\n",
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"This uses one of the new indexes xarray is providing. See [xarray-indexes](https://xarray-indexes.readthedocs.io/) for more in-depth details on that.\n",
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"\n",
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"Needs latest xarray '2025.7.1'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1",
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"metadata": {},
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"outputs": [],
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"source": [
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"import cmweather # noqa\n",
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"import numpy as np\n",
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"import xarray as xr\n",
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"from open_radar_data import DATASETS"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2",
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"metadata": {},
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"outputs": [],
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"source": [
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"xr.__version__"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3",
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"metadata": {},
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"source": [
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"# Step-by-step guide"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4",
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"metadata": {},
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"source": [
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"## Load radar data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5",
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"metadata": {},
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"outputs": [],
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"source": [
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"fname = DATASETS.fetch(\"DWD-Vol-2_99999_20180601054047_00.h5\")\n",
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"ds = xr.open_dataset(fname, engine=\"gamic\", group=\"sweep_9\")\n",
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"display(ds)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6",
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"metadata": {},
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"source": [
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"## Georeference\n",
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"\n",
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"Add x,y,z - 2D-coordinates."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7",
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"metadata": {},
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"outputs": [],
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"source": [
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"ds = ds.xradar.georeference()\n",
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"display(ds)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8",
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"metadata": {},
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"source": [
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"## Add NDPointIndex\n",
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"\n",
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"This uses scipy.KDTree under the hood. See also Indexes-Section in the html-repr below."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9",
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"metadata": {},
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"outputs": [],
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"source": [
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"ds = ds.set_xindex((\"x\", \"y\"), xr.indexes.NDPointIndex)\n",
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"display(ds)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "10",
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"metadata": {},
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"source": [
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"## Plot\n",
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"\n",
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"This works as usual with the new NDPointIndex."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "11",
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"metadata": {},
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"outputs": [],
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"source": [
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"ds.DBZH.plot(\n",
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" x=\"x\", y=\"y\", xlim=(-10e3, 10e3), ylim=(-10e3, 10e3), cmap=\"HomeyerRainbow\", vmin=0\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "12",
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"metadata": {},
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"source": [
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"## Nearest neighbour interpolation with NDPointIndex\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "13",
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"metadata": {},
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"source": [
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"### Create 1D DataArrays for x and y selection"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "14",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = xr.DataArray(np.arange(-100e3, 100e3, 500), dims=\"y\", name=\"y\", attrs=ds.y.attrs)\n",
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"x = xr.DataArray(np.arange(-100e3, 100e3, 500), dims=\"x\", name=\"x\", attrs=ds.x.attrs)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "15",
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"metadata": {},
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"source": [
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"### Select with above 1D DataArrays"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "16",
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"metadata": {},
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"outputs": [],
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"source": [
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"actual = ds.sel(y=y, x=x, method=\"nearest\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "17",
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"metadata": {},
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"source": [
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"### Assign the 1D DataArrays"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "18",
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"metadata": {},
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"outputs": [],
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"source": [
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"actual = actual.assign(x=x, y=y)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "19",
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"metadata": {},
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"outputs": [],
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"source": [
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"display(actual)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "20",
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"metadata": {},
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"source": [
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"## Plot cartesian representation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "21",
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"metadata": {},
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"outputs": [],
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"source": [
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"actual.DBZH.plot(xlim=(-10e3, 10e3), ylim=(-10e3, 10e3), cmap=\"HomeyerRainbow\", vmin=0)"
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]
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}
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],
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"metadata": {
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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