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DataTree tutorial with GPM_3IMERGHH_07 #307
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datatree imerghh_7 notebook
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,305 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "\n", | ||
| "# How to use `xarray.DataTree` with hierarchical data\n", | ||
| "\n", | ||
| "\n", | ||
| "## Overview: \n", | ||
| "\n", | ||
| "This notebook will demonstrate how to use `xarray.DataTree` with [_GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHH_07)_](https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_07/summary) and use xarray's plotting capabilities to plot precipitation in the Gulf of Mexico during Hurricane Ida. GPM_3IMERGHH_07 is a L3 gridded product with a group hierarchical structure." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import cartopy.crs as ccrs\n", | ||
| "import matplotlib.pyplot as plt\n", | ||
| "from xarray import open_datatree\n", | ||
| "from metpy.plots import ctables" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Opening the dataset with `open_datatree()`" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7 = open_datatree(\n", | ||
| " '~/Downloads/3B-HHR.MS.MRG.3IMERG.20210829-S073000-E075959.0450.V07B.HDF5', engine='h5netcdf'\n", | ||
| ")\n", | ||
| "gpm_imerghh_7" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### List all of the groups with `.groups`" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7.groups" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Accessing variables in a nested groups\n", | ||
| "Nested variables and groups can be accessed with either dict-like syntax or method based syntax." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid']\n", | ||
| "\n", | ||
| "# Returns only the data contained in the \"/Grid\" group" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid/precipitation']" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7.Grid.precipitation" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Get the parent and child nodes from a group" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid/Intermediate'].parent" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7.Grid.children" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### `Xarray.DataTree` objects and `xarray.Dataset` objects have the same key properties like:\n", | ||
| "\n", | ||
| "- `dims`: a dictionary mapping of dimension names to lengths, for the variables in a node, and a node’s ancestors.\n", | ||
| "\n", | ||
| "- `data_vars`: a dict-like container of DataArrays corresponding to variables in a node.\n", | ||
| "\n", | ||
| "- `coords`: another dict-like container of DataArrays, corresponding to coordinate variables in a node, and a node’s ancestors.\n", | ||
| "\n", | ||
| "- `attrs`: dict with metadata relevant to data in a node.\n", | ||
| "\n", | ||
| "With `DataTree` you can get these properties at any of the nodes (groups) they are defined in." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7.dims\n", | ||
| "# Note there are no dimensions, coordinates, or data variables defined at the root node" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7.attrs" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid'].dims" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid/Intermediate'].dims" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gpm_imerghh_7['/Grid/Intermediate'].data_vars" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Plotting precipitation data with DataTree\n", | ||
| "Xarray’s plotting capabilities are centered around DataArray objects. To plot DataTree objects we access their relevant DataArrays in this case, `gpm_imerghh_7['/Grid/precipitation']`. \n", | ||
| "\n", | ||
| "We use the `.where()` method to get a subset of precipitation data over the Gulf of Mexico." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "precipitation_subset = gpm_imerghh_7['/Grid/precipitation'].where(\n", | ||
| " (gpm_imerghh_7['/Grid/precipitation'].lat >= 20)\n", | ||
| " & (gpm_imerghh_7['/Grid/precipitation'].lat <= 35)\n", | ||
| " & (gpm_imerghh_7['/Grid/precipitation'].lon >= -110)\n", | ||
| " & (gpm_imerghh_7['/Grid/precipitation'].lon <= -78),\n", | ||
| " drop=True,\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Data masking\n", | ||
| "We add a data mask to the precipitation values that are zero." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "precipitation_subset_mask = precipitation_subset.where(precipitation_subset > 0.0)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Add a custom precipitation color map from [metpy](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.ctables.html)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "clevs = [0, 1, 2.5, 5, 7.5, 10, 15, 20, 30, 40, 50, 70, 100, 150, 200, 250, 300, 400, 500, 600, 750]\n", | ||
| "norm, cmap = ctables.registry.get_with_boundaries('precipitation', clevs)\n", | ||
| "cmap" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Plot the data with `.plot()`\n", | ||
| "Note since this data is two-dimensional it calls `xarray.plot.pcolormesh()` by default with just the `.plot()` method." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Set the figure size, projection, extent and grid lines to the plot\n", | ||
| "fig = plt.figure(figsize=(8, 8))\n", | ||
| "ax = plt.axes(projection=ccrs.PlateCarree())\n", | ||
| "ax.set_extent([-100, -80, 20, 35])\n", | ||
| "ax.coastlines()\n", | ||
| "gl = ax.gridlines(draw_labels=True, linewidth=1, color='black', linestyle='--')\n", | ||
| "gl.right_labels = False\n", | ||
| "gl.top_labels = False\n", | ||
| "\n", | ||
| "# Get the minimum and maximum values in the array\n", | ||
| "min = precipitation_subset_mask.min()\n", | ||
| "max = precipitation_subset_mask.max()\n", | ||
| "\n", | ||
| "# Plot the precipitation data\n", | ||
| "precipitation_subset_mask[0].plot(\n", | ||
| " x=\"lon\",\n", | ||
| " y=\"lat\",\n", | ||
| " ax=ax,\n", | ||
| " cmap=cmap,\n", | ||
| " cbar_kwargs={\"orientation\": \"horizontal\", \"pad\": 0.05},\n", | ||
| " vmin=min,\n", | ||
| " vmax=max,\n", | ||
| ")\n", | ||
| "\n", | ||
| "plt.title('Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } | ||
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This line is going to change once this is merged pydata/xarray-data#31