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Commit a9926cf

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eni-awowalepre-commit-ci[bot]ianhi
authored
Hierarchical trees of related groups (DataTree) for SciPy35 (#331)
* datatree imerghh_7 notebook * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * added more methods and suggestions * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * chore: pull sync fork * feature: datatree notebook * chore: updated yml * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix header order for myst * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Ian Hunt-Isaak <ianhuntisaak@gmail.com>
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‎_toc.yml‎

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- file: fundamentals/01_datastructures
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- file: fundamentals/01.1_creating_data_structures
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- file: fundamentals/01.1_io
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- file: fundamentals/01_datatree_hierarchical_data.ipynb
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- file: fundamentals/02_labeled_data.md
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sections:
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- file: fundamentals/02.1_indexing_Basic.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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"metadata": {},
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"source": [
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"# `xarray.DataTree` and hierarchical data\n",
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"\n",
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"In this lesson, we will learn how to use `xarray.DataTree` with hierarchical data. By the end of the lesson, we will be able to:\n",
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"\n",
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":::{admonition} Learning Goals\n",
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"- Understand a basic `DataTree` structure (nodes, parents and children)\n",
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"- Selecting `DataTree`\n",
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"- Understand coordinate inheritance :::"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"import xarray as xr"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Opening a dataset with `open_datatree()`\n",
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"\n",
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"Let's open up a precipitation dataset. This dataset was derived from \"GPM_3IMERGHH_07\" and \"M2T1NXFLX_5.12.4\" products."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation = xr.tutorial.open_datatree('precipitation.nc4')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Nodes\n",
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"Groups in a netcdf4 or hdf5 file in the DataTree model are represented as \"nodes\" in the DataTree model.\n",
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"We can list all of the groups with `.groups`"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.groups"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Accessing variables in a nested groups\n",
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"Nested variables and groups can be accessed with either dict-like syntax or method based syntax."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation['observed']\n",
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"\n",
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"# Returns a DataTree object, containing the variables, dimensions, and coordinates in the \"observed\" node"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation['/observed/precipitation']"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.reanalysis.precipitation\n",
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"\n",
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"# Method based syntax"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Get the parent and child nodes from a group"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation['reanalysis'].parent"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.children"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Inheritance\n",
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"DataTree implements a simple inheritance mechanism. Coordinates, dimensions and their associated indices are propagated downward from the root node to all descendent nodes.\n",
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"\n",
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"Let's take a look at some inherited coordinates with our precipitation dataset"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.time"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The `\"time\"` dimension is defined at the root node of our dataset and is propagated downward to the \"observed\" and \"reanalysis\" group"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.observed"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"precipitation.reanalysis"
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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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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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