From 1a18f763530a5d51a98c78cb0ef7da15527fc0d1 Mon Sep 17 00:00:00 2001 From: Andrew Huang Date: Wed, 9 Aug 2023 15:22:13 -0400 Subject: [PATCH 1/5] Add a streaming viz cookbook --- ...isualizations_with_Hvplot_Datashader.ipynb | 316 ++++++++++++++++++ notebooks/images/kerchunk.gif | Bin 0 -> 2640249 bytes notebooks/images/thredds.gif | Bin 0 -> 3485621 bytes 3 files changed, 316 insertions(+) create mode 100644 notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb create mode 100644 notebooks/images/kerchunk.gif create mode 100644 notebooks/images/thredds.gif diff --git a/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb new file mode 100644 index 0000000..ae9e353 --- /dev/null +++ b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb @@ -0,0 +1,316 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "f6c39c84", + "metadata": {}, + "source": [ + "# Kerchunk, hvPlot, and Datashader: Visualizing datasets on-the-fly" + ] + }, + { + "cell_type": "markdown", + "id": "9eced552", + "metadata": {}, + "source": [ + "## Overview\n", + " \n", + "Within this notebook, we will cover:\n", + "\n", + "1. How to use Kerchunk, hvPlot, and Datashader to easily parts of the dataset in a streaming fashion.\n", + "\n", + "We will be building off content from [Kerchunk and Pangeo-Forge](../case_studies/NetCDF_Pangeo_Forge_gridMET.ipynb), so it's encouraged you first go through that.\n", + "\n", + "## Prerequisites\n", + "| Concepts | Importance | Notes |\n", + "| --- | --- | --- |\n", + "| [Kerchunk Basics](../foundations/kerchunk_basics) | Required | Core |\n", + "| [Multiple Files and Kerchunk](../foundations/kerchunk_multi_file) | Required | Core |\n", + "| [Introduction to Xarray](https://foundations.projectpythia.org/core/xarray/xarray-intro.html) | Required | IO |\n", + "| [Introduction to hvPlot](https://hvplot.holoviz.org/) | Required | Data Visualization |\n", + "| [Introduction to Datashader](https://datashader.org/index.html) | Required | Big Data Visualization |\n", + "- **Time to learn**: 10 minutes\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "4043365b", + "metadata": {}, + "source": [ + "## Motivation\n", + "\n", + "Using Kerchunk, we don't have to create a copy of the data--instead we create a collection of reference files, so that the original data files can be read as if they were Zarr.\n", + "\n", + "This enables visualization on-the-fly; simply pass in the URL to the dataset and use hvplot." + ] + }, + { + "cell_type": "markdown", + "id": "f8d0f8f1", + "metadata": {}, + "source": [ + "## Imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "706c1b95", + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = false;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== 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"display_data" + } + ], + "source": [ + "import os\n", + "import time\n", + "\n", + "import apache_beam as beam\n", + "import fsspec\n", + "import hvplot.xarray\n", + "import xarray as xr\n", + "from pangeo_forge_recipes.patterns import ConcatDim, FilePattern\n", + "from pangeo_forge_recipes.transforms import (\n", + " CombineReferences,\n", + " OpenWithKerchunk,\n", + " WriteCombinedReference,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "858399ce", + "metadata": {}, + "source": [ + "## Preprocess Dataset\n", + "\n", + "Here we will be preparing the Kerchunk reference files by using the recipe described in [Kerchunk and Pangeo-Forge](../case_studies/NetCDF_Pangeo_Forge_gridMET.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "06fb2af3", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants\n", + "target_root = \"references\"\n", + "store_name = \"Pangeo_Forge\"\n", + "full_path = os.path.join(target_root, store_name, \"reference.json\")\n", + "years = list(range(1979, 1980))\n", + "time_dim = ConcatDim(\"time\", keys=years)\n", + "\n", + "\n", + "# Functions\n", + "def format_function(time):\n", + " return f\"http://www.northwestknowledge.net/metdata/data/bi_{time}.nc\"\n", + "\n", + "# Patterns\n", + "pattern = FilePattern(format_function, time_dim, file_type=\"netcdf4\")\n", + "pattern = pattern.prune()\n", + "\n", + "# Apache Beam transforms\n", + "transforms = (\n", + " beam.Create(pattern.items())\n", + " | OpenWithKerchunk(file_type=pattern.file_type)\n", + " | CombineReferences(\n", + " concat_dims=[\"day\"],\n", + " identical_dims=[\"lat\", \"lon\", \"crs\"],\n", + " )\n", + " | WriteCombinedReference(target_root=target_root, store_name=store_name)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "7818440e", + "metadata": {}, + "source": [ + "## Opening the Kerchunk Dataset\n", + "\n", + "Now, it's a matter of opening the Kerchunk dataset and calling `hvplot` with the `rasterize=True` keyword argument.\n", + "\n", + "If you're running this notebook locally, try zooming around the map by hovering over the plot and scrolling; it should update fairly quickly. Note, it will **not** update if you're viewing this on the docs page online as there is no backend server, but don't fret because there's a demo GIF below!" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ce0f1766", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fc6316ac2fb945d5bb1604d399ded9d7", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "BokehModel(combine_events=True, render_bundle={'docs_json': {'d4abebd3-8330-4dcf-b066-c430f8ef8a12': {'version…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4.3 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit -r 1 -n 1\n", + "\n", + "mapper = fsspec.get_mapper(\n", + " \"reference://\",\n", + " fo=full_path,\n", + " remote_protocol=\"http\",\n", + ")\n", + "ds_kerchunk = xr.open_dataset(\n", + " mapper, engine=\"zarr\", decode_coords=\"all\", backend_kwargs={\"consolidated\": False}\n", + ")\n", + "display(ds_kerchunk.hvplot(\"lon\", \"lat\", rasterize=True))" + ] + }, + { + "cell_type": "markdown", + "id": "e53531df", + "metadata": {}, + "source": [ + "\"Kerchunk" + ] + }, + { + "cell_type": "markdown", + "id": "f2c56945", + "metadata": {}, + "source": [ + "## Comparing Against THREDDS\n", + "\n", + "Now, we will be repeating the previous cell, but with THREDDS.\n", + "\n", + "Note how the initial load is longer.\n", + "\n", + "If you're running the notebook locally (or a demo GIF below), zooming in/out also takes longer to finish buffering as well." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "368ac51d", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ebdd3f3383e94820a921a8956747cda4", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "BokehModel(combine_events=True, render_bundle={'docs_json': {'b9c96370-5795-4c0a-b3b2-d6f5c1428aea': {'version…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "6.65 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit -r 1 -n 1\n", + "\n", + "def url_gen(year):\n", + " return (\n", + " f\"http://thredds.northwestknowledge.net:8080/thredds/dodsC/MET/bi/bi_{year}.nc\"\n", + " )\n", + "\n", + "urls_list = [url_gen(year) for year in years]\n", + "netcdf_ds = xr.open_mfdataset(urls_list, engine=\"netcdf4\")\n", + "display(netcdf_ds.hvplot(\"lon\", \"lat\", rasterize=True))" + ] + }, + { + "cell_type": "markdown", + "id": "6c0dd0cd", + "metadata": {}, + "source": [ + "\"THREDDS" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + 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znvT~eIw)T4w}Ef{#09oVODIzYDPpI}n|`dz1|_QI_~Ah5+sl_H#{^mG2yR z|5Z$@2xdB!7%>5#&Q}?ZK6mWUspHq14JY8KV=-ZVEk4)_MV6s-fgx7|6v{_m1FZYB zRU-=VttvaAu-xME7S)Ng4o(9=hLzU>gX~s_AR{A5gV(}T9JLu^)>{t1Mq@P~-^DOJ ztrq%F3J3}TAK2IKXSoh{tSYcaT{D}9?v4&(Q7@X212pvw|EvNTvGsqo@#Y|+aG6k! zk&mBgBU|yMbhHfCARo$bf&4rf9Sw>A;?52y-`|JY1=ud)`uOOZ(br?2w3|(U`$?cr zCuDKl4fqD?#$5xDF%z_{F+~M8Ca$Af8My6qw3m8QK$n!ej@ufSl>26GSyNt~_c zt^6k!{a)VM|LYb@t|P>}Bh Date: Wed, 9 Aug 2023 15:23:21 -0400 Subject: [PATCH 2/5] Reset notebook output --- ...isualizations_with_Hvplot_Datashader.ipynb | 99 ++----------------- 1 file changed, 7 insertions(+), 92 deletions(-) diff --git a/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb index ae9e353..e211dcf 100644 --- a/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb +++ b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb @@ -55,51 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append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n", - "application/vnd.holoviews_load.v0+json": "" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import os\n", "import time\n", @@ -128,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "06fb2af3", "metadata": {}, "outputs": [], @@ -175,32 +134,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "ce0f1766", "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "fc6316ac2fb945d5bb1604d399ded9d7", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "BokehModel(combine_events=True, render_bundle={'docs_json': {'d4abebd3-8330-4dcf-b066-c430f8ef8a12': {'version…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4.3 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" - ] - } - ], + "outputs": [], "source": [ "%%timeit -r 1 -n 1\n", "\n", @@ -239,32 +176,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "368ac51d", "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ebdd3f3383e94820a921a8956747cda4", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "BokehModel(combine_events=True, render_bundle={'docs_json': {'b9c96370-5795-4c0a-b3b2-d6f5c1428aea': {'version…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6.65 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" - ] - } - ], + "outputs": [], "source": [ "%%timeit -r 1 -n 1\n", "\n", From 89218df405aa9da688400e4364c91de8629320ab Mon Sep 17 00:00:00 2001 From: Andrew Huang Date: Wed, 9 Aug 2023 15:25:29 -0400 Subject: [PATCH 3/5] Add toc --- _toc.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/_toc.yml b/_toc.yml index b6ce37a..ff3a88d 100644 --- a/_toc.yml +++ b/_toc.yml @@ -16,3 +16,4 @@ parts: - file: notebooks/case_studies/GRIB2_HRRR - file: notebooks/case_studies/GeoTIFF_FMI - file: notebooks/case_studies/NetCDF_Pangeo_Forge_gridMET + - file: notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader \ No newline at end of file From 678aa0bd5ad7837afdf861d0f53b9b8ebe3bcbd0 Mon Sep 17 00:00:00 2001 From: Andrew <15331990+ahuang11@users.noreply.github.com> Date: Wed, 9 Aug 2023 15:56:56 -0400 Subject: [PATCH 4/5] Update environment.yml --- environment.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/environment.yml b/environment.yml index f947893..2ae8e16 100644 --- a/environment.yml +++ b/environment.yml @@ -34,6 +34,8 @@ dependencies: - ujson - xarray - zarr + - hvplot + - datashader - pip: - sphinx-pythia-theme From 969598499a45bd6a27ce6ce0431b357132e79563 Mon Sep 17 00:00:00 2001 From: Andrew Huang Date: Thu, 10 Aug 2023 16:44:01 -0400 Subject: [PATCH 5/5] Address comments --- ...ing_Visualizations_with_Hvplot_Datashader.ipynb | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb index e211dcf..b65ef6e 100644 --- a/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb +++ b/notebooks/case_studies/Streaming_Visualizations_with_Hvplot_Datashader.ipynb @@ -15,9 +15,7 @@ "source": [ "## Overview\n", " \n", - "Within this notebook, we will cover:\n", - "\n", - "1. How to use Kerchunk, hvPlot, and Datashader to easily parts of the dataset in a streaming fashion.\n", + "This notebook will demonstrate how to use Kerchunk with hvPlot and Datashader to lazily visualize a reference dataset in a streaming fashion.\n", "\n", "We will be building off content from [Kerchunk and Pangeo-Forge](../case_studies/NetCDF_Pangeo_Forge_gridMET.ipynb), so it's encouraged you first go through that.\n", "\n", @@ -45,6 +43,16 @@ "This enables visualization on-the-fly; simply pass in the URL to the dataset and use hvplot." ] }, + { + "cell_type": "markdown", + "id": "8e2c4765", + "metadata": {}, + "source": [ + "## Getting to Know The Data\n", + "\n", + "`gridMET` is a high-resolution daily meteorological dataset covering CONUS from 1979-2023. It is produced by the Climatology Lab at UC Merced. In this example, we are going to look create a virtual Zarr dataset of a derived variable, Burn Index. " + ] + }, { "cell_type": "markdown", "id": "f8d0f8f1",

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