From 0f5f64dae87f35f13c009b12e83819cc2ee9e253 Mon Sep 17 00:00:00 2001 From: ayushnag <35325113+ayushnag@users.noreply.github.com> Date: Tue, 17 Dec 2024 10:56:53 -0500 Subject: [PATCH] add initial vz tutorial notebook --- docs/tutorials/dmrpp-virtualizarr.ipynb | 2832 +++++++++++++++++++++++ 1 file changed, 2832 insertions(+) create mode 100644 docs/tutorials/dmrpp-virtualizarr.ipynb diff --git a/docs/tutorials/dmrpp-virtualizarr.ipynb b/docs/tutorials/dmrpp-virtualizarr.ipynb new file mode 100644 index 00000000..e32de6da --- /dev/null +++ b/docs/tutorials/dmrpp-virtualizarr.ipynb @@ -0,0 +1,2832 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Creating cloud optimized reference files with earthaccess and virtualizarr\n", + "This notebook will focus on the usage of `earthaccess.open_virtual_dataset` and `earthaccess.open_virtual_mfdataset` to create cloud optimized reference files for the data stored in the cloud.\n", + "\n", + "All of the examples in this tutorial load data over https (`access=\"indirect\"`). However, there is a **significant** speed improvement when using these functions in-cloud and enabling `access=\"direct\"`. For example, using managed cloud JupyterHubs like NASA VEDA or 2i2c Openscapes. This is because the data is streamed directly from cloud storage to cloud compute.\n", + "\n", + "> WARNING: This feature is current experimental and may change in the future. This feature relies on NASA DMR++ metadata files which may not always be present for your dataset and you may get a `FileNotFoundError`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import earthaccess\n", + "import xarray as xr" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "32" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# NASA JPL Multiscale Ultrahigh Resolution (MUR) Sea Surface Temperature (SST) dataset - 0.01 degree resolution\n", + "results = earthaccess.search_data(\n", + " temporal=(\"2010-01-01\", \"2010-01-31\"), short_name=\"MUR-JPL-L4-GLOB-v4.1\"\n", + ")\n", + "len(results)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 1.37 s, sys: 189 ms, total: 1.55 s\n", + "Wall time: 17.6 s\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset> Size: 581GB\n",
+       "Dimensions:           (time: 32, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "  * lat               (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n",
+       "  * lon               (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time              (time) datetime64[ns] 256B 2010-01-01T09:00:00 ... 2010...\n",
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 166GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    analysis_error    (time, lat, lon) float64 166GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    mask              (time, lat, lon) float32 83GB dask.array<chunksize=(1, 1447, 2895), meta=np.ndarray>\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 166GB dask.array<chunksize=(1, 1447, 2895), meta=np.ndarray>\n",
+       "Attributes: (12/42)\n",
+       "    Conventions:                CF-1.5\n",
+       "    title:                      Daily MUR SST, Final product\n",
+       "    summary:                    A merged, multi-sensor L4 Foundation SST anal...\n",
+       "    references:                 http://podaac.jpl.nasa.gov/Multi-scale_Ultra-...\n",
+       "    institution:                Jet Propulsion Laboratory\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    publisher_name:             GHRSST Project Office\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    publisher_email:            ghrsst-po@nceo.ac.uk\n",
+       "    processing_level:           L4\n",
+       "    cdm_data_type:              grid
" + ], + "text/plain": [ + " Size: 581GB\n", + "Dimensions: (time: 32, lat: 17999, lon: 36000)\n", + "Coordinates:\n", + " * lat (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n", + " * lon (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n", + " * time (time) datetime64[ns] 256B 2010-01-01T09:00:00 ... 2010...\n", + "Data variables:\n", + " analysed_sst (time, lat, lon) float64 166GB dask.array\n", + " analysis_error (time, lat, lon) float64 166GB dask.array\n", + " mask (time, lat, lon) float32 83GB dask.array\n", + " sea_ice_fraction (time, lat, lon) float64 166GB dask.array\n", + "Attributes: (12/42)\n", + " Conventions: CF-1.5\n", + " title: Daily MUR SST, Final product\n", + " summary: A merged, multi-sensor L4 Foundation SST anal...\n", + " references: http://podaac.jpl.nasa.gov/Multi-scale_Ultra-...\n", + " institution: Jet Propulsion Laboratory\n", + " history: created at nominal 4-day latency; replaced nr...\n", + " ... ...\n", + " project: NASA Making Earth Science Data Records for Us...\n", + " publisher_name: GHRSST Project Office\n", + " publisher_url: http://www.ghrsst.org\n", + " publisher_email: ghrsst-po@nceo.ac.uk\n", + " processing_level: L4\n", + " cdm_data_type: grid" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "mur = earthaccess.open_virtual_mfdataset(\n", + " results,\n", + " access=\"indirect\",\n", + " load=True,\n", + " concat_dim=\"time\",\n", + " coords=\"all\",\n", + " compat=\"override\",\n", + " combine_attrs=\"drop_conflicts\",\n", + ")\n", + "mur" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "580.575960252 GB\n" + ] + } + ], + "source": [ + "print(f\"{mur.nbytes / 1e9} GB\")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mur.isel(time=0).sel(\n", + " lat=slice(20, 45), lon=slice(-95, -50)\n", + ").analysed_sst.plot.pcolormesh(x=\"lon\", y=\"lat\", cmap=\"plasma\", figsize=(8, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Save virtual reference file and load with xarray\n", + "If you have a dataset you frequently access or you want to share this blueprint file with others, it is recommended to create a virtual reference file that points to the data in the cloud. This allows xarray to rapidly load the dataset as if it was a [Zarr store](https://zarr.dev/).\n", + "\n", + "Notice below that `load=False`. This means that the output of `open_virtual_mfdataset` is a virtual xarray Dataset that contains only chunk information and metadata. You can modify this dataset, then save it to a virtual reference file (as JSON), and then simply load that file with xarray. For more information on virtual reference files, see the [virtualizarr documentation](https://virtualizarr.readthedocs.io/en/latest/).\n", + "\n", + "Sample workflow:\n", + "1. Open a dataset with `open_virtual_mfdataset` with `load=False`\n", + "2. Modify the dataset as needed\n", + "3. Save the dataset to a virtual reference file with `vds.virtualize.to_kerchunk(...)`\n", + "4. Load the virtual reference file with `xr.open_dataset(..., engine='kerchunk')`" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 481 ms, sys: 50.4 ms, total: 531 ms\n", + "Wall time: 6.87 s\n" + ] + }, + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 124GB\n",
+       "Dimensions:           (time: 32, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "    time              (time) int32 128B ManifestArray<shape=(32,), dtype=int3...\n",
+       "    lat               (lat) float32 72kB ManifestArray<shape=(17999,), dtype=...\n",
+       "    lon               (lon) float32 144kB ManifestArray<shape=(36000,), dtype...\n",
+       "Data variables:\n",
+       "    mask              (time, lat, lon) int8 21GB ManifestArray<shape=(32, 179...\n",
+       "    sea_ice_fraction  (time, lat, lon) int8 21GB ManifestArray<shape=(32, 179...\n",
+       "    analysed_sst      (time, lat, lon) int16 41GB ManifestArray<shape=(32, 17...\n",
+       "    analysis_error    (time, lat, lon) int16 41GB ManifestArray<shape=(32, 17...\n",
+       "Attributes: (12/42)\n",
+       "    Conventions:                CF-1.5\n",
+       "    title:                      Daily MUR SST, Final product\n",
+       "    summary:                    A merged, multi-sensor L4 Foundation SST anal...\n",
+       "    references:                 http://podaac.jpl.nasa.gov/Multi-scale_Ultra-...\n",
+       "    institution:                Jet Propulsion Laboratory\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    publisher_name:             GHRSST Project Office\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    publisher_email:            ghrsst-po@nceo.ac.uk\n",
+       "    processing_level:           L4\n",
+       "    cdm_data_type:              grid
" + ], + "text/plain": [ + " Size: 124GB\n", + "Dimensions: (time: 32, lat: 17999, lon: 36000)\n", + "Coordinates:\n", + " time (time) int32 128B ManifestArray Size: 581GB\n", + "Dimensions: (time: 32, lat: 17999, lon: 36000)\n", + "Coordinates:\n", + " * lat (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n", + " * lon (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n", + " * time (time) datetime64[ns] 256B 2010-01-01T09:00:00 ... 2010...\n", + "Data variables:\n", + " analysed_sst (time, lat, lon) float64 166GB dask.array\n", + " analysis_error (time, lat, lon) float64 166GB dask.array\n", + " mask (time, lat, lon) float32 83GB dask.array\n", + " sea_ice_fraction (time, lat, lon) float64 166GB dask.array\n", + "Attributes: (12/42)\n", + " Conventions: CF-1.5\n", + " title: Daily MUR SST, Final product\n", + " summary: A merged, multi-sensor L4 Foundation SST anal...\n", + " references: http://podaac.jpl.nasa.gov/Multi-scale_Ultra-...\n", + " institution: Jet Propulsion Laboratory\n", + " history: created at nominal 4-day latency; replaced nr...\n", + " ... ...\n", + " project: NASA Making Earth Science Data Records for Us...\n", + " publisher_name: GHRSST Project Office\n", + " publisher_url: http://www.ghrsst.org\n", + " publisher_email: ghrsst-po@nceo.ac.uk\n", + " processing_level: L4\n", + " cdm_data_type: grid\n", + "CPU times: user 153 ms, sys: 76.7 ms, total: 229 ms\n", + "Wall time: 6.99 s\n" + ] + } + ], + "source": [ + "%%time\n", + "fs = earthaccess.get_fsspec_https_session()\n", + "ds = xr.open_dataset(\n", + " \"reference://\",\n", + " engine=\"zarr\",\n", + " chunks={},\n", + " backend_kwargs={\n", + " \"consolidated\": False,\n", + " \"storage_options\": {\n", + " \"fo\": \"mur_kerchunk.json\",\n", + " \"remote_protocol\": fs.protocol,\n", + " \"remote_options\": fs.storage_options,\n", + " },\n", + " },\n", + ")\n", + "print(ds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Read datasets with groups" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# NASA TEMPO NO2 tropospheric and stratospheric columns V03\n", + "results = earthaccess.search_data(count=2, doi=\"10.5067/IS-40e/TEMPO/NO2_L2.003\")\n", + "len(results)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 7MB\n",
+       "Dimensions:                                  (mirror_step: 123, xtrack: 2048)\n",
+       "Dimensions without coordinates: mirror_step, xtrack\n",
+       "Data variables:\n",
+       "    main_data_quality_flag                   (mirror_step, xtrack) int16 504kB ManifestArray<shape=(123, 2048), dtype=int16, chunks=(123, 2048...\n",
+       "    vertical_column_troposphere              (mirror_step, xtrack) float64 2MB ManifestArray<shape=(123, 2048), dtype=float64, chunks=(123, 2048...\n",
+       "    vertical_column_stratosphere             (mirror_step, xtrack) float64 2MB ManifestArray<shape=(123, 2048), dtype=float64, chunks=(123, 2048...\n",
+       "    vertical_column_troposphere_uncertainty  (mirror_step, xtrack) float64 2MB ManifestArray<shape=(123, 2048), dtype=float64, chunks=(123, 2048...
" + ], + "text/plain": [ + " Size: 7MB\n", + "Dimensions: (mirror_step: 123, xtrack: 2048)\n", + "Dimensions without coordinates: mirror_step, xtrack\n", + "Data variables:\n", + " main_data_quality_flag (mirror_step, xtrack) int16 504kB ManifestArray\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset> Size: 1GB\n",
+       "Dimensions:                                (cycle_num: 1, pass_num: 10,\n",
+       "                                            num_lines: 9866, num_pixels: 69,\n",
+       "                                            num_sides: 2)\n",
+       "Coordinates:\n",
+       "    longitude                              (pass_num, num_lines, num_pixels) int32 27MB ManifestArray<shape=(10, 9866, 69), dtype=int32, chunks=(1,...\n",
+       "    latitude                               (pass_num, num_lines, num_pixels) int32 27MB ManifestArray<shape=(10, 9866, 69), dtype=int32, chunks=(1,...\n",
+       "    latitude_nadir                         (pass_num, num_lines) int32 395kB ...\n",
+       "    longitude_nadir                        (pass_num, num_lines) int32 395kB ...\n",
+       "  * cycle_num                              (cycle_num) int64 8B 1\n",
+       "  * pass_num                               (pass_num) int64 80B 149 150 ... 158\n",
+       "Dimensions without coordinates: num_lines, num_pixels, num_sides\n",
+       "Data variables: (12/98)\n",
+       "    height_cor_xover_qual                  (cycle_num, pass_num, num_lines, num_pixels) uint8 7MB ManifestArray<shape=(1, 10, 9866, 69), dtype=uint8, chu...\n",
+       "    swh_ssb_cor_source                     (cycle_num, pass_num, num_lines, num_pixels) uint8 7MB ManifestArray<shape=(1, 10, 9866, 69), dtype=uint8, chu...\n",
+       "    rain_rate                              (cycle_num, pass_num, num_lines, num_pixels) uint8 7MB ManifestArray<shape=(1, 10, 9866, 69), dtype=uint8, chu...\n",
+       "    dynamic_ice_flag                       (cycle_num, pass_num, num_lines, num_pixels) uint8 7MB ManifestArray<shape=(1, 10, 9866, 69), dtype=uint8, chu...\n",
+       "    orbit_qual                             (cycle_num, pass_num, num_lines) uint8 99kB ManifestArray<shape=(1, 10, 9866), dtype=uint8, chunks=(1,...\n",
+       "    ancillary_surface_classification_flag  (cycle_num, pass_num, num_lines, num_pixels) uint8 7MB ManifestArray<shape=(1, 10, 9866, 69), dtype=uint8, chu...\n",
+       "    ...                                     ...\n",
+       "    sig0_cor_atmos_model                   (cycle_num, pass_num, num_lines, num_pixels) float32 27MB ManifestArray<shape=(1, 10, 9866, 69), dtype=float32, ...\n",
+       "    cross_track_distance                   (cycle_num, pass_num, num_lines, num_pixels) float32 27MB ManifestArray<shape=(1, 10, 9866, 69), dtype=float32, ...\n",
+       "    sig0_karin_uncert                      (cycle_num, pass_num, num_lines, num_pixels) float32 27MB ManifestArray<shape=(1, 10, 9866, 69), dtype=float32, ...\n",
+       "    time                                   (cycle_num, pass_num, num_lines) float64 789kB ManifestArray<shape=(1, 10, 9866), dtype=float64, chunks=...\n",
+       "    time_tai                               (cycle_num, pass_num, num_lines) float64 789kB ManifestArray<shape=(1, 10, 9866), dtype=float64, chunks=...\n",
+       "    polarization_karin                     (cycle_num, pass_num, num_lines, num_sides) object 2MB ManifestArray<shape=(1, 10, 9866, 2), dtype=object, ch...\n",
+       "Attributes: (12/29)\n",
+       "    Conventions:                      CF-1.7\n",
+       "    title:                            Level 2 Low Rate Sea Surface Height Dat...\n",
+       "    institution:                      JPL\n",
+       "    source:                           Ka-band radar interferometer\n",
+       "    platform:                         SWOT\n",
+       "    reference_document:               D-56407_SWOT_Product_Description_L2_LR_SSH\n",
+       "    ...                               ...\n",
+       "    xref_pole_location_file:          SMM_PO1_AXXCNE20231122_020000_19900101_...\n",
+       "    xref_wave_model_files:            SMM_WMA_AXPCNE20230727_072014_20230726_...\n",
+       "    xref_geco_database_version:       v102\n",
+       "    ellipsoid_semi_major_axis:        6378137.0\n",
+       "    ellipsoid_flattening:             0.0033528106647474805\n",
+       "    references:                       V1.2.1
" + ], + "text/plain": [ + " Size: 1GB\n", + "Dimensions: (cycle_num: 1, pass_num: 10,\n", + " num_lines: 9866, num_pixels: 69,\n", + " num_sides: 2)\n", + "Coordinates:\n", + " longitude (pass_num, num_lines, num_pixels) int32 27MB ManifestArray xr.Dataset:\n", + " # Add cycle number and pass_number as dimensions\n", + " return ds.expand_dims([\"cycle_num\", \"pass_num\"]).assign_coords(\n", + " cycle_num=[ds.attrs[\"cycle_number\"]], pass_num=[ds.attrs[\"pass_number\"]]\n", + " )\n", + "\n", + "\n", + "swot = earthaccess.open_virtual_mfdataset(\n", + " results,\n", + " access=\"indirect\",\n", + " load=False,\n", + " preprocess=preprocess,\n", + " concat_dim=\"pass_num\",\n", + " coords=\"all\",\n", + " compat=\"override\",\n", + " combine_attrs=\"drop_conflicts\",\n", + ")\n", + "swot" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".env", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}