diff --git a/docs/tutorials/dask.ipynb b/docs/tutorials/dask.ipynb deleted file mode 100644 index 6170de47..00000000 --- a/docs/tutorials/dask.ipynb +++ /dev/null @@ -1,2131 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "8f552380-cc0a-4fb8-b4b3-276a6564b239", - "metadata": {}, - "source": [ - "# Analyzing NASA Data with Dask" - ] - }, - { - "cell_type": "markdown", - "id": "9e4dbac6-b20b-43c3-b64a-189a614a3fb9", - "metadata": {}, - "source": [ - "## Create cluster on AWS\n", - "\n", - "_This cell is all that's needed to run this analysis on a cluster_" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "cbd1ed19-c6db-427c-9076-2e6af892558d", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'coiled'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m:2\u001b[0m\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'coiled'" - ] - } - ], - "source": [ - "%%time\n", - "\n", - "# Spin up a Coiled cluster in region us-west-2\n", - "import coiled\n", - "\n", - "cluster = coiled.Cluster(n_workers=20, region=\"us-west-2\")\n", - "client = cluster.get_client()" - ] - }, - { - "cell_type": "markdown", - "id": "4a30aadb-41d4-4c08-a6fa-5ea60c6bd695", - "metadata": {}, - "source": [ - "## Get data files with `earthaccess`" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "899b10a6-51fc-4d97-96d2-54e81a8b8f7d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You're now authenticated with NASA Earthdata Login\n", - "Using token with expiration date: 08/04/2023\n", - "Using environment variables for EDL\n" - ] - } - ], - "source": [ - "# Authenticate my machine with `earthaccess`\n", - "import earthaccess\n", - "\n", - "earthaccess.login();" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "c9c3d184-ffff-494f-ad77-f6b2cc31f6c5", - "metadata": {}, - "outputs": [], - "source": [ - "# Define region bounding box\n", - "lon0, lat0 = -124.5, 36.5\n", - "dlon, dlat = 2.5, 2.0 # half of box width in lon/lat\n", - "lon_min, lon_max = lon0 - dlon, lon0 + dlon\n", - "lat_min, lat_max = lat0 - dlat, lat0 + dlat\n", - "\n", - "bounding_box = (lon_min, lat_min, lon_max, lat_max)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "8cad710e-9a9e-45fd-b2fd-f01990db37d6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Granules found: 196\n" - ] - } - ], - "source": [ - "# Retrieve data files for the dataset I'm interested in\n", - "results = earthaccess.search_data(\n", - " short_name=\"VIIRS_NPP-STAR-L3U-v2.80\",\n", - " concept_id=\"C2147485059-POCLOUD\",\n", - " cloud_hosted=True,\n", - " bounding_box=bounding_box,\n", - " temporal=(\"2021-04-01\", \"2021-05-6\"),\n", - " count=30, # For demo purposes\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "cbe32079-17f9-45a8-9601-c0fe21980183", - "metadata": {}, - "source": [ - "## Analyze data on my cluster with Xarray" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "a231efb7-0b37-48be-a432-74afbde099de", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Opening 30 granules, approx size: 0.0 GB\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "38f7f8a98abb4fc780198d04f75c49fe", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "SUBMITTING | : 0%| | 0/30 [00:00\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
<xarray.Dataset>\n",
-       "Dimensions:                  (lon: 18000, lat: 9000, time: 30)\n",
-       "Coordinates:\n",
-       "  * lon                      (lon) float32 -180.0 -180.0 -179.9 ... 180.0 180.0\n",
-       "  * lat                      (lat) float32 89.99 89.97 89.95 ... -89.97 -89.99\n",
-       "  * time                     (time) datetime64[ns] 2021-04-01T08:10:01 ... 20...\n",
-       "Data variables: (12/13)\n",
-       "    quality_level            (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    l2p_flags                (time, lat, lon) int16 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    or_number_of_pixels      (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    sea_surface_temperature  (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    dt_analysis              (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    satellite_zenith_angle   (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    ...                       ...\n",
-       "    sses_standard_deviation  (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    wind_speed               (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    sst_dtime                (time, lat, lon) timedelta64[ns] dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    crs                      (time) int32 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
-       "    sst_gradient_magnitude   (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "    sst_front_position       (time, lat, lon) float32 dask.array<chunksize=(1, 9000, 18000), meta=np.ndarray>\n",
-       "Attributes: (12/58)\n",
-       "    Conventions:                Conventions = CF-1.7, ACDD-1.3\n",
-       "    acknowledgement:            Please acknowledge the use of these data with...\n",
-       "    cdm_data_type:              grid\n",
-       "    comment:                    SSTs are a weighted average of the SSTs of co...\n",
-       "    creator_email:              Alex.Ignatov@noaa.gov\n",
-       "    creator_name:               Alex Ignatov\n",
-       "    ...                         ...\n",
-       "    col_start:                  2879\n",
-       "    col_count:                  3875\n",
-       "    l3u_bias_subskin_night:     0.034\n",
-       "    l3u_bias_subskin_day:       0.018\n",
-       "    l3u_bias_depth_night:       0.01\n",
-       "    l3u_bias_depth_day:         0.012
" - ], - "text/plain": [ - "\n", - "Dimensions: (lon: 18000, lat: 9000, time: 30)\n", - "Coordinates:\n", - " * lon (lon) float32 -180.0 -180.0 -179.9 ... 180.0 180.0\n", - " * lat (lat) float32 89.99 89.97 89.95 ... -89.97 -89.99\n", - " * time (time) datetime64[ns] 2021-04-01T08:10:01 ... 20...\n", - "Data variables: (12/13)\n", - " quality_level (time, lat, lon) float32 dask.array\n", - " l2p_flags (time, lat, lon) int16 dask.array\n", - " or_number_of_pixels (time, lat, lon) float32 dask.array\n", - " sea_surface_temperature (time, lat, lon) float32 dask.array\n", - " dt_analysis (time, lat, lon) float32 dask.array\n", - " satellite_zenith_angle (time, lat, lon) float32 dask.array\n", - " ... ...\n", - " sses_standard_deviation (time, lat, lon) float32 dask.array\n", - " wind_speed (time, lat, lon) float32 dask.array\n", - " sst_dtime (time, lat, lon) timedelta64[ns] dask.array\n", - " crs (time) int32 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n", - " sst_gradient_magnitude (time, lat, lon) float32 dask.array\n", - " sst_front_position (time, lat, lon) float32 dask.array\n", - "Attributes: (12/58)\n", - " Conventions: Conventions = CF-1.7, ACDD-1.3\n", - " acknowledgement: Please acknowledge the use of these data with...\n", - " cdm_data_type: grid\n", - " comment: SSTs are a weighted average of the SSTs of co...\n", - " creator_email: Alex.Ignatov@noaa.gov\n", - " creator_name: Alex Ignatov\n", - " ... ...\n", - " col_start: 2879\n", - " col_count: 3875\n", - " l3u_bias_subskin_night: 0.034\n", - " l3u_bias_subskin_day: 0.018\n", - " l3u_bias_depth_night: 0.01\n", - " l3u_bias_depth_day: 0.012" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "\n", - "# Open data files with Xarray\n", - "\n", - "import xarray as xr\n", - "\n", - "ds = xr.open_mfdataset(earthaccess.open(results))\n", - "ds" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "546cea9d-5cd8-406b-aea6-b64dd24b1755", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 266 ms, sys: 71.1 ms, total: 337 ms\n", - "Wall time: 35 s\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%%time\n", - "\n", - "# Compute and plot some results from the dataset\n", - "\n", - "result = ds.sea_surface_temperature.notnull().mean({'lon','lat'}).compute()\n", - "result.plot();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9de61942-ed61-4668-ac67-e1b48375c965", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.9.16" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}