From 802ba8b6a71b7e03e98c67fa87e8c6ff004e6e7e Mon Sep 17 00:00:00 2001 From: spestana Date: Sat, 16 Mar 2024 13:27:00 -0700 Subject: [PATCH] Add wip demo notebook --- examples/jsontest.ipynb | 8127 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 8127 insertions(+) create mode 100644 examples/jsontest.ipynb diff --git a/examples/jsontest.ipynb b/examples/jsontest.ipynb new file mode 100644 index 0000000..2f1ed91 --- /dev/null +++ b/examples/jsontest.ipynb @@ -0,0 +1,8127 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "======================================== goes-py =========================================\n", + " A Python package can be useful to download dataset from goes satellite on AWS 0.2.1v\n", + "==========================================================================================\n" + ] + } + ], + "source": [ + "import goes_ortho as go" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Files will be downloaded and then cropped to these bounds:\n", + "\t(-120.0,34.0).\t.(-118.0,34.0)\n", + "\n", + "\n", + "\n", + "\t(-120.0,32.0).\t.(-118.0,32.0)\n", + "\n", + "For each S3 bucket, download the corresponding observations\n", + "Downloading... the product ABI-L1b-RadC \n", + "Downloading dataset to... 00 UTC\n", + "OR_ABI-L1b-RadC-M6C14_G17_s20200630056176_e20200630058549_c20200630059063.nc: [##########] 100% 5.105948 MB/5.105948 MB\n", + "Subsetting files in.../storage/spestana/scratchspace//goes17/2020/3/3/ABI-L1b-RadC/00/C14/\n", + "\n", + "Dimensions: (y: 1500, x: 2500,\n", + " number_of_time_bounds: 2,\n", + " number_of_image_bounds: 2,\n", + " band: 1,\n", + " num_star_looks: 24)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 0.1282 ... ...\n", + " * x (x) float64 -0.06997 .....\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_id (band) int8 ...\n", + " band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T00:04:06.1Z\n", + " time_coverage_start: 2020-03-03T00:01:17.6Z\n", + " time_coverage_end: 2020-03-03T00:03:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: 2efe35f5-c89d-468b-aeee-556765794503\n", + "SW Corner: 0.04259563855199094, 0.09060644043472878\n", + "SE Corner: 0.04735111161809259, 0.09046438908222797\n", + "NW Corner: 0.0414986973393493, 0.09529637773914672\n", + "NE Corner: 0.04613392766596448, 0.09515084077391966\n", + "Corner coords chosen: N: 0.09529637773914672, S: 0.09046438908222797; E: 0.04735111161809259, W: 0.0414986973393493\n", + "\n", + "Dimensions: (y: 1500, x: 2500,\n", + " number_of_time_bounds: 2,\n", + " number_of_image_bounds: 2,\n", + " band: 1,\n", + " num_star_looks: 24)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 0.1282 ... ...\n", + " * x (x) float64 -0.06997 .....\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_id (band) int8 ...\n", + " band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T00:09:05.2Z\n", + " time_coverage_start: 2020-03-03T00:06:17.6Z\n", + " time_coverage_end: 2020-03-03T00:08:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: ace15021-a63e-46d7-8d0c-4afdd34c868d\n", + "SW Corner: 0.04259563855199094, 0.09060644043472878\n", + "SE Corner: 0.04735111161809259, 0.09046438908222797\n", + "NW Corner: 0.0414986973393493, 0.09529637773914672\n", + "NE Corner: 0.04613392766596448, 0.09515084077391966\n", + "Corner coords chosen: N: 0.09529637773914672, S: 0.09046438908222797; E: 0.04735111161809259, W: 0.0414986973393493\n", + "\n", + "Dimensions: (y: 1500, x: 2500,\n", + " number_of_time_bounds: 2,\n", + " number_of_image_bounds: 2,\n", + " band: 1,\n", + " num_star_looks: 24)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 0.1282 ... ...\n", + " * x (x) float64 -0.06997 .....\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_id (band) int8 ...\n", + " band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T00:14:03.7Z\n", + " 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t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " 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1,\n", + " num_star_looks: 24)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 0.1282 ... ...\n", + " * x (x) float64 -0.06997 .....\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_id (band) int8 ...\n", + " band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " 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(number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T12:34:04.1Z\n", + " time_coverage_start: 2020-03-03T12:31:17.6Z\n", + " time_coverage_end: 2020-03-03T12:33:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: 097a8786-3c53-44b6-8729-24c887564115\n", + "SW Corner: 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"Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " 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" band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " 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...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T12:49:04.7Z\n", + " time_coverage_start: 2020-03-03T12:46:17.6Z\n", + " time_coverage_end: 2020-03-03T12:48:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: a7c39c42-e741-410b-ad44-c3ba888e2d6a\n", + "SW Corner: 0.04259563855199094, 0.09060644043472878\n", + "SE Corner: 0.04735111161809259, 0.09046438908222797\n", + "NW Corner: 0.0414986973393493, 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datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T12:54:00.9Z\n", + " time_coverage_start: 2020-03-03T12:51:17.6Z\n", + " time_coverage_end: 2020-03-03T12:53:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: a50996d1-2ef3-4cc2-a586-19bb3fb98306\n", + "SW Corner: 0.04259563855199094, 0.09060644043472878\n", + "SE Corner: 0.04735111161809259, 0.09046438908222797\n", + "NW Corner: 0.0414986973393493, 0.09529637773914672\n", + "NE Corner: 0.04613392766596448, 0.09515084077391966\n", + "Corner coords chosen: N: 0.09529637773914672, S: 0.09046438908222797; E: 0.04735111161809259, W: 0.0414986973393493\n", + "\n", + "Dimensions: (y: 1500, x: 2500,\n", + " number_of_time_bounds: 2,\n", + " number_of_image_bounds: 2,\n", + " band: 1,\n", + " num_star_looks: 24)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 0.1282 ... ...\n", + " * x (x) float64 -0.06997 .....\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_id (band) int8 ...\n", + " band_wavelength (band) float32 ...\n", + " t_star_look (num_star_looks) datetime64[ns] ...\n", + " band_wavelength_star_look (num_star_looks) float32 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band, num_star_looks\n", + "Data variables: (12/35)\n", + " Rad (y, x) float32 ...\n", + " DQF (y, x) float32 ...\n", + " time_bounds (number_of_time_bounds) datetime64[ns] ...\n", + " goes_imager_projection int32 ...\n", + " y_image_bounds (number_of_image_bounds) float32 ...\n", + " x_image_bounds (number_of_image_bounds) float32 ...\n", + " ... ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " earth_sun_distance_anomaly_in_AU float32 ...\n", + " algorithm_dynamic_input_data_container int32 ...\n", + " processing_parm_version_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + " star_id (num_star_looks) float32 ...\n", + "Attributes: (12/30)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " production_site: RBU\n", + " ... ...\n", + " timeline_id: ABI Mode 6\n", + " date_created: 2020-03-03T12:59:02.4Z\n", + " time_coverage_start: 2020-03-03T12:56:17.6Z\n", + " time_coverage_end: 2020-03-03T12:58:54.9Z\n", + " LUT_Filenames: SpaceLookParams(FM2A_CDRL79RevP_DO_08_00_01)-6...\n", + " id: dcb2f407-c360-47ae-8f4f-77041e99c5e1\n", + "SW Corner: 0.04259563855199094, 0.09060644043472878\n", + "SE Corner: 0.04735111161809259, 0.09046438908222797\n", + "NW Corner: 0.0414986973393493, 0.09529637773914672\n", + "NE Corner: 0.04613392766596448, 0.09515084077391966\n", + "Corner coords chosen: N: 0.09529637773914672, S: 0.09046438908222797; E: 0.04735111161809259, W: 0.0414986973393493\n", + "Done\n" + ] + } + ], + "source": [ + "go.get_data.download_abi('example.json')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import xarray as xr\n", + "ds = xr.open_dataset('/storage/spestana/scratchspace/goes17/2020/3/3/ABI-L1b-RadC/00/C14/OR_ABI-L1b-RadC-M6C14_G17_s20200630001176_e20200630003549_c20200630004061.nc')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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