{
    "info": {
        "author": "Team Deep-Data",
        "author_email": "seansmith@mines.edu",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
        ],
        "description": "################################################################################\n#\n# Copyright (C) 2019 Team Deep-Data, Colorado School of Mines\n#\n# Date created: 1/22/19\n# Date last updated:\n#\n# Creators:\n#   - Sean Smith            seansmith@mines.edu\n#   - Tyler Murphy          tmurphy@mines.edu\n#   - Tyler Blount          trblount@mines.edu\n#   - Sydney Nelson         snelson1@mines.edu\n#   - Josh Grego            jgrego@mines.edu\n#   - Jake Steiner          msteiner@mines.edu\n#   - Marcelo Gonzales      magonzal@mines.edu\n#   - Daniel Hanuszczak     danielhanuszczak@mines.edu\n#\n################################################################################\n\n\nIncluded below are file descriptions for all files in deep_data_package module\nalong will descriptions of functionality.\n\n\n################################################################################\n###                              file_reader.py                              ###\n################################################################################\n\n    Module for reading AVIRIS flight data and mapping\n\n# OVERVIEW =====================================================================\n\n    Classes ====================================================================\n        hyperion_band_reader\n        aviris_band_reader\n        pickled_aviris_band_reader\n\n    Functions ==================================================================\n        select_closest_band\n        create_pickled_aviris_flight\n        get_available_aviris_flights\n        get_available_pickled_aviris_flights\n        get_available_hyperion_passes\n\n\n\n# CLASS hyperion_band_reader ===================================================\n\n      Class for reading Hyperion data from GEOtiff L1 files\n\n      NOTE: bands 1-70 and VNIR, bands 71-242 are SWIR\n\n    Reference ==================================================================\n        https://archive.usgs.gov/archive/sites/eo1.usgs.gov/EO1userguidev2pt320030715UC.pdf\n        https://crisp.nus.edu.sg/~research/tutorial/eo1.htm\n        https://crisp.nus.edu.sg/~research/tutorial/eo1.htm\n\n    Inputs =====================================================================\n        Optional:\n            hyperion_pass - name of Hyperion pass to load (Default EO1H0410362008289110KF)\n            scale_factor - number to divide bands by (Defaul 80 to get radiance values)\n\n    Returns ====================================================================\n        class to load radiance bands as np arrays\n\n    class Attributes ===========================================================\n        band_reader.hyperion_pass - Hyperion flight loaded\n        band_reader.scale_factor - number to divide bands by (Defaul 80 to get radiance values)\n        band_reader.mode - self identified mode for reference ('hyperion')\n        band_reader.approx_band_centers - string refence to what band centers correspond to what files in Hyperion GEOtif files\n        self.swir_actual_band_centers - caluclated band centers for SWIR bands (for reference)\n\n\n    METHODS ====================================================================\n\n        load_band ==============================================================\n            By defualt loads Hyperion pass EO1H0410362008289110KF over sunshine canyon\n            landfill\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                band_req - band wavelength to load\n                adjust_for_gain - N/A\n\n            Returns ============================================================\n                2D np array of radiance data for band wavelength called\n\n                - To load a row\n\n                    band_array[row_number, :]\n\n                - To load a column\n\n                    band_array[:, col_number]\n\n                - To load a pixel\n\n                    band_array[row_number, col_number]\n\n\n        load_pixel =============================================================\n            Function for reading all bands of an individual pixel from AVIRIS\n            flight data\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                row - int of row number of requested pixel\n                col - int of column number of requested pixel\n                adjust_for_gain - N/A\n\n            Returns ==========================================================\n                Ordered dict of wavelengths vs irradiance for requested pixel\n\n\n\n# CLASS aviris_band_reader =====================================================\n\n      Class for reading AVIRIS flight data from uncompressed AVIRIS flight\n      folder. No files need to be modified after downloading from AVIRIS data\n      portal. Just uncompress in the aviris_flight_folder and go.\n\n      By defualt loads AVIRIS flight f111115t01p00r08 over sunshine canyon\n      landfill\n\n    Reference ==============================================================\n        N/A\n\n    Inputs =================================================================\n        Optional:\n            aviris_flight_number - AVIRIS flight number to load\n            aviris_filename - filename to load in AVIRIS flight number folder\n            samples - from hdr file in AVERIS flight folder (Defualt 780)\n            lines - from hdr file in AVERIS flight folder (Defualt 8355)\n            bands - from hdr file in AVERIS flight folder (Defualt 224)\n            aviris_calibration_filename - name of AVIRIS file for reflectance calibration\n            aviris_gain_filename - name of AVIRIS gain file for reflectance calibration\n\n    Returns ================================================================\n        class to load radiance bands as np arrays\n\n    class Attributes =======================================================\n        band_reader.aviris_flight -  AVIRIS flight loaded\n        band_reader.n_cols - number of columns in AVIRIS band file (equals input samples)\n        band_reader.n_rows - number of rows in AVIRIS band file (equals input lines)\n        band_reader.n_bands - number of bands in AVIRIS band file (equals input bands)\n        band_reader.scale_factor - multiplier of bands (equals input scale_factor)\n        band_reader.aviris_flight_folder_filepath - full filepath for AVIRIS flight folder\n        band_reader.bands_filepath - full filepath for AVIRIS band file\n\n        band_reader.info - dict with useful info from AVIRIS flight\n            Contains:\n                # General info\n                ['info']['n_rows'] = number of rows in .npy files\n                ['info']['n_cols'] = number of columns in .npy files\n                ['info']['n_bands'] = number of bands from AVIRIS flight\n                ['info']['AVIRIS_flight'] = aviris_flight\n\n                # Band info\n                ['band_calibration']['band_quantity'] = 'Wavelength'\n                ['band_calibration']['band_unit'] = 'nm'\n                ['band_calibration']['centers'] = mathmatical center of wavelength\n                ['band_calibration']['bandwidths'] = bandwidths of wavelengths\n                ['band_calibration']['bands'] = wavelengths callable\n\n                # Gain values\n                ['gain_values'] = np array of gain values for each band\n\n            Call any of above w/ band_reader.info['INSERT_AS_SHOWN_ABOVE']\n\n    METHODS ====================================================================\n\n        parse_aviris_flight ====================================================\n            Function for loading AVIRIS flight files of the first time\n            By defualt loads AVIRIS flight f111115t01p00r08 over sunshine canyon landfill\n\n            Inputs =============================================================\n                info_file_name - name for info file to be written by parser\n                aviris_calibration_filename - name of AVIRIS file for reflectance calibration\n                aviris_gain_filename - name of AVIRIS gain file for reflectance calibration\n\n            Returns ============================================================\n                flight_dict - dict with useful info from AVIRIS flight\n                    Contains:\n                        # General info\n                        ['info']['n_rows'] = number of rows in .npy files\n                        ['info']['n_cols'] = number of columns in .npy files\n                        ['info']['n_bands'] = number of bands from AVIRIS flight\n                        ['info']['AVIRIS_flight'] = aviris_flight\n\n                        # Band info\n                        ['band_calibration']['band_quantity'] = 'Wavelength'\n                        ['band_calibration']['band_unit'] = 'nm'\n                        ['band_calibration']['centers'] = mathmatical center of wavelength\n                        ['band_calibration']['bandwidths'] = bandwidths of wavelengths\n                        ['band_calibration']['bands'] = wavelengths callable\n\n                        # Gain values\n                        ['gain_values'] = np array of gain values for each band\n\n\n        get_memmap =============================================================\n            Function for loading memmap of AVIRIS band file\n\n            Inputs =============================================================\n                N/A\n\n            Returns ============================================================\n                np.memmap of AVIRIS band file\n\n\n        load_band ==============================================================\n            Function for reading AVIRIS flight data from .npy files pickled by\n            create_pickled_aviris_flight()\n\n            By defualt loads AVIRIS flight f111115t01p00r08 over sunshine canyon\n            landfill\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                band_req - band wavelength to load\n                adjust_for_gain - If want to divide band array by gain value in .gain file (Default: False)\n\n            Returns ============================================================\n                2D np array of radiance data for band wavelength called\n\n                - To load a row\n\n                    band_array[row_number, :]\n\n                - To load a column\n\n                    band_array[:, col_number]\n\n                - To load a pixel\n\n                    band_array[row_number, col_number]\n\n\n        load_pixel =============================================================\n            Function for reading all bands of an individual pixel from AVIRIS\n            flight data\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                row - int of row number of requested pixel\n                col - int of column number of requested pixel\n                adjust_for_gain - N/A\n\n            Returns ============================================================\n                Ordered dict of wavelengths vs irradience for requested pixel\n\n\n\n# CLASS pickled_aviris_band_reader =============================================\n\n      Class for reading AVIRIS flight data from .npy files pickled by\n      create_pickled_aviris_flight()\n\n      By defualt loads AVIRIS flight f111115t01p00r08 over sunshine canyon\n      landfill\n\n    Reference ==============================================================\n        N/A\n\n    Inputs =================================================================\n        Optional:\n            aviris_flight - AVIRIS flight to load\n\n    Returns ================================================================\n        class to load radiance bands as np arrays\n\n    class Attributes =======================================================\n        band_reader.aviris_flight -  AVIRIS flight loaded\n        band_reader.np_path - path will load .npy files from\n\n        band_reader.info - dict with useful info from AVIRIS flight\n            Contains:\n                # General info\n                ['info']['n_rows'] = number of rows in .npy files\n                ['info']['n_cols'] = number of columns in .npy files\n                ['info']['n_bands'] = number of bands from AVIRIS flight\n                ['info']['AVIRIS_flight'] = aviris_flight\n\n                # Band info\n                ['band_calibration']['band_quantity'] = 'Wavelength'\n                ['band_calibration']['band_unit'] = 'nm'\n                ['band_calibration']['centers'] = mathmatical center of wavelength\n                ['band_calibration']['bandwidths'] = bandwidths of wavelengths\n                ['band_calibration']['bands'] = wavelengths callable\n\n                # Gain values\n                ['gain_values'] = np array of gain values for each band\n\n            Call any of above w/ band_reader.info['INSERT_AS_SHOWN_ABOVE']\n\n    METHODS ====================================================================\n\n        load_band ==============================================================\n            Function for reading AVIRIS flight data from .npy files pickled by\n            create_pickled_aviris_flight()\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                band_req - band wavelength to load\n\n            Returns ============================================================\n                2D np array of radiance data for band wavelength called\n\n                - To load a row\n\n                    band_array[row_number, :]\n\n                - To load a column\n\n                    band_array[:, col_number]\n\n                - To load a pixel\n\n                    band_array[row_number, col_number]\n\n\n        load_pixel =============================================================\n            Function for reading all bands of an individual pixel from AVIRIS\n            flight data from .npy files pickled by create_pickled_aviris_flight()\n\n            Reference ==========================================================\n                N/A\n\n            Inputs =============================================================\n                row - int of row number of requested pixel\n                col - int of column number of requested pixel\n                adjust_for_gain - N/A\n\n            Returns ============================================================\n                Ordered dict of wavelengths vs irradience for requested pixel\n\n\n\n# FUNCTION select_closest_band =================================================\n\n    Returns closest band available to band_req.\n\n    Inputs =============================================================\n        band_req - band wavelength to match\n        band_req - list of band wavelengths available\n\n    Returns ============================================================\n        band available, if two numbers are equally close, returns the\n        smallest number.\n\n\n\n# FUNCTION create_pickled_aviris_flight ========================================\n\n    Function for creating pickled AVIRIS flight data using spectral python library\n\n    By defualt loads AVIRIS flight f111115t01p00r08 over sunshine canyon landfill\n\n    Reference ==============================================================\n        N/A\n\n    Inputs =================================================================\n        Optional:\n            aviris_flight - AVIRIS flight number\n            aviris_flight_folder - AVIRIS flight folder to load\n            aviris_bands_filename - filename to load in AVIRIS flight number folder\n            samples - from hdr file in AVERIS flight folder (Defualt 780)\n            lines - from hdr file in AVERIS flight folder (Defualt 8355)\n            bands - from hdr file in AVERIS flight folder (Defualt 224)\n            aviris_calibration_filename - name of AVIRIS file for reflectance calibration\n            aviris_gain_filename - name of AVIRIS gain file for reflectance calibration\n            adjust_for_gain - if should devide bands by associated gain value to true values (Default False)\n            scale_factor - if want to dived all values by some value (Default 10000.0)\n\n    Returns ================================================================\n        N/A\n\n\n\n# FUNCTION get_available_aviris_flights ========================================\n\n    Function listing all AVIRIS flights available\n\n    Inputs =================================================================\n        N/A\n\n    Returns ================================================================\n        List of AVIRIS flights available\n\n\n\n# FUNCTION get_available_pickled_aviris_flights ================================\n\n    Function listing all pickled AVIRIS flights available\n\n    Inputs =================================================================\n        N/A\n\n    Returns ================================================================\n        List of pickled AVIRIS flights available\n\n\n\n# FUNCTION get_available_hyperion_passes =======================================\n\n    Function listing all Hyperion passes available\n\n    Inputs =================================================================\n        N/A\n\n    Returns ================================================================\n        List of Hyperion passes available\n\n\n\n################################################################################\n\n\n\n################################################################################\n###                                 mapper.py                                ###\n################################################################################\n\n    Module for mapping band ratio output arrays\n\n# OVERVIEW =====================================================================\n\n    Functions ==================================================================\n        create_heatmap_interactive\n\n\n\n# FUNCTION create_heatmap_interactive ==========================================\n\n    Function for creating an interactive heatmap\n\n    Reference ==============================================================\n        N/A\n\n    Inputs =================================================================\n        band_reader - band_reader class instance\n        bandratio_array - bandratio result array for heatmap\n        bandratio_array_name - name of bandratio calculated\n        flight_name - name of the flight\n        alpha - transparency value of overlay (Defualt 0.6)\n        gamma_1 - threshold value for map (Default mean of normalized bandratio_array)\n        interval - step value of threshold slider (Default 0.00001)\n        std_multiplier - multiplier of std for range of values of threshold slider (Default 3)\n        clipped - if want clipped heatmap instead of default treshhold (Default False)\n        display - show plt (Default True)\n        save - save plt when (Default False)\n        cmap - color scheme for heatmap (Default 'hot' for threshold, 'jet' for clipped)\n        quiet - if should not log info about bandratio_array (Defualt False)\n        rgb_scale_value - float value to increase brightness of rgb image\n\n    Returns ================================================================\n        N/A\n\n\n\n################################################################################\n\n\n\n################################################################################\n###                              band_ratios.py                              ###\n################################################################################\n\n    Module for calculating band ratios\n\n# OVERVIEW =====================================================================\n\n    Functions ==================================================================\n      Deep_Data\n      HI_1453\n      HI_1215\n      HI_1732\n      GM\n      NDVI\n      NDPI\n\n\n\n# FUNCTION Deep_Data ===========================================================\n\n    Deep-Data Hydrocarbon Index ================================================\n        Convert numpy arrays of radiance data to a Deep-Data hydrocarbon\n        index map\n\n    Inputs =====================================================================\n        L_1197 : At-sensor radiance at 1197 nm wavelength (numpy array)\n        L_1216 : At-sensor radiance at 1216 nm wavelength (numpy array)\n        L_1235 : At-sensor radiance at 1235 nm wavelength (numpy array)\n        L_1373 : At-sensor radiance at 1373 nm wavelength (numpy array)\n        L_1453 : At-sensor radiance at 1453 nm wavelength (numpy array)\n        L_1503 : At-sensor radiance at 1503 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        Deep-Data Hydrocarbon Index Map\n\n\n\n# FUNCTION HI_1453 =============================================================\n\n    1453 Hydrocarbon Index =====================================================\n        Convert numpy arrays of radiance data to a 1453 hydrocarbon index map\n\n    Inputs =====================================================================\n        L_1373 : At-sensor radiance at 1373 nm wavelength (numpy array)\n        L_1453 : At-sensor radiance at 1453 nm wavelength (numpy array)\n        L_1503 : At-sensor radiance at 1503 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        1453 Hydrocarbon Index Map\n\n\n\n# FUNCTION HI_1215 =============================================================\n\n    1215 Hydrocarbon Index =====================================================\n        Convert numpy arrays of radiance data to a 1215 hydrocarbon index map\n\n    Inputs =====================================================================\n        L_1197 : At-sensor radiance at 1197 nm wavelength (numpy array)\n        L_1216 : At-sensor radiance at 1216 nm wavelength (numpy array)\n        L_1235 : At-sensor radiance at 1235 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        1215 Hydrocarbon Index Map\n\n\n\n# FUNCTION HI_1732 =============================================================\n\n    1732 Hydrocarbon Index =================================================\n        Convert numpy arrays of radiance data to a 1732 hydrocarbon index map\n\n    Inputs =====================================================================\n        L_1705 : At-sensor radiance at 1705 nm wavelength (numpy array)\n        L_1729 : At-sensor radiance at 1729 nm wavelength (numpy array)\n        L_1741 : At-sensor radiance at 1741 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        1732 Hydrocarbon Index Map\n\n\n\n# FUNCTION GM ==================================================================\n\n    Goddijn-Murphy Index =======================================================\n        From: \"Proof of concept for a model of light reflectance of plastics\n        floating on natural waters\" by Lonneke Goddijn-Murphy and Juvenal\n        Dufaur. - See Table 5\n\n        Convert numpy arrays of radiance data to a Goddijn-Murphy map\n\n    Inputs =====================================================================\n        L_850 : At-sensor radiance at 850 nm wavelength (numpy array)\n        L_1660 : At-sensor radiance at 1660 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        Goddijn-Murphy Map\n\n\n\n# FUNCTION NDVI ================================================================\n\n    NDVI =======================================================================\n        Convert numpy arrays of radiance data to a NDVI map\n\n    Inputs =====================================================================\n        L_1006 : At-sensor radiance at 1006 nm wavelength (numpy array)\n        L_675 : At-sensor radiance at 675 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        NDVI Map\n\n\n\n# FUNCTION NDPI ================================================================\n\n    NDPI =======================================================================\n        Convert numpy arrays of radiance data to a NDPI map\n\n    Inputs =====================================================================\n        L_1263 : At-sensor radiance at 1263 nm wavelength (numpy array)\n        L_2417 : At-sensor radiance at 2417 nm wavelength (numpy array)\n\n    Returns ====================================================================\n        NDPI Map\n\n\n\n################################################################################",
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