Added new plio io modules from PySAT.

import os

import numpy as np

import pandas as pd

def EDR(input_file):

    f = open(input_file, 'rb')  # read as bytes so python won't complain about the binary part of the file

    # read lines of the header until reaching the end of the libs table (collecting other metadata along the way)

    end_of_libs_table = False

    while end_of_libs_table is False:

        line = str(f.readline(), 'utf-8').replace('\r', '').replace('\n',

                                                                    '')  # convert the current line to a string and get rid of newline characters

        line = line.split('=')  # split the line on equals sign if present

        # look for the name of the value we want, if the current line has it, then set the value

        if 'RECORD_BYTES' in line[0]:

            rbytes = int(line[1])

        if 'LABEL_RECORDS' in line[0]:

            lrecs = int(line[1])

        if 'SPACECRAFT_CLOCK_START_COUNT' in line[0]:

            sclock = int(line[1].replace('"', '').split('.')[0])

        if 'SEQUENCE_ID' in line[0]:

            seqID = line[1].replace('"', '')

        if 'INSTRUMENT_FOCUS_DISTANCE' in line[0]:

            focus_dist = int(line[1])

        if 'INSTRUMENT_TEMPERATURE' in line[0]:

            instrument_temps = line[1] \

                               + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '') \

                               + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '') \

                               + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '')

            instrument_temps = [float(i) for i in

                                instrument_temps.replace('<degC>', '').replace('(', '').replace(')', '').replace(' ',

                                                                                                                 '').split(

                                    ',')]

            instrument_temps_name = str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '')

            instrument_temps_name = instrument_temps_name.split('=')[1] \

                                    + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '') \

                                    + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '') \

                                    + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '') \

                                    + str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '')

            instrument_temps_name = instrument_temps_name.replace(' ', '').replace('(', '').replace(')', '').replace(

                '"', '').split(',')

            f.readline()

            pass

        try:

            if 'CCAM_LIBS_DATA_CONTAINER' in line[1]:

                nshots = int(str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '').split('=')[1])

                start_byte = int(str(f.readline(), 'utf-8').replace('\r', '').replace('\n', '').split('=')[1])

            if 'END_OBJECT' in line[0] and 'CCAM_LIBS_TABLE' in line[1]:

                end_of_libs_table = True

        except:

            pass

    f.close()

    header_skip = lrecs * rbytes  # calculate the number of header bytes to skip to get to the real data

    with open(input_file, "rb") as f:

        f.seek(header_skip + start_byte - 1, 0)

        spectra = []

        while spectra.__len__() < nshots:

            spectrum = []

            while spectrum.__len__() < 6444:

                spectrum.append(int.from_bytes(f.read(2), byteorder='big', signed=False))

            spectra.append(spectrum)

    spectra = np.array(spectra, dtype='int')

    cols = np.array(list(range(spectra.shape[1]))) + 1

    cols = [('channel', i) for i in cols]

    inds = np.array(list(range(spectra.shape[0]))) + 1

    sp = pd.DataFrame(spectra, columns=pd.MultiIndex.from_tuples(cols), index=inds)

    sp[('meta', 'EDR_file')] = os.path.basename(input_file)

    sp[('meta', 'Spacecraft_Clock')] = sclock

    sp[('meta', 'Shot')] = sp.index

    sp[('meta', 'SeqID')] = seqID

    sp[('meta', 'Focus_Distance')] = focus_dist

    for ind, name in enumerate(instrument_temps_name):

        sp[('meta', name + '_temp')] = instrument_temps[ind]

    sp.to_csv('test.csv')

    return sp

import numpy as np

from osgeo import gdal

def openm3(input_data):

    if input_data.split('.')[-1] == 'hdr':

        # GDAL wants the img, but many users aim at the .hdr

        input_data = input_data.split('.')[0] + '.img'

    ds = gdal.Open(input_data)

    ref_array = ds.GetRasterBand(1).ReadAsArray()

    metadata = ds.GetMetadata()

    wv_array = metadatatoband(metadata)

    return wv_array, ref_array, ds

def metadatatoband(metadata):

    wv2band = []

    for k, v in metadata.iteritems():

        try:

            wv2band.append(float(value))

        except:

            v = v.split(" ")[-1].split("(")[1].split(")")[0]

            wv2band.append(float(v))

    wv2band.sort(key=int)

    return np.asarray(wv2band)

import numpy as np

from osgeo import gdal

def openmi(input_data):

    ds = gdal.Open(input_data)

    band_pointers = []

    nbands = ds.RasterCount

    for b in xrange(1, nbands + 1):

        band_pointers.append(ds.GetRasterBand(b))

    ref_array = ds.GetRasterBand(1).ReadAsArray()

    wv_array = None

    return wv_array, ref_array[::3, ::3], ds

def getspectra(x, y, ds):

    nbands = ds.RasterCount

    reflectance = np.empty(nbands)

    for b in range(1, nbands + 1):

        reflectance[b - 1] = ds.GetRasterBand(b).ReadAsArray(y, x, 1, 1)

    mergedref = np.empty(nbands - 1)

    mergedref[:4] = reflectance[:4]

    mergedref[4] = (reflectance[4] + reflectance[5]) / 2

    mergedref[5:] = reflectance[6:]

    return mergedref

try:

import yaml

except:

    print('YAML package not installed, disabling yaml_io module')

def read_yaml(inputfile):