import ruamel_yaml as yml
import numpy as np
# import xarray as xr

import read_data as rd
import tests

import ancillary_data as anc


def main():
    datapath = '/ships19/hercules/pveglio/neige_data/snpp_test_input'
    fname_l1b = 'VNP02MOD.A2014213.1548.001.2017301015346.uwssec.bowtie_restored_scaled.nc'
    fname_geo = 'VNP03MOD.A2014213.1548.001.2017301015705.uwssec.nc'
    thresh_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'

    anc_dir = '/ships19/hercules/pveglio/neige_data/snpp_test_input/ancillary/2014_08_01_213'
    sst_file = 'oisst.20140730'
    ndvi_file = 'NDVI.FM.c004.v2.0.WS.00-04.209.hdf'
    geos_cnst = 'GEOS.fp.asm.const_2d_asm_Nx.00000000_0000.V01.nc4'
    geos_lnd = 'GEOS.fpit.asm.tavg1_2d_lnd_Nx.GEOS5124.20140801_1530.V01.nc4'
    geos_ocn = 'GEOS.fpit.asm.tavg1_2d_ocn_Nx.GEOS5124.20140801_1530.V01.nc4'
    geos1 = 'GEOS.fpit.asm.inst3_2d_asm_Nx.GEOS5124.20140801_1500.V01.nc4'
    geos2 = 'GEOS.fpit.asm.inst3_2d_asm_Nx.GEOS5124.20140801_1800.V01.nc4'

    start_time = '2014-08-01 15:48:00.000'
    viirs_data = rd.read_data('viirs', f'{datapath}/{fname_l1b}', f'{datapath}/{fname_geo}')

    sst = np.empty((3232*3200, ), dtype=np.float32)
    ndvi = np.empty((3232*3200, ), dtype=np.float32)
    eco = np.empty((3232*3200, ), dtype=np.ubyte)

    geos_data = {'tpw': np.empty((3232*3200, ), dtype=np.float32),
                 'snowfr': np.empty((3232*3200, ), dtype=np.float32),
                 'icefr': np.empty((3232*3200, ), dtype=np.float32),
                 'ocnfr': np.empty((3232*3200, ), dtype=np.float32),
                 'landicefr': np.empty((3232*3200, ), dtype=np.float32),
                 'sfct': np.empty((3232*3200, ), dtype=np.float32),
                 }

    tpw = np.ones((3232*3200, ), dtype=np.float32)
    snowfr = np.empty((3232*3200, ), dtype=np.float32)
    icefr = np.empty((3232*3200, ), dtype=np.float32)
    ocnfr = np.empty((3232*3200, ), dtype=np.float32)
    landicefr = np.empty((3232*3200, ), dtype=np.float32)
    sfct = np.empty((3232*3200, ), dtype=np.float32)

    sst = anc.py_get_Reynolds_SST(viirs_data.latitude.values.reshape((3232*3200, )),
                                  viirs_data.longitude.values.reshape((3232*3200, )),
                                  anc_dir, sst_file, sst)

    ndvi = anc.py_get_NDVI_background(viirs_data.latitude.values.reshape((3232*3200, )),
                                      viirs_data.longitude.values.reshape((3232*3200, )),
                                      anc_dir, ndvi_file, ndvi)

    eco = anc.py_get_Olson_eco(viirs_data.latitude.values.reshape((3232*3200, )),
                               viirs_data.longitude.values.reshape((3232*3200, )),
                               anc_dir, eco)

    tpw = anc.py_get_GEOS(viirs_data.latitude.values.reshape((3232*3200, )),
                          viirs_data.longitude.values.reshape((3232*3200, )),
                          start_time, anc_dir, geos1, geos2, geos_lnd, geos_ocn, geos_cnst,
                          tpw, snowfr, icefr, ocnfr, landicefr, sfct)

    print(tpw[:10])
    #print(geos_data['tpw'][:10])
    #print(geos_data['snowfr'][:10])
    #print(geos_data['icefr'][:10])
    #print(geos_data['ocnfr'][:10])
    #print(geos_data['landicefr'][:10])
    #print(geos_data['sfct'][:10])

    with open(thresh_file) as f:
        text = f.read()
    thresholds = yml.safe_load(text)

    confidence = np.zeros((5, viirs_data['M01'].shape[0], viirs_data['M01'].shape[1]))

    confidence[0, :, :] = tests.test_11um(viirs_data.M15.values, thresholds['Daytime_Ocean'])
    confidence[1, :, :] = tests.test_11_4diff(viirs_data.M15.values, viirs_data.M13.values,
                                              thresholds['Daytime_Ocean'], viirs_data,
                                              thresholds['Sun_Glint']['bounds'][3])

    confidence[2, :, :] = tests.nir_refl_test(viirs_data.M07.values, thresholds['Daytime_Ocean'],
                                              thresholds['Sun_Glint'], viirs_data)

    # Note that here I'm using M05/M07 but the corresponding hi-res channelsa re I1/I2
    # IMPORTANT: conf_test_dble() needs to be verified. I don't think it's working as intended at the moment
    confidence[3, :, :] = tests.vis_nir_ratio_test(viirs_data.M05.values, viirs_data.M07.values,
                                                   thresholds['Daytime_Ocean'], thresholds['Sun_Glint'])

    # This test needs to be verified, for the granule I'm running everything is zero
    confidence[4, :, :] = tests.test_11um_var(viirs_data.M15.values, thresholds['Nighttime_Ocean'],
                                              thresholds['Daytime_Ocean_Spatial_Variability'])

    return confidence


def test_main():

    rad1 = [[255, 260, 265, 248, 223],
            [278, 285, 270, 268, 256],
            [275, 273, 266, 254, 259]]
    rad2 = [[270, 273, 271, 268, 265],
            [277, 286, 275, 277, 269],
            [280, 281, 272, 270, 267]]
    thresh_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'

    with open(thresh_file) as f:
        text = f.read()

    rad1 = np.array(rad1)
    rad2 = np.array(rad2)

    confidence = np.zeros((2, rad1.shape[0], rad1.shape[1]))

    thresholds = yml.safe_load(text)

    confidence[0, :, :] = tests.test_11um(rad1, thresholds['Daytime_Ocean'])
    confidence[1, :, :] = tests.test_11_4diff(rad1, rad2, thresholds['Daytime_Ocean'])

    print(f'Confidence[0,:,:]: \n {confidence[0, :, :]}')
    print(f'Confidence[1,:,:]: \n {confidence[1, :, :]}')

    return confidence


if __name__ == "__main__":
    test_main()