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# http://cimss.ssec.wisc.edu/training_data/
# Record number:15,704
# Record length: 338
# Datatype: real*4
# RECORD FIELDS
# 1:101 temperature profile [K]
# 102:202 mixing ratio profile [kg/kg]
# 203:303 ozone profile [ppmv]
# 304 latitude
# 305 longitude
# 306 surface pressure [hPa]
# 307 skin temperature [K]
# 308 wind speed (m/s)
# - value used for finding seawater emissivity
# (equal to 1 2 3 4 5 6 7 8 9 10 12.5 or 15)
# ** For Land, this field is -999
# 309 tpw [cm]
# 310 ecosystem, igbp classification
# 311 elevation [m]
# 312 fraction land
# 313 year
# 314 month
# 315 day
# 316 hour
# 317 profile type
# 1 NOAA - 88b 2 TIGR - 3 3 Radiosondes 4 Ozonesondes 5 ECMWF
# 318:327 frequency (wavenumber) of emissivity at 10 BF emis hinge points
# 328:337 emissivity spectra
# 338 spare
import numpy as np
f = open('SeeBorV5.1_Training_data_Emis10inf2004.bin','rb')
data = np.fromfile(file=f, dtype=np.float32)
data = data.reshape((15704, 338))
(temperature_profile, mixing_ratio_profile, ozone_profile, latitude,
longitude, surface_pressure, skin_temperature, wind_speed, tpw,
ecosystem, elevation, fraction_land, year, month, day, hour,
profile_type, frequency, emissivity_spectra) = (data[:, range(0,100)],
data[:, range(101, 201)], data[:, range(202, 302)], data[:, 303],
data[:, 304], data[:, 305], data[:, 306], data[:, 307], data[:, 308],
data[:, 309], data[:, 310], data[:, 311], data[:, 312], data[:, 313],
data[:, 314], data[:, 315], data[:, 316], data[:, range(317, 326)],
data[:, range(327, 336)])
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