def _apply_sens_correction(self, band_num, band_wns, band_data, gain):
if self.sens_corr_data == None:
return band_data
band_index = SWIR_BANDS.index(band_num)
corr_obj = self.sens_corr_data[band_index]
unit_col_idx = corr_obj.labels.index(RAD_CNV_UNIT_COL)
for pol_idx, pol_name in enumerate(POL_ORDER):
corr_col_name = RAD_CNV_SENS_COL_TMPL % (band_num, pol_name, gain[pol_idx])
try:
corr_col_idx = corr_obj.labels.index(corr_col_name)
except:
raise IOError('Could not find column named: %s in sensitivity file: %s' % (corr_col_name, corr_obj.filename))
# Retrieve correction data
resampled_corr_data = numpy.zeros(band_data.shape[0], dtype=float)
src_corr_data = corr_obj.data[:,corr_col_idx]
resampled_corr_data = OCO_MathUtil.linear_interpol(src_corr_data, corr_obj.data[:, unit_col_idx], band_wns[:,pol_idx], extrapolate=False, extrap_err=False)
valid_points = numpy.where(abs(resampled_corr_data) > 0.0)[0]
band_data[valid_points, pol_idx] *= resampled_corr_data[valid_points]
return band_data
def get_value(self, time_struct):
year, month, doy = (time_struct.tm_year, time_struct.tm_mon, time_struct.tm_yday)
year_frac = float(doy) / float(time.strftime('%j', datetime.datetime(year, 12, 31).utctimetuple()))
curr_dec_date = year + year_frac
trend_value = OCO_MathUtil.linear_interpol(self.values, self.dates, [curr_dec_date], extrapolate=True, extrap_err=False)
# Resulting trend value should be in first element of matrix
return trend_value[0]
def get_value(self, time_struct):
year, month, doy = (time_struct.tm_year, time_struct.tm_mon,
time_struct.tm_yday)
year_frac = float(doy) / float(
time.strftime('%j',
datetime.datetime(year, 12, 31).utctimetuple()))
curr_dec_date = year + year_frac
trend_value = OCO_MathUtil.linear_interpol(self.values,
self.dates, [curr_dec_date],
extrapolate=True,
extrap_err=False)
# Resulting trend value should be in first element of matrix
return trend_value[0]
