def get_netd(self,filters,spav='all',non_ill=1):
self.organized(spav=spav)
mean_netd = zeros([11])
mean_ner = zeros([11])
mean_sigma = zeros([11])
mean_sitf_temp = zeros([11])
mean_sitf_rad = zeros([11])
all_mean = self.all_mean
all_std = self.all_std
all_tms = self.all_tms
for fil in filters:
k = filters_positions.index(fil)
if spav == 'all' or spav == 'fast':
correct_pixels = [i for i in range(2) if all_mean[k,0,i]*all_mean[k,1,i]!=0]
else:
correct_pixels = [i for i in self.illuminated if all_mean[k,0,i]*all_mean[k,1,i]!=0]
if not array(correct_pixels).size: # anomalies on all pixels, then no calculations
print "NO GOOD PIXELS"
mean_netd[num]=0
mean_sigma[num]=0
mean_sitf[num]=0
else:
i_abb = searchsorted(self.temp_tms,all_tms[k,0])-1
i_hbb = searchsorted(self.temp_tms,all_tms[k,1])-1
sitf_temp = (all_mean[k,1,:] - all_mean[k,0,:])/(self.temp_hbb[i_hbb] - self.temp_abb[i_abb])
rad_hbb = Toolbox.radiance(self.temp_hbb[i_hbb]+273.15,fil,emiss_wls,emiss,self.temp_pm[i_hbb])
rad_abb = Toolbox.radiance(self.temp_abb[i_abb]+273.15,fil,emiss_wls,emiss,self.temp_pm[i_abb])
sitf_rad = (all_mean[k,1,:] - all_mean[k,0,:])/(rad_hbb - rad_abb)
netd = abs(all_std[k,0,:]/sitf_temp)
ner = abs(all_std[k,0,:]/sitf_temp)
mean_netd[k] = mean(netd[correct_pixels])
mean_ner[k] = mean(ner[correct_pixels])
mean_sitf_temp[k] = mean(sitf_temp[correct_pixels])
mean_sitf_rad[k] = mean(sitf_rad[correct_pixels])
mean_sigma[k] = mean(all_std[k,0,correct_pixels])
self.sigma = mean_sigma
self.netd = mean_netd
self.ner = mean_ner
self.sitf_temp = mean_sitf_temp
self.sitf_rad = mean_sitf_rad
from pylab import *
import os
import glob
from scipy.integrate import trapz, simps
import Toolbox
h = 6.62e-34
c = 3e8
kb = 1.38e-23
epsilon_wls = array([1, 50])
epsilon = array([1, 1])
Tpm = 300
filtres_ref = ["open", "F0007", "F0008", "F0009", "F0034", "F0035", "F0036", "F0010", "F0011", "F0014"]
n = len(filtres_ref)
temp = linspace(51, 350, 270)
l = len(temp)
LUT_radiances = zeros([l, n + 1])
LUT_radiances[:, 0] = temp[:]
for k, f in enumerate(filtres_ref):
for i, t in enumerate(temp):
print t
LUT_radiances[i, k + 1] = Toolbox.radiance(t, f, epsilon_wls, epsilon, 300)
savetxt("LUT_radiances_new.txt", LUT_radiances)
emiss = em[:,1]
"""Treat measurements as a """
"""Extract some nadir BB measurements only"""
print "Computing NBB radiances"
dates_select = []
rad_nadir = []
new_select = []
count = 0
for k in range(l):
count+=1
if count%120==0:
if selection[k] == 1:
dates_select+=[dates[k]]
rad_nadir+=[Toolbox.radiance(t_nadir[k]+273.15,all_filters[j],emiss_wls,emiss,24+273.15) for j in list_filters]
n_select = len(dates_select)
rad_nadir=reshape(array(rad_nadir),(n_select,11))
dnum = array([date2num(dates[k]) for k in range(l)])
if meas == "SET1":
series = FirrSeries("/media/quentin/LACIE SHARE/FIRR_measurements/LR-TECH/SET1")
elif meas == "SET2":
series = FirrSeries("/media/quentin/LACIE SHARE/FIRR_measurements/LR-TECH/SET2")
sequences = series.sequences
series.get_temperature()
temp_firr = series.temperature
temp_firr_time = series.temp_time
