def MakeAGrid(name, dir):
dat = rd.Data_Level1(name, dir)
dat.OneStep()
GCP = dat.GCPs
SigmaNaught = dat.denoiseNRCS
y_lim, x_lim = SigmaNaught.shape
del dat, SigmaNaught
n = 10
gm.AllLonLat('Base', x_lim, y_lim, GCP, n)
return None
def OtherLayer(d, n):
for indice in range(n, len(d.series)):
temp = rd.Data_Level1(d.series[indice], d.FList[indice])
temp.OneStep()
GCP = temp.GCPs
SigmaNaught = temp.denoiseNRCS
name = 'Layer' + str(indice) + '-' + d.series[indice]
del temp
y1, x1 = SigmaNaught.shape
gm.AllLonLat(name, x1, y1, GCP, 5)
start = time.time()
SigmaNaught = Lc.Resize_SigmaNaught(SigmaNaught, 5)
print('Time for resize SigmaNaught:', (time.time() - start) / 60,
'mins')
Sigma_N, nums_arr = gm.GridSigmaNaught(SigmaNaught)
print('Time for resampling 1 SAR image:', (time.time() - start) / 60,
'mins')
jo.Matrix_save(Sigma_N, name, layer_root)
return None
def Resample(n, mode='uniform'):
d = rd.SentinelData()
d.Get_List(file_root)
m = 1 # resize factor
for indice in range(n, len(d.series)):
stt = time.time()
temp = rd.Data_Level1(d.series[indice], d.FList[indice])
temp.OneStep()
GCP = temp.GCPs
SigmaNaught = temp.denoiseNRCS
name = 'Layer' + str(indice) + '-' + d.series[indice]
del temp
y1, x1 = SigmaNaught.shape
sub_img, up_left = cod.N_sub(tempN, SigmaNaught)
del SigmaNaught, up_left
jo.NMatrix_save(sub_img, 'SigmaNaught', temp_root)
del sub_img
md2.AllLonLat(name, x1, y1, GCP, m)
img, pixel_num = md2.GridLL_SigmaNaught(mode)
jo.Matrix_save(img, name, layer_root)
jo.Matrix_save(pixel_num, name + '-distribution', layer_root)
print('1 image:', (time.time() - stt) / 60, 'mins')
print('Done!\n')
return None