def combine_gome_band34(self, wavelens, response, sol_wavelens,
sol_response):
# 把gome的通道做成390-800波段间隔1纳米的响应
gome_wavelens = np.arange(390, 801, 1)
gome_shape = (response.shape[0], len(gome_wavelens))
gome_response3 = np.full(gome_shape, 0)
gome_response4 = np.full(gome_shape, 0)
for i in xrange(response.shape[0]):
gome_response3[i, :] = spec_interp(wavelens[0:1024],
response[i,
0:1024], gome_wavelens)
gome_response4[i, :] = spec_interp(wavelens[1024:],
response[i,
1024:], gome_wavelens)
gome_response = gome_response3 + gome_response4
solar_response3 = spec_interp(sol_wavelens[0:1024],
sol_response[0:1024], gome_wavelens)
solar_response4 = spec_interp(sol_wavelens[1024:], sol_response[1024:],
gome_wavelens)
solar_response = solar_response3 + solar_response4
return gome_wavelens, gome_response, solar_response
def get_rad_tbb(self, D1, bandLst):
'''
D1是目标类的实例
'''
# iasi 的光谱波数范围
WaveNum2 = self.wavenumber
for Band in bandLst:
# gome 不需要用波数，使用波长即可
WaveNum1 = 10**7 / D1.waveNum[Band][::-1]
WaveRad1 = D1.waveRad[Band][::-1]
WaveRad2 = pb_sat.spec_interp(WaveNum1, WaveRad1, WaveNum2)
newRad = pb_sat.spec_convolution(WaveNum2, WaveRad2, self.radiance)
newRad = newRad.reshape(newRad.size, 1)
# 把数据1光谱插值到gome的太阳光谱
WaveRad2_solar = pb_sat.spec_interp(WaveNum1, WaveRad1, WaveNum2)
# WaveRad2_solar = D1.spec_interp(WaveNum1, WaveRad1, self.vec_Solar_WL)
newRad_solar = pb_sat.spec_convolution(self.vec_Solar_WL,
WaveRad2_solar,
self.vec_Solar_L)
# ref = newRad / newRad_solar * np.pi / np.cos(np.deg2rad(self.sunZenith))
ref = np.pi * newRad / newRad_solar
self.Ref[Band] = ref.reshape(ref.size, 1)
def get_ref(self, wave_nums, wave_spec, band_list, central_wave_nums, a, b,
lut):
"""
wave_nums: 波数cm-1（字典形式，key是通道信息，针对FY数据）
wave_spec: 响应0-1（字典形式，key是通道信息，针对FY数据）
band_list： CH_20-CH_25
center_wave_nums: 目前未用，只是为了和get_tbb统一
a: 目前未用，只是为了和get_tbb统一
b: 目前未用，只是为了和get_tbb统一
return channel rad
"""
data = dict()
if self.resolution == 40000:
satellite_type1 = ['METOP-A', 'METOP-B']
if self.satellite in satellite_type1:
# gome 不需要用波数，使用波长即可
gome_wavelens, gome_response = self.get_spectral_response()
for band in sorted(band_list):
wave_nums1 = wave_nums[band]
wave_spec1 = wave_spec[band]
# 插值 把FY光谱插值到GOME光谱上
wave_spec2 = spec_interp(wave_nums1, wave_spec1,
gome_wavelens)
# 对应FY的响应值，大小一致就可以和FY比较了，响应是IASI的
rads = spec_convolution(gome_wavelens, wave_spec2,
gome_response)
print band, np.allclose(rads, np.nan, equal_nan=True)
# 过滤<=0的结果
# 把数据1光谱插值到gome的太阳光谱
wave_spec2_sol = spec_interp(wave_nums1, wave_spec1,
gome_wavelens)
# WaveRad2_solar = D1.spec_interp(WaveNum1, WaveRad1, self.vec_Solar_WL)
rads_sol = spec_convolution(gome_wavelens, wave_spec2_sol,
self.solar_response)
solar_zen = self.get_solar_zenith()
data[band] = rads / rads_sol * \
np.pi # / np.cos(np.deg2rad(solar_zen)) wrh 建议注释掉
# print data
else:
raise ValueError('Cant read this satellite`s data.: {}'.format(
self.satellite))
else:
raise ValueError(
'Cant read this data, please check its resolution: {}'.format(
self.in_file))
return data
def get_rad(self, wave_nums, wave_spec, band_list, central_wave_nums, a, b, lut):
"""
wave_nums: 波数cm-1（字典形式，key是通道信息，针对FY数据）
wave_spec: 响应0-1（字典形式，key是通道信息，针对FY数据）
band_list： CH_20-CH_25
center_wave_nums: 目前未用，只是为了和get_tbb统一
a: 目前未用，只是为了和get_tbb统一
b: 目前未用，只是为了和get_tbb统一
return channel rad
"""
data = dict()
if self.resolution == 24000 or self.resolution == 24001:
satellite_type1 = ['METOP-A', 'METOP-B']
if self.satellite in satellite_type1:
# 获取iasi的光谱响应
wave_nums2, response = self.get_spectral_response()
for band in sorted(band_list):
wave_nums1 = wave_nums[band]
wave_spec1 = wave_spec[band]
# 插值 把FY光谱插值到IASI光谱上
wave_spec2 = spec_interp(
wave_nums1, wave_spec1, wave_nums2)
# 更换业务测试
# file3 = 'D:/data/VIRR/FY3C_VIRR_srf_b04_IASI.txt'
# data_spec1 = np.loadtxt(file3)
# wave_spec2 = data_spec1[:8462, 1]
# 输出测试
# aa = np.stack((wave_nums2, wave_spec2), axis=1)
# np.savetxt(
# 'D:/data/VIRR/FY3C_VIRR_srf_b03_IASI_test.txt', aa, fmt='%0.2f %0.5f')
# print aa.shape
# 对应FY的响应值，大小一致就可以和FY比较了，响应是IASI的
rads = spec_convolution(wave_nums2, wave_spec2, response)
# print band, np.allclose(rads, np.nan, equal_nan=True)
# 过滤<=0的结果
idx = np.where(rads <= 0.)
if len(idx[0] > 0):
rads[idx] = np.nan
data[band] = rads # .reshape(rads.size, 1)
else:
raise ValueError(
'Cant read this satellite`s data.: {}'.format(self.satellite))
else:
raise ValueError(
'Cant read this data, please check its resolution: {}'.format(self.in_file))
return data
def get_rad_tbb_test(self, D1, bandLst):
'''
D1是目标类的实例
'''
# iasi 的光谱波数范围
WaveNum2 = self.wavenumber
for Band in bandLst:
# 把gome的通道做成390-800波段间隔1纳米的响应
solar_x = np.arange(390, 801, 1)
WaveNum1 = 10 ** 7 / D1.waveNum[Band][::-1]
WaveRad1 = D1.waveRad[Band][::-1]
y = pb_sat.spec_interp(WaveNum1, WaveRad1, solar_x)
# newRad = D1.spec_convolution(WaveNum2, WaveRad2, self.radiance)
# newRad = newRad.reshape(newRad.size, 1)
# print newRad.shape
# 太阳光谱插值
WaveRad2_solar = pb_sat.spec_interp(
WaveNum1, WaveRad1, self.vec_Solar_WL)
# 太阳光谱插值
# 把gome的通道做成390-800波段间隔1纳米的响应
solar_x = np.arange(390, 801, 1)
solar_y1 = pb_sat.spec_interp(
self.vec_Solar_WL[0:1024], self.vec_Solar_L[0:1024], solar_x)
solar_y2 = pb_sat.spec_interp(
self.vec_Solar_WL[1024:], self.vec_Solar_L[1024:], solar_x)
solar_y = solar_y1 + solar_y2
solar_rad = pb_sat.spec_convolution(solar_x, y, solar_y)
print solar_y
print np.min(WaveRad2_solar)
print np.max(WaveRad2_solar)
# print WaveRad2_solar
# np.savetxt('testall.txt', WaveRad2_solar)
# np.savetxt('test.txt', WaveRad2_solar)
# WaveRad2_solar = D1.spec_interp(WaveNum1, WaveRad1, self.vec_Solar_WL)
# newRad_solar = D1.spec_convolution(self.vec_Solar_WL, WaveRad2_solar, self.vec_Solar_L)
gome_rad1 = self.radiance[:, 0:1024]
gome_rad2 = self.radiance[:, 1024:]
print gome_rad1.shape
print gome_rad2.shape
gome_y1_lst = []
gome_y2_lst = []
for i in xrange(self.radiance.shape[0]):
gome_y1 = pb_sat.spec_interp(
self.wavenumber[0:1024], self.radiance[i, 0:1024], solar_x)
gome_y2 = pb_sat.spec_interp(
self.wavenumber[1024:], self.radiance[i, 1024:], solar_x)
gome_y1_lst.append(gome_y1)
gome_y2_lst.append(gome_y2)
gome_y = np.array(gome_y1_lst) + np.array(gome_y2_lst)
gome_rad = pb_sat.spec_convolution(solar_x, y, gome_y)
gome_rad = gome_rad.reshape(gome_rad.size, 1)
ref = gome_rad / solar_rad * np.pi / \
np.cos(np.deg2rad(self.sunZenith))
self.Ref[Band] = ref.reshape(ref.size, 1)
def get_rad_tbb(self, D1, BandLst):
'''
D1是目标类的实例
'''
# iasi 的光谱波数范围
WaveNum2 = self.wavenumber
for Band in BandLst:
WaveNum1 = D1.waveNum[Band]
WaveRad1 = D1.waveRad[Band]
WaveRad2 = pb_sat.spec_interp(WaveNum1, WaveRad1, WaveNum2)
newRad = pb_sat.spec_convolution(WaveNum2, WaveRad2, self.radiance)
tbb = pb_sat.planck_r2t(newRad, D1.WN[Band])
tbb = tbb * D1.TeA[Band] + D1.TeB[Band]
self.Tbb[Band] = tbb.reshape(tbb.size, 1)
self.Rad[Band] = newRad.reshape(newRad.size, 1)
def get_rad(self, wave_nums, wave_spec, band_list, central_wave_nums, a, b,
lut):
"""
wave_nums: 波数cm-1（字典形式，key是通道信息，针对FY数据）
wave_spec: 响应0-1（字典形式，key是通道信息，针对FY数据）
band_list： CH_20-CH_25
center_wave_nums: 目前未用，只是为了和get_tbb统一
a: 目前未用，只是为了和get_tbb统一
b: 目前未用，只是为了和get_tbb统一
return channel rad
"""
data = dict()
if self.resolution == 13500:
satellite_type1 = ['AQUA', 'TERRA']
if self.satellite in satellite_type1:
# 获取iasi的光谱响应
wave_nums2, response = self.get_spectral_response()
for band in sorted(band_list):
wave_nums1 = wave_nums[band]
wave_spec1 = wave_spec[band]
# 插值 把FY插值到AIRS上
wave_spec2 = spec_interp(wave_nums1, wave_spec1,
wave_nums2)
# 对应FY的响应值，大小一致就可以和FY比较了，响应是IASI的
rads = spec_convolution(wave_nums2, wave_spec2, response)
# print band, np.allclose(rads, np.nan, equal_nan=True)
# 过滤<=0的结果
# print rads
idx = np.where(rads <= 0.)
if len(idx[0] > 0):
rads[idx] = np.nan
data[band] = rads # .reshape(rads.size, 1)
else:
raise ValueError('Cant read this satellite`s data.: {}'.format(
self.satellite))
else:
raise ValueError(
'Cant read this data, please check its resolution: {}'.format(
self.in_file))
return data
def get_rad(self, wave_nums, wave_spec, band_list, center_wave_nums, a, b,
lut):
"""
wave_nums: 波数cm-1（字典形式，key是通道信息，针对FY数据）
wave_spec: 响应0-1（字典形式，key是通道信息，针对FY数据）
band_list： CH_20-CH_25
center_wave_nums: 目前未用，只是为了和get_tbb统一
a: 目前未用，只是为了和get_tbb统一
b: 目前未用，只是为了和get_tbb统一
return channel rad
"""
data = dict()
if self.resolution == 16000:
satellite_type1 = ['NPP']
# print a, b
# print lut
if self.satellite in satellite_type1:
# 获取iasi的光谱响应 服务器上这个日期开始下载全分辨率cris
wave_nums2, response = self.get_spectral_response()
for band in sorted(band_list):
wave_nums1 = wave_nums[band]
wave_spec1 = wave_spec[band]
# 插值 把FY插值到IASI上
wave_spec2 = spec_interp(wave_nums1, wave_spec1,
wave_nums2)
# 对应FY的响应值，大小一致就可以和FY比较了，响应是IASI的
# print wave_spec2
rads = spec_convolution(wave_nums2, wave_spec2, response)
# data[band] = rads
# 过滤<=0的结果
# print rads
idx = np.where(rads <= 0.)
rads[idx] = np.nan
# data[band] = rads.reshape(rads.size, 1)
data[band] = rads # .reshape(rads.size, 1)
else:
raise ValueError('Cant read this satellite`s data.: {}'.format(
self.satellite))
else:
raise ValueError(
'Cant read this data, please check its resolution: {}'.format(
self.in_file))
return data