本文整理匯總了Python中lsst.sims.photUtils.Sed.Sed.multiplySED方法的典型用法代碼示例。如果您正苦於以下問題：Python Sed.multiplySED方法的具體用法？Python Sed.multiplySED怎麽用？Python Sed.multiplySED使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類lsst.sims.photUtils.Sed.Sed的用法示例。
在下文中一共展示了Sed.multiplySED方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: read_asteroids_reflectance
# 需要導入模塊: from lsst.sims.photUtils.Sed import Sed [as 別名]
# 或者: from lsst.sims.photUtils.Sed.Sed import multiplySED [as 別名]
def read_asteroids_reflectance(dataDir='.'):
# Read the sun's spectrum.
sun = Sed()
sun.readSED_flambda('kurucz_sun')
# Read the asteroid reflectance spectra.
allfiles = os.listdir(dataDir)
asteroidDtype = numpy.dtype([
('wavelength', numpy.float),
('A', numpy.float),
('A_sig', numpy.float),
('B', numpy.float),
('B_sig', numpy.float),
('C', numpy.float),
('C_sig', numpy.float),
('Cb', numpy.float),
('Cb_sig', numpy.float),
('Cg', numpy.float),
('Cg_sig', numpy.float),
('Cgh', numpy.float),
('Cgh_sig', numpy.float),
('Ch', numpy.float),
('Ch_sig', numpy.float),
('D', numpy.float),
('D_sig', numpy.float),
('K', numpy.float),
('K_sig', numpy.float),
('L', numpy.float),
('L_sig', numpy.float),
('O', numpy.float),
('O_sig', numpy.float),
('Q', numpy.float),
('Q_sig', numpy.float),
('R', numpy.float),
('R_sig', numpy.float),
('S', numpy.float),
('S_sig', numpy.float),
('Sa', numpy.float),
('Sa_sig', numpy.float),
('Sq', numpy.float),
('Sq_sig', numpy.float),
('Sr', numpy.float),
('Sr_sig', numpy.float),
('Sv', numpy.float),
('Sv_sig', numpy.float),
('T', numpy.float),
('T_sig', numpy.float),
('V', numpy.float),
('V_sig', numpy.float),
('X', numpy.float),
('X_sig', numpy.float),
('Xc', numpy.float),
('Xc_sig', numpy.float),
('Xe', numpy.float),
('Xe_sig', numpy.float),
('Xk', numpy.float),
('Xk_sig', numpy.float),
])
data = numpy.loadtxt(os.path.join(dataDir,'meanspectra.tab'),
dtype = asteroidDtype)
data['wavelength'] *= 1000.0 #because spectra are in microns
wavelen_step = min(numpy.diff(data['wavelength']).min(), numpy.diff(sun.wavelen).min())
wavelen = numpy.arange(sun.wavelen[0], data['wavelength'][-1], wavelen_step)
ast_reflect = {}
for a in data.dtype.names:
if a == 'wavelength' or a[-3:] == 'sig':
continue
# Read the basic reflectance data
ast_reflect[a] = Sed(wavelen=data['wavelength'], flambda=data[a])
# And now add an extrapolation to the blue end.
# Binzel cuts off at 450nm.
condition = ((ast_reflect[a].wavelen >= 450) & (ast_reflect[a].wavelen < 700))
x = ast_reflect[a].wavelen[condition]
y = ast_reflect[a].flambda[condition]
p = numpy.polyfit(x, y, deg=2)
condition = (wavelen < 450)
flambda = numpy.zeros(len(wavelen), 'float')
interpolated = numpy.polyval(p, wavelen[condition])
flambda[condition] = [ii if ii > 0.0 else 0.0 for ii in interpolated]
condition = (wavelen >= 450)
flambda[condition] = numpy.interp(wavelen[condition], ast_reflect[a].wavelen, ast_reflect[a].flambda)
ast_reflect[a] = Sed(wavelen, flambda)
ast = {}
for a in ast_reflect:
ast[a] = sun.multiplySED(ast_reflect[a], wavelen_step=wavelen_step)
for a in ast:
name = a + '.dat'
normalizedSed = Sed(wavelen=ast[a].wavelen, flambda=ast[a].flambda)
norm = numpy.interp(500.0, normalizedSed.wavelen, normalizedSed.flambda)
normalizedSed.multiplyFluxNorm(1.0/norm)
normalizedSed.writeSED(name, print_header='21 April 2015; normalized to flambda=1 at 500nm')
#.........這裏部分代碼省略.........