def fnBuildStarTemplate(CCFs, nOrders=1, Templates=None):
if Templates == None:
Templates = sorted(CCFs.keys())
# defining template CCF class
templateCCF = clsHARPSCCF(CCFs[Templates[0]].data)
nOrders = len(templateCCF.data)
templateCCF.wave = np.indices(np.shape(templateCCF.data))[1, :, :]
templateCCF.ccfAmplitude, templateCCF.ccfMeanPixel, templateCCF.ccfFWHMPixels, templateCCF.ccfB = (
np.empty(nOrders), np.empty(nOrders), np.empty(nOrders),
np.empty(nOrders))
# building template orders
for order, orderWave, orderData in zip(range(nOrders), templateCCF.wave,
templateCCF.data):
meanPixel = np.nanmean(
[CCFs[CCFName].ccfMeanPixel[order] for CCFName in Templates])
orderData[:] = np.nansum([
fnShiftCCF(CCFs[CCFName].data[order].copy(), orderWave,
CCFs[CCFName].ccfMeanPixel[order] - meanPixel)
for CCFName in Templates
],
axis=0)
templateCCF.ccfAmplitude[order], templateCCF.ccfMeanPixel[
order], templateCCF.ccfFWHMPixels[order], templateCCF.ccfB[
order] = fnGaussianFitOLD(orderWave,
orderData,
GaussParamsInitGuess=[
max(orderData) - min(orderData),
len(orderData) / 2, 10.,
max(orderData)
])
return templateCCF
def fnOpenHARPSFits(FitsFileName, headerOnly=False, allOrders=False):
if headerOnly == True:
data = []
header = fits.getheader(FitsFileName)
else:
ccfFits = fits.open(FitsFileName)[0].copy()
if allOrders:
data = np.array(ccfFits.data).copy()
else:
data = np.array(ccfFits.data)[-1].copy()
header = ccfFits.header
ccfFile = clsHARPSCCF(data, header)
return ccfFile
def fnOpenHARPSFits2(FitsFileName):
ccfFits = fits.open(FitsFileName)
ccfClass = clsHARPSCCF(ccfFits[0].data, ccfFits[0].header)
return ccfClass