def Get_DRACS(filepath, chip): """Filepath needs to point object""" filename = get_filenames(filepath, "CRIRE*.norm.comb.fits", "*_" + str(chip+1) + ".*") print("Filename =", filepath + filename[0]) print("length filename",len(filename)) assert len(filename) is 1 # Check only one filename found hdr = fits.getheader(filepath + filename[0]) data = fits.getdata(filepath + filename[0]) return hdr, data
def test_resampler(): """ Test reampler visually""" import matplotlib.pyplot as plt from astropy.io import fits from Get_filenames import get_filenames detector = 1 folder = "/home/jneal/Phd/data/Crires/BDs-DRACS/HD30501-1/Combined_Nods/" file_names = get_filenames(folder, "C*_{}.nod.*".format(detector), "*wavecal.fits") print("file names", file_names) data = fits.getdata(file_names[0]) resampled_data = log_resampler(data["Wavelength"], data["Extracted_dracs"]) plt.plot(data["Wavelength"], data["Extracted_dracs"], label="org") plt.plot(10 ** resampled_data[0], resampled_data[1], "o-", label="resampled") plt.legend() plt.show()
#path = "C:/Users/Jason/Dropbox/PhD/CriresReduction/{0}/".format(observation_name) #intermediate_path = path + "Intermediate_steps/" #combined_path = path + "Combined_Nods/" #image_path = path + "quicklooks/" # To run dir_path = os.getcwd() intermediate_path = dir_path + "/Intermediate_steps/" combined_path = dir_path + "/Combined_Nods/" image_path = dir_path + "/images/" observation_name = os.path.split(dir_path)[-1] for chip_num in range(1, 5): combined_name = get_filenames(combined_path, 'CRIRE*.sum.fits', "*_{}.*".format(chip_num)) nod_names = get_filenames(intermediate_path, 'CRIRE*.ms.fits', "*_{}.*".format(chip_num)) norm_names = get_filenames(intermediate_path, 'CRIRE*.ms.norm.fits', "*_{}.*".format(chip_num)) combined_data = fits.getdata(combined_path + combined_name[0]) nod_data = [fits.getdata(name) for name in nod_names] norm_data = [fits.getdata(name) for name in norm_names] median_nod = np.median(norm_data, axis=0) # Median combine normalzied spectra # Plot Reuslts fig = plt.figure() plt.suptitle("{0}, Chip-{1}".format(observation_name, chip_num), fontsize=16) ax1 = plt.subplot(311) for i, data in enumerate(nod_data): ax1.plot(data, label=i+1)