Tibeuleu/FOC_Reduction
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quick but dirty fix for readfos.specpol.__add__

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Thibault Barnouin
2025-01-20 01:05:03 +01:00
parent a0e952d877
commit bdfed1190f
1 changed files with 7 additions and 6 deletions
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13
package/src/readfos.py
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@@ -217,10 +217,10 @@ class specpol(object):
out.wav_r_err = deepcopy(self.wav_r_err) out.wav_r_err = deepcopy(self.wav_r_err)
else: else:
# Create "raw" flux spectra from previously unbinned spectra # Create "raw" flux spectra from previously unbinned spectra
out.I_r = deepcopy(self.I) out.I_r = deepcopy(self.I[self.I > 0.0])
out.I_r_err = deepcopy(self.I_err) out.I_r_err = deepcopy(self.I_err[self.I > 0.0])
out.wav_r = deepcopy(self.wav) out.wav_r = deepcopy(self.wav[self.I > 0.0])
out.wav_r_err = deepcopy(self.wav_err) out.wav_r_err = deepcopy(self.wav_err[self.I > 0.0])
for i in range(bin_edges.shape[0] - 1): for i in range(bin_edges.shape[0] - 1):
# Set the wavelength as the mean wavelength of acquisitions in bin, default to the bin center # Set the wavelength as the mean wavelength of acquisitions in bin, default to the bin center
@@ -364,8 +364,8 @@ class specpol(object):
elif self.bin_edges[-1] > bin_edges[-1]: elif self.bin_edges[-1] > bin_edges[-1]:
bin_edges = np.concat((bin_edges, deepcopy(self.bin_edges[self.bin_edges > bin_edges[-1]])), axis=0) bin_edges = np.concat((bin_edges, deepcopy(self.bin_edges[self.bin_edges > bin_edges[-1]])), axis=0)
# Rebin spectra to be added to ensure same binning # Rebin spectra to be added to ensure same binning
spec_a = specpol(self.bin(bin_edges=bin_edges)) spec_a = specpol(specpol(self).bin(bin_edges=bin_edges))
spec_b = specpol(other.bin(bin_edges=bin_edges)) spec_b = specpol(specpol(other).bin(bin_edges=bin_edges))
# Create sum spectra # Create sum spectra
spec = specpol(bin_edges.shape[0] - 1) spec = specpol(bin_edges.shape[0] - 1)
@@ -391,6 +391,7 @@ class specpol(object):
spec.I_r_err = deepcopy(np.concat((other.I_r_err, self.I_r_err[self.wav_r > other.wav_r[-1]]), axis=0)) spec.I_r_err = deepcopy(np.concat((other.I_r_err, self.I_r_err[self.wav_r > other.wav_r[-1]]), axis=0))
# When both spectra intersect, compute intersection as the mean # When both spectra intersect, compute intersection as the mean
edges = np.concat((spec.wav_r - spec.wav_r_err[:, 0], [spec.wav_r[-1] + spec.wav_r_err[-1, 1]])) edges = np.concat((spec.wav_r - spec.wav_r_err[:, 0], [spec.wav_r[-1] + spec.wav_r_err[-1, 1]]))
edges.sort()
bin, bino = np.digitize(self.wav_r, edges) - 1, np.digitize(other.wav_r, edges) - 1 bin, bino = np.digitize(self.wav_r, edges) - 1, np.digitize(other.wav_r, edges) - 1
for w in np.arange(spec.wav_r.shape[0])[np.logical_and(spec.wav_r >= inter[0], spec.wav_r <= inter[1])]: for w in np.arange(spec.wav_r.shape[0])[np.logical_and(spec.wav_r >= inter[0], spec.wav_r <= inter[1])]:
if self.hd["DENSITY"] and np.any(bin == w): if self.hd["DENSITY"] and np.any(bin == w):