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added some comments for binning on q-grid

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stahn
2024-04-19 14:14:08 +02:00
parent 722d10f710
commit ece5d8e22e
1 changed files with 13 additions and 5 deletions
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18
libeos/reduction.py
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@@ -258,19 +258,27 @@ class AmorReduction:
dq_lzf = dq_lz.flatten()[mask_lzf]
norm_lzf = norm_lz.flatten()[mask_lzf]
N_q = np.histogram(q_lzf, bins = q_q, weights = norm_lzf )[0]
weights_lzf = norm_lzf
#weights_lzf = np.sqrt(norm_lzf)
#weights_lzf = 1 / dR_lzf
N_q = np.histogram(q_lzf, bins = q_q, weights = weights_lzf )[0]
N_q = np.where(N_q > 0, N_q, np.nan)
R_q = np.histogram(q_lzf, bins = q_q, weights = norm_lzf * R_lzf )[0]
R_q = np.histogram(q_lzf, bins = q_q, weights = weights_lzf * R_lzf )[0]
R_q = R_q / N_q
dR_q = np.histogram(q_lzf, bins = q_q, weights = (norm_lzf * dR_lzf)**2 )[0]
dR_q = np.histogram(q_lzf, bins = q_q, weights = (weights_lzf * dR_lzf)**2 )[0]
dR_q = np.sqrt( dR_q ) / N_q
# TODO: different error propagations for dR and dq!
N_q = np.histogram(q_lzf, bins = q_q, weights = norm_lzf**2 )[0]
# this is what should work:
#dq_q = np.histogram(q_lzf, bins = q_q, weights = (weights_lzf * dq_lzf)**2 )[0]
#dq_q = np.sqrt( dq_q ) / N_q
# and this actually works:
N_q = np.histogram(q_lzf, bins = q_q, weights = weights_lzf**2 )[0]
N_q = np.where(N_q > 0, N_q, np.nan)
dq_q = np.histogram(q_lzf, bins = q_q, weights = (norm_lzf * dq_lzf)**2 )[0]
dq_q = np.histogram(q_lzf, bins = q_q, weights = (weights_lzf * dq_lzf)**2 )[0]
dq_q = np.sqrt( dq_q / N_q )
q_q = 0.5 * (q_q + np.roll(q_q, 1))