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Add code for 1D detector #69

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usov_i merged 118 commits from det1d into master 2020-10-22 12:07:50 +02:00
Conversation 22 Commits 118 Files Changed 15 +1785 -45
14 changed files with 1785 additions and 45 deletions
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pyzebra/fit2.py
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@ -67,19 +67,25 @@ def fitccl(
# return in case of more than 1 peaks
print("More than 1 peak, measurement skipped")
return
if binning is None or binning == 0 or binning == 1:
x = list(meas["om"])
y = list(meas["Counts"])
y_err = list(np.sqrt(y)) if meas.get("sigma", None) is None else list(meas["sigma"])
print(meas["peak_indexes"])
if not meas["peak_indexes"]:
centre = np.mean(x)
else:
centre = x[int(meas["peak_indexes"])]
else:
x = list(meas["om"])
if not meas["peak_indexes"]:
centre = np.mean(x)
else:
centre = x[int(meas["peak_indexes"])]
x = bin_data(x, binning)
y = list(meas["Counts"])
y_err = list(np.sqrt(y)) if meas.get("sigma", None) is None else list(meas["sigma"])
combined = bin_data(create_uncertanities(y, y_err), binning)
combined = bin_data(create_uncertanities(y,y_err), binning)
y = [combined[i].n for i in range(len(combined))]
y_err = [combined[i].s for i in range(len(combined))]