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Average counts per scan position upon scan merging

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Fix #42
This commit is contained in:
usov_i 2021-11-08 16:00:52 +01:00
parent 7dcd20198f
commit 6557b2f3a4
1 changed files with 30 additions and 21 deletions
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51
pyzebra/ccl_process.py
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@ -99,30 +99,39 @@ def merge_scans(scan_into, scan_from):
scan_motor = scan_into["scan_motor"] # the same as scan_from["scan_motor"]
if (
scan_into[scan_motor].shape == scan_from[scan_motor].shape
and np.max(np.abs(scan_into[scan_motor] - scan_from[scan_motor])) < 0.0005
):
counts_tmp = 0
counts_err_tmp = 0
pos_all = np.array([])
val_all = np.array([])
err_all = np.array([])
for scan in [scan_into["init_scan"], *scan_into["merged_scans"]]:
pos_all = np.append(pos_all, scan[scan_motor])
val_all = np.append(val_all, scan["counts"])
err_all = np.append(err_all, scan["counts_err"] ** 2)
for scan in [scan_into["init_scan"], *scan_into["merged_scans"]]:
counts_tmp += scan["counts"]
counts_err_tmp += scan["counts_err"] ** 2
sort_index = np.argsort(pos_all)
pos_all = pos_all[sort_index]
val_all = val_all[sort_index]
err_all = err_all[sort_index]
scan_into["counts"] = counts_tmp / (1 + len(scan_into["merged_scans"]))
scan_into["counts_err"] = np.sqrt(counts_err_tmp)
pos_tmp = pos_all[:1]
val_tmp = val_all[:1]
err_tmp = err_all[:1]
num_tmp = np.array([1])
for pos, val, err in zip(pos_all[1:], val_all[1:], err_all[1:]):
if pos - pos_tmp[-1] < 0.0005:
# the repeated motor position
val_tmp[-1] += val
err_tmp[-1] += err
num_tmp[-1] += 1
else:
# a new motor position
pos_tmp = np.append(pos_tmp, pos)
val_tmp = np.append(val_tmp, val)
err_tmp = np.append(err_tmp, err)
num_tmp = np.append(num_tmp, 1)
else:
motor_pos = np.concatenate((scan_into[scan_motor], scan_from[scan_motor]))
counts = np.concatenate((scan_into["counts"], scan_from["counts"]))
counts_err = np.concatenate((scan_into["counts_err"], scan_from["counts_err"]))
index = np.argsort(motor_pos)
scan_into[scan_motor] = motor_pos[index]
scan_into["counts"] = counts[index]
scan_into["counts_err"] = counts_err[index]
scan_into[scan_motor] = pos_tmp
scan_into["counts"] = val_tmp / num_tmp
scan_into["counts_err"] = np.sqrt(err_tmp)
scan_from["export"] = False