Correctly merge multiple scans in one
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c2be907113
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@ -81,23 +81,30 @@ def merge_datasets(dataset_into, dataset_from):
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def merge_scans(scan_into, scan_from):
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# TODO: does it need to be "scan_motor" instead of omega for a generalized solution?
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if "init_omega" not in scan_into:
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scan_into["init_omega"] = scan_into["omega"]
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scan_into["init_counts"] = scan_into["counts"]
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scan_into["init_counts_err"] = scan_into["counts_err"]
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if "init_scan" not in scan_into:
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scan_into["init_scan"] = scan_into.copy()
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if "merged_scans" not in scan_into:
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scan_into["merged_scans"] = []
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if scan_from in scan_into["merged_scans"]:
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return
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scan_into["merged_scans"].append(scan_from)
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if (
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scan_into["omega"].shape == scan_from["omega"].shape
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and np.max(np.abs(scan_into["omega"] - scan_from["omega"])) < 0.0005
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):
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scan_into["counts"] = (scan_into["counts"] + scan_from["counts"]) / 2
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scan_into["counts_err"] = np.sqrt(
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scan_into["counts_err"] ** 2 + scan_from["counts_err"] ** 2
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)
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counts_tmp = 0
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counts_err_tmp = 0
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for scan in [scan_into["init_scan"], *scan_into["merged_scans"]]:
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counts_tmp += scan["counts"]
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counts_err_tmp += scan["counts_err"] ** 2
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scan_into["counts"] = counts_tmp / (1 + len(scan_into["merged_scans"]))
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scan_into["counts_err"] = np.sqrt(counts_err_tmp)
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else:
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omega = np.concatenate((scan_into["omega"], scan_from["omega"]))
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@ -118,18 +125,14 @@ def merge_scans(scan_into, scan_from):
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def restore_scan(scan):
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if "init_omega" in scan:
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scan["omega"] = scan["init_omega"]
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scan["counts"] = scan["init_counts"]
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scan["counts_err"] = scan["init_counts_err"]
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del scan["init_omega"]
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del scan["init_counts"]
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del scan["init_counts_err"]
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if "merged_scans" in scan:
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for merged_scan in scan["merged_scans"]:
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merged_scan["active"] = True
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del scan["merged_scans"]
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if "init_scan" in scan:
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tmp = scan["init_scan"]
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scan.clear()
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scan.update(tmp)
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def fit_scan(scan, model_dict, fit_from=None, fit_to=None):
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