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Consolidate naming

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* replace "Counts" with "counts"
* better names for vars in scan merge procedure
This commit is contained in:
usov_i
2021-05-26 13:41:47 +02:00
parent 3fe4fca96a
commit 502a4b8096
4 changed files with 35 additions and 34 deletions
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37
pyzebra/ccl_process.py
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@@ -29,7 +29,7 @@ AREA_METHODS = ("fit_area", "int_area")
def normalize_dataset(dataset, monitor=100_000):
for scan in dataset:
monitor_ratio = monitor / scan["monitor"]
scan["Counts"] *= monitor_ratio
scan["counts"] *= monitor_ratio
scan["monitor"] = monitor
@@ -64,30 +64,31 @@ def _parameters_match(scan1, scan2):
return True
def merge_datasets(dataset1, dataset2):
for scan_j in dataset2:
for scan_i in dataset1:
if _parameters_match(scan_i, scan_j):
merge_scans(scan_i, scan_j)
def merge_datasets(dataset_into, dataset_from):
for scan_from in dataset_from:
for scan_into in dataset_into:
if _parameters_match(scan_into, scan_from):
merge_scans(scan_into, scan_from)
break
dataset1.append(scan_j)
dataset_into.append(scan_from)
def merge_scans(scan1, scan2):
omega = np.concatenate((scan1["omega"], scan2["omega"]))
counts = np.concatenate((scan1["Counts"], scan2["Counts"]))
def merge_scans(scan_into, scan_from):
# TODO: does it need to be "scan_motor" instead of omega for a generalized solution?
omega = np.concatenate((scan_into["omega"], scan_from["omega"]))
counts = np.concatenate((scan_into["counts"], scan_from["counts"]))
index = np.argsort(omega)
scan1["omega"] = omega[index]
scan1["Counts"] = counts[index]
scan_into["omega"] = omega[index]
scan_into["counts"] = counts[index]
scan2["active"] = False
scan_from["active"] = False
fname1 = os.path.basename(scan1["original_filename"])
fname2 = os.path.basename(scan2["original_filename"])
print(f'Merging scans: {scan1["idx"]} ({fname1}) <-- {scan2["idx"]} ({fname2})')
fname1 = os.path.basename(scan_into["original_filename"])
fname2 = os.path.basename(scan_from["original_filename"])
print(f'Merging scans: {scan_into["idx"]} ({fname1}) <-- {scan_from["idx"]} ({fname2})')
def fit_scan(scan, model_dict, fit_from=None, fit_to=None):
@@ -96,7 +97,7 @@ def fit_scan(scan, model_dict, fit_from=None, fit_to=None):
if fit_to is None:
fit_to = np.inf
y_fit = scan["Counts"]
y_fit = scan["counts"]
x_fit = scan[scan["scan_motor"]]
# apply fitting range
@@ -173,7 +174,7 @@ def get_area(scan, area_method, lorentz):
area_s = np.nan
else: # area_method == "int_area"
y_val = scan["Counts"]
y_val = scan["counts"]
x_val = scan[scan["scan_motor"]]
y_bkg = scan["fit"].eval_components(x=x_val)["f0_"]
area_n = simpson(y_val, x=x_val) - trapezoid(y_bkg, x=x_val)