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Update prints in fitting functions

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This commit is contained in:
usov_i 2020-11-02 16:20:02 +01:00
parent 45f295fcf8
commit 7b6e6bf396
1 changed files with 5 additions and 6 deletions
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11
pyzebra/fit2.py
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@ -61,15 +61,15 @@ def fitccl(
""" """
if "peak_indexes" not in scan: if "peak_indexes" not in scan:
scan["peak_indexes"] = [] scan["peak_indexes"] = []
if len(scan["peak_indexes"]) > 1: if len(scan["peak_indexes"]) > 1:
# return in case of more than 1 peaks # return in case of more than 1 peaks
print("More than 1 peak, scan skipped")
return return
if binning is None or binning == 0 or binning == 1: if binning is None or binning == 0 or binning == 1:
x = list(scan["om"]) x = list(scan["om"])
y = list(scan["Counts"]) y = list(scan["Counts"])
y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"]) y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"])
print(scan["peak_indexes"])
if not scan["peak_indexes"]: if not scan["peak_indexes"]:
centre = np.mean(x) centre = np.mean(x)
else: else:
@ -89,7 +89,6 @@ def fitccl(
if len(scan["peak_indexes"]) == 0: if len(scan["peak_indexes"]) == 0:
# Case for no peak, gaussian in centre, sigma as 20% of range # Case for no peak, gaussian in centre, sigma as 20% of range
print("No peak")
peak_index = find_nearest(x, np.mean(x)) peak_index = find_nearest(x, np.mean(x))
guess[0] = centre if guess[0] is None else guess[0] guess[0] = centre if guess[0] is None else guess[0]
guess[1] = (x[-1] - x[0]) / 5 if guess[1] is None else guess[1] guess[1] = (x[-1] - x[0]) / 5 if guess[1] is None else guess[1]
@ -100,7 +99,6 @@ def fitccl(
elif len(scan["peak_indexes"]) == 1: elif len(scan["peak_indexes"]) == 1:
# case for one peak, takse into account users guesses # case for one peak, takse into account users guesses
print("one peak")
peak_height = scan["peak_heights"] peak_height = scan["peak_heights"]
guess[0] = centre if guess[0] is None else guess[0] guess[0] = centre if guess[0] is None else guess[0]
guess[1] = 0.1 if guess[1] is None else guess[1] guess[1] = 0.1 if guess[1] is None else guess[1]
@ -135,6 +133,7 @@ def fitccl(
y, params, weights=[np.abs(1 / val) for val in y_err], x=x, calc_covar=True, y, params, weights=[np.abs(1 / val) for val in y_err], x=x, calc_covar=True,
) )
except ValueError: except ValueError:
print(f"Couldn't fit scan {scan['scan_number']}")
return return
if result.params["g_amp"].stderr is None: if result.params["g_amp"].stderr is None:
@ -215,9 +214,9 @@ def fitccl(
d = {} d = {}
for pars in result.params: for pars in result.params:
d[str(pars)] = (result.params[str(pars)].value, result.params[str(pars)].vary) d[str(pars)] = (result.params[str(pars)].value, result.params[str(pars)].vary)
print(result.fit_report())
print((result.params["g_amp"].value - int_area.n) / result.params["g_amp"].value) print("Scan", scan["scan_number"])
print(result.fit_report())
d["ratio"] = (result.params["g_amp"].value - int_area.n) / result.params["g_amp"].value d["ratio"] = (result.params["g_amp"].value - int_area.n) / result.params["g_amp"].value
d["int_area"] = int_area d["int_area"] = int_area