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Allow fitting of measurements without peaks

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This commit is contained in:
usov_i 2020-10-16 16:43:43 +02:00
parent 23c8a573d7
commit 6337afb4c3
1 changed files with 56 additions and 51 deletions
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107
pyzebra/app/panel_ccl_integrate.py
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@ -154,8 +154,17 @@ def create():
(params["g_amp"].value - fit["int_area"].n) / params["g_amp"].value, (params["g_amp"].value - fit["int_area"].n) / params["g_amp"].value,
) )
) )
numfit_min_span.location = x[fit["numfit"][0]] numfit_min, numfit_max = fit["numfit"]
numfit_max_span.location = x[fit["numfit"][1]] if numfit_min is None:
numfit_min_span.location = None
else:
numfit_min_span.location = x[numfit_min]
if numfit_max is None:
numfit_max_span.location = None
else:
numfit_max_span.location = x[numfit_max]
else: else:
plot_gauss_source.data.update(x=[], y=[]) plot_gauss_source.data.update(x=[], y=[])
plot_bkg_source.data.update(x=[], y=[]) plot_bkg_source.data.update(x=[], y=[])
@ -334,56 +343,8 @@ def create():
def fit_all_button_callback(): def fit_all_button_callback():
for meas in det_data["meas"].values(): for meas in det_data["meas"].values():
num_of_peaks = meas.get("num_of_peaks")
if num_of_peaks is not None and num_of_peaks == 1:
pyzebra.fitccl(
meas,
guess=[
centre_guess.value,
sigma_guess.value,
ampl_guess.value,
slope_guess.value,
offset_guess.value,
],
vary=[
centre_vary.active,
sigma_vary.active,
ampl_vary.active,
slope_vary.active,
offset_vary.active,
],
constraints_min=[
centre_min.value,
sigma_min.value,
ampl_min.value,
slope_min.value,
offset_min.value,
],
constraints_max=[
centre_max.value,
sigma_max.value,
ampl_max.value,
slope_max.value,
offset_max.value,
],
numfit_min=integ_from.value,
numfit_max=integ_to.value,
)
sel_ind = meas_table_source.selected.indices[-1]
_update_plot(meas_table_source.data["measurement"][sel_ind])
fit_all_button = Button(label="Fit All", button_type="primary", default_size=145)
fit_all_button.on_click(fit_all_button_callback)
def fit_button_callback():
sel_ind = meas_table_source.selected.indices[-1]
meas = meas_table_source.data["measurement"][sel_ind]
num_of_peaks = det_data["meas"][meas].get("num_of_peaks")
if num_of_peaks is not None and num_of_peaks == 1:
pyzebra.fitccl( pyzebra.fitccl(
det_data["meas"][meas], meas,
guess=[ guess=[
centre_guess.value, centre_guess.value,
sigma_guess.value, sigma_guess.value,
@ -412,8 +373,52 @@ def create():
slope_max.value, slope_max.value,
offset_max.value, offset_max.value,
], ],
numfit_min=integ_from.value,
numfit_max=integ_to.value,
) )
sel_ind = meas_table_source.selected.indices[-1]
_update_plot(meas_table_source.data["measurement"][sel_ind])
fit_all_button = Button(label="Fit All", button_type="primary", default_size=145)
fit_all_button.on_click(fit_all_button_callback)
def fit_button_callback():
sel_ind = meas_table_source.selected.indices[-1]
meas = meas_table_source.data["measurement"][sel_ind]
pyzebra.fitccl(
det_data["meas"][meas],
guess=[
centre_guess.value,
sigma_guess.value,
ampl_guess.value,
slope_guess.value,
offset_guess.value,
],
vary=[
centre_vary.active,
sigma_vary.active,
ampl_vary.active,
slope_vary.active,
offset_vary.active,
],
constraints_min=[
centre_min.value,
sigma_min.value,
ampl_min.value,
slope_min.value,
offset_min.value,
],
constraints_max=[
centre_max.value,
sigma_max.value,
ampl_max.value,
slope_max.value,
offset_max.value,
],
)
_update_plot(meas) _update_plot(meas)
fit_button = Button(label="Fit Current", default_size=145) fit_button = Button(label="Fit Current", default_size=145)