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Display peak components and allow to hide plots

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This commit is contained in:
usov_i 2021-03-11 18:00:41 +01:00
parent d606230feb
commit 526821e073
2 changed files with 67 additions and 14 deletions
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41
pyzebra/app/panel_ccl_integrate.py
View File

@ -21,6 +21,7 @@ from bokeh.models import (
Legend,
Line,
LinearAxis,
MultiLine,
MultiSelect,
NumberEditor,
Panel,
@ -200,23 +201,38 @@ def create():
x_fit = np.linspace(x[0], x[-1], 100)
plot_fit_source.data.update(x=x_fit, y=fit.eval(x=x_fit))
x_bkg = []
y_bkg = []
xs_peak = []
ys_peak = []
comps = fit.eval_components(x=x_fit)
for i, model in enumerate(fit_params):
if "linear" in model:
comps = fit.eval_components(x=x_fit)
plot_bkg_source.data.update(x=x_fit, y=comps[f"f{i}_"])
break
else:
plot_bkg_source.data.update(x=[], y=[])
x_bkg = x_fit
y_bkg = comps[f"f{i}_"]
elif any(val in model for val in ("gaussian", "voigt", "pvoigt")):
xs_peak.append(x_fit)
ys_peak.append(comps[f"f{i}_"])
plot_bkg_source.data.update(x=x_bkg, y=y_bkg)
plot_peak_source.data.update(xs=xs_peak, ys=ys_peak)
fit_output_textinput.value = fit.fit_report()
else:
plot_fit_source.data.update(x=[], y=[])
plot_bkg_source.data.update(x=[], y=[])
plot_peak_source.data.update(xs=[], ys=[])
fit_output_textinput.value = ""
# Main plot
plot = Plot(x_range=DataRange1d(), y_range=DataRange1d(), plot_height=470, plot_width=700)
plot = Plot(
x_range=DataRange1d(),
y_range=DataRange1d(only_visible=True),
plot_height=470,
plot_width=700,
)
plot.add_layout(LinearAxis(axis_label="Counts"), place="left")
plot.add_layout(LinearAxis(axis_label="Scan motor"), place="below")
@ -238,6 +254,11 @@ def create():
plot_bkg_source, Line(x="x", y="y", line_color="green", line_dash="dashed")
)
plot_peak_source = ColumnDataSource(dict(xs=[0], ys=[0]))
plot_peak = plot.add_glyph(
plot_peak_source, MultiLine(xs="xs", ys="ys", line_color="red", line_dash="dashed")
)
fit_from_span = Span(location=None, dimension="height", line_dash="dashed")
plot.add_layout(fit_from_span)
@ -246,8 +267,14 @@ def create():
plot.add_layout(
Legend(
items=[("data", [plot_scatter]), ("best fit", [plot_fit]), ("linear", [plot_bkg])],
items=[
("data", [plot_scatter]),
("best fit", [plot_fit]),
("peak", [plot_peak]),
("linear", [plot_bkg]),
],
location="top_left",
click_policy="hide",
)
)

40
pyzebra/app/panel_param_study.py
View File

@ -214,19 +214,29 @@ def create():
x_fit = np.linspace(x[0], x[-1], 100)
plot_fit_source.data.update(x=x_fit, y=fit.eval(x=x_fit))
x_bkg = []
y_bkg = []
xs_peak = []
ys_peak = []
comps = fit.eval_components(x=x_fit)
for i, model in enumerate(fit_params):
if "linear" in model:
comps = fit.eval_components(x=x_fit)
plot_bkg_source.data.update(x=x_fit, y=comps[f"f{i}_"])
break
else:
plot_bkg_source.data.update(x=[], y=[])
x_bkg = x_fit
y_bkg = comps[f"f{i}_"]
elif any(val in model for val in ("gaussian", "voigt", "pvoigt")):
xs_peak.append(x_fit)
ys_peak.append(comps[f"f{i}_"])
plot_bkg_source.data.update(x=x_bkg, y=y_bkg)
plot_peak_source.data.update(xs=xs_peak, ys=ys_peak)
fit_output_textinput.value = fit.fit_report()
else:
plot_fit_source.data.update(x=[], y=[])
plot_bkg_source.data.update(x=[], y=[])
plot_peak_source.data.update(xs=[], ys=[])
fit_output_textinput.value = ""
def _update_overview():
@ -260,7 +270,12 @@ def create():
ov_param_plot_scatter_source.data.update(x=x, y=y, param=par)
# Main plot
plot = Plot(x_range=DataRange1d(), y_range=DataRange1d(), plot_height=450, plot_width=700)
plot = Plot(
x_range=DataRange1d(),
y_range=DataRange1d(only_visible=True),
plot_height=450,
plot_width=700,
)
plot.add_layout(LinearAxis(axis_label="Counts"), place="left")
plot.add_layout(LinearAxis(axis_label="Scan motor"), place="below")
@ -282,6 +297,11 @@ def create():
plot_bkg_source, Line(x="x", y="y", line_color="green", line_dash="dashed")
)
plot_peak_source = ColumnDataSource(dict(xs=[0], ys=[0]))
plot_peak = plot.add_glyph(
plot_peak_source, MultiLine(xs="xs", ys="ys", line_color="red", line_dash="dashed")
)
fit_from_span = Span(location=None, dimension="height", line_dash="dashed")
plot.add_layout(fit_from_span)
@ -290,8 +310,14 @@ def create():
plot.add_layout(
Legend(
items=[("data", [plot_scatter]), ("best fit", [plot_fit]), ("linear", [plot_bkg])],
items=[
("data", [plot_scatter]),
("best fit", [plot_fit]),
("peak", [plot_peak]),
("linear", [plot_bkg]),
],
location="top_left",
click_policy="hide",
)
)