Simplify plot creation in panel_param_study
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7503076a1b
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@ -9,35 +9,23 @@ import numpy as np
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from bokeh.io import curdoc
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from bokeh.layouts import column, row
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from bokeh.models import (
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BasicTicker,
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Button,
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CellEditor,
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CheckboxEditor,
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CheckboxGroup,
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ColumnDataSource,
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CustomJS,
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DataRange1d,
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DataTable,
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Div,
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Dropdown,
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FileInput,
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Grid,
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HoverTool,
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Image,
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Legend,
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Line,
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LinearAxis,
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LinearColorMapper,
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MultiLine,
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MultiSelect,
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NumberEditor,
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Panel,
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PanTool,
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Plot,
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RadioGroup,
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Range1d,
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ResetTool,
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Scatter,
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Select,
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Spacer,
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Span,
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@ -45,10 +33,10 @@ from bokeh.models import (
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TableColumn,
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Tabs,
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TextAreaInput,
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WheelZoomTool,
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Whisker,
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)
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from bokeh.palettes import Category10, Plasma256
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from bokeh.plotting import figure
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from scipy import interpolate
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import pyzebra
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@ -123,7 +111,7 @@ def create():
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file_list.append(os.path.basename(scan["original_filename"]))
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scan_table_source.data.update(
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file=file_list, scan=scan_list, param=param, fit=[0] * len(scan_list), export=export,
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file=file_list, scan=scan_list, param=param, fit=[0] * len(scan_list), export=export
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)
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scan_table_source.selected.indices = []
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scan_table_source.selected.indices = [0]
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@ -281,12 +269,12 @@ def create():
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x = scan[scan_motor]
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plot.axis[0].axis_label = scan_motor
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plot_scatter_source.data.update(x=x, y=y, y_upper=y + y_err, y_lower=y - y_err)
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scatter_source.data.update(x=x, y=y, y_upper=y + y_err, y_lower=y - y_err)
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fit = scan.get("fit")
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if fit is not None:
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x_fit = np.linspace(x[0], x[-1], 100)
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plot_fit_source.data.update(x=x_fit, y=fit.eval(x=x_fit))
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fit_source.data.update(x=x_fit, y=fit.eval(x=x_fit))
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x_bkg = []
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y_bkg = []
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@ -302,15 +290,15 @@ def create():
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xs_peak.append(x_fit)
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ys_peak.append(comps[f"f{i}_"])
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plot_bkg_source.data.update(x=x_bkg, y=y_bkg)
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plot_peak_source.data.update(xs=xs_peak, ys=ys_peak)
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bkg_source.data.update(x=x_bkg, y=y_bkg)
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peak_source.data.update(xs=xs_peak, ys=ys_peak)
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fit_output_textinput.value = fit.fit_report()
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else:
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plot_fit_source.data.update(x=[], y=[])
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plot_bkg_source.data.update(x=[], y=[])
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plot_peak_source.data.update(xs=[], ys=[])
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fit_source.data.update(x=[], y=[])
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bkg_source.data.update(x=[], y=[])
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peak_source.data.update(xs=[], ys=[])
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fit_output_textinput.value = ""
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def _update_overview():
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@ -336,9 +324,9 @@ def create():
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ov_plot.axis[0].axis_label = scan_motor
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ov_param_plot.axis[0].axis_label = scan_motor
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ov_plot_mline_source.data.update(xs=xs, ys=ys, param=param, color=color_palette(len(xs)))
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ov_mline_source.data.update(xs=xs, ys=ys, param=param, color=color_palette(len(xs)))
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ov_param_plot_scatter_source.data.update(x=x, y=y)
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ov_param_scatter_source.data.update(x=x, y=y)
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if y:
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x1, x2 = min(x), max(x)
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@ -348,7 +336,7 @@ def create():
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np.linspace(y1, y2, ov_param_plot.inner_height),
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)
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image = interpolate.griddata((x, y), par, (grid_x, grid_y))
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ov_param_plot_image_source.data.update(
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ov_param_image_source.data.update(
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image=[image], x=[x1], y=[y1], dw=[x2 - x1], dh=[y2 - y1]
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)
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@ -363,7 +351,7 @@ def create():
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y_range.bounds = (y1, y2)
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else:
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ov_param_plot_image_source.data.update(image=[], x=[], y=[], dw=[], dh=[])
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ov_param_image_source.data.update(image=[], x=[], y=[], dw=[], dh=[])
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def _update_param_plot():
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x = []
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@ -382,40 +370,31 @@ def create():
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y_lower.append(param_fit_val - param_fit_std)
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y_upper.append(param_fit_val + param_fit_std)
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param_plot_scatter_source.data.update(x=x, y=y, y_lower=y_lower, y_upper=y_upper)
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param_scatter_source.data.update(x=x, y=y, y_lower=y_lower, y_upper=y_upper)
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# Main plot
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plot = Plot(
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x_range=DataRange1d(),
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y_range=DataRange1d(only_visible=True),
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plot = figure(
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x_axis_label="Scan motor",
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y_axis_label="Counts",
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plot_height=450,
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plot_width=700,
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tools="pan,wheel_zoom,reset",
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)
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plot.add_layout(LinearAxis(axis_label="Counts"), place="left")
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plot.add_layout(LinearAxis(axis_label="Scan motor"), place="below")
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plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
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plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
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plot_scatter_source = ColumnDataSource(dict(x=[0], y=[0], y_upper=[0], y_lower=[0]))
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plot_scatter = plot.add_glyph(
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plot_scatter_source, Scatter(x="x", y="y", line_color="steelblue", fill_color="steelblue")
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scatter_source = ColumnDataSource(dict(x=[0], y=[0], y_upper=[0], y_lower=[0]))
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plot.circle(
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source=scatter_source, line_color="steelblue", fill_color="steelblue", legend_label="data"
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)
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plot.add_layout(Whisker(source=plot_scatter_source, base="x", upper="y_upper", lower="y_lower"))
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plot.add_layout(Whisker(source=scatter_source, base="x", upper="y_upper", lower="y_lower"))
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plot_fit_source = ColumnDataSource(dict(x=[0], y=[0]))
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plot_fit = plot.add_glyph(plot_fit_source, Line(x="x", y="y"))
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fit_source = ColumnDataSource(dict(x=[0], y=[0]))
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plot.line(source=fit_source, legend_label="best fit")
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plot_bkg_source = ColumnDataSource(dict(x=[0], y=[0]))
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plot_bkg = plot.add_glyph(
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plot_bkg_source, Line(x="x", y="y", line_color="green", line_dash="dashed")
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)
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bkg_source = ColumnDataSource(dict(x=[0], y=[0]))
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plot.line(source=bkg_source, line_color="green", line_dash="dashed", legend_label="linear")
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plot_peak_source = ColumnDataSource(dict(xs=[[0]], ys=[[0]]))
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plot_peak = plot.add_glyph(
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plot_peak_source, MultiLine(xs="xs", ys="ys", line_color="red", line_dash="dashed")
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)
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peak_source = ColumnDataSource(dict(xs=[[0]], ys=[[0]]))
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plot.multi_line(source=peak_source, line_color="red", line_dash="dashed", legend_label="peak")
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fit_from_span = Span(location=None, dimension="height", line_dash="dashed")
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plot.add_layout(fit_from_span)
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@ -423,80 +402,61 @@ def create():
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fit_to_span = Span(location=None, dimension="height", line_dash="dashed")
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plot.add_layout(fit_to_span)
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plot.add_layout(
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Legend(
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items=[
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("data", [plot_scatter]),
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("best fit", [plot_fit]),
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("peak", [plot_peak]),
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("linear", [plot_bkg]),
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],
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location="top_left",
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click_policy="hide",
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)
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)
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plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())
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plot.y_range.only_visible = True
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plot.toolbar.logo = None
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plot.legend.click_policy = "hide"
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# Overview multilines plot
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ov_plot = Plot(x_range=DataRange1d(), y_range=DataRange1d(), plot_height=450, plot_width=700)
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ov_plot = figure(
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x_axis_label="Scan motor",
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y_axis_label="Counts",
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plot_height=450,
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plot_width=700,
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tools="pan,wheel_zoom,reset",
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)
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ov_plot.add_layout(LinearAxis(axis_label="Counts"), place="left")
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ov_plot.add_layout(LinearAxis(axis_label="Scan motor"), place="below")
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ov_mline_source = ColumnDataSource(dict(xs=[], ys=[], param=[], color=[]))
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ov_plot.multi_line(source=ov_mline_source, line_color="color")
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ov_plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
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ov_plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
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ov_plot.add_tools(HoverTool(tooltips=[("param", "@param")]))
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ov_plot_mline_source = ColumnDataSource(dict(xs=[], ys=[], param=[], color=[]))
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ov_plot.add_glyph(ov_plot_mline_source, MultiLine(xs="xs", ys="ys", line_color="color"))
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hover_tool = HoverTool(tooltips=[("param", "@param")])
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ov_plot.add_tools(PanTool(), WheelZoomTool(), hover_tool, ResetTool())
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ov_plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())
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ov_plot.toolbar.logo = None
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# Overview perams plot
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ov_param_plot = Plot(x_range=Range1d(), y_range=Range1d(), plot_height=450, plot_width=700)
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ov_param_plot.add_layout(LinearAxis(axis_label="Param"), place="left")
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ov_param_plot.add_layout(LinearAxis(axis_label="Scan motor"), place="below")
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ov_param_plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
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ov_param_plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
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# Overview params plot
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ov_param_plot = figure(
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x_axis_label="Scan motor",
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y_axis_label="Param",
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x_range=Range1d(),
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y_range=Range1d(),
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plot_height=450,
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plot_width=700,
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tools="pan,wheel_zoom,reset",
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)
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color_mapper = LinearColorMapper(palette=Plasma256)
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ov_param_plot_image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
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ov_param_plot.add_glyph(
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ov_param_plot_image_source,
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Image(image="image", x="x", y="y", dw="dw", dh="dh", color_mapper=color_mapper),
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)
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ov_param_image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
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ov_param_plot.image(source=ov_param_image_source, color_mapper=color_mapper)
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ov_param_plot_scatter_source = ColumnDataSource(dict(x=[], y=[]))
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ov_param_plot.add_glyph(
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ov_param_plot_scatter_source, Scatter(x="x", y="y", marker="dot", size=15),
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)
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ov_param_scatter_source = ColumnDataSource(dict(x=[], y=[]))
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ov_param_plot.dot(source=ov_param_scatter_source, size=15, color="black")
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ov_param_plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())
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ov_param_plot.toolbar.logo = None
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# Parameter plot
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param_plot = Plot(x_range=DataRange1d(), y_range=DataRange1d(), plot_height=400, plot_width=700)
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param_plot.add_layout(LinearAxis(axis_label="Fit parameter"), place="left")
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param_plot.add_layout(LinearAxis(axis_label="Parameter"), place="below")
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param_plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
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param_plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
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param_plot_scatter_source = ColumnDataSource(dict(x=[], y=[], y_upper=[], y_lower=[]))
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param_plot.add_glyph(param_plot_scatter_source, Scatter(x="x", y="y"))
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param_plot.add_layout(
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Whisker(source=param_plot_scatter_source, base="x", upper="y_upper", lower="y_lower")
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param_plot = figure(
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x_axis_label="Parameter",
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y_axis_label="Fit parameter",
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plot_height=400,
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plot_width=700,
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tools="pan,wheel_zoom,reset",
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)
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param_scatter_source = ColumnDataSource(dict(x=[], y=[], y_upper=[], y_lower=[]))
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param_plot.circle(source=param_scatter_source)
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param_plot.add_layout(
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Whisker(source=param_scatter_source, base="x", upper="y_upper", lower="y_lower")
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)
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param_plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())
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param_plot.toolbar.logo = None
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def fit_param_select_callback(_attr, _old, _new):
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@ -684,7 +644,7 @@ def create():
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n = len(params)
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fitparams = dict(
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param=params, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n,
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param=params, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n
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)
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if function == "linear":
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