Extract fit controls

pyzebra/app/__init__.py

@@ -0,0 +1 @@
+from pyzebra.app.fit_controls import FitControls

pyzebra/app/fit_controls.py

@@ -0,0 +1,169 @@
+import types
+
+from bokeh.models import (
+    Button,
+    CellEditor,
+    CheckboxEditor,
+    CheckboxGroup,
+    ColumnDataSource,
+    DataTable,
+    Dropdown,
+    MultiSelect,
+    NumberEditor,
+    RadioGroup,
+    Spinner,
+    TableColumn,
+    TextAreaInput,
+)
+
+import pyzebra
+
+
+def _params_factory(function):
+    if function == "linear":
+        param_names = ["slope", "intercept"]
+    elif function == "gaussian":
+        param_names = ["amplitude", "center", "sigma"]
+    elif function == "voigt":
+        param_names = ["amplitude", "center", "sigma", "gamma"]
+    elif function == "pvoigt":
+        param_names = ["amplitude", "center", "sigma", "fraction"]
+    elif function == "pseudovoigt1":
+        param_names = ["amplitude", "center", "g_sigma", "l_sigma", "fraction"]
+    else:
+        raise ValueError("Unknown fit function")
+
+    n = len(param_names)
+    params = dict(
+        param=param_names, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n
+    )
+
+    if function == "linear":
+        params["value"] = [0, 1]
+        params["vary"] = [False, True]
+        params["min"] = [None, 0]
+
+    elif function == "gaussian":
+        params["min"] = [0, None, None]
+
+    return params
+
+
+class FitControls:
+    def __init__(self):
+        self.params = {}
+
+        def add_function_button_callback(click):
+            # bokeh requires (str, str) for MultiSelect options
+            new_tag = f"{click.item}-{function_select.tags[0]}"
+            function_select.options.append((new_tag, click.item))
+            self.params[new_tag] = _params_factory(click.item)
+            function_select.tags[0] += 1
+
+        add_function_button = Dropdown(
+            label="Add fit function",
+            menu=[
+                ("Linear", "linear"),
+                ("Gaussian", "gaussian"),
+                ("Voigt", "voigt"),
+                ("Pseudo Voigt", "pvoigt"),
+                # ("Pseudo Voigt1", "pseudovoigt1"),
+            ],
+            width=145,
+        )
+        add_function_button.on_click(add_function_button_callback)
+        self.add_function_button = add_function_button
+
+        def function_list_callback(_attr, old, new):
+            # Avoid selection of multiple indicies (via Shift+Click or Ctrl+Click)
+            if len(new) > 1:
+                # drop selection to the previous one
+                function_select.value = old
+                return
+
+            if len(old) > 1:
+                # skip unnecessary update caused by selection drop
+                return
+
+            if new:
+                params_table_source.data.update(self.params[new[0]])
+            else:
+                params_table_source.data.update(dict(param=[], value=[], vary=[], min=[], max=[]))
+
+        function_select = MultiSelect(options=[], height=120, width=145)
+        function_select.tags = [0]
+        function_select.on_change("value", function_list_callback)
+        self.function_select = function_select
+
+        def remove_function_button_callback():
+            if function_select.value:
+                sel_tag = function_select.value[0]
+                del self.params[sel_tag]
+                for elem in function_select.options:
+                    if elem[0] == sel_tag:
+                        function_select.options.remove(elem)
+                        break
+
+                function_select.value = []
+
+        remove_function_button = Button(label="Remove fit function", width=145)
+        remove_function_button.on_click(remove_function_button_callback)
+        self.remove_function_button = remove_function_button
+
+        params_table_source = ColumnDataSource(dict(param=[], value=[], vary=[], min=[], max=[]))
+        self.params_table = DataTable(
+            source=params_table_source,
+            columns=[
+                TableColumn(field="param", title="Parameter", editor=CellEditor()),
+                TableColumn(field="value", title="Value", editor=NumberEditor()),
+                TableColumn(field="vary", title="Vary", editor=CheckboxEditor()),
+                TableColumn(field="min", title="Min", editor=NumberEditor()),
+                TableColumn(field="max", title="Max", editor=NumberEditor()),
+            ],
+            height=200,
+            width=350,
+            index_position=None,
+            editable=True,
+            auto_edit=True,
+        )
+
+        # start with `background` and `gauss` fit functions added
+        add_function_button_callback(types.SimpleNamespace(item="linear"))
+        add_function_button_callback(types.SimpleNamespace(item="gaussian"))
+        function_select.value = ["gaussian-1"]  # put selection on gauss
+
+        self.from_spinner = Spinner(title="Fit from:", width=145)
+        self.to_spinner = Spinner(title="to:", width=145)
+
+        self.area_method_radiogroup = RadioGroup(labels=["Function", "Area"], active=0, width=145)
+
+        self.lorentz_checkbox = CheckboxGroup(
+            labels=["Lorentz Correction"], width=145, margin=(13, 5, 5, 5)
+        )
+
+        self.result_textarea = TextAreaInput(title="Fit results:", width=750, height=200)
+
+    def _process_scan(self, scan):
+        pyzebra.fit_scan(
+            scan, self.params, fit_from=self.from_spinner.value, fit_to=self.to_spinner.value
+        )
+        pyzebra.get_area(
+            scan,
+            area_method=pyzebra.AREA_METHODS[self.area_method_radiogroup.active],
+            lorentz=self.lorentz_checkbox.active,
+        )
+
+    def fit_scan(self, scan):
+        self._process_scan(scan)
+
+    def fit_dataset(self, dataset):
+        for scan in dataset:
+            if scan["export"]:
+                self._process_scan(scan)
+
+    def update_result_textarea(self, scan):
+        fit = scan.get("fit")
+        if fit is None:
+            self.result_textarea.value = ""
+        else:
+            self.result_textarea.value = fit.fit_report()

pyzebra/app/panel_ccl_compare.py

@@ -2,7 +2,6 @@ import base64
 import io
 import os
 import tempfile
-import types
 
 import numpy as np
 from bokeh.io import curdoc
@@ -11,15 +10,12 @@ from bokeh.models import (
     Button,
     CellEditor,
     CheckboxEditor,
-    CheckboxGroup,
     ColumnDataSource,
     CustomJS,
     DataTable,
     Div,
-    Dropdown,
     FileInput,
     MultiSelect,
-    NumberEditor,
     Panel,
     RadioGroup,
     Select,
@@ -33,7 +29,7 @@ from bokeh.models import (
 from bokeh.plotting import figure
 
 import pyzebra
-from pyzebra import AREA_METHODS, EXPORT_TARGETS
+from pyzebra import EXPORT_TARGETS, app
 
 javaScript = """
 let j = 0;
@@ -61,7 +57,6 @@ def create():
     doc = curdoc()
     dataset1 = []
     dataset2 = []
-    fit_params = {}
     js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
 
     def file_select_update_for_proposal():
@@ -244,7 +239,7 @@ def create():
                 xs_peak = []
                 ys_peak = []
                 comps = fit.eval_components(x=x_fit)
-                for i, model in enumerate(fit_params):
+                for i, model in enumerate(app_fitctrl.params):
                     if "linear" in model:
                         x_bkg = x_fit
                         y_bkg = comps[f"f{i}_"]
@@ -264,7 +259,7 @@ def create():
                 bkg_source.data.update(x=[], y=[])
                 peak_source.data.update(xs=[], ys=[])
 
-        fit_output_textinput.value = fit_output
+        app_fitctrl.result_textarea.value = fit_output
 
     # Main plot
     plot = figure(
@@ -425,136 +420,21 @@ def create():
     restore_button = Button(label="Restore scan", width=145)
     restore_button.on_click(restore_button_callback)
 
+    app_fitctrl = app.FitControls()
+
     def fit_from_spinner_callback(_attr, _old, new):
         fit_from_span.location = new
 
-    fit_from_spinner = Spinner(title="Fit from:", width=145)
+    app_fitctrl.from_spinner.on_change("value", fit_from_spinner_callback)
-    fit_from_spinner.on_change("value", fit_from_spinner_callback)
 
     def fit_to_spinner_callback(_attr, _old, new):
         fit_to_span.location = new
 
-    fit_to_spinner = Spinner(title="to:", width=145)
+    app_fitctrl.to_spinner.on_change("value", fit_to_spinner_callback)
-    fit_to_spinner.on_change("value", fit_to_spinner_callback)
-
-    def fitparams_add_dropdown_callback(click):
-        # bokeh requires (str, str) for MultiSelect options
-        new_tag = f"{click.item}-{fitparams_select.tags[0]}"
-        fitparams_select.options.append((new_tag, click.item))
-        fit_params[new_tag] = fitparams_factory(click.item)
-        fitparams_select.tags[0] += 1
-
-    fitparams_add_dropdown = Dropdown(
-        label="Add fit function",
-        menu=[
-            ("Linear", "linear"),
-            ("Gaussian", "gaussian"),
-            ("Voigt", "voigt"),
-            ("Pseudo Voigt", "pvoigt"),
-            # ("Pseudo Voigt1", "pseudovoigt1"),
-        ],
-        width=145,
-    )
-    fitparams_add_dropdown.on_click(fitparams_add_dropdown_callback)
-
-    def fitparams_select_callback(_attr, old, new):
-        # Avoid selection of multiple indicies (via Shift+Click or Ctrl+Click)
-        if len(new) > 1:
-            # drop selection to the previous one
-            fitparams_select.value = old
-            return
-
-        if len(old) > 1:
-            # skip unnecessary update caused by selection drop
-            return
-
-        if new:
-            fitparams_table_source.data.update(fit_params[new[0]])
-        else:
-            fitparams_table_source.data.update(dict(param=[], value=[], vary=[], min=[], max=[]))
-
-    fitparams_select = MultiSelect(options=[], height=120, width=145)
-    fitparams_select.tags = [0]
-    fitparams_select.on_change("value", fitparams_select_callback)
-
-    def fitparams_remove_button_callback():
-        if fitparams_select.value:
-            sel_tag = fitparams_select.value[0]
-            del fit_params[sel_tag]
-            for elem in fitparams_select.options:
-                if elem[0] == sel_tag:
-                    fitparams_select.options.remove(elem)
-                    break
-
-            fitparams_select.value = []
-
-    fitparams_remove_button = Button(label="Remove fit function", width=145)
-    fitparams_remove_button.on_click(fitparams_remove_button_callback)
-
-    def fitparams_factory(function):
-        if function == "linear":
-            params = ["slope", "intercept"]
-        elif function == "gaussian":
-            params = ["amplitude", "center", "sigma"]
-        elif function == "voigt":
-            params = ["amplitude", "center", "sigma", "gamma"]
-        elif function == "pvoigt":
-            params = ["amplitude", "center", "sigma", "fraction"]
-        elif function == "pseudovoigt1":
-            params = ["amplitude", "center", "g_sigma", "l_sigma", "fraction"]
-        else:
-            raise ValueError("Unknown fit function")
-
-        n = len(params)
-        fitparams = dict(
-            param=params, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n
-        )
-
-        if function == "linear":
-            fitparams["value"] = [0, 1]
-            fitparams["vary"] = [False, True]
-            fitparams["min"] = [None, 0]
-
-        elif function == "gaussian":
-            fitparams["min"] = [0, None, None]
-
-        return fitparams
-
-    fitparams_table_source = ColumnDataSource(dict(param=[], value=[], vary=[], min=[], max=[]))
-    fitparams_table = DataTable(
-        source=fitparams_table_source,
-        columns=[
-            TableColumn(field="param", title="Parameter", editor=CellEditor()),
-            TableColumn(field="value", title="Value", editor=NumberEditor()),
-            TableColumn(field="vary", title="Vary", editor=CheckboxEditor()),
-            TableColumn(field="min", title="Min", editor=NumberEditor()),
-            TableColumn(field="max", title="Max", editor=NumberEditor()),
-        ],
-        height=200,
-        width=350,
-        index_position=None,
-        editable=True,
-        auto_edit=True,
-    )
-
-    # start with `background` and `gauss` fit functions added
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="linear"))
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="gaussian"))
-    fitparams_select.value = ["gaussian-1"]  # add selection to gauss
-
-    fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in [*dataset1, *dataset2]:
+        app_fitctrl.fit_dataset(dataset1)
-            if scan["export"]:
+        app_fitctrl.fit_dataset(dataset2)
-                pyzebra.fit_scan(
-                    scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
-                )
-                pyzebra.get_area(
-                    scan,
-                    area_method=AREA_METHODS[area_method_radiobutton.active],
-                    lorentz=lorentz_checkbox.active,
-                )
 
         _update_plot()
         _update_table()
@@ -563,15 +443,9 @@ def create():
     proc_all_button.on_click(proc_all_button_callback)
 
     def proc_button_callback():
-        for scan in _get_selected_scan():
+        scan1, scan2 = _get_selected_scan()
-            pyzebra.fit_scan(
+        app_fitctrl.fit_scan(scan1)
-                scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
+        app_fitctrl.fit_scan(scan2)
-            )
-            pyzebra.get_area(
-                scan,
-                area_method=AREA_METHODS[area_method_radiobutton.active],
-                lorentz=lorentz_checkbox.active,
-            )
 
         _update_plot()
         _update_table()
@@ -579,16 +453,11 @@ def create():
     proc_button = Button(label="Process Current", width=145)
     proc_button.on_click(proc_button_callback)
 
-    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
-    area_method_radiobutton = RadioGroup(labels=["Function", "Area"], active=0, width=145)
-
     intensity_diff_div = Div(text="Intensity difference:", margin=(5, 5, 0, 5))
     intensity_diff_radiobutton = RadioGroup(
         labels=["file1 - file2", "file2 - file1"], active=0, width=145
     )
 
-    lorentz_checkbox = CheckboxGroup(labels=["Lorentz Correction"], width=145, margin=(13, 5, 5, 5))
-
     export_preview_textinput = TextAreaInput(title="Export file(s) preview:", width=500, height=400)
 
     def _update_preview():
@@ -648,19 +517,24 @@ def create():
     save_button = Button(label="Download File(s)", button_type="success", width=200)
     save_button.js_on_click(CustomJS(args={"js_data": js_data}, code=javaScript))
 
+    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
     fitpeak_controls = row(
-        column(fitparams_add_dropdown, fitparams_select, fitparams_remove_button),
+        column(
-        fitparams_table,
+            app_fitctrl.add_function_button,
+            app_fitctrl.function_select,
+            app_fitctrl.remove_function_button,
+        ),
+        app_fitctrl.params_table,
         Spacer(width=20),
         column(
-            fit_from_spinner,
+            app_fitctrl.from_spinner,
-            lorentz_checkbox,
+            app_fitctrl.lorentz_checkbox,
             area_method_div,
-            area_method_radiobutton,
+            app_fitctrl.area_method_radiogroup,
             intensity_diff_div,
             intensity_diff_radiobutton,
         ),
-        column(fit_to_spinner, proc_button, proc_all_button),
+        column(app_fitctrl.to_spinner, proc_button, proc_all_button),
     )
 
     scan_layout = column(
@@ -680,7 +554,7 @@ def create():
 
     tab_layout = column(
         row(import_layout, scan_layout, plot, Spacer(width=30), export_layout),
-        row(fitpeak_controls, fit_output_textinput),
+        row(fitpeak_controls, app_fitctrl.result_textarea),
     )
 
     return Panel(child=tab_layout, title="ccl compare")

pyzebra/app/panel_ccl_integrate.py

@@ -2,7 +2,6 @@ import base64
 import io
 import os
 import tempfile
-import types
 
 import numpy as np
 from bokeh.io import curdoc
@@ -11,17 +10,13 @@ from bokeh.models import (
     Button,
     CellEditor,
     CheckboxEditor,
-    CheckboxGroup,
     ColumnDataSource,
     CustomJS,
     DataTable,
     Div,
-    Dropdown,
     FileInput,
     MultiSelect,
-    NumberEditor,
     Panel,
-    RadioGroup,
     Select,
     Spacer,
     Span,
@@ -33,7 +28,7 @@ from bokeh.models import (
 from bokeh.plotting import figure
 
 import pyzebra
-from pyzebra import AREA_METHODS, EXPORT_TARGETS
+from pyzebra import EXPORT_TARGETS, app
 
 javaScript = """
 let j = 0;
@@ -60,7 +55,6 @@ for (let i = 0; i < js_data.data['fname'].length; i++) {
 def create():
     doc = curdoc()
     dataset = []
-    fit_params = {}
     js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
 
     def file_select_update_for_proposal():
@@ -259,7 +253,7 @@ def create():
             xs_peak = []
             ys_peak = []
             comps = fit.eval_components(x=x_fit)
-            for i, model in enumerate(fit_params):
+            for i, model in enumerate(app_fitctrl.params):
                 if "linear" in model:
                     x_bkg = x_fit
                     y_bkg = comps[f"f{i}_"]
@@ -271,13 +265,12 @@ def create():
             bkg_source.data.update(x=x_bkg, y=y_bkg)
             peak_source.data.update(xs=xs_peak, ys=ys_peak)
 
-            fit_output_textinput.value = fit.fit_report()
-
         else:
             fit_source.data.update(x=[], y=[])
             bkg_source.data.update(x=[], y=[])
             peak_source.data.update(xs=[], ys=[])
-            fit_output_textinput.value = ""
+
+        app_fitctrl.update_result_textarea(scan)
 
     # Main plot
     plot = figure(
@@ -403,136 +396,20 @@ def create():
     restore_button = Button(label="Restore scan", width=145)
     restore_button.on_click(restore_button_callback)
 
+    app_fitctrl = app.FitControls()
+
     def fit_from_spinner_callback(_attr, _old, new):
         fit_from_span.location = new
 
-    fit_from_spinner = Spinner(title="Fit from:", width=145)
+    app_fitctrl.from_spinner.on_change("value", fit_from_spinner_callback)
-    fit_from_spinner.on_change("value", fit_from_spinner_callback)
 
     def fit_to_spinner_callback(_attr, _old, new):
         fit_to_span.location = new
 
-    fit_to_spinner = Spinner(title="to:", width=145)
+    app_fitctrl.to_spinner.on_change("value", fit_to_spinner_callback)
-    fit_to_spinner.on_change("value", fit_to_spinner_callback)
-
-    def fitparams_add_dropdown_callback(click):
-        # bokeh requires (str, str) for MultiSelect options
-        new_tag = f"{click.item}-{fitparams_select.tags[0]}"
-        fitparams_select.options.append((new_tag, click.item))
-        fit_params[new_tag] = fitparams_factory(click.item)
-        fitparams_select.tags[0] += 1
-
-    fitparams_add_dropdown = Dropdown(
-        label="Add fit function",
-        menu=[
-            ("Linear", "linear"),
-            ("Gaussian", "gaussian"),
-            ("Voigt", "voigt"),
-            ("Pseudo Voigt", "pvoigt"),
-            # ("Pseudo Voigt1", "pseudovoigt1"),
-        ],
-        width=145,
-    )
-    fitparams_add_dropdown.on_click(fitparams_add_dropdown_callback)
-
-    def fitparams_select_callback(_attr, old, new):
-        # Avoid selection of multiple indicies (via Shift+Click or Ctrl+Click)
-        if len(new) > 1:
-            # drop selection to the previous one
-            fitparams_select.value = old
-            return
-
-        if len(old) > 1:
-            # skip unnecessary update caused by selection drop
-            return
-
-        if new:
-            fitparams_table_source.data.update(fit_params[new[0]])
-        else:
-            fitparams_table_source.data.update(dict(param=[], value=[], vary=[], min=[], max=[]))
-
-    fitparams_select = MultiSelect(options=[], height=120, width=145)
-    fitparams_select.tags = [0]
-    fitparams_select.on_change("value", fitparams_select_callback)
-
-    def fitparams_remove_button_callback():
-        if fitparams_select.value:
-            sel_tag = fitparams_select.value[0]
-            del fit_params[sel_tag]
-            for elem in fitparams_select.options:
-                if elem[0] == sel_tag:
-                    fitparams_select.options.remove(elem)
-                    break
-
-            fitparams_select.value = []
-
-    fitparams_remove_button = Button(label="Remove fit function", width=145)
-    fitparams_remove_button.on_click(fitparams_remove_button_callback)
-
-    def fitparams_factory(function):
-        if function == "linear":
-            params = ["slope", "intercept"]
-        elif function == "gaussian":
-            params = ["amplitude", "center", "sigma"]
-        elif function == "voigt":
-            params = ["amplitude", "center", "sigma", "gamma"]
-        elif function == "pvoigt":
-            params = ["amplitude", "center", "sigma", "fraction"]
-        elif function == "pseudovoigt1":
-            params = ["amplitude", "center", "g_sigma", "l_sigma", "fraction"]
-        else:
-            raise ValueError("Unknown fit function")
-
-        n = len(params)
-        fitparams = dict(
-            param=params, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n
-        )
-
-        if function == "linear":
-            fitparams["value"] = [0, 1]
-            fitparams["vary"] = [False, True]
-            fitparams["min"] = [None, 0]
-
-        elif function == "gaussian":
-            fitparams["min"] = [0, None, None]
-
-        return fitparams
-
-    fitparams_table_source = ColumnDataSource(dict(param=[], value=[], vary=[], min=[], max=[]))
-    fitparams_table = DataTable(
-        source=fitparams_table_source,
-        columns=[
-            TableColumn(field="param", title="Parameter", editor=CellEditor()),
-            TableColumn(field="value", title="Value", editor=NumberEditor()),
-            TableColumn(field="vary", title="Vary", editor=CheckboxEditor()),
-            TableColumn(field="min", title="Min", editor=NumberEditor()),
-            TableColumn(field="max", title="Max", editor=NumberEditor()),
-        ],
-        height=200,
-        width=350,
-        index_position=None,
-        editable=True,
-        auto_edit=True,
-    )
-
-    # start with `background` and `gauss` fit functions added
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="linear"))
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="gaussian"))
-    fitparams_select.value = ["gaussian-1"]  # add selection to gauss
-
-    fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in dataset:
+        app_fitctrl.fit_dataset(dataset)
-            if scan["export"]:
-                pyzebra.fit_scan(
-                    scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
-                )
-                pyzebra.get_area(
-                    scan,
-                    area_method=AREA_METHODS[area_method_radiobutton.active],
-                    lorentz=lorentz_checkbox.active,
-                )
 
         _update_plot()
         _update_table()
@@ -541,15 +418,7 @@ def create():
     proc_all_button.on_click(proc_all_button_callback)
 
     def proc_button_callback():
-        scan = _get_selected_scan()
+        app_fitctrl.fit_scan(_get_selected_scan())
-        pyzebra.fit_scan(
-            scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
-        )
-        pyzebra.get_area(
-            scan,
-            area_method=AREA_METHODS[area_method_radiobutton.active],
-            lorentz=lorentz_checkbox.active,
-        )
 
         _update_plot()
         _update_table()
@@ -557,11 +426,6 @@ def create():
     proc_button = Button(label="Process Current", width=145)
     proc_button.on_click(proc_button_callback)
 
-    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
-    area_method_radiobutton = RadioGroup(labels=["Function", "Area"], active=0, width=145)
-
-    lorentz_checkbox = CheckboxGroup(labels=["Lorentz Correction"], width=145, margin=(13, 5, 5, 5))
-
     export_preview_textinput = TextAreaInput(title="Export file(s) preview:", width=500, height=400)
 
     def _update_preview():
@@ -615,12 +479,22 @@ def create():
     save_button = Button(label="Download File(s)", button_type="success", width=200)
     save_button.js_on_click(CustomJS(args={"js_data": js_data}, code=javaScript))
 
+    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
     fitpeak_controls = row(
-        column(fitparams_add_dropdown, fitparams_select, fitparams_remove_button),
+        column(
-        fitparams_table,
+            app_fitctrl.add_function_button,
+            app_fitctrl.function_select,
+            app_fitctrl.remove_function_button,
+        ),
+        app_fitctrl.params_table,
         Spacer(width=20),
-        column(fit_from_spinner, lorentz_checkbox, area_method_div, area_method_radiobutton),
+        column(
-        column(fit_to_spinner, proc_button, proc_all_button),
+            app_fitctrl.from_spinner,
+            app_fitctrl.lorentz_checkbox,
+            area_method_div,
+            app_fitctrl.area_method_radiogroup,
+        ),
+        column(app_fitctrl.to_spinner, proc_button, proc_all_button),
     )
 
     scan_layout = column(
@@ -647,7 +521,7 @@ def create():
 
     tab_layout = column(
         row(import_layout, scan_layout, plot, Spacer(width=30), export_layout),
-        row(fitpeak_controls, fit_output_textinput),
+        row(fitpeak_controls, app_fitctrl.result_textarea),
     )
 
     return Panel(child=tab_layout, title="ccl integrate")

pyzebra/app/panel_param_study.py

@@ -3,7 +3,6 @@ import io
 import itertools
 import os
 import tempfile
-import types
 
 import numpy as np
 from bokeh.io import curdoc
@@ -12,19 +11,16 @@ from bokeh.models import (
     Button,
     CellEditor,
     CheckboxEditor,
-    CheckboxGroup,
     ColumnDataSource,
     CustomJS,
     DataTable,
     Div,
-    Dropdown,
     FileInput,
     HoverTool,
     LinearColorMapper,
     MultiSelect,
     NumberEditor,
     Panel,
-    RadioGroup,
     Range1d,
     Select,
     Spacer,
@@ -40,7 +36,7 @@ from bokeh.plotting import figure
 from scipy import interpolate
 
 import pyzebra
-from pyzebra import AREA_METHODS
+from pyzebra import app
 
 javaScript = """
 let j = 0;
@@ -72,7 +68,6 @@ def color_palette(n_colors):
 def create():
     doc = curdoc()
     dataset = []
-    fit_params = {}
     js_data = ColumnDataSource(data=dict(content=[""], fname=[""], ext=[""]))
 
     def file_select_update_for_proposal():
@@ -281,7 +276,7 @@ def create():
             xs_peak = []
             ys_peak = []
             comps = fit.eval_components(x=x_fit)
-            for i, model in enumerate(fit_params):
+            for i, model in enumerate(app_fitctrl.params):
                 if "linear" in model:
                     x_bkg = x_fit
                     y_bkg = comps[f"f{i}_"]
@@ -293,13 +288,12 @@ def create():
             bkg_source.data.update(x=x_bkg, y=y_bkg)
             peak_source.data.update(xs=xs_peak, ys=ys_peak)
 
-            fit_output_textinput.value = fit.fit_report()
-
         else:
             fit_source.data.update(x=[], y=[])
             bkg_source.data.update(x=[], y=[])
             peak_source.data.update(xs=[], ys=[])
-            fit_output_textinput.value = ""
+
+        app_fitctrl.update_result_textarea(scan)
 
     def _update_overview():
         xs = []
@@ -562,136 +556,20 @@ def create():
     )
     param_select.on_change("value", param_select_callback)
 
+    app_fitctrl = app.FitControls()
+
     def fit_from_spinner_callback(_attr, _old, new):
         fit_from_span.location = new
 
-    fit_from_spinner = Spinner(title="Fit from:", width=145)
+    app_fitctrl.from_spinner.on_change("value", fit_from_spinner_callback)
-    fit_from_spinner.on_change("value", fit_from_spinner_callback)
 
     def fit_to_spinner_callback(_attr, _old, new):
         fit_to_span.location = new
 
-    fit_to_spinner = Spinner(title="to:", width=145)
+    app_fitctrl.to_spinner.on_change("value", fit_to_spinner_callback)
-    fit_to_spinner.on_change("value", fit_to_spinner_callback)
-
-    def fitparams_add_dropdown_callback(click):
-        # bokeh requires (str, str) for MultiSelect options
-        new_tag = f"{click.item}-{fitparams_select.tags[0]}"
-        fitparams_select.options.append((new_tag, click.item))
-        fit_params[new_tag] = fitparams_factory(click.item)
-        fitparams_select.tags[0] += 1
-
-    fitparams_add_dropdown = Dropdown(
-        label="Add fit function",
-        menu=[
-            ("Linear", "linear"),
-            ("Gaussian", "gaussian"),
-            ("Voigt", "voigt"),
-            ("Pseudo Voigt", "pvoigt"),
-            # ("Pseudo Voigt1", "pseudovoigt1"),
-        ],
-        width=145,
-    )
-    fitparams_add_dropdown.on_click(fitparams_add_dropdown_callback)
-
-    def fitparams_select_callback(_attr, old, new):
-        # Avoid selection of multiple indicies (via Shift+Click or Ctrl+Click)
-        if len(new) > 1:
-            # drop selection to the previous one
-            fitparams_select.value = old
-            return
-
-        if len(old) > 1:
-            # skip unnecessary update caused by selection drop
-            return
-
-        if new:
-            fitparams_table_source.data.update(fit_params[new[0]])
-        else:
-            fitparams_table_source.data.update(dict(param=[], value=[], vary=[], min=[], max=[]))
-
-    fitparams_select = MultiSelect(options=[], height=120, width=145)
-    fitparams_select.tags = [0]
-    fitparams_select.on_change("value", fitparams_select_callback)
-
-    def fitparams_remove_button_callback():
-        if fitparams_select.value:
-            sel_tag = fitparams_select.value[0]
-            del fit_params[sel_tag]
-            for elem in fitparams_select.options:
-                if elem[0] == sel_tag:
-                    fitparams_select.options.remove(elem)
-                    break
-
-            fitparams_select.value = []
-
-    fitparams_remove_button = Button(label="Remove fit function", width=145)
-    fitparams_remove_button.on_click(fitparams_remove_button_callback)
-
-    def fitparams_factory(function):
-        if function == "linear":
-            params = ["slope", "intercept"]
-        elif function == "gaussian":
-            params = ["amplitude", "center", "sigma"]
-        elif function == "voigt":
-            params = ["amplitude", "center", "sigma", "gamma"]
-        elif function == "pvoigt":
-            params = ["amplitude", "center", "sigma", "fraction"]
-        elif function == "pseudovoigt1":
-            params = ["amplitude", "center", "g_sigma", "l_sigma", "fraction"]
-        else:
-            raise ValueError("Unknown fit function")
-
-        n = len(params)
-        fitparams = dict(
-            param=params, value=[None] * n, vary=[True] * n, min=[None] * n, max=[None] * n
-        )
-
-        if function == "linear":
-            fitparams["value"] = [0, 1]
-            fitparams["vary"] = [False, True]
-            fitparams["min"] = [None, 0]
-
-        elif function == "gaussian":
-            fitparams["min"] = [0, None, None]
-
-        return fitparams
-
-    fitparams_table_source = ColumnDataSource(dict(param=[], value=[], vary=[], min=[], max=[]))
-    fitparams_table = DataTable(
-        source=fitparams_table_source,
-        columns=[
-            TableColumn(field="param", title="Parameter", editor=CellEditor()),
-            TableColumn(field="value", title="Value", editor=NumberEditor()),
-            TableColumn(field="vary", title="Vary", editor=CheckboxEditor()),
-            TableColumn(field="min", title="Min", editor=NumberEditor()),
-            TableColumn(field="max", title="Max", editor=NumberEditor()),
-        ],
-        height=200,
-        width=350,
-        index_position=None,
-        editable=True,
-        auto_edit=True,
-    )
-
-    # start with `background` and `gauss` fit functions added
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="linear"))
-    fitparams_add_dropdown_callback(types.SimpleNamespace(item="gaussian"))
-    fitparams_select.value = ["gaussian-1"]  # add selection to gauss
-
-    fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in dataset:
+        app_fitctrl.fit_dataset(dataset)
-            if scan["export"]:
-                pyzebra.fit_scan(
-                    scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
-                )
-                pyzebra.get_area(
-                    scan,
-                    area_method=AREA_METHODS[area_method_radiobutton.active],
-                    lorentz=lorentz_checkbox.active,
-                )
 
         _update_single_scan_plot()
         _update_overview()
@@ -708,15 +586,7 @@ def create():
     proc_all_button.on_click(proc_all_button_callback)
 
     def proc_button_callback():
-        scan = _get_selected_scan()
+        app_fitctrl.fit_scan(_get_selected_scan())
-        pyzebra.fit_scan(
-            scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
-        )
-        pyzebra.get_area(
-            scan,
-            area_method=AREA_METHODS[area_method_radiobutton.active],
-            lorentz=lorentz_checkbox.active,
-        )
 
         _update_single_scan_plot()
         _update_overview()
@@ -732,11 +602,6 @@ def create():
     proc_button = Button(label="Process Current", width=145)
     proc_button.on_click(proc_button_callback)
 
-    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
-    area_method_radiobutton = RadioGroup(labels=["Function", "Area"], active=0, width=145)
-
-    lorentz_checkbox = CheckboxGroup(labels=["Lorentz Correction"], width=145, margin=(13, 5, 5, 5))
-
     export_preview_textinput = TextAreaInput(title="Export file preview:", width=450, height=400)
 
     def _update_preview():
@@ -769,12 +634,22 @@ def create():
     save_button = Button(label="Download File", button_type="success", width=220)
     save_button.js_on_click(CustomJS(args={"js_data": js_data}, code=javaScript))
 
+    area_method_div = Div(text="Intensity:", margin=(5, 5, 0, 5))
     fitpeak_controls = row(
-        column(fitparams_add_dropdown, fitparams_select, fitparams_remove_button),
+        column(
-        fitparams_table,
+            app_fitctrl.add_function_button,
+            app_fitctrl.function_select,
+            app_fitctrl.remove_function_button,
+        ),
+        app_fitctrl.params_table,
         Spacer(width=20),
-        column(fit_from_spinner, lorentz_checkbox, area_method_div, area_method_radiobutton),
+        column(
-        column(fit_to_spinner, proc_button, proc_all_button),
+            app_fitctrl.from_spinner,
+            app_fitctrl.lorentz_checkbox,
+            area_method_div,
+            app_fitctrl.area_method_radiogroup,
+        ),
+        column(app_fitctrl.to_spinner, proc_button, proc_all_button),
     )
 
     scan_layout = column(
@@ -796,7 +671,7 @@ def create():
 
     tab_layout = column(
         row(import_layout, scan_layout, plots, Spacer(width=30), export_layout),
-        row(fitpeak_controls, fit_output_textinput),
+        row(fitpeak_controls, app_fitctrl.result_textarea),
     )
 
     return Panel(child=tab_layout, title="param study")