Drop peakfinding step

The initial guesses via lmfit seems to work just fine

pyzebra/__init__.py

@@ -1,5 +1,4 @@
 from pyzebra.anatric import *
-from pyzebra.ccl_findpeaks import ccl_findpeaks
 from pyzebra.ccl_io import export_1D, load_1D, parse_1D
 from pyzebra.fit2 import fitccl
 from pyzebra.h5 import *

pyzebra/app/panel_ccl_integrate.py

@@ -8,7 +8,6 @@ from copy import deepcopy
 import numpy as np
 from bokeh.layouts import column, row
 from bokeh.models import (
-    Asterisk,
     BasicTicker,
     Button,
     CheckboxEditor,
@@ -68,7 +67,6 @@ PROPOSAL_PATH = "/afs/psi.ch/project/sinqdata/2020/zebra/"
 def create():
     det_data = {}
     fit_params = {}
-    peak_pos_textinput_lock = False
     js_data = {
         ".comm": ColumnDataSource(data=dict(cont=[], ext=[])),
         ".incomm": ColumnDataSource(data=dict(cont=[], ext=[])),
@@ -91,11 +89,7 @@ def create():
         hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in det_data]
         export = [s.get("active", True) for s in det_data]
         scan_table_source.data.update(
-            scan=scan_list,
+            scan=scan_list, hkl=hkl, fit=[0] * len(scan_list), export=export,
-            hkl=hkl,
-            peaks=[0] * len(scan_list),
-            fit=[0] * len(scan_list),
-            export=export,
         )
         scan_table_source.selected.indices = []
         scan_table_source.selected.indices = [0]
@@ -178,14 +172,10 @@ def create():
     monitor_spinner.on_change("value", monitor_spinner_callback)
 
     def _update_table():
-        num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data]
         fit_ok = [(1 if "fit" in scan else 0) for scan in det_data]
-        scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
+        scan_table_source.data.update(fit=fit_ok)
 
     def _update_plot(scan):
-        nonlocal peak_pos_textinput_lock
-        peak_pos_textinput_lock = True
-
         scan_motor = scan["scan_motor"]
 
         y = scan["Counts"]
@@ -194,23 +184,6 @@ def create():
         plot.axis[0].axis_label = scan_motor
         plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
 
-        num_of_peaks = len(scan.get("peak_indexes", []))
-        if num_of_peaks is not None and num_of_peaks > 0:
-            peak_indexes = scan["peak_indexes"]
-            if len(peak_indexes) == 1:
-                peak_pos_textinput.value = str(scan[scan_motor][peak_indexes[0]])
-            else:
-                peak_pos_textinput.value = str([scan[scan_motor][ind] for ind in peak_indexes])
-
-            plot_peak_source.data.update(x=scan[scan_motor][peak_indexes], y=scan["peak_heights"])
-            plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"])
-        else:
-            peak_pos_textinput.value = None
-            plot_peak_source.data.update(x=[], y=[])
-            plot_line_smooth_source.data.update(x=[], y=[])
-
-        peak_pos_textinput_lock = False
-
         fit = scan.get("fit")
         if fit is not None:
             comps = fit.eval_components()
@@ -249,20 +222,12 @@ def create():
     plot.add_glyph(plot_scatter_source, Scatter(x="x", y="y", line_color="steelblue"))
     plot.add_layout(Whisker(source=plot_scatter_source, base="x", upper="y_upper", lower="y_lower"))
 
-    plot_line_smooth_source = ColumnDataSource(dict(x=[0], y=[0]))
-    plot.add_glyph(
-        plot_line_smooth_source, Line(x="x", y="y", line_color="steelblue", line_dash="dashed")
-    )
-
     plot_gauss_source = ColumnDataSource(dict(x=[0], y=[0]))
     plot.add_glyph(plot_gauss_source, Line(x="x", y="y", line_color="red", line_dash="dashed"))
 
     plot_bkg_source = ColumnDataSource(dict(x=[0], y=[0]))
     plot.add_glyph(plot_bkg_source, Line(x="x", y="y", line_color="green", line_dash="dashed"))
 
-    plot_peak_source = ColumnDataSource(dict(x=[], y=[]))
-    plot.add_glyph(plot_peak_source, Asterisk(x="x", y="y", size=10, line_color="red"))
-
     numfit_min_span = Span(location=None, dimension="height", line_dash="dashed")
     plot.add_layout(numfit_min_span)
 
@@ -290,17 +255,16 @@ def create():
 
         _update_plot(det_data[new[0]])
 
-    scan_table_source = ColumnDataSource(dict(scan=[], hkl=[], peaks=[], fit=[], export=[]))
+    scan_table_source = ColumnDataSource(dict(scan=[], hkl=[], fit=[], export=[]))
     scan_table = DataTable(
         source=scan_table_source,
         columns=[
             TableColumn(field="scan", title="Scan", width=50),
             TableColumn(field="hkl", title="hkl", width=100),
-            TableColumn(field="peaks", title="Peaks", width=50),
             TableColumn(field="fit", title="Fit", width=50),
             TableColumn(field="export", title="Export", editor=CheckboxEditor(), width=50),
         ],
-        width=360,  # +60 because of the index column
+        width=310,  # +60 because of the index column
         fit_columns=False,
         editable=True,
     )
@@ -327,27 +291,6 @@ def create():
     merge_button = Button(label="Merge scans", width=145)
     merge_button.on_click(merge_button_callback)
 
-    def peak_pos_textinput_callback(_attr, _old, new):
-        if new is not None and not peak_pos_textinput_lock:
-            scan = _get_selected_scan()
-
-            peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
-            scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
-            scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
-            _update_table()
-            _update_plot(scan)
-
-    peak_pos_textinput = TextInput(title="Peak position:", default_size=145)
-    peak_pos_textinput.on_change("value", peak_pos_textinput_callback)
-
-    peak_int_ratio_spinner = Spinner(
-        title="Peak intensity ratio:", value=0.8, step=0.01, low=0, high=1, default_size=145
-    )
-    peak_prominence_spinner = Spinner(title="Peak prominence:", value=50, low=0, default_size=145)
-    smooth_toggle = Toggle(label="Smooth curve", default_size=145)
-    window_size_spinner = Spinner(title="Window size:", value=7, step=2, low=1, default_size=145)
-    poly_order_spinner = Spinner(title="Poly order:", value=3, low=0, default_size=145)
-
     integ_from = Spinner(title="Integrate from:", default_size=145, disabled=True)
     integ_to = Spinner(title="to:", default_size=145, disabled=True)
 
@@ -456,36 +399,6 @@ def create():
 
     fit_output_textinput = TextAreaInput(title="Fit results:", width=450, height=200)
 
-    def _get_peakfind_params():
-        return dict(
-            int_threshold=peak_int_ratio_spinner.value,
-            prominence=peak_prominence_spinner.value,
-            smooth=smooth_toggle.active,
-            window_size=window_size_spinner.value,
-            poly_order=poly_order_spinner.value,
-        )
-
-    def peakfind_all_button_callback():
-        peakfind_params = _get_peakfind_params()
-        for scan in det_data:
-            pyzebra.ccl_findpeaks(scan, **peakfind_params)
-
-        _update_table()
-        _update_plot(_get_selected_scan())
-
-    peakfind_all_button = Button(label="Peak Find All", button_type="primary", default_size=145)
-    peakfind_all_button.on_click(peakfind_all_button_callback)
-
-    def peakfind_button_callback():
-        scan = _get_selected_scan()
-        pyzebra.ccl_findpeaks(scan, **_get_peakfind_params())
-
-        _update_table()
-        _update_plot(scan)
-
-    peakfind_button = Button(label="Peak Find Current", default_size=145)
-    peakfind_button.on_click(peakfind_button_callback)
-
     def fit_all_button_callback():
         for scan in det_data:
             pyzebra.fit_scan(scan, fit_params)
@@ -581,13 +494,6 @@ def create():
     save_button.js_on_click(CustomJS(args={"js_data": js_data[".comm"]}, code=javaScript))
     save_button.js_on_click(CustomJS(args={"js_data": js_data[".incomm"]}, code=javaScript))
 
-    findpeak_controls = column(
-        row(peak_pos_textinput, column(Spacer(height=19), smooth_toggle)),
-        row(peak_int_ratio_spinner, peak_prominence_spinner),
-        row(window_size_spinner, poly_order_spinner),
-        row(peakfind_button, peakfind_all_button),
-    )
-
     fitpeak_controls = row(
         column(fitparams_add_dropdown, fitparams_select, fitparams_remove_button),
         fitparams_table,
@@ -623,7 +529,7 @@ def create():
             monitor_spinner,
         ),
         row(scan_layout, plot, Spacer(width=30), export_layout),
-        row(findpeak_controls, Spacer(width=30), fitpeak_controls, fit_output_textinput),
+        row(fitpeak_controls, fit_output_textinput),
     )
 
     return Panel(child=tab_layout, title="ccl integrate")

pyzebra/app/panel_param_study.py

@@ -9,7 +9,6 @@ from copy import deepcopy
 import numpy as np
 from bokeh.layouts import column, row
 from bokeh.models import (
-    Asterisk,
     BasicTicker,
     Button,
     CheckboxEditor,
@@ -77,7 +76,6 @@ def color_palette(n_colors):
 def create():
     det_data = []
     fit_params = {}
-    peak_pos_textinput_lock = False
     js_data = {
         ".comm": ColumnDataSource(data=dict(cont=[], ext=[])),
         ".incomm": ColumnDataSource(data=dict(cont=[], ext=[])),
@@ -106,7 +104,6 @@ def create():
             file=file_list,
             scan=scan_list,
             param=[""] * len(scan_list),
-            peaks=[0] * len(scan_list),
             fit=[0] * len(scan_list),
             export=[True] * len(scan_list),
         )
@@ -189,18 +186,14 @@ def create():
     monitor_spinner.on_change("value", monitor_spinner_callback)
 
     def _update_table():
-        num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data]
         fit_ok = [(1 if "fit" in scan else 0) for scan in det_data]
-        scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
+        scan_table_source.data.update(fit=fit_ok)
 
     def _update_plot():
         _update_single_scan_plot(_get_selected_scan())
         _update_overview()
 
     def _update_single_scan_plot(scan):
-        nonlocal peak_pos_textinput_lock
-        peak_pos_textinput_lock = True
-
         scan_motor = scan["scan_motor"]
 
         y = scan["Counts"]
@@ -209,23 +202,6 @@ def create():
         plot.axis[0].axis_label = scan_motor
         plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
 
-        num_of_peaks = len(scan.get("peak_indexes", []))
-        if num_of_peaks is not None and num_of_peaks > 0:
-            peak_indexes = scan["peak_indexes"]
-            if len(peak_indexes) == 1:
-                peak_pos_textinput.value = str(x[peak_indexes[0]])
-            else:
-                peak_pos_textinput.value = str([x[ind] for ind in peak_indexes])
-
-            plot_peak_source.data.update(x=x[peak_indexes], y=scan["peak_heights"])
-            plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"])
-        else:
-            peak_pos_textinput.value = None
-            plot_peak_source.data.update(x=[], y=[])
-            plot_line_smooth_source.data.update(x=[], y=[])
-
-        peak_pos_textinput_lock = False
-
         fit = scan.get("fit")
         if fit is not None:
             comps = fit.eval_components()
@@ -290,11 +266,6 @@ def create():
     plot.add_glyph(plot_scatter_source, Scatter(x="x", y="y", line_color="steelblue"))
     plot.add_layout(Whisker(source=plot_scatter_source, base="x", upper="y_upper", lower="y_lower"))
 
-    plot_line_smooth_source = ColumnDataSource(dict(x=[0], y=[0]))
-    plot.add_glyph(
-        plot_line_smooth_source, Line(x="x", y="y", line_color="steelblue", line_dash="dashed"),
-    )
-
     plot_gauss_source = ColumnDataSource(dict(x=[0], y=[0]))
     plot.add_glyph(
         plot_gauss_source, Line(x="x", y="y", line_color="red", line_dash="dashed"),
@@ -305,9 +276,6 @@ def create():
         plot_bkg_source, Line(x="x", y="y", line_color="green", line_dash="dashed"),
     )
 
-    plot_peak_source = ColumnDataSource(dict(x=[], y=[]))
-    plot.add_glyph(plot_peak_source, Asterisk(x="x", y="y", size=10, line_color="red"))
-
     numfit_min_span = Span(location=None, dimension="height", line_dash="dashed")
     plot.add_layout(numfit_min_span)
 
@@ -380,20 +348,17 @@ def create():
 
         _update_plot()
 
-    scan_table_source = ColumnDataSource(
+    scan_table_source = ColumnDataSource(dict(file=[], scan=[], param=[], fit=[], export=[]))
-        dict(file=[], scan=[], param=[], peaks=[], fit=[], export=[])
-    )
     scan_table = DataTable(
         source=scan_table_source,
         columns=[
             TableColumn(field="file", title="file", width=150),
             TableColumn(field="scan", title="scan", width=50),
             TableColumn(field="param", title="param", width=50),
-            TableColumn(field="peaks", title="Peaks", width=50),
             TableColumn(field="fit", title="Fit", width=50),
             TableColumn(field="export", title="Export", editor=CheckboxEditor(), width=50),
         ],
-        width=460,  # +60 because of the index column
+        width=410,  # +60 because of the index column
         editable=True,
         fit_columns=False,
     )
@@ -408,27 +373,6 @@ def create():
     def _get_selected_scan():
         return det_data[scan_table_source.selected.indices[0]]
 
-    def peak_pos_textinput_callback(_attr, _old, new):
-        if new is not None and not peak_pos_textinput_lock:
-            scan = _get_selected_scan()
-
-            peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
-            scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
-            scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
-            _update_table()
-            _update_plot()
-
-    peak_pos_textinput = TextInput(title="Peak position:", default_size=145)
-    peak_pos_textinput.on_change("value", peak_pos_textinput_callback)
-
-    peak_int_ratio_spinner = Spinner(
-        title="Peak intensity ratio:", value=0.8, step=0.01, low=0, high=1, default_size=145
-    )
-    peak_prominence_spinner = Spinner(title="Peak prominence:", value=50, low=0, default_size=145)
-    smooth_toggle = Toggle(label="Smooth curve", default_size=145)
-    window_size_spinner = Spinner(title="Window size:", value=7, step=2, low=1, default_size=145)
-    poly_order_spinner = Spinner(title="Poly order:", value=3, low=0, default_size=145)
-
     integ_from = Spinner(title="Integrate from:", default_size=145, disabled=True)
     integ_to = Spinner(title="to:", default_size=145, disabled=True)
 
@@ -537,36 +481,6 @@ def create():
 
     fit_output_textinput = TextAreaInput(title="Fit results:", width=450, height=200)
 
-    def _get_peakfind_params():
-        return dict(
-            int_threshold=peak_int_ratio_spinner.value,
-            prominence=peak_prominence_spinner.value,
-            smooth=smooth_toggle.active,
-            window_size=window_size_spinner.value,
-            poly_order=poly_order_spinner.value,
-        )
-
-    def peakfind_all_button_callback():
-        peakfind_params = _get_peakfind_params()
-        for scan in det_data:
-            pyzebra.ccl_findpeaks(scan, **peakfind_params)
-
-        _update_table()
-        _update_plot()
-
-    peakfind_all_button = Button(label="Peak Find All", button_type="primary", default_size=145)
-    peakfind_all_button.on_click(peakfind_all_button_callback)
-
-    def peakfind_button_callback():
-        scan = _get_selected_scan()
-        pyzebra.ccl_findpeaks(scan, **_get_peakfind_params())
-
-        _update_table()
-        _update_plot()
-
-    peakfind_button = Button(label="Peak Find Current", default_size=145)
-    peakfind_button.on_click(peakfind_button_callback)
-
     def fit_all_button_callback():
         for scan in det_data:
             pyzebra.fit_scan(scan, fit_params)
@@ -656,13 +570,6 @@ def create():
     save_button.js_on_click(CustomJS(args={"js_data": js_data[".comm"]}, code=javaScript))
     save_button.js_on_click(CustomJS(args={"js_data": js_data[".incomm"]}, code=javaScript))
 
-    findpeak_controls = column(
-        row(peak_pos_textinput, column(Spacer(height=19), smooth_toggle)),
-        row(peak_int_ratio_spinner, peak_prominence_spinner),
-        row(window_size_spinner, poly_order_spinner),
-        row(peakfind_button, peakfind_all_button),
-    )
-
     fitpeak_controls = row(
         column(fitparams_add_dropdown, fitparams_select, fitparams_remove_button),
         fitparams_table,
@@ -688,7 +595,7 @@ def create():
             monitor_spinner,
         ),
         row(scan_table, plots, Spacer(width=30), export_layout),
-        row(findpeak_controls, Spacer(width=30), fitpeak_controls, fit_output_textinput),
+        row(fitpeak_controls, fit_output_textinput),
     )
 
     return Panel(child=tab_layout, title="param study")

pyzebra/ccl_findpeaks.py

@@ -1,75 +0,0 @@
-import numpy as np
-import scipy as sc
-from scipy.interpolate import interp1d
-from scipy.signal import savgol_filter
-
-
-def ccl_findpeaks(
-    scan,
-    int_threshold=0.8,
-    prominence=50,
-    smooth=False,
-    window_size=7,
-    poly_order=3,
-    variable="omega",
-):
-
-    """function iterates through the dictionary created by load_cclv2 and locates peaks for each scan
-    args:   scan - a single scan,
-
-            int_threshold - fraction of threshold_intensity/max_intensity, must be positive num between 0 and 1
-                        i.e. will only detect peaks above 75% of max intensity
-
-            prominence - defines a drop of values that must be between two peaks, must be positive number
-                        i.e. if promimence is 20, it will detect two neigbouring peaks of 300 and 310 intesities,
-                        if none of the itermediate values are lower that 290
-
-            smooth  - if true, smooths data by savitzky golay filter, if false - no smoothing
-
-            window_size - window size for savgol filter, must be odd positive integer
-
-            poly_order =  order of the polynomial used in savgol filter, must be positive integer smaller than
-    """
-    if not 0 <= int_threshold <= 1:
-        int_threshold = 0.8
-        print(
-            "Invalid value for int_threshold, select value between 0 and 1, new value set to:",
-            int_threshold,
-        )
-
-    if not isinstance(window_size, int) or (window_size % 2) == 0 or window_size <= 1:
-        window_size = 7
-        print(
-            "Invalid value for window_size, select positive odd integer, new value set to!:",
-            window_size,
-        )
-
-    if not isinstance(poly_order, int) or window_size < poly_order:
-        poly_order = 3
-        print(
-            "Invalid value for poly_order, select positive integer smaller than window_size, new value set to:",
-            poly_order,
-        )
-
-    if not isinstance(prominence, (int, float)) and prominence < 0:
-        prominence = 50
-        print("Invalid value for prominence, select positive number, new value set to:", prominence)
-
-    omega = scan[variable]
-    counts = np.array(scan["Counts"])
-    if smooth:
-        itp = interp1d(omega, counts, kind="linear")
-        absintensity = [abs(number) for number in counts]
-        lowest_intensity = min(absintensity)
-        counts[counts < 0] = lowest_intensity
-        smooth_peaks = savgol_filter(itp(omega), window_size, poly_order)
-
-    else:
-        smooth_peaks = counts
-
-    peaks, properties = sc.signal.find_peaks(
-        smooth_peaks, height=int_threshold * max(smooth_peaks), prominence=prominence
-    )
-    scan["peak_indexes"] = peaks
-    scan["peak_heights"] = properties["peak_heights"]
-    scan["smooth_peaks"] = smooth_peaks  # smoothed curve