Speedup of the GUI

* annotation routine optimized
* reduced constrained_layout calls

prasopes/__main__.py

@@ -377,6 +377,8 @@ def main():
     main_window.setAcceptDrops(True)
     main_window.keyPressEvent = lambda event: key_pressed(
             event, augCanvas, config)
+    main_window.resizeEvent = lambda event: augCanvas.constrained_draw()
+    update.signal.connect(lambda: augCanvas.constrained_draw())
 
     main_window.addToolBar(QtCore.Qt.TopToolBarArea, toolBar)
     main_window.addDockWidget(QtCore.Qt.LeftDockWidgetArea, treedock)

prasopes/graphtools.py

@@ -54,6 +54,11 @@ class AugFigureCanvas(FigureCanvas):
                 self.chromplot, lambda x_min, x_max: pick_times(
                     x_min, x_max, self), 'horizontal', useblit=True,
                 rectprops=dict(alpha=0.15, facecolor='purple'), button=3)
+        self.figure.set_constrained_layout(False)
+
+    def constrained_draw(self):
+        self.figure.execute_constrained_layout()
+        self.draw()
 
 
 class AugSpanSelector(SpanSelector):
@@ -118,6 +123,16 @@ class AugSpanSelector(SpanSelector):
         ann_spec(self.ax, self.data)
 
 
+class FixedScalarFormatter(matplotlib.ticker.ScalarFormatter):
+    def __init__(self):
+        super().__init__()
+        self._powerlimits = (0,0)
+
+    def _set_format(self):
+        """_set_format override"""
+        self.format = "%.2f"
+
+
 def zoom_factory(axis, base_scale, plot_data=None):
     """returns zooming functionality to axis"""
     def zoom_fun(event, pd, ax, scale):
@@ -187,7 +202,6 @@ def pan_factory(axis, plot=None):
                     action, id_drag, id_release, pd, ax))
 
     def drag_fun(event, ax):
-        ax.figure.set_constrained_layout(False)
         ax.drag_pan(1, 'x', event.x, event.y)
         ax.figure.canvas.draw()
 
@@ -198,7 +212,6 @@ def pan_factory(axis, plot=None):
             if type(pd) is dict and "annotation" in pd:
                 ann_spec(ax, pd)
             ax.figure.canvas.draw()
-            ax.figure.set_constrained_layout(True)
 
     fig = axis.get_figure()
     fig.canvas.mpl_connect('button_press_event',
@@ -341,20 +354,18 @@ def ann_spec(ms_spec, msdata, ann_limit=0.01):
     """annotate spectrum
 
     First define the array, in which the annotation should occur.
-    Then remove values which are invalid as local maximas. Then select
-    local maximas from the array by forcycling. Local maximas are then
+    Then remove values which are invalid as local maximas. Local maximas are then
     reduced to a representation of the important ones by the sub_peaks
     function"""
 
     def sub_peaks(peakz, hardpeaks, xrange, yrange, coef_x=10, coef_y=10):
         """Returns reasonable subselection of local maximas"""
-        hardxy = np.array(([i.xy for i in hardpeaks]), dtype=[
-                ('x', float), ('y', float)])
-        sort_peaks = np.flipud(np.sort(np.array(peakz, dtype=[
-            ('x', float), ('y', float)]), order='y')).copy()
+        hardxy = np.array([i.xy for i in hardpeaks], dtype=[
+            ('x', np.float32), ('y', np.float32)])
+        sort_peaks = np.flipud(np.sort(np.array(peakz))).copy()
         red_x = xrange / coef_x
         red_y = yrange / coef_y
-        big_peaks = np.array([], dtype=[('x', float), ('y', float)])
+        big_peaks = np.array([], dtype=[('x', np.float32), ('y', np.float32)])
         for peak in np.nditer(sort_peaks, flags=["zerosize_ok"]):
             if not (np.any((abs(peak['y'] - big_peaks['y']) < red_y)
                            & (abs(peak['x'] - big_peaks['x']) < red_x)) or
@@ -366,14 +377,19 @@ def ann_spec(ms_spec, msdata, ann_limit=0.01):
     peaks = []
     for line in ms_spec.lines:
         xdata, ydata = line.get_data()
-        argvis = dt.argsubselect(xdata, *ms_spec.get_xlim())
-        # remove tails which cannot be evaluated as maximas
-        argvis = argvis[np.where((argvis != 0)
-                                 & (argvis != (len(xdata)-1)))]
-        lim = ms_spec.get_ylim()[1] * ann_limit
-        for i in argvis:
-            if ydata[i] > lim and ydata[i] > max(ydata[i-1], ydata[i+1]):
-                peaks.append((xdata[i], ydata[i]))
+        # Thanks to:
+        # https://gist.github.com/ben741/d8c70b608d96d9f7ed231086b237ba6b
+        minlim = ms_spec.get_ylim()[1] * ann_limit
+        lims = [*ms_spec.get_xlim(),*ms_spec.get_ylim()]
+        maxargs = np.where((xdata[1:-1] > lims[0]) & (xdata[1:-1] < lims[1]) &
+                           (ydata[1:-1] > minlim) & (ydata[1:-1] < lims[3]) &
+                           (ydata[1:-1] > ydata[0:-2]) &
+                           (ydata[1:-1] > ydata[2:]))[0] + 1
+        peakline = np.empty([len(maxargs)], dtype=[('x', np.float32), ('y', np.float32)])
+        peakline['x'], peakline['y'] = xdata[maxargs], ydata[maxargs]
+        peaks.append(peakline)
+    peaks = np.concatenate(peaks)
+
     s_peaks = sub_peaks(peaks, msdata['texts'],
                         np.diff(ms_spec.get_xlim()),
                         np.diff(ms_spec.get_ylim()))
@@ -384,11 +400,10 @@ def ann_spec(ms_spec, msdata, ann_limit=0.01):
     # remove them from tracking
     msdata['annotation'].clear()
 
+    dispints = cf.settings().value("view/intensities", type=bool)
     for peak in s_peaks:
-        if cf.settings().value("view/intensities", type=bool):
-            annotation = '{0:.2f}\n{1: .2e}'.format(peak['x'], peak['y'])
-        else:
-            annotation = '{0:.2f}'.format(peak['x'])
+        annotation = '{0:.2f}\n{1: .2e}'.format(peak[0], peak[1])\
+                if dispints else '{0:.2f}'.format(peak[0])
         peaktext = ms_spec.annotate(
             annotation, xy=(peak['x'], peak['y']), textcoords='data',
             picker=True, in_layout=False)
@@ -404,7 +419,7 @@ def pop_plot(xdata, ydata, plot, plot_data, colornum=0, legend=None):
     plot.set_ylabel(plot_data['ylabel'])
     plot.set_ylim(plot.get_ylim()[1] * -0.01,
                   plot.get_ylim()[1] * 1.1)
-    plot.ticklabel_format(scilimits=(0, 0), axis='y')
+    plot.yaxis.set_major_formatter(FixedScalarFormatter())
     # put hardcoded annotation if there is some
     if "texts" in plot_data and not any(
             data in plot.get_children() for data in plot_data['texts']):
@@ -506,7 +521,7 @@ def populate(augCanvas):
             ax.get_legend().set_in_layout(False)
         ax.autoscale(True)
         ax.set_ylim(ax.get_ylim()[1]*-0.01, ax.get_ylim()[1]*1.1)
-        augCanvas.draw()
+    augCanvas.constrained_draw()
     return