fix: crosshair snaps to correct coordinates also with logx and logy

bec_widgets/qt_utils/crosshair.py

@@ -13,6 +13,8 @@ class Crosshair(QObject):
 
     def __init__(self, plot_item, precision=None, parent=None):
         super().__init__(parent)
+        self.is_log_y = None
+        self.is_log_x = None
         self.plot_item = plot_item
         self.precision = precision
         self.v_line = pg.InfiniteLine(angle=90, movable=False)
@@ -62,9 +64,6 @@ class Crosshair(QObject):
             for x_data, y_data in data:
                 closest_x, closest_y = self.closest_x_y_value(x, x_data, y_data)
                 y_values.append(closest_y)
-            if self.precision is not None:
-                x = round(x, self.precision)
-                y_values = [round(y_val, self.precision) for y_val in y_values]
             return x, y_values
         elif isinstance(data[0], np.ndarray):  # 2D plot
             x_idx = int(np.clip(x, 0, data[0].shape[0] - 1))
@@ -89,27 +88,54 @@ class Crosshair(QObject):
         return list_x[i], list_y[i]
 
     def mouse_moved(self, event):
+        self.check_log()
         pos = event[0]
         if self.plot_item.vb.sceneBoundingRect().contains(pos):
             mouse_point = self.plot_item.vb.mapSceneToView(pos)
-            x, y_values = self.snap_to_data(mouse_point.x(), mouse_point.y())
+            x, y = mouse_point.x(), mouse_point.y()
+            if self.is_log_x:
+                x = 10**x
+            if self.is_log_y:
+                y = 10**y
+            x, y_values = self.snap_to_data(x, y)
             self.v_line.setPos(mouse_point.x())
             self.h_line.setPos(mouse_point.y())
             if isinstance(y_values, list):  # 1D plot
-                self.coordinatesChanged1D.emit(x, y_values)
+                self.coordinatesChanged1D.emit(
+                    round(x, self.precision), [round(y_val, self.precision) for y_val in y_values]
+                )
                 for i, y_val in enumerate(y_values):
-                    self.marker_moved_1d[i].setData([x], [y_val])
+                    self.marker_moved_1d[i].setData(
+                        [x if not self.is_log_x else np.log10(x)],
+                        [y_val if not self.is_log_y else np.log10(y_val)],
+                    )
             else:  # 2D plot
                 self.coordinatesChanged2D.emit(x, y_values)
 
     def mouse_clicked(self, event):
+        self.check_log()
         if self.plot_item.vb.sceneBoundingRect().contains(event._scenePos):
             mouse_point = self.plot_item.vb.mapSceneToView(event._scenePos)
-            x, y_values = self.snap_to_data(mouse_point.x(), mouse_point.y())
+            x, y = mouse_point.x(), mouse_point.y()
+            if self.is_log_x:
+                x = 10**x
+            if self.is_log_y:
+                y = 10**y
+            x, y_values = self.snap_to_data(x, y)
             if isinstance(y_values, list):  # 1D plot
-                self.coordinatesClicked1D.emit(x, y_values)
+                self.coordinatesClicked1D.emit(
+                    round(x, self.precision), [round(y_val, self.precision) for y_val in y_values]
+                )
                 for i, y_val in enumerate(y_values):
-                    self.marker_clicked_1d[i].setData([x], [y_val])
+                    self.marker_clicked_1d[i].setData(
+                        [x if not self.is_log_x else np.log10(x)],
+                        [y_val if not self.is_log_y else np.log10(y_val)],
+                    )
             else:  # 2D plot
                 self.coordinatesClicked2D.emit(x, y_values)
                 self.marker_2d.setPos([x, y_values])
+
+    def check_log(self):
+        # Check if plot uses log scale
+        self.is_log_x = self.plot_item.ctrl.logXCheck.isChecked()
+        self.is_log_y = self.plot_item.ctrl.logYCheck.isChecked()

bec_widgets/qt_utils/utils_example.py

@@ -29,7 +29,7 @@ class ExampleApp(QWidget):
         # PlotWidget
         self.plot_widget_1d = pg.PlotWidget(title="1D PlotWidget with multiple curves")
         self.plot_item_1d = self.plot_widget_1d.getPlotItem()
-        self.plot_item_1d.setLogMode(True, False)
+        self.plot_item_1d.setLogMode(True, True)
 
         # 1D Datasets
         self.x_data = np.linspace(0, 10, 1000)
@@ -37,9 +37,6 @@ class ExampleApp(QWidget):
         def gauss(x, mu, sigma):
             return (1 / (sigma * np.sqrt(2 * np.pi))) * np.exp(-0.5 * ((x - mu) / sigma) ** 2)
 
-        mu = 1  # mean
-        sigma = 1  # standard deviation
-
         # same convention as in line_plot.py
         self.y_value_list = [
             np.sin(self.x_data),
@@ -47,8 +44,8 @@ class ExampleApp(QWidget):
             np.sin(2 * self.x_data),
         ]  # List of y-values for multiple curves
 
-        self.y_value_list = [gauss(self.x_data, mu, sigma)]
-        self.curve_names = ["Gauss"]  # ,"Sine", "Cosine", "Sine2x"]
+        self.y_value_list = [gauss(self.x_data, 1, 1), gauss(self.x_data, 1.5, 3)]
+        self.curve_names = ["Gauss(1,1)", "Gauss(1.5,3)"]  # ,"Sine", "Cosine", "Sine2x"]
 
         # Curves
         color_list = ["#384c6b", "#e28a2b", "#5E3023", "#e41a1c", "#984e83", "#4daf4a"]
@@ -66,7 +63,7 @@ class ExampleApp(QWidget):
         # 2D Plot
         ##########################
         self.plot_widget_2d = pg.PlotWidget(title="2D plot with crosshair and ROI square")
-        self.data_2D = np.random.random((100, 100))
+        self.data_2D = np.random.random((100, 200))
         self.plot_item_2d = self.plot_widget_2d.getPlotItem()
         self.image_item = pg.ImageItem(self.data_2D)
         self.plot_item_2d.addItem(self.image_item)
@@ -83,7 +80,7 @@ class ExampleApp(QWidget):
         # Signals & Cross-hairs
         ##########################
         # 1D
-        self.crosshair_1d = Crosshair(self.plot_item_1d, precision=2)
+        self.crosshair_1d = Crosshair(self.plot_item_1d, precision=4)
         self.crosshair_1d.coordinatesChanged1D.connect(
             lambda x, y: self.update_table(self.table, x, y, column=0)
         )