more fixes

fastplotlib · kushalkolar · Sep 9, 2026 · Aug 8, 2026 · Aug 8, 2026 · Aug 13, 2026
commit b57d0a4bc6aa732f3eb25de2611c2bb9cb07f845
@@ -44,10 +44,7 @@
     line_selector_text,
     offset=(0., 1.75, 0.),
     anchor="middle-left",
-    font_size=32,
-    face_color=line.colors[0],
-    outline_color="w",
-    outline_thickness=0.1,
+    font_size=24,
 )
 
 
@@ -65,18 +62,15 @@ def line_selector_changed(ev):
          f"y value: {line.data[index, 1]:.2f}\n"
          f"index: {index}")
 
-    # set text color based on line color at selection index
-    line_selection_label.face_color = line.colors[index]
-
 
 # line stack, sine and cosine wave
-line_stack = figure[0, 1].add_line_stack([sine, cosine], colors=["magenta", "cyan"], separation=1)
+line_stack = figure[0, 1].add_line_stack([sine, cosine], colors=["magenta", "cyan"], separation=(0, 1, 0))
 line_stack_selector = line_stack.add_linear_selector()
 
 line_stack_selector_text = (f"x value: {line_stack_selector.selection / np.pi:.2f}π\n"
                             f"index: {line_selector.get_selected_index()}\n"
-                            f"sine y value: {line_stack[0].data[0, 1]:.2f}\n"
-                            f"cosine y value: {line_stack[1].data[0, 1]:.2f}\n")
+                            f"sine y value: {line_stack.data[0, 0, 1]:.2f}\n"
+                            f"cosine y value: {line_stack.data[1, 0, 1]:.2f}\n")
 
 # a label that will change to display line_stack data based on the linear selector
 line_stack_selector_label = figure[0, 1].add_text(
@@ -99,8 +93,8 @@ def line_stack_selector_changed(ev):
     line_stack_selector_label.text = \
         (f"x value: {selection / np.pi:.2f}π\n"
          f"index: {index}\n"
-         f"sine y value: {line_stack[0].data[index, 1]:.2f}\n"
-         f"cosine y value: {line_stack[1].data[index, 1]:.2f}\n")
+         f"sine y value: {line_stack.data[0, index, 1]:.2f}\n"
+         f"cosine y value: {line_stack.data[1, index, 1]:.2f}\n")
 
 
 # add an event handler, you can also use a decorator

@@ -33,8 +33,10 @@ def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
 
 pos_xy = np.vstack(circles)
 
+colors = np.random.rand(len(circles), 3)
+
 # add image
-line_collection = figure[0, 0].add_line_collection(circles, cmap="jet", thickness=5)
+line_collection = figure[0, 0].add_line_collection(circles, colors=colors, thickness=5)
 
 # add polygon selector to image graphic
 polygon_selector = line_collection.add_polygon_selector(
@@ -45,11 +47,12 @@ def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
 # add event handler to highlight selected indices
 @polygon_selector.add_event_handler("selection")
 def color_indices(ev):
-    line_collection.cmap = "jet"
+    line_collection.colors = colors
     ixs = ev.get_selected_indices()
     # iterate through each of the selected indices, if the array size > 0 that mean it's under the selection
     selected_line_ixs = [i for i in range(len(ixs)) if ixs[i].size > 0]
-    line_collection[selected_line_ixs].colors = "w"
+    # boolean indexing of a collection property
+    line_collection.colors[selected_line_ixs] = "w"
 
 
 # # manually move selector to make a nice gallery image :D

@@ -253,6 +253,11 @@ def __setitem__(self, key, value):
         # multiple graphics: they must all be the same mode, then split `value` along the
         # graphic axis and hand each graphic its piece
         selected = self._graphics[graphic_key]
+
+        if len(selected < 1):
+            # nothing to set
+            return
+
         self._verify_homogenous_buffer_type(selected)
         for graphic, graphic_value in zip(
             selected, self._broadcast_over_graphics(value, len(selected))

@@ -281,14 +281,14 @@ def __init__(self, data: Any, property_name: str = "data"):
     def _fix_data(self, data):
         if data.ndim == 1:
             # if user provides a 1D array, assume these are y-values
-            data = np.column_stack([np.arange(data.size, dtype=data.dtype), data])
+            data = np.column_stack([np.arange(data.size, dtype=np.float32), data])
 
         if data.shape[1] != 3:
             if data.shape[1] != 2:
                 raise ValueError(f"Must pass 1D, 2D or 3D data")
 
             # zeros for z
-            zs = np.zeros(data.shape[0], dtype=data.dtype)
+            zs = np.zeros(data.shape[0], dtype=np.float32)
 
             # column stack [x, y, z] to make data of shape [n_points, 3]
             data = np.column_stack([data[:, 0], data[:, 1], zs])