Set matplotlib axis scale type earlier so axis limits are correct

When the axis scale is changed to "log", matplotlib changes the default
axis limits from (0, 1) to something around (0.1, 10). Since MplDrawer
got the limits and the set them back on the axes after setting the
scale, it was reapplying a minimum of 0 to the log scale plot, leading
to a user warning. matplotlib by default changes the limits to the range
of the data when data is added, so this case only came up when
generating a figure with no data.

Author: wshanks

qiskit_experiments/visualization/drawers/mpl_drawer.py

@@ -147,6 +147,31 @@ def format_canvas(self):
         else:
             all_axes = [self._axis]
 
+        # Set axes scale. This needs to be done before anything tries work with
+        # the axis limits because if no limits or data are set explicitly the
+        # default limits depend on the scale method (for example, the minimum
+        # value is 0 for linear scaling but not for log scaling).
+        def signed_sqrt(x):
+            return np.sign(x) * np.sqrt(abs(x))
+
+        def signed_square(x):
+            return np.sign(x) * x**2
+
+        for ax_type in ("x", "y"):
+            for sub_ax in all_axes:
+                scale = self.figure_options.get(f"{ax_type}scale")
+                if ax_type == "x":
+                    mpl_setscale = sub_ax.set_xscale
+                else:
+                    mpl_setscale = sub_ax.set_yscale
+
+                # Apply non linear axis spacing
+                if scale is not None:
+                    if scale == "quadratic":
+                        mpl_setscale("function", functions=(signed_square, signed_sqrt))
+                    else:
+                        mpl_setscale(scale)
+
         # Get axis formatter from drawing options
         formatter_opts = {}
         for ax_type in ("x", "y"):
@@ -181,12 +206,6 @@ def format_canvas(self):
                 "max_ax_vals": max_vals,
             }
 
-        def signed_sqrt(x):
-            return np.sign(x) * np.sqrt(abs(x))
-
-        def signed_square(x):
-            return np.sign(x) * x**2
-
         for i, sub_ax in enumerate(all_axes):
             # Add data labels if there are multiple labels registered per sub_ax.
             _, labels = sub_ax.get_legend_handles_labels()
@@ -197,18 +216,15 @@ def signed_square(x):
                 limit = formatter_opts[ax_type]["limit"][i]
                 unit = formatter_opts[ax_type]["unit"][i]
                 unit_scale = formatter_opts[ax_type]["unit_scale"][i]
-                scale = self.figure_options.get(f"{ax_type}scale")
                 min_ax_vals = formatter_opts[ax_type]["min_ax_vals"]
                 max_ax_vals = formatter_opts[ax_type]["max_ax_vals"]
                 share_axis = self.figure_options.get(f"share{ax_type}")
 
                 if ax_type == "x":
-                    mpl_setscale = sub_ax.set_xscale
                     mpl_axis_obj = getattr(sub_ax, "xaxis")
                     mpl_setlimit = sub_ax.set_xlim
                     mpl_share = sub_ax.sharex
                 else:
-                    mpl_setscale = sub_ax.set_yscale
                     mpl_axis_obj = getattr(sub_ax, "yaxis")
                     mpl_setlimit = sub_ax.set_ylim
                     mpl_share = sub_ax.sharey
@@ -219,13 +235,6 @@ def signed_square(x):
                     else:
                         limit = min_ax_vals[i], max_ax_vals[i]
 
-                # Apply non linear axis spacing
-                if scale is not None:
-                    if scale == "quadratic":
-                        mpl_setscale("function", functions=(signed_square, signed_sqrt))
-                    else:
-                        mpl_setscale(scale)
-
                 # Create formatter for axis tick label notation
                 if unit and unit_scale:
                     # If value is specified, automatically scale axis magnitude

test/visualization/test_plotter_mpldrawer.py

@@ -104,7 +104,6 @@ def test_scale(self):
         plotter.set_figure_options(
             xscale="quadratic",
             yscale="log",
-            ylim=(0.1, 1.0),
         )
 
         plotter.figure()