Don't let margins expand polar plots to negative radii by default.

anntzer · anntzer · commit f0da0cf0d687 · 2019-04-19T00:45:24.000+02:00
This is implemented by altering the semantics of sticky edges as
documented in the changelog.  As it turns out, this change also improves
consistency for streamplot():

- in test_streamplot.py::test_{linewidth,mask_and_nans}, the change
  is necessary because the axes limits would now be (-3, 3) (matching
  the vector field limits), whereas they were previously
  xlim=(-3.0, 2.9999999999999947), ylim=(-3.0000000000000004, 2.9999999999999947)
  (they can be inspected with
  `plt.gcf().canvas.draw(); print(plt.gca().get_xlim(), plt.gca().get_ylim())`).

- in test_streamplot.py::test_maxlength, note that the previous version
  expanded the axes limits *beyond* (-3, 3), whereas the current doesn't
  do so anymore.  It doesn't actually make much sense if the vector
  field limits are applied if the streamplot goes all the way to the
  edges, but are ignored otherwise.
diff --git a/doc/api/next_api_changes/2019-04-17-AL.rst b/doc/api/next_api_changes/2019-04-17-AL.rst
@@ -0,0 +1,24 @@
+Change in the application of ``Artist.sticky_edges``
+````````````````````````````````````````````````````
+
+Previously, the ``sticky_edges`` attribute of artists was a list of values such
+that if an axis limit coincides with a sticky edge, it would not be expanded by
+the axes margins (this is the mechanism that e.g. prevents margins from being
+added around images).
+
+``sticky_edges`` now have an additional effect on margins application: even if
+an axis limit did not coincide with a sticky edge, it cannot *cross* a sticky
+edge through margin application -- instead, the margins will only expand the
+axis limit until it bumps against the sticky edge.
+
+This change improves the margins of axes displaying a `~Axes.streamplot`:
+
+- if the streamplot goes all the way to the edges of the vector field, then the
+  axis limits are set to match exactly the vector field limits (whereas they
+  would be sometimes be off by a small floating point error previously).
+- if the streamplot does not reach the edges of the vector field (e.g., due to
+  the use of ``start_points`` and ``maxlength``), then margins expansion will
+  not cross the the vector field limits anymore.
+
+This change is also used internally to ensure that polar plots don't display
+negative *r* values unless the user really passes in a negative value.
diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
@@ -2402,14 +2402,14 @@ def autoscale_view(self, tight=None, scalex=True, scaley=True):
                 (self._xmargin and scalex and self._autoscaleXon) or
                 (self._ymargin and scaley and self._autoscaleYon)):
             stickies = [artist.sticky_edges for artist in self.get_children()]
-            x_stickies = np.array([x for sticky in stickies for x in sticky.x])
-            y_stickies = np.array([y for sticky in stickies for y in sticky.y])
+            x_stickies = np.sort([x for sticky in stickies for x in sticky.x])
+            y_stickies = np.sort([y for sticky in stickies for y in sticky.y])
             if self.get_xscale().lower() == 'log':
                 x_stickies = x_stickies[x_stickies > 0]
             if self.get_yscale().lower() == 'log':
                 y_stickies = y_stickies[y_stickies > 0]
         else:  # Small optimization.
-            x_stickies, y_stickies = [], []
+            x_stickies = y_stickies = np.array([])
 
         def handle_single_axis(scale, autoscaleon, shared_axes, interval,
                                minpos, axis, margin, stickies, set_bound):
@@ -2450,29 +2450,33 @@ def handle_single_axis(scale, autoscaleon, shared_axes, interval,
             locator = axis.get_major_locator()
             x0, x1 = locator.nonsingular(x0, x1)
 
+            # Prevent margin addition from crossing a sticky value.  Small
+            # tolerances (whose value come from isclose()) must be used due to
+            # floating point issues with streamplot.
+            # Index of largest element < x0 + tol, if any.
+            i0 = stickies.searchsorted(x0 + 1e-5 * abs(x0) + 1e-8) - 1
+            x0bound = stickies[i0] if i0 != -1 else None
+            # Index of smallest element > x1 - tol, if any.
+            i1 = stickies.searchsorted(x1 - 1e-5 * abs(x1) - 1e-8)
+            x1bound = stickies[i1] if i1 != len(stickies) else None
+
             # Add the margin in figure space and then transform back, to handle
             # non-linear scales.
             minpos = getattr(bb, minpos)
             transform = axis.get_transform()
             inverse_trans = transform.inverted()
-            # We cannot use exact equality due to floating point issues e.g.
-            # with streamplot.
-            do_lower_margin = not np.any(np.isclose(x0, stickies))
-            do_upper_margin = not np.any(np.isclose(x1, stickies))
             x0, x1 = axis._scale.limit_range_for_scale(x0, x1, minpos)
             x0t, x1t = transform.transform([x0, x1])
-
-            if np.isfinite(x1t) and np.isfinite(x0t):
-                delta = (x1t - x0t) * margin
-            else:
-                # If at least one bound isn't finite, set margin to zero
-                delta = 0
-
-            if do_lower_margin:
-                x0t -= delta
-            if do_upper_margin:
-                x1t += delta
-            x0, x1 = inverse_trans.transform([x0t, x1t])
+            delta = (x1t - x0t) * margin
+            if not np.isfinite(delta):
+                delta = 0  # If a bound isn't finite, set margin to zero.
+            x0, x1 = inverse_trans.transform([x0t - delta, x1t + delta])
+
+            # Apply sticky bounds.
+            if x0bound is not None:
+                x0 = max(x0, x0bound)
+            if x1bound is not None:
+                x1 = min(x1, x1bound)
 
             if not self._tight:
                 x0, x1 = locator.view_limits(x0, x1)
diff --git a/lib/matplotlib/tests/baseline_images/test_streamplot/streamplot_maxlength.png b/lib/matplotlib/tests/baseline_images/test_streamplot/streamplot_maxlength.png
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -824,6 +824,12 @@ def test_polar_rlim_bottom(fig_test, fig_ref):
     ax.set_rmin(.5)
 
 
+def test_polar_rlim_zero():
+    ax = plt.figure().add_subplot(projection='polar')
+    ax.plot(np.arange(10), np.arange(10) + .01)
+    assert ax.get_ylim()[0] == 0
+
+
 @image_comparison(baseline_images=['axvspan_epoch'])
 def test_axvspan_epoch():
     from datetime import datetime
diff --git a/lib/matplotlib/tests/test_streamplot.py b/lib/matplotlib/tests/test_streamplot.py
@@ -48,18 +48,23 @@ def test_colormap():
     plt.colorbar()
 
 
+# Tolerance due to change in sticky-edges logic.
 @image_comparison(baseline_images=['streamplot_linewidth'],
                   tol={'aarch64': 0.02}.get(platform.machine(), 0.0),
                   remove_text=True, style='mpl20')
 def test_linewidth():
     X, Y, U, V = velocity_field()
     speed = np.hypot(U, V)
     lw = 5 * speed / speed.max()
-    df = 25 / 30   # Compatibility factor for old test image
+   # Compatibility for old test image
+    df = 25 / 30
+    plt.gca().set(xlim=(-3.0, 2.9999999999999947),
+                  ylim=(-3.0000000000000004, 2.9999999999999947))
     plt.streamplot(X, Y, U, V, density=[0.5 * df, 1. * df], color='k',
                    linewidth=lw)
 
 
+# Tolerance due to change in sticky-edges logic.
 @image_comparison(baseline_images=['streamplot_masks_and_nans'],
                   tol=0.04 if on_win else 0,
                   remove_text=True, style='mpl20')
@@ -69,6 +74,9 @@ def test_masks_and_nans():
     mask[40:60, 40:60] = 1
     U[:20, :20] = np.nan
     U = np.ma.array(U, mask=mask)
+   # Compatibility for old test image
+    plt.gca().set(xlim=(-3.0, 2.9999999999999947),
+                  ylim=(-3.0000000000000004, 2.9999999999999947))
     with np.errstate(invalid='ignore'):
         plt.streamplot(X, Y, U, V, color=U, cmap=plt.cm.Blues)
 
