STY: Fix underindented continuation lines.

I don't agree with *all* indent choices of pycodestyle but these look
mostly like improvements.

Author: anntzer

.flake8

@@ -4,7 +4,7 @@ ignore =
     # Normal default
     E121,E123,E126,E226,E24,E704,W503,W504,
     # Additional ignores:
-    E122, E125, E127, E128, E129, E131,
+    E122, E125, E127, E129, E131,
     E265, E266,
     E305, E306,
     E722, E741,

doc/sphinxext/missing_references.py

@@ -47,8 +47,8 @@ def _record_reference(self, record):
             self.app.env.missing_references_warnings = defaultdict(set)
 
         record_missing_reference(self.app,
-            self.app.env.missing_references_warnings,
-            record.location)
+                                 self.app.env.missing_references_warnings,
+                                 record.location)
 
     def filter(self, record):
         self._record_reference(record)
@@ -157,13 +157,14 @@ def _warn_unused_missing_references(app):
         return
 
     # This is a dictionary of {(domain_type, target): locations}
-    references_ignored = getattr(app.env,
-        'missing_references_ignored_references', {})
+    references_ignored = getattr(
+        app.env, 'missing_references_ignored_references', {})
     references_events = getattr(app.env, 'missing_references_events', {})
 
     # Warn about any reference which is no longer missing.
     for (domain_type, target), locations in references_ignored.items():
-        missing_reference_locations = [_truncate_location(location)
+        missing_reference_locations = [
+            _truncate_location(location)
             for location in references_events.get((domain_type, target), [])]
 
         # For each ignored reference location, ensure a missing reference
@@ -176,9 +177,9 @@ def _warn_unused_missing_references(app):
                        f" from {app.config.missing_references_filename}."
                         "It is no longer a missing reference in the docs.")
                 logger.warning(msg,
-                    location=ignored_reference_location,
-                    type='ref',
-                    subtype=domain_type)
+                               location=ignored_reference_location,
+                               type='ref',
+                               subtype=domain_type)
 
 
 def save_missing_references_handler(app, exc):

examples/color/custom_cmap.py

@@ -147,9 +147,9 @@
 # in the middle of the range.
 cdict4 = {**cdict3,
           'alpha': ((0.0, 1.0, 1.0),
-                #   (0.25, 1.0, 1.0),
+                    # (0.25, 1.0, 1.0),
                     (0.5, 0.3, 0.3),
-                #   (0.75, 1.0, 1.0),
+                    # (0.75, 1.0, 1.0),
                     (1.0, 1.0, 1.0)),
           }
 

examples/images_contours_and_fields/contour_image.py

@@ -41,7 +41,7 @@
 axs = _axs.flatten()
 
 cset1 = axs[0].contourf(X, Y, Z, levels, norm=norm,
-                     cmap=cm.get_cmap(cmap, len(levels) - 1))
+                        cmap=cm.get_cmap(cmap, len(levels) - 1))
 # It is not necessary, but for the colormap, we need only the
 # number of levels minus 1.  To avoid discretization error, use
 # either this number or a large number such as the default (256).
@@ -84,7 +84,7 @@
 # image pixel (each color block on the following subplot), so the
 # domain that is contoured does not extend beyond these pixel centers.
 im = axs[3].imshow(Z, interpolation='nearest', extent=extent,
-                cmap=cmap, norm=norm)
+                   cmap=cmap, norm=norm)
 axs[3].contour(Z, levels, colors='k', origin='image', extent=extent)
 ylim = axs[3].get_ylim()
 axs[3].set_ylim(ylim[::-1])

examples/images_contours_and_fields/plot_streamplot.py

@@ -47,7 +47,7 @@
 
 ax3 = fig.add_subplot(gs[1, 1])
 strm = ax3.streamplot(X, Y, U, V, color=U, linewidth=2,
-                     cmap='autumn', start_points=seed_points.T)
+                      cmap='autumn', start_points=seed_points.T)
 fig.colorbar(strm.lines)
 ax3.set_title('Controlling Starting Points')
 

examples/images_contours_and_fields/tricontour_smooth_delaunay.py

@@ -119,8 +119,8 @@ def experiment_res(x, y):
 
 fig, ax = plt.subplots()
 ax.set_aspect('equal')
-ax.set_title("Filtering a Delaunay mesh\n" +
-          "(application to high-resolution tricontouring)")
+ax.set_title("Filtering a Delaunay mesh\n"
+             "(application to high-resolution tricontouring)")
 
 # 1) plot of the refined (computed) data contours:
 ax.tricontour(tri_refi, z_test_refi, levels=levels, cmap=cmap,

examples/lines_bars_and_markers/markevery_demo.py

@@ -53,7 +53,7 @@ def trim_axs(axs, N):
 ###############################################################################
 # Plot each markevery case for linear x and y scales
 
-fig1, axs = plt.subplots(rows, cols, figsize=figsize, constrained_layout=True)
+axs = plt.figure(figsize=figsize, constrained_layout=True).subplots(rows, cols)
 axs = trim_axs(axs, len(cases))
 for ax, case in zip(axs, cases):
     ax.set_title('markevery=%s' % str(case))
@@ -62,7 +62,7 @@ def trim_axs(axs, N):
 ###############################################################################
 # Plot each markevery case for log x and y scales
 
-fig2, axs = plt.subplots(rows, cols, figsize=figsize, constrained_layout=True)
+axs = plt.figure(figsize=figsize, constrained_layout=True).subplots(rows, cols)
 axs = trim_axs(axs, len(cases))
 for ax, case in zip(axs, cases):
     ax.set_title('markevery=%s' % str(case))
@@ -76,7 +76,7 @@ def trim_axs(axs, N):
 # it is always interpreted with respect to the first data point which might be
 # different to the first visible data point.
 
-fig3, axs = plt.subplots(rows, cols, figsize=figsize, constrained_layout=True)
+axs = plt.figure(figsize=figsize, constrained_layout=True).subplots(rows, cols)
 axs = trim_axs(axs, len(cases))
 for ax, case in zip(axs, cases):
     ax.set_title('markevery=%s' % str(case))
@@ -91,8 +91,8 @@ def trim_axs(axs, N):
 ###############################################################################
 # Plot each markevery case for polar plots
 
-fig4, axs = plt.subplots(rows, cols, figsize=figsize,
-        subplot_kw={'projection': 'polar'}, constrained_layout=True)
+axs = plt.figure(figsize=figsize, constrained_layout=True).subplots(
+    rows, cols, subplot_kw={'projection': 'polar'})
 axs = trim_axs(axs, len(cases))
 for ax, case in zip(axs, cases):
     ax.set_title('markevery=%s' % str(case))

examples/statistics/barchart_demo.py

@@ -139,10 +139,11 @@ def plot_student_results(student, scores, cohort_size):
 
         # Center the text vertically in the bar
         yloc = rect.get_y() + rect.get_height() / 2
-        label = ax1.annotate(rank_str, xy=(width, yloc), xytext=(xloc, 0),
-                            textcoords="offset points",
-                            ha=align, va='center',
-                            color=clr, weight='bold', clip_on=True)
+        label = ax1.annotate(
+            rank_str, xy=(width, yloc), xytext=(xloc, 0),
+            textcoords="offset points",
+            horizontalalignment=align, verticalalignment='center',
+            color=clr, weight='bold', clip_on=True)
         rect_labels.append(label)
 
     # make the interactive mouse over give the bar title

examples/statistics/confidence_ellipse.py

@@ -70,11 +70,8 @@ def confidence_ellipse(x, y, ax, n_std=3.0, facecolor='none', **kwargs):
     # two-dimensionl dataset.
     ell_radius_x = np.sqrt(1 + pearson)
     ell_radius_y = np.sqrt(1 - pearson)
-    ellipse = Ellipse((0, 0),
-        width=ell_radius_x * 2,
-        height=ell_radius_y * 2,
-        facecolor=facecolor,
-        **kwargs)
+    ellipse = Ellipse((0, 0), width=ell_radius_x * 2, height=ell_radius_y * 2,
+                      facecolor=facecolor, **kwargs)
 
     # Calculating the stdandard deviation of x from
     # the squareroot of the variance and multiplying
@@ -176,11 +173,11 @@ def get_correlated_dataset(n, dependency, mu, scale):
 ax_nstd.scatter(x, y, s=0.5)
 
 confidence_ellipse(x, y, ax_nstd, n_std=1,
-    label=r'$1\sigma$', edgecolor='firebrick')
+                   label=r'$1\sigma$', edgecolor='firebrick')
 confidence_ellipse(x, y, ax_nstd, n_std=2,
-    label=r'$2\sigma$', edgecolor='fuchsia', linestyle='--')
+                   label=r'$2\sigma$', edgecolor='fuchsia', linestyle='--')
 confidence_ellipse(x, y, ax_nstd, n_std=3,
-    label=r'$3\sigma$', edgecolor='blue', linestyle=':')
+                   label=r'$3\sigma$', edgecolor='blue', linestyle=':')
 
 ax_nstd.scatter(mu[0], mu[1], c='red', s=3)
 ax_nstd.set_title('Different standard deviations')
@@ -209,7 +206,7 @@ def get_correlated_dataset(n, dependency, mu, scale):
 # Plot the ellipse with zorder=0 in order to demonstrate
 # its transparency (caused by the use of alpha).
 confidence_ellipse(x, y, ax_kwargs,
-    alpha=0.5, facecolor='pink', edgecolor='purple', zorder=0)
+                   alpha=0.5, facecolor='pink', edgecolor='purple', zorder=0)
 
 ax_kwargs.scatter(x, y, s=0.5)
 ax_kwargs.scatter(mu[0], mu[1], c='red', s=3)

examples/subplots_axes_and_figures/axes_box_aspect.py

@@ -99,8 +99,8 @@
 # figure.
 
 fig5, axs = plt.subplots(2, 2, sharex="col", sharey="row",
-                        gridspec_kw=dict(height_ratios=[1, 3],
-                                         width_ratios=[3, 1]))
+                         gridspec_kw=dict(height_ratios=[1, 3],
+                                          width_ratios=[3, 1]))
 axs[0, 1].set_visible(False)
 axs[0, 0].set_box_aspect(1/3)
 axs[1, 0].set_box_aspect(1)
@@ -138,7 +138,7 @@
 # following creates a 2 by 3 subplot grid with all square axes.
 
 fig7, axs = plt.subplots(2, 3, subplot_kw=dict(box_aspect=1),
-                        sharex=True, sharey=True, constrained_layout=True)
+                         sharex=True, sharey=True, constrained_layout=True)
 
 for i, ax in enumerate(axs.flat):
     ax.scatter(i % 3, -((i // 3) - 0.5)*200, c=[plt.cm.hsv(i / 6)], s=300)