PEP8 on tri module source code.

Author: ianthomas23

lib/matplotlib/tri/triangulation.py

@@ -54,12 +54,10 @@ def __init__(self, x, y, triangles=None, mask=None):
             # No triangulation specified, so use matplotlib.delaunay.
             dt = delaunay.Triangulation(self.x, self.y)
             self.triangles = np.asarray(
-                                 dt.to_client_point_indices(dt.triangle_nodes),
-                                 dtype=np.int32)
+                dt.to_client_point_indices(dt.triangle_nodes), dtype=np.int32)
             if mask is None:
                 self._edges = np.asarray(
-                                  dt.to_client_point_indices(dt.edge_db),
-                                  dtype=np.int32)
+                    dt.to_client_point_indices(dt.edge_db), dtype=np.int32)
                 # Delaunay triangle_neighbors uses different edge indexing,
                 # so convert.
                 neighbors = np.asarray(dt.triangle_neighbors, dtype=np.int32)
@@ -77,8 +75,8 @@ def __init__(self, x, y, triangles=None, mask=None):
 
         if mask is not None:
             self.mask = np.asarray(mask, dtype=np.bool)
-            if len(self.mask.shape) != 1 or \
-                    self.mask.shape[0] != self.triangles.shape[0]:
+            if (len(self.mask.shape) != 1 or
+                    self.mask.shape[0] != self.triangles.shape[0]):
                 raise ValueError('mask array must have same length as '
                                  'triangles array')
 
@@ -195,8 +193,8 @@ def set_mask(self, mask):
             self.mask = None
         else:
             self.mask = np.asarray(mask, dtype=np.bool)
-            if len(self.mask.shape) != 1 or \
-                    self.mask.shape[0] != self.triangles.shape[0]:
+            if (len(self.mask.shape) != 1 or
+                    self.mask.shape[0] != self.triangles.shape[0]):
                 raise ValueError('mask array must have same length as '
                                  'triangles array')
 

lib/matplotlib/tri/tricontour.py

@@ -50,7 +50,7 @@ def _process_args(self, *args, **kwargs):
             x1 = tri.x.max()
             y0 = tri.y.min()
             y1 = tri.y.max()
-            self.ax.update_datalim([(x0,y0), (x1,y1)])
+            self.ax.update_datalim([(x0, y0), (x1, y1)])
             self.ax.autoscale_view()
 
         self.cppContourGenerator = C
@@ -65,7 +65,7 @@ def _get_allsegs_and_allkinds(self):
             allkinds = []
             for lower, upper in zip(lowers, uppers):
                 segs, kinds = self.cppContourGenerator.create_filled_contour(
-                                                                 lower, upper)
+                    lower, upper)
                 allsegs.append([segs])
                 allkinds.append([kinds])
         else:
@@ -76,10 +76,12 @@ def _get_allsegs_and_allkinds(self):
         return allsegs, allkinds
 
     def _contour_args(self, args, kwargs):
-        if self.filled: fn = 'contourf'
-        else:           fn = 'contour'
-        tri, args, kwargs = \
-            Triangulation.get_from_args_and_kwargs(*args, **kwargs)
+        if self.filled:
+            fn = 'contourf'
+        else:
+            fn = 'contour'
+        tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args,
+                                                                   **kwargs)
         z = np.asarray(args[0])
         if z.shape != tri.x.shape:
             raise ValueError('z array must have same length as triangulation x'
@@ -275,14 +277,16 @@ def _contour_args(self, args, kwargs):
 
 
 def tricontour(ax, *args, **kwargs):
-    if not ax._hold: ax.cla()
+    if not ax._hold:
+        ax.cla()
     kwargs['filled'] = False
     return TriContourSet(ax, *args, **kwargs)
 tricontour.__doc__ = TriContourSet.tricontour_doc
 
 
 def tricontourf(ax, *args, **kwargs):
-    if not ax._hold: ax.cla()
+    if not ax._hold:
+        ax.cla()
     kwargs['filled'] = True
     return TriContourSet(ax, *args, **kwargs)
 tricontourf.__doc__ = TriContourSet.tricontour_doc

lib/matplotlib/tri/triinterpolate.py

@@ -286,7 +286,7 @@ def _interpolate_single_key(self, return_key, tri_index, x, y):
         elif return_key == 'dzdy':
             return self._plane_coefficients[tri_index, 1]
         else:
-            raise ValueError("Invalid return_key: "+return_key)
+            raise ValueError("Invalid return_key: " + return_key)
 
 
 class CubicTriInterpolator(TriInterpolator):
@@ -526,7 +526,7 @@ def _get_alpha_vec(x, y, tris_pts):
         ab = _transpose_vectorized(abT)
         x = np.expand_dims(x, ndim)
         y = np.expand_dims(y, ndim)
-        OM = np.concatenate([x, y], ndim)-tris_pts[:, 0, :]
+        OM = np.concatenate([x, y], ndim) - tris_pts[:, 0, :]
 
         metric = _prod_vectorized(ab, abT)
         # Here we try to deal with the colinear cases.
@@ -563,8 +563,8 @@ def _get_jacobian(tris_pts):
                     ksi: element parametric coordinates in triangle first apex
                     local basis.
         """
-        a = np.array(tris_pts[:, 1, :]-tris_pts[:, 0, :])
-        b = np.array(tris_pts[:, 2, :]-tris_pts[:, 0, :])
+        a = np.array(tris_pts[:, 1, :] - tris_pts[:, 0, :])
+        b = np.array(tris_pts[:, 2, :] - tris_pts[:, 0, :])
         J = _to_matrix_vectorized([[a[:, 0], a[:, 1]],
                                    [b[:, 0], b[:, 1]]])
         return J
@@ -595,9 +595,9 @@ def _compute_tri_eccentricities(tris_pts):
         dot_c = _prod_vectorized(_transpose_vectorized(c), c)[:, 0, 0]
         # Note that this line will raise a warning for dot_a, dot_b or dot_c
         # zeros, but we choose not to support triangles with duplicate points.
-        return _to_matrix_vectorized([[(dot_c-dot_b)/dot_a],
-                                      [(dot_a-dot_c)/dot_b],
-                                      [(dot_b-dot_a)/dot_c]])
+        return _to_matrix_vectorized([[(dot_c-dot_b) / dot_a],
+                                      [(dot_a-dot_c) / dot_b],
+                                      [(dot_b-dot_a) / dot_c]])
 
 
 # FEM element used for interpolation and for solving minimisation
@@ -1363,7 +1363,7 @@ def _cg(A, b, x0=None, tol=1.e-10, maxiter=1000):
 
     # Following C. T. Kelley
     while (np.sqrt(abs(rho)) > tol*b_norm) and (k < maxiter):
-        p = w+beta*p
+        p = w + beta*p
         z = A.dot(p)
         alpha = rho/np.dot(p, z)
         r = r - alpha*z

lib/matplotlib/tri/tripcolor.py

@@ -4,6 +4,7 @@
 from matplotlib.tri.triangulation import Triangulation
 import numpy as np
 
+
 def tripcolor(ax, *args, **kwargs):
     """
     Create a pseudocolor plot of an unstructured triangular grid.
@@ -49,7 +50,8 @@ def tripcolor(ax, *args, **kwargs):
 
         .. plot:: mpl_examples/pylab_examples/tripcolor_demo.py
     """
-    if not ax._hold: ax.cla()
+    if not ax._hold:
+        ax.cla()
 
     alpha = kwargs.pop('alpha', 1.0)
     norm = kwargs.pop('norm', None)
@@ -61,7 +63,7 @@ def tripcolor(ax, *args, **kwargs):
 
     tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args, **kwargs)
 
-    # C is the colors array, defined at either points or faces (i.e. triangles).
+    # C is the colors array defined at either points or faces (i.e. triangles).
     # If facecolors is None, C are defined at points.
     # If facecolors is not None, C are defined at faces.
     if facecolors is not None:
@@ -74,17 +76,16 @@ def tripcolor(ax, *args, **kwargs):
     # length of C whether it refers to points or faces.
     # Do not do this for gouraud shading.
     if (facecolors is None and len(C) == len(tri.triangles) and
-           len(C) != len(tri.x) and shading != 'gouraud'):
+            len(C) != len(tri.x) and shading != 'gouraud'):
         facecolors = C
 
     # Check length of C is OK.
-    if ( (facecolors is None and len(C) != len(tri.x)) or
-           (facecolors is not None and len(C) != len(tri.triangles)) ):
+    if ((facecolors is None and len(C) != len(tri.x)) or
+            (facecolors is not None and len(C) != len(tri.triangles))):
         raise ValueError('Length of color values array must be the same '
                          'as either the number of triangulation points '
                          'or triangles')
 
-
     # Handling of linewidths, shading, edgecolors and antialiased as
     # in Axes.pcolor
     linewidths = (0.25,)
@@ -105,7 +106,6 @@ def tripcolor(ax, *args, **kwargs):
     if 'antialiaseds' not in kwargs and ec.lower() == "none":
         kwargs['antialiaseds'] = False
 
-
     if shading == 'gouraud':
         if facecolors is not None:
             raise ValueError('Gouraud shading does not support the use '
@@ -118,8 +118,8 @@ def tripcolor(ax, *args, **kwargs):
     else:
         # Vertices of triangles.
         maskedTris = tri.get_masked_triangles()
-        verts = np.concatenate((tri.x[maskedTris][...,np.newaxis],
-                                tri.y[maskedTris][...,np.newaxis]), axis=2)
+        verts = np.concatenate((tri.x[maskedTris][..., np.newaxis],
+                                tri.y[maskedTris][..., np.newaxis]), axis=2)
 
         # Color values.
         if facecolors is None:
@@ -133,7 +133,8 @@ def tripcolor(ax, *args, **kwargs):
 
     collection.set_alpha(alpha)
     collection.set_array(C)
-    if norm is not None: assert(isinstance(norm, Normalize))
+    if norm is not None:
+        assert(isinstance(norm, Normalize))
     collection.set_cmap(cmap)
     collection.set_norm(norm)
     if vmin is not None or vmax is not None:
@@ -147,7 +148,7 @@ def tripcolor(ax, *args, **kwargs):
     miny = tri.y.min()
     maxy = tri.y.max()
     corners = (minx, miny), (maxx, maxy)
-    ax.update_datalim( corners)
+    ax.update_datalim(corners)
     ax.autoscale_view()
     ax.add_collection(collection)
     return collection