matplotlib · tacaswell · Aug 26, 2014 · Jul 12, 2014 · Jul 12, 2014 · Jul 12, 2014
diff --git a/lib/matplotlib/bezier.py b/lib/matplotlib/bezier.py
@@ -256,7 +256,7 @@ def split_path_inout(path, inside, tolerence=0.01, reorder_inout=False):
 
     for ctl_points, command in path_iter:
         iold = i
-        i += len(ctl_points) / 2
+        i += len(ctl_points) // 2
         if inside(ctl_points[-2:]) != begin_inside:
             bezier_path = concat([ctl_points_old[-2:], ctl_points])
             break

diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -1737,7 +1737,7 @@ def simple_linear_interpolation(a, steps):
     if steps == 1:
         return a
 
-    steps = np.floor(steps)
+    steps = int(np.floor(steps))
     new_length = ((len(a) - 1) * steps) + 1
     new_shape = list(a.shape)
     new_shape[0] = new_length
@@ -1747,7 +1747,6 @@ def simple_linear_interpolation(a, steps):
     a0 = a[0:-1]
     a1 = a[1:]
     delta = ((a1 - a0) / steps)
-    steps = int(steps)
     for i in range(1, steps):
         result[i::steps] = delta * i + a0
     result[steps::steps] = a1

diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -222,7 +222,8 @@ def is_color_like(c):
 
 def rgb2hex(rgb):
     'Given an rgb or rgba sequence of 0-1 floats, return the hex string'
-    return '#%02x%02x%02x' % tuple([np.round(val * 255) for val in rgb[:3]])
+    a = '#%02x%02x%02x' % tuple([int(np.round(val * 255)) for val in rgb[:3]])
+    return a
 
 hexColorPattern = re.compile("\A#[a-fA-F0-9]{6}\Z")
 

diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
@@ -474,20 +474,21 @@ def calc_label_rot_and_inline(self, slc, ind, lw, lc=None, spacing=5):
                 xy2 = mlab.less_simple_linear_interpolation(
                     pl, lc, [xi[1]])
 
-            # Make integer
+            # Round to integer values but keep as float
+            # To allow check against nan below
             I = [np.floor(I[0]), np.ceil(I[1])]
 
             # Actually break contours
             if closed:
                 # This will remove contour if shorter than label
                 if np.all(~np.isnan(I)):
-                    nlc.append(np.r_[xy2, lc[I[1]:I[0] + 1], xy1])
+                    nlc.append(np.r_[xy2, lc[int(I[1]):int(I[0]) + 1], xy1])
             else:
                 # These will remove pieces of contour if they have length zero
                 if not np.isnan(I[0]):
-                    nlc.append(np.r_[lc[:I[0] + 1], xy1])
+                    nlc.append(np.r_[lc[:int(I[0]) + 1], xy1])
                 if not np.isnan(I[1]):
-                    nlc.append(np.r_[xy2, lc[I[1]:]])
+                    nlc.append(np.r_[xy2, lc[int(I[1]):]])
 
             # The current implementation removes contours completely
             # covered by labels.  Uncomment line below to keep

diff --git a/lib/matplotlib/hatch.py b/lib/matplotlib/hatch.py
@@ -21,7 +21,7 @@ class HatchPatternBase:
 
 class HorizontalHatch(HatchPatternBase):
     def __init__(self, hatch, density):
-        self.num_lines = (hatch.count('-') + hatch.count('+')) * density
+        self.num_lines = int((hatch.count('-') + hatch.count('+')) * density)
         self.num_vertices = self.num_lines * 2
 
     def set_vertices_and_codes(self, vertices, codes):
@@ -38,7 +38,7 @@ def set_vertices_and_codes(self, vertices, codes):
 
 class VerticalHatch(HatchPatternBase):
     def __init__(self, hatch, density):
-        self.num_lines = (hatch.count('|') + hatch.count('+')) * density
+        self.num_lines = int((hatch.count('|') + hatch.count('+')) * density)
         self.num_vertices = self.num_lines * 2
 
     def set_vertices_and_codes(self, vertices, codes):
@@ -55,8 +55,8 @@ def set_vertices_and_codes(self, vertices, codes):
 
 class NorthEastHatch(HatchPatternBase):
     def __init__(self, hatch, density):
-        self.num_lines = (hatch.count('/') + hatch.count('x') +
-                          hatch.count('X')) * density
+        self.num_lines = int((hatch.count('/') + hatch.count('x') +
+                          hatch.count('X')) * density)
         if self.num_lines:
             self.num_vertices = (self.num_lines + 1) * 2
         else:
@@ -74,8 +74,8 @@ def set_vertices_and_codes(self, vertices, codes):
 
 class SouthEastHatch(HatchPatternBase):
     def __init__(self, hatch, density):
-        self.num_lines = (hatch.count('\\') + hatch.count('x') +
-                          hatch.count('X')) * density
+        self.num_lines = int((hatch.count('\\') + hatch.count('x') +
+                          hatch.count('X')) * density)
         self.num_vertices = (self.num_lines + 1) * 2
         if self.num_lines:
             self.num_vertices = (self.num_lines + 1) * 2
@@ -100,8 +100,8 @@ def __init__(self, hatch, density):
             self.num_shapes = 0
             self.num_vertices = 0
         else:
-            self.num_shapes = ((self.num_rows / 2 + 1) * (self.num_rows + 1) +
-                               (self.num_rows / 2) * (self.num_rows))
+            self.num_shapes = ((self.num_rows // 2 + 1) * (self.num_rows + 1) +
+                               (self.num_rows // 2) * (self.num_rows))
             self.num_vertices = (self.num_shapes *
                                  len(self.shape_vertices) *
                                  (self.filled and 1 or 2))

diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -523,7 +523,7 @@ def test_nonfinite_limits():
         y = np.log(x)
     finally:
         np.seterr(**olderr)
-    x[len(x)/2] = np.nan
+    x[len(x)//2] = np.nan
     fig = plt.figure()
     ax = fig.add_subplot(111)
     ax.plot(x, y)

diff --git a/lib/matplotlib/tests/test_mlab.py b/lib/matplotlib/tests/test_mlab.py
@@ -1325,8 +1325,8 @@ def createStim(self, fstims, iscomplex, sides, nsides, len_x=None,
 
         freqs_specgram = freqs_density
         # time points for specgram
-        t_start = NFFT_specgram_real/2
-        t_stop = len(x) - NFFT_specgram_real/2+1
+        t_start = NFFT_specgram_real//2
+        t_stop = len(x) - NFFT_specgram_real//2+1
         t_step = NFFT_specgram_real - nover_specgram_real
         t_specgram = x[t_start:t_stop:t_step]
         if NFFT_specgram_real % 2:

diff --git a/lib/matplotlib/tests/test_simplification.py b/lib/matplotlib/tests/test_simplification.py
@@ -153,7 +153,7 @@ def test_start_with_moveto():
         decodebytes = base64.decodestring
 
     verts = np.fromstring(decodebytes(data), dtype='<i4')
-    verts = verts.reshape((len(verts) / 2, 2))
+    verts = verts.reshape((len(verts) // 2, 2))
     path = Path(verts)
     segs = path.iter_segments(transforms.IdentityTransform(), clip=(0.0, 0.0, 100.0, 100.0))
     segs = list(segs)

diff --git a/lib/matplotlib/tri/trirefine.py b/lib/matplotlib/tri/trirefine.py
@@ -231,7 +231,7 @@ def _refine_triangulation_once(triangulation, ancestors=None):
         # points
         # hint: each apex is shared by 2 masked_triangles except the borders.
         borders = np.sum(neighbors == -1)
-        added_pts = (3*ntri + borders) / 2
+        added_pts = (3*ntri + borders) // 2
         refi_npts = npts + added_pts
         refi_x = np.zeros(refi_npts)
         refi_y = np.zeros(refi_npts)