fix some pep8 issues overseen by autopep8

matplotlib · efiring · Sep 9, 2014 · Aug 26, 2014 · Aug 26, 2014 · Aug 27, 2014
commit 1171a967c1d4b645b56b46523f072cc7721f2acb
diff --git a/examples/animation/double_pendulum_animated.py b/examples/animation/double_pendulum_animated.py
@@ -22,7 +22,8 @@ def derivs(state, t):
    del_ = state[2]-state[0]
    den1 = (M1+M2)*L1 - M2*L1*cos(del_)*cos(del_)
    dydx[1] = (M2*L1*state[1]*state[1]*sin(del_)*cos(del_)
-               + M2*G*sin(state[2])*cos(del_) + M2*L2*state[3]*state[3]*sin(del_)
+               + M2*G*sin(state[2])*cos(del_)
+               + M2*L2*state[3]*state[3]*sin(del_)
               - (M1+M2)*G*sin(state[0]))/den1

    dydx[2] = state[3]

diff --git a/examples/animation/subplots.py b/examples/animation/subplots.py
@@ -3,11 +3,11 @@
 from matplotlib.lines import Line2D
 import matplotlib.animation as animation

-# This example uses subclassing, but there is no reason that the proper function
-# couldn't be set up and then use FuncAnimation. The code is long, but not
-# really complex. The length is due solely to the fact that there are a total
-# of 9 lines that need to be changed for the animation as well as 3 subplots
-# that need initial set up.
+# This example uses subclassing, but there is no reason that the proper
+# function couldn't be set up and then use FuncAnimation. The code is long, but
+# not really complex. The length is due solely to the fact that there are a
+# total of 9 lines that need to be changed for the animation as well as 3
+# subplots that need initial set up.


 class SubplotAnimation(animation.TimedAnimation):

diff --git a/examples/api/date_demo.py b/examples/api/date_demo.py
@@ -41,10 +41,10 @@
 datemax = datetime.date(r.date.max().year + 1, 1, 1)
 ax.set_xlim(datemin, datemax)

-# format the coords message box
-

-def price(x): return '$%1.2f' % x
+# format the coords message box
+def price(x):
+    return '$%1.2f' % x
 ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
 ax.format_ydata = price
 ax.grid(True)

diff --git a/examples/api/logo2.py b/examples/api/logo2.py
@@ -26,8 +26,14 @@ def add_math_background():

    text = []
    text.append(
-        (r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]$", (0.7, 0.2), 20))
-    text.append((r"$\frac{d\rho}{d t} + \rho \vec{v}\cdot\nabla\vec{v} = -\nabla p + \mu\nabla^2 \vec{v} + \rho \vec{g}$",
+        (r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = "
+         r"U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2}"
+         r"\int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 "
+         r"\left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - "
+         r"\alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} "
+         r"}{U^{0\beta}_{\rho_1 \sigma_2}}\right]$", (0.7, 0.2), 20))
+    text.append((r"$\frac{d\rho}{d t} + \rho \vec{v}\cdot\nabla\vec{v} "
+                 r"= -\nabla p + \mu\nabla^2 \vec{v} + \rho \vec{g}$",
                 (0.35, 0.9), 20))
    text.append((r"$\int_{-\infty}^\infty e^{-x^2}dx=\sqrt{\pi}$",
                 (0.15, 0.3), 25))
@@ -36,8 +42,8 @@ def add_math_background():
    text.append((r"$F_G = G\frac{m_1m_2}{r^2}$",
                 (0.85, 0.7), 30))
    for eq, (x, y), size in text:
-        ax.text(x, y, eq, ha='center', va='center', color="#11557c", alpha=0.25,
-                transform=ax.transAxes, fontsize=size)
+        ax.text(x, y, eq, ha='center', va='center', color="#11557c",
+                alpha=0.25, transform=ax.transAxes, fontsize=size)
    ax.set_axis_off()
    return ax


diff --git a/examples/api/mathtext_asarray.py b/examples/api/mathtext_asarray.py
@@ -2,18 +2,15 @@
 Load a mathtext image as numpy array
 """

-import numpy as np
 import matplotlib.mathtext as mathtext
 import matplotlib.pyplot as plt
 import matplotlib
 matplotlib.rc('image', origin='upper')

 parser = mathtext.MathTextParser("Bitmap")
-
-
-parser.to_png(
-    'test2.png', r'$\left[\left\lfloor\frac{5}{\frac{\left(3\right)}{4}} y\right)\right]$', color='green', fontsize=14, dpi=100)
-
+parser.to_png('test2.png',
+              r'$\left[\left\lfloor\frac{5}{\frac{\left(3\right)}{4}} '
+              r'y\right)\right]$', color='green', fontsize=14, dpi=100)

 rgba1, depth1 = parser.to_rgba(
    r'IQ: $\sigma_i=15$', color='blue', fontsize=20, dpi=200)

diff --git a/examples/api/radar_chart.py b/examples/api/radar_chart.py
@@ -116,10 +116,11 @@ def example_data():
    # The following data is from the Denver Aerosol Sources and Health study.
    # See  doi:10.1016/j.atmosenv.2008.12.017
    #
-    # The data are pollution source profile estimates for five modeled pollution
-    # sources (e.g., cars, wood-burning, etc) that emit 7-9 chemical species.
-    # The radar charts are experimented with here to see if we can nicely
-    # visualize how the modeled source profiles change across four scenarios:
+    # The data are pollution source profile estimates for five modeled
+    # pollution sources (e.g., cars, wood-burning, etc) that emit 7-9 chemical
+    # species. The radar charts are experimented with here to see if we can
+    # nicely visualize how the modeled source profiles change across four
+    # scenarios:
    #  1) No gas-phase species present, just seven particulate counts on
    #     Sulfate
    #     Nitrate

diff --git a/examples/api/sankey_demo_rankine.py b/examples/api/sankey_demo_rankine.py
@@ -1,14 +1,16 @@
-"""Demonstrate the Sankey class with a practicle example of a Rankine power cycle.
+"""Demonstrate the Sankey class with a practicle example of a Rankine power
+cycle.
+
 """
-import numpy as np
 import matplotlib.pyplot as plt

 from matplotlib.sankey import Sankey

 fig = plt.figure(figsize=(8, 9))
 ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[],
-                     title="Rankine Power Cycle: Example 8.6 from Moran and Shapiro\n"
-                           + "\x22Fundamentals of Engineering Thermodynamics\x22, 6th ed., 2008")
+                     title="Rankine Power Cycle: Example 8.6 from Moran and "
+                     "Shapiro\n\x22Fundamentals of Engineering Thermodynamics "
+                     "\x22, 6th ed., 2008")
 Hdot = [260.431, 35.078, 180.794, 221.115, 22.700,
        142.361, 10.193, 10.210, 43.670, 44.312,
        68.631, 10.758, 10.758, 0.017, 0.642,

diff --git a/examples/api/skewt.py b/examples/api/skewt.py
@@ -128,8 +128,8 @@ def _set_lim_and_transforms(self):
        # coordinates thus performing the transform around the proper origin
        # We keep the pre-transAxes transform around for other users, like the
        # spines for finding bounds
-        self.transDataToAxes = self.transScale + (self.transLimits +
-                                                  transforms.Affine2D().skew_deg(rot, 0))
+        self.transDataToAxes = self.transScale + \
+            self.transLimits + transforms.Affine2D().skew_deg(rot, 0)

        # Create the full transform from Data to Pixels
        self.transData = self.transDataToAxes + self.transAxes
@@ -148,7 +148,6 @@ def _set_lim_and_transforms(self):
 if __name__ == '__main__':
    # Now make a simple example using the custom projection.
    from matplotlib.ticker import ScalarFormatter, MultipleLocator
-    from matplotlib.collections import LineCollection
    import matplotlib.pyplot as plt
    from StringIO import StringIO
    import numpy as np
@@ -227,7 +226,8 @@ def _set_lim_and_transforms(self):
  107.8  15850  -64.1  -75.1     21   0.01    265     58  395.0  395.1  395.0
  105.0  16010  -64.7  -75.7     21   0.01    272     50  396.9  396.9  396.9
  103.0  16128  -62.9  -73.9     21   0.02    277     45  402.5  402.6  402.5
-  100.0  16310  -62.5  -73.5     21   0.02    285     36  406.7  406.8  406.7'''
+  100.0  16310  -62.5  -73.5     21   0.02    285     36  406.7  406.8  406.7
+    '''

    # Parse the data
    sound_data = StringIO(data_txt)

diff --git a/examples/axes_grid/demo_axes_divider.py b/examples/axes_grid/demo_axes_divider.py
@@ -97,27 +97,25 @@ def demo():
    fig1 = plt.figure(1, (6, 6))
    fig1.clf()

-    ## PLOT 1
+    # PLOT 1
    # simple image & colorbar
    ax = fig1.add_subplot(2, 2, 1)
    demo_simple_image(ax)

-    ## PLOT 2
+    # PLOT 2
    # image and colorbar whose location is adjusted in the drawing time.
    # a hard way

    demo_locatable_axes_hard(fig1)

-
-    ## PLOT 3
+    # PLOT 3
    # image and colorbar whose location is adjusted in the drawing time.
    # a easy way

    ax = fig1.add_subplot(2, 2, 3)
    demo_locatable_axes_easy(ax)

-
-    ## PLOT 4
+    # PLOT 4
    # two images side by side with fixed padding.

    ax = fig1.add_subplot(2, 2, 4)

diff --git a/examples/axes_grid/demo_curvelinear_grid.py b/examples/axes_grid/demo_curvelinear_grid.py
@@ -1,14 +1,13 @@
 import numpy as np
-#from matplotlib.path import Path

 import matplotlib.pyplot as plt
 import matplotlib.cbook as cbook

-from mpl_toolkits.axisartist.grid_helper_curvelinear import GridHelperCurveLinear
 from mpl_toolkits.axisartist import Subplot
-
 from mpl_toolkits.axisartist import SubplotHost, \
    ParasiteAxesAuxTrans
+from mpl_toolkits.axisartist.grid_helper_curvelinear import \
+    GridHelperCurveLinear


 def curvelinear_test1(fig):

diff --git a/examples/axes_grid/demo_curvelinear_grid2.py b/examples/axes_grid/demo_curvelinear_grid2.py
@@ -1,9 +1,8 @@
 import numpy as np
-#from matplotlib.path import Path
-
 import matplotlib.pyplot as plt

-from mpl_toolkits.axes_grid.grid_helper_curvelinear import GridHelperCurveLinear
+from mpl_toolkits.axes_grid.grid_helper_curvelinear import \
+    GridHelperCurveLinear
 from mpl_toolkits.axes_grid.axislines import Subplot

 import mpl_toolkits.axes_grid.angle_helper as angle_helper

diff --git a/examples/axes_grid/demo_floating_axes.py b/examples/axes_grid/demo_floating_axes.py
@@ -34,9 +34,6 @@ def setup_axes2(fig, rect):
    With custom locator and formatter.
    Note that the extreme values are swapped.
    """
-
-    #tr_scale = Affine2D().scale(np.pi/180., 1.)
-
    tr = PolarAxes.PolarTransform()

    pi = np.pi
@@ -48,13 +45,12 @@ def setup_axes2(fig, rect):

    grid_locator2 = MaxNLocator(2)

-    grid_helper = floating_axes.GridHelperCurveLinear(tr,
-                                                      extremes=(.5*pi, 0, 2, 1),
-                                                      grid_locator1=grid_locator1,
-                                                      grid_locator2=grid_locator2,
-                                                      tick_formatter1=tick_formatter1,
-                                                      tick_formatter2=None,
-                                                      )
+    grid_helper = floating_axes.GridHelperCurveLinear(
+        tr, extremes=(.5*pi, 0, 2, 1),
+        grid_locator1=grid_locator1,
+        grid_locator2=grid_locator2,
+        tick_formatter1=tick_formatter1,
+        tick_formatter2=None)

    ax1 = floating_axes.FloatingSubplot(fig, rect, grid_helper=grid_helper)
    fig.add_subplot(ax1)
@@ -91,14 +87,12 @@ def setup_axes3(fig, rect):

    ra0, ra1 = 8.*15, 14.*15
    cz0, cz1 = 0, 14000
-    grid_helper = floating_axes.GridHelperCurveLinear(tr,
-                                                      extremes=(
-                                                          ra0, ra1, cz0, cz1),
-                                                      grid_locator1=grid_locator1,
-                                                      grid_locator2=grid_locator2,
-                                                      tick_formatter1=tick_formatter1,
-                                                      tick_formatter2=None,
-                                                      )
+    grid_helper = floating_axes.GridHelperCurveLinear(
+        tr, extremes=(ra0, ra1, cz0, cz1),
+        grid_locator1=grid_locator1,
+        grid_locator2=grid_locator2,
+        tick_formatter1=tick_formatter1,
+        tick_formatter2=None)

    ax1 = floating_axes.FloatingSubplot(fig, rect, grid_helper=grid_helper)
    fig.add_subplot(ax1)
@@ -138,7 +132,7 @@ def setup_axes3(fig, rect):

    # theta = np.random.rand(10) #*.5*np.pi
    # radius = np.random.rand(10) #+1.
-    #aux_ax1.scatter(theta, radius)
+    # aux_ax1.scatter(theta, radius)

    ax2, aux_ax2 = setup_axes2(fig, 132)