matplotlib
diff --git a/‎examples/axisartist/demo_curvelinear_grid.py
Copy file name to clipboardExpand all lines: examples/axisartist/demo_curvelinear_grid.py
+40-61Lines changed: 40 additions & 61 deletions b/‎examples/axisartist/demo_curvelinear_grid.py
Copy file name to clipboardExpand all lines: examples/axisartist/demo_curvelinear_grid.py
+40-61Lines changed: 40 additions & 61 deletions
@@ -1,31 +1,31 @@
 """
 =====================
-Demo Curvelinear Grid
+Curvilinear grid demo
 =====================
 
 Custom grid and ticklines.
 
-This example demonstrates how to use GridHelperCurveLinear to define
-custom grids and ticklines by applying a transformation on the grid.
-This can be used, as showcase on the second plot, to create polar
-projections in a rectangular box.
+This example demonstrates how to use
+`~.grid_helper_curvelinear.GridHelperCurveLinear` to define custom grids and
+ticklines by applying a transformation on the grid.  This can be used, as
+shown on the second plot, to create polar projections in a rectangular box.
 """
 
 import numpy as np
 
 import matplotlib.pyplot as plt
-import matplotlib.cbook as cbook
+from matplotlib.projections import PolarAxes
+from matplotlib.transforms import Affine2D
 
-from mpl_toolkits.axisartist import Subplot
-from mpl_toolkits.axisartist import SubplotHost, \
-    ParasiteAxesAuxTrans
-from mpl_toolkits.axisartist.grid_helper_curvelinear import \
-    GridHelperCurveLinear
+from mpl_toolkits.axisartist import (
+    angle_helper, Subplot, SubplotHost, ParasiteAxesAuxTrans)
+from mpl_toolkits.axisartist.grid_helper_curvelinear import (
+    GridHelperCurveLinear)
 
 
 def curvelinear_test1(fig):
     """
-    grid for custom transform.
+    Grid for custom transform.
     """
 
     def tr(x, y):
@@ -46,89 +46,68 @@ def inv_tr(x, y):
 
     fig.add_subplot(ax1)
 
-    xx, yy = tr([3, 6], [5.0, 10.])
+    xx, yy = tr([3, 6], [5, 10])
     ax1.plot(xx, yy, linewidth=2.0)
 
-    ax1.set_aspect(1.)
-    ax1.set_xlim(0, 10.)
-    ax1.set_ylim(0, 10.)
+    ax1.set_aspect(1)
+    ax1.set_xlim(0, 10)
+    ax1.set_ylim(0, 10)
 
-    ax1.axis["t"] = ax1.new_floating_axis(0, 3.)
-    ax1.axis["t2"] = ax1.new_floating_axis(1, 7.)
+    ax1.axis["t"] = ax1.new_floating_axis(0, 3)
+    ax1.axis["t2"] = ax1.new_floating_axis(1, 7)
     ax1.grid(True, zorder=0)
 
 
-import mpl_toolkits.axisartist.angle_helper as angle_helper
-
-from matplotlib.projections import PolarAxes
-from matplotlib.transforms import Affine2D
-
-
 def curvelinear_test2(fig):
     """
-    polar projection, but in a rectangular box.
+    Polar projection, but in a rectangular box.
     """
 
     # PolarAxes.PolarTransform takes radian. However, we want our coordinate
     # system in degree
-    tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()
-
-    # polar projection, which involves cycle, and also has limits in
+    tr = Affine2D().scale(np.pi/180, 1) + PolarAxes.PolarTransform()
+    # Polar projection, which involves cycle, and also has limits in
     # its coordinates, needs a special method to find the extremes
     # (min, max of the coordinate within the view).
-
-    # 20, 20 : number of sampling points along x, y direction
-    extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
-                                                     lon_cycle=360,
-                                                     lat_cycle=None,
-                                                     lon_minmax=None,
-                                                     lat_minmax=(0, np.inf),
-                                                     )
-
+    extreme_finder = angle_helper.ExtremeFinderCycle(
+        nx=20, ny=20,  # Number of sampling points in each direction.
+        lon_cycle=360, lat_cycle=None,
+        lon_minmax=None, lat_minmax=(0, np.inf),
+    )
+    # Find grid values appropriate for the coordinate (degree, minute, second).
     grid_locator1 = angle_helper.LocatorDMS(12)
-    # Find a grid values appropriate for the coordinate (degree,
-    # minute, second).
-
+    # Use an appropriate formatter.  Note that the acceptable Locator and
+    # Formatter classes are a bit different than that of Matplotlib, which
+    # cannot directly be used here (this may be possible in the future).
     tick_formatter1 = angle_helper.FormatterDMS()
-    # And also uses an appropriate formatter.  Note that,the
-    # acceptable Locator and Formatter class is a bit different than
-    # that of mpl's, and you cannot directly use mpl's Locator and
-    # Formatter here (but may be possible in the future).
-
-    grid_helper = GridHelperCurveLinear(tr,
-                                        extreme_finder=extreme_finder,
-                                        grid_locator1=grid_locator1,
-                                        tick_formatter1=tick_formatter1
-                                        )
 
+    grid_helper = GridHelperCurveLinear(
+        tr, extreme_finder=extreme_finder,
+        grid_locator1=grid_locator1, tick_formatter1=tick_formatter1)
     ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper)
 
     # make ticklabels of right and top axis visible.
     ax1.axis["right"].major_ticklabels.set_visible(True)
     ax1.axis["top"].major_ticklabels.set_visible(True)
-
     # let right axis shows ticklabels for 1st coordinate (angle)
     ax1.axis["right"].get_helper().nth_coord_ticks = 0
     # let bottom axis shows ticklabels for 2nd coordinate (radius)
     ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
 
     fig.add_subplot(ax1)
 
+    ax1.set_aspect(1)
+    ax1.set_xlim(-5, 12)
+    ax1.set_ylim(-5, 10)
+
+    ax1.grid(True, zorder=0)
+
     # A parasite axes with given transform
     ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
     # note that ax2.transData == tr + ax1.transData
     # Anything you draw in ax2 will match the ticks and grids of ax1.
     ax1.parasites.append(ax2)
-    intp = cbook.simple_linear_interpolation
-    ax2.plot(intp(np.array([0, 30]), 50),
-             intp(np.array([10., 10.]), 50),
-             linewidth=2.0)
-
-    ax1.set_aspect(1.)
-    ax1.set_xlim(-5, 12)
-    ax1.set_ylim(-5, 10)
-
-    ax1.grid(True, zorder=0)
+    ax2.plot(np.linspace(0, 30, 51), np.linspace(10, 10, 51), linewidth=2)
 
 
 if __name__ == "__main__":