/usr/lib/python3/dist-packages/matplotlib/tests/test_skew.py is in python3-matplotlib 1.5.1-1ubuntu1.
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Testing that skewed axes properly work
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import itertools
from matplotlib.externals import six
from nose.tools import assert_true
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import cleanup, image_comparison
from matplotlib.axes import Axes
import matplotlib.transforms as transforms
import matplotlib.axis as maxis
import matplotlib.spines as mspines
import matplotlib.path as mpath
import matplotlib.patches as mpatch
from matplotlib.projections import register_projection
# The sole purpose of this class is to look at the upper, lower, or total
# interval as appropriate and see what parts of the tick to draw, if any.
class SkewXTick(maxis.XTick):
def draw(self, renderer):
if not self.get_visible():
return
renderer.open_group(self.__name__)
lower_interval = self.axes.xaxis.lower_interval
upper_interval = self.axes.xaxis.upper_interval
if self.gridOn and transforms.interval_contains(
self.axes.xaxis.get_view_interval(), self.get_loc()):
self.gridline.draw(renderer)
if transforms.interval_contains(lower_interval, self.get_loc()):
if self.tick1On:
self.tick1line.draw(renderer)
if self.label1On:
self.label1.draw(renderer)
if transforms.interval_contains(upper_interval, self.get_loc()):
if self.tick2On:
self.tick2line.draw(renderer)
if self.label2On:
self.label2.draw(renderer)
renderer.close_group(self.__name__)
# This class exists to provide two separate sets of intervals to the tick,
# as well as create instances of the custom tick
class SkewXAxis(maxis.XAxis):
def __init__(self, *args, **kwargs):
maxis.XAxis.__init__(self, *args, **kwargs)
self.upper_interval = 0.0, 1.0
def _get_tick(self, major):
return SkewXTick(self.axes, 0, '', major=major)
@property
def lower_interval(self):
return self.axes.viewLim.intervalx
def get_view_interval(self):
return self.upper_interval[0], self.axes.viewLim.intervalx[1]
# This class exists to calculate the separate data range of the
# upper X-axis and draw the spine there. It also provides this range
# to the X-axis artist for ticking and gridlines
class SkewSpine(mspines.Spine):
def __init__(self, axes, spine_type):
if spine_type == 'bottom':
loc = 0.0
else:
loc = 1.0
mspines.Spine.__init__(self, axes, spine_type,
mpath.Path([(13, loc), (13, loc)]))
def _adjust_location(self):
trans = self.axes.transDataToAxes.inverted()
if self.spine_type == 'top':
yloc = 1.0
else:
yloc = 0.0
left = trans.transform_point((0.0, yloc))[0]
right = trans.transform_point((1.0, yloc))[0]
pts = self._path.vertices
pts[0, 0] = left
pts[1, 0] = right
self.axis.upper_interval = (left, right)
# This class handles registration of the skew-xaxes as a projection as well
# as setting up the appropriate transformations. It also overrides standard
# spines and axes instances as appropriate.
class SkewXAxes(Axes):
# The projection must specify a name. This will be used be the
# user to select the projection, i.e. ``subplot(111,
# projection='skewx')``.
name = 'skewx'
def _init_axis(self):
#Taken from Axes and modified to use our modified X-axis
self.xaxis = SkewXAxis(self)
self.spines['top'].register_axis(self.xaxis)
self.spines['bottom'].register_axis(self.xaxis)
self.yaxis = maxis.YAxis(self)
self.spines['left'].register_axis(self.yaxis)
self.spines['right'].register_axis(self.yaxis)
def _gen_axes_spines(self):
spines = {'top': SkewSpine(self, 'top'),
'bottom': mspines.Spine.linear_spine(self, 'bottom'),
'left': mspines.Spine.linear_spine(self, 'left'),
'right': mspines.Spine.linear_spine(self, 'right')}
return spines
def _set_lim_and_transforms(self):
"""
This is called once when the plot is created to set up all the
transforms for the data, text and grids.
"""
rot = 30
#Get the standard transform setup from the Axes base class
Axes._set_lim_and_transforms(self)
# Need to put the skew in the middle, after the scale and limits,
# but before the transAxes. This way, the skew is done in Axes
# 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)))
# Create the full transform from Data to Pixels
self.transData = self.transDataToAxes + self.transAxes
# Blended transforms like this need to have the skewing applied using
# both axes, in axes coords like before.
self._xaxis_transform = (transforms.blended_transform_factory(
self.transScale + self.transLimits,
transforms.IdentityTransform()) +
transforms.Affine2D().skew_deg(rot, 0)) + self.transAxes
# Now register the projection with matplotlib so the user can select
# it.
register_projection(SkewXAxes)
@image_comparison(baseline_images=['skew_axes'], remove_text=True)
def test_set_line_coll_dash_image():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='skewx')
ax.set_xlim(-50, 50)
ax.set_ylim(50, -50)
ax.grid(True)
# An example of a slanted line at constant X
l = ax.axvline(0, color='b')
@image_comparison(baseline_images=['skew_rects'], remove_text=True)
def test_skew_rectange():
fix, axes = plt.subplots(5, 5, sharex=True, sharey=True, figsize=(16, 12))
axes = axes.flat
rotations = list(itertools.product([-3, -1, 0, 1, 3], repeat=2))
axes[0].set_xlim([-4, 4])
axes[0].set_ylim([-4, 4])
axes[0].set_aspect('equal')
for ax, (xrots, yrots) in zip(axes, rotations):
xdeg, ydeg = 45 * xrots, 45 * yrots
t = transforms.Affine2D().skew_deg(xdeg, ydeg)
ax.set_title('Skew of {0} in X and {1} in Y'.format(xdeg, ydeg))
ax.add_patch(mpatch.Rectangle([-1, -1], 2, 2,
transform=t + ax.transData,
alpha=0.5, facecolor='coral'))
plt.subplots_adjust(wspace=0, left=0, right=1, bottom=0)
if __name__ == '__main__':
import nose
nose.runmodule(argv=['-s', '--with-doctest'], exit=False)
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