Apr 17, 2020
diff --git a/examples/axisartist/demo_axisline_style.py b/examples/axisartist/demo_axisline_style.py
diff --git a/examples/recipes/centered_spines_with_arrows.py b/examples/recipes/centered_spines_with_arrows.py
 """
 ===========================
 Centered spines with arrows
 ===========================

 This examples shows two ways to draw a "math textbook" style plot, where the
 spines ("axes lines") are drawn at ``x = 0`` and ``y = 0``, and have arrows at
 their ends.
 """

 import matplotlib.pyplot as plt
 from mpl_toolkits.axisartist.axislines import SubplotZero
 import numpy as np


 fig, ax = plt.subplots()
 # Move the left and bottom spines to x = 0 and y = 0, respectively.
 ax.spines["left"].set_position(("data", 0))
 ax.spines["bottom"].set_position(("data", 0))
 # Hide the top and right spines.
 ax.spines["top"].set_visible(False)
 ax.spines["right"].set_visible(False)

 # Draw arrows (as black triangles: ">k"/"^k") at the end of the axes.  In each
 # case, one of the coordinates (0) is a data coordinate (i.e., y = 0 or x = 0,
 # respectively) and the other one (1) is an axes coordinate (i.e., at the very
 # right/top of the axes).  Also, disable clipping (clip_on=False) as the marker
 # actually spills out of the axes.
 ax.plot(1, 0, ">k", transform=ax.get_yaxis_transform(), clip_on=False)
 ax.plot(0, 1, "^k", transform=ax.get_xaxis_transform(), clip_on=False)

 # Some sample data.
 x = np.linspace(-0.5, 1., 100)
 ax.plot(x, np.sin(x*np.pi))

 ###############################################################################
 # Alternatively, one can use mpl_toolkit's SubplotZero, but note that many
 # standard Matplotlib options (e.g. rcParams) have no effect.

 fig = plt.figure()
 ax = SubplotZero(fig, 111)
 fig.add_subplot(ax)

 for direction in ["xzero", "yzero"]:
    # adds arrows at the ends of each axis
    ax.axis[direction].set_axisline_style("-|>")
    # adds X and Y-axis from the origin
    ax.axis[direction].set_visible(True)

 for direction in ["left", "right", "bottom", "top"]:
    # hides borders
    ax.axis[direction].set_visible(False)

 x = np.linspace(-0.5, 1., 100)
 ax.plot(x, np.sin(x*np.pi))


 plt.show()
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,58 @@
		"""
		===========================
		Centered spines with arrows
		===========================

		This examples shows two ways to draw a "math textbook" style plot, where the
		spines ("axes lines") are drawn at ``x = 0`` and ``y = 0``, and have arrows at
		their ends.
		"""

		import matplotlib.pyplot as plt
		from mpl_toolkits.axisartist.axislines import SubplotZero
		import numpy as np


		fig, ax = plt.subplots()
		# Move the left and bottom spines to x = 0 and y = 0, respectively.
		ax.spines["left"].set_position(("data", 0))
		ax.spines["bottom"].set_position(("data", 0))
		# Hide the top and right spines.
		ax.spines["top"].set_visible(False)
		ax.spines["right"].set_visible(False)

		# Draw arrows (as black triangles: ">k"/"^k") at the end of the axes. In each
		# case, one of the coordinates (0) is a data coordinate (i.e., y = 0 or x = 0,
		# respectively) and the other one (1) is an axes coordinate (i.e., at the very
		# right/top of the axes). Also, disable clipping (clip_on=False) as the marker
		# actually spills out of the axes.
		ax.plot(1, 0, ">k", transform=ax.get_yaxis_transform(), clip_on=False)
		ax.plot(0, 1, "^k", transform=ax.get_xaxis_transform(), clip_on=False)

		# Some sample data.
		x = np.linspace(-0.5, 1., 100)
		ax.plot(x, np.sin(x*np.pi))

		###############################################################################
		# Alternatively, one can use mpl_toolkit's SubplotZero, but note that many
		# standard Matplotlib options (e.g. rcParams) have no effect.

		fig = plt.figure()
		ax = SubplotZero(fig, 111)
		fig.add_subplot(ax)

		for direction in ["xzero", "yzero"]:
		# adds arrows at the ends of each axis
		ax.axis[direction].set_axisline_style("-\|>")
		# adds X and Y-axis from the origin
		ax.axis[direction].set_visible(True)

		for direction in ["left", "right", "bottom", "top"]:
		# hides borders
		ax.axis[direction].set_visible(False)

		x = np.linspace(-0.5, 1., 100)
		ax.plot(x, np.sin(x*np.pi))


		plt.show()