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Convert SubplotZero example into centered-spines-with-arrows recipe. #17170

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Convert SubplotZero example into centered-spines-with-arrows recipe. #17170

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32 changes: 0 additions & 32 deletions examples/axisartist/demo_axisline_style.py
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58 changes: 58 additions & 0 deletions examples/recipes/centered_spines_with_arrows.py
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"""
===========================
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()