Usetex demo is slow on windows #15802
Description
Bug report
Bug summary
I just downloaded usetex_demo.html
from
https://matplotlib.org/3.1.1/gallery/text_labels_and_annotations/usetex_demo.html
I did not modify it, nothing at all. I just try to run it.
Code for reproduction
exactly what I downloaded.
Actual outcome
The canvas/figure appears on a window as usual when invoking plt.show() but it has no content and it is unresponsive. I have to kill it, which reports the problem to Microsoft.
Expected outcome
A figure similar to that shown on the documentation.
Matplotlib version
- Operating system: Windows 10, 64
- Matplotlib version:
- Matplotlib backend (
print(matplotlib.get_backend())): TkAgg - Python version: 3.7
- Jupyter version (if applicable): N/A
- Other libraries: numpy #as included in the demo. I load the code into VSCode, then hit F5. My VSCode installation is working fine. Everything runs inside a venv. Typical setup. All packages updated using pip. I installed everything from pip
pip freeze:
altgraph==0.16.1
astroid==2.3.2
cffi==1.13.2
colorama==0.4.1
cryptography==2.8
cx-Freeze==6.0
cycler==0.10.0
future==0.18.2
isort==4.3.21
kiwisolver==1.1.0
lazy-object-proxy==1.4.3
matplotlib==3.1.1
mccabe==0.6.1
numpy==1.17.3
pefile==2019.4.18
plint==0.1
pycparser==2.19
pylint==2.4.3
pyparsing==2.4.2
PyQt5==5.13.2
PyQt5-sip==12.7.0
python-dateutil==2.8.1
pywin32-ctypes==0.2.0
scipy==1.3.1
six==1.12.0
typed-ast==1.4.0
wrapt==1.11.2
"""
Usetex Demo
Shows how to use latex in a plot.
Also, refer to the :doc:/tutorials/text/usetex guide.
This code from: https://matplotlib.org/3.1.1/gallery/text_labels_and_annotations/usetex_demo.html
import numpy as np
import matplotlib.pyplot as plt
plt.rc('text', usetex=True)
# interface tracking profiles
N = 500
delta = 0.6
X = np.linspace(-1, 1, N)
plt.plot(X, (1 - np.tanh(4 * X / delta)) / 2, # phase field tanh profiles
X, (1.4 + np.tanh(4 * X / delta)) / 4, "C2", # composition profile
X, X < 0, 'k--') # sharp interface
# legend
plt.legend(('phase field', 'level set', 'sharp interface'),
shadow=True, loc=(0.01, 0.48), handlelength=1.5, fontsize=16)
# the arrow
plt.annotate("", xy=(-delta / 2., 0.1), xytext=(delta / 2., 0.1),
arrowprops=dict(arrowstyle="<->", connectionstyle="arc3"))
plt.text(0, 0.1, r'$\delta$',
{'color': 'black', 'fontsize': 24, 'ha': 'center', 'va': 'center',
'bbox': dict(boxstyle="round", fc="white", ec="black", pad=0.2)})
# Use tex in labels
plt.xticks((-1, 0, 1), ('$-1$', r'$\pm 0$', '$+1$'), color='k', size=20)
# Left Y-axis labels, combine math mode and text mode
plt.ylabel(r'\bf{phase field} $\phi$', {'color': 'C0', 'fontsize': 20})
plt.yticks((0, 0.5, 1), (r'\bf{0}', r'\bf{.5}', r'\bf{1}'), color='k', size=20)
# Right Y-axis labels
plt.text(1.02, 0.5, r"\bf{level set} $\phi$", {'color': 'C2', 'fontsize': 20},
horizontalalignment='left',
verticalalignment='center',
rotation=90,
clip_on=False,
transform=plt.gca().transAxes)
# Use multiline environment inside a `text`.
# level set equations
eq1 = r"\begin{eqnarray*}" + \
r"|\nabla\phi| &=& 1,\\" + \
r"\frac{\partial \phi}{\partial t} + U|\nabla \phi| &=& 0 " + \
r"\end{eqnarray*}"
plt.text(1, 0.9, eq1, {'color': 'C2', 'fontsize': 18}, va="top", ha="right")
# phase field equations
eq2 = r'\begin{eqnarray*}' + \
r'\mathcal{F} &=& \int f\left( \phi, c \right) dV, \\ ' + \
r'\frac{ \partial \phi } { \partial t } &=& -M_{ \phi } ' + \
r'\frac{ \delta \mathcal{F} } { \delta \phi }' + \
r'\end{eqnarray*}'
plt.text(0.18, 0.18, eq2, {'color': 'C0', 'fontsize': 16})
plt.text(-1, .30, r'gamma: $\gamma$', {'color': 'r', 'fontsize': 20})
plt.text(-1, .18, r'Omega: $\Omega$', {'color': 'b', 'fontsize': 20})
plt.show()