Matplotlib chart does not display in PyCharm
Solution 1
The %
notation is for magic functions. The particular magic function and argument you reference, %matplotlib inline
, is meant for an IPython notebook session. You will get a syntax error using magic functions in a normal python session.
The %matplotlib
magic function is meant to specify a backend for matplotlib and the argument inline
will produce an error if you are not in an IPython notebook session.
To show your plot you should use plt.show
for an interactive window or plt.savefig
to save it to file. For example,
plt.show()
or
plt.savefig( 'myfig.png' )
Solution 2
plot show with some value, helped in providing the window where I was able to see the image. By default the interactive mode was false. I neeed to turn on the interactive mode.
plt.interactive(True)
Add the plt.show command after plotting the graph.
plt.show(10)
Solution 3
I got my plot to show by selecting Edit Configurations... and under Execution, check the box Run with Python console. I just used plt.tight_layout(). I was not in a Notebook.
Solution 4
if using an IDE such as Pycharm, instead of using '%matplotlib inline'. Try using: (1) 'import matplotlib.pyplot as plt' (2) plt.imshow(argurment(s))
william007
Updated on August 19, 2021Comments
-
william007 over 2 years
I run the following code in PyCharm 3.4.1, and it highlighted
%matplotlib inline
showing syntax error, and I delete the first line, and run, I expect it will prompt me some charts, but it runs normally withProcess finished with exit code 0
, and no charts is showing.My question is: 1. What is
%matplotlib inline
use for; 2. How to let pycharm shows matplotlib chart?%matplotlib inline from IPython.core.pylabtools import figsize import numpy as np from matplotlib import pyplot as plt figsize(11, 9) import scipy.stats as stats dist = stats.beta n_trials = [0, 1, 2, 3, 4, 5, 8, 15, 50, 500] data = stats.bernoulli.rvs(0.5, size=n_trials[-1]) x = np.linspace(0, 1, 100) # For the already prepared, I'm using Binomial's conj. prior. for k, N in enumerate(n_trials): sx = plt.subplot(len(n_trials) / 2, 2, k + 1) plt.xlabel("$p$, probability of heads") \ if k in [0, len(n_trials) - 1] else None plt.setp(sx.get_yticklabels(), visible=False) heads = data[:N].sum() y = dist.pdf(x, 1 + heads, 1 + N - heads) plt.plot(x, y, label="observe %d tosses,\n %d heads" % (N, heads)) plt.fill_between(x, 0, y, color="#348ABD", alpha=0.4) plt.vlines(0.5, 0, 4, color="k", linestyles="--", lw=1) leg = plt.legend() leg.get_frame().set_alpha(0.4) plt.autoscale(tight=True) plt.suptitle("Bayesian updating of posterior probabilities", y=1.02, fontsize=14) plt.tight_layout()