Matplotlib chart does not display in PyCharm

60,081

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))

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william007
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william007

Updated on August 19, 2021

Comments

  • william007
    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 with Process 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()