VS2019 Preview; Interactive Window Warning

[Anapo14]

Using VS 16.0.0 Version 4.2 on Windows 10 with Anaconda 2018.12, but the issue also occurs with Anaconda 5.2.0.

I'm attempting to use the Interactive Window to plot a Mandelbrot Set. While the plot still happens in-line, I get the attached warning. I've also attached a screenshot of the ipykernel_launcher.py file that the warning refers to (have a look at lines 6 and 7 of the file).

Warning:

Python File:

[huguesv]

I tried on 2018.12 and don't see the warning. I used this code from our documentation:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 5, 10)
y = x ** 2
plt.plot(x, y, 'r', x, x ** 3, 'g', x, x ** 4, 'b')

@Anapo14 do you see the warning when using that code? If not, can you provide a code snippet (as text) that reproduces the warning?

[Anapo14]

@huguesv I used the sample script above with the 2018.12 environment and I didn't get the warnings. The code I used is here:

import numpy as np
print("Hello World")
#%%

def mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon=2.0):
    X = np.linspace(xmin, xmax, xn, dtype=np.float32)
    Y = np.linspace(ymin, ymax, yn, dtype=np.float32)
    C = X + Y[:, None]*1j
    N = np.zeros(C.shape, dtype=int)
    Z = np.zeros(C.shape, np.complex64)
    for n in range(maxiter):
        I = np.less(abs(Z), horizon)
        N[I] = n
        Z[I] = Z[I]**2 + C[I]
    N[N == maxiter-1] = 0
    return Z, N

#%% 

if __name__ == '__main__':
    import time
    import matplotlib
    from matplotlib import colors
    import matplotlib.pyplot as plt

    xmin, xmax, xn = -2.25, +0.75, 3000/2
    ymin, ymax, yn = -1.25, +1.25, 2500/2
    maxiter = 200
    horizon = 2.0 ** 40
    log_horizon = np.log(np.log(horizon))/np.log(2)
    Z, N = mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon)

    # Normalized recount as explained in:
    # https://linas.org/art-gallery/escape/smooth.html
    # https://www.ibm.com/developerworks/community/blogs/jfp/entry/My_Christmas_Gift

    # This line will generate warnings for null values but it is faster to
    # process them afterwards using the nan_to_num
    with np.errstate(invalid='ignore'):
        M = np.nan_to_num(N + 1 -
                          np.log(np.log(abs(Z)))/np.log(2) +
                          log_horizon)

    dpi = 72
    width = 10
    height = 10*yn/xn
    fig = plt.figure(figsize=(width, height), dpi=dpi)
    ax = fig.add_axes([0.0, 0.0, 1.0, 1.0], frameon=False, aspect=1)

    # Shaded rendering
    light = colors.LightSource(azdeg=315, altdeg=10)
    M = light.shade(M, cmap=plt.cm.hot, vert_exag=1.5,
                    norm=colors.PowerNorm(0.3), blend_mode='hsv')
    plt.imshow(M, extent=[xmin, xmax, ymin, ymax], interpolation="bicubic")
    ax.set_xticks([])
    ax.set_yticks([])

    #%%
    # Some advertisement for matplotlib
    year = time.strftime("%Y")
    major, minor, micro = matplotlib.__version__.split('.', 2)
    text = ("The Mandelbrot fractal set\n"
            "Rendered with matplotlib %s.%s, %s - http://matplotlib.org"
            % (major, minor, year))
    ax.text(xmin+.025, ymin+.025, text, color="white", fontsize=12, alpha=0.5)
    #%%
    plt.show()

It's sample code from the matplotlib gallery! Note: that even when I run this code from the 2018.12 environment, I still can reproduce the error.

[huguesv]

Closing as an IPython issue (this can be reproduced in Jupyter notebook).