Ndtyjky

Got this in my code with matplotlib library:

ax.spines['top'].set_visible(False)

ax.spines['right'].set_visible(False)

ax.spines['bottom'].set_position('zero')

ax.spines['left'].set_position('zero')

and it shows me :

I was expecting axes to cut! How to get cut axes?

Here's the full code:

import matplotlib.pyplot as plt



pgcd = lambda a, b: a if b==0 else pgcd(b, a%b)





def EKG(n):

    ekg = [1, 2]

    i = 2

    while i < n:

        j = 1

        while j in ekg or pgcd(j, ekg[i-1]) == 1:

            j += 1

        ekg.append(j)

        i += 1

    return ekg





supEKG = lambda n: sum(a>n for a in EKG(n))



arr = 

r = range(3, 100)

for n in r:

    arr.append(supEKG(n))





f = plt.figure()

ax = f.add_subplot(1,1,1)

ax.plot(r, arr)



ax.spines['top'].set_visible(False)

ax.spines['right'].set_visible(False)

ax.spines['bottom'].set_position('zero')

ax.spines['left'].set_position('zero')



plt.show()

look at below sample, that will help you to get what you want.

"""

Broken axis example, where the x-axis will have a portion cut out.

"""

import matplotlib.pylab as plt

import numpy as np



x = np.linspace(0, 10, 100)

x[75:] = np.linspace(40, 42.5, 25)



y = np.sin(x)



f, (ax, ax2) = plt.subplots(1, 2, sharey=True, facecolor='w')



# plot the same data on both axes

ax.plot(x, y)

ax2.plot(x, y)



ax.set_xlim(0, 7.5)

ax2.set_xlim(40, 42.5)



# hide the spines between ax and ax2

ax.spines['right'].set_visible(False)

ax2.spines['left'].set_visible(False)

ax.yaxis.tick_left()

ax.tick_params(labelright='off')

ax2.yaxis.tick_right()



# This looks pretty good, and was fairly painless, but you can get that

# cut-out diagonal lines look with just a bit more work. The important

# thing to know here is that in axes coordinates, which are always

# between 0-1, spine endpoints are at these locations (0,0), (0,1),

# (1,0), and (1,1).  Thus, we just need to put the diagonals in the

# appropriate corners of each of our axes, and so long as we use the

# right transform and disable clipping.



d = .015  # how big to make the diagonal lines in axes coordinates

# arguments to pass plot, just so we don't keep repeating them

kwargs = dict(transform=ax.transAxes, color='k', clip_on=False)

ax.plot((1 - d, 1 + d), (-d, +d), **kwargs)

ax.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)



kwargs.update(transform=ax2.transAxes)  # switch to the bottom axes

ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs)

ax2.plot((-d, +d), (-d, +d), **kwargs)



# What's cool about this is that now if we vary the distance between

# ax and ax2 via f.subplots_adjust(hspace=...) or plt.subplot_tool(),

# the diagonal lines will move accordingly, and stay right at the tips

# of the spines they are 'breaking'



plt.show()

this approach was in broken axes.