Square scale using matplotlib / python

Question

I want to make a square root scale graph using Python:

However, I have no idea how to do this. Matplotlib allows you to do log scale, but in this case I need something like a power scale.

Answer 1

You can make your own ScaleBaseclass for this. I modified the example from here (which made a square scale, not a square scale) for your purposes. Also see the documentation here .

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import matplotlib.scale as mscale
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import matplotlib.ticker as ticker
import numpy as np

class SquareRootScale(mscale.ScaleBase):
    """
    ScaleBase class for generating square root scale.
    """

    name = 'squareroot'

    def __init__(self, axis, **kwargs):
        mscale.ScaleBase.__init__(self)

    def set_default_locators_and_formatters(self, axis):
        axis.set_major_locator(ticker.AutoLocator())
        axis.set_major_formatter(ticker.ScalarFormatter())
        axis.set_minor_locator(ticker.NullLocator())
        axis.set_minor_formatter(ticker.NullFormatter())

    def limit_range_for_scale(self, vmin, vmax, minpos):
        return  max(0., vmin), vmax

    class SquareRootTransform(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def transform_non_affine(self, a): 
            return np.array(a)**0.5

        def inverted(self):
            return SquareRootScale.InvertedSquareRootTransform()

    class InvertedSquareRootTransform(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def transform(self, a):
            return np.array(a)**2

        def inverted(self):
            return SquareRootScale.SquareRootTransform()

    def get_transform(self):
        return self.SquareRootTransform()

mscale.register_scale(SquareRootScale)

fig, ax = plt.subplots(1)

ax.plot(np.arange(0, 9)**2, label='$y=x^2$')
ax.legend()

ax.set_yscale('squareroot')
ax.set_yticks(np.arange(0,9,2)**2)
ax.set_yticks(np.arange(0,8.5,0.5)**2, minor=True)

plt.show()

Answer 2

lolopop tom, set_yticks set_yticklabels, :

x = np.arange(2, 15, 2)
y = x * x

fig = plt.figure()
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

ax1.plot(x,y)

ax2.plot(x, np.sqrt(y))
ax2.set_yticks([2,4,6,8,10,12,14])
ax2.set_yticklabels(['4','16','36','64','100','144','196'])