Python: clockwise polar plot

add these strings:

ax.set_theta_direction(-1)

ax.set_theta_offset(pi/2.0)

ax.set_theta_direction(-1) ax.set_theta_zero_location('N')

is slightly more comprehensible.

Edit: Please note that Pavel has provided a much better solution!

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The SO question you linked to contains the answer. Here is a slightly modified version of ptomato's NorthPolarAxes class with theta=0 pointing East and increasing clockwise:

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.projections as projections
import matplotlib.transforms as mtransforms

class EastPolarAxes(projections.PolarAxes):
    '''
    A variant of PolarAxes where theta starts pointing East and goes
    clockwise.
    https://stackoverflow.com/questions/2417794/2433287#2433287
    https://stackoverflow.com/questions/7664153/7664545#7664545    
    '''
    name = 'eastpolar'

    class EastPolarTransform(projections.PolarAxes.PolarTransform):
        """
        The base polar transform.  This handles projection *theta* and
        *r* into Cartesian coordinate space *x* and *y*, but does not
        perform the ultimate affine transformation into the correct
        position.
        """        
        def transform(self, tr):
            xy   = np.zeros(tr.shape, np.float_)
            t    = tr[:, 0:1]
            r    = tr[:, 1:2]
            x    = xy[:, 0:1]
            y    = xy[:, 1:2]
            x[:] = r * np.cos(-t)
            y[:] = r * np.sin(-t)
            return xy

        transform_non_affine = transform

        def inverted(self):
            return EastPolarAxes.InvertedEastPolarTransform()

    class InvertedEastPolarTransform(projections.PolarAxes.InvertedPolarTransform):
        """
        The inverse of the polar transform, mapping Cartesian
        coordinate space *x* and *y* back to *theta* and *r*.
        """        
        def transform(self, xy):
            x = xy[:, 0:1]
            y = xy[:, 1:]
            r = np.sqrt(x*x + y*y)
            theta = npy.arccos(x / r)
            theta = npy.where(y > 0, 2 * npy.pi - theta, theta)
            return np.concatenate((theta, r), 1)

        def inverted(self):
            return EastPolarAxes.EastPolarTransform()

    def _set_lim_and_transforms(self):
        projections.PolarAxes._set_lim_and_transforms(self)
        self.transProjection = self.EastPolarTransform()
        self.transData = (
            self.transScale + 
            self.transProjection + 
            (self.transProjectionAffine + self.transAxes))
        self._xaxis_transform = (
            self.transProjection +
            self.PolarAffine(mtransforms.IdentityTransform(), mtransforms.Bbox.unit()) +
            self.transAxes)
        self._xaxis_text1_transform = (
            self._theta_label1_position +
            self._xaxis_transform)
        self._yaxis_transform = (
            mtransforms.Affine2D().scale(np.pi * 2.0, 1.0) +
            self.transData)
        self._yaxis_text1_transform = (
            self._r_label1_position +
            mtransforms.Affine2D().scale(1.0 / 360.0, 1.0) +
            self._yaxis_transform)

def eastpolar_axes():
    projections.register_projection(EastPolarAxes)
    ax=plt.subplot(1, 1, 1, projection='eastpolar')    
    theta=np.linspace(0,2*np.pi,37)
    x = [3.00001,3,3,3,3,3,3,3,3,3,3,3,3,3,2.5,2,2,2,2,
         2,1.5,1.5,1,1.5,2,2,2.5,2.5,3,3,3,3,3,3,3,3,3]
    ax.plot(theta, x)
    plt.show()

eastpolar_axes()

---

The doc strings from matplotlib/projections/polar.py's PolarTransform and InvertedPolarTransform were added because I think they help explain what each component is doing. That guides you in changing the formulas.

To get clockwise behavior, you simply change t --> -t:

        x[:] = r * np.cos(-t)
        y[:] = r * np.sin(-t)

and in InvertedEastPolarTransform, we want to use 2 * npy.pi - theta when y > 0 (the upper half-plane) instead of when y < 0.