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!

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 pltimport numpy as npimport matplotlib.projections as projectionsimport matplotlib.transforms as mtransformsclass 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.