顺时针极坐标图，顶部为0度。

Question

我该如何制作一个顺时针的极坐标图？有人提出了类似的问题在这里：如何使matplotlib极坐标图中的角度顺时针，上方为0度？，但是我不理解。

import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
ax.grid(True)

theta = np.arange(0,370,10)
theta = [i*np.pi/180.0 for i in theta]  # convert to radians

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()

编辑：

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.projections import PolarAxes, register_projection
from matplotlib.transforms import Affine2D, Bbox, IdentityTransform

class NorthPolarAxes(PolarAxes):
    '''
    A variant of PolarAxes where theta starts pointing north and goes
    clockwise.
    '''
    name = 'northpolar'

    class NorthPolarTransform(PolarAxes.PolarTransform):
        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.sin(t)
            y[:] = r * np.cos(t)
            return xy

        transform_non_affine = transform

        def inverted(self):
            return NorthPolarAxes.InvertedNorthPolarTransform()

    class InvertedNorthPolarTransform(PolarAxes.InvertedPolarTransform):
        def transform(self, xy):
            x = xy[:, 0:1]
            y = xy[:, 1:]
            r = np.sqrt(x*x + y*y)

fig = plt.figure()
register_projection(NorthPolarAxes)
ax=plt.subplot(1, 1, 1, projection='northpolar')    
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()

如何正确使用register_projection(NorthPolarAxes)？

- kame

Answer 1

添加以下这些行：

ax.set_theta_direction(-1)
ax.set_theta_offset(pi/2.0)

- Pavel

Answer 2

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

更易理解一些。

- gbronner

Answer 3

编辑：请注意，Pavel提供了更好的解决方案！

---

您提供的SO问题包含答案。这是一个稍微修改过的ptomato's NorthPolarAxes class版本，其中theta=0指向东方并顺时针增加：

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://dev59.com/o3E95IYBdhLWcg3wMa91
    https://dev59.com/5Gsz5IYBdhLWcg3wxq4V    
    '''
    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()

---

< p > 我认为从 matplotlib/projections/polar.py 的 PolarTransform 和 InvertedPolarTransform 中添加文档字符串是有帮助的，因为它们有助于解释每个组件正在执行的操作。这可以指导您更改公式。

要获得顺时针行为，只需更改t --> -t:

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

在InvertedEastPolarTransform中，当y > 0（上半平面）时，我们希望使用2 * npy.pi - theta，而不是当y < 0时。

- unutbu