我发现了-matplotlib允许您创建自定义投影。我创建了一个继承自的代码
PolarAxes。
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.projections import PolarAxes, register_projectionfrom matplotlib.transforms import Affine2D, Bbox, IdentityTransformclass 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) theta = np.arctan2(y, x) return np.concatenate((theta, r), 1) def inverted(self): return NorthPolarAxes.NorthPolarTransform() def _set_lim_and_transforms(self): PolarAxes._set_lim_and_transforms(self) self.transProjection = self.NorthPolarTransform() self.transData = (self.transScale + self.transProjection + (self.transProjectionAffine + self.transAxes)) self._xaxis_transform = (self.transProjection + self.PolarAffine(IdentityTransform(), Bbox.unit()) + self.transAxes) self._xaxis_text1_transform = (self._theta_label1_position + self._xaxis_transform) self._yaxis_transform = (Affine2D().scale(np.pi * 2.0, 1.0) + self.transData) self._yaxis_text1_transform = (self._r_label1_position + Affine2D().scale(1.0 / 360.0, 1.0) + self._yaxis_transform)register_projection(NorthPolarAxes)angle = np.arange(0, 360, 10, dtype=float) * np.pi / 180.0arbitrary_data = (np.abs(np.sin(angle)) + 0.1 * (np.random.random_sample(size=angle.shape) - 0.5))plt.clf()plt.subplot(1, 1, 1, projection='northpolar')plt.plot(angle, arbitrary_data)plt.show()
