# 演示Curvelinear网格2 自定义网格和记号行。 此示例演示如何通过在网格上应用转换,使用GridHelperCurve线性来定义自定义网格和注释行。作为打印上的演示,轴上将显示5x5矩阵。 ![Curvelinear网格2示例](https://matplotlib.org/_images/sphx_glr_demo_curvelinear_grid2_001.png) ```python import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.axisartist.grid_helper_curvelinear import \ GridHelperCurveLinear from mpl_toolkits.axisartist.axislines import Subplot import mpl_toolkits.axisartist.angle_helper as angle_helper def curvelinear_test1(fig): """ grid for custom transform. """ def tr(x, y): sgn = np.sign(x) x, y = np.abs(np.asarray(x)), np.asarray(y) return sgn*x**.5, y def inv_tr(x, y): sgn = np.sign(x) x, y = np.asarray(x), np.asarray(y) return sgn*x**2, y extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=None, lat_cycle=None, # (0, np.inf), lon_minmax=None, lat_minmax=None, ) grid_helper = GridHelperCurveLinear((tr, inv_tr), extreme_finder=extreme_finder) ax1 = Subplot(fig, 111, grid_helper=grid_helper) # ax1 will have a ticks and gridlines defined by the given # transform (+ transData of the Axes). Note that the transform of # the Axes itself (i.e., transData) is not affected by the given # transform. fig.add_subplot(ax1) ax1.imshow(np.arange(25).reshape(5, 5), vmax=50, cmap=plt.cm.gray_r, interpolation="nearest", origin="lower") # tick density grid_helper.grid_finder.grid_locator1._nbins = 6 grid_helper.grid_finder.grid_locator2._nbins = 6 if 1: fig = plt.figure(1, figsize=(7, 4)) fig.clf() curvelinear_test1(fig) plt.show() ``` ## 下载这个示例 - [下载python源码: demo_curvelinear_grid2.py](https://matplotlib.org/_downloads/demo_curvelinear_grid2.py) - [下载Jupyter notebook: demo_curvelinear_grid2.ipynb](https://matplotlib.org/_downloads/demo_curvelinear_grid2.ipynb)