.. _axes_grid-demo_curvelinear_grid: axes_grid example code: demo_curvelinear_grid.py ================================================ .. plot:: /home/tcaswell/src/p/matplotlib/doc/mpl_examples/axes_grid/demo_curvelinear_grid.py :: """ Custom grid and ticklines. This example demonstrates how to use GridHelperCurveLinear to define custom grids and ticklines by applying a transformation on the grid. This can be used, as showcase on the second plot, to create polar projections in a rectangular box. """ import numpy as np import matplotlib.pyplot as plt import matplotlib.cbook as cbook from mpl_toolkits.axisartist import Subplot from mpl_toolkits.axisartist import SubplotHost, \ ParasiteAxesAuxTrans from mpl_toolkits.axisartist.grid_helper_curvelinear import \ GridHelperCurveLinear def curvelinear_test1(fig): """ grid for custom transform. """ def tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y - x def inv_tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y + x grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = Subplot(fig, 1, 2, 1, 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) xx, yy = tr([3, 6], [5.0, 10.]) ax1.plot(xx, yy, linewidth=2.0) ax1.set_aspect(1.) ax1.set_xlim(0, 10.) ax1.set_ylim(0, 10.) ax1.axis["t"] = ax1.new_floating_axis(0, 3.) ax1.axis["t2"] = ax1.new_floating_axis(1, 7.) ax1.grid(True, zorder=0) import mpl_toolkits.axisartist.angle_helper as angle_helper from matplotlib.projections import PolarAxes from matplotlib.transforms import Affine2D def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) # Find a grid values appropriate for the coordinate (degree, # minute, second). tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") # note that ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) intp = cbook.simple_linear_interpolation ax2.plot(intp(np.array([0, 30]), 50), intp(np.array([10., 10.]), 50), linewidth=2.0) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True, zorder=0) if 1: fig = plt.figure(1, figsize=(7, 4)) fig.clf() curvelinear_test1(fig) curvelinear_test2(fig) plt.draw() plt.show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)