def curvelinear_test1(fig): """ Grid for custom transform. """ def tr(x, y): x, y = numpy.asarray(x), numpy.asarray(y) return x, y - (2 * x) # return x + (5 * y), (7 * y) + (3 * x) def inv_tr(x, y): x, y = numpy.asarray(x), numpy.asarray(y) return x, y + (2 * x) grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = Subplot(fig, 1, 1, 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([0, 1], [0, 2]) ax1.plot(xx, yy, linewidth=2.0) ax1.set_aspect(1) ax1.set_xlim(-3, 3) ax1.set_ylim(-3, 3) ax1.axis["t"] = ax1.new_floating_axis( 0, 0 ) # first argument appears to be slope, second argument appears to be starting point on vertical ax1.axis["t2"] = ax1.new_floating_axis(1, 0) ax1.axhline(y=0, color='r') ax1.axvline(x=0, color='r') ax1.grid(True, zorder=0)