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)
