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
grid_helper = GridHelperCurveLinear(
(tr, inv_tr),
extreme_finder=ExtremeFinderSimple(20, 20),
# better tick density
grid_locator1=MaxNLocator(nbins=6),
grid_locator2=MaxNLocator(nbins=6))
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,
origin="lower")
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
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