def __call__(self, value, clip=None):
if clip is None:
clip = self.clip
if cbook.iterable(value):
vtype = 'array'
val = ma.asarray(value).astype(npy.float)
else:
vtype = 'scalar'
val = ma.array([value]).astype(npy.float)
self.autoscale_None(val)
vmin, vmax = self.vmin, self.vmax
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin<=0:
raise ValueError("values must all be positive")
elif vmin==vmax:
return 0.0 * val
else:
if clip:
mask = ma.getmask(val)
val = ma.array(npy.clip(val.filled(vmax), vmin, vmax),
mask=mask)
result = (ma.log(val)-npy.log(vmin))/(npy.log(vmax)-npy.log(vmin))
if vtype == 'scalar':
result = result[0]
return result
def __call__(self, value, clip=None):
if clip is None:
clip = self.clip
if cbook.iterable(value):
vtype = 'array'
val = ma.asarray(value).astype(npy.float)
else:
vtype = 'scalar'
val = ma.array([value]).astype(npy.float)
self.autoscale_None(val)
vmin, vmax = self.vmin, self.vmax
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin <= 0:
raise ValueError("values must all be positive")
elif vmin == vmax:
return 0.0 * val
else:
if clip:
mask = ma.getmask(val)
val = ma.array(npy.clip(val.filled(vmax), vmin, vmax),
mask=mask)
result = (ma.log(val) - npy.log(vmin)) / (npy.log(vmax) -
npy.log(vmin))
if vtype == 'scalar':
result = result[0]
return result
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = 10 * (Z1 - Z2)
# interior badmask doesn't work yet for filled contours
if test_masking:
badmask = zeros(shape(Z))
badmask[5,5] = 1
badmask[5,6] = 1
Z[5,5] = 0
Z[5,6] = 0
badmask[0,0] = 1
Z[0,0] = 0
Z = ma.array(Z, mask=badmask)
# We are using automatic selection of contour levels;
# this is usually not such a good idea, because they don't
# occur on nice boundaries, but we do it here for purposes
# of illustration.
CS = contourf(X, Y, Z, 10, # [-1, -0.1, 0, 0.1],
#alpha=0.5,
cmap=cm.bone,
origin=origin)
# Note that in the following, we explicitly pass in a subset of
# the contour levels used for the filled contours. Alternatively,
# We could pass in additional levels to provide extra resolution.
CS2 = contour(X, Y, Z, CS.levels[::2],