def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = 'scalar'
val = array([value])
else:
vtype = 'array'
val = asarray(value)
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None: vmin = nxmin(rval)
if vmax is None: vmax = nxmax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin==vmax:
return 0.*value
else:
val = where(val<vmin, vmin, val)
val = where(val>vmax, vmax, val)
result = (1.0/(vmax-vmin))*(val-vmin)
if vtype == 'scalar':
result = result[0]
return result
def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = 'scalar'
val = array([value])
else:
vtype = 'array'
val = asarray(value)
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None: vmin = nxmin(rval)
if vmax is None: vmax = nxmax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin==vmax:
return 0.*value
else:
val = where(val<vmin, vmin, val)
val = where(val>vmax, vmax, val)
result = (1.0/(vmax-vmin))*(val-vmin)
if vtype == 'scalar':
result = result[0]
return result
def autoscale(self, A):
if not self.scaled():
rval = ravel(A)
if self.vmin is None: self.vmin = nxmin(rval)
if self.vmax is None: self.vmax = nxmax(rval)
def autoscale(self, A):
if not self.scaled():
rval = ravel(A)
if self.vmin is None: self.vmin = nxmin(rval)
if self.vmax is None: self.vmax = nxmax(rval)
