def clamp(x, xmin, xmax):
"""Constrain a value to lie between two further values, element-wise.
The returned value is computed as `min(max(x, xmin), xmax)`.
The arguments can be scalars or :class:`~taichi.Matrix`,
as long as they can be broadcasted to a common shape.
Args:
x (:mod:`~taichi.types.primitive_types`, :class:`~taichi.Matrix`): Specify
the value to constrain.
y (:mod:`~taichi.types.primitive_types`, :class:`~taichi.Matrix`): Specify
the lower end of the range into which to constrain `x`.
a (:mod:`~taichi.types.primitive_types`, :class:`~taichi.Matrix`): Specify
the upper end of the range into which to constrain `x`.
Returns:
The value of `x` constrained to the range `xmin` to `xmax`.
Example::
>>> v = ti.Vector([0, 0.5, 1.0, 1.5])
>>> ti.clamp(v, 0.5, 1.0)
[0.5, 0.5, 1.0, 1.0]
>>> x = ti.Matrix([[0, 1], [-2, 2]], ti.f32)
>>> y = ti.Matrix([[1, 2], [1, 2]], ti.f32)
>>> ti.clamp(x, 0.5, y)
[[0.5, 1.0], [0.5, 2.0]]
"""
return min(xmax, max(xmin, x))
def __init__(self, *args):
args = list(args)
for i, arg in enumerate(args):
if not isinstance(arg, collections.abc.Sequence):
args[i] = (0, arg)
if len(args[i]) != 2:
raise TaichiSyntaxError(
"Every argument of ndrange should be a scalar or a tuple/list like (begin, end)"
)
args[i] = (args[i][0], ops.max(args[i][0], args[i][1]))
for arg in args:
for bound in arg:
if not isinstance(bound, int) and not (
isinstance(bound, Expr)
and is_integral(bound.ptr.get_ret_type())):
raise TaichiTypeError(
"Every argument of ndrange should be an integer scalar or a tuple/list of (int, int)"
)
self.bounds = args
self.dimensions = [None] * len(args)
for i, bound in enumerate(self.bounds):
self.dimensions[i] = bound[1] - bound[0]
self.acc_dimensions = self.dimensions.copy()
for i in reversed(range(len(self.bounds) - 1)):
self.acc_dimensions[
i] = self.acc_dimensions[i] * self.acc_dimensions[i + 1]
if len(self.acc_dimensions
) == 0: # for the empty case, e.g. ti.ndrange()
self.acc_dimensions = [1]