def broadcast(lh_expr, rh_expr):
"""Broacast the binary operator.
"""
lh_expr = Expression.cast_to_const(lh_expr)
rh_expr = Expression.cast_to_const(rh_expr)
if lh_expr.is_scalar() and not rh_expr.is_scalar():
lh_expr = cvxtypes.promote()(lh_expr, rh_expr.shape)
elif rh_expr.is_scalar() and not lh_expr.is_scalar():
rh_expr = cvxtypes.promote()(rh_expr, lh_expr.shape)
# Broadcasting.
if lh_expr.ndim == 2 and rh_expr.ndim == 2:
# Replicate dimensions of size 1.
dims = [max(lh_expr.shape[i], rh_expr.shape[i]) for i in range(2)]
# Broadcast along dim 0.
if lh_expr.shape[0] == 1 and lh_expr.shape[0] < dims[0]:
lh_expr = np.ones((dims[0], 1)) @ lh_expr
if rh_expr.shape[0] == 1 and rh_expr.shape[0] < dims[0]:
rh_expr = np.ones((dims[0], 1)) @ rh_expr
# Broadcast along dim 1.
if lh_expr.shape[1] == 1 and lh_expr.shape[1] < dims[1]:
lh_expr = lh_expr @ np.ones((1, dims[1]))
if rh_expr.shape[1] == 1 and rh_expr.shape[1] < dims[1]:
rh_expr = rh_expr @ np.ones((1, dims[1]))
return lh_expr, rh_expr
def __init__(self, x, y, z, alpha, constr_id=None) -> None:
Expression = cvxtypes.expression()
self.x = Expression.cast_to_const(x)
self.y = Expression.cast_to_const(y)
self.z = Expression.cast_to_const(z)
for val in [self.x, self.y, self.z]:
if not (val.is_affine() and val.is_real()):
raise ValueError('All arguments must be affine and real.')
alpha = Expression.cast_to_const(alpha)
if alpha.is_scalar():
alpha = cvxtypes.promote()(alpha, self.x.shape)
self.alpha = alpha
if np.any(self.alpha.value <= 0) or np.any(self.alpha.value >= 1):
msg = "Argument alpha must have entries in the open interval (0, 1)."
raise ValueError(msg)
arg_shapes = [self.x.shape, self.y.shape, self.z.shape, self.alpha.shape]
if any(arg_shapes[0] != s for s in arg_shapes[1:]):
msg = ("All arguments must have the same shapes. Provided arguments have"
"shapes %s" % str(arg_shapes))
raise ValueError(msg)
super(PowCone3D, self).__init__([self.x, self.y, self.z],
constr_id)
