Source code for cvxpy.atoms.affine.promote

"""
Copyright 2013 Steven Diamond

This file is part of CVXPY.

CVXPY is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

CVXPY is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with CVXPY.  If not, see <http://www.gnu.org/licenses/>.
"""

from cvxpy.atoms.affine.affine_atom import AffAtom
from cvxpy.expressions.expression import Expression
import cvxpy.lin_ops.lin_utils as lu
import numpy as np


[docs]def promote(expr, shape): """ Promote a scalar expression to a vector/matrix. Parameters ---------- expr : Expression The expression to promote. shape : tuple The shape to promote to. Raises ------ ValueError If ``expr`` is not a scalar. """ expr = Expression.cast_to_const(expr) if expr.shape != shape: if not expr.is_scalar(): raise ValueError('Only scalars may be promoted.') return Promote(expr, shape) else: return expr
class Promote(AffAtom): """ Promote a scalar expression to a vector/matrix. Attributes ---------- expr : Expression The expression to promote. shape : tuple The shape to promote to. """ def __init__(self, expr, shape): self.promoted_shape = shape super(Promote, self).__init__(expr) @AffAtom.numpy_numeric def numeric(self, values): """Promotes the value. """ return np.ones(self.promoted_shape) * values[0] def is_symmetric(self): """Is the expression symmetric? """ return self.ndim == 2 and self.shape[0] == self.shape[1] def shape_from_args(self): """Returns the (row, col) shape of the expression. """ return self.promoted_shape def get_data(self): """Returns info needed to reconstruct the expression besides the args. """ return [self.promoted_shape] @staticmethod def graph_implementation(arg_objs, shape, data=None): """Promote scalar to vector/matrix Parameters ---------- arg_objs : list LinExpr for each argument. shape : tuple The shape of the resulting expression. data : Additional data required by the atom. Returns ------- tuple (LinOp for objective, list of constraints) """ return (lu.promote(arg_objs[0], shape), [])