Source code for cvxpy.atoms.affine.upper_tri

Copyright 2013 Steven Diamond

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

[docs]class upper_tri(AffAtom): """The vectorized strictly upper triagonal entries. """ def __init__(self, expr): super(upper_tri, self).__init__(expr) @AffAtom.numpy_numeric def numeric(self, values): """Vectorize the upper triagonal entries. """ value = np.zeros(self.shape[0]) count = 0 for i in range(values[0].shape[0]): for j in range(values[0].shape[1]): if i < j: value[count] = values[0][i, j] count += 1 return value def validate_arguments(self): """Checks that the argument is a square matrix. """ if not self.args[0].ndim == 2 or self.args[0].shape[0] != self.args[0].shape[1]: raise ValueError( "Argument to upper_tri must be a square matrix." ) def shape_from_args(self): """A vector. """ rows, cols = self.args[0].shape return (rows*(cols-1)//2, 1) def is_atom_log_log_convex(self): """Is the atom log-log convex? """ return True def is_atom_log_log_concave(self): """Is the atom log-log concave? """ return True @staticmethod def graph_implementation(arg_objs, shape, data=None): """Vectorized strictly upper triagonal entries. 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.upper_tri(arg_objs[0]), [])