Source code for cvxpy.atoms.affine.hstack

Copyright 2013 Steven Diamond

Licensed under the Apache License, Version 2.0 (the "License");
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import cvxpy.lin_ops.lin_utils as lu
from cvxpy.atoms.affine.affine_atom import AffAtom
import numpy as np

[docs]def hstack(arg_list): """Horizontal concatenation of an arbitrary number of Expressions. Parameters ---------- arg_list : list of Expression The Expressions to concatenate. """ arg_list = [AffAtom.cast_to_const(arg) for arg in arg_list] for idx, arg in enumerate(arg_list): if arg.ndim == 0: arg_list[idx] = arg.flatten() return Hstack(*arg_list)
class Hstack(AffAtom): """ Horizontal concatenation """ def is_atom_log_log_convex(self): return True def is_atom_log_log_concave(self): return True # Returns the hstack of the values. def numeric(self, values): return np.hstack(values) # The shape is the common width and the sum of the heights. def shape_from_args(self): if self.args[0].ndim == 1: return (sum(arg.size for arg in self.args),) else: cols = sum(arg.shape[1] for arg in self.args) return (self.args[0].shape[0], cols) + self.args[0].shape[2:] # All arguments must have the same width. def validate_arguments(self): model = self.args[0].shape error = ValueError(("All the input dimensions except" " for axis 1 must match exactly.")) for arg in self.args[1:]: if len(arg.shape) != len(model): raise error elif len(model) > 1: for i in range(len(model)): if i != 1 and arg.shape[i] != model[i]: raise error @staticmethod def graph_implementation(arg_objs, shape, data=None): """Stack the expressions horizontally. 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.hstack(arg_objs, shape), [])