Source code for cvxpy.atoms.affine.vstack

Copyright 2013 Steven Diamond

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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 vstack(arg_list): """Wrapper on vstack to ensure list argument. """ return Vstack(*arg_list)
class Vstack(AffAtom): """ Vertical concatenation """ 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 # Returns the vstack of the values. @AffAtom.numpy_numeric def numeric(self, values): return np.vstack(values) # The shape is the common width and the sum of the heights. def shape_from_args(self): self.args[0].shape if self.args[0].ndim == 0: return (len(self.args), 1) elif self.args[0].ndim == 1: return (len(self.args), self.args[0].shape[0]) else: rows = sum(arg.shape[0] for arg in self.args) return (rows,) + self.args[0].shape[1:] # All arguments must have the same width. def validate_arguments(self): model = self.args[0].shape for arg in self.args[1:]: if len(arg.shape) != len(model) or \ (len(model) > 1 and model[1:] != arg.shape[1:]) or \ (len(model) <= 1 and model != arg.shape): raise ValueError(("All the input dimensions except" " for axis 0 must match exactly.")) @staticmethod def graph_implementation(arg_objs, shape, data=None): """Stack the expressions vertically. 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.vstack(arg_objs, shape), [])