Source code for cvxpy.atoms.norm1

Copyright 2013 Steven Diamond

This file is part of CVXPY.

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import numpy as np
import scipy.sparse as sp

from cvxpy.atoms.axis_atom import AxisAtom

[docs]class norm1(AxisAtom): _allow_complex = True def numeric(self, values): """Returns the one norm of x. """ if self.axis is None: values = np.array(values[0]).flatten() else: values = np.array(values[0]) return np.linalg.norm(values, 1, axis=self.axis, keepdims=self.keepdims) def sign_from_args(self): """Returns sign (is positive, is negative) of the expression. """ # Always positive. return (True, False) def is_atom_convex(self): """Is the atom convex? """ return True def is_atom_concave(self): """Is the atom concave? """ return False def is_incr(self, idx): """Is the composition non-decreasing in argument idx? """ return self.args[0].is_nonneg() def is_decr(self, idx): """Is the composition non-increasing in argument idx? """ return self.args[0].is_nonpos() def is_pwl(self): """Is the atom piecewise linear? """ return self.args[0].is_pwl() def get_data(self): return [self.axis] def name(self): return "%s(%s)" % (self.__class__.__name__, self.args[0].name()) def _domain(self): """Returns constraints describing the domain of the node. """ return [] def _grad(self, values): """Gives the (sub/super)gradient of the atom w.r.t. each argument. Matrix expressions are vectorized, so the gradient is a matrix. Args: values: A list of numeric values for the arguments. Returns: A list of SciPy CSC sparse matrices or None. """ return self._axis_grad(values) def _column_grad(self, value): """Gives the (sub/super)gradient of the atom w.r.t. a column argument. Matrix expressions are vectorized, so the gradient is a matrix. Args: value: A numeric value for a column. Returns: A NumPy ndarray matrix or None. """ rows = self.args[0].size D_null = sp.csc_matrix((rows, 1), dtype='float64') D_null += (value > 0) D_null -= (value < 0) return sp.csc_matrix(D_null.A.ravel(order='F')).T