The minimum of an expression.
MinEntries(x, axis = NA_real_, keepdims = FALSE)# S4 method for MinEntries
to_numeric(object, values)
# S4 method for MinEntries
sign_from_args(object)
# S4 method for MinEntries
is_atom_convex(object)
# S4 method for MinEntries
is_atom_concave(object)
# S4 method for MinEntries
is_atom_log_log_convex(object)
# S4 method for MinEntries
is_atom_log_log_concave(object)
# S4 method for MinEntries
is_incr(object, idx)
# S4 method for MinEntries
is_decr(object, idx)
# S4 method for MinEntries
is_pwl(object)
# S4 method for MinEntries
.grad(object, values)
# S4 method for MinEntries
.column_grad(object, value)
(Optional) The dimension across which to apply the function: 1
indicates rows, 2
indicates columns, and NA
indicates rows and columns. The default is NA
.
(Optional) Should dimensions be maintained when applying the atom along an axis? If FALSE
, result will be collapsed into an \(n x 1\) column vector. The default is FALSE
.
A list of numeric values for the arguments
An index into the atom.
A numeric value
to_numeric
: The largest entry in x
.
sign_from_args
: The sign of the atom.
is_atom_convex
: The atom is not convex.
is_atom_concave
: The atom is concave.
is_atom_log_log_convex
: Is the atom log-log convex?
is_atom_log_log_concave
: Is the atom log-log concave?
is_incr
: The atom is weakly increasing in every argument.
is_decr
: The atom is not weakly decreasing in any argument.
is_pwl
: Is x
piecewise linear?
.grad
: Gives the (sub/super)gradient of the atom w.r.t. each variable
.column_grad
: Gives the (sub/super)gradient of the atom w.r.t. each column variable
axis
(Optional) The dimension across which to apply the function: 1
indicates rows, 2
indicates columns, and NA
indicates rows and columns. The default is NA
.
keepdims
(Optional) Should dimensions be maintained when applying the atom along an axis? If FALSE
, result will be collapsed into an \(n x 1\) column vector. The default is FALSE
.