def replace_var(expr, old_var_id, new_var):
if (expr.expression_type == Expression.VARIABLE
and expr.variable.variable_id == old_var_id):
return new_var
return expression.from_proto(
expr.proto,
[replace_var(arg, old_var_id, new_var) for arg in expr.arg], expr.data)
def replace_var(expr, old_var_id, new_var):
if (expr.expression_type == Expression.VARIABLE and
expr.variable.variable_id == old_var_id):
return new_var
return expression.from_proto(
expr.proto,
[replace_var(arg, old_var_id, new_var) for arg in expr.arg])
def transform_expr(expr, constrs):
expr = expression.from_proto(
expr.proto,
[transform_expr(arg, constrs) for arg in expr.arg])
f_name = "transform_" + Expression.Type.Name(expr.expression_type).lower()
if f_name in globals():
return globals()[f_name](expr, constrs)
return expr
def transform_linear_map(expr, constrs):
if expr.arg[0].expression_type == Expression.LINEAR_MAP:
# TODO(mwytock): need more complete logic here, i.e. need to do type
# inference across the entire chain using something like affine_props
A = affine.LinearMapType(expr.linear_map)
B = affine.LinearMapType(expr.arg[0].linear_map)
if ((A.kronecker_product or B.kronecker_product) and
not (A*B).kronecker_product):
t, epi_constrs = epi_transform(expr.arg[0], "split_linear_map")
constrs += [linear.transform_expr(x) for x in epi_constrs]
return expression.from_proto(expr.proto, [t], expr.data)
return expr
def transform_expr(expr):
log_debug_expr("conic transform_expr", expr)
constrs = []
transformed_args = []
for arg in expr.arg:
obj_arg, constr = transform_expr(arg)
transformed_args.append(obj_arg)
constrs += constr
# Create the same expression but now with linear arguments.
obj_linear = expression.from_proto(expr.proto, transformed_args)
if not obj_linear.dcp_props.affine:
f_name = ("transform_" +
Expression.Type.Name(obj_linear.expression_type).lower())
if f_name not in globals():
raise TransformError("No conic transform", expr)
obj_linear, constr = globals()[f_name](obj_linear)
constrs += constr
return obj_linear, constrs
def transform_expr(expr):
log_debug_expr("conic transform_expr", expr)
constrs = []
transformed_args = []
for arg in expr.arg:
obj_arg, constr = transform_expr(arg)
transformed_args.append(obj_arg)
constrs += constr
# Create the same expression but now with linear arguments.
obj_linear = expression.from_proto(expr.proto, transformed_args, expr.data)
if not obj_linear.dcp_props.affine:
f_name = ("transform_" +
Expression.Type.Name(obj_linear.expression_type).lower())
if f_name not in globals():
raise TransformError("No conic transform", expr)
obj_linear, constr = globals()[f_name](obj_linear)
constrs += constr
return obj_linear, constrs
