def get_integer(
self, tree: Union[ast.Primary, ast.ComponentRef, ast.Expression,
ast.Slice]
) -> Union[int, ca.MX, np.ndarray]:
# CasADi needs to know the dimensions of symbols at instantiation.
# We therefore need a mechanism to evaluate expressions that define dimensions of symbols.
if isinstance(tree, ast.Primary):
return None if tree.value is None else int(tree.value)
if isinstance(tree, ast.ComponentRef):
s = self.current_class.symbols[tree.name]
assert (s.type.name == 'Integer')
return self.get_integer(s.value)
if isinstance(tree, ast.Expression):
# Make sure that the expression has been converted to MX by (re)visiting the
# relevant part of the AST.
ast_walker = TreeWalker()
ast_walker.walk(self, tree)
# Obtain expression
expr = self.get_mx(tree)
# Obtain the symbols it depends on
free_vars = ca.symvar(expr)
# Find the values of the symbols
vals = []
for free_var in free_vars:
if free_var.is_symbolic():
if (len(self.for_loops) > 0) and (
free_var.name() == self.for_loops[-1].name):
vals.append(self.for_loops[-1].index_variable)
else:
vals.append(
self.get_integer(self.current_class.symbols[
free_var.name()].value))
# Evaluate the expression
F = ca.Function('get_integer', free_vars, [expr])
ret = F.call(vals, *self.function_mode)
if ret[0].is_constant():
# We managed to evaluate the expression. Assume the result to be integer.
return int(ret[0])
else:
# Expression depends on other symbols. Could not extract integer value.
return ret[0]
if isinstance(tree, ast.Slice):
start = self.get_integer(tree.start)
step = self.get_integer(tree.step)
stop = self.get_integer(tree.stop)
return slice(start, stop, step)
else:
raise Exception('Unexpected node type {}'.format(
tree.__class__.__name__))
def generate(ast_tree: ast.Tree, model_name: str):
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:return: sympy source code for model
"""
component_ref = ast.ComponentRef.from_string(model_name)
ast_tree_new = copy.deepcopy(ast_tree)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree_new, component_ref)
sympy_gen = SympyGenerator()
ast_walker.walk(sympy_gen, flat_tree)
return sympy_gen.src[flat_tree]
def generate(ast_tree: ast.Tree, model_name: str):
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:return: sympy source code for model
"""
component_ref = ast.ComponentRef.from_string(model_name)
ast_tree_new = copy.deepcopy(ast_tree)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree_new, component_ref)
gen = XmlGenerator()
ast_walker.walk(gen, flat_tree)
return etree.tostring(gen.xml[flat_tree], pretty_print=True).decode('utf-8')
def generate(ast_tree: ast.Tree, model_name: str):
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:return: sympy source code for model
"""
component_ref = ast.ComponentRef.from_string(model_name)
ast_tree_new = copy.deepcopy(ast_tree)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree_new, component_ref)
gen = XmlGenerator()
ast_walker.walk(gen, flat_tree)
return etree.tostring(gen.xml[flat_tree], pretty_print=True).decode('utf-8')
def generate(ast_tree: ast.Tree, model_name: str):
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:return: sympy source code for model
"""
component_ref = ast.ComponentRef.from_string(model_name)
ast_tree_new = copy.deepcopy(ast_tree)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree_new, component_ref)
sympy_gen = SympyGenerator()
ast_walker.walk(sympy_gen, flat_tree)
return sympy_gen.src[flat_tree]
def generate(ast_tree: ast.Tree,
model_name: str,
options: Dict[str, Union[bool, str]] = None) -> str:
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:param options: options to pass to generator
:return: sympy source code for model
"""
_ = options # Unused
component_ref = ast.ComponentRef.from_string(model_name)
ast_tree_new = copy.deepcopy(ast_tree)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree_new, component_ref)
sympy_gen = SympyGenerator()
ast_walker.walk(sympy_gen, flat_tree)
return sympy_gen.src[flat_tree]
def get_integer(self, tree: Union[ast.Primary, ast.ComponentRef, ast.Expression, ast.Slice]) -> Union[int, ca.MX, np.ndarray]:
# CasADi needs to know the dimensions of symbols at instantiation.
# We therefore need a mechanism to evaluate expressions that define dimensions of symbols.
if isinstance(tree, ast.Primary):
return None if tree.value is None else int(tree.value)
if isinstance(tree, ast.ComponentRef):
s = self.current_class.symbols[tree.name]
assert (s.type.name == 'Integer')
return self.get_integer(s.value)
if isinstance(tree, ast.Expression):
# Make sure that the expression has been converted to MX by (re)visiting the
# relevant part of the AST.
ast_walker = TreeWalker()
ast_walker.walk(self, tree)
# Obtain expression
expr = self.get_mx(tree)
# Obtain the symbols it depends on
free_vars = ca.symvar(expr)
# Find the values of the symbols
vals = []
for free_var in free_vars:
if free_var.is_symbolic():
if (len(self.for_loops) > 0) and (free_var.name() == self.for_loops[-1].name):
vals.append(self.for_loops[-1].index_variable)
else:
vals.append(self.get_integer(self.current_class.symbols[free_var.name()].value))
# Evaluate the expression
F = ca.Function('get_integer', free_vars, [expr])
ret = F.call(vals, *self.function_mode)
if ret[0].is_constant():
# We managed to evaluate the expression. Assume the result to be integer.
return int(ret[0])
else:
# Expression depends on other symbols. Could not extract integer value.
return ret[0]
if isinstance(tree, ast.Slice):
start = self.get_integer(tree.start)
step = self.get_integer(tree.step)
stop = self.get_integer(tree.stop)
return slice(start, stop, step)
else:
raise Exception('Unexpected node type {}'.format(tree.__class__.__name__))
def generate(ast_tree: ast.Tree,
model_name: str,
options: Dict[str, bool] = None) -> Model:
"""
:param ast_tree: AST to generate from
:param model_name: class to generate
:param options: dictionary of generator options
:return: casadi model
"""
if options is None:
options = {}
component_ref = ast.ComponentRef.from_string(model_name)
ast_walker = TreeWalker()
flat_tree = flatten(ast_tree, component_ref)
component_ref_tuple = component_ref.to_tuple()
casadi_gen = Generator(flat_tree, component_ref_tuple[-1], options)
ast_walker.walk(casadi_gen, flat_tree)
return casadi_gen.model