def test(self):
for filename in os.listdir(
os.path.realpath(
os.path.join(os.path.dirname(__file__),
os.path.join('..', 'models')))):
if filename.endswith(".nestml"):
print('Start creating AST for ' + filename + ' ...'),
input_file = FileStream(
os.path.join(
os.path.dirname(__file__),
os.path.join(os.path.join('..', 'models'), filename)))
lexer = PyNestMLLexer(input_file)
lexer._errHandler = BailErrorStrategy()
lexer._errHandler.reset(lexer)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
parser._errHandler = BailErrorStrategy()
parser._errHandler.reset(parser)
compilation_unit = parser.nestMLCompilationUnit()
# now build the meta_model
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
assert isinstance(ast, ASTNestMLCompilationUnit)
def _test_single_input_path(cls, input_path):
print('Start creating AST for ' + input_path + ' ...'),
input_file = FileStream(input_path)
lexer = PyNestMLLexer(input_file)
lexer._errHandler = BailErrorStrategy()
lexer._errHandler.reset(lexer)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
parser._errHandler = BailErrorStrategy()
parser._errHandler.reset(parser)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# now build the meta_model
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
assert isinstance(ast, ASTNestMLCompilationUnit)
# now, do the actual test for clone()
ast_copy = ast.clone()
assert str(ast) == str(ast_copy)
ast.get_neuron_list()[0].name = "foo"
ast_copy.get_neuron_list()[0].name = "bar"
assert str(ast) != str(ast_copy)
ast_copy.get_neuron_list()[0].name = "foo"
assert str(ast) == str(ast_copy)
def test(self):
# print('Start creating AST for ' + filename + ' ...'),
input_file = FileStream(
os.path.join(
os.path.realpath(
os.path.join(os.path.dirname(__file__), 'resources')),
'CommentTest.nestml'))
lexer = PyNestMLLexer(input_file)
lexer._errHandler = BailErrorStrategy()
lexer._errHandler.reset(lexer)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
parser._errHandler = BailErrorStrategy()
parser._errHandler.reset(parser)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# now build the meta_model
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
neuron_body_elements = ast.get_neuron_list()[0].get_body(
).get_body_elements()
# check if init values comment is correctly detected
assert (neuron_body_elements[0].get_comment()[0] == 'state comment ok')
# check that all declaration comments are detected
comments = neuron_body_elements[0].get_declarations()[0].get_comment()
assert (comments[0] == 'pre comment 1 ok')
assert (comments[1] == 'pre comment 2 ok')
assert (comments[2] == 'inline comment ok')
assert (comments[3] == 'post comment 1 ok')
assert (comments[4] == 'post comment 2 ok')
assert ('pre comment not ok' not in comments)
assert ('post comment not ok' not in comments)
# check that equation block comment is detected
self.assertEqual(neuron_body_elements[1].get_comment()[0],
'equations comment ok')
# check that parameters block comment is detected
self.assertEqual(neuron_body_elements[2].get_comment()[0],
'parameters comment ok')
# check that internals block comment is detected
self.assertEqual(neuron_body_elements[3].get_comment()[0],
'internals comment ok')
# check that input comment is detected
self.assertEqual(neuron_body_elements[4].get_comment()[0],
'input comment ok')
# check that output comment is detected
self.assertEqual(neuron_body_elements[5].get_comment()[0],
'output comment ok')
# check that update comment is detected
self.assertEqual(neuron_body_elements[6].get_comment()[0],
'update comment ok')
def test(self):
for filename in os.listdir(
os.path.realpath(
os.path.join(os.path.dirname(__file__),
os.path.join('..', 'models')))):
if filename.endswith(".nestml"):
input_file = FileStream(
os.path.join(
os.path.dirname(__file__),
os.path.join(os.path.join('..', 'models'), filename)))
lexer = PyNestMLLexer(input_file)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# create a new visitor and return the new AST
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
# update the corresponding symbol tables
SymbolTable.initialize_symbol_table(ast.get_source_position())
symbol_table_visitor = ASTSymbolTableVisitor()
for neuron in ast.get_neuron_list():
neuron.accept(symbol_table_visitor)
SymbolTable.add_neuron_scope(name=neuron.get_name(),
scope=neuron.get_scope())
self.assertTrue(isinstance(ast, ASTNestMLCompilationUnit))
return
def test(self):
for filename in os.listdir(os.path.realpath(os.path.join(os.path.dirname(__file__),
os.path.join('..', 'models')))):
if filename.endswith(".nestml"):
input_file = FileStream(
os.path.join(os.path.dirname(__file__), os.path.join(os.path.join('..', 'models'), filename)))
lexer = PyNestMLLexer(input_file)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# create a new visitor and return the new AST
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
# update the corresponding symbol tables
SymbolTable.initialize_symbol_table(ast.get_source_position())
symbol_table_visitor = ASTSymbolTableVisitor()
for neuron in ast.get_neuron_list():
neuron.accept(symbol_table_visitor)
SymbolTable.add_neuron_scope(name=neuron.get_name(), scope=neuron.get_scope())
self.assertTrue(isinstance(ast, ASTNestMLCompilationUnit))
return
def test(self):
# print('Start Expression Parser Test...'),
input_file = FileStream(
os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), 'resources')),
'ExpressionCollection.nestml'))
lexer = PyNestMLLexer(input_file)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
compilation_unit = parser.nestMLCompilationUnit()
# print('done')
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
# print('done')
self.assertTrue(isinstance(ast, ASTNestMLCompilationUnit))
def test(cls):
for filename in os.listdir(os.path.realpath(os.path.join(os.path.dirname(__file__),
os.path.join('..', 'models')))):
if filename.endswith(".nestml"):
# print('Start creating AST for ' + filename + ' ...'),
input_file = FileStream(
os.path.join(os.path.dirname(__file__), os.path.join(os.path.join('..', 'models'), filename)))
lexer = PyNestMLLexer(input_file)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# now build the meta_model
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
assert isinstance(ast, ASTNestMLCompilationUnit)
def test(self):
# print('Start creating AST for ' + filename + ' ...'),
input_file = FileStream(
os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), 'resources')),
'CommentTest.nestml'))
lexer = PyNestMLLexer(input_file)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
# process the comments
compilation_unit = parser.nestMLCompilationUnit()
# now build the meta_model
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
neuron_body_elements = ast.get_neuron_list()[0].get_body().get_body_elements()
# check if init values comment is correctly detected
assert (neuron_body_elements[0].get_comment()[0] == 'init_values comment ok')
# check that all declaration comments are detected
comments = neuron_body_elements[0].get_declarations()[0].get_comment()
assert (comments[0] == 'pre comment 1 ok')
assert (comments[1] == 'pre comment 2 ok')
assert (comments[2] == 'inline comment ok')
assert (comments[3] == 'post comment 1 ok')
assert (comments[4] == 'post comment 2 ok')
assert ('pre comment not ok' not in comments)
assert ('post comment not ok' not in comments)
# check that equation block comment is detected
self.assertEqual(neuron_body_elements[1].get_comment()[0], 'equations comment ok')
# check that parameters block comment is detected
self.assertEqual(neuron_body_elements[2].get_comment()[0], 'parameters comment ok')
# check that internals block comment is detected
self.assertEqual(neuron_body_elements[3].get_comment()[0], 'internals comment ok')
# check that input comment is detected
self.assertEqual(neuron_body_elements[4].get_comment()[0], 'input comment ok')
# check that output comment is detected
self.assertEqual(neuron_body_elements[5].get_comment()[0], 'output comment ok')
# check that update comment is detected
self.assertEqual(neuron_body_elements[6].get_comment()[0], 'update comment ok')
def test(self):
input_file = FileStream(
os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), 'resources')),
'ExpressionCollection.nestml'))
lexer = PyNestMLLexer(input_file)
lexer._errHandler = BailErrorStrategy()
lexer._errHandler.reset(lexer)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
parser._errHandler = BailErrorStrategy()
parser._errHandler.reset(parser)
compilation_unit = parser.nestMLCompilationUnit()
assert compilation_unit is not None
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
self.assertTrue(isinstance(ast, ASTNestMLCompilationUnit))
def test(self):
# print('Start special block parsing and AST-building test...'),
input_file = FileStream(
os.path.join(os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), 'resources')),
'BlockTest.nestml')))
lexer = PyNestMLLexer(input_file)
lexer._errHandler = BailErrorStrategy()
lexer._errHandler.reset(lexer)
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
# parse the file
parser = PyNestMLParser(stream)
parser._errHandler = BailErrorStrategy()
parser._errHandler.reset(parser)
compilation_unit = parser.nestMLCompilationUnit()
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
self.assertTrue(isinstance(ast, ASTNestMLCompilationUnit))
def parse_model(cls, file_path=None):
"""
Parses a handed over model and returns the meta_model representation of it.
:param file_path: the path to the file which shall be parsed.
:type file_path: str
:return: a new ASTNESTMLCompilationUnit object.
:rtype: ASTNestMLCompilationUnit
"""
try:
input_file = FileStream(file_path)
except IOError:
code, message = Messages.get_input_path_not_found(path=file_path)
Logger.log_message(node=None, code=None, message=message,
error_position=None, log_level=LoggingLevel.ERROR)
return
code, message = Messages.get_start_processing_file(file_path)
Logger.log_message(node=None, code=code, message=message, error_position=None, log_level=LoggingLevel.INFO)
# create a lexer and hand over the input
lexer = PyNestMLLexer()
lexer.removeErrorListeners()
lexer.addErrorListener(ConsoleErrorListener())
lexerErrorListener = NestMLErrorListener()
lexer.addErrorListener(lexerErrorListener)
# lexer._errHandler = BailErrorStrategy() # N.B. uncomment this line and the next to halt immediately on lexer errors
# lexer._errHandler.reset(lexer)
lexer.inputStream = input_file
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
if lexerErrorListener._error_occurred:
code, message = Messages.get_lexer_error()
Logger.log_message(node=None, code=None, message=message,
error_position=None, log_level=LoggingLevel.ERROR)
return
# parse the file
parser = PyNestMLParser(None)
parser.removeErrorListeners()
parser.addErrorListener(ConsoleErrorListener())
parserErrorListener = NestMLErrorListener()
parser.addErrorListener(parserErrorListener)
# parser._errHandler = BailErrorStrategy() # N.B. uncomment this line and the next to halt immediately on parse errors
# parser._errHandler.reset(parser)
parser.setTokenStream(stream)
compilation_unit = parser.nestMLCompilationUnit()
if parserErrorListener._error_occurred:
code, message = Messages.get_parser_error()
Logger.log_message(node=None, code=None, message=message,
error_position=None, log_level=LoggingLevel.ERROR)
return
# create a new visitor and return the new AST
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
# create and update the corresponding symbol tables
SymbolTable.initialize_symbol_table(ast.get_source_position())
for neuron in ast.get_neuron_list():
neuron.accept(ASTSymbolTableVisitor())
SymbolTable.add_neuron_scope(neuron.get_name(), neuron.get_scope())
# store source paths
for neuron in ast.get_neuron_list():
neuron.file_path = file_path
ast.file_path = file_path
return ast
def parse_model(cls, file_path=None):
"""
Parses a handed over model and returns the meta_model representation of it.
:param file_path: the path to the file which shall be parsed.
:type file_path: str
:return: a new ASTNESTMLCompilationUnit object.
:rtype: ASTNestMLCompilationUnit
"""
try:
input_file = FileStream(file_path)
except IOError:
code, message = Messages.get_input_path_not_found(path=file_path)
Logger.log_message(neuron=None, code=None, message=message, error_position=None, log_level=LoggingLevel.ERROR)
return
code, message = Messages.get_start_processing_file(file_path)
Logger.log_message(neuron=None, code=code, message=message, error_position=None, log_level=LoggingLevel.INFO)
# create a lexer and hand over the input
lexer = PyNestMLLexer()
lexer.removeErrorListeners()
lexer.addErrorListener(ConsoleErrorListener())
lexerErrorListener = NestMLErrorListener()
lexer.addErrorListener(lexerErrorListener)
# lexer._errHandler = BailErrorStrategy() # N.B. uncomment this line and the next to halt immediately on lexer errors
# lexer._errHandler.reset(lexer)
lexer.inputStream = input_file
# create a token stream
stream = CommonTokenStream(lexer)
stream.fill()
if lexerErrorListener._error_occurred:
code, message = Messages.get_lexer_error()
Logger.log_message(neuron=None, code=None, message=message, error_position=None, log_level=LoggingLevel.ERROR)
return
# parse the file
parser = PyNestMLParser(None)
parser.removeErrorListeners()
parser.addErrorListener(ConsoleErrorListener())
parserErrorListener = NestMLErrorListener()
parser.addErrorListener(parserErrorListener)
# parser._errHandler = BailErrorStrategy() # N.B. uncomment this line and the next to halt immediately on parse errors
# parser._errHandler.reset(parser)
parser.setTokenStream(stream)
compilation_unit = parser.nestMLCompilationUnit()
if parserErrorListener._error_occurred:
code, message = Messages.get_parser_error()
Logger.log_message(neuron=None, code=None, message=message, error_position=None, log_level=LoggingLevel.ERROR)
return
# create a new visitor and return the new AST
ast_builder_visitor = ASTBuilderVisitor(stream.tokens)
ast = ast_builder_visitor.visit(compilation_unit)
# create and update the corresponding symbol tables
SymbolTable.initialize_symbol_table(ast.get_source_position())
log_to_restore = copy.deepcopy(Logger.get_log())
counter = Logger.curr_message
# replace all derived variables through a computer processable names: e.g. g_in''' -> g_in__ddd
restore_differential_order = []
for ode in ASTUtils.get_all(ast, ASTOdeEquation):
lhs_variable = ode.get_lhs()
if lhs_variable.get_differential_order() > 0:
lhs_variable.differential_order = lhs_variable.get_differential_order() - 1
restore_differential_order.append(lhs_variable)
for shape in ASTUtils.get_all(ast, ASTOdeShape):
lhs_variable = shape.get_variable()
if lhs_variable.get_differential_order() > 0:
lhs_variable.differential_order = lhs_variable.get_differential_order() - 1
restore_differential_order.append(lhs_variable)
# than replace remaining variables
for variable in ASTUtils.get_all(ast, ASTVariable):
if variable.get_differential_order() > 0:
variable.set_name(variable.get_name() + "__" + "d" * variable.get_differential_order())
variable.differential_order = 0
# now also equations have no ' at lhs. replace every occurrence of last d to ' to compensate
for ode_variable in restore_differential_order:
ode_variable.differential_order = 1
Logger.set_log(log_to_restore, counter)
for neuron in ast.get_neuron_list():
neuron.accept(ASTSymbolTableVisitor())
SymbolTable.add_neuron_scope(neuron.get_name(), neuron.get_scope())
return ast