def test_solve_odes_and_shapes(self):
input_path = str(os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(
os.pardir, 'models', 'iaf_psc_alpha.nestml'))))
compilation_unit = ModelParser.parse_model(input_path)
assert len(compilation_unit.get_neuron_list()) == 1
ast_neuron = compilation_unit.get_neuron_list()[0]
nestCodeGenerator = NESTCodeGenerator()
ast_neuron = nestCodeGenerator.transform_shapes_and_odes(ast_neuron, {})
def test_iaf_psc_alpha(self):
input_path = str(
os.path.realpath(
os.path.join(
os.path.dirname(__file__),
os.path.join(os.pardir, 'models',
'iaf_psc_alpha.nestml'))))
params = list()
params.append('--input_path')
params.append(input_path)
params.append('--logging_level')
params.append('INFO')
params.append('--target_path')
params.append(self.target_path)
params.append('--dev')
FrontendConfiguration.parse_config(params)
compilation_unit = ModelParser.parse_model(input_path)
nestCodeGenerator = NESTCodeGenerator()
nestCodeGenerator.generate_code(compilation_unit.get_neuron_list())
def test_vector_code_generation(self):
input_path = str(
os.path.realpath(
os.path.join(
os.path.dirname(__file__),
os.path.join('valid',
'VectorsDeclarationAndAssignment.nestml'))))
params = list()
params.append('--input_path')
params.append(input_path)
params.append('--logging_level')
params.append('INFO')
params.append('--target_path')
params.append(self.target_path)
params.append('--dev')
FrontendConfiguration.parse_config(params)
compilation_unit = ModelParser.parse_model(input_path)
nestCodeGenerator = NESTCodeGenerator()
nestCodeGenerator.generate_code(compilation_unit.get_neuron_list())
def from_target_name(
target_name: str,
options: Optional[Mapping[str, Any]] = None) -> CodeGenerator:
"""Static factory method that returns a new instance of a child class of CodeGenerator"""
assert target_name.upper() in CodeGenerator.get_known_targets(
), "Unknown target platform requested: \"" + str(target_name) + "\""
if target_name.upper() == "NEST":
from pynestml.codegeneration.nest_codegenerator import NESTCodeGenerator
return NESTCodeGenerator(options)
elif target_name.upper() == "AUTODOC":
from pynestml.codegeneration.autodoc_codegenerator import AutoDocCodeGenerator
assert options is None or options == {}, "\"autodoc\" code generator does not support options"
return AutoDocCodeGenerator()
elif target_name == "":
# dummy/null target: user requested to not generate any code
code, message = Messages.get_no_code_generated()
Logger.log_message(None, code, message, None, LoggingLevel.INFO)
return CodeGenerator("", options)
assert False # cannot reach here due to earlier assert -- silence static checker warnings
def generate_code(self, neurons):
"""
Generate code for the given neurons and (depending on the target) generate an index page, module entrypoint or
similar that incorporates an enumeration of all neurons.
:param neurons: a list of neurons.
:type neurons: List[ASTNode]
"""
if self._target.upper() == "NEST":
from pynestml.codegeneration.nest_codegenerator import NESTCodeGenerator
_codeGenerator = NESTCodeGenerator()
_codeGenerator.generate_code(neurons)
elif self._target.upper() == "AUTODOC":
from pynestml.codegeneration.autodoc_codegenerator import AutoDocCodeGenerator
_codeGenerator = AutoDocCodeGenerator()
_codeGenerator.generate_code(neurons)
else:
# dummy/null target: user requested to not generate any code
assert self._target == ""
code, message = Messages.get_no_code_generated()
Logger.log_message(None, code, message, None, LoggingLevel.INFO)
def test_model_preparation(self):
input_path = str(os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(
os.pardir, 'models', 'iaf_psc_alpha.nestml'))))
compilation_unit = ModelParser.parse_model(input_path)
assert len(compilation_unit.get_neuron_list()) == 1
ast_neuron = compilation_unit.get_neuron_list()[0]
equations_block = ast_neuron.get_equations_block()
# the idea here is to go through the rhs, print expressions, use the same mechanism as before, and reread them
# again
# TODO: add tests for this function
# this function changes stuff inplace
nestCodeGenerator = NESTCodeGenerator()
nestCodeGenerator.make_functions_self_contained(equations_block.get_ode_functions())
nestCodeGenerator.replace_functions_through_defining_expressions(equations_block.get_ode_equations(),
equations_block.get_ode_functions())
json_representation = nestCodeGenerator.transform_ode_and_shapes_to_json(equations_block)
self.assertTrue("convolve(I_shape_in, in_spikes)" in json_representation["odes"][0]["definition"])
self.assertTrue("convolve(I_shape_ex, ex_spikes)" in json_representation["odes"][0]["definition"])
