Beispiel #1
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def test_profile_singlepop():
    
    dv = .0001
    update_method = 'approx'
    tol = 1e-14
    
    run_dict = {'dt':.0001, 't0':0, 'tf':.2}

    simulation = get_network(dv=dv, update_method=update_method, tol=tol)
    profile_result = profile_network(simulation, run_dict)

    run_time = extract_value(profile_result, 'network.py', 'run')
Beispiel #2
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def test_profile_singlepop():
    
    dv = .0001
    update_method = 'approx'
    approx_order = None
    tol = 1e-14
    
    run_dict = {'dt':.0001, 't0':0, 'tf':.2}

    simulation = get_network(dv=dv, update_method=update_method, approx_order=approx_order, tol=tol)
    profile_result = profile_network(simulation, run_dict)

    run_time = extract_value(profile_result, 'network.py', 'run')
Beispiel #3
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    # Create neuroml doc:
    nml_doc = nml.NeuroMLDocument(id=doc_id)

    # Append types:
    #     nml_doc.iaf_cells.append(nml.IafCell0)

    population_type_list = {}
    for p in network.population_list:
        curr_population_name = p.__class__.__name__
        if curr_population_name == 'InternalPopulation':
            print neuroml_internal_population_parameter_dict_adapter(p)
        elif curr_population_name == 'ExternalPopulation':
            pass


#             print neuroml_external_population_parameter_dict_adapter(p)
        else:
            raise Exception(
                'Population Type (%s) not recognize when converting to NeuroML'
                % curr_population_name)

if __name__ == "__main__":

    warnings.warn('NeuroML adapter is in prototype stage and not debugged.')

    from dipde.examples.singlepop import get_network

    network = get_network(tol=1e-14)

    network_to_neuroml(network, 'temp.net.nml')
Beispiel #4
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    # Create neuroml doc:
    nml_doc = nml.NeuroMLDocument(id=doc_id)
    print nml_doc
    
    validate_neuroml2(nml_doc)
    
    # Append types:
#     nml_doc.iaf_cells.append(nml.IafCell0)
    
    population_type_list = {}
    for p in network.population_list:
        curr_population_name = p.__class__.__name__
        if curr_population_name == 'InternalPopulation':
            output = neuroml_internal_population_parameter_dict_adapter(p)
        elif curr_population_name == 'ExternalPopulation':
            pass
#             print neuroml_external_population_parameter_dict_adapter(p)
        else:
            raise Exception('Population Type (%s) not recognize when converting to NeuroML' % curr_population_name)


if __name__ == "__main__":
    
    warnings.warn('NeuroML adapter is in prototype stage and not debugged.')
    
    from dipde.examples.singlepop import get_network
    
    network = get_network(tol=1e-14)
    
    network_to_neuroml(network, 'temp.net.nml')