#import os
import sys
import miind.include as include
import miind.algorithms as algorithms
import miind.nodes as nodes
import miind.connections as connections
import miind.simulation as simulation
import miind.variables as variables
import xml.etree.ElementTree as ET
import argparse
import miind.directories as directories

XML_EXTENSION = '.xml'

# Nothing too fancy for the weight type

WEIGHTTYPES = ['double', 'DelayedConnection']

def generate_preamble(outfile):
    outfile.write('//Machine-generated by miind.py. Edit at your own risk.\n\n')
    for inc in include.lib_includes:
        outfile.write(inc +'\n')

    return

def define_network_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'typedef MPILib::MPINetwork<' + s + ', MPILib::utilities::CircularDistribution> Network;\n'

def abstract_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'MPILib::MiindTvbModelAbstract<' + s + ', MPILib::utilities::CircularDistribution>'

def define_abstract_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'define_python_MiindTvbModelAbstract<' + s + ', MPILib::utilities::CircularDistribution>();\n'


def generate_closing(outfile, typ, tree):
    outfile.write('\t}\n')
    outfile.write('\t\n')
    name=tree.find('SimulationIO/SimulationName')
    name_str = name.text
    outfile.write('\tstd::string sim_name = \"' + name_str + '\";\n')
    outfile.write('#ifdef ENABLE_ROOT_REPORTER\n')
    outfile.write('\treport_handler = new MPILib::report::handler::RootReportHandler(sim_name,true);\n')
    outfile.write('#else\n')
    outfile.write('\treport_handler = new MPILib::report::handler::InactiveReportHandler();\n')
    outfile.write('#endif\n')
    outfile.write('\t\n')
    outfile.write('\tSimulationRunParameter par_run( *report_handler,(_simulation_length/_time_step)+1,0,\n')
    name=tree.find('SimulationRunParameter/name_log')
    log_name = name.text
    report_t_step = tree.find('SimulationRunParameter/t_report')
    report_state_t_step = tree.find('SimulationRunParameter/t_state_report')
    outfile.write('\t\t\t_simulation_length,' + report_t_step.text + ',_time_step,\"' + log_name + '\",'+ report_state_t_step.text + ');\n')
    outfile.write('\t\n')
    outfile.write('\tnetwork.configureSimulation(par_run);\n')

    outfile.write('\tbool close_display = false;\n')
    outfile.write('\tTwoDLib::Display::getInstance()->AssignCloseDisplayPointer(&close_display);\n')
    outfile.write('\tTwoDLib::Display::getInstance()->AssignNetworkPointer(&network);\n')

    outfile.write('\tstd::thread t1(TwoDLib::Display::stat_runthreaded);\n')
    outfile.write('\tt1.detach();\n')


    outfile.write('\t}\n')
    outfile.write('};\n\n')

    for t in  algorithms.RATEFUNCTIONS:
        outfile.write(t)

    outfile.write('\n\n')
    variable_list = tree.findall('Variable')
    outfile.write('BOOST_PYTHON_MODULE(lib' + name_str + ')\n')
    outfile.write('{\n')
    outfile.write('\tusing namespace boost::python;\n')
    outfile.write('\t' + define_abstract_type(typ))
    outfile.write('\tclass_<MiindModel, bases<' + abstract_type(typ) + '>>("MiindModel", init<int,long>())\n')

    if len(variable_list) > 0:
        var_types = variables.parse_variable_types(variable_list)
        outfile.write('\t.def(init<int,long' + var_types + '>())\n')
    outfile.write('\t.def("init", &MiindModel::init)\n')
    outfile.write('\t.def("endSim", &MiindModel::endSim);\n')
    outfile.write('}\n')

def parse_xml(infile, outfile):
    tree=ET.fromstring(infile.read())
    m=tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree

def constructor_override(outfile,tree,typ):

    variable_list = tree.findall('Variable')
    variables.parse_variables(variable_list,outfile)

    outfile.write('\tMiindModel(int num_nodes, long simulation_length ):\n')
    outfile.write('\t\tMiindTvbModelAbstract(num_nodes, simulation_length){}\n\n')

    if len(variable_list) > 0:
        outfile.write('\tMiindModel(int num_nodes, long simulation_length \n')
        variables.parse_variables_as_parameters(variable_list,outfile)
        outfile.write('):\n')
        outfile.write('\t\tMiindTvbModelAbstract(num_nodes, simulation_length)\n')
        variables.parse_variables_as_constructor_defaults(variable_list, outfile)
        outfile.write('{}\n\n')

    outfile.write('\tvoid endSim(){\n')
    outfile.write('\tclose_display = true;\n')
    # outfile.write('\t' + abstract_type(typ) + '::endSimulation();\n')
    outfile.write('\t}\n\n')

def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree,typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


def model_name(fn):
    '''Identifies model files mentioned in an XML file. For example used in placing the right model file in
    the same directory as an XML file.'''
    infile = open(fn)
    tree=ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm')

    modelnames = []
    for a in ma:
        if a.attrib['type'] == 'MeshAlgorithm' or a.attrib['type'] == 'GridAlgorithm':
            modelnames.append(a.attrib['modelfile'])
    return modelnames

def matrix_names(fn):
    '''Find the file names of all MatrixFiles, mentioned in an XML file.'''
    infile = open(fn)
    tree=ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames

def generate_outputfile(infile, outfile):
    generate_preamble(outfile)
    nettype, tree = parse_xml(infile,outfile)
    outfile.write(nettype)
    outfile.write('\t// defining variables\n') # whatever variables are use are global

    algies = tree.findall('Algorithms')
    if len(algies) != 1:
        raise ValueError

    alg_list = algies[0].findall('Algorithm')
    weighttype = tree.find('WeightType')
    generate_opening(outfile, tree, weighttype.text)
    outfile.write('\t// generating algorithms\n')
    algorithms.parse_algorithms(alg_list,weighttype,outfile)
    node_list = tree.findall('Nodes/Node')
    outfile.write('\t// generating nodes\n')
    nodes.parse_nodes(node_list,weighttype,outfile)
    outfile.write('\t// generating connections\n')
    connection_list = tree.findall('Connections/Connection')
    connections.parse_connections(connection_list,weighttype,outfile)
    connection_list = tree.findall('Connections/IncomingConnection')
    connections.parse_incoming_connections(connection_list,weighttype,outfile)
    connection_list = tree.findall('Connections/OutgoingConnection')
    connections.parse_outgoing_connections(connection_list,outfile)
    generate_closing(outfile, weighttype.text, tree)
    algorithms.reset_algorithms()
    nodes.reset_nodes()

3c05a86155f7b4aa510cafc378081b6b261580c7
<mask token>


def define_network_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'typedef MPILib::MPINetwork<' + s + """, MPILib::utilities::CircularDistribution> Network;
"""


def abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return ('MPILib::MiindTvbModelAbstract<' + s +
        ', MPILib::utilities::CircularDistribution>')


<mask token>


def parse_xml(infile, outfile):
    tree = ET.fromstring(infile.read())
    m = tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree


<mask token>


def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree, typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


<mask token>


def matrix_names(fn):
    """Find the file names of all MatrixFiles, mentioned in an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames


<mask token>

<mask token>


def generate_preamble(outfile):
    outfile.write('//Machine-generated by miind.py. Edit at your own risk.\n\n'
        )
    for inc in include.lib_includes:
        outfile.write(inc + '\n')
    return


def define_network_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'typedef MPILib::MPINetwork<' + s + """, MPILib::utilities::CircularDistribution> Network;
"""


def abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return ('MPILib::MiindTvbModelAbstract<' + s +
        ', MPILib::utilities::CircularDistribution>')


def define_abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'define_python_MiindTvbModelAbstract<' + s + """, MPILib::utilities::CircularDistribution>();
"""


<mask token>


def parse_xml(infile, outfile):
    tree = ET.fromstring(infile.read())
    m = tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree


def constructor_override(outfile, tree, typ):
    variable_list = tree.findall('Variable')
    variables.parse_variables(variable_list, outfile)
    outfile.write('\tMiindModel(int num_nodes, long simulation_length ):\n')
    outfile.write(
        '\t\tMiindTvbModelAbstract(num_nodes, simulation_length){}\n\n')
    if len(variable_list) > 0:
        outfile.write('\tMiindModel(int num_nodes, long simulation_length \n')
        variables.parse_variables_as_parameters(variable_list, outfile)
        outfile.write('):\n')
        outfile.write(
            '\t\tMiindTvbModelAbstract(num_nodes, simulation_length)\n')
        variables.parse_variables_as_constructor_defaults(variable_list,
            outfile)
        outfile.write('{}\n\n')
    outfile.write('\tvoid endSim(){\n')
    outfile.write('\tclose_display = true;\n')
    outfile.write('\t}\n\n')


def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree, typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


def model_name(fn):
    """Identifies model files mentioned in an XML file. For example used in placing the right model file in
    the same directory as an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm')
    modelnames = []
    for a in ma:
        if a.attrib['type'] == 'MeshAlgorithm' or a.attrib['type'
            ] == 'GridAlgorithm':
            modelnames.append(a.attrib['modelfile'])
    return modelnames


def matrix_names(fn):
    """Find the file names of all MatrixFiles, mentioned in an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames


def generate_outputfile(infile, outfile):
    generate_preamble(outfile)
    nettype, tree = parse_xml(infile, outfile)
    outfile.write(nettype)
    outfile.write('\t// defining variables\n')
    algies = tree.findall('Algorithms')
    if len(algies) != 1:
        raise ValueError
    alg_list = algies[0].findall('Algorithm')
    weighttype = tree.find('WeightType')
    generate_opening(outfile, tree, weighttype.text)
    outfile.write('\t// generating algorithms\n')
    algorithms.parse_algorithms(alg_list, weighttype, outfile)
    node_list = tree.findall('Nodes/Node')
    outfile.write('\t// generating nodes\n')
    nodes.parse_nodes(node_list, weighttype, outfile)
    outfile.write('\t// generating connections\n')
    connection_list = tree.findall('Connections/Connection')
    connections.parse_connections(connection_list, weighttype, outfile)
    connection_list = tree.findall('Connections/IncomingConnection')
    connections.parse_incoming_connections(connection_list, weighttype, outfile
        )
    connection_list = tree.findall('Connections/OutgoingConnection')
    connections.parse_outgoing_connections(connection_list, outfile)
    generate_closing(outfile, weighttype.text, tree)
    algorithms.reset_algorithms()
    nodes.reset_nodes()

<mask token>


def generate_preamble(outfile):
    outfile.write('//Machine-generated by miind.py. Edit at your own risk.\n\n'
        )
    for inc in include.lib_includes:
        outfile.write(inc + '\n')
    return


def define_network_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'typedef MPILib::MPINetwork<' + s + """, MPILib::utilities::CircularDistribution> Network;
"""


def abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return ('MPILib::MiindTvbModelAbstract<' + s +
        ', MPILib::utilities::CircularDistribution>')


def define_abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'define_python_MiindTvbModelAbstract<' + s + """, MPILib::utilities::CircularDistribution>();
"""


def generate_closing(outfile, typ, tree):
    outfile.write('\t}\n')
    outfile.write('\t\n')
    name = tree.find('SimulationIO/SimulationName')
    name_str = name.text
    outfile.write('\tstd::string sim_name = "' + name_str + '";\n')
    outfile.write('#ifdef ENABLE_ROOT_REPORTER\n')
    outfile.write(
        """	report_handler = new MPILib::report::handler::RootReportHandler(sim_name,true);
"""
        )
    outfile.write('#else\n')
    outfile.write(
        '\treport_handler = new MPILib::report::handler::InactiveReportHandler();\n'
        )
    outfile.write('#endif\n')
    outfile.write('\t\n')
    outfile.write(
        """	SimulationRunParameter par_run( *report_handler,(_simulation_length/_time_step)+1,0,
"""
        )
    name = tree.find('SimulationRunParameter/name_log')
    log_name = name.text
    report_t_step = tree.find('SimulationRunParameter/t_report')
    report_state_t_step = tree.find('SimulationRunParameter/t_state_report')
    outfile.write('\t\t\t_simulation_length,' + report_t_step.text +
        ',_time_step,"' + log_name + '",' + report_state_t_step.text + ');\n')
    outfile.write('\t\n')
    outfile.write('\tnetwork.configureSimulation(par_run);\n')
    outfile.write('\tbool close_display = false;\n')
    outfile.write(
        '\tTwoDLib::Display::getInstance()->AssignCloseDisplayPointer(&close_display);\n'
        )
    outfile.write(
        '\tTwoDLib::Display::getInstance()->AssignNetworkPointer(&network);\n')
    outfile.write('\tstd::thread t1(TwoDLib::Display::stat_runthreaded);\n')
    outfile.write('\tt1.detach();\n')
    outfile.write('\t}\n')
    outfile.write('};\n\n')
    for t in algorithms.RATEFUNCTIONS:
        outfile.write(t)
    outfile.write('\n\n')
    variable_list = tree.findall('Variable')
    outfile.write('BOOST_PYTHON_MODULE(lib' + name_str + ')\n')
    outfile.write('{\n')
    outfile.write('\tusing namespace boost::python;\n')
    outfile.write('\t' + define_abstract_type(typ))
    outfile.write('\tclass_<MiindModel, bases<' + abstract_type(typ) +
        """>>("MiindModel", init<int,long>())
""")
    if len(variable_list) > 0:
        var_types = variables.parse_variable_types(variable_list)
        outfile.write('\t.def(init<int,long' + var_types + '>())\n')
    outfile.write('\t.def("init", &MiindModel::init)\n')
    outfile.write('\t.def("endSim", &MiindModel::endSim);\n')
    outfile.write('}\n')


def parse_xml(infile, outfile):
    tree = ET.fromstring(infile.read())
    m = tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree


def constructor_override(outfile, tree, typ):
    variable_list = tree.findall('Variable')
    variables.parse_variables(variable_list, outfile)
    outfile.write('\tMiindModel(int num_nodes, long simulation_length ):\n')
    outfile.write(
        '\t\tMiindTvbModelAbstract(num_nodes, simulation_length){}\n\n')
    if len(variable_list) > 0:
        outfile.write('\tMiindModel(int num_nodes, long simulation_length \n')
        variables.parse_variables_as_parameters(variable_list, outfile)
        outfile.write('):\n')
        outfile.write(
            '\t\tMiindTvbModelAbstract(num_nodes, simulation_length)\n')
        variables.parse_variables_as_constructor_defaults(variable_list,
            outfile)
        outfile.write('{}\n\n')
    outfile.write('\tvoid endSim(){\n')
    outfile.write('\tclose_display = true;\n')
    outfile.write('\t}\n\n')


def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree, typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


def model_name(fn):
    """Identifies model files mentioned in an XML file. For example used in placing the right model file in
    the same directory as an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm')
    modelnames = []
    for a in ma:
        if a.attrib['type'] == 'MeshAlgorithm' or a.attrib['type'
            ] == 'GridAlgorithm':
            modelnames.append(a.attrib['modelfile'])
    return modelnames


def matrix_names(fn):
    """Find the file names of all MatrixFiles, mentioned in an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames


def generate_outputfile(infile, outfile):
    generate_preamble(outfile)
    nettype, tree = parse_xml(infile, outfile)
    outfile.write(nettype)
    outfile.write('\t// defining variables\n')
    algies = tree.findall('Algorithms')
    if len(algies) != 1:
        raise ValueError
    alg_list = algies[0].findall('Algorithm')
    weighttype = tree.find('WeightType')
    generate_opening(outfile, tree, weighttype.text)
    outfile.write('\t// generating algorithms\n')
    algorithms.parse_algorithms(alg_list, weighttype, outfile)
    node_list = tree.findall('Nodes/Node')
    outfile.write('\t// generating nodes\n')
    nodes.parse_nodes(node_list, weighttype, outfile)
    outfile.write('\t// generating connections\n')
    connection_list = tree.findall('Connections/Connection')
    connections.parse_connections(connection_list, weighttype, outfile)
    connection_list = tree.findall('Connections/IncomingConnection')
    connections.parse_incoming_connections(connection_list, weighttype, outfile
        )
    connection_list = tree.findall('Connections/OutgoingConnection')
    connections.parse_outgoing_connections(connection_list, outfile)
    generate_closing(outfile, weighttype.text, tree)
    algorithms.reset_algorithms()
    nodes.reset_nodes()

import sys
import miind.include as include
import miind.algorithms as algorithms
import miind.nodes as nodes
import miind.connections as connections
import miind.simulation as simulation
import miind.variables as variables
import xml.etree.ElementTree as ET
import argparse
import miind.directories as directories
XML_EXTENSION = '.xml'
WEIGHTTYPES = ['double', 'DelayedConnection']


def generate_preamble(outfile):
    outfile.write('//Machine-generated by miind.py. Edit at your own risk.\n\n'
        )
    for inc in include.lib_includes:
        outfile.write(inc + '\n')
    return


def define_network_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'typedef MPILib::MPINetwork<' + s + """, MPILib::utilities::CircularDistribution> Network;
"""


def abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return ('MPILib::MiindTvbModelAbstract<' + s +
        ', MPILib::utilities::CircularDistribution>')


def define_abstract_type(type):
    if type == 'DelayedConnection':
        s = 'MPILib::' + type
    else:
        s = 'double'
    return 'define_python_MiindTvbModelAbstract<' + s + """, MPILib::utilities::CircularDistribution>();
"""


def generate_closing(outfile, typ, tree):
    outfile.write('\t}\n')
    outfile.write('\t\n')
    name = tree.find('SimulationIO/SimulationName')
    name_str = name.text
    outfile.write('\tstd::string sim_name = "' + name_str + '";\n')
    outfile.write('#ifdef ENABLE_ROOT_REPORTER\n')
    outfile.write(
        """	report_handler = new MPILib::report::handler::RootReportHandler(sim_name,true);
"""
        )
    outfile.write('#else\n')
    outfile.write(
        '\treport_handler = new MPILib::report::handler::InactiveReportHandler();\n'
        )
    outfile.write('#endif\n')
    outfile.write('\t\n')
    outfile.write(
        """	SimulationRunParameter par_run( *report_handler,(_simulation_length/_time_step)+1,0,
"""
        )
    name = tree.find('SimulationRunParameter/name_log')
    log_name = name.text
    report_t_step = tree.find('SimulationRunParameter/t_report')
    report_state_t_step = tree.find('SimulationRunParameter/t_state_report')
    outfile.write('\t\t\t_simulation_length,' + report_t_step.text +
        ',_time_step,"' + log_name + '",' + report_state_t_step.text + ');\n')
    outfile.write('\t\n')
    outfile.write('\tnetwork.configureSimulation(par_run);\n')
    outfile.write('\tbool close_display = false;\n')
    outfile.write(
        '\tTwoDLib::Display::getInstance()->AssignCloseDisplayPointer(&close_display);\n'
        )
    outfile.write(
        '\tTwoDLib::Display::getInstance()->AssignNetworkPointer(&network);\n')
    outfile.write('\tstd::thread t1(TwoDLib::Display::stat_runthreaded);\n')
    outfile.write('\tt1.detach();\n')
    outfile.write('\t}\n')
    outfile.write('};\n\n')
    for t in algorithms.RATEFUNCTIONS:
        outfile.write(t)
    outfile.write('\n\n')
    variable_list = tree.findall('Variable')
    outfile.write('BOOST_PYTHON_MODULE(lib' + name_str + ')\n')
    outfile.write('{\n')
    outfile.write('\tusing namespace boost::python;\n')
    outfile.write('\t' + define_abstract_type(typ))
    outfile.write('\tclass_<MiindModel, bases<' + abstract_type(typ) +
        """>>("MiindModel", init<int,long>())
""")
    if len(variable_list) > 0:
        var_types = variables.parse_variable_types(variable_list)
        outfile.write('\t.def(init<int,long' + var_types + '>())\n')
    outfile.write('\t.def("init", &MiindModel::init)\n')
    outfile.write('\t.def("endSim", &MiindModel::endSim);\n')
    outfile.write('}\n')


def parse_xml(infile, outfile):
    tree = ET.fromstring(infile.read())
    m = tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree


def constructor_override(outfile, tree, typ):
    variable_list = tree.findall('Variable')
    variables.parse_variables(variable_list, outfile)
    outfile.write('\tMiindModel(int num_nodes, long simulation_length ):\n')
    outfile.write(
        '\t\tMiindTvbModelAbstract(num_nodes, simulation_length){}\n\n')
    if len(variable_list) > 0:
        outfile.write('\tMiindModel(int num_nodes, long simulation_length \n')
        variables.parse_variables_as_parameters(variable_list, outfile)
        outfile.write('):\n')
        outfile.write(
            '\t\tMiindTvbModelAbstract(num_nodes, simulation_length)\n')
        variables.parse_variables_as_constructor_defaults(variable_list,
            outfile)
        outfile.write('{}\n\n')
    outfile.write('\tvoid endSim(){\n')
    outfile.write('\tclose_display = true;\n')
    outfile.write('\t}\n\n')


def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree, typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


def model_name(fn):
    """Identifies model files mentioned in an XML file. For example used in placing the right model file in
    the same directory as an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm')
    modelnames = []
    for a in ma:
        if a.attrib['type'] == 'MeshAlgorithm' or a.attrib['type'
            ] == 'GridAlgorithm':
            modelnames.append(a.attrib['modelfile'])
    return modelnames


def matrix_names(fn):
    """Find the file names of all MatrixFiles, mentioned in an XML file."""
    infile = open(fn)
    tree = ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames


def generate_outputfile(infile, outfile):
    generate_preamble(outfile)
    nettype, tree = parse_xml(infile, outfile)
    outfile.write(nettype)
    outfile.write('\t// defining variables\n')
    algies = tree.findall('Algorithms')
    if len(algies) != 1:
        raise ValueError
    alg_list = algies[0].findall('Algorithm')
    weighttype = tree.find('WeightType')
    generate_opening(outfile, tree, weighttype.text)
    outfile.write('\t// generating algorithms\n')
    algorithms.parse_algorithms(alg_list, weighttype, outfile)
    node_list = tree.findall('Nodes/Node')
    outfile.write('\t// generating nodes\n')
    nodes.parse_nodes(node_list, weighttype, outfile)
    outfile.write('\t// generating connections\n')
    connection_list = tree.findall('Connections/Connection')
    connections.parse_connections(connection_list, weighttype, outfile)
    connection_list = tree.findall('Connections/IncomingConnection')
    connections.parse_incoming_connections(connection_list, weighttype, outfile
        )
    connection_list = tree.findall('Connections/OutgoingConnection')
    connections.parse_outgoing_connections(connection_list, outfile)
    generate_closing(outfile, weighttype.text, tree)
    algorithms.reset_algorithms()
    nodes.reset_nodes()

#import os
import sys
import miind.include as include
import miind.algorithms as algorithms
import miind.nodes as nodes
import miind.connections as connections
import miind.simulation as simulation
import miind.variables as variables
import xml.etree.ElementTree as ET
import argparse
import miind.directories as directories

XML_EXTENSION = '.xml'

# Nothing too fancy for the weight type

WEIGHTTYPES = ['double', 'DelayedConnection']

def generate_preamble(outfile):
    outfile.write('//Machine-generated by miind.py. Edit at your own risk.\n\n')
    for inc in include.lib_includes:
        outfile.write(inc +'\n')

    return

def define_network_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'typedef MPILib::MPINetwork<' + s + ', MPILib::utilities::CircularDistribution> Network;\n'

def abstract_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'MPILib::MiindTvbModelAbstract<' + s + ', MPILib::utilities::CircularDistribution>'

def define_abstract_type(type):
    if type ==  "DelayedConnection":
        s = "MPILib::" + type
    else:
        s = "double"
    return 'define_python_MiindTvbModelAbstract<' + s + ', MPILib::utilities::CircularDistribution>();\n'


def generate_closing(outfile, typ, tree):
    outfile.write('\t}\n')
    outfile.write('\t\n')
    name=tree.find('SimulationIO/SimulationName')
    name_str = name.text
    outfile.write('\tstd::string sim_name = \"' + name_str + '\";\n')
    outfile.write('#ifdef ENABLE_ROOT_REPORTER\n')
    outfile.write('\treport_handler = new MPILib::report::handler::RootReportHandler(sim_name,true);\n')
    outfile.write('#else\n')
    outfile.write('\treport_handler = new MPILib::report::handler::InactiveReportHandler();\n')
    outfile.write('#endif\n')
    outfile.write('\t\n')
    outfile.write('\tSimulationRunParameter par_run( *report_handler,(_simulation_length/_time_step)+1,0,\n')
    name=tree.find('SimulationRunParameter/name_log')
    log_name = name.text
    report_t_step = tree.find('SimulationRunParameter/t_report')
    report_state_t_step = tree.find('SimulationRunParameter/t_state_report')
    outfile.write('\t\t\t_simulation_length,' + report_t_step.text + ',_time_step,\"' + log_name + '\",'+ report_state_t_step.text + ');\n')
    outfile.write('\t\n')
    outfile.write('\tnetwork.configureSimulation(par_run);\n')

    outfile.write('\tbool close_display = false;\n')
    outfile.write('\tTwoDLib::Display::getInstance()->AssignCloseDisplayPointer(&close_display);\n')
    outfile.write('\tTwoDLib::Display::getInstance()->AssignNetworkPointer(&network);\n')

    outfile.write('\tstd::thread t1(TwoDLib::Display::stat_runthreaded);\n')
    outfile.write('\tt1.detach();\n')


    outfile.write('\t}\n')
    outfile.write('};\n\n')

    for t in  algorithms.RATEFUNCTIONS:
        outfile.write(t)

    outfile.write('\n\n')
    variable_list = tree.findall('Variable')
    outfile.write('BOOST_PYTHON_MODULE(lib' + name_str + ')\n')
    outfile.write('{\n')
    outfile.write('\tusing namespace boost::python;\n')
    outfile.write('\t' + define_abstract_type(typ))
    outfile.write('\tclass_<MiindModel, bases<' + abstract_type(typ) + '>>("MiindModel", init<int,long>())\n')

    if len(variable_list) > 0:
        var_types = variables.parse_variable_types(variable_list)
        outfile.write('\t.def(init<int,long' + var_types + '>())\n')
    outfile.write('\t.def("init", &MiindModel::init)\n')
    outfile.write('\t.def("endSim", &MiindModel::endSim);\n')
    outfile.write('}\n')

def parse_xml(infile, outfile):
    tree=ET.fromstring(infile.read())
    m=tree.find('WeightType')
    s = m.text
    return define_network_type(s), tree

def constructor_override(outfile,tree,typ):

    variable_list = tree.findall('Variable')
    variables.parse_variables(variable_list,outfile)

    outfile.write('\tMiindModel(int num_nodes, long simulation_length ):\n')
    outfile.write('\t\tMiindTvbModelAbstract(num_nodes, simulation_length){}\n\n')

    if len(variable_list) > 0:
        outfile.write('\tMiindModel(int num_nodes, long simulation_length \n')
        variables.parse_variables_as_parameters(variable_list,outfile)
        outfile.write('):\n')
        outfile.write('\t\tMiindTvbModelAbstract(num_nodes, simulation_length)\n')
        variables.parse_variables_as_constructor_defaults(variable_list, outfile)
        outfile.write('{}\n\n')

    outfile.write('\tvoid endSim(){\n')
    outfile.write('\tclose_display = true;\n')
    # outfile.write('\t' + abstract_type(typ) + '::endSimulation();\n')
    outfile.write('\t}\n\n')

def generate_opening(outfile, tree, typ):
    outfile.write('class MiindModel : public ' + abstract_type(typ) + ' {\n')
    outfile.write('public:\n\n')
    outfile.write('\tbool close_display;\n')
    constructor_override(outfile, tree,typ)
    outfile.write('\n')
    outfile.write('\tvoid init(boost::python::list params)\n')
    outfile.write('\t{\n')
    t_step = tree.find('SimulationRunParameter/t_step')
    outfile.write('\t\t_time_step = ' + t_step.text + ';\n')
    outfile.write('\t\tfor(int i=0; i<_num_nodes; i++) {\n')


def model_name(fn):
    '''Identifies model files mentioned in an XML file. For example used in placing the right model file in
    the same directory as an XML file.'''
    infile = open(fn)
    tree=ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm')

    modelnames = []
    for a in ma:
        if a.attrib['type'] == 'MeshAlgorithm' or a.attrib['type'] == 'GridAlgorithm':
            modelnames.append(a.attrib['modelfile'])
    return modelnames

def matrix_names(fn):
    '''Find the file names of all MatrixFiles, mentioned in an XML file.'''
    infile = open(fn)
    tree=ET.fromstring(infile.read())
    ma = tree.findall('Algorithms/Algorithm/MatrixFile')
    matrixnames = []
    for a in ma:
        matrixnames.append(a.text)
    return matrixnames

def generate_outputfile(infile, outfile):
    generate_preamble(outfile)
    nettype, tree = parse_xml(infile,outfile)
    outfile.write(nettype)
    outfile.write('\t// defining variables\n') # whatever variables are use are global

    algies = tree.findall('Algorithms')
    if len(algies) != 1:
        raise ValueError

    alg_list = algies[0].findall('Algorithm')
    weighttype = tree.find('WeightType')
    generate_opening(outfile, tree, weighttype.text)
    outfile.write('\t// generating algorithms\n')
    algorithms.parse_algorithms(alg_list,weighttype,outfile)
    node_list = tree.findall('Nodes/Node')
    outfile.write('\t// generating nodes\n')
    nodes.parse_nodes(node_list,weighttype,outfile)
    outfile.write('\t// generating connections\n')
    connection_list = tree.findall('Connections/Connection')
    connections.parse_connections(connection_list,weighttype,outfile)
    connection_list = tree.findall('Connections/IncomingConnection')
    connections.parse_incoming_connections(connection_list,weighttype,outfile)
    connection_list = tree.findall('Connections/OutgoingConnection')
    connections.parse_outgoing_connections(connection_list,outfile)
    generate_closing(outfile, weighttype.text, tree)
    algorithms.reset_algorithms()
    nodes.reset_nodes()
