# (C) Copyright 2018- ECMWF.
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation
# nor does it submit to any jurisdiction.

from collections import OrderedDict, defaultdict
from pathlib import Path
from hashlib import sha256

from loki.backend import maxjgen, fgen, cgen
from loki.expression import (
    FindVariables, SubstituteExpressions, ExpressionCallbackMapper,
    SubstituteExpressionsMapper, ExpressionRetriever, symbols as sym
)
from loki import ir
from loki.module import Module
from loki.pragma_utils import is_loki_pragma, pragmas_attached
from loki.sourcefile import Sourcefile
from loki.subroutine import Subroutine
from loki.tools import as_tuple, flatten
from loki.transform.fortran_c_transform import FortranCTransformation
from loki.transform.transformation import Transformation
from loki.transform.transform_array_indexing import (
    shift_to_zero_indexing, invert_array_indices,
    resolve_vector_notation, normalize_range_indexing
)
from loki.transform.transform_utilities import replace_intrinsics
from loki.types import SymbolAttributes, BasicType, DerivedType
from loki.visitors import Transformer, FindNodes


__all__ = ['FortranMaxTransformation']


class FortranMaxTransformation(Transformation):
    """
    Fortran-to-Maxeler transformation that translates the given routine
    into .maxj and generates a matching manager and host code with
    corresponding ISO-C wrappers.
    """

    def __init__(self):
        super().__init__()

        # Maps from original type name to ISO-C and C-struct types
        self.c_structs = OrderedDict()

    def transform_subroutine(self, routine, **kwargs):
        self.maxj_src = Path(kwargs.get('path')) / routine.name
        self.maxj_src.mkdir(exist_ok=True)

        for arg in routine.arguments:
            if isinstance(arg.type.dtype, DerivedType):
                self.c_structs[arg.type.name.lower()] = FortranCTransformation.c_struct_typedef(arg.type)

        # Create a copy of the kernel and apply some common transformations
        routine = routine.clone()
        routine = self._convert_variables_to_lowercase(routine)
        routine = self._remove_implicit_statements(routine)

        # Generate the DFE kernel
        maxj_kernel = self._generate_dfe_kernel(routine)
        self.maxj_kernel_path = (self.maxj_src / maxj_kernel.name).with_suffix('.maxj')
        maxj_module = self._generate_dfe_kernel_module(maxj_kernel)
        Sourcefile.to_file(source=maxjgen(maxj_module), path=self.maxj_kernel_path)

        # Generate the SLiC host interface
        host_interface = self._generate_slic_interface(routine, maxj_kernel)

        # Generate Fortran wrapper module
        wrapper = FortranCTransformation.generate_iso_c_wrapper_routine(
            host_interface, self.c_structs, bind_name=host_interface.name)
        self.wrapperpath = (self.maxj_src / wrapper.name.lower()).with_suffix('.f90')
        contains = ir.Section(body=(ir.Intrinsic('CONTAINS'), wrapper))
        module = Module(name=f'{wrapper.name.upper()}_MOD', contains=contains)
        Sourcefile.to_file(source=fgen(module), path=self.wrapperpath)

        # Generate C host code
        host_interface.spec.prepend(ir.Import(f'{routine.name}.h', c_import=True))
        host_interface = self._convert_arguments_to_pointer(host_interface)
        self.c_path = (self.maxj_src / host_interface.name).with_suffix('.c')
        Sourcefile.to_file(source=cgen(host_interface), path=self.c_path)

        # Generate kernel manager
        maxj_manager_intf = self._generate_dfe_manager_intf(maxj_kernel)
        self.maxj_manager_intf_path = (self.maxj_src / maxj_manager_intf.name).with_suffix('.maxj')
        Sourcefile.to_file(source=maxjgen(maxj_manager_intf), path=self.maxj_manager_intf_path)

        maxj_manager = self._generate_dfe_manager(maxj_kernel)
        self.maxj_manager_path = (self.maxj_src / maxj_manager.name).with_suffix('.maxj')
        Sourcefile.to_file(source=maxjgen(maxj_manager), path=self.maxj_manager_path)

    @staticmethod
    def _convert_variables_to_lowercase(routine):
        """
        Convert all variables to lower-case, as Java and C are case-sensitive.
        """
        vmap = {v: v.clone(name=v.name.lower()) for v in FindVariables().visit(routine.ir)
                if not v.name.islower()}
        routine.spec = SubstituteExpressions(vmap).visit(routine.spec)
        routine.body = SubstituteExpressions(vmap).visit(routine.body)
        return routine

    @staticmethod
    def _remove_implicit_statements(routine):
        """
        Remove all IMPLICIT statements.
        """
        stmt_map = {stmt: None for stmt in FindNodes(ir.Intrinsic).visit(routine.spec)
                    if stmt.text.lstrip().lower().startswith('implicit')}
        routine.spec = Transformer(stmt_map).visit(routine.spec)
        return routine

    @staticmethod
    def _split_and_order_arguments(routine):
        """
        Copy all arguments and split 'inout' arguments into a new 'in'-argument and
        the original 'inout' argument that has the 'in'-argument as initial value assigned.
        """
        declarations = FindNodes(ir.VariableDeclaration).visit(routine.spec)
        decl_map = dict((v, decl) for decl in declarations for v in decl.symbols)

        arguments = []
        out_map = {}
        var_map = {}
        for arg in routine.arguments:
            if arg.type.intent.lower() == 'inout':
                # Create matching instream argument
                in_type = arg.type.clone(intent='in', dfevar=True)
                arg_in = arg.clone(name=f'{arg.name}_in', type=in_type)
                # Modify existing argument
                arg_out = arg.clone(type=arg.type.clone(dfevar=True, initial=arg_in))
                var_map[arg] = arg_out
                arguments += [arg_in, arg_out]
                # Enlist declaration of modified argument for removal
                decl = decl_map[arg]
                if len(decl.symbols) > 1:
                    out_map[decl] = decl.clone(symbols=tuple(v for v in decl.symbols if v != arg))
                else:
                    out_map[decl] = None
            elif arg.type.intent is not None:
                arguments += [arg.clone(type=arg.type.clone(dfevar=True))]
            else:
                arguments += [arg]

        # In the SLiC interface, scalars are kept in-order apparently, followed by
        # instreams (alphabetically) and then outstreams (alphabetically)
        scalar_arguments = [arg for arg in arguments
                            if arg.type.intent.lower() == 'in' and isinstance(arg, sym.Scalar)]
        in_arguments = [arg for arg in arguments
                        if arg.type.intent.lower() == 'in' and isinstance(arg, sym.Array)]
        out_arguments = [arg for arg in arguments if arg.type.intent.lower() in ('inout', 'out')]
        in_arguments.sort(key=lambda a: a.name)
        out_arguments.sort(key=lambda a: a.name)

        # Remove declarations of inout-arguments that now depend on the new in arguments and
        # thus have to be declared at the end
        routine.spec = Transformer(out_map).visit(routine.spec)

        # Update the argument list of the routine
        # This also re-creates the deleted declarations
        routine.arguments = scalar_arguments + in_arguments + out_arguments

        return routine

    @staticmethod
    def _convert_arguments_to_pointer(routine):
        """
        Force pointer on reference-passed arguments (i.e., all except input scalars).
        """
        routine.arguments = [arg if arg.type.intent.lower() == 'in' and isinstance(arg, sym.Scalar)
                             else arg.clone(type=arg.type.clone(pointer=True)) for arg in routine.arguments]
        return routine

    def _generate_dfe_kernel(self, routine, **kwargs):  # pylint: disable=unused-argument
        # Create a copy for the MaxJ kernel
        max_kernel = routine.clone(name=f'{routine.name}Kernel')

        # Transform arguments list
        max_kernel = self._split_and_order_arguments(max_kernel)

        # Remove parameter declarations for data types
        max_kernel.variables = [v for v in max_kernel.variables
                                if not (isinstance(v.initial, sym.InlineCall) and
                                        'select_real_kind' in v.initial.name)]

        # Some vector notation sanitation
        resolve_vector_notation(max_kernel)
        normalize_range_indexing(max_kernel)

        # Remove dataflow loops
        loop_map = {}
        var_map = {}
        dataflow_indices = []
        with pragmas_attached(max_kernel, ir.Loop):
            for loop in FindNodes(ir.Loop).visit(max_kernel.body):
                if is_loki_pragma(loop.pragma, starts_with='dataflow'):
                    loop_map[loop] = loop.body
                    # We have to add 1 since FORTRAN counts from 1
                    call_fct = sym.ProcedureSymbol('control.count.simpleCounter', scope=max_kernel)
                    vinit = sym.Sum((sym.InlineCall(call_fct, parameters=(sym.Literal(32),)), sym.Literal(1)))
                    # TODO: Add support for wrap point
                    #                      parameters=(Literal(32), loop.bounds[1]))
                    var_map[loop.variable] = loop.variable.clone(
                        type=loop.variable.type.clone(dfevar=True, initial=vinit))
                    dataflow_indices += [str(loop.variable)]
        max_kernel.spec = SubstituteExpressions(var_map).visit(max_kernel.spec)
        max_kernel.body = Transformer(loop_map).visit(max_kernel.body)

        # Replace conditionals by conditional statements
        # TODO: This does not handle nested conditionals!
        cond_map = {}
        cond_type = SymbolAttributes(BasicType.LOGICAL)
        for cnt, cond in enumerate(FindNodes(ir.Conditional).visit(max_kernel.body)):
            body = []

            # Extract conditions as separate variables
            cond_var = sym.Variable(name=f'cond_{cnt}', type=cond_type.clone(), scope=max_kernel)
            body += [ir.Assignment(lhs=cond_var, rhs=cond.condition)]
            max_kernel.variables += as_tuple(cond_var)

            # Hacky heuristic: We use body and else body to hangle us along the order of statements
            # TODO: Do this in a better way!
            else_stmts = FindNodes(ir.Assignment).visit(cond.else_body)
            for stmt in FindNodes(ir.Assignment).visit(cond.body):
                # Try to find a matching statement in else_stmts
                for i, s in enumerate(else_stmts):
                    if s.lhs == stmt.lhs:
                        else_index = i
                        break
                else:
                    else_index = -1

                # Create conditional assignment
                if else_index == -1:
                    # no matching else-stmt: insert only body-stmt
                    cond_stmt = ir.ConditionalAssignment(lhs=stmt.lhs, condition=cond_var,
                                                         rhs=stmt.rhs, else_rhs=stmt.lhs)
                    body += [cond_stmt]
                else:
                    # insert any else-stmts before the matching stmt
                    for else_stmt in else_stmts[:else_index]:
                        cond_stmt = ir.ConditionalAssignment(lhs=else_stmt.lhs, condition=cond_var,
                                                             rhs=else_stmt.lhs, else_rhs=else_stmt.rhs)
                        body += [cond_stmt]

                    # conditional assignment with body-stmt rhs and else-stmt rhs
                    cond_stmt = ir.ConditionalAssignment(lhs=stmt.lhs, condition=cond_var,
                                                         rhs=stmt.rhs, else_rhs=else_stmts[else_index].rhs)
                    body += [cond_stmt]

                    # remove processed else_stmts
                    else_stmts = else_stmts[else_index+1:]

            cond_map[cond] = body
        max_kernel.body = Transformer(cond_map).visit(max_kernel.body)

        # Mark DFEVar variables:
        # Add the attribute `dfevar` to the type of all variables that depend on a
        # `dfevar` variable (which are initially all 'in', 'inout'-arguments and dataflow loop
        # variables)
        def is_dfevar(expr, *args, **kwargs):  # pylint: disable=unused-argument
            return {isinstance(expr, (sym.Scalar, sym.Array)) and expr.type.dfevar is True}
        dfevar_mapper = ExpressionCallbackMapper(callback=is_dfevar, combine=lambda v: {any(v)})
        node_fields = {ir.Assignment: ('rhs',),
                       ir.ConditionalAssignment: ('condition', 'rhs', 'else_rhs')}

        for stmt in FindNodes(tuple(node_fields.keys())).visit(max_kernel.body):
            is_dfe = any(dfevar_mapper(getattr(stmt, attr)).pop()
                         for attr in node_fields[stmt.__class__])
            if not stmt.lhs.type.dfevar and is_dfe:
                max_kernel.symbol_attrs[stmt.lhs.name] = stmt.lhs.type.clone(dfevar=is_dfe)

        # Replace array access by stream inflow
        if dataflow_indices:
            scalar_retriever = ExpressionRetriever(lambda e: isinstance(e, sym.Scalar))
            vmap = {}
            arr_args = {arg.name: arg for arg in max_kernel.arguments if isinstance(arg, sym.Array)}
            for v in FindVariables(unique=False).visit(max_kernel.ir):
                # All array subscripts must be transformed to streams/stream offsets
                if isinstance(v, sym.Array) and v.dimensions is not None:
                    dfe_dims = {d: d.name in dataflow_indices for d in scalar_retriever.retrieve(v)}
                    if not any(dfe_dims.values()) or v in vmap:
                        continue

                    # TODO: we can only handle 1D arrays for now
                    dim = dataflow_indices[0]
                    if len(v.dimensions) > 1:
                        raise NotImplementedError('Can not handle >1 dataflow dimensions!')
                    index = v.dimensions[0]

                    # Make sure the stream for that array exists
                    assert v.name in arr_args
                    # if v.name not in in_streams:
                    #     in_streams[v.name] = v.clone(dimensions=None, type=v_type, initial=None)

                    # Stream should have no shape but the stream property instead
                    if arr_args[v.name] not in vmap:
                        new_type = arr_args[v.name].type.clone(shape=None, dfestream=True)
                        stream = arr_args[v.name].clone(dimensions=None, type=new_type)
                        vmap[arr_args[v.name]] = stream
                    else:
                        stream = vmap[arr_args[v.name]]

                    # Array subscript corresponds to current stream position: Replace array
                    # subscript by stream argument
                    if str(index) == dim:
                        vmap[v] = stream
                    elif v not in vmap:  # We have to create/use an offset stream
                        # Hacky: Replace dataflow index (loop variable) by zero
                        retriever = ExpressionRetriever(lambda e, dim=dim: isinstance(e, sym.Scalar) and str(e) == dim)
                        dmap = {d: sym.Literal(0) for d in retriever.retrieve(v)}
                        offset = SubstituteExpressionsMapper(dmap)(index)
                        # Create the offset-variable
                        fct_symbol = sym.ProcedureSymbol('stream.offset', scope=max_kernel)
                        initial = sym.InlineCall(fct_symbol, parameters=(stream, offset))
                        var_hash = sha256(str(v).encode('utf-8')).hexdigest()[:10]
                        name = f'{v.name}_{var_hash}'
                        vmap[v] = v.clone(name=name, dimensions=None,
                                          type=stream.type.clone(intent=None, initial=initial))
            max_kernel.spec = SubstituteExpressions(vmap).visit(max_kernel.spec)
            max_kernel.body = SubstituteExpressions(vmap).visit(max_kernel.body)

            # Update list of variables to include new offset streams
            variables = [v for v in max_kernel.variables if v not in vmap or v in vmap.values()]
            new_vars = [v for v in vmap.values() if v not in variables]
            max_kernel.variables = as_tuple(variables + new_vars)

        # Find out which streams are actually unneeded and remove them
        # (e.g., because they got obsolete with the removal of the dataflow loop or due to 'inout'
        # being split up into 'in' and 'out' but the argument being actually purely 'in' or 'out')
        used_var_names = [v.name for v in FindVariables().visit(max_kernel.body)]
        for v in max_kernel.variables:
            # We have to add initialization variables by hand because the mapper does not recurse
            # to them
            if v.initial is not None:
                used_var_names += [i.name for i in FindVariables().visit(v.initial)]
        obsolete_args = [arg for arg in max_kernel.arguments if arg.name not in used_var_names]
        max_kernel.variables = [v for v in max_kernel.variables if v not in obsolete_args]

        # Add casts to dataflow constants for literal assignments
        smap = {}
        for stmt in FindNodes(ir.Assignment).visit(max_kernel.body):
            if stmt.lhs.type.dfevar:
                if isinstance(stmt.rhs, (sym.FloatLiteral, sym.IntLiteral)):
                    _type = sym.InlineCall(sym.ProcedureSymbol(f'{stmt.lhs.name}.getType',
                                                               scope=max_kernel))
                    rhs = sym.InlineCall(sym.ProcedureSymbol('constant.var', scope=max_kernel),
                                         parameters=(_type, stmt.rhs))
                    smap[stmt] = ir.Assignment(lhs=stmt.lhs, rhs=rhs)
        max_kernel.body = Transformer(smap).visit(max_kernel.body)

        def base_type(var_type):
            # TODO: put this somewhere else
            if var_type.dtype == BasicType.LOGICAL:
                return sym.InlineCall(sym.ProcedureSymbol('dfeBool', scope=max_kernel))
            if var_type.dtype == BasicType.INTEGER:
                # TODO: Distinguish between signed and unsigned
                return sym.InlineCall(sym.ProcedureSymbol('dfeUInt', scope=max_kernel),
                                      parameters=(sym.IntLiteral(32),))
            if var_type.dtype == BasicType.REAL:
                if var_type.kind in ['real32']:
                    parameters = (sym.IntLiteral(8), sym.IntLiteral(24))
                else:
                    parameters = (sym.IntLiteral(11), sym.IntLiteral(53))
                return sym.InlineCall(sym.ProcedureSymbol('dfeFloat', scope=max_kernel),
                                      parameters=parameters)
            raise ValueError()

        def decl_type(var_type):
            # TODO: put this somewhere else
            if not var_type.shape:
                return 'DFEVar'
            return f'DFEVector<{decl_type(var_type.clone(shape=var_type.shape[:-1]))}>'

        def init_type(var_type):
            # TODO: put this somewhere else
            if not var_type.shape:
                return base_type(var_type)
            sub_type = var_type.clone(shape=var_type.shape[:-1])
            name = f'new DFEVectorType<{decl_type(sub_type)}>'
            parameters = (init_type(sub_type), var_type.shape[-1])
            return sym.InlineCall(sym.ProcedureSymbol(name, scope=max_kernel), parameters=parameters)

        # Initialization of dfevars
        var_map = {}
        for var in max_kernel.variables:
            if var.type.dfevar:
                if var.type.intent and var.type.intent.lower() == 'in':
                    if isinstance(var, sym.Array) or var.type.dfestream:
                        name = 'io.input'
                    else:
                        name = 'io.scalarInput'
                    parameters = (sym.StringLiteral(f'"{var.name}"'), init_type(var.type))
                    initial = sym.InlineCall(sym.ProcedureSymbol(name, scope=max_kernel),
                                             parameters=parameters)
                    var_map[var] = var.clone(type=var.type.clone(initial=initial))
                elif var.initial is None:
                    name = f'{init_type(var.type)}.newInstance'
                    if isinstance(var, sym.Array):
                        parameters = (sym.IntrinsicLiteral('this'),)
                    else:
                        parameters = (sym.IntrinsicLiteral('this'), sym.IntLiteral(0))
                    initial = sym.InlineCall(sym.ProcedureSymbol(name, scope=max_kernel),
                                             parameters=parameters)
                    var_map[var] = var.clone(type=var.type.clone(initial=initial))
        max_kernel.spec = SubstituteExpressions(var_map).visit(max_kernel.spec)

        # Insert outflow statements for output variables
        for var in max_kernel.arguments:
            if var.type.intent.lower() in ('inout', 'out'):
                if isinstance(var, sym.Array) or var.type.dfestream:
                    name = sym.Variable(name='io.output')
                else:
                    name = sym.Variable(name='io.scalarOutput')
                parameters = (sym.StringLiteral(f'"{var.name}"'),
                              var.clone(dimensions=None), init_type(var.type))
                stmt = ir.CallStatement(name, arguments=parameters)
                max_kernel.body.append(stmt)

        # TODO: Resolve reductions (eg. SUM(myvar(:)))
        shift_to_zero_indexing(max_kernel)
        invert_array_indices(max_kernel)
        replace_intrinsics(max_kernel, function_map={'mod': 'KernelMath.modulo'})

        return max_kernel

    @staticmethod
    def _generate_dfe_kernel_module(kernel, **kwargs):  # pylint: disable=unused-argument
        """
        Create the Maxj kernel module that wraps the DFE kernel routine.
        """
        # Some boilerplate imports
        standard_imports = ['Kernel', 'KernelParameters', 'stdlib.KernelMath', 'types.base.DFEVar',
                            'types.composite.DFEVector', 'types.composite.DFEVectorType']
        standard_imports_basepath = 'com.maxeler.maxcompiler.v2.kernelcompiler.'
        spec = [ir.Import(standard_imports_basepath + imprt) for imprt in standard_imports]

        max_module = Module(name=kernel.name, spec=ir.Section(body=as_tuple(spec)))
        max_kernel = kernel.clone(parent=max_module)

        # Remove all arguments (as they are streamed in now) and insert parameter argument
        arg_type = SymbolAttributes(DerivedType('KernelParameters'), intent='in')
        arg = sym.Variable(name='params', type=arg_type, scope=max_kernel)
        max_kernel.arguments = as_tuple(arg)
        max_kernel.spec.prepend(ir.CallStatement(sym.Variable(name='super'), arguments=(arg,)))

        # Add kernel to wrapper module
        max_module.contains = ir.Section(body=as_tuple(max_kernel))
        return max_module

    @staticmethod
    def _generate_dfe_manager_intf(kernel, **kwargs):  # pylint: disable=unused-argument
        """
        Create the Maxj manager interface that configures the DFE kernel.
        """
        name = kernel.name.replace('Kernel', '')

        # Create the manager class
        # TODO: Use a TypeDef once we have typebound procedures etc.
        spec = [ir.Import('com.maxeler.maxcompiler.v2.kernelcompiler.Kernel')]
        spec += [ir.Import('com.maxeler.maxcompiler.v2.managers.custom.blocks.KernelBlock')]
        spec += [ir.Import('com.maxeler.maxcompiler.v2.managers.custom.api.ManagerPCIe')]
        spec += [ir.Import('com.maxeler.maxcompiler.v2.managers.custom.api.ManagerKernel')]
        spec += [ir.Intrinsic(f'static final String kernelName = "{kernel.name}";')]
        manager = Module(name=f'{name}Manager', spec=ir.Section(body=as_tuple(spec)))

        # Create the setup
        setup = Subroutine(name='default void setup', parent=manager, spec=ir.Section(body=()))

        body = [ir.Intrinsic(f'Kernel kernel = new {kernel.name}(makeKernelParameters(kernelName));')]

        # Insert in/out streams
        streams = defaultdict(list)
        for arg in kernel.arguments:
            if arg.type.intent and (arg.type.dfestream or isinstance(arg, sym.Array)):
                streams[arg.type.intent.lower()] += [arg]

        if streams:
            body += [ir.Intrinsic('KernelBlock kernelBlock = addKernel(kernel);')]
        else:
            body += [ir.Intrinsic('addKernel(kernel);')]

        for stream in streams['in']:
            body += [ir.Intrinsic(
                f'kernelBlock.getInput("{stream.name}") <== addStreamFromCPU("{stream.name}");')]
        for stream in streams['inout'] + streams['out']:
            body += [ir.Intrinsic(
                f'addStreamToCPU("{stream.name}") <== kernelBlock.getOutput("{stream.name}");')]
        setup.body = ir.Section(body=as_tuple(body))

        # Insert functions into manager class
        manager.contains = ir.Section(body=as_tuple(setup))
        return manager

    @staticmethod
    def _generate_dfe_manager(kernel, **kwargs):  # pylint: disable=unused-argument
        """
        Create the Maxj manager for the MAX5C platform.
        """
        name = kernel.name.replace('Kernel', '')

        # Create the manager class
        # TODO: Use a TypeDef once we have typebound procedures etc.
        standard_imports = ['maxcompiler.v2.build.EngineParameters',
                            'platform.max5.manager.MAX5CManager']
        standard_imports_basepath = 'com.maxeler.'
        spec = [ir.Import(standard_imports_basepath + imprt) for imprt in standard_imports]
        manager = Module(name=f'{name}ManagerMAX5C', spec=ir.Section(body=as_tuple(spec)))

        # Create the constructor
        constructor = Subroutine(name=manager.name, parent=manager, spec=ir.Section(body=()))
        params_type = SymbolAttributes(DerivedType('EngineParameters'), intent='in')
        params = sym.Variable(name='params', type=params_type, scope=constructor)
        body = [ir.CallStatement(sym.Variable(name='super'), arguments=(params,)),
                ir.CallStatement(sym.Variable(name='setup'), arguments=())]
        constructor.arguments = as_tuple(params)
        constructor.body = ir.Section(body=as_tuple(body))

        # Create the main function for maxJavaRun
        main = Subroutine(name='public static void main', parent=manager,
                          spec=ir.Section(body=()))
        args_type = SymbolAttributes(DerivedType('String[]'), intent='in')
        args = sym.Variable(name='args', type=args_type, scope=main)
        main.arguments = as_tuple(args)

        params_type = SymbolAttributes(
            DerivedType('EngineParameters'), initial=sym.InlineCall(
                sym.ProcedureSymbol('new EngineParameters', scope=main), parameters=(args,)))
        params = sym.Variable(name='params', type=params_type, scope=main)
        mgr_type = SymbolAttributes(
            DerivedType('MAX5CManager'), initial=sym.InlineCall(
                sym.ProcedureSymbol(f'new {manager.name}', scope=main), parameters=(params,)))
        mgr = sym.Variable(name='manager', type=mgr_type, scope=main)
        main.variables += as_tuple([params, mgr])
        body = (ir.CallStatement(sym.Variable(name='manager.build'), arguments=()), )
        main.body = ir.Section(body=body)

        # Insert functions into manager class
        manager.contains = ir.Section(body=(constructor, main))
        return manager

    @staticmethod
    def _generate_slic_interface(routine, kernel, **kwargs):  # pylint: disable=unused-argument
        """
        Create the SLiC interface that calls the DFE kernel.
        """
        # Create a copy of the routine that has only the routine's spec
        slic_routine = routine.clone(name=f'{routine.name}_c', body=None)

        # Add an argument for ticks
        size_t_type = SymbolAttributes(BasicType.INTEGER, intent='in')  # TODO: make this size_t
        ticks_argument = sym.Variable(name='ticks', type=size_t_type, scope=kernel)
        arguments = (ticks_argument,) + slic_routine.arguments

        # The DFE wants to know array sizes, so we replace array arguments by pairs (arg, arg_size)
        def generate_arg_tuple(arg):
            if isinstance(arg, sym.Array):
                return (arg, sym.Variable(name=f'{arg.name}_size', type=size_t_type, scope=slic_routine))
            return arg
        arguments = flatten([generate_arg_tuple(arg) for arg in arguments])

        # Remove initial values from arguments
        arguments = tuple(arg.clone(type=arg.type.clone(initial=None)) for arg in arguments)

        # Update the routine's arguments and remove any other variables
        slic_routine.variables = ()  # [v for v in slic_routine.variables if v.type.parameter]
        slic_routine.arguments = arguments

        # Create the call to the DFE kernel
        variable_map = slic_routine.variable_map

        # TODO: actually create a CallStatement. Not possible currently because we don't represent
        #       all the cases around pointer dereferencing etc that are necessary here
        call_arguments = [ticks_argument.name]  # pylint: disable=no-member
        for arg in kernel.arguments:
            if arg.name.endswith('_in') and arg.name not in variable_map:
                if isinstance(arg, sym.Array) or arg.type.dfestream:
                    call_arguments += [arg.name[:-3]]
                else:
                    call_arguments += [f'*{arg.name[:-3]}']
            else:
                call_arguments += [arg.name]
            if isinstance(arg, sym.Array) or arg.type.dfestream:
                call_arguments += [f'{call_arguments[-1]}_size']
        call = ir.Intrinsic(f'{routine.name}({", ".join(call_arguments)});')

        # Assign the body of the SLiC interface routine
        slic_routine.body = ir.Section(body=as_tuple(call))
        return slic_routine
