#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
***********************************************************************************
                           tutorial_dealii_7.py
                DAE Tools: pyDAE module, www.daetools.com
                Copyright (C) Dragan Nikolic
***********************************************************************************
DAE Tools is free software; you can redistribute it and/or modify it under the
terms of the GNU General Public License version 3 as published by the Free Software
Foundation. DAE Tools is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with the
DAE Tools software; if not, see <http://www.gnu.org/licenses/>.
************************************************************************************
"""
__doc__ = """
In this example 2D transient Stokes flow driven by the differences in buoyancy caused
by the temperature differences in the fluid is solved 
(`deal.II step-31 <https://www.dealii.org/8.5.0/doxygen/deal.II/step_31.html>`_).

The differences to the original problem are that the grid is not adaptive and no 
stabilisation method is used.

The problem can be described using the Stokes equations:

.. code-block:: none

   -div(2 * eta * eps(u)) + nabla(p) = -rho * beta * g * T in Omega
   -div(u) = 0 in Omega
   dT/dt + div(u * T) - div(k * nabla(T)) = gamma in Omega

The mesh is a simple square (0,1)x(0,1):

.. image:: _static/square(0,1)x(0,1)-50x50.png
   :width: 300 px

The temperature and the velocity vectors plot:

.. image:: _static/tutorial_dealii_7-results.png
   :height: 400 px

Animation:
    
.. image:: _static/tutorial_dealii_7-animation.gif
   :height: 400 px
"""

import os, sys, numpy, json, tempfile, random
from time import localtime, strftime
from daetools.pyDAE import *
from daetools.solvers.deal_II import *
from daetools.solvers.superlu import pySuperLU

# Standard variable types are defined in variable_types.py
from pyUnits import m, kg, s, K, Pa, mol, J, W

class VelocityFunction_2D(adoubleFunction_2D):
    def __init__(self, n_components = 1):
        adoubleFunction_2D.__init__(self, n_components)
        
        self.n_components = n_components

    def vector_value(self, point):
        values = [adouble(0.0)] * self.n_components
        values[0] = adouble(0.0) # ux component
        values[1] = adouble(0.0) # uy component
        return values

class TemperatureSource_2D(Function_2D):
    def __init__(self, n_components = 1):
        Function_2D.__init__(self, n_components)

        # Centers of the heat source objects
        self.centers = [Point_2D(0.3, 0.1), 
                        Point_2D(0.45, 0.1), 
                        Point_2D(0.75, 0.1)]
        # Radius of the heat source objects
        self.radius  = 1.0 / 32.0

    def value(self, point, component = 0):
        if (self.centers[0].distance(point) < self.radius) or \
           (self.centers[1].distance(point) < self.radius) or \
           (self.centers[2].distance(point) < self.radius):
            return 1.0
        else:
            return 0.0

    def vector_value(self, point):
        return [self.value(point, c) for c in range(self.n_components)]

class modTutorial(daeModel):
    def __init__(self, Name, Parent = None, Description = ""):
        daeModel.__init__(self, Name, Parent, Description)

        dofs = [dealiiFiniteElementDOF_2D(name='u',
                                          description='Velocity',
                                          fe = FE_Q_2D(1),
                                          multiplicity=2),
                dealiiFiniteElementDOF_2D(name='p',
                                          description='Pressure',
                                          fe = FE_Q_2D(1),
                                          multiplicity=1),
                dealiiFiniteElementDOF_2D(name='T',
                                          description='Temperature',
                                          fe = FE_Q_2D(1),
                                          multiplicity=1)]
        self.n_components = int(numpy.sum([dof.Multiplicity for dof in dofs]))

        meshes_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'meshes')
        mesh_file  = os.path.join(meshes_dir, 'square(0,1)x(0,1)-96x96.msh')

        # Store the object so it does not go out of scope while still in use by daetools
        self.fe_system = dealiiFiniteElementSystem_2D(meshFilename    = mesh_file,     # path to mesh
                                                      quadrature      = QGauss_2D(3),  # quadrature formula
                                                      faceQuadrature  = QGauss_1D(3),  # face quadrature formula
                                                      dofs            = dofs)          # degrees of freedom

        self.fe_model = daeFiniteElementModel('Boussinesq', self, 'The Boussinesq equation', self.fe_system)

    def DeclareEquations(self):
        daeModel.DeclareEquations(self)

        # Boundary IDs
        left_edge   = 0
        top_edge    = 1
        right_edge  = 2
        bottom_edge = 3

        # Create some auxiliary objects for readability
        phi_p_i         =  phi_2D('p', fe_i, fe_q)
        phi_p_j         =  phi_2D('p', fe_j, fe_q)
        dphi_p_i        = dphi_2D('p', fe_i, fe_q)
        dphi_p_j        = dphi_2D('p', fe_j, fe_q)
        
        phi_vector_u_i  =         phi_vector_2D('u', fe_i, fe_q)
        phi_vector_u_j  =         phi_vector_2D('u', fe_j, fe_q)
        div_phi_u_i     =            div_phi_2D('u', fe_i, fe_q)
        div_phi_u_j     =            div_phi_2D('u', fe_j, fe_q)
        sym_grad_u_i    = symmetric_gradient_2D('u', fe_i, fe_q)
        sym_grad_u_j    = symmetric_gradient_2D('u', fe_j, fe_q)
        
        phi_T_i         =  phi_2D('T', fe_i, fe_q)
        phi_T_j         =  phi_2D('T', fe_j, fe_q)
        dphi_T_i        = dphi_2D('T', fe_i, fe_q)
        dphi_T_j        = dphi_2D('T', fe_j, fe_q)
        
        # FE approximation of T at the specified quadrature point (adouble object)
        T_dof = dof_approximation_2D('T', fe_q)
        
        # FE approximation of u at the specified quadrature point (SUM(Tensor<1>*u(j)) object
        u_dof = vector_dof_approximation_2D('u', fe_q)
        
        normal  = normal_2D(fe_q)
        xyz     = xyz_2D(fe_q)
        JxW     = JxW_2D(fe_q)
        
        #h       = cell_diameter_2D()
        #sqrt_fe = feExpression_2D.sqrt
        #kappa_art = 0.25 * h * sqrt_fe(u_dof*u_dof)
        
        self.gammaFun = TemperatureSource_2D()
        gamma = function_value_2D("gamma", self.gammaFun, xyz)
        
        kappa = 2E-05
        beta  = 10.0
        eta   = 1.0
        rho   = 1.0
        g     = -Point_2D(0.0, 1.0)
        gravity = tensor1_2D(g)

        dirichletBC = {}
        dirichletBC[left_edge]   = [('p', adoubleConstantFunction_2D(adouble(0.0))),
                                    ('u', VelocityFunction_2D(self.n_components))]
        dirichletBC[top_edge]    = [('p', adoubleConstantFunction_2D(adouble(0.0))),
                                    ('u', VelocityFunction_2D(self.n_components))]
        dirichletBC[right_edge]  = [('p', adoubleConstantFunction_2D(adouble(0.0))),
                                    ('u', VelocityFunction_2D(self.n_components))]
        dirichletBC[bottom_edge] = [('p', adoubleConstantFunction_2D(adouble(0.0))),
                                    ('u', VelocityFunction_2D(self.n_components))]
        
        # Mass and stiffness matrix contributions can also be in the form of a three item tuple:
        #  (q_loop_expression, i_loop_expression, j_loop_expression)
        # which is evaluated as q_loop_expression*i_loop_expression*j_loop_expression
        # while load vector contributions can also be in the form of a two item tuple:
        #  (q_loop_expression, i_loop_expression)
        # The advantage of splitting loops is faster assembly (i.e. q_loop_expressions are evaluated only once per quadrature point)
        # and much simpler evaluation trees resulting in low memory requirements.

        # Contributions from the Stokes equation:
        Aij_u_gradient     = 2 * eta * (sym_grad_u_i * sym_grad_u_j) * JxW
        Aij_p_gradient     = -(div_phi_u_i * phi_p_j) * JxW
        Fi_buoyancy        = (T_dof, -rho * beta * (gravity * phi_vector_u_i) * JxW)  # -> float * adouble
        
        # Contributions from the continuity equation:
        Aij_continuity     = -(phi_p_i * div_phi_u_j) * JxW

        # Contributions from the heat convection-diffusion equation:
        Mij_T_accumulation = phi_T_i * phi_T_j * JxW
        #Aij_T_convection   = u_dof*(phi_T_i*dphi_T_j * JxW) # -> Tensor<rank=1,float> * Tensor<rank=1,adouble> 
        Aij_T_convection   = (u_dof, phi_T_i, dphi_T_j * JxW)
        Aij_T_diffusion    = kappa * (dphi_T_i * dphi_T_j) * JxW
        #Aij_T_diffusion    = (kappa + kappa_art, dphi_T_i, dphi_T_j * JxW)
        Fi_T_source        = phi_T_i * gamma * JxW

        # Total contributions (using the new way - python lists of expressions or tuples):
        Mij = [Mij_T_accumulation]
        Aij = [Aij_u_gradient + Aij_p_gradient + Aij_continuity, Aij_T_diffusion,  Aij_T_convection]
        Fi  = [Fi_T_source, Fi_buoyancy]
        
        weakForm = dealiiFiniteElementWeakForm_2D(Aij = Aij,
                                                  Mij = Mij,
                                                  Fi  = Fi,
                                                  functionsDirichletBC = dirichletBC)

        self.fe_system.WeakForm = weakForm

class simTutorial(daeSimulation):
    def __init__(self):
        daeSimulation.__init__(self)
        self.m = modTutorial("tutorial_dealii_7")
        self.m.Description = __doc__
        self.m.fe_model.Description = __doc__

    def SetUpParametersAndDomains(self):
        pass

    def SetUpVariables(self):
        setFEInitialConditions(self.m.fe_model, self.m.fe_system, 'T', 0.0)
        
def run(**kwargs):
    guiRun = kwargs.get('guiRun', False)
    
    simulation = simTutorial()
    
    # Create SuperLU LA solver
    lasolver = pySuperLU.daeCreateSuperLUSolver()

    # Create and setup two data reporters:
    datareporter = daeDelegateDataReporter()
    simName = simulation.m.Name + strftime(" [%d.%m.%Y %H:%M:%S]", localtime())
    if guiRun:
        results_folder = tempfile.mkdtemp(suffix = '-results', prefix = 'tutorial_deal_II_7-')
        daeQtMessage("deal.II", "The simulation results will be located in: %s" % results_folder)
    else:
        results_folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tutorial_deal_II_7-results')
        print("The simulation results will be located in: %s" % results_folder)
    
    # 1. deal.II (exports only FE DOFs in .vtk format to the specified directory)
    feDataReporter = simulation.m.fe_system.CreateDataReporter()
    datareporter.AddDataReporter(feDataReporter)
    if not feDataReporter.Connect(results_folder, simName):
        sys.exit()
        
    # 2. TCP/IP
    tcpipDataReporter = daeTCPIPDataReporter()
    datareporter.AddDataReporter(tcpipDataReporter)
    if not tcpipDataReporter.Connect("", simName):
        sys.exit()

    return daeActivity.simulate(simulation, reportingInterval = 0.5, 
                                            timeHorizon       = 50,
                                            lasolver          = lasolver,
                                            datareporter      = datareporter,
                                            **kwargs)

if __name__ == "__main__":
    guiRun = False if (len(sys.argv) > 1 and sys.argv[1] == 'console') else True
    run(guiRun = guiRun)