#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
@file   python_eigen_strain_test.py

@author Till Junge <till.junge@epfl.ch>

@date   22 Nov 2019

@brief  Unit tests for python bindings

Copyright © 2018 Till Junge

µSpectre is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation, either version 3, or (at
your option) any later version.

µSpectre 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
Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License
along with µSpectre; see the file COPYING. If not, write to the
Free Software Foundation, Inc., 59 Temple Place - Suite 330,
Boston, MA 02111-1307, USA.

Additional permission under GNU GPL version 3 section 7

If you modify this Program, or any covered work, by linking or combining it
with proprietary FFT implementations or numerical libraries, containing parts
covered by the terms of those libraries' licenses, the licensors of this
Program grant you additional permission to convey the resulting work.
"""

import unittest
import numpy as np
from python_test_imports import µ


class EigenStrainCheck(unittest.TestCase):
    def setUp(self):
        self.nb_grid_pts = [3, 3]  # [5,7]
        self.lengths = [3., 3.]  # [5.2, 8.3]
        self.formulation = µ.Formulation.small_strain
        self.cell1 = µ.Cell(self.nb_grid_pts,
                            self.lengths,
                            self.formulation)
        self.cell2 = µ.Cell(self.nb_grid_pts,
                            self.lengths,
                            self.formulation)
        self.mat1 = µ.material.MaterialLinearElastic1_2d.make(
            self.cell1, "simple", 210e9, .33)
        self.mat2 = µ.material.MaterialLinearElastic2_2d.make(
            self.cell2, "eigen", 210e9, .33)
        self.mat3 = µ.material.MaterialLinearElastic2_2d.make(
            self.cell2, "eigen2", 120e9, .33)
        self.dim = len(self.nb_grid_pts)

    def test_globalisation_constant(self):
        for pixel_id in self.cell2.pixel_indices:
            if pixel_id % 2 == 0:
                self.mat2.add_pixel(pixel_id, np.ones((2, 2)))
            else:
                self.mat3.add_pixel(pixel_id, np.ones((2, 2)))
        self.cell2.initialise()
        glo_eigenstrain = self.cell2.get_globalised_internal_real_field(
            "Eigenstrain")
        error = np.linalg.norm(glo_eigenstrain.array()-1)
        self.assertEqual(error, 0)

    def test_globalisation(self):
        for pixel_id in self.cell2.pixel_indices:
            self.mat2.add_pixel(pixel_id, np.random.rand(2, 2))
        self.cell2.initialise()
        loc_eigenstrain = self.mat2.collection.get_real_field(
            "Eigenstrain")
        # At the moment, the cell returns reshaped arrays and the material returns the
        # 2D eigen arrays from muSpectre (To be changed) -> Reshape loc_eigenstrain
        glo_eigenstrain = self.cell2.get_globalised_internal_real_field(
            "Eigenstrain")
        error = np.linalg.norm(loc_eigenstrain.array().ravel(order='A') -
                               glo_eigenstrain.array().ravel(order='A'))
        self.assertEqual(error, 0)

    def test_solve(self):
        verbose_test = False
        if verbose_test:
            print("start test_solve")
        grad = np.array([[1.1,  .2],
                         [.3, 1.5]])
        gl_strain = -0.5*(grad.T.dot(grad) - np.eye(2))
        gl_strain = -0.5*(grad.T + grad - 2*np.eye(2))
        grad = -gl_strain
        if verbose_test:
            print("grad =\n{}\ngl_strain =\n{}".format(grad, gl_strain))
        for pixel_id in self.cell1.pixel_indices:
            self.mat1.add_pixel(pixel_id)
            self.mat2.add_pixel(pixel_id, gl_strain)
        self.cell1.initialise()
        self.cell2.initialise()
        tol = 1e-6
        Del0_1 = grad
        Del0_2 = np.zeros_like(grad)
        maxiter = 2
        verbose = µ.Verbosity.Silent


        def solve(cell, grad):
            solver = µ.solvers.KrylovSolverCG(
                cell, tol, maxiter, verbose)
            r = µ.solvers.newton_cg(cell, grad,
                                    solver, tol, tol, verbose)
            return r
        results = [solve(cell, del0) for (cell, del0)
                   in zip((self.cell1, self.cell2),
                          (Del0_1, Del0_2))]
        P1 = results[0].stress
        P2 = results[1].stress
        error = np.linalg.norm(P1-P2)/np.linalg.norm(.5*(P1+P2))

        if verbose_test:
            print("cell 1, no eigenstrain")
            print("P1:\n{}".format(P1[:, 0]))
            print("F1:\n{}".format(results[0].grad[:, 0]))

            print("cell 2, with eigenstrain")
            print("P2:\n{}".format(P2[:, 0]))
            print("F2:\n{}".format(results[1].grad[:, 0]))
            print("end test_solve")
        self.assertLess(error, tol)


if __name__ == "__main__":
    unittest.main()
