import time
import shutil
import os
from datetime import datetime

import pytest
import numpy as np
import h5py

import damask
from damask import Result
from damask import mechanics

@pytest.fixture
def default(tmp_path,reference_dir):
    """Small Result file in temp location for modification."""
    fname = '12grains6x7x8_tensionY.hdf5'
    shutil.copy(os.path.join(reference_dir,fname),tmp_path)
    f = Result(os.path.join(tmp_path,fname))
    f.pick('times',20.0)
    return f

@pytest.fixture
def single_phase(tmp_path,reference_dir):
    """Single phase Result file in temp location for modification."""
    fname = '6grains6x7x8_single_phase_tensionY.hdf5'
    shutil.copy(os.path.join(reference_dir,fname),tmp_path)
    return Result(os.path.join(tmp_path,fname))

@pytest.fixture
def reference_dir(reference_dir_base):
    """Directory containing reference results."""
    return os.path.join(reference_dir_base,'Result')


class TestResult:

    def test_self_report(self,default):
        print(default)


    def test_pick_all(self,default):
        default.pick('increments',True)
        a = default.get_dataset_location('F')
        default.pick('increments','*')
        b = default.get_dataset_location('F')
        default.pick('increments',default.incs_in_range(0,np.iinfo(int).max))
        c = default.get_dataset_location('F')

        default.pick('times',True)
        d = default.get_dataset_location('F')
        default.pick('times','*')
        e = default.get_dataset_location('F')
        default.pick('times',default.times_in_range(0.0,np.inf))
        f = default.get_dataset_location('F')
        assert a == b == c == d == e ==f

    @pytest.mark.parametrize('what',['increments','times','constituents'])                          # ToDo: discuss materialpoints
    def test_pick_none(self,default,what):
        default.pick(what,False)
        a = default.get_dataset_location('F')
        default.pick(what,[])
        b = default.get_dataset_location('F')

        assert a == b == []

    @pytest.mark.parametrize('what',['increments','times','constituents'])                          # ToDo: discuss materialpoints
    def test_pick_more(self,default,what):
        default.pick(what,False)
        default.pick_more(what,'*')
        a = default.get_dataset_location('F')

        default.pick(what,True)
        b = default.get_dataset_location('F')

        assert a == b

    @pytest.mark.parametrize('what',['increments','times','constituents'])                          # ToDo: discuss materialpoints
    def test_pick_less(self,default,what):
        default.pick(what,True)
        default.pick_less(what,'*')
        a = default.get_dataset_location('F')

        default.pick(what,False)
        b = default.get_dataset_location('F')

        assert a == b == []

    def test_pick_invalid(self,default):
        with pytest.raises(AttributeError):
            default.pick('invalid',True)

    def test_add_absolute(self,default):
        default.add_absolute('Fe')
        loc = {'Fe':   default.get_dataset_location('Fe'),
               '|Fe|': default.get_dataset_location('|Fe|')}
        in_memory = np.abs(default.read_dataset(loc['Fe'],0))
        in_file   = default.read_dataset(loc['|Fe|'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_calculation(self,default):
        default.add_calculation('x','2.0*np.abs(#F#)-1.0','-','my notes')
        loc = {'F':    default.get_dataset_location('F'),
               'x':    default.get_dataset_location('x')}
        in_memory = 2.0*np.abs(default.read_dataset(loc['F'],0))-1.0
        in_file   = default.read_dataset(loc['x'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_Cauchy(self,default):
        default.add_Cauchy('P','F')
        loc = {'F':    default.get_dataset_location('F'),
               'P':    default.get_dataset_location('P'),
               'sigma':default.get_dataset_location('sigma')}
        in_memory = mechanics.Cauchy(default.read_dataset(loc['P'],0),
                                     default.read_dataset(loc['F'],0))
        in_file   = default.read_dataset(loc['sigma'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_determinant(self,default):
        default.add_determinant('P')
        loc = {'P':     default.get_dataset_location('P'),
               'det(P)':default.get_dataset_location('det(P)')}
        in_memory = np.linalg.det(default.read_dataset(loc['P'],0)).reshape(-1,1)
        in_file   = default.read_dataset(loc['det(P)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_deviator(self,default):
        default.add_deviator('P')
        loc = {'P'  :default.get_dataset_location('P'),
               's_P':default.get_dataset_location('s_P')}
        in_memory = mechanics.deviatoric_part(default.read_dataset(loc['P'],0))
        in_file   = default.read_dataset(loc['s_P'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_eigenvalues(self,default):
        default.add_Cauchy('P','F')
        default.add_eigenvalues('sigma')
        loc = {'sigma'        :default.get_dataset_location('sigma'),
               'lambda(sigma)':default.get_dataset_location('lambda(sigma)')}
        in_memory = mechanics.eigenvalues(default.read_dataset(loc['sigma'],0))
        in_file   = default.read_dataset(loc['lambda(sigma)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_eigenvectors(self,default):
        default.add_Cauchy('P','F')
        default.add_eigenvectors('sigma')
        loc = {'sigma'   :default.get_dataset_location('sigma'),
               'v(sigma)':default.get_dataset_location('v(sigma)')}
        in_memory = mechanics.eigenvectors(default.read_dataset(loc['sigma'],0))
        in_file   = default.read_dataset(loc['v(sigma)'],0)
        assert np.allclose(in_memory,in_file)

    @pytest.mark.parametrize('d',[[1,0,0],[0,1,0],[0,0,1]])
    def test_add_IPFcolor(self,default,d):
        default.add_IPFcolor('orientation',d)
        loc = {'orientation': default.get_dataset_location('orientation'),
               'color':       default.get_dataset_location('IPFcolor_[{} {} {}]'.format(*d))}
        qu = default.read_dataset(loc['orientation']).view(np.double).reshape(-1,4)
        crystal_structure = default.get_crystal_structure()
        in_memory = np.empty((qu.shape[0],3),np.uint8)
        for i,q in enumerate(qu):
            o = damask.Orientation(q,crystal_structure).reduced()
            in_memory[i] = np.uint8(o.IPFcolor(np.array(d))*255)
        in_file = default.read_dataset(loc['color'])
        assert np.allclose(in_memory,in_file)

    def test_add_maximum_shear(self,default):
        default.add_Cauchy('P','F')
        default.add_maximum_shear('sigma')
        loc = {'sigma'           :default.get_dataset_location('sigma'),
               'max_shear(sigma)':default.get_dataset_location('max_shear(sigma)')}
        in_memory = mechanics.maximum_shear(default.read_dataset(loc['sigma'],0)).reshape(-1,1)
        in_file   = default.read_dataset(loc['max_shear(sigma)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_Mises_strain(self,default):
        t = ['V','U'][np.random.randint(0,2)]
        m = np.random.random()*2.0 - 1.0
        default.add_strain_tensor('F',t,m)
        label = 'epsilon_{}^{}(F)'.format(t,m)
        default.add_Mises(label)
        loc = {label      :default.get_dataset_location(label),
               label+'_vM':default.get_dataset_location(label+'_vM')}
        in_memory = mechanics.Mises_strain(default.read_dataset(loc[label],0)).reshape(-1,1)
        in_file   = default.read_dataset(loc[label+'_vM'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_Mises_stress(self,default):
        default.add_Cauchy('P','F')
        default.add_Mises('sigma')
        loc = {'sigma'   :default.get_dataset_location('sigma'),
               'sigma_vM':default.get_dataset_location('sigma_vM')}
        in_memory = mechanics.Mises_stress(default.read_dataset(loc['sigma'],0)).reshape(-1,1)
        in_file   = default.read_dataset(loc['sigma_vM'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_norm(self,default):
        default.add_norm('F',1)
        loc = {'F':    default.get_dataset_location('F'),
               '|F|_1':default.get_dataset_location('|F|_1')}
        in_memory = np.linalg.norm(default.read_dataset(loc['F'],0),ord=1,axis=(1,2),keepdims=True)
        in_file   = default.read_dataset(loc['|F|_1'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_PK2(self,default):
        default.add_PK2('P','F')
        loc = {'F':default.get_dataset_location('F'),
               'P':default.get_dataset_location('P'),
               'S':default.get_dataset_location('S')}
        in_memory = mechanics.PK2(default.read_dataset(loc['P'],0),
                                  default.read_dataset(loc['F'],0))
        in_file   = default.read_dataset(loc['S'],0)
        assert np.allclose(in_memory,in_file)

    @pytest.mark.parametrize('polar',[True,False])
    def test_add_pole(self,default,polar):
        pole = np.array([1.,0.,0.])
        default.add_pole('orientation',pole,polar)
        loc = {'orientation': default.get_dataset_location('orientation'),
               'pole':        default.get_dataset_location('p^{}_[1 0 0)'.format(u'rφ' if polar else 'xy'))}
        rot = damask.Rotation(default.read_dataset(loc['orientation']).view(np.double))
        rotated_pole = rot * np.broadcast_to(pole,rot.shape+(3,))
        xy = rotated_pole[:,0:2]/(1.+abs(pole[2]))
        in_memory = xy if not polar else \
                    np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
        in_file = default.read_dataset(loc['pole'])
        assert np.allclose(in_memory,in_file)

    def test_add_rotational_part(self,default):
        default.add_rotational_part('F')
        loc = {'F':    default.get_dataset_location('F'),
               'R(F)': default.get_dataset_location('R(F)')}
        in_memory = mechanics.rotational_part(default.read_dataset(loc['F'],0))
        in_file   = default.read_dataset(loc['R(F)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_spherical(self,default):
        default.add_spherical('P')
        loc = {'P':   default.get_dataset_location('P'),
               'p_P': default.get_dataset_location('p_P')}
        in_memory = mechanics.spherical_part(default.read_dataset(loc['P'],0)).reshape(-1,1)
        in_file   = default.read_dataset(loc['p_P'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_strain(self,default):
        t = ['V','U'][np.random.randint(0,2)]
        m = np.random.random()*2.0 - 1.0
        default.add_strain_tensor('F',t,m)
        label = 'epsilon_{}^{}(F)'.format(t,m)
        loc = {'F':   default.get_dataset_location('F'),
               label: default.get_dataset_location(label)}
        in_memory = mechanics.strain_tensor(default.read_dataset(loc['F'],0),t,m)
        in_file   = default.read_dataset(loc[label],0)
        assert np.allclose(in_memory,in_file)

    def test_add_stretch_right(self,default):
        default.add_stretch_tensor('F','U')
        loc = {'F':    default.get_dataset_location('F'),
               'U(F)': default.get_dataset_location('U(F)')}
        in_memory = mechanics.right_stretch(default.read_dataset(loc['F'],0))
        in_file   = default.read_dataset(loc['U(F)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_stretch_left(self,default):
        default.add_stretch_tensor('F','V')
        loc = {'F':    default.get_dataset_location('F'),
               'V(F)': default.get_dataset_location('V(F)')}
        in_memory = mechanics.left_stretch(default.read_dataset(loc['F'],0))
        in_file   = default.read_dataset(loc['V(F)'],0)
        assert np.allclose(in_memory,in_file)

    def test_add_invalid(self,default):
        with pytest.raises(TypeError):
            default.add_calculation('#invalid#*2')

    @pytest.mark.parametrize('overwrite',['off','on'])
    def test_add_overwrite(self,default,overwrite):
        default.pick('times',default.times_in_range(0,np.inf)[-1])

        default.add_Cauchy()
        loc = default.get_dataset_location('sigma')
        print(loc)
        with h5py.File(default.fname,'r') as f:
            created_first = f[loc[0]].attrs['Created'].decode()
        created_first = datetime.strptime(created_first,'%Y-%m-%d %H:%M:%S%z')

        if overwrite == 'on':
            default.enable_overwrite()
        else:
            default.disable_overwrite()

        time.sleep(2.)
        default.add_calculation('sigma','#sigma#*0.0+311.','not the Cauchy stress')
        with h5py.File(default.fname,'r') as f:
            created_second = f[loc[0]].attrs['Created'].decode()
        created_second = datetime.strptime(created_second,'%Y-%m-%d %H:%M:%S%z')
        if overwrite == 'on':
            assert created_first < created_second and np.allclose(default.read_dataset(loc),311.)
        else:
            assert created_first == created_second and not np.allclose(default.read_dataset(loc),311.)

    @pytest.mark.parametrize('output',['F',[],['F','P']])
    def test_vtk(self,tmp_path,default,output):
        os.chdir(tmp_path)
        default.to_vtk(output)

    def test_XDMF(self,tmp_path,single_phase):
        os.chdir(tmp_path)
        single_phase.write_XDMF