import pytest

from diofant import Matrix, eye
from diofant.combinatorics import Permutation
from diofant.core import S, Rational, Symbol, Basic, Integer
from diofant.core.containers import Tuple
from diofant.core.symbol import symbols
from diofant.external import import_module
from diofant.functions.elementary.miscellaneous import sqrt
from diofant.printing.pretty.pretty import pretty
from diofant.tensor.tensor import (TensorIndexType, tensor_indices, TensorSymmetry,
                                   get_symmetric_group_sgs, TensorType, TensorIndex,
                                   tensor_mul, TensAdd, riemann_cyclic_replace,
                                   riemann_cyclic, TensMul, tensorsymmetry,
                                   tensorhead, TensorManager, TensExpr, TIDS)

numpy = import_module("numpy")


def _is_equal(arg1, arg2):
    if isinstance(arg1, TensExpr):
        return arg1.equals(arg2)
    elif isinstance(arg2, TensExpr):
        return arg2.equals(arg1)
    return arg1 == arg2


# ################### Tests from tensor_can.py ##################### #
def test_canonicalize_no_slot_sym():
    # A_d0 * B^d0; T_c = A^d0*B_d0
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, d0, d1 = tensor_indices('a,b,d0,d1', Lorentz)
    sym1 = tensorsymmetry([1])
    S1 = TensorType([Lorentz], sym1)
    A, B = S1('A,B')
    t = A(-d0)*B(d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0)*B(-L_0)'

    # A^a * B^b;  T_c = T
    t = A(a)*B(b)
    tc = t.canon_bp()
    assert tc == t
    # B^b * A^a
    t1 = B(b)*A(a)
    tc = t1.canon_bp()
    assert str(tc) == 'A(a)*B(b)'

    # A symmetric
    # A^{b}_{d0}*A^{d0, a}; T_c = A^{a d0}*A{b}_{d0}
    sym2 = tensorsymmetry([1]*2)
    S2 = TensorType([Lorentz]*2, sym2)
    A = S2('A')
    t = A(b, -d0)*A(d0, a)
    tc = t.canon_bp()
    assert str(tc) == 'A(a, L_0)*A(b, -L_0)'

    # A^{d1}_{d0}*B^d0*C_d1
    # T_c = A^{d0 d1}*B_d0*C_d1
    B, C = S1('B,C')
    t = A(d1, -d0)*B(d0)*C(-d1)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-L_0)*C(-L_1)'

    # A without symmetry
    # A^{d1}_{d0}*B^d0*C_d1 ord=[d0,-d0,d1,-d1]; g = [2,1,0,3,4,5]
    # T_c = A^{d0 d1}*B_d1*C_d0; can = [0,2,3,1,4,5]
    nsym2 = tensorsymmetry([1], [1])
    NS2 = TensorType([Lorentz]*2, nsym2)
    A = NS2('A')
    B, C = S1('B, C')
    t = A(d1, -d0)*B(d0)*C(-d1)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-L_1)*C(-L_0)'

    # A, B without symmetry
    # A^{d1}_{d0}*B_{d1}^{d0}
    # T_c = A^{d0 d1}*B_{d0 d1}
    B = NS2('B')
    t = A(d1, -d0)*B(-d1, d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-L_0, -L_1)'
    # A_{d0}^{d1}*B_{d1}^{d0}
    # T_c = A^{d0 d1}*B_{d1 d0}
    t = A(-d0, d1)*B(-d1, d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-L_1, -L_0)'

    # A, B, C without symmetry
    # A^{d1 d0}*B_{a d0}*C_{d1 b}
    # T_c=A^{d0 d1}*B_{a d1}*C_{d0 b}
    C = NS2('C')
    t = A(d1, d0)*B(-a, -d0)*C(-d1, -b)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-a, -L_1)*C(-L_0, -b)'

    # A symmetric, B and C without symmetry
    # A^{d1 d0}*B_{a d0}*C_{d1 b}
    # T_c = A^{d0 d1}*B_{a d0}*C_{d1 b}
    A = S2('A')
    t = A(d1, d0)*B(-a, -d0)*C(-d1, -b)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-a, -L_0)*C(-L_1, -b)'

    # A and C symmetric, B without symmetry
    # A^{d1 d0}*B_{a d0}*C_{d1 b} ord=[a,b,d0,-d0,d1,-d1]
    # T_c = A^{d0 d1}*B_{a d0}*C_{b d1}
    C = S2('C')
    t = A(d1, d0)*B(-a, -d0)*C(-d1, -b)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1)*B(-a, -L_0)*C(-b, -L_1)'


def test_canonicalize_no_dummies():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, c, d = tensor_indices('a, b, c, d', Lorentz)
    sym1 = tensorsymmetry([1])
    sym2 = tensorsymmetry([1]*2)
    sym2a = tensorsymmetry([2])

    # A commuting
    # A^c A^b A^a
    # T_c = A^a A^b A^c
    S1 = TensorType([Lorentz], sym1)
    A = S1('A')
    t = A(c)*A(b)*A(a)
    tc = t.canon_bp()
    assert str(tc) == 'A(a)*A(b)*A(c)'

    # A anticommuting
    # A^c A^b A^a
    # T_c = -A^a A^b A^c
    A = S1('A', 1)
    t = A(c)*A(b)*A(a)
    tc = t.canon_bp()
    assert str(tc) == '-A(a)*A(b)*A(c)'

    # A commuting and symmetric
    # A^{b,d}*A^{c,a}
    # T_c = A^{a c}*A^{b d}
    S2 = TensorType([Lorentz]*2, sym2)
    A = S2('A')
    t = A(b, d)*A(c, a)
    tc = t.canon_bp()
    assert str(tc) == 'A(a, c)*A(b, d)'

    # A anticommuting and symmetric
    # A^{b,d}*A^{c,a}
    # T_c = -A^{a c}*A^{b d}
    A = S2('A', 1)
    t = A(b, d)*A(c, a)
    tc = t.canon_bp()
    assert str(tc) == '-A(a, c)*A(b, d)'

    # A^{c,a}*A^{b,d}
    # T_c = A^{a c}*A^{b d}
    t = A(c, a)*A(b, d)
    tc = t.canon_bp()
    assert str(tc) == 'A(a, c)*A(b, d)'


def test_no_metric_symmetry():
    # no metric symmetry; A no symmetry
    # A^d1_d0 * A^d0_d1
    # T_c = A^d0_d1 * A^d1_d0
    Lorentz = TensorIndexType('Lorentz', metric=None, dummy_fmt='L')
    d0, d1, d2, d3 = tensor_indices('d:4', Lorentz)
    A = tensorhead('A', [Lorentz]*2, [[1], [1]])
    t = A(d1, -d0)*A(d0, -d1)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, -L_1)*A(L_1, -L_0)'

    # A^d1_d2 * A^d0_d3 * A^d2_d1 * A^d3_d0
    # T_c = A^d0_d1 * A^d1_d0 * A^d2_d3 * A^d3_d2
    t = A(d1, -d2)*A(d0, -d3)*A(d2, -d1)*A(d3, -d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, -L_1)*A(L_1, -L_0)*A(L_2, -L_3)*A(L_3, -L_2)'

    # A^d0_d2 * A^d1_d3 * A^d3_d0 * A^d2_d1
    # T_c = A^d0_d1 * A^d1_d2 * A^d2_d3 * A^d3_d0
    t = A(d0, -d1)*A(d1, -d2)*A(d2, -d3)*A(d3, -d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, -L_1)*A(L_1, -L_2)*A(L_2, -L_3)*A(L_3, -L_0)'


def test_canonicalize1():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, a0, a1, a2, a3, b, d0, d1, d2, d3 = \
      tensor_indices('a,a0,a1,a2,a3,b,d0,d1,d2,d3', Lorentz)
    sym1 = tensorsymmetry([1])
    base3, gens3 = get_symmetric_group_sgs(3)
    sym2 = tensorsymmetry([1]*2)
    sym2a = tensorsymmetry([2])
    sym3 = tensorsymmetry([1]*3)
    sym3a = tensorsymmetry([3])

    # A_d0*A^d0; ord = [d0,-d0]
    # T_c = A^d0*A_d0
    S1 = TensorType([Lorentz], sym1)
    A = S1('A')
    t = A(-d0)*A(d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0)*A(-L_0)'

    # A commuting
    # A_d0*A_d1*A_d2*A^d2*A^d1*A^d0
    # T_c = A^d0*A_d0*A^d1*A_d1*A^d2*A_d2
    t = A(-d0)*A(-d1)*A(-d2)*A(d2)*A(d1)*A(d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0)*A(-L_0)*A(L_1)*A(-L_1)*A(L_2)*A(-L_2)'

    # A anticommuting
    # A_d0*A_d1*A_d2*A^d2*A^d1*A^d0
    # T_c 0
    A = S1('A', 1)
    t = A(-d0)*A(-d1)*A(-d2)*A(d2)*A(d1)*A(d0)
    tc = t.canon_bp()
    assert tc == 0

    # A commuting symmetric
    # A^{d0 b}*A^a_d1*A^d1_d0
    # T_c = A^{a d0}*A^{b d1}*A_{d0 d1}
    S2 = TensorType([Lorentz]*2, sym2)
    A = S2('A')
    t = A(d0, b)*A(a, -d1)*A(d1, -d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(a, L_0)*A(b, L_1)*A(-L_0, -L_1)'

    # A, B commuting symmetric
    # A^{d0 b}*A^d1_d0*B^a_d1
    # T_c = A^{b d0}*A_d0^d1*B^a_d1
    B = S2('B')
    t = A(d0, b)*A(d1, -d0)*B(a, -d1)
    tc = t.canon_bp()
    assert str(tc) == 'A(b, L_0)*A(-L_0, L_1)*B(a, -L_1)'

    # A commuting symmetric
    # A^{d1 d0 b}*A^{a}_{d1 d0}; ord=[a,b, d0,-d0,d1,-d1]
    # T_c = A^{a d0 d1}*A^{b}_{d0 d1}
    S3 = TensorType([Lorentz]*3, sym3)
    A = S3('A')
    t = A(d1, d0, b)*A(a, -d1, -d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(a, L_0, L_1)*A(b, -L_0, -L_1)'

    # A^{d3 d0 d2}*A^a0_{d1 d2}*A^d1_d3^a1*A^{a2 a3}_d0
    # T_c = A^{a0 d0 d1}*A^a1_d0^d2*A^{a2 a3 d3}*A_{d1 d2 d3}
    t = A(d3, d0, d2)*A(a0, -d1, -d2)*A(d1, -d3, a1)*A(a2, a3, -d0)
    tc = t.canon_bp()
    assert str(tc) == 'A(a0, L_0, L_1)*A(a1, -L_0, L_2)*A(a2, a3, L_3)*A(-L_1, -L_2, -L_3)'

    # A commuting symmetric, B antisymmetric
    # A^{d0 d1 d2} * A_{d2 d3 d1} * B_d0^d3
    # in this esxample and in the next three,
    # renaming dummy indices and using symmetry of A,
    # T = A^{d0 d1 d2} * A_{d0 d1 d3} * B_d2^d3
    # can = 0
    S2a = TensorType([Lorentz]*2, sym2a)
    A = S3('A')
    B = S2a('B')
    t = A(d0, d1, d2)*A(-d2, -d3, -d1)*B(-d0, d3)
    tc = t.canon_bp()
    assert tc == 0

    # A anticommuting symmetric, B anticommuting
    # A^{d0 d1 d2} * A_{d2 d3 d1} * B_d0^d3
    # T_c = A^{d0 d1 d2} * A_{d0 d1}^d3 * B_{d2 d3}
    A = S3('A', 1)
    B = S2a('B')
    t = A(d0, d1, d2)*A(-d2, -d3, -d1)*B(-d0, d3)
    tc = t.canon_bp()
    assert str(tc) == 'A(L_0, L_1, L_2)*A(-L_0, -L_1, L_3)*B(-L_2, -L_3)'

    # A anticommuting symmetric, B antisymmetric commuting, antisymmetric metric
    # A^{d0 d1 d2} * A_{d2 d3 d1} * B_d0^d3
    # T_c = -A^{d0 d1 d2} * A_{d0 d1}^d3 * B_{d2 d3}
    Spinor = TensorIndexType('Spinor', metric=1, dummy_fmt='S')
    a, a0, a1, a2, a3, b, d0, d1, d2, d3 = \
      tensor_indices('a,a0,a1,a2,a3,b,d0,d1,d2,d3', Spinor)
    S3 = TensorType([Spinor]*3, sym3)
    S2a = TensorType([Spinor]*2, sym2a)
    A = S3('A', 1)
    B = S2a('B')
    t = A(d0, d1, d2)*A(-d2, -d3, -d1)*B(-d0, d3)
    tc = t.canon_bp()
    assert str(tc) == '-A(S_0, S_1, S_2)*A(-S_0, -S_1, S_3)*B(-S_2, -S_3)'

    # A anticommuting symmetric, B antisymmetric anticommuting,
    # no metric symmetry
    # A^{d0 d1 d2} * A_{d2 d3 d1} * B_d0^d3
    # T_c = A^{d0 d1 d2} * A_{d0 d1 d3} * B_d2^d3
    Mat = TensorIndexType('Mat', metric=None, dummy_fmt='M')
    a, a0, a1, a2, a3, b, d0, d1, d2, d3 = \
      tensor_indices('a,a0,a1,a2,a3,b,d0,d1,d2,d3', Mat)
    S3 = TensorType([Mat]*3, sym3)
    S2a = TensorType([Mat]*2, sym2a)
    A = S3('A', 1)
    B = S2a('B')
    t = A(d0, d1, d2)*A(-d2, -d3, -d1)*B(-d0, d3)
    tc = t.canon_bp()
    assert str(tc) == 'A(M_0, M_1, M_2)*A(-M_0, -M_1, -M_3)*B(-M_2, M_3)'

    # Gamma anticommuting
    # Gamma_{mu nu} * gamma^rho * Gamma^{nu mu alpha}
    # T_c = -Gamma^{mu nu} * gamma^rho * Gamma_{alpha mu nu}
    S1 = TensorType([Lorentz], sym1)
    S2a = TensorType([Lorentz]*2, sym2a)
    S3a = TensorType([Lorentz]*3, sym3a)
    alpha, beta, gamma, mu, nu, rho = \
      tensor_indices('alpha,beta,gamma,mu,nu,rho', Lorentz)
    Gamma = S1('Gamma', 2)
    Gamma2 = S2a('Gamma', 2)
    Gamma3 = S3a('Gamma', 2)
    t = Gamma2(-mu, -nu)*Gamma(rho)*Gamma3(nu, mu, alpha)
    tc = t.canon_bp()
    assert str(tc) == '-Gamma(L_0, L_1)*Gamma(rho)*Gamma(alpha, -L_0, -L_1)'

    # Gamma_{mu nu} * Gamma^{gamma beta} * gamma_rho * Gamma^{nu mu alpha}
    # T_c = Gamma^{mu nu} * Gamma^{beta gamma} * gamma_rho * Gamma^alpha_{mu nu}
    t = Gamma2(mu, nu)*Gamma2(beta, gamma)*Gamma(-rho)*Gamma3(alpha, -mu, -nu)
    tc = t.canon_bp()
    assert str(tc) == 'Gamma(L_0, L_1)*Gamma(beta, gamma)*Gamma(-rho)*Gamma(alpha, -L_0, -L_1)'

    # f^a_{b,c} antisymmetric in b,c; A_mu^a no symmetry
    # f^c_{d a} * f_{c e b} * A_mu^d * A_nu^a * A^{nu e} * A^{mu b}
    # g = [8,11,5, 9,13,7, 1,10, 3,4, 2,12, 0,6, 14,15]
    # T_c = -f^{a b c} * f_a^{d e} * A^mu_b * A_{mu d} * A^nu_c * A_{nu e}
    Flavor = TensorIndexType('Flavor', dummy_fmt='F')
    a, b, c, d, e, ff = tensor_indices('a,b,c,d,e,f', Flavor)
    mu, nu = tensor_indices('mu,nu', Lorentz)
    sym_f = tensorsymmetry([1], [2])
    S_f = TensorType([Flavor]*3, sym_f)
    sym_A = tensorsymmetry([1], [1])
    S_A = TensorType([Lorentz, Flavor], sym_A)
    f = S_f('f')
    A = S_A('A')
    t = f(c, -d, -a)*f(-c, -e, -b)*A(-mu, d)*A(-nu, a)*A(nu, e)*A(mu, b)
    tc = t.canon_bp()
    assert str(tc) == '-f(F_0, F_1, F_2)*f(-F_0, F_3, F_4)*A(L_0, -F_1)*A(-L_0, -F_3)*A(L_1, -F_2)*A(-L_1, -F_4)'


def test_bug_correction_tensor_indices():
    # to make sure that tensor_indices does not return a list if creating
    # only one index:
    from diofant.tensor.tensor import tensor_indices, TensorIndexType, TensorIndex
    A = TensorIndexType("A")
    i = tensor_indices('i', A)
    assert not isinstance(i, (tuple, list))
    assert isinstance(i, TensorIndex)


def test_riemann_invariants():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    d0, d1, d2, d3, d4, d5, d6, d7, d8, d9, d10, d11 = \
            tensor_indices('d0:12', Lorentz)
    # R^{d0 d1}_{d1 d0}; ord = [d0,-d0,d1,-d1]
    # T_c = -R^{d0 d1}_{d0 d1}
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    t = R(d0, d1, -d1, -d0)
    tc = t.canon_bp()
    assert str(tc) == '-R(L_0, L_1, -L_0, -L_1)'

    # R_d11^d1_d0^d5 * R^{d6 d4 d0}_d5 * R_{d7 d2 d8 d9} *
    # R_{d10 d3 d6 d4} * R^{d2 d7 d11}_d1 * R^{d8 d9 d3 d10}
    # can = [0,2,4,6, 1,3,8,10, 5,7,12,14, 9,11,16,18, 13,15,20,22,
    #        17,19,21<F10,23, 24,25]
    # T_c = R^{d0 d1 d2 d3} * R_{d0 d1}^{d4 d5} * R_{d2 d3}^{d6 d7} *
    # R_{d4 d5}^{d8 d9} * R_{d6 d7}^{d10 d11} * R_{d8 d9 d10 d11}

    t = R(-d11, d1, -d0, d5)*R(d6, d4, d0, -d5)*R(-d7, -d2, -d8, -d9) * \
        R(-d10, -d3, -d6, -d4)*R(d2, d7, d11, -d1)*R(d8, d9, d3, d10)
    tc = t.canon_bp()
    assert str(tc) == 'R(L_0, L_1, L_2, L_3)*R(-L_0, -L_1, L_4, L_5)*R(-L_2, -L_3, L_6, L_7)*R(-L_4, -L_5, L_8, L_9)*R(-L_6, -L_7, L_10, L_11)*R(-L_8, -L_9, -L_10, -L_11)'


def test_riemann_products():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    d0, d1, d2, d3, d4, d5, d6 = tensor_indices('d0:7', Lorentz)
    a0, a1, a2, a3, a4, a5 = tensor_indices('a0:6', Lorentz)
    a, b = tensor_indices('a,b', Lorentz)
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    # R^{a b d0}_d0 = 0
    t = R(a, b, d0, -d0)
    tc = t.canon_bp()
    assert tc == 0

    # R^{d0 b a}_d0
    # T_c = -R^{a d0 b}_d0
    t = R(d0, b, a, -d0)
    tc = t.canon_bp()
    assert str(tc) == '-R(a, L_0, b, -L_0)'

    # R^d1_d2^b_d0 * R^{d0 a}_d1^d2; ord=[a,b,d0,-d0,d1,-d1,d2,-d2]
    # T_c = -R^{a d0 d1 d2}* R^b_{d0 d1 d2}
    t = R(d1, -d2, b, -d0)*R(d0, a, -d1, d2)
    tc = t.canon_bp()
    assert str(tc) == '-R(a, L_0, L_1, L_2)*R(b, -L_0, -L_1, -L_2)'

    # A symmetric commuting
    # R^{d6 d5}_d2^d1 * R^{d4 d0 d2 d3} * A_{d6 d0} A_{d3 d1} * A_{d4 d5}
    # g = [12,10,5,2, 8,0,4,6, 13,1, 7,3, 9,11,14,15]
    # T_c = -R^{d0 d1 d2 d3} * R_d0^{d4 d5 d6} * A_{d1 d4}*A_{d2 d5}*A_{d3 d6}
    V = tensorhead('V', [Lorentz]*2, [[1]*2])
    t = R(d6, d5, -d2, d1)*R(d4, d0, d2, d3)*V(-d6, -d0)*V(-d3, -d1)*V(-d4, -d5)
    tc = t.canon_bp()
    assert str(tc) == '-R(L_0, L_1, L_2, L_3)*R(-L_0, L_4, L_5, L_6)*V(-L_1, -L_4)*V(-L_2, -L_5)*V(-L_3, -L_6)'

    # R^{d2 a0 a2 d0} * R^d1_d2^{a1 a3} * R^{a4 a5}_{d0 d1}
    # T_c = R^{a0 d0 a2 d1}*R^{a1 a3}_d0^d2*R^{a4 a5}_{d1 d2}
    t = R(d2, a0, a2, d0)*R(d1, -d2, a1, a3)*R(a4, a5, -d0, -d1)
    tc = t.canon_bp()
    assert str(tc) == 'R(a0, L_0, a2, L_1)*R(a1, a3, -L_0, L_2)*R(a4, a5, -L_1, -L_2)'
######################################################################


def test_canonicalize2():
    D = Symbol('D')
    Eucl = TensorIndexType('Eucl', metric=0, dim=D, dummy_fmt='E')
    i0, i1, i2, i3, i4, i5, i6, i7, i8, i9, i10, i11, i12, i13, i14 = \
            tensor_indices('i0:15', Eucl)
    A = tensorhead('A', [Eucl]*3, [[3]])

    # two examples from Cvitanovic, Group Theory page 59
    # of identities for antisymmetric tensors of rank 3
    # contracted according to the Kuratowski graph  eq.(6.59)
    t = A(i0, i1, i2)*A(-i1, i3, i4)*A(-i3, i7, i5)*A(-i2, -i5, i6)*A(-i4, -i6, i8)
    t1 = t.canon_bp()
    assert t1 == 0

    # eq.(6.60)
    # t = A(i0,i1,i2)*A(-i1,i3,i4)*A(-i2,i5,i6)*A(-i3,i7,i8)*A(-i6,-i7,i9)*
    #    A(-i8,i10,i13)*A(-i5,-i10,i11)*A(-i4,-i11,i12)*A(-i3,-i12,i14)
    t = A(i0, i1, i2)*A(-i1, i3, i4)*A(-i2, i5, i6)*A(-i3, i7, i8)*A(-i6, -i7, i9) *\
        A(-i8, i10, i13)*A(-i5, -i10, i11)*A(-i4, -i11, i12)*A(-i9, -i12, i14)
    t1 = t.canon_bp()
    assert t1 == 0


def test_canonicalize3():
    D = Symbol('D')
    Spinor = TensorIndexType('Spinor', dim=D, metric=True, dummy_fmt='S')
    a0, a1, a2, a3, a4 = tensor_indices('a0:5', Spinor)
    C = Spinor.metric
    chi, psi = tensorhead('chi,psi', [Spinor], [[1]], 1)

    t = chi(a1)*psi(a0)
    t1 = t.canon_bp()
    assert t1 == t

    t = psi(a1)*chi(a0)
    t1 = t.canon_bp()
    assert t1 == -chi(a0)*psi(a1)


class Metric(Basic):
    def __new__(cls, name, antisym, **kwargs):
        obj = Basic.__new__(cls, name, antisym, **kwargs)
        obj.name = name
        obj.antisym = antisym
        return obj


def test_TensorIndexType():
    D = Symbol('D')
    G = Metric('g', False)
    Lorentz = TensorIndexType('Lorentz', metric=G, dim=D, dummy_fmt='L')
    m0, m1, m2, m3, m4 = tensor_indices('m0:5', Lorentz)
    sym2 = tensorsymmetry([1]*2)
    sym2n = tensorsymmetry(*get_symmetric_group_sgs(2))
    assert sym2 == sym2n
    g = Lorentz.metric
    assert str(g) == 'g(Lorentz,Lorentz)'
    assert Lorentz.eps_dim == Lorentz.dim

    TSpace = TensorIndexType('TSpace')
    i0, i1 = tensor_indices('i0 i1', TSpace)
    g = TSpace.metric
    A = tensorhead('A', [TSpace]*2, [[1]*2])
    assert str(A(i0, -i0).canon_bp()) == 'A(TSpace_0, -TSpace_0)'


def test_indices():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, c, d = tensor_indices('a,b,c,d', Lorentz)
    assert a.tensortype == Lorentz
    assert a != -a
    A, B = tensorhead('A B', [Lorentz]*2, [[1]*2])
    t = A(a, b)*B(-b, c)
    indices = t.get_indices()
    L_0 = TensorIndex('L_0', Lorentz)
    assert indices == [a, L_0, -L_0, c]
    pytest.raises(ValueError, lambda: tensor_indices(3, Lorentz))
    pytest.raises(ValueError, lambda: A(a, b, c))


def test_tensorsymmetry():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    sym = tensorsymmetry([1]*2)
    sym1 = TensorSymmetry(get_symmetric_group_sgs(2))
    assert sym == sym1
    sym = tensorsymmetry([2])
    sym1 = TensorSymmetry(get_symmetric_group_sgs(2, 1))
    assert sym == sym1
    sym2 = tensorsymmetry()
    assert sym2.base == Tuple() and sym2.generators == Tuple(Permutation(1))
    pytest.raises(NotImplementedError, lambda: tensorsymmetry([2, 1]))


def test_TensorType():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    sym = tensorsymmetry([1]*2)
    A = tensorhead('A', [Lorentz]*2, [[1]*2])
    assert A.typ == TensorType([Lorentz]*2, sym)
    assert A.types == [Lorentz]
    typ = TensorType([Lorentz]*2, sym)
    assert str(typ) == "TensorType(['Lorentz', 'Lorentz'])"
    pytest.raises(ValueError, lambda: typ(2))


def test_TensExpr():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, c, d = tensor_indices('a,b,c,d', Lorentz)
    g = Lorentz.metric
    A, B = tensorhead('A B', [Lorentz]*2, [[1]*2])
    pytest.raises(ValueError, lambda: g(c, d)/g(a, b))
    pytest.raises(ValueError, lambda: S.One/g(a, b))
    pytest.raises(ValueError, lambda: (A(c, d) + g(c, d))/g(a, b))
    pytest.raises(ValueError, lambda: S.One/(A(c, d) + g(c, d)))
    pytest.raises(ValueError, lambda: A(a, b) + A(a, c))
    t = A(a, b) + B(a, b)
    pytest.raises(NotImplementedError, lambda: TensExpr.__mul__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__add__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__radd__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__sub__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__rsub__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__div__(t, 'a'))
    pytest.raises(NotImplementedError, lambda: TensExpr.__rdiv__(t, 'a'))
    pytest.raises(ValueError, lambda: A(a, b)**2)
    pytest.raises(NotImplementedError, lambda: 2**A(a, b))
    pytest.raises(NotImplementedError, lambda: abs(A(a, b)))


def test_TensorHead():
    assert TensAdd() == 0
    # simple example of algebraic expression
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b = tensor_indices('a,b', Lorentz)
    # A, B symmetric
    A = tensorhead('A', [Lorentz]*2, [[1]*2])
    assert A.rank == 2
    assert A.symmetry == tensorsymmetry([1]*2)


def test_add1():
    assert TensAdd() == 0
    # simple example of algebraic expression
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, d0, d1, i, j, k = tensor_indices('a,b,d0,d1,i,j,k', Lorentz)
    # A, B symmetric
    A, B = tensorhead('A,B', [Lorentz]*2, [[1]*2])
    t1 = A(b, -d0)*B(d0, a)
    assert TensAdd(t1).equals(t1)
    t2a = B(d0, a) + A(d0, a)
    t2 = A(b, -d0)*t2a
    assert str(t2) == 'A(a, L_0)*A(b, -L_0) + A(b, L_0)*B(a, -L_0)'
    t2b = t2 + t1
    assert str(t2b) == '2*A(b, L_0)*B(a, -L_0) + A(a, L_0)*A(b, -L_0)'
    p, q, r = tensorhead('p,q,r', [Lorentz], [[1]])
    t = q(d0)*2
    assert str(t) == '2*q(d0)'
    t = 2*q(d0)
    assert str(t) == '2*q(d0)'
    t1 = p(d0) + 2*q(d0)
    assert str(t1) == '2*q(d0) + p(d0)'
    t2 = p(-d0) + 2*q(-d0)
    assert str(t2) == '2*q(-d0) + p(-d0)'
    t1 = p(d0)
    t3 = t1*t2
    assert str(t3) == '2*p(L_0)*q(-L_0) + p(L_0)*p(-L_0)'
    t3 = t2*t1
    assert str(t3) == '2*p(L_0)*q(-L_0) + p(L_0)*p(-L_0)'
    t1 = p(d0) + 2*q(d0)
    t3 = t1*t2
    assert str(t3) == '4*p(L_0)*q(-L_0) + 4*q(L_0)*q(-L_0) + p(L_0)*p(-L_0)'
    t1 = p(d0) - 2*q(d0)
    assert str(t1) == '-2*q(d0) + p(d0)'
    t2 = p(-d0) + 2*q(-d0)
    t3 = t1*t2
    assert t3 == p(d0)*p(-d0) - 4*q(d0)*q(-d0)
    t = p(i)*p(j)*(p(k) + q(k)) + p(i)*(p(j) + q(j))*(p(k) - 3*q(k))
    assert t == 2*p(i)*p(j)*p(k) - 2*p(i)*p(j)*q(k) + p(i)*p(k)*q(j) - 3*p(i)*q(j)*q(k)
    t1 = (p(i) + q(i) + 2*r(i))*(p(j) - q(j))
    t2 = (p(j) + q(j) + 2*r(j))*(p(i) - q(i))
    t = t1 + t2
    assert t == 2*p(i)*p(j) + 2*p(i)*r(j) + 2*p(j)*r(i) - 2*q(i)*q(j) - 2*q(i)*r(j) - 2*q(j)*r(i)
    t = p(i)*q(j)/2
    assert 2*t == p(i)*q(j)
    t = (p(i) + q(i))/2
    assert 2*t == p(i) + q(i)

    t = S.One - p(i)*p(-i)
    assert (t + p(-j)*p(j)).equals(1)
    t = S.One + p(i)*p(-i)
    assert (t - p(-j)*p(j)).equals(1)

    t = A(a, b) + B(a, b)
    assert t.rank == 2
    t1 = t - A(a, b) - B(a, b)
    assert t1 == 0
    t = 1 - (A(a, -a) + B(a, -a))
    t1 = 1 + (A(a, -a) + B(a, -a))
    assert (t + t1).equals(2)
    t2 = 1 + A(a, -a)
    assert t1 != t2
    assert t2 != TensMul.from_data(0, [], [], [])
    t = p(i) + q(i)
    pytest.raises(ValueError, lambda: t(i, j))


def test_special_eq_ne():
    # test special equality cases:
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, d0, d1, i, j, k = tensor_indices('a,b,d0,d1,i,j,k', Lorentz)
    # A, B symmetric
    A, B = tensorhead('A,B', [Lorentz]*2, [[1]*2])
    p, q, r = tensorhead('p,q,r', [Lorentz], [[1]])

    t = 0*A(a, b)
    assert _is_equal(t, 0)
    assert _is_equal(t, S.Zero)

    assert p(i) != A(a, b)
    assert A(a, -a) != A(a, b)
    assert 0*(A(a, b) + B(a, b)) == 0
    assert 0*(A(a, b) + B(a, b)) == S.Zero

    assert 3*(A(a, b) - A(a, b)) == S.Zero

    assert p(i) + q(i) != A(a, b)
    assert p(i) + q(i) != A(a, b) + B(a, b)

    assert p(i) - p(i) == 0
    assert p(i) - p(i) == S.Zero

    assert _is_equal(A(a, b), A(b, a))


def test_add2():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    m, n, p, q = tensor_indices('m,n,p,q', Lorentz)
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    A = tensorhead('A', [Lorentz]*3, [[3]])
    t1 = 2*R(m, n, p, q) - R(m, q, n, p) + R(m, p, n, q)
    t2 = t1*A(-n, -p, -q)
    assert t2 == 0
    t1 = Rational(2, 3)*R(m, n, p, q) - Rational(1, 3)*R(m, q, n, p) + Rational(1, 3)*R(m, p, n, q)
    t2 = t1*A(-n, -p, -q)
    assert t2 == 0
    t = A(m, -m, n) + A(n, p, -p)
    assert t == 0


def test_mul():
    from diofant.abc import x
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b, c, d = tensor_indices('a,b,c,d', Lorentz)
    sym = tensorsymmetry([1]*2)
    t = TensMul.from_data(S.One, [], [], [])
    assert str(t) == '1'
    A, B = tensorhead('A B', [Lorentz]*2, [[1]*2])
    t = (1 + x)*A(a, b)
    assert str(t) == '(x + 1)*A(a, b)'
    assert t.types == [Lorentz]
    assert t.rank == 2
    assert t.dum == []
    assert t.coeff == 1 + x
    assert sorted(t.free) == [(a, 0, 0), (b, 1, 0)]
    assert t.components == [A]

    ts = A(a, b)
    assert str(ts) == 'A(a, b)'
    assert ts.types == [Lorentz]
    assert ts.rank == 2
    assert ts.dum == []
    assert ts.coeff == 1
    assert sorted(ts.free) == [(a, 0, 0), (b, 1, 0)]
    assert ts.components == [A]

    t = A(-b, a)*B(-a, c)*A(-c, d)
    t1 = tensor_mul(*t.split())
    assert t == t(-b, d)
    assert t == t1
    assert tensor_mul(*[]) == TensMul.from_data(S.One, [], [], [])

    t = TensMul.from_data(1, [], [], [])
    zsym = tensorsymmetry()
    typ = TensorType([], zsym)
    C = typ('C')
    assert str(C()) == 'C'
    assert str(t) == '1'
    assert t.split()[0] == t
    pytest.raises(ValueError, lambda: TIDS.free_dum_from_indices(a, a))
    pytest.raises(ValueError, lambda: TIDS.free_dum_from_indices(-a, -a))
    pytest.raises(ValueError, lambda: A(a, b)*A(a, c))
    t = A(a, b)*A(-a, c)
    pytest.raises(ValueError, lambda: t(a, b, c))


def test_substitute_indices():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    i, j, k, l, m, n, p, q = tensor_indices('i,j,k,l,m,n,p,q', Lorentz)
    A, B = tensorhead('A,B', [Lorentz]*2, [[1]*2])
    t = A(i, k)*B(-k, -j)
    t1 = t.substitute_indices((i, j), (j, k))
    t1a = A(j, l)*B(-l, -k)
    assert t1 == t1a

    p = tensorhead('p', [Lorentz], [[1]])
    t = p(i)
    t1 = t.substitute_indices((j, k))
    assert t1 == t
    t1 = t.substitute_indices((i, j))
    assert t1 == p(j)
    t1 = t.substitute_indices((i, -j))
    assert t1 == p(-j)
    t1 = t.substitute_indices((-i, j))
    assert t1 == p(-j)
    t1 = t.substitute_indices((-i, -j))
    assert t1 == p(j)

    A_tmul = A(m, n)
    A_c = A_tmul(m, -m)
    assert _is_equal(A_c, A(n, -n))
    ABm = A(i, j)*B(m, n)
    ABc1 = ABm(i, j, -i, -j)
    assert _is_equal(ABc1, A(i, -j)*B(-i, j))
    ABc2 = ABm(i, -i, j, -j)
    assert _is_equal(ABc2, A(m, -m)*B(-n, n))

    asum = A(i, j) + B(i, j)
    asc1 = asum(i, -i)
    assert _is_equal(asc1, A(i, -i) + B(i, -i))

    assert A(i, -i) == A(i, -i)()
    assert A(i, -i) + B(-j, j) == ((A(i, -i) + B(i, -i)))()
    assert _is_equal(A(i, j)*B(-j, k), (A(m, -j)*B(j, n))(i, k))
    pytest.raises(ValueError, lambda: A(i, -i)(j, k))


def test_riemann_cyclic_replace():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    m0, m1, m2, m3 = tensor_indices('m:4', Lorentz)
    symr = tensorsymmetry([2, 2])
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    t = R(m0, m2, m1, m3)
    t1 = riemann_cyclic_replace(t)
    t1a = -S.One/3*R(m0, m3, m2, m1) + S.One/3*R(m0, m1, m2, m3) + Rational(2, 3)*R(m0, m2, m1, m3)
    assert t1 == t1a


def test_riemann_cyclic():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    i, j, k, l, m, n, p, q = tensor_indices('i,j,k,l,m,n,p,q', Lorentz)
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    t = R(i, j, k, l) + R(i, l, j, k) + R(i, k, l, j) - \
        R(i, j, l, k) - R(i, l, k, j) - R(i, k, j, l)
    t2 = t*R(-i, -j, -k, -l)
    t3 = riemann_cyclic(t2)
    assert t3 == 0
    t = R(i, j, k, l)*(R(-i, -j, -k, -l) - 2*R(-i, -k, -j, -l))
    t1 = riemann_cyclic(t)
    assert t1 == 0
    t = R(i, j, k, l)
    t1 = riemann_cyclic(t)
    assert t1 == -Rational(1, 3)*R(i, l, j, k) + Rational(1, 3)*R(i, k, j, l) + Rational(2, 3)*R(i, j, k, l)

    t = R(i, j, k, l)*R(-k, -l, m, n)*(R(-m, -n, -i, -j) + 2*R(-m, -j, -n, -i))
    t1 = riemann_cyclic(t)
    assert t1 == 0


def test_div():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    m0, m1, m2, m3 = tensor_indices('m0:4', Lorentz)
    R = tensorhead('R', [Lorentz]*4, [[2, 2]])
    t = R(m0, m1, -m1, m3)
    t1 = t/Integer(4)
    assert str(t1) == '1/4*R(m0, L_0, -L_0, m3)'
    t = t.canon_bp()
    assert not t1._is_canon_bp
    t1 = t*4
    assert t1._is_canon_bp
    t1 = t1/4
    assert t1._is_canon_bp


def test_contract_metric1():
    D = Symbol('D')
    Lorentz = TensorIndexType('Lorentz', dim=D, dummy_fmt='L')
    a, b, c, d, e = tensor_indices('a,b,c,d,e', Lorentz)
    g = Lorentz.metric
    p = tensorhead('p', [Lorentz], [[1]])
    t = g(a, b)*p(-b)
    t1 = t.contract_metric(g)
    assert t1 == p(a)
    A, B = tensorhead('A,B', [Lorentz]*2, [[1]*2])

    # case with g with all free indices
    t1 = A(a, b)*B(-b, c)*g(d, e)
    t2 = t1.contract_metric(g)
    assert t1 == t2

    # case of g(d, -d)
    t1 = A(a, b)*B(-b, c)*g(-d, d)
    t2 = t1.contract_metric(g)
    assert t2 == D*A(a, d)*B(-d, c)

    # g with one free index
    t1 = A(a, b)*B(-b, -c)*g(c, d)
    t2 = t1.contract_metric(g)
    assert t2 == A(a, c)*B(-c, d)

    # g with both indices contracted with another tensor
    t1 = A(a, b)*B(-b, -c)*g(c, -a)
    t2 = t1.contract_metric(g)
    assert _is_equal(t2, A(a, b)*B(-b, -a))

    t1 = A(a, b)*B(-b, -c)*g(c, d)*g(-a, -d)
    t2 = t1.contract_metric(g)
    assert _is_equal(t2, A(a, b)*B(-b, -a))

    t1 = A(a, b)*g(-a, -b)
    t2 = t1.contract_metric(g)
    assert _is_equal(t2, A(a, -a))
    assert not t2.free
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    a, b = tensor_indices('a,b', Lorentz)
    g = Lorentz.metric
    pytest.raises(ValueError, lambda: g(a, -a).contract_metric(g))  # no dim


def test_contract_metric2():
    D = Symbol('D')
    Lorentz = TensorIndexType('Lorentz', dim=D, dummy_fmt='L')
    a, b, c, d, e, L_0 = tensor_indices('a,b,c,d,e,L_0', Lorentz)
    g = Lorentz.metric
    p, q = tensorhead('p,q', [Lorentz], [[1]])

    t1 = g(a, b)*p(c)*p(-c)
    t2 = 3*g(-a, -b)*q(c)*q(-c)
    t = t1*t2
    t = t.contract_metric(g)
    assert t == 3*D*p(a)*p(-a)*q(b)*q(-b)
    t1 = g(a, b)*p(c)*p(-c)
    t2 = 3*q(-a)*q(-b)
    t = t1*t2
    t = t.contract_metric(g)
    t = t.canon_bp()
    assert t == 3*p(a)*p(-a)*q(b)*q(-b)

    t1 = 2*g(a, b)*p(c)*p(-c)
    t2 = - 3*g(-a, -b)*q(c)*q(-c)
    t = t1*t2
    t = t.contract_metric(g)
    t = 6*g(a, b)*g(-a, -b)*p(c)*p(-c)*q(d)*q(-d)
    t = t.contract_metric(g)

    t1 = 2*g(a, b)*p(c)*p(-c)
    t2 = q(-a)*q(-b) + 3*g(-a, -b)*q(c)*q(-c)
    t = t1*t2
    t = t.contract_metric(g)
    assert t == (2 + 6*D)*p(a)*p(-a)*q(b)*q(-b)

    t1 = p(a)*p(b) + p(a)*q(b) + 2*g(a, b)*p(c)*p(-c)
    t2 = q(-a)*q(-b) - g(-a, -b)*q(c)*q(-c)
    t = t1*t2
    t = t.contract_metric(g)
    t1 = (1 - 2*D)*p(a)*p(-a)*q(b)*q(-b) + p(a)*q(-a)*p(b)*q(-b)
    assert t == t1

    t = g(a, b)*g(c, d)*g(-b, -c)
    t1 = t.contract_metric(g)
    assert t1 == g(a, d)

    t1 = g(a, b)*g(c, d) + g(a, c)*g(b, d) + g(a, d)*g(b, c)
    t2 = t1.substitute_indices((a, -a), (b, -b), (c, -c), (d, -d))
    t = t1*t2
    t = t.contract_metric(g)
    assert t.equals(3*D**2 + 6*D)

    t = 2*p(a)*g(b, -b)
    t1 = t.contract_metric(g)
    assert t1.equals(2*D*p(a))

    t = 2*p(a)*g(b, -a)
    t1 = t.contract_metric(g)
    assert t1 == 2*p(b)

    M = Symbol('M')
    t = (p(a)*p(b) + g(a, b)*M**2)*g(-a, -b) - D*M**2
    t1 = t.contract_metric(g)
    assert t1 == p(a)*p(-a)

    A = tensorhead('A', [Lorentz]*2, [[1]*2])
    t = A(a, b)*p(L_0)*g(-a, -b)
    t1 = t.contract_metric(g)
    assert str(t1) == 'A(L_1, -L_1)*p(L_0)' or str(t1) == 'A(-L_1, L_1)*p(L_0)'


def test_metric_contract3():
    D = Symbol('D')
    Spinor = TensorIndexType('Spinor', dim=D, metric=True, dummy_fmt='S')
    a0, a1, a2, a3, a4 = tensor_indices('a0:5', Spinor)
    C = Spinor.metric
    chi, psi = tensorhead('chi,psi', [Spinor], [[1]], 1)
    B = tensorhead('B', [Spinor]*2, [[1], [1]])

    t = C(a0, -a0)
    t1 = t.contract_metric(C)
    assert t1.equals(-D)

    t = C(-a0, a0)
    t1 = t.contract_metric(C)
    assert t1.equals(D)

    t = C(a0, a1)*C(-a0, -a1)
    t1 = t.contract_metric(C)
    assert t1.equals(D)

    t = C(a1, a0)*C(-a0, -a1)
    t1 = t.contract_metric(C)
    assert t1.equals(-D)

    t = C(-a0, a1)*C(a0, -a1)
    t1 = t.contract_metric(C)
    assert t1.equals(-D)

    t = C(a1, -a0)*C(a0, -a1)
    t1 = t.contract_metric(C)
    assert t1.equals(D)

    t = C(a0, a1)*B(-a1, -a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, B(a0, -a0))

    t = C(a1, a0)*B(-a1, -a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -B(a0, -a0))

    t = C(a0, -a1)*B(a1, -a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -B(a0, -a0))

    t = C(-a0, a1)*B(-a1, a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -B(a0, -a0))

    t = C(-a0, -a1)*B(a1, a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, B(a0, -a0))

    t = C(-a1, a0)*B(a1, -a0)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, B(a0, -a0))

    t = C(a0, a1)*psi(-a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, psi(a0))

    t = C(a1, a0)*psi(-a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -psi(a0))

    t = C(a0, a1)*chi(-a0)*psi(-a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -chi(a1)*psi(-a1))

    t = C(a1, a0)*chi(-a0)*psi(-a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, chi(a1)*psi(-a1))

    t = C(-a1, a0)*chi(-a0)*psi(a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, chi(-a1)*psi(a1))

    t = C(a0, -a1)*chi(-a0)*psi(a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -chi(-a1)*psi(a1))

    t = C(-a0, -a1)*chi(a0)*psi(a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, chi(-a1)*psi(a1))

    t = C(-a1, -a0)*chi(a0)*psi(a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -chi(-a1)*psi(a1))

    t = C(-a1, -a0)*B(a0, a2)*psi(a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, -B(-a1, a2)*psi(a1))

    t = C(a1, a0)*B(-a2, -a0)*psi(-a1)
    t1 = t.contract_metric(C)
    assert _is_equal(t1, B(-a2, a1)*psi(-a1))


def test_epsilon():
    Lorentz = TensorIndexType('Lorentz', dim=4, dummy_fmt='L')
    a, b, c, d, e = tensor_indices('a,b,c,d,e', Lorentz)
    g = Lorentz.metric
    epsilon = Lorentz.epsilon
    p, q, r, s = tensorhead('p,q,r,s', [Lorentz], [[1]])

    t = epsilon(b, a, c, d)
    t1 = t.canon_bp()
    assert t1 == -epsilon(a, b, c, d)

    t = epsilon(c, b, d, a)
    t1 = t.canon_bp()
    assert t1 == epsilon(a, b, c, d)

    t = epsilon(c, a, d, b)
    t1 = t.canon_bp()
    assert t1 == -epsilon(a, b, c, d)

    t = epsilon(a, b, c, d)*p(-a)*q(-b)
    t1 = t.canon_bp()
    assert t1 == epsilon(c, d, a, b)*p(-a)*q(-b)

    t = epsilon(c, b, d, a)*p(-a)*q(-b)
    t1 = t.canon_bp()
    assert t1 == epsilon(c, d, a, b)*p(-a)*q(-b)

    t = epsilon(c, a, d, b)*p(-a)*q(-b)
    t1 = t.canon_bp()
    assert t1 == -epsilon(c, d, a, b)*p(-a)*q(-b)

    t = epsilon(c, a, d, b)*p(-a)*p(-b)
    t1 = t.canon_bp()
    assert t1 == 0

    t = epsilon(c, a, d, b)*p(-a)*q(-b) + epsilon(a, b, c, d)*p(-b)*q(-a)
    t1 = t.canon_bp()
    assert t1 == -2*epsilon(c, d, a, b)*p(-a)*q(-b)


def test_contract_delta1():
    # see Group Theory by Cvitanovic page 9
    n = Symbol('n')
    Color = TensorIndexType('Color', metric=None, dim=n, dummy_fmt='C')
    a, b, c, d, e, f = tensor_indices('a,b,c,d,e,f', Color)
    delta = Color.delta

    def idn(a, b, d, c):
        assert a.is_up and d.is_up
        assert not (b.is_up or c.is_up)
        return delta(a, c)*delta(d, b)

    def T(a, b, d, c):
        assert a.is_up and d.is_up
        assert not (b.is_up or c.is_up)
        return delta(a, b)*delta(d, c)

    def P1(a, b, c, d):
        return idn(a, b, c, d) - 1/n*T(a, b, c, d)

    def P2(a, b, c, d):
        return 1/n*T(a, b, c, d)

    t = P1(a, -b, e, -f)*P1(f, -e, d, -c)
    t1 = t.contract_delta(delta)
    assert t1 == P1(a, -b, d, -c)

    t = P2(a, -b, e, -f)*P2(f, -e, d, -c)
    t1 = t.contract_delta(delta)
    assert t1 == P2(a, -b, d, -c)

    t = P1(a, -b, e, -f)*P2(f, -e, d, -c)
    t1 = t.contract_delta(delta)
    assert t1 == 0

    t = P1(a, -b, b, -a)
    t1 = t.contract_delta(delta)
    assert t1.equals(n**2 - 1)


def test_fun():
    D = Symbol('D')
    Lorentz = TensorIndexType('Lorentz', dim=D, dummy_fmt='L')
    a, b, c, d, e = tensor_indices('a,b,c,d,e', Lorentz)
    g = Lorentz.metric

    p, q = tensorhead('p q', [Lorentz], [[1]])
    t = q(c)*p(a)*q(b) + g(a, b)*g(c, d)*q(-d)
    assert t(a, b, c) == t
    assert t - t(b, a, c) == q(c)*p(a)*q(b) - q(c)*p(b)*q(a)
    assert t(b, c, d) == q(d)*p(b)*q(c) + g(b, c)*g(d, e)*q(-e)
    t1 = t.fun_eval((a, b), (b, a))
    assert t1 == q(c)*p(b)*q(a) + g(a, b)*g(c, d)*q(-d)

    # check that g_{a b; c} = 0
    # example taken from  L. Brewin
    # "A brief introduction to Cadabra" arxiv:0903.2085
    # dg_{a b c} = \partial_{a} g_{b c} is symmetric in b, c
    dg = tensorhead('dg', [Lorentz]*3, [[1], [1]*2])
    # gamma^a_{b c} is the Christoffel symbol
    gamma = S.Half*g(a, d)*(dg(-b, -d, -c) + dg(-c, -b, -d) - dg(-d, -b, -c))
    # t = g_{a b; c}
    t = dg(-c, -a, -b) - g(-a, -d)*gamma(d, -b, -c) - g(-b, -d)*gamma(d, -a, -c)
    t = t.contract_metric(g)
    assert t == 0
    t = q(c)*p(a)*q(b)
    assert t(b, c, d) == q(d)*p(b)*q(c)


def test_TensorManager():
    Lorentz = TensorIndexType('Lorentz', dummy_fmt='L')
    LorentzH = TensorIndexType('LorentzH', dummy_fmt='LH')
    i, j = tensor_indices('i,j', Lorentz)
    ih, jh = tensor_indices('ih,jh', LorentzH)
    p, q = tensorhead('p q', [Lorentz], [[1]])
    ph, qh = tensorhead('ph qh', [LorentzH], [[1]])

    Gsymbol = Symbol('Gsymbol')
    GHsymbol = Symbol('GHsymbol')
    TensorManager.set_comm(Gsymbol, GHsymbol, 0)
    G = tensorhead('G', [Lorentz], [[1]], Gsymbol)
    assert TensorManager._comm_i2symbol[G.comm] == Gsymbol
    GH = tensorhead('GH', [LorentzH], [[1]], GHsymbol)
    ps = G(i)*p(-i)
    psh = GH(ih)*ph(-ih)
    t = ps + psh
    t1 = t*t
    assert t1 == ps*ps + 2*ps*psh + psh*psh
    qs = G(i)*q(-i)
    qsh = GH(ih)*qh(-ih)
    assert _is_equal(ps*qsh, qsh*ps)
    assert not _is_equal(ps*qs, qs*ps)
    n = TensorManager.comm_symbols2i(Gsymbol)
    assert TensorManager.comm_i2symbol(n) == Gsymbol

    assert GHsymbol in TensorManager._comm_symbols2i
    pytest.raises(ValueError, lambda: TensorManager.set_comm(GHsymbol, 1, 2))
    TensorManager.set_comms((Gsymbol, GHsymbol, 0), (Gsymbol, 1, 1))
    assert TensorManager.get_comm(n, 1) == TensorManager.get_comm(1, n) == 1
    TensorManager.clear()
    assert TensorManager.comm == [{0: 0, 1: 0, 2: 0}, {0: 0, 1: 1, 2: None}, {0: 0, 1: None}]
    assert GHsymbol not in TensorManager._comm_symbols2i
    nh = TensorManager.comm_symbols2i(GHsymbol)
    assert GHsymbol in TensorManager._comm_symbols2i


def test_hash():
    D = Symbol('D')
    Lorentz = TensorIndexType('Lorentz', dim=D, dummy_fmt='L')
    a, b, c, d, e = tensor_indices('a,b,c,d,e', Lorentz)
    g = Lorentz.metric

    p, q = tensorhead('p q', [Lorentz], [[1]])
    p_type = p.args[1]
    t1 = p(a)*q(b)
    t2 = p(a)*p(b)
    assert hash(t1) != hash(t2)
    t3 = p(a)*p(b) + g(a, b)
    t4 = p(a)*p(b) - g(a, b)
    assert hash(t3) != hash(t4)

    assert a.func(*a.args) == a
    assert Lorentz.func(*Lorentz.args) == Lorentz
    assert g.func(*g.args) == g
    assert p.func(*p.args) == p
    assert p_type.func(*p_type.args) == p_type
    assert p(a).func(*(p(a)).args) == p(a)
    assert t1.func(*t1.args) == t1
    assert t2.func(*t2.args) == t2
    assert t3.func(*t3.args) == t3
    assert t4.func(*t4.args) == t4

    assert hash(a.func(*a.args)) == hash(a)
    assert hash(Lorentz.func(*Lorentz.args)) == hash(Lorentz)
    assert hash(g.func(*g.args)) == hash(g)
    assert hash(p.func(*p.args)) == hash(p)
    assert hash(p_type.func(*p_type.args)) == hash(p_type)
    assert hash(p(a).func(*(p(a)).args)) == hash(p(a))
    assert hash(t1.func(*t1.args)) == hash(t1)
    assert hash(t2.func(*t2.args)) == hash(t2)
    assert hash(t3.func(*t3.args)) == hash(t3)
    assert hash(t4.func(*t4.args)) == hash(t4)

    def check_all(obj):
        return all([isinstance(_, Basic) for _ in obj.args])

    assert check_all(a)
    assert check_all(Lorentz)
    assert check_all(g)
    assert check_all(p)
    assert check_all(p_type)
    assert check_all(p(a))
    assert check_all(t1)
    assert check_all(t2)
    assert check_all(t3)
    assert check_all(t4)

    tsymmetry = tensorsymmetry([2], [1], [1, 1, 1])

    assert tsymmetry.func(*tsymmetry.args) == tsymmetry
    assert hash(tsymmetry.func(*tsymmetry.args)) == hash(tsymmetry)
    assert check_all(tsymmetry)


def test_hidden_indices_for_matrix_multiplication():
    L = TensorIndexType('Lorentz')
    S = TensorIndexType('Matind')

    m0, m1, m2, m3, m4, m5 = tensor_indices('m0:6', L)
    s0, s1, s2 = tensor_indices('s0:3', S)

    A = tensorhead('A', [L, S, S], [[1], [1], [1]], matrix_behavior=True)
    B = tensorhead('B', [L, S], [[1], [1]], matrix_behavior=True)
    D = tensorhead('D', [L, L, S, S], [[1, 1], [1, 1]], matrix_behavior=True)
    E = tensorhead('E', [L, L, L, L], [[1], [1], [1], [1]], matrix_behavior=True)
    F = tensorhead('F', [L], [[1]], matrix_behavior=True)

    assert (A(m0)) == A(m0, S.auto_left, -S.auto_right)
    assert (B(-m1)) == B(-m1, S.auto_left)

    A0 = A(m0)
    B0 = B(-m0)
    B1 = B(m1)

    assert _is_equal((B1*A0*B0), B(m1, s0)*A(m0, -s0, s1)*B(-m0, -s1))
    assert _is_equal((B0*A0), B(-m0, s0)*A(m0, -s0, S.auto_left))
    assert _is_equal((A0*B0), A(m0, S.auto_left, s0)*B(-m0, -s0))

    C = tensorhead('C', [L, L], [[1]*2])

    assert _is_equal((C(True, True)), C(L.auto_left, -L.auto_right))

    assert _is_equal((A(m0)*C(m1, -m0)), A(m2, S.auto_left, -S.auto_right)*C(m1, -m2))

    assert _is_equal((C(True, True)*C(True, True)), C(L.auto_left, m0)*C(-m0, -L.auto_right))

    assert _is_equal(A(m0), A(m0))
    assert _is_equal(B(-m1), B(-m1))

    assert _is_equal(A(m0) - A(m0), 0)
    ts1 = A(m0)*A(m1) + A(m1)*A(m0)
    ts2 = A(m1)*A(m0) + A(m0)*A(m1)
    assert _is_equal(ts1, ts2)
    assert _is_equal(A(m0)*A(m1) + A(m1)*A(m0), A(m1)*A(m0) + A(m0)*A(m1))

    assert _is_equal(A(m0), (2*A(m0))/2)
    assert _is_equal(A(m0), -(-A(m0)))
    assert _is_equal(2*A(m0) - 3*A(m0), -A(m0))
    assert _is_equal(2*D(m0, m1) - 5*D(m1, m0), -3*D(m0, m1))

    D0 = D(True, True, True, True)
    Aa = A(True, True, True)

    assert _is_equal(D0 * Aa, D(L.auto_left, m0, S.auto_left, s0)*A(-m0, -s0, -S.auto_right))
    assert D(m0, m1) == D(m0, m1, S.auto_left, -S.auto_right)

    pytest.raises(ValueError, lambda: C(True))
    pytest.raises(ValueError, lambda: C())

    pytest.raises(ValueError, lambda: E(True, True, True, True))

    # test that a delta is automatically added on missing auto-matrix indices in TensAdd
    assert F(m2)*F(m3)*F(m4)*A(m1) + E(m1, m2, m3, m4) == \
        E(m1, m2, m3, m4)*S.delta(S.auto_left, -S.auto_right) +\
        F(m2)*F(m3)*F(m4)*A(m1, S.auto_left, -S.auto_right)
    assert E(m1, m2) + F(m1)*F(m2) == E(m1, m2) + F(m1)*F(m2)*L.delta(L.auto_left, -L.auto_right)
    assert E(m1, m2)*A(m3) + F(m1)*F(m2)*F(m3) == \
        E(m1, m2, L.auto_left, -L.auto_right)*A(m3, S.auto_left, -S.auto_right) +\
        F(m1)*F(m2)*F(m3)*L.delta(L.auto_left, -L.auto_right)*S.delta(S.auto_left, -S.auto_right)

    assert L.delta() == L.delta(L.auto_left, -L.auto_right)
    assert S.delta() == S.delta(S.auto_left, -S.auto_right)

    assert L.metric() == L.metric(L.auto_left, -L.auto_right)
    assert S.metric() == S.metric(S.auto_left, -S.auto_right)


# ### TEST VALUED TENSORS ###

numpy = import_module('numpy')


@pytest.mark.skipif(numpy is None, reason="no numpy")
def _get_valued_base_test_variables():
    minkowski = Matrix((
        (1, 0, 0, 0),
        (0, -1, 0, 0),
        (0, 0, -1, 0),
        (0, 0, 0, -1),
    ))
    Lorentz = TensorIndexType('Lorentz', dim=4)
    Lorentz.data = minkowski

    i0, i1, i2, i3, i4 = tensor_indices('i0:5', Lorentz)

    E, px, py, pz = symbols('E px py pz')
    A = tensorhead('A', [Lorentz], [[1]])
    A.data = [E, px, py, pz]
    B = tensorhead('B', [Lorentz], [[1]], 'Gcomm')
    B.data = range(4)
    AB = tensorhead("AB", [Lorentz] * 2, [[1]]*2)
    AB.data = minkowski

    ba_matrix = Matrix((
        (1, 2, 3, 4),
        (5, 6, 7, 8),
        (9, 0, -1, -2),
        (-3, -4, -5, -6),
    ))

    BA = tensorhead("BA", [Lorentz] * 2, [[1]]*2)
    BA.data = ba_matrix

    BA(i0, i1)*A(-i0)*B(-i1)

    # Let's test the diagonal metric, with inverted Minkowski metric:
    LorentzD = TensorIndexType('LorentzD')
    LorentzD.data = [-1, 1, 1, 1]
    mu0, mu1, mu2 = tensor_indices('mu0:3', LorentzD)
    C = tensorhead('C', [LorentzD], [[1]])
    C.data = [E, px, py, pz]

    # ### non-diagonal metric ###
    ndm_matrix = (
        (1, 1, 0,),
        (1, 0, 1),
        (0, 1, 0,),
    )
    ndm = TensorIndexType("ndm")
    ndm.data = ndm_matrix
    n0, n1, n2 = tensor_indices('n0:3', ndm)
    NA = tensorhead('NA', [ndm], [[1]])
    NA.data = range(10, 13)
    NB = tensorhead('NB', [ndm]*2, [[1]]*2)
    NB.data = [[i+j for j in range(10, 13)] for i in range(10, 13)]
    NC = tensorhead('NC', [ndm]*3, [[1]]*3)
    NC.data = [[[i+j+k for k in range(4, 7)] for j in range(1, 4)] for i in range(2, 5)]

    return (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
            n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4)


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_iter():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    # iteration on VTensorHead
    assert list(A) == [E, px, py, pz]
    assert list(ba_matrix) == list(BA)

    # iteration on VTensMul
    assert list(A(i1)) == [E, px, py, pz]
    assert list(BA(i1, i2)) == list(ba_matrix)
    assert list(3 * BA(i1, i2)) == [3 * i for i in list(ba_matrix)]
    assert list(-5 * BA(i1, i2)) == [-5 * i for i in list(ba_matrix)]

    # iteration on VTensAdd
    # A(i1) + A(i1)
    assert list(A(i1) + A(i1)) == [2*E, 2*px, 2*py, 2*pz]
    assert BA(i1, i2) - BA(i1, i2) == 0
    assert list(BA(i1, i2) - 2 * BA(i1, i2)) == [-i for i in list(ba_matrix)]


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_covariant_contravariant_elements():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    assert A(-i0)[0] == A(i0)[0]
    assert A(-i0)[1] == -A(i0)[1]

    assert AB(i0, i1)[1, 1] == -1
    assert AB(i0, -i1)[1, 1] == 1
    assert AB(-i0, -i1)[1, 1] == -1
    assert AB(-i0, i1)[1, 1] == 1


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_get_matrix():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    matab = AB(i0, i1).get_matrix()
    assert matab == Matrix([
        [1,  0,  0,  0],
        [0, -1,  0,  0],
        [0,  0, -1,  0],
        [0,  0,  0, -1],
    ])
    # when alternating contravariant/covariant with [1, -1, -1, -1] metric
    # it becomes the identity matrix:
    assert AB(i0, -i1).get_matrix() == eye(4)

    # covariant and contravariant forms:
    assert A(i0).get_matrix() == Matrix([E, px, py, pz])
    assert A(-i0).get_matrix() == Matrix([E, -px, -py, -pz])


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_contraction():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    assert (A(i0) * A(-i0)).data == E ** 2 - px ** 2 - py ** 2 - pz ** 2
    assert (A(i0) * A(-i0)).data == A ** 2
    assert (A(i0) * A(-i0)).data == A(i0) ** 2
    assert (A(i0) * B(-i0)).data == -px - 2 * py - 3 * pz

    for i in range(4):
        for j in range(4):
            assert (A(i0) * B(-i1))[i, j] == [E, px, py, pz][i] * [0, -1, -2, -3][j]

    # test contraction on the alternative Minkowski metric: [-1, 1, 1, 1]
    assert (C(mu0) * C(-mu0)).data == -E ** 2 + px ** 2 + py ** 2 + pz ** 2

    contrexp = A(i0) * AB(i1, -i0)
    assert A(i0).rank == 1
    assert AB(i1, -i0).rank == 2
    assert contrexp.rank == 1
    for i in range(4):
        assert contrexp[i] == [E, px, py, pz][i]


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_self_contraction():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    assert AB(i0, -i0).data == 4
    assert BA(i0, -i0).data == 2


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_pow():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    assert C**2 == -E**2 + px**2 + py**2 + pz**2
    assert C**1 == sqrt(-E**2 + px**2 + py**2 + pz**2)
    assert C(mu0)**2 == C**2
    assert C(mu0)**1 == C**1


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_tensor_expressions():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    x1, x2, x3 = symbols('x1:4')

    # test coefficient in contraction:
    rank2coeff = x1 * A(i3) * B(i2)
    assert rank2coeff[1, 1] == x1 * px
    assert rank2coeff[3, 3] == 3 * pz * x1
    coeff_expr = ((x1 * A(i4)) * (B(-i4) / x2)).data

    assert coeff_expr.expand() == -px*x1/x2 - 2*py*x1/x2 - 3*pz*x1/x2

    add_expr = A(i0) + B(i0)

    assert add_expr[0] == E
    assert add_expr[1] == px + 1
    assert add_expr[2] == py + 2
    assert add_expr[3] == pz + 3

    sub_expr = A(i0) - B(i0)

    assert sub_expr[0] == E
    assert sub_expr[1] == px - 1
    assert sub_expr[2] == py - 2
    assert sub_expr[3] == pz - 3

    assert (add_expr * B(-i0)).data == -px - 2*py - 3*pz - 14

    expr1 = x1*A(i0) + x2*B(i0)
    expr2 = expr1 * B(i1) * (-4)
    expr3 = expr2 + 3*x3*AB(i0, i1)
    expr4 = expr3 / 2
    assert expr4 * 2 == expr3
    expr5 = (expr4 * BA(-i1, -i0))

    assert expr5.data.expand() == 28*E*x1 + 12*px*x1 + 20*py*x1 + 28*pz*x1 + 136*x2 + 3*x3


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_noncommuting_components():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    euclid = TensorIndexType('Euclidean')
    euclid.data = [1, 1]
    i1, i2, i3 = tensor_indices('i1:4', euclid)

    a, b, c, d = symbols('a b c d', commutative=False)
    V1 = tensorhead('V1', [euclid] * 2, [[1]]*2)
    V1.data = [[a, b], (c, d)]
    V2 = tensorhead('V2', [euclid] * 2, [[1]]*2)
    V2.data = [[a, c], [b, d]]

    vtp = V1(i1, i2) * V2(-i2, -i1)

    assert vtp.data == a**2 + b**2 + c**2 + d**2
    assert vtp.data != a**2 + 2*b*c + d**2

    Vc = (b * V1(i1, -i1)).data
    assert Vc.expand() == b * a + b * d


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_non_diagonal_metric():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    mmatrix = Matrix(ndm_matrix)
    assert (NA(n0)*NA(-n0)).data == (NA(n0).get_matrix().T * mmatrix * NA(n0).get_matrix())[0, 0]


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_assign_numpy_ndarray():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    # this is needed to make sure that a numpy.ndarray can be assigned to a
    # tensor.
    arr = [E+1, px-1, py, pz]
    A.data = numpy.array(arr)
    for i in range(4):
            assert A(i0).data[i] == arr[i]

    qx, qy, qz = symbols('qx qy qz')
    A(-i0).data = numpy.array([E, qx, qy, qz])
    for i in range(4):
        assert A(i0).data[i] == [E, -qx, -qy, -qz][i]
        assert A.data[i] == [E, -qx, -qy, -qz][i]

    # test on multi-indexed tensors.
    random_4x4_data = [[(i**3 - 3*i**2) % (j + 7) for i in range(4)] for j in range(4)]
    AB(-i0, -i1).data = random_4x4_data
    for i in range(4):
        for j in range(4):
            assert AB(i0, i1).data[i, j] == random_4x4_data[i][j]*(-1 if i else 1)*(-1 if j else 1)
            assert AB(-i0, i1).data[i, j] == random_4x4_data[i][j]*(-1 if j else 1)
            assert AB(i0, -i1).data[i, j] == random_4x4_data[i][j]*(-1 if i else 1)
            assert AB(-i0, -i1).data[i, j] == random_4x4_data[i][j]

    AB(-i0, i1).data = random_4x4_data
    for i in range(4):
        for j in range(4):
            assert AB(i0, i1).data[i, j] == random_4x4_data[i][j]*(-1 if i else 1)
            assert AB(-i0, i1).data[i, j] == random_4x4_data[i][j]
            assert AB(i0, -i1).data[i, j] == random_4x4_data[i][j]*(-1 if i else 1)*(-1 if j else 1)
            assert AB(-i0, -i1).data[i, j] == random_4x4_data[i][j]*(-1 if j else 1)


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_metric_inverse():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    # let's assign some fancy matrix, just to verify it:
    # (this has no physical sense, it's just testing diofant);
    # it is symmetrical:
    md = [[2, 2, 2, 1], [2, 3, 1, 0], [2, 1, 2, 3], [1, 0, 3, 2]]
    Lorentz.data = md
    m = Matrix(md)
    metric = Lorentz.metric
    minv = m.inv()

    meye = eye(4)

    # the Kronecker Delta:
    KD = Lorentz.get_kronecker_delta()

    for i in range(4):
        for j in range(4):
            assert metric(i0, i1).data[i, j] == m[i, j]
            assert metric(-i0, -i1).data[i, j] == minv[i, j]
            assert metric(i0, -i1).data[i, j] == meye[i, j]
            assert metric(-i0, i1).data[i, j] == meye[i, j]
            assert metric(i0, i1)[i, j] == m[i, j]
            assert metric(-i0, -i1)[i, j] == minv[i, j]
            assert metric(i0, -i1)[i, j] == meye[i, j]
            assert metric(-i0, i1)[i, j] == meye[i, j]

            assert KD(i0, -i1)[i, j] == meye[i, j]


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_canon_bp_swapaxes():
    (A, B, AB, BA, C, Lorentz, E, px, py, pz, LorentzD, mu0, mu1, mu2, ndm, n0, n1,
     n2, NA, NB, NC, minkowski, ba_matrix, ndm_matrix, i0, i1, i2, i3, i4) = _get_valued_base_test_variables()

    e1 = A(i1)*A(i0)
    e1.data[0, 1] = 44
    e2 = e1.canon_bp()
    assert e2 == A(i0)*A(i1)
    for i in range(4):
        for j in range(4):
            assert e1[i, j] == e2[j, i]
    o1 = B(i2)*A(i1)*B(i0)
    o2 = o1.canon_bp()
    for i in range(4):
        for j in range(4):
            for k in range(4):
                assert o1[i, j, k] == o2[j, i, k]


def test_pprint():
    Lorentz = TensorIndexType('Lorentz')
    i0, i1, i2, i3, i4 = tensor_indices('i0:5', Lorentz)
    A = tensorhead('A', [Lorentz], [[1]])

    assert pretty(A) == "A(Lorentz)"
    assert pretty(A(i0)) == "A(i0)"


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_contract_automatrix_and_data():
    L = TensorIndexType('L')
    S = TensorIndexType('S')
    G = tensorhead('G', [L, S, S], [[1]]*3, matrix_behavior=True)

    def G_data():
        G.data = [[[1]]]
    pytest.raises(ValueError, G_data)
    L.data = [1, -1]
    pytest.raises(ValueError, G_data)
    S.data = [[1, 0], [0, 2]]
    G.data = [
        [[1, 2],
         [3, 4]],
        [[5, 6],
         [7, 8]]
    ]
    m0, m1, m2 = tensor_indices('m0:3', L)
    s0, s1, s2 = tensor_indices('s0:3', S)

    assert (G(-m0).data == numpy.array([
        [[1, 4],
         [3, 8]],
        [[-5, -12],
         [-7, -16]]])).all()

    (G(m0) * G(-m0)).data
    G(m0, s0, -s1).data

    c1 = G(m0, s0, -s1)*G(-m0, s1, -s2)
    c2 = G(m0) * G(-m0)

    assert (c1.data == c2.data).all()

    del L.data
    del S.data
    del G.data
    assert L.data is None
    assert S.data is None
    assert G.data is None


@pytest.mark.skipif(numpy is None, reason="no numpy")
def test_valued_components_with_wrong_symmetry():
    IT = TensorIndexType('IT', dim=3)
    i0, i1, i2, i3 = tensor_indices('i0:4', IT)
    IT.data = [1, 1, 1]
    A_nosym = tensorhead('A', [IT]*2, [[1]]*2)
    A_sym = tensorhead('A', [IT]*2, [[1]*2])
    A_antisym = tensorhead('A', [IT]*2, [[2]])

    mat_nosym = Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    mat_sym = mat_nosym + mat_nosym.T
    mat_antisym = mat_nosym - mat_nosym.T

    A_nosym.data = mat_nosym
    A_nosym.data = mat_sym
    A_nosym.data = mat_antisym

    def assign(A, dat):
        A.data = dat

    A_sym.data = mat_sym
    pytest.raises(ValueError, lambda: assign(A_sym, mat_nosym))
    pytest.raises(ValueError, lambda: assign(A_sym, mat_antisym))

    A_antisym.data = mat_antisym
    pytest.raises(ValueError, lambda: assign(A_antisym, mat_sym))
    pytest.raises(ValueError, lambda: assign(A_antisym, mat_nosym))

    A_sym.data = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
    A_antisym.data = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
