Needed Modules ============== .. Do not edit this section It was auto-generated .. by the `update_README.py` script. .. image:: tree_dependency.png * `Perturbation `_ * `Selectors_full `_ * `Generators_full `_ * `Psiref_Utils `_ * `Psiref_CAS `_ Documentation ============= .. Do not edit this section It was auto-generated .. by the `update_README.py` script. `a_coef `_ Undocumented `active_excitation_to_determinants_idx `_ Sparse matrix A containing the matrix to transform the active excitations to determinants : A | \Psi_0 > = | \Psi_SD > `active_excitation_to_determinants_val `_ Sparse matrix A containing the matrix to transform the active excitations to determinants : A | \Psi_0 > = | \Psi_SD > `active_hh_idx `_ is_active_exc : True if the excitation involves at least one active MO .br n_exc_active : Number of active excitations : Number of excitations without the inactive ones. .br active_hh_idx : .br active_pp_idx : `active_pp_idx `_ is_active_exc : True if the excitation involves at least one active MO .br n_exc_active : Number of active excitations : Number of excitations without the inactive ones. .br active_hh_idx : .br active_pp_idx : `add_poly `_ Add two polynomials D(t) =! D(t) +( B(t)+C(t)) `add_poly_multiply `_ Add a polynomial multiplied by a constant D(t) =! D(t) +( cst * B(t)) `apply_hole_local `_ Undocumented `apply_particle_local `_ Undocumented `apply_rotation `_ Apply the rotation found by find_rotation `approx_dble `_ Undocumented `b_coef `_ Undocumented `binom `_ Binomial coefficients `binom_func `_ .. math :: .br \frac{i!}{j!(i-j)!} .br `binom_transp `_ Binomial coefficients `ci_eigenvectors_dressed `_ Eigenvectors/values of the dressed CI matrix `ci_eigenvectors_s2_dressed `_ Eigenvectors/values of the dressed CI matrix `ci_electronic_energy_dressed `_ Eigenvectors/values of the dressed CI matrix `ci_energy_dressed `_ N_states lowest eigenvalues of the dressed CI matrix `davidson_diag_hjj_mrcc `_ Davidson diagonalization with specific diagonal elements of the H matrix .br H_jj : specific diagonal H matrix elements to diagonalize de Davidson .br dets_in : bitmasks corresponding to determinants .br u_in : guess coefficients on the various states. Overwritten on exit .br dim_in : leftmost dimension of u_in .br sze : Number of determinants .br N_st : Number of eigenstates .br N_st_diag : Number of states in which H is diagonalized .br iunit : Unit for the I/O .br Initial guess vectors are not necessarily orthonormal `davidson_diag_hjj_sjj_mrcc `_ Davidson diagonalization with specific diagonal elements of the H matrix .br H_jj : specific diagonal H matrix elements to diagonalize de Davidson .br S2_jj : specific diagonal S^2 matrix elements .br dets_in : bitmasks corresponding to determinants .br u_in : guess coefficients on the various states. Overwritten on exit .br dim_in : leftmost dimension of u_in .br sze : Number of determinants .br N_st : Number of eigenstates .br N_st_diag : Number of states in which H is diagonalized. Assumed > sze .br iunit : Unit for the I/O .br Initial guess vectors are not necessarily orthonormal `davidson_diag_mrcc `_ Davidson diagonalization. .br dets_in : bitmasks corresponding to determinants .br u_in : guess coefficients on the various states. Overwritten on exit .br dim_in : leftmost dimension of u_in .br sze : Number of determinants .br N_st : Number of eigenstates .br iunit : Unit number for the I/O .br Initial guess vectors are not necessarily orthonormal `davidson_diag_mrcc_hs2 `_ Davidson diagonalization. .br dets_in : bitmasks corresponding to determinants .br u_in : guess coefficients on the various states. Overwritten on exit .br dim_in : leftmost dimension of u_in .br sze : Number of determinants .br N_st : Number of eigenstates .br iunit : Unit number for the I/O .br Initial guess vectors are not necessarily orthonormal `dble_fact `_ Undocumented `dble_fact_even `_ n!! `dble_fact_odd `_ n!! `dble_logfact `_ n!! `ddfact2 `_ Undocumented `dec_exc `_ Undocumented `degree_max_integration_lebedev `_ integrate correctly a polynom of order "degree_max_integration_lebedev" needed for the angular integration according to LEBEDEV formulae `diagonalize_ci_dressed `_ Replace the coefficients of the CI states by the coefficients of the eigenstates of the CI matrix `dij `_ Undocumented `dij_unique `_ Undocumented `dset_order `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. `dset_order_big `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. This is a version for very large arrays where the indices need to be in integer*8 format `dsort `_ Sort array x(isize). iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `dtranspose `_ Transpose input matrix A into output matrix B `erf0 `_ Undocumented `exc_inf `_ Undocumented `exccmp `_ Undocumented `exceq `_ Undocumented `extrapolate_data `_ Extrapolate the data to the FCI limit `f_integral `_ function that calculates the following integral \int_{\-infty}^{+\infty} x^n \exp(-p x^2) dx `fact `_ n! `fact_inv `_ 1/n! `find_rotation `_ Find A.C = B `find_triples_and_quadruples `_ Undocumented `find_triples_and_quadruples_micro `_ Undocumented `gammln `_ Undocumented `gammp `_ Undocumented `gaussian_product `_ Gaussian product in 1D. e^{-a (x-x_A)^2} e^{-b (x-x_B)^2} = K_{ab}^x e^{-p (x-x_P)^2} `gaussian_product_x `_ Gaussian product in 1D. e^{-a (x-x_A)^2} e^{-b (x-x_B)^2} = K_{ab}^x e^{-p (x-x_P)^2} `gcf `_ Undocumented `get_dij `_ Undocumented `get_dij_index `_ Undocumented `get_inverse `_ Returns the inverse of the square matrix A `get_pseudo_inverse `_ Find C = A^-1 `give_explicit_poly_and_gaussian `_ Transforms the product of (x-x_A)^a(1) (x-x_B)^b(1) (x-x_A)^a(2) (y-y_B)^b(2) (z-z_A)^a(3) (z-z_B)^b(3) exp(-(r-A)^2 alpha) exp(-(r-B)^2 beta) into fact_k * [ sum (l_x = 0,i_order(1)) P_new(l_x,1) * (x-P_center(1))^l_x ] exp (- p (x-P_center(1))^2 ) * [ sum (l_y = 0,i_order(2)) P_new(l_y,2) * (y-P_center(2))^l_y ] exp (- p (y-P_center(2))^2 ) * [ sum (l_z = 0,i_order(3)) P_new(l_z,3) * (z-P_center(3))^l_z ] exp (- p (z-P_center(3))^2 ) `give_explicit_poly_and_gaussian_double `_ Transforms the product of (x-x_A)^a(1) (x-x_B)^b(1) (x-x_A)^a(2) (y-y_B)^b(2) (z-z_A)^a(3) (z-z_B)^b(3) exp(-(r-A)^2 alpha) exp(-(r-B)^2 beta) exp(-(r-Nucl_center)^2 gama .br into fact_k * [ sum (l_x = 0,i_order(1)) P_new(l_x,1) * (x-P_center(1))^l_x ] exp (- p (x-P_center(1))^2 ) * [ sum (l_y = 0,i_order(2)) P_new(l_y,2) * (y-P_center(2))^l_y ] exp (- p (y-P_center(2))^2 ) * [ sum (l_z = 0,i_order(3)) P_new(l_z,3) * (z-P_center(3))^l_z ] exp (- p (z-P_center(3))^2 ) `give_explicit_poly_and_gaussian_x `_ Transform the product of (x-x_A)^a(1) (x-x_B)^b(1) (x-x_A)^a(2) (y-y_B)^b(2) (z-z_A)^a(3) (z-z_B)^b(3) exp(-(r-A)^2 alpha) exp(-(r-B)^2 beta) into fact_k (x-x_P)^iorder(1) (y-y_P)^iorder(2) (z-z_P)^iorder(3) exp(-p(r-P)^2) `gser `_ Undocumented h_apply_mrcc Calls H_apply on the HF determinant and selects all connected single and double excitations (of the same symmetry). Auto-generated by the ``generate_h_apply`` script. h_apply_mrcc_diexc Undocumented h_apply_mrcc_diexcorg Generate all double excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. h_apply_mrcc_diexcp Undocumented h_apply_mrcc_monoexc Generate all single excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. h_apply_mrcc_pt2 Calls H_apply on the HF determinant and selects all connected single and double excitations (of the same symmetry). Auto-generated by the ``generate_h_apply`` script. h_apply_mrcc_pt2_diexc Undocumented h_apply_mrcc_pt2_diexcorg Generate all double excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. h_apply_mrcc_pt2_diexcp Undocumented h_apply_mrcc_pt2_monoexc Generate all single excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. h_apply_mrcepa_pt2 Calls H_apply on the HF determinant and selects all connected single and double excitations (of the same symmetry). Auto-generated by the ``generate_h_apply`` script. h_apply_mrcepa_pt2_diexc Undocumented h_apply_mrcepa_pt2_diexcorg Generate all double excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. h_apply_mrcepa_pt2_diexcp Undocumented h_apply_mrcepa_pt2_monoexc Generate all single excitations of key_in using the bit masks of holes and particles. Assume N_int is already provided. `h_matrix_dressed `_ Dressed H with Delta_ij `h_s2_u_0_mrcc_nstates `_ Computes v_0 = H|u_0> and s_0 = S^2 |u_0> .br n : number of determinants .br H_jj : array of .br S2_jj : array of `h_u_0_mrcc_nstates `_ Computes v_0 = H|u_0> .br n : number of determinants .br H_jj : array of `has_a_unique_parent `_ True if the determinant in the non-reference has a unique parent `heap_dsort `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `heap_dsort_big `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `heap_i2sort `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `heap_i2sort_big `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `heap_i8sort `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `heap_i8sort_big `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `heap_isort `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `heap_isort_big `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `heap_sort `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `heap_sort_big `_ Sort array x(isize) using the heap sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `hermite `_ Hermite polynomial `hh_exists `_ .br hh_exists : .br pp_exists : .br hh_shortcut : .br hh_nex : Total number of excitation operators .br `hh_nex `_ .br hh_exists : .br pp_exists : .br hh_shortcut : .br hh_nex : Total number of excitation operators .br `hh_shortcut `_ .br hh_exists : .br pp_exists : .br hh_shortcut : .br hh_nex : Total number of excitation operators .br `hij_mrcc `_ < ref | H | Non-ref > matrix `i2radix_sort `_ Sort integer array x(isize) using the radix sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. iradix should be -1 in input. `i2set_order `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. `i2set_order_big `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. This is a version for very large arrays where the indices need to be in integer*8 format `i2sort `_ Sort array x(isize). iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `i8radix_sort `_ Sort integer array x(isize) using the radix sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. iradix should be -1 in input. `i8radix_sort_big `_ Sort integer array x(isize) using the radix sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. iradix should be -1 in input. `i8set_order `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. `i8set_order_big `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. This is a version for very large arrays where the indices need to be in integer*8 format `i8sort `_ Sort array x(isize). iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_dsort `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_dsort_big `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `insertion_i2sort `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_i2sort_big `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `insertion_i8sort `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_i8sort_big `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `insertion_isort `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_isort_big `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `insertion_sort `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `insertion_sort_big `_ Sort array x(isize) using the insertion sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. This is a version for very large arrays where the indices need to be in integer*8 format `inv_int `_ 1/i `iradix_sort `_ Sort integer array x(isize) using the radix sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. iradix should be -1 in input. `iradix_sort_big `_ Sort integer array x(isize) using the radix sort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. iradix should be -1 in input. `is_active_exc `_ is_active_exc : True if the excitation involves at least one active MO .br n_exc_active : Number of active excitations : Number of excitations without the inactive ones. .br active_hh_idx : .br active_pp_idx : `is_generable `_ Undocumented `iset_order `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. `iset_order_big `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. This is a version for very large arrays where the indices need to be in integer*8 format `isort `_ Sort array x(isize). iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `lambda_mrcc `_ cm/ or perturbative 1/Delta_E(m) `lambda_mrcc_kept `_ cm/ or perturbative 1/Delta_E(m) `lambda_mrcc_pt2 `_ cm/ or perturbative 1/Delta_E(m) `lapack_diag `_ Diagonalize matrix H .br H is untouched between input and ouptut .br eigevalues(i) = ith lowest eigenvalue of the H matrix .br eigvectors(i,j) = where i is the basis function and psi_j is the j th eigenvector .br `lapack_diag_s2 `_ Diagonalize matrix H .br H is untouched between input and ouptut .br eigevalues(i) = ith lowest eigenvalue of the H matrix .br eigvectors(i,j) = where i is the basis function and psi_j is the j th eigenvector .br `lapack_diagd `_ Diagonalize matrix H .br H is untouched between input and ouptut .br eigevalues(i) = ith lowest eigenvalue of the H matrix .br eigvectors(i,j) = where i is the basis function and psi_j is the j th eigenvector .br `lapack_partial_diag `_ Diagonalize matrix H .br H is untouched between input and ouptut .br eigevalues(i) = ith lowest eigenvalue of the H matrix .br eigvectors(i,j) = where i is the basis function and psi_j is the j th eigenvector .br `logfact `_ n! `lowercase `_ Transform to lower case `map_load_from_disk `_ Undocumented `map_save_to_disk `_ Undocumented `matrix_vector_product `_ performs u1 =! performs u1 +( u0 * matrix) `mrcc_ata_ind `_ A is active_excitation_to_determinants in At.A `mrcc_ata_val `_ A is active_excitation_to_determinants in At.A `mrcc_col_shortcut `_ A is active_excitation_to_determinants in At.A `mrcc_dress `_ Undocumented `mrcc_n_col `_ A is active_excitation_to_determinants in At.A `mrmode `_ Undocumented `multi_state `_ Multi-state mixing `multiply_poly `_ Multiply two polynomials D(t) =! D(t) +( B(t)*C(t)) `n_ex_exists `_ Undocumented `n_exc_active `_ is_active_exc : True if the excitation involves at least one active MO .br n_exc_active : Number of active excitations : Number of excitations without the inactive ones. .br active_hh_idx : .br active_pp_idx : `n_exc_active_sze `_ Dimension of arrays to avoid zero-sized arrays `n_hh_exists `_ Undocumented `n_points_integration_angular_lebedev `_ Number of points needed for the angular integral `n_pp_exists `_ Undocumented `normalize `_ Normalizes vector u `nproc `_ Number of current OpenMP threads `ortho_canonical `_ Compute C_new=C_old.U.s^-1/2 canonical orthogonalization. .br overlap : overlap matrix .br LDA : leftmost dimension of overlap array .br N : Overlap matrix is NxN (array is (LDA,N) ) .br C : Coefficients of the vectors to orthogonalize. On exit, orthogonal vectors .br LDC : leftmost dimension of C .br m : Coefficients matrix is MxN, ( array is (LDC,N) ) .br `ortho_lowdin `_ Compute C_new=C_old.S^-1/2 orthogonalization. .br overlap : overlap matrix .br LDA : leftmost dimension of overlap array .br N : Overlap matrix is NxN (array is (LDA,N) ) .br C : Coefficients of the vectors to orthogonalize. On exit, orthogonal vectors .br LDC : leftmost dimension of C .br M : Coefficients matrix is MxN, ( array is (LDC,N) ) .br `ortho_qr `_ Orthogonalization using Q.R factorization .br A : matrix to orthogonalize .br LDA : leftmost dimension of A .br n : Number of rows of A .br m : Number of columns of A .br `ortho_qr_unblocked `_ Orthogonalization using Q.R factorization .br A : matrix to orthogonalize .br LDA : leftmost dimension of A .br n : Number of rows of A .br m : Number of columns of A .br `overlap_a_b_c `_ Undocumented `overlap_gaussian_x `_ .. math:: .br \sum_{-infty}^{+infty} (x-A_x)^ax (x-B_x)^bx exp(-alpha(x-A_x)^2) exp(-beta(x-B_X)^2) dx .br `overlap_gaussian_xyz `_ .. math:: .br S_x = \int (x-A_x)^{a_x} exp(-\alpha(x-A_x)^2) (x-B_x)^{b_x} exp(-beta(x-B_x)^2) dx \\ S = S_x S_y S_z .br `overlap_x_abs `_ .. math :: .br \int_{-infty}^{+infty} (x-A_center)^(power_A) * (x-B_center)^power_B * exp(-alpha(x-A_center)^2) * exp(-beta(x-B_center)^2) dx .br `phi_angular_integration_lebedev `_ Theta phi values together with the weights values for the angular integration : integral [dphi,dtheta] f(x,y,z) = 4 * pi * sum (1`_ .br hh_exists : .br pp_exists : .br hh_shortcut : .br hh_nex : Total number of excitation operators .br `progress_active `_ Current status for displaying progress bars. Global variable. `progress_bar `_ Current status for displaying progress bars. Global variable. `progress_timeout `_ Current status for displaying progress bars. Global variable. `progress_title `_ Current status for displaying progress bars. Global variable. `progress_value `_ Current status for displaying progress bars. Global variable. `psi_non_ref_sorted `_ Undocumented `psi_non_ref_sorted_idx `_ Undocumented `psi_ref_lock `_ Locks on ref determinants to fill delta_ij `quick_dsort `_ Sort array x(isize) using the quicksort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `quick_i2sort `_ Sort array x(isize) using the quicksort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `quick_i8sort `_ Sort array x(isize) using the quicksort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `quick_isort `_ Sort array x(isize) using the quicksort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `quick_sort `_ Sort array x(isize) using the quicksort algorithm. iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `rec__quicksort `_ Undocumented `rec_d_quicksort `_ Undocumented `rec_i2_quicksort `_ Undocumented `rec_i8_quicksort `_ Undocumented `rec_i_quicksort `_ Undocumented `recentered_poly2 `_ Recenter two polynomials `rho_mrcc `_ Undocumented `rint `_ .. math:: .br \int_0^1 dx \exp(-p x^2) x^n .br `rint1 `_ Standard version of rint `rint_large_n `_ Version of rint for large values of n `rint_sum `_ Needed for the calculation of two-electron integrals. `rinteg `_ Undocumented `rintgauss `_ Undocumented `run_progress `_ Display a progress bar with documentation of what is happening `sabpartial `_ Undocumented `searchdet `_ Undocumented `searchexc `_ Undocumented `set_generators_bitmasks_as_holes_and_particles `_ Undocumented `set_order `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. `set_order_big `_ array A has already been sorted, and iorder has contains the new order of elements of A. This subroutine changes the order of x to match the new order of A. This is a version for very large arrays where the indices need to be in integer*8 format `set_zero_extra_diag `_ Undocumented `sort `_ Sort array x(isize). iorder in input should be (1,2,3,...,isize), and in output contains the new order of the elements. `sort_det `_ Undocumented `sort_exc `_ Undocumented `sorted_dnumber `_ Returns the number of sorted elements `sorted_i2number `_ Returns the number of sorted elements `sorted_i8number `_ Returns the number of sorted elements `sorted_inumber `_ Returns the number of sorted elements `sorted_number `_ Returns the number of sorted elements `start_progress `_ Starts the progress bar `stop_progress `_ Stop the progress bar `svd `_ Compute A = U.D.Vt .br LDx : leftmost dimension of x .br Dimsneion of A is m x n .br `tamise_exc `_ Uncodumented : TODO `theta_angular_integration_lebedev `_ Theta phi values together with the weights values for the angular integration : integral [dphi,dtheta] f(x,y,z) = 4 * pi * sum (1`_ Transpose input matrix A into output matrix B `u_0_h_u_0_mrcc_nstates `_ Computes e_0 = / .br n : number of determinants .br `u_dot_u `_ Compute `u_dot_v `_ Compute `unsortedsearchdet `_ Undocumented `wall_time `_ The equivalent of cpu_time, but for the wall time. `weights_angular_integration_lebedev `_ Theta phi values together with the weights values for the angular integration : integral [dphi,dtheta] f(x,y,z) = 4 * pi * sum (1`_ Write the last git commit in file iunit.