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Merge lpqsv26:QCaml
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commit
316a3df20d
132
CI/F12CI.ml
132
CI/F12CI.ml
@ -130,6 +130,11 @@ let p12 det_space =
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(Spindeterminant.of_bitstring @@
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Bitstring.(logor a (logand not_aux_mask beta))
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) )
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| 1, 0
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| 0, 1 -> Some (Determinant.negate_phase k)
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(*
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| 0, 1 -> Some (Determinant.vac 1)
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*)
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| _ -> None
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@ -312,6 +317,7 @@ Printf.printf "Add aux basis\n%!";
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let rec iteration ~state psi =
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let column_idx = iamax (Mat.to_col_vecs psi).(state-1) in
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let delta =
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(* delta_i = {% $\sum_j c_j H_{ij}$ %} *)
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dressing_vector ~frozen_core aux_basis psi ci
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@ -328,40 +334,112 @@ Printf.printf "Add aux basis\n%!";
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delta.{column_idx,state} *. psi.{column_idx,state} )
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in
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Printf.printf "Delta_00 : %e %e\n" delta.{column_idx,state} delta_00;
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delta.{column_idx,state} <- delta.{column_idx,state} -. delta_00;
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let diagonal =
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Vec.init (Matrix.dim1 m_H) (fun i ->
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if i = column_idx then
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Matrix.get m_H i i +. delta.{column_idx,state} *. f
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else
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Matrix.get m_H i i
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)
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in
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let matrix_prod c =
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let w =
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Matrix.mm ~transa:`T m_H c
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|> Matrix.to_mat
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in
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let c11 = Matrix.get c column_idx state in
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Util.list_range 1 (Mat.dim1 w)
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|> List.iter (fun i ->
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let dci =
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delta.{i,state} *. f ;
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in
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w.{i,state} <- w.{i,state} +. dci *. c11;
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if (i <> column_idx) then
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w.{column_idx,state} <- w.{column_idx,state} +. dci *. (Matrix.get c i state);
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);
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Matrix.dense_of_mat w
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in
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let eigenvectors, eigenvalues =
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(* Column dressing
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*)
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let delta = lacpy delta in
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Mat.scal f delta;
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for k=1 to state-1 do
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for i=1 to Mat.dim1 delta do
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delta.{i,k} <- delta.{i,state}
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done;
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done;
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let diagonal =
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Vec.init (Matrix.dim1 m_H) (fun i ->
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if i = column_idx then
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Matrix.get m_H i i +. delta.{column_idx,state}
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else
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Matrix.get m_H i i
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)
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in
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let matrix_prod c =
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let w =
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Matrix.mm ~transa:`T m_H c
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|> Matrix.to_mat
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in
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let c = Matrix.to_mat c in
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for k=1 to state do
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for i=1 to (Mat.dim1 w) do
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w.{i,k} <- w.{i,k} +. delta.{i,k} *. c.{column_idx, k} ;
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w.{column_idx,k} <- w.{column_idx,k} +. delta.{i,k} *. c.{i,k};
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done;
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w.{column_idx,k} <- w.{column_idx,k} -.
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delta.{column_idx,k} *. c.{column_idx,k};
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done;
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Matrix.dense_of_mat w
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in
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(* Diagonal dressing *)
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(*
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let diagonal =
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Vec.init (Matrix.dim1 m_H) (fun i ->
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Matrix.get m_H i i +.
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if (abs_float psi.{i,state} > 1.e-8) then
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delta.{i,state} /. psi.{i,state}
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else 0.
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)
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in
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let matrix_prod c =
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let w =
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Matrix.mm ~transa:`T m_H c
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|> Matrix.to_mat
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in
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for i=1 to (Mat.dim1 w) do
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w.{i,state} <- w.{i,state} +. delta.{i,state}
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done;
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Matrix.dense_of_mat w
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in
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*)
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Parallel.broadcast (lazy (
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Davidson.make ~threshold:1.e-6 ~guess:psi ~n_states:state diagonal matrix_prod
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Davidson.make ~threshold:1.e-9 ~guess:psi ~n_states:state diagonal matrix_prod
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))
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(*
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let m_H = Matrix.to_mat m_H |> lacpy in
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*)
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(* DIAGONAL TEST
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for i=1 to Mat.dim1 m_H do
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if (abs_float psi.{i,state} > 1.e-8) then
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m_H.{i,i} <- m_H.{i,i} +. delta.{i,state} /. psi.{i,state};
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done;
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*)
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(* COLUMN TEST
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for i=1 to Mat.dim1 m_H do
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let d = delta.{i,state} /. psi.{column_idx,state} in
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m_H.{i,column_idx} <- m_H.{i,column_idx} +. d;
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if (i <> column_idx) then
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begin
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m_H.{column_idx,i} <- m_H.{column_idx,i} +. d;
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m_H.{column_idx,column_idx} <- m_H.{column_idx,column_idx} -.
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d *. psi.{i,state}
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end
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done;
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*)
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(*
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let m_v = syev m_H in
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m_H, m_v
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*)
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in
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Vec.iter (fun energy -> Printf.printf "%g\t" energy) eigenvalues;
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print_newline ();
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@ -5,8 +5,8 @@ type t
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let make
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?guess
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?(n_states=1)
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?(n_iter=10)
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?(threshold=1.e-6)
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?(n_iter=8)
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?(threshold=1.e-7)
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diagonal
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matrix_prod
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=
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@ -105,13 +105,14 @@ let make
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(* Compute the residual as proposed new vectors *)
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let u_proposed =
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Mat.init_cols n m (fun i k ->
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let delta = diagonal.{i} -. lambda.{k} in
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let delta = lambda.{k} -. diagonal.{i} in
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let delta =
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if abs_float delta > 0.01 then delta
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else if delta < 0. then -.0.01
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else 0.01
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if abs_float delta > 1.e-2 then delta
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else if delta > 0. then 1.e-2
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else (-1.e-2)
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in
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(lambda.{k} *. m_new_U.{i,k} -. m_new_W.{i,k}) /. delta )
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(lambda.{k} *. m_new_U.{i,k} -. m_new_W.{i,k}) /. delta
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)
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|> Mat.to_col_vecs_list
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in
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@ -130,11 +131,12 @@ let make
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end;
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(* Make new vectors sparse *)
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let u_proposed =
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Mat.of_col_vecs_list u_proposed
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in
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let maxu = lange u_proposed ~norm:`M in
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let thr = maxu *. 0.01 in
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let thr = maxu *. 0.001 in
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let u_proposed =
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Mat.map (fun x -> if abs_float x < thr then 0. else x) u_proposed
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|> Mat.to_col_vecs_list
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@ -155,6 +157,6 @@ let make
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(m_new_U |> pick_new |> Mat.of_col_vecs_list), lambda
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in
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iteration [] u_new [] 1 5
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iteration [] u_new [] 1 30
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