Updates for new Core API v0.13.0

CHANGES.md

@@ -1,7 +1,9 @@
-### ?.?.? (????-??-??)
+### 1.5.0 (2019-11-22)
 
   * Switched to OPAM file generation via `dune-project`
 
+  * Updates for new Core API v0.13.0
+
 
 ### 1.4.1 (2018-10-24)
 

app/ocaml_gpr.ml

@@ -135,7 +135,8 @@ module Args = struct
         );
       ]
 
-  let usage_msg = sprintf "%s: -cmd [ train | test ] -model file" Sys.argv.(0)
+  let usage_msg =
+    sprintf "%s: -cmd [ train | test ] -model file" (Sys.get_argv ()).(0)
 
   let anon_fun _ = failwith "no anonymous arguments allowed"
 
@@ -325,7 +326,7 @@ let train args =
       let last_deriv_time = ref 0. in
       let maybe_print last_time line =
         let now = Unix.gettimeofday () in
-        if !last_time +. 1. < now then begin
+        if Float.(!last_time + 1. < now) then begin
           last_time := now;
           prerr_endline line;
         end

dune-project

@@ -21,7 +21,7 @@ and GPR implements some of the latest advances in this field.")
     (ocaml (>= 4.08))
     (dune (>= 1.10))
     base-threads
-    (core (>= 0.9.1))
+    (core (>= v0.13))
     (lacaml (>= 11.0.0))
     (gsl (>= 1.24.0))
   )

gpr.opam

@@ -21,7 +21,7 @@ depends: [
   "ocaml" {>= "4.08"}
   "dune" {>= "1.10"}
   "base-threads"
-  "core" {>= "0.9.1"}
+  "core" {>= "v0.13"}
   "lacaml" {>= "11.0.0"}
   "gsl" {>= "1.24.0"}
 ]

src/fitc_gp.ml

@@ -151,7 +151,7 @@ module Make_common (Spec : Specs.Eval) = struct
     type co_variance_coeffs = mat * mat
 
     let check_sigma2 sigma2 =
-      if sigma2 < 0. then failwith "Model.check_sigma2: sigma2 < 0"
+      if Float.(sigma2 < 0.) then failwith "Model.check_sigma2: sigma2 < 0"
 
     let calc_internal inputs sigma2 ~kn_diag ~v_mat ~r_vec =
       check_sigma2 sigma2;
@@ -189,7 +189,7 @@ module Make_common (Spec : Specs.Eval) = struct
           else
             let el =
               let el = r_mat.{r, r} in
-              if el > 0. then el
+              if Float.(el > 0.) then el
               else
                 (* Cannot happen with LAPACK version 3.2 and greater *)
                 let neg_el = -. el in
@@ -340,15 +340,15 @@ module Make_common (Spec : Specs.Eval) = struct
       let means = Trained.calc_means trained in
       let rec loop madsum i =
         if i = 0 then madsum /. f_samples
-        else loop (madsum +. Float.abs (y.{i} -. means.{i})) (i - 1)
+        else loop Float.(madsum + abs (y.{i} - means.{i})) (i - 1)
       in
       loop 0. n_samples
 
     let calc_maxad ({ Trained.y } as trained) =
       let means = Trained.calc_means trained in
       let rec loop maxad i =
         if i = 0 then maxad
-        else loop (max maxad (Float.abs (y.{i} -. means.{i}))) (i - 1)
+        else loop Float.(max maxad (abs (y.{i} - means.{i}))) (i - 1)
       in
       loop 0. (Vec.dim y)
 
@@ -368,7 +368,7 @@ module Make_common (Spec : Specs.Eval) = struct
           if i = 0 then madsum /. f_samples, maxad
           else
             let ad = Float.abs (y.{i} -. means.{i}) in
-            loop ~madsum:(madsum +. ad) ~maxad:(max maxad ad) (i - 1)
+            loop ~madsum:(madsum +. ad) ~maxad:(Float.max maxad ad) (i - 1)
         in
         loop ~madsum:0. ~maxad:0. n_samples
       in
@@ -1209,7 +1209,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
       let is_bad_deriv ~finite_el ~deriv ~tol =
         Float.is_nan finite_el
           || Float.is_nan deriv
-          || Float.abs (finite_el -. deriv) > tol
+          || Float.(abs (finite_el - deriv) > tol)
 
       let check_deriv_hyper ?(eps = 1e-8) ?(tol = 1e-2)
             kernel1 inducing_points1 points1 hyper =
@@ -1436,7 +1436,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
     module Optim = struct
       let get_sigma2 targets = function
         | None -> Vec.sqr_nrm2 targets /. float (Vec.dim targets)
-        | Some sigma2 when sigma2 < 0. ->
+        | Some sigma2 when Float.(sigma2 < 0.) ->
             failwithf "Optim.get_sigma2: sigma2 < 0: %f" sigma2 ()
         | Some sigma2 -> sigma2
 
@@ -1494,7 +1494,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
         exception Optim_exception of exn
 
         let check_exception seen_exception_ref res =
-          if Float.classify res = Float.Class.Nan then
+          if Poly.(Float.classify res = Float.Class.Nan) then
             match !seen_exception_ref with
             | None ->
                 failwith "Gpr.Optim.Gsl: optimization function returned nan"
@@ -1561,7 +1561,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
           let update_best_model trained log_evidence =
             match !best_model_ref with
             | Some (_, old_log_evidence)
-              when old_log_evidence >= log_evidence -> ()
+              when Float.(old_log_evidence >= log_evidence) -> ()
             | _ ->
                 report_trained_model ~iter:!iter_count trained;
                 best_model_ref := Some (trained, log_evidence)
@@ -1633,7 +1633,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
               try report_gradient_norm ~iter:!iter_count gnorm
               with exc -> raise (Optim_exception exc)
             end;
-            if gnorm < epsabs then get_best_model ()
+            if Float.(gnorm < epsabs) then get_best_model ()
             else begin
               incr iter_count;
               Gd.iterate mumin;
@@ -1676,15 +1676,15 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
           | Some max_iter -> max_iter
         in
         let rec loop n ~best_le ~best ~t =
-          if n = 0 || gradient_norm t < epsabs then best
+          if n = 0 || Float.(gradient_norm t < epsabs) then best
           else
             let new_t = step t in
             let best_le, best =
               let new_trained = get_trained new_t in
               let new_log_evidence =
                 Eval_trained.calc_log_evidence new_trained
               in
-              if new_log_evidence <= best_le then best_le, best
+              if Float.(new_log_evidence <= best_le) then best_le, best
               else begin
                 report new_t;
                 new_log_evidence, new_t
@@ -1714,7 +1714,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
               ~inputs ~targets () =
           let loc = "Gpr.Fitc_gp.Optim.SGD.create" in
           let fail_neg0 what v =
-            if v <= 0. then failwithf "%s: %s (%f) <= 0" loc what v ()
+            if Float.(v <= 0.) then failwithf "%s: %s (%f) <= 0" loc what v ()
           in
           fail_neg0 "tau" tau;
           fail_neg0 "eta0" eta;
@@ -1817,14 +1817,14 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
           let lambda =
             match lambda with
             | None -> 0.1
-            | Some lambda when lambda < 0. || lambda > 1. ->
+            | Some lambda when Float.(lambda < 0. || lambda > 1.) ->
                 failwithf "%s: violating 0 <= lambda(%f) <= 1" loc lambda ()
             | Some lambda -> lambda
           in
           let mu =
             match mu with
             | None -> 1e-3
-            | Some mu when mu < 0. ->
+            | Some mu when Float.(mu < 0.) ->
                 failwithf "%s: violating 0 <= mu(%f)" loc mu ()
             | Some mu -> mu
           in
@@ -1850,7 +1850,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
                 else begin
                   for i = 1 to n_all_hypers do
                     let eta0_i = eta0.{i} in
-                    if eta0_i <= 0. then
+                    if Float.(eta0_i <= 0.) then
                       failwithf "%s: eta0.{%d} < 0: %f" loc i eta0_i ()
                   done;
                   eta0
@@ -1933,7 +1933,7 @@ module Make_common_deriv (Spec : Specs.Deriv) = struct
           for i = 1 to n_all_hypers do
             eta.{i} <-
               old_eta.{i} *.
-                max 0.5 (1. +. mu *. old_gradient.{i} *. old_nu.{i})
+                Float.max 0.5 (1. +. mu *. old_gradient.{i} *. old_nu.{i})
           done;
           let sigma2, hyper_ix =
             if learn_sigma2 then