(* Title:  MathEngBasic/problem.sml

   Author: Walther Neuper 2019

   (c) due to copyright terms

\<open>ML_structure Problem\<close> holds the essential information required for automated doing

\<open>ML_structure Specification\<close> and \<open>ML_structure Solution\<close>.

Why \<open>ML_structure Problem\<close> is not parsed on the fly within the current \<open>ML_structure Context\<close> 

see \<open>ML_structure Refine\<close>.

*)

signature PROBLEM =

sig

  type T = Probl_Def.T

  val empty: T

  type id = Probl_Def.id

  type id_reverse

  val id_empty: id

  val id_to_string: id -> string

  type input                          

  type model_input

  val split_did: term -> term * term

  (* TODO: ---------- remove always empty ----- vvvvvvvvvvv -- vvv*)

  val prep_input : theory -> Check_Unique.id -> string list -> id -> input -> T * id

  val set_data: Rule_Def.rule_set -> theory -> theory

  val the_data: theory -> Rule_Def.rule_set

  val parse_item: string parser -> 'a parser -> 'a parser

  val parse_item_name: string parser -> string -> string parser

  val parse_item_names: string parser -> string list parser

  val parse_model_input: model_input parser

  val parse_authors: string list parser

  val parse_cas: Token.T list -> string option * Token.T list

  val parse_methods: string list parser

  val ml: string -> ML_Lex.token Antiquote.antiquote list

(*val adapt_to_type: Proof.context -> T -> T*)

(** )val from_store: id -> T( **)

  val from_store: Proof.context -> id -> T

end

(**)

structure Problem(**): PROBLEM(**) =

struct

(**)

type T = Probl_Def.T;

val empty = Probl_Def.empty

(*

  elements if the id are in reverse order as compared to MethodC:

  e.g. ["linear", "univariate", "equation"] has "equation" as parent node --

  -- this makes the id readable.

*)

type id = Probl_Def.id;

(* same order as for MethodC (used in Store )*)

type id_reverse = Probl_Def.id;

val id_empty = Probl_Def.id_empty;

val id_to_string = Probl_Def.id_to_string;

(** prepare Problem for Store **)

type model_input =

  (Model_Pattern.m_field *     (* "#Given", "#Find", "#Where", "#Relate" *)

    TermC.as_string list)      (* list of items belonging to m_field     *)

  list;                        (* list of "#Given" .. "#Relate"          *)

type input =

  id *                         (* the key into the problem hierarchy     *)

  model_input *                (* e.g. ("#Given", ["unsorted u_u"]) list *)

  Rule_Set.T *                 (* for evaluating "#Where"                *)

  TermC.as_string option *     (* CAS_Cmd                                *)

  Meth_Def.id list;            (* methods that can solve the problem     *)

(* split a term into description and (id | structured variable) for pbt, met.ppc *)

fun split_did t =

  let

    val (hd, arg) = case strip_comb t of

      (hd, [arg]) => (hd, arg)

    | _ => raise ERROR ("split_did: doesn't match (hd,[arg]) for t = xxxxx" (*^ UnparseC.term t*))

  in (hd, arg) end

(* prepare problem-types before storing in pbltypes; 

   dont forget to "check_guh_unique" before inserting   *)

fun prep_input thy guh maa init (pblID, dsc_dats, ev, ca, metIDs) =

    let

      fun eq f (f', _) = f = f';

val _ = writeln "#prep_input 1";

      val gi = filter (eq "#Given") dsc_dats;

val _ = writeln "#prep_input 1a";

      val gi = (case gi of

		    [] => []

		  | ((_, gi') :: []) =>

        map (split_did o (Syntax.read_term_global thy)) gi'

		  | _ => raise ERROR ("prep_input: more than one '#Given' in xxxxx" (*^ strs2str pblID*)));

val _ = writeln "#prep_input 1b";

		  val gi = map (pair "#Given") gi;

val _ = writeln "#prep_input 2";

		  val fi = filter (eq "#Find") dsc_dats;

		  val fi = (case fi of

		    [] => []

		  | ((_, fi') :: []) =>

        (*(case \<^try>\<open> *)map (split_did o (Syntax.read_term_global thy)) fi'(*\<close> of

          SOME x => x

        | NONE => raise ERROR ("prep_input: syntax raise ERROR in '#Find' of " ^ strs2str pblID))*)

		  | _ => raise ERROR ("prep_input: more than one '#Find' in xxxxx" (*^ strs2str pblID*)));

		  val fi = map (pair "#Find") fi;

val _ = writeln "#prep_input 3";

		  val re = filter (eq "#Relate") dsc_dats;

		  val re = (case re of

		    [] => []

		  | ((_, re') :: []) =>

        (*(case \<^try>\<open> *)map (split_did o (Syntax.read_term_global thy)) re'(*\<close> of

          SOME x => x

        | NONE => raise ERROR ("prep_input: syntax raise ERROR in '#Relate' of " ^ strs2str pblID))*)

		  | _ => raise ERROR ("prep_input: more than one '#Relate' in xxxxx" (*^ strs2str pblID*)));

		  val re = map (pair "#Relate") re;

val _ = writeln "#prep_input 4";

		  val wh = filter (eq "#Where") dsc_dats;

		  val wh = (case wh of

		    [] => []

		  | ((_, wh') :: []) => (*special case in parsing*)

        (*(case \<^try>\<open> *)map (TermC.parse_patt thy) wh'(*\<close> of

          SOME x => x

        | NONE => raise ERROR ("prep_input: syntax raise ERROR in '#Where' of " ^ strs2str pblID))*)

		  | _ => raise ERROR ("prep_input: more than one '#Where' in xxxxx" (*^ strs2str pblID*)));

    in

      ({guh = guh, mathauthors = maa, init = init, thy = thy,

        cas = Option.map (Syntax.read_term_global thy) ca,

			  prls = ev, where_ = wh, ppc = gi @ fi @ re, met = metIDs}, pblID)

    end;

(** Isar command **)

(* theory data *)

structure Data = Theory_Data

(

  type T = Rule_Set.T option;

  val empty = NONE;

  val extend = I;

  fun merge _ = NONE;

);

val set_data = Data.put o SOME;

val the_data = the o Data.get;

(* auxiliary parsers *)

fun parse_item (keyword: string parser) (parse: 'a parser) =

  (keyword -- Args.colon) |-- Parse.!!! parse;

fun parse_item_name keyword =

  Scan.optional (parse_item keyword Parse.name);

fun parse_item_names (keyword: string parser) =

  Scan.optional (parse_item keyword (Scan.repeat1 Parse.name)) [];

fun parse_tagged_terms keyword (tag: string) =

  Scan.optional (parse_item keyword (Scan.repeat Parse.term) >> (fn ts => [(tag, ts)])) [];

val parse_model_input : model_input parser =

  parse_tagged_terms \<^keyword>\<open>Given\<close> "#Given" @@@

  parse_tagged_terms \<^keyword>\<open>Where\<close> "#Where" @@@

  parse_tagged_terms \<^keyword>\<open>Find\<close> "#Find" @@@

  parse_tagged_terms \<^keyword>\<open>Relate\<close> "#Relate";

val parse_authors = parse_item_names \<^keyword>\<open>Author\<close>;

val parse_cas = Scan.option (parse_item \<^keyword>\<open>CAS\<close> Parse.term);

val parse_methods = parse_item_names \<^keyword>\<open>Method_Ref\<close>;

val ml = ML_Lex.read;

(* command definition *)

local

val _ =

  Outer_Syntax.command \<^command_keyword>\<open>problem\<close>

    "prepare ISAC problem type and register it to Knowledge Store"

    (Parse.name -- Parse.!!! (\<^keyword>\<open>:\<close> |-- Parse.name --

      Parse.!!! (\<^keyword>\<open>=\<close> |-- Parse.ML_source -- parse_authors --

        parse_methods -- parse_cas -- parse_model_input)) >>

      (fn (name, (id, ((((source, maa), mets), cas), model_input))) =>

        Toplevel.theory (fn thy =>

          let

(*Ouptut from Biegelinie.problem pbl_bieg : "Biegelinien":*)

            val pblID = References_Def.explode_id id;

            val metIDs = map References_Def.explode_id mets;

(*val _ = writeln ("#problem source: " ^ @{make_string} source)*)

            val set_data =

              ML_Context.expression (Input.pos_of source)

                (ml "Theory.setup (Problem.set_data (" @ ML_Lex.read_source source @ ml "))")

              |> Context.theory_map;

(*val _ = writeln ("#problem set_data: " ^ @{make_string} set_data)*)

            (* Context.theory_map HAS STORED THE ml-source IN Theory_Data ALREADY,

               BUT prep_input REQUIRES ml-source AGAIN ... *)

            val input = the_data (set_data thy);

(*val _ = writeln ("#problem input: " ^ @{make_string} input)*)

(*

val _ = writeln ("#problem model_input: " ^ @{make_string} model_input)

val (m1, m2) = case model_input of

  ("#Given", [m1, m2]) :: _ => (m1, m2) (*=("<markup>", "<markup>")*)

| _ => ("different case model_input", "different case model_input")

val _ = writeln ("#problem m1: " ^ m1)  (*= Traegerlaenge l_l*)

val _ = writeln ("#problem m2: " ^ m2)  (*= Streckenlast q_q *)

            ( * TODO: 

             * parse_model_input should preserve Position.T, Position.range, etc

             * ? preserve Position.T etc within ML_Lex.token Antiquote.antiquote list ?.. 

               ..in analogy to set_data ?!?

             * by Context.theory_map notify Isabelle/PIDE of errors from model_input at Position.T

             * in case there are no errors, do prep_input (to be simplified)

             *)

            val arg = prep_input thy name maa id_empty (pblID, model_input, input, cas, metIDs);

          in KEStore_Elems.add_pbls @{context} [arg] thy end)))

in end;

(** get Problem from Store **)

fun adapt_to_type ctxt ({guh, mathauthors, init, thy, cas, met, prls, where_, ppc} : Probl_Def.T) =

  let

    val cas = case cas of

          SOME t => SOME (Model_Pattern.adapt_term_to_type ctxt t)

        | NONE => NONE

    val where_ = map (Model_Pattern.adapt_term_to_type ctxt) where_

    val model = map (Model_Pattern.adapt_to_type ctxt) ppc

  in

    {guh = guh, mathauthors = mathauthors, init = init, thy = thy, cas = cas, met = met,

      prls = prls, where_ = where_, ppc = model}

    end

(** )

fun from_store id =

  (Store.get (get_pbls ()) id (rev id))

    handle ERROR _ =>

      raise error ("*** ERROR Problem.from_store " ^ strs2str id ^ " not found");

( **)

fun from_store ctxt id =

  let

    val pbl = Store.get (get_pbls ()) id (rev id)

  in adapt_to_type ctxt pbl end

    handle ERROR _ =>

      raise error ("*** ERROR Problem.from_store " ^ strs2str id ^ " not found");

(**)end(**)