# Function.py -- Pamhyr
# Copyright (C) 2023-2026  INRAE
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.

# -*- coding: utf-8 -*-

import struct
import logging
import itertools
import numpy as np

from tools import logger_exception

from Model.Except import NotImplementedMethodeError
from Model.Tools.PamhyrDB import SQLSubModel
from Model.Scenario import Scenario

logger = logging.getLogger()


class Function(SQLSubModel):
    _sub_classes = []

    def __init__(self, id: int = -1,
                 name: str = "", script: str = "",
                 status=None):
        super(Function, self).__init__(
            id=id, status=status,
            owner_scenario=0
        )

        self._name = name
        self._type = "generic"
        self._script = script

    @classmethod
    def _db_create(cls, execute, ext=""):
        execute(f"""
          CREATE TABLE ensemble_function{ext} (
            {cls.create_db_add_pamhyr_id()},
            deleted BOOLEAN NOT NULL DEFAULT FALSE,
            name TEXT NOT NULL,
            script TEXT NOT NULL,
            PRIMARY KEY(pamhyr_id)
          )
        """)

        if ext == "_tmp":
            return True

        return cls._create_submodel(execute)

    @classmethod
    def _db_update(cls, execute, version, data=None):
        major, minor, release = version.strip().split(".")
        if major == "0" and int(minor) < 2:
            cls._db_create(execute)
        elif major == "0" and int(minor) == 2:
            if int(release) < 8:
                cls._db_create(execute)

        return cls._update_submodel(execute, version, data)

    @classmethod
    def _db_load(cls, execute, data=None):
        new = []
        scenario = data["scenario"]
        loaded = data['loaded_pid']

        table = execute(
            "SELECT pamhyr_id, deleted, name, script " +
            "FROM ensemble_function " +
            f"WHERE pamhyr_id NOT IN ({', '.join(map(str, loaded))})"
        )

        for row in table:
            it = iter(row)

            id = next(it)
            deleted = (next(it) == 1)
            name = next(it)
            script = next(it)

            new_function = cls(
                id, name=name, script=script,
                status=data["status"]
            )
            if deleted:
                new_function.set_as_deleted()

            loaded.add(id)
            new.append(new_function)

        return new

    def _db_save(self, execute, data=None):
        # Only save custom function
        if self._type != "custom":
            return True

        if not self.must_be_saved():
            return True

        execute(
            "INSERT INTO " +
            "ensemble_function(pamhyr_id, deleted, " +
            "  name, script) " +
            "VALUES (?, ?, ?, ?)",
            self.pamhyr_id, self.is_deleted(),
            self._name, self._script
        )

        return True

    def _data_traversal(self,
                        predicate=lambda obj, data: True,
                        modifier=lambda obj, data: None,
                        data={}):
        if predicate(self, data):
            modifier(self, data)

    def get_sample(self, r):
        raise NotImplementedMethodeError(cls, cls._load)


###########################
# FUNCTION IMPLEMENTATION #
###########################

class Uniform(Function):
    _sub_classes = []

    def __init__(self, id: int = -1,
                 name: str = "uniform", script: str = "",
                 status=None):
        super(Uniform, self).__init__(
            id=id, status=status,
            name=name, script=script
        )

    def get_sample(self, ens_range, nb):
        b = ens_range[0]
        t = ens_range[1]

        step = (t - b) / nb

        return np.arange(b, t, step)


class Custom(Function):
    _sub_classes = []

    def __init__(self, id: int = -1,
                 name: str = "", script: str = "",
                 status=None):
        super(Custom, self).__init__(
            id=id, status=status,
            name=name, script=script
        )

        self._type = "custom"

    def get_sample(self, ens_range, nb):
        try:
            # Run script to (re)define the sample function
            f = eval(self._script)
            return f(ens_range, nb)
        except Exception as e:
            logger_exception(e)
            return None         # TODO: Raise helpful exception