Pamhyr2/src/Model/Results/Results.py

242 lines
7.0 KiB
Python

# Results.py -- Pamhyr
# Copyright (C) 2023-2025 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/>.
import struct
import logging
import itertools
import numpy as np
from copy import deepcopy
from datetime import datetime
from Model.Scenario import Scenario
from Model.Tools.PamhyrDB import SQLSubModel
from Model.Results.River.River import River
logger = logging.getLogger()
class Results(SQLSubModel):
_sub_classes = [River]
def __init__(self, id=-1, study=None, solver=None,
repertory="", name="0"):
super(Results, self).__init__(
id=id, status=study.status,
owner_scenario=study.status.scenario.id
)
self._name = name
self._study = study
self._river = River(self._study)
self._solver = solver
self._repertory = repertory
self._meta_data = {
# Keep results creation date
"creation_date": datetime.now(),
"study_revision": study.status.version,
}
if solver is not None:
self.set("solver_type", solver._type)
@property
def date(self):
date = self._meta_data["creation_date"]
return f"{date.isoformat(sep=' ')}"
@property
def river(self):
return self._river
@property
def study(self):
return self._study
def set(self, key, value):
self._meta_data[key] = value
@property
def is_valid(self):
return ("timestamps" in self._meta_data)
@property
def solver_name(self):
if self._solver is None:
return self._meta_data["solver_name"]
return self._solver.name
def get(self, key):
return self._meta_data[key]
def reload(self):
return self._solver.results(
self._study,
self._repertory,
qlog=None,
)
def timestamps_to_struct(self):
ts = self._meta_data["timestamps"]
sf = ">" + ''.join(itertools.repeat("d", len(ts)))
return struct.pack(sf, ts)
@classmethod
def _db_create(cls, execute, ext=""):
execute(f"""
CREATE TABLE results{ext} (
{cls.create_db_add_pamhyr_id()},
solver_name TEXT NOT NULL,
solver_type TEXT NOT NULL,
study_revision INTEGER NOT NULL,
creation_data DATE NOT NULL,
nb_timestamps INTEGER NOT NULL,
timestamps BLOB NOT NULL,
{Scenario.create_db_add_scenario()},
{Scenario.create_db_add_scenario_fk()},
PRIMARY KEY(pamhyr_id, scenario)
)
""")
if ext != "":
return True
return cls._create_submodel(execute)
@classmethod
def _db_update(cls, execute, version, data=None):
major, minor, release = version.strip().split(".")
create = False
if major == "0" and int(minor) < 2:
cls._db_create(execute)
create = True
if major == "0" and int(minor) == 2:
if int(release) < 1 and not create:
cls._db_create(execute)
create = True
return cls._update_submodel(execute, version, data)
@classmethod
def _db_load(cls, execute, data=None):
new = None
study = data['study']
status = data['status']
scenario = data["scenario"]
table = execute(
"SELECT pamhyr_id, solver_name, solver_type, " +
"study_revision, creation_data, nb_timestamps, timestamps, " +
"scenario " +
"FROM results " +
f"WHERE scenario = {scenario.id}"
)
if table is None:
yield
if len(table) > 1:
logger.warning("Multiple results for this scenario")
for v in table:
it = iter(v)
pid = next(it)
solver_name = next(it)
solver_type = next(it)
revision = next(it)
creation_date = next(it)
nb_timestamps = next(it)
timestamps_bytes = next(it)
owner_scenario = next(it)
new_results = cls(study=study)
new_results.set("solver_name", solver_name)
new_results.set("solver_type", solver_type)
new_results.set("study_revision", revision)
new_results.set("creation_date", creation_date)
sf = ">" + ''.join(itertools.repeat("d", nb_timestamps))
ts = struct.unpack(sf, timestamps_bytes)
new_results.set("timestamps", ts)
data["timestamps"] = sorted(ts)
new_results._river = River._db_load(execute, data)
yield (solver_type, new_results)
def _db_save_clear(self, execute, solver_type, data=None):
old_pid = execute(
"SELECT pamhyr_id FROM results " +
f"WHERE scenario = {self._owner_scenario} " +
f"AND solver_type = '{solver_type}'"
)
if len(old_pid) != 0:
for pid in old_pid:
pid = pid[0]
execute(
"DELETE FROM results " +
f"WHERE scenario = {self._owner_scenario} " +
f"AND solver_type = '{solver_type}'"
)
execute(
"DELETE FROM results_data " +
f"WHERE scenario = {self._owner_scenario} " +
f"AND result = {pid}"
)
def _db_save(self, execute, data=None):
if self._status.scenario.id != self._owner_scenario:
return
pid = self._pamhyr_id
if self._solver is None:
solver_name = self.get("solver_name")
solver_type = self.get("solver_type")
else:
solver_name = self._solver._name
solver_type = self._solver._type
self._db_save_clear(execute, solver_type, data=data)
ts = sorted(self.get("timestamps"))
sf = ">" + ''.join(itertools.repeat("d", len(ts)))
execute(
"INSERT INTO " +
"results (pamhyr_id, solver_name, solver_type, " +
"study_revision, creation_data, " +
"nb_timestamps, timestamps, " +
"scenario) VALUES (?, ?, ?, ?, ?, ?, ?, ?)",
self._pamhyr_id, solver_name, solver_type,
self._status.version, self.get("creation_date"),
len(ts), struct.pack(sf, *ts), self._owner_scenario
)
data["result"] = self._pamhyr_id
self._river._db_save(execute, data)
return True