Files
Pamhyr2/src/Model/Ensembles/Ensemble.py
T

280 lines
7.9 KiB
Python

# Ensemble.py -- Pamhyr
# Copyright (C) 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 Model.Tools.PamhyrDB import SQLSubModel
from Model.Scenario import Scenario
from Model.Ensembles.Distribution import Uniform
logger = logging.getLogger()
class Ensemble(SQLSubModel):
_sub_classes = []
def __init__(self, id: int = -1, name: str = "",
distribution=None, params=[0., 100.],
data_type=None, target_data=None,
status=None, owner_scenario=-1):
super(Ensemble, self).__init__(
id=id, status=status,
owner_scenario=owner_scenario
)
self._name = name
self._data_type = data_type
self._distribution = distribution
self._params = params
self._target_data = target_data
@classmethod
def _db_create(cls, execute, ext=""):
execute(f"""
CREATE TABLE ensemble{ext} (
{cls.create_db_add_pamhyr_id()},
deleted BOOLEAN NOT NULL DEFAULT FALSE,
name TEXT NOT NULL,
type VARCHAR(8) NOT NULL,
distribution INTEGER NOT NULL,
distribution_name VARCHAR(32) NOT NULL,
params BLOB NOT NULL,
params_len INTEGER NOT NULL,
data_pid INTEGER NOT NULL,
{Scenario.create_db_add_scenario()},
{Scenario.create_db_add_scenario_fk()},
PRIMARY KEY(pamhyr_id, scenario)
)
""")
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"]
distributions = data["ens_distributions"]
stricklers = data["stricklers"]
loaded = data['loaded_pid']
table = execute(
"SELECT pamhyr_id, deleted, name, type, " +
"distribution, distribution_name, params, params_len, data_pid, " +
"scenario " +
"FROM ensemble " +
f"WHERE scenario = {scenario.id} " +
f"AND 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)
data_type = next(it)
fid = next(it)
fname = next(it)
params = next(it)
params_len = next(it)
data_pid = next(it)
owner_scenario = next(it)
def fn(f): return f._name == fname
if fid != -1:
def fn(f): return f._pamhyr_id == fid
distribution = next(
filter(fn, distributions.lst),
None
)
target_data = next(
filter(
lambda s: s._pamhyr_id == data_pid,
stricklers.lst
),
None
)
rdata = list(cls._decode_params(params, params_len))
new_ensemble = cls(
id, name=name,
distribution=distribution,
params=rdata,
data_type=data_type,
target_data=target_data,
status=data["status"],
owner_scenario=owner_scenario
)
if deleted:
new_ensemble.set_as_deleted()
loaded.add(id)
new.append(new_ensemble)
return new
def _db_save(self, execute, data=None):
if not self.must_be_saved():
return True
execute(
"DELETE FROM ensemble " +
f"WHERE pamhyr_id = {self.pamhyr_id} " +
f"AND scenario = {self._status.scenario_id}"
)
bparams, length = self._encode_params()
if self._distribution is None:
fid = -1
fname = "NULL"
else:
fid = self._distribution._pamhyr_id
fname = self._distribution._name
if self._distribution._type == "generic":
fid = -1
data_pid = -1
if self._target_data is not None:
data_pid = self._target_data._pamhyr_id
execute(
"INSERT INTO " +
"ensemble(pamhyr_id, deleted, name, type, " +
" distribution, distribution_name, params, params_len, " +
" data_pid, scenario) " +
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
self.pamhyr_id, self.is_deleted(),
self._name, self._data_type,
fid, fname, bparams, length,
data_pid, self._status.scenario_id
)
return True
def _encode_params(self):
length = len(self._params)
data_format = ">" + ''.join(itertools.repeat("d", length))
return struct.pack(data_format, *self._params), length
@classmethod
def _decode_params(cls, bparams, length):
data_format = ">" + ''.join(itertools.repeat("d", length))
return struct.unpack(data_format, bparams)
def random(self, nb):
return np.nditer(
self._distribution.random(
self._params, nb
)
)
@property
def name(self):
return self._name
@name.setter
def name(self, name):
self._name = name
self._status.modified()
@property
def distribution(self):
return self._distribution
@distribution.setter
def distribution(self, distribution):
self._distribution = distribution
self._status.modified()
@property
def params(self):
return self._params
@params.setter
def params(self, params):
self._params = params
self._status.modified()
@property
def data_type(self):
return self._data_type
@data_type.setter
def data_type(self, data_type):
self._data_type = data_type
self._status.modified()
@property
def target_data(self):
return self._target_data
@target_data.setter
def target_data(self, target_data):
self._target_data = target_data
self._status.modified()
def get_data_dict(self, use_ids=False):
target_data = self.target_data
distribution = self.distribution
if use_ids:
if self.target_data:
target_data = self.target_data.pamhyr_id
if self.distribution:
distribution = self.distribution.name
return {
"name": self.name,
"data_type": self.data_type,
"target_data": target_data,
"distribution": distribution,
"params": self.params,
}
def set_data_dict(self, data):
self.name = data["name"]
self.data_type = data["data_type"]
self.target_data = data["target_data"]
self.distribution = data["distribution"]
self.params = data["params"]