symbolic-regression/Code/generate_claimed_results.py
Abdalaziz Rashid 28f3d5b140 Refactoring
2020-08-05 14:42:45 +03:00

115 lines
3.2 KiB
Python

import logging
import argparse
import pathlib
import os
from threading import active_count
from multiprocessing import Pool
from multiprocessing.pool import ThreadPool
from random import shuffle
from tabulate import tabulate
from pathlib import Path
from functools import partial
from S_run_aifeynman import run_aifeynman
_CFG = {
"dataset_path" : "../Feynman_without_units/",
"operations_file" : "./14ops.txt",
"polynomial_degree" : 3,
"number_of_epochs" : 500,
"bruteforce_time" : 60,
"test_percentage" : 0,
}
class RunAll:
"""
Run the solver on the whole dataset
"""
def __init__(self, *, cfg=_CFG):
logging.basicConfig(filename="output_no_units_parallel.log", level=logging.DEBUG)
self.cfg = cfg
self.results = {}
def print_results(self):
table = []
for file, sol in self.results.items():
table.append(sol[-1])
print(tabulate(
table,
headers=[
"Average error",
"Cumulative error",
"Error",
"Symbolic expression",
],
)
)
def run_solver(self, dirs=None):
if not dirs:
path = Path(self.cfg["dataset_path"])
dirs = list(path.iterdir())
shuffle(dirs) # Shuffle to sample a different file each time
else:
path=Path(self.cfg["dataset_path"])
child = dirs
# for child in dirs:
# print(child)
print(f"Process PID: {os.getpid()} ---------------- Number of threads: {active_count()}" )
self.results[str(child).split("/")[-1]] = run_aifeynman(
pathdir=str(path.resolve()) + "/",
filename=str(child).split("/")[-1],
BF_try_time=int(self.cfg["bruteforce_time"]),
BF_ops_file_type=Path(self.cfg["operations_file"]),
polyfit_deg=int(self.cfg["polynomial_degree"]),
NN_epochs=int(self.cfg["number_of_epochs"]),
vars_name=[],
test_percentage=int(self.cfg["test_percentage"]),
)
logging.info(self.results)
print("@"*120)
print("@"*120)
self.print_results()
def get_files(dirs, chunks=5):
dirs = list(path.iterdir())
dirs = [file for file in dirs if not (str(file).endswith("test") or str(file).endswith("train"))]
for i in range(0, len(dirs), chunks):
yield dirs[i : i + chunks]
if __name__ == "__main__":
#cfg_path = pathlib.Path("/home/aziz/lambda_lab/AI-Feynman/configs.cfg")
#if cfg_path.exists():
# RunAll(cfg_path=cfg_path)
#else:
# print(f"No such a file {cfg_path}")
solver = RunAll().run_solver
path = Path(_CFG["dataset_path"])
#dirs = list(path.iterdir())
#chunked_dirs = list(get_files(dirs, chunks=24))
# print(chunked_dirs[0], len(chunked_dirs[0]))
# for dd in chunked_dirs:
# pool = Pool(len(dd))
# print(dd, len(dd))
# pool.map(print, dd)
# pool.map(solver, dd)
# pool.close()
parser = argparse.ArgumentParser(description='Solver')
parser.add_argument('--file', help='Enter file path')
args = parser.parse_args()
solver(args.file)