Spaces:
Sleeping
Sleeping
File size: 2,165 Bytes
745ec89 b007552 2b58e9e b007552 745ec89 2b58e9e 745ec89 6ab7b97 745ec89 6ab7b97 745ec89 cfec30d 2b58e9e 745ec89 6ab7b97 745ec89 19997c8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import os
import pandas as pd
import traceback as tb
import numpy as np
from argparse import ArgumentParser
# Args:
# niterations
# binary_operators
# unary_operators
# col_to_fit
empty_df = pd.DataFrame(
{
"equation": [],
"loss": [],
"complexity": [],
}
)
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument("--niterations", type=int)
parser.add_argument("--maxsize", type=int)
parser.add_argument("--binary_operators", type=str)
parser.add_argument("--unary_operators", type=str)
parser.add_argument("--col_to_fit", type=str)
parser.add_argument("--filename", type=str)
args = parser.parse_args()
niterations = args.niterations
binary_operators = eval(args.binary_operators)
unary_operators = eval(args.unary_operators)
col_to_fit = args.col_to_fit
filename = args.filename
maxsize = args.maxsize
os.environ["PATH"] += ":/home/user/.local/bin/"
try:
import pysr
from julia.api import JuliaInfo
info = JuliaInfo.load(julia="/home/user/.local/bin/julia")
from julia import Main as _Main
pysr.sr.Main = _Main
from pysr import PySRRegressor
df = pd.read_csv(filename)
y = np.array(df[col_to_fit])
X = df.drop([col_to_fit], axis=1)
model = PySRRegressor(
update=False,
progress=False,
maxsize=maxsize,
niterations=niterations,
binary_operators=binary_operators,
unary_operators=unary_operators,
)
model.fit(X, y)
df = model.equations_[["equation", "loss", "complexity"]]
# Convert all columns to string type:
df = df.astype(str)
error_message = (
"Success!\n"
f"You may run the model locally (faster) with "
f"the following parameters:\n" + str(model.get_params())
)
except Exception as e:
error_message = tb.format_exc()
# Dump to file:
df = empty_df
df.to_csv("pysr_output.csv", index=False)
with open("error.log", "w") as f:
f.write(error_message)
|