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| import streamlit as st | |
| import os | |
| # Need to install PySR in separate python instance: | |
| os.system( | |
| """ | |
| if [ ! -d "$HOME/.julia/environments/pysr-0.9.1" ]; then | |
| python -c 'import pysr; pysr.install()' | |
| fi | |
| """ | |
| ) | |
| import pysr | |
| from pysr import PySRRegressor | |
| import numpy as np | |
| import pandas as pd | |
| st.title("Interactive PySR") | |
| file_name = st.file_uploader( | |
| "Upload a data file, with your output column labeled 'y'", type=["csv"] | |
| ) | |
| if file_name is not None: | |
| col1, col2 = st.columns(2) | |
| df = pd.read_csv(file_name) | |
| y = np.array(df["y"]) | |
| X = df.drop(["y"], axis=1) | |
| model = PySRRegressor(update=False) | |
| model.fit(X, y) | |
| col1.header("Equation") | |
| col2.header("Loss") | |
| for i, row in model.equations_.iterrows(): | |
| col1.subheader(str(row["equation"])) | |
| col2.subheader(str(row["loss"])) | |
| model = None | |
| Main = None | |
| pysr.sr.Main = None | |
| pysr.sr.already_ran = False | |