import numpy as np
from pysr import pysr, best

# Dataset
X = 2 * np.random.randn(100, 5)
y = 2 * np.cos(X[:, 3]) + X[:, 0] ** 2 - 2

# Learn equations
equations = pysr(
    X,
    y,
    niterations=5,
    binary_operators=["plus", "mult"],
    unary_operators=[
        "cos",
        "exp",
        "sin",  # Pre-defined library of operators (see https://pysr.readthedocs.io/en/latest/docs/operators/)
        "inv(x) = 1/x",
    ],
    loss="loss(x, y) = abs(x - y)",  # Custom loss function
    julia_project="../SymbolicRegression.jl",
)  # Define your own operator! (Julia syntax)

...  # (you can use ctl-c to exit early)

print(best(equations))