Spaces:
Running
Running
File size: 1,500 Bytes
2f38c9c 41e5fd5 9bfcbfa 41e5fd5 2f38c9c 51a6b05 2f38c9c 9bfcbfa b07eb2d 9bfcbfa a6b7d35 9bfcbfa a6b7d35 9bfcbfa b07eb2d 9bfcbfa 51a6b05 9bfcbfa |
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 |
import unittest
import numpy as np
from pysr import sympy2jax, get_hof
import pandas as pd
from jax import numpy as jnp
from jax import random
from jax import grad
import sympy
class TestJAX(unittest.TestCase):
def setUp(self):
np.random.seed(0)
def test_sympy2jax(self):
x, y, z = sympy.symbols('x y z')
cosx = 1.0 * sympy.cos(x) + y
key = random.PRNGKey(0)
X = random.normal(key, (1000, 2))
true = 1.0 * jnp.cos(X[:, 0]) + X[:, 1]
f, params = sympy2jax(cosx, [x, y, z])
self.assertTrue(jnp.all(jnp.isclose(f(X, params), true)).item())
def test_pipeline(self):
X = np.random.randn(100, 10)
equations = pd.DataFrame({
'Equation': ['1.0', 'cos(x0)', 'square(cos(x0))'],
'MSE': [1.0, 0.1, 1e-5],
'Complexity': [1, 2, 3]
})
equations['Complexity MSE Equation'.split(' ')].to_csv(
'equation_file.csv.bkup', sep='|')
equations = get_hof(
'equation_file.csv', n_features=2, variables_names='x1 x2 x3'.split(' '),
extra_sympy_mappings={}, output_jax_format=True,
multioutput=False, nout=1, selection=[1, 2, 3])
jformat = equations.iloc[-1].jax_format
np.testing.assert_almost_equal(
np.array(jformat['callable'](jnp.array(X), jformat['parameters'])),
np.square(np.cos(X[:, 1])), # Select feature 1
decimal=4
)
|