mirror of https://github.com/pyodide/pyodide.git
51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
import pytest
|
|
from pytest_pyodide.fixture import selenium_context_manager
|
|
|
|
|
|
@pytest.mark.driver_timeout(40)
|
|
@pytest.mark.xfail_browsers(
|
|
chrome="Times out in chrome", firefox="Times out in firefox"
|
|
)
|
|
def test_scikit_learn(selenium_module_scope):
|
|
with selenium_context_manager(selenium_module_scope) as selenium:
|
|
selenium.load_package("scikit-learn")
|
|
assert (
|
|
selenium.run(
|
|
"""
|
|
import numpy as np
|
|
import sklearn
|
|
from sklearn.linear_model import LogisticRegression
|
|
|
|
rng = np.random.RandomState(42)
|
|
X = rng.rand(100, 20)
|
|
y = rng.randint(5, size=100)
|
|
|
|
estimator = LogisticRegression(solver='liblinear')
|
|
estimator.fit(X, y)
|
|
print(estimator.predict(X))
|
|
estimator.score(X, y)
|
|
"""
|
|
)
|
|
> 0
|
|
)
|
|
|
|
|
|
@pytest.mark.driver_timeout(40)
|
|
@pytest.mark.xfail_browsers(
|
|
chrome="Times out in chrome", firefox="Times out in firefox"
|
|
)
|
|
def test_logistic_regression(selenium_module_scope):
|
|
with selenium_context_manager(selenium_module_scope) as selenium:
|
|
selenium.load_package("scikit-learn")
|
|
selenium.run(
|
|
"""
|
|
from sklearn.datasets import load_iris
|
|
from sklearn.linear_model import LogisticRegression
|
|
X, y = load_iris(return_X_y=True)
|
|
clf = LogisticRegression(random_state=0).fit(X, y)
|
|
print(clf.predict(X[:2, :]))
|
|
print(clf.predict_proba(X[:2, :]))
|
|
print(clf.score(X, y))
|
|
"""
|
|
)
|