def test_changed_only():
# Make sure the changed_only param is correctly used
set_config(print_changed_only=True)
lr = LogisticRegression(C=99)
expected = """LogisticRegression(C=99)"""
assert lr.__repr__() == expected
# Check with a repr that doesn't fit on a single line
lr = LogisticRegression(C=99, class_weight=.4, fit_intercept=False,
tol=1234, verbose=True)
expected = """
LogisticRegression(C=99, class_weight=0.4, fit_intercept=False, tol=1234,
verbose=True)"""
expected = expected[1:] # remove first \n
assert lr.__repr__() == expected
imputer = SimpleImputer(missing_values=0)
expected = """SimpleImputer(missing_values=0)"""
assert imputer.__repr__() == expected
# Defaults to np.NaN, trying with float('NaN')
imputer = SimpleImputer(missing_values=float('NaN'))
expected = """SimpleImputer()"""
assert imputer.__repr__() == expected
# make sure array parameters don't throw error (see #13583)
repr(LogisticRegressionCV(Cs=np.array([0.1, 1])))
set_config(print_changed_only=False)
def test_suppress_validation():
X = np.array([0, np.inf])
assert_raises(ValueError, assert_all_finite, X)
mrex.set_config(assume_finite=True)
assert_all_finite(X)
mrex.set_config(assume_finite=False)
assert_raises(ValueError, assert_all_finite, X)
def test_set_config():
assert get_config()['assume_finite'] is False
set_config(assume_finite=None)
assert get_config()['assume_finite'] is False
set_config(assume_finite=True)
assert get_config()['assume_finite'] is True
set_config(assume_finite=None)
assert get_config()['assume_finite'] is True
set_config(assume_finite=False)
assert get_config()['assume_finite'] is False
# No unknown arguments
assert_raises(TypeError, set_config, do_something_else=True)
def test_config_context():
assert get_config() == {'assume_finite': False, 'working_memory': 1024,
'print_changed_only': False}
# Not using as a context manager affects nothing
config_context(assume_finite=True)
assert get_config()['assume_finite'] is False
with config_context(assume_finite=True):
assert get_config() == {'assume_finite': True, 'working_memory': 1024,
'print_changed_only': False}
assert get_config()['assume_finite'] is False
with config_context(assume_finite=True):
with config_context(assume_finite=None):
assert get_config()['assume_finite'] is True
assert get_config()['assume_finite'] is True
with config_context(assume_finite=False):
assert get_config()['assume_finite'] is False
with config_context(assume_finite=None):
assert get_config()['assume_finite'] is False
# global setting will not be retained outside of context that
# did not modify this setting
set_config(assume_finite=True)
assert get_config()['assume_finite'] is True
assert get_config()['assume_finite'] is False
assert get_config()['assume_finite'] is True
assert get_config() == {'assume_finite': False, 'working_memory': 1024,
'print_changed_only': False}
# No positional arguments
assert_raises(TypeError, config_context, True)
# No unknown arguments
assert_raises(TypeError, config_context(do_something_else=True).__enter__)
def pytest_runtest_teardown(item, nextitem):
if isinstance(item, DoctestItem):
set_config(print_changed_only=False)
def pytest_runtest_setup(item):
if isinstance(item, DoctestItem):
set_config(print_changed_only=True)
"""
=================================
Compact estimator representations
=================================
This example illustrates the use of the print_changed_only global parameter.
Setting print_changed_only to True will alterate the representation of
estimators to only show the parameters that have been set to non-default
values. This can be used to have more compact representations.
"""
print(__doc__)
from mrex.linear_model import LogisticRegression
from mrex import set_config
lr = LogisticRegression(penalty='l1')
print('Default representation:')
print(lr)
# LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
# intercept_scaling=1, l1_ratio=None, max_iter=100,
# multi_class='auto', n_jobs=None, penalty='l1',
# random_state=None, solver='warn', tol=0.0001, verbose=0,
# warm_start=False)
set_config(print_changed_only=True)
print('\nWith changed_only option:')
print(lr)
# LogisticRegression(penalty='l1')
if os.path.exists(image):
c_thumb = os.path.join(image_dir, glr_plot[:-4] + '_carousel.png')
sphinx_gallery.gen_rst.scale_image(image, c_thumb, max_width, 190)
# Config for sphinx_issues
# we use the issues path for PRs since the issues URL will forward
issues_github_path = 'scikit-learn/scikit-learn'
def setup(app):
# to hide/show the prompt in code examples:
app.add_javascript('js/copybutton.js')
app.add_javascript('js/extra.js')
app.connect('build-finished', make_carousel_thumbs)
# The following is used by sphinx.ext.linkcode to provide links to github
linkcode_resolve = make_linkcode_resolve('mrex',
'https://github.com/scikit-learn/'
'scikit-learn/blob/{revision}/'
'{package}/{path}#L{lineno}')
warnings.filterwarnings("ignore", category=UserWarning,
message='Matplotlib is currently using agg, which is a'
' non-GUI backend, so cannot show the figure.')
# Reduces the output of estimators
mrex.set_config(print_changed_only=True)