def test_data_generate_categorical2(self):
X_train, X_test, y_train, y_test = \
generate_data_categorical(n_train=self.n_train,
n_test=self.n_test,
n_features=4,
contamination=self.contamination,
random_state=self.random_state)
assert_allclose(X_train.shape, (self.n_train, 4))
assert_allclose(X_test.shape, (self.n_test, 4))
def test_data_generate_categorical3(self):
X_train, y_train, X_test, y_test = \
generate_data_categorical(n_train=self.n_train,
n_test=self.n_test,
n_features=3,
contamination=self.contamination,
random_state=self.random_state)
X_train2, y_train2, X_test2, y_test2 = \
generate_data_categorical(n_train=self.n_train,
n_test=self.n_test,
n_features=3,
contamination=self.contamination,
random_state=self.random_state)
assert np.array_equal(X_train, X_train2)
assert np.array_equal(X_train, X_train2)
assert np.array_equal(X_test, X_test2)
assert np.array_equal(y_train, y_train2)
assert np.array_equal(y_test, y_test2)
def test_data_generate_categorical(self):
X_train, X_test, y_train, y_test = \
generate_data_categorical(n_train=self.n_train,
n_test=self.n_test,
n_features=2,
contamination=self.contamination,
random_state=self.random_state)
assert_equal(y_train.shape[0], X_train.shape[0])
assert_equal(y_test.shape[0], X_test.shape[0])
assert (self.n_train - X_train.shape[0] <= 1)
assert_equal(X_train.shape[1], 2)
assert (self.n_test - X_test.shape[0] <= 1)
assert_equal(X_test.shape[1], 2)
out_perc = (np.sum(y_train) + np.sum(y_test)) / (
self.n_train + self.n_test)
assert_allclose(self.contamination, out_perc, atol=0.01)
def test_data_generate_categorical5(self):
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=-1)
with assert_raises(ValueError):
generate_data_categorical(n_train=0, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=-1,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train='not int', n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test='not int',
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=0,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features='not int',
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=-1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative='not int', n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination=0.6,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=3,
n_informative=1, n_features=1,
contamination='not float',
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=-1, n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in='not int',
n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=self.n_train + self.n_test + 1,
n_category_out=3,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5, n_category_out=-1,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5,
n_category_out='not int',
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5,
n_category_out=self.n_train + self.n_test + 1,
n_informative=1, n_features=1,
contamination=self.contamination,
random_state=self.random_state)
with assert_raises(ValueError):
generate_data_categorical(n_train=self.n_train, n_test=self.n_test,
n_category_in=5,
n_category_out=5,
n_informative=2, n_features=2,
contamination=self.contamination,
shuffle='not bool',
random_state=self.random_state)
