fix test failures by removing sample size scaling in testing file

tests/test_transforms.py

@@ -30,30 +30,30 @@
 def test_method_name_valid(transform):
     """Raise ValueError for invalue `method`."""
     with pytest.raises(ValueError):
-        transform_univariate(VALS, VALS, N, transform, method="dummy")
+        transform_univariate(VALS, VALS, transform, method="dummy")
 
 
 @pytest.mark.parametrize("transform", UNIVARIATE_TRANSFORM_LIST)
 def test_input_len_match(transform):
     """Raise ValueError if lengths of input vectors don't match."""
     with pytest.raises(ValueError):
-        transform_univariate(VALS, VALS * 2, N, transform)
+        transform_univariate(VALS, VALS * 2, transform)
 
 
 @pytest.mark.parametrize("transform", UNIVARIATE_TRANSFORM_LIST)
 def test_sigma_negative(transform):
     """Raise ValueError if `sigma` contains negative values."""
     vals = VALS + [-0.1]
     with pytest.raises(ValueError):
-        transform_univariate(vals, vals, N, transform)
+        transform_univariate(vals, vals, transform)
 
 
 @pytest.mark.parametrize("transform", UNIVARIATE_TRANSFORM_LIST)
 def test_sigma_zero(transform):
     """Display warning if `sigma` contains zeros."""
     vals = VALS + [0.0]
     with pytest.warns(UserWarning):
-        transform_univariate(vals, vals, N, transform)
+        transform_univariate(vals, vals, transform)
 
 
 def test_transform_name_valid():
@@ -66,15 +66,15 @@ def test_transform_name_valid():
 @pytest.mark.parametrize("transform", UNIVARIATE_TRANSFORM_LIST)
 def test_output_type(transform):
     """Output should be numpy arrays."""
-    mu, sigma = transform_univariate(VALS, VALS, N, transform)
+    mu, sigma = transform_univariate(VALS, VALS, transform)
     assert isinstance(mu, np.ndarray)
     assert isinstance(sigma, np.ndarray)
 
 
 @pytest.mark.parametrize("transform", UNIVARIATE_TRANSFORM_LIST)
 def test_outout_len_match(transform):
     """Length of output vectors should match."""
-    mu, sigma = transform_univariate(VALS, VALS, N, transform)
+    mu, sigma = transform_univariate(VALS, VALS, transform)
     assert len(mu) == len(sigma)
 
 
@@ -84,8 +84,8 @@ def test_delta_result(transform):
     mu = np.random.uniform(0.1, 1.0, size=10)
     sigma = np.random.uniform(0.1, 1.0, size=10)
     mu_ref = UNIVARIATE_TRANSFORM_DICT[transform][0](mu)
-    sigma_ref = sigma * UNIVARIATE_TRANSFORM_DICT[transform][1](mu) / np.sqrt(N)
-    mu_trans, sigma_trans = transform_univariate(mu, sigma, N, transform)
+    sigma_ref = sigma * UNIVARIATE_TRANSFORM_DICT[transform][1](mu)
+    mu_trans, sigma_trans = transform_univariate(mu, sigma, transform)
     assert np.allclose(mu_trans, mu_ref)
     assert np.allclose(sigma_trans, sigma_ref)