scikit-learn
diff --git a/‎sklearn/preprocessing/_data.py
Copy file name to clipboardExpand all lines: sklearn/preprocessing/_data.py
+9-26Lines changed: 9 additions & 26 deletions b/‎sklearn/preprocessing/_data.py
Copy file name to clipboardExpand all lines: sklearn/preprocessing/_data.py
+9-26Lines changed: 9 additions & 26 deletions
@@ -25,7 +25,7 @@
 from ..utils import assert_all_finite, check_array
 from ..utils.extmath import row_norms
 from ..utils.extmath import _incremental_mean_and_var
-from ..utils.fixes import np_version, parse_version
+from ..utils.fixes import linspace
 from ..utils.sparsefuncs_fast import (inplace_csr_row_normalize_l1,
                                       inplace_csr_row_normalize_l2)
 from ..utils.sparsefuncs import (inplace_column_scale,
@@ -1916,19 +1916,8 @@ def get_base_knot_positions(X, n_knots=10, knots='uniform'):
             # knots == 'uniform':
             x_min = np.amin(X, axis=0)
             x_max = np.amax(X, axis=0)
-
-            # FIXME: to be removed if min version becomes numpy 1.16
-            # start and stop arrays for linspace logspace and geomspace
-            # https://github.com/numpy/numpy/pull/12388
-            if np_version < parse_version('1.16'):
-                n_features = X.shape[1]
-                knots = np.empty((n_knots, n_features))
-                for j in range(n_features):
-                    knots[:, j] = np.linspace(start=x_min[j], stop=x_max[j],
-                                              num=n_knots, endpoint=True)
-            else:
-                knots = np.linspace(start=x_min, stop=x_max, num=n_knots,
-                                    endpoint=True)
+            knots = linspace(start=x_min, stop=x_max, num=n_knots,
+                             endpoint=True)
 
         return knots
 
@@ -2023,18 +2012,12 @@ def fit(self, X, y=None):
         # Instead, we reuse the distance of the 2 fist/last knots.
         dist_min = base_knots[1] - base_knots[0]
         dist_max = base_knots[-1] - base_knots[-2]
-        # FIXME: to be removed if min version becomes numpy 1.16
-        # start and stop arrays for linspace logspace and geomspace
-        # https://github.com/numpy/numpy/pull/12388
-        if np_version < parse_version('1.16'):
-
-        else:
-            knots = np.r_[np.linspace(base_knots[0] - degree * dist_min,
-                                      base_knots[0] - dist_min, num=degree),
-                          base_knots,
-                          np.linspace(base_knots[-1] + dist_max,
-                                      base_knots[-1] + degree * dist_max,
-                                      num=degree)]
+        knots = np.r_[linspace(base_knots[0] - degree * dist_min,
+                               base_knots[0] - dist_min, num=degree),
+                      base_knots,
+                      np.linspace(base_knots[-1] + dist_max,
+                                  base_knots[-1] + degree * dist_max,
+                                  num=degree)]
 
         # With a diagonal coefficient matrix, we get back the spline basis
         # elements, i.e. the design matrix of the spline.