🔨 Remove usage of internal sklearn.utils api, replace with equivalent

sklift/utils/__init__.py

@@ -1,3 +1,3 @@
-from .utils import check_is_binary
+from .utils import check_is_binary, check_matplotlib_support
 
-__all__ = ['check_is_binary']
+__all__ = ['check_is_binary', 'check_matplotlib_support']

sklift/utils/utils.py

@@ -11,3 +11,20 @@ def check_is_binary(array):
         raise ValueError(f"Input array is not binary. "
                          f"Array should contain only int or float binary values 0 (or 0.) and 1 (or 1.). "
                          f"Got values {np.unique(array)}.")
+
+
+def check_matplotlib_support(caller_name):
+    """Raise ImportError with detailed error message if mpl is not installed.
+    Plot utilities like any of the Display's plotting functions should lazily import
+    matplotlib and call this helper before any computation.
+
+    Args:
+        caller_name (str): The name of the caller that requires matplotlib.
+    """
+    try:
+        import matplotlib  # noqa
+    except ImportError as e:
+        raise ImportError(
+            "{} requires matplotlib. You can install matplotlib with "
+            "`pip install matplotlib`".format(caller_name)
+        ) from e

sklift/viz/base.py

@@ -1,9 +1,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from sklearn.utils.validation import check_consistent_length
-from sklearn.utils import check_matplotlib_support
 
-from ..utils import check_is_binary
+from ..utils import check_is_binary, check_matplotlib_support
 from ..metrics import (
     uplift_curve, perfect_uplift_curve, uplift_auc_score,
     qini_curve, perfect_qini_curve, qini_auc_score,