alias

skcriteria/tests/test_validate.py

@@ -74,20 +74,32 @@ def test_from_list(self):
         self.assertAllClose(arr, arr_result)
         self.assertIsInstance(arr_result, np.ndarray)
 
-    def test_from_array(self):
-        arr = np.array(
-            [random.choice(self.min_max) for _ in self.rrange(100, 1000)])
-        arr_result = criteriarr(arr)
-        self.assertAllClose(arr, arr_result)
-        self.assertIsInstance(arr_result, np.ndarray)
-        self.assertIs(arr, arr_result)
-
     def test_no_min_max(self):
         arr = [
             random.choice(self.min_max) for _ in self.rrange(100, 1000)] + [2]
         with self.assertRaises(ValueError):
             criteriarr(arr)
 
+    def test_alias(self):
+        original = np.array([-1, 1])
+        criterias = (
+            [min, max],
+            [np.min, np.max],
+            [np.amin, np.amax],
+            [np.nanmin, np.nanmax],
+            ["minimize", "maximize"],
+            ["min", "max"])
+        for arr in criterias:
+            parsed = criteriarr(arr)
+            self.assertArrayEqual(parsed, original)
+            with self.assertRaises(ValueError):
+                criteriarr(arr + [2])
+            with self.assertRaises(ValueError):
+                criteriarr(arr + [range])
+            with self.assertRaises(ValueError):
+                criteriarr(arr + ["foo"])
+
+
 
 class IsMtx(SKCriteriaTestCase):
 

skcriteria/validate.py

@@ -57,6 +57,8 @@
 # IMPORTS
 # =============================================================================
 
+import itertools as it
+
 import numpy as np
 
 
@@ -67,9 +69,16 @@
 MIN = -1
 """Int: Minimization criteria"""
 
+MIN_ALIASES = [MIN, min, np.min, np.nanmin, np.amin, "min", "minimize"]
+"""Another ways to name the minimization criterias."""
+
 MAX = 1
 """Int: Maximization criteria"""
 
+MAX_ALIASES = [MAX, max, np.max, np.nanmax, np.amax, "max", "maximize"]
+"""Another way to name the maximization criterias."""
+
+
 CRITERIA_STR = {
     MIN: "min",
     MAX: "max"
@@ -82,6 +91,9 @@
 }
 
 
+ALIASES = dict(it.chain(dict.fromkeys(MIN_ALIASES, MIN).items(),
+                        dict.fromkeys(MAX_ALIASES, MAX).items()))
+
 # =============================================================================
 # EXCEPTIONS
 # =============================================================================
@@ -122,8 +134,9 @@ def is_mtx(mtx, size=None):
 
 
 def criteriarr(criteria):
-    """Validate if the iterable only contains MIN (-1) and MAX (1) values. And
-    also always returns an ndarray representation of the iterable.
+    """Validate if the iterable only contains MIN (or any alias) and MAX
+    (or any alias) values. And also always returns an ndarray representation
+    of the iterable.
 
     Parameters
     ----------
@@ -145,9 +158,9 @@ def criteriarr(criteria):
 
     """
 
-    criteria = np.asarray(criteria)
-    if np.setdiff1d(criteria, [MIN, MAX]):
-        msg = "Criteria Array only accept '{}' or '{}' Values. Found {}"
+    criteria = np.array([ALIASES.get(c, c) for c in criteria])
+    if np.setdiff1d(criteria, [MIN, MAX]).size > 0:
+        msg = "Criteria Array only accept minimize or maximize Values. Found {}"
         raise DataValidationError(msg.format(MAX, MIN, criteria))
     return criteria