Prevent np.asarray from destroying series indices

fixes has2k1/plotnine#210

doc/changelog.rst

@@ -1,6 +1,16 @@
 Changelog
 =========
 
+v0.5.2
+------
+*(2018-17-10)*
+
+Bug Fixes
+*********
+
+- Fixed issue where some functions that took pandas series
+  would return output where the index did not match that of the input.
+
 v0.5.1
 ------
 *(2018-15-10)*

mizani/bounds.py

@@ -107,7 +107,9 @@ def rescale_mid(x, to=(0, 1), _from=None, mid=0):
         array_like = False
         x = [x]
 
-    x = np.asarray(x)
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
+
     if _from is None:
         _from = np.array([np.min(x), np.max(x)])
     else:
@@ -174,7 +176,9 @@ def rescale_max(x, to=(0, 1), _from=None):
         array_like = False
         x = [x]
 
-    x = np.asarray(x)
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
+
     if _from is None:
         _from = np.array([np.min(x), np.max(x)])
 
@@ -210,7 +214,9 @@ def squish_infinite(x, range=(0, 1)):
     [0.0, -10.0, 0.5, 0.25, 9.0]
     """
     xtype = type(x)
-    x = np.asarray(x)
+
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
 
     x[x == -np.inf] = range[0]
     x[x == np.inf] = range[1]
@@ -247,7 +253,9 @@ def squish(x, range=(0, 1), only_finite=True):
     [0.0, 0.0, 0.2, 0.5, 0.8, 1.0, 1.0]
     """
     xtype = type(x)
-    x = np.asarray(x)
+
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
 
     finite = np.isfinite(x) if only_finite else True
 

mizani/tests/test_bounds.py

@@ -254,6 +254,11 @@ def test_rescale_max():
     # branches #
     assert rescale_max(2, _from=(0, 10)) == 0.2
 
+    # Maintains the same index
+    s = pd.Series([1, 2, 3], index=[3, 2, 1])
+    result = rescale_max(s)
+    assert s.index.equals(result.index)
+
 
 def test_rescale_mid():
     a = [1, 2, 3]
@@ -272,6 +277,11 @@ def test_rescale_mid():
         rescale_mid([2], _from=(2, 2), to=(2, 2), mid=2),
         [2])
 
+    # Maintains the same index
+    s = pd.Series([1, 2, 3], index=[3, 2, 1])
+    result = rescale_mid(s, mid=1)
+    assert s.index.equals(result.index)
+
 
 def test_squish_infinite():
     a = [-np.inf, np.inf, -np.inf, np.inf]
@@ -283,6 +293,11 @@ def test_squish_infinite():
     npt.assert_allclose(squish_infinite(b, (1, 10)),
                         [5, 1, 2, 3, 6])
 
+    # Maintains the same index
+    s = pd.Series([1, 2, 3, 4], index=[4, 3, 2, 1])
+    result = squish_infinite(s)
+    assert s.index.equals(result.index)
+
 
 def test_squish():
     a = [-np.inf, np.inf, -np.inf, np.inf]
@@ -300,6 +315,11 @@ def test_squish():
                         [5, 1, 2, 3, 6])
     npt.assert_allclose(squish(c, (1, 10)), c)
 
+    # Maintains the same index
+    s = pd.Series([.1, .2, .3, 9], index=[4, 3, 2, 1])
+    result = squish(s)
+    assert s.index.equals(result.index)
+
 
 def test_zero_range():
     c = np.array

mizani/tests/test_utils.py

@@ -17,6 +17,11 @@ def test_round_any():
     assert round_any(x, 5) == 5
     assert round_any(x, 1.5) == 4.5
 
+    # Maintains the same index
+    s = pd.Series([1.1, 2.2, 3.3], index=[3, 2, 1])
+    result = round_any(s, 2)
+    assert s.index.equals(result.index)
+
 
 def test_min_max():
     x = [1, 2, 3, 4, 5]

mizani/utils.py

@@ -44,7 +44,9 @@ def round_any(x, accuracy, f=np.round):
     """
     Round to multiple of any number.
     """
-    x = np.asarray(x)
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
+
     return f(x / accuracy) * accuracy
 
 
@@ -66,7 +68,9 @@ def min_max(x, na_rm=False, finite=True):
     out : tuple
         (minimum, maximum) of x
     """
-    x = np.asarray(x)
+    if not hasattr(x, 'dtype'):
+        x = np.asarray(x)
+
     if na_rm and finite:
         x = x[np.isfinite(x)]
     elif not na_rm and np.any(np.isnan(x)):