>> updated median[_by]() and var[_by]()

Author: alixdamman

larray/core/array.py

@@ -4686,7 +4686,7 @@ def mean_by(self, *args, **kwargs):
 
     @_decorate_agg_method(np.median, np.nanmedian, commutative=True)
     def median(self, *args, **kwargs):
-        """{signature}
+        r"""{signature}
 
         Computes the arithmetic median.
 
@@ -4705,12 +4705,12 @@ def median(self, *args, **kwargs):
         Examples
         --------
         >>> arr = ndtest((4, 4))
-        >>> arr[:,:] = [[10, 7, 5, 9], \
-                        [5, 8, 3, 7], \
-                        [6, 2, 0, 9], \
-                        [9, 10, 5, 6]]
+        >>> arr[:,:] = [[10, 7, 5, 9],
+        ...             [5, 8, 3, 7],
+        ...             [6, 2, 0, 9],
+        ...             [9, 10, 5, 6]]
         >>> arr
-        a\\b  b0  b1  b2  b3
+        a\b  b0  b1  b2  b3
          a0  10   7   5   9
          a1   5   8   3   7
          a2   6   2   0   9
@@ -4737,7 +4737,7 @@ def median(self, *args, **kwargs):
         Split an axis in several parts
 
         >>> arr.median((['a0', 'a1'], ['a2', 'a3']))
-          a\\b   b0   b1   b2   b3
+          a\b   b0   b1   b2   b3
         a0,a1  7.5  7.5  4.0  8.0
         a2,a3  7.5  6.0  2.5  7.5
         >>> # or equivalently
@@ -4746,7 +4746,7 @@ def median(self, *args, **kwargs):
         Same with renaming
 
         >>> arr.median((X.a['a0', 'a1'] >> 'a01', X.a['a2', 'a3'] >> 'a23'))
-        a\\b   b0   b1   b2   b3
+        a\b   b0   b1   b2   b3
         a01  7.5  7.5  4.0  8.0
         a23  7.5  6.0  2.5  7.5
         >>> # or equivalently
@@ -4756,7 +4756,7 @@ def median(self, *args, **kwargs):
 
     @_decorate_agg_method(np.median, np.nanmedian, commutative=True, by_agg=True, long_name="mediane")
     def median_by(self, *args, **kwargs):
-        """{signature}
+        r"""{signature}
 
         Computes the arithmetic median.
 
@@ -4775,12 +4775,12 @@ def median_by(self, *args, **kwargs):
         Examples
         --------
         >>> arr = ndtest((4, 4))
-        >>> arr[:,:] = [[10, 7, 5, 9], \
-                        [5, 8, 3, 7], \
-                        [6, 2, 0, 9], \
-                        [9, 10, 5, 6]]
+        >>> arr[:,:] = [[10, 7, 5, 9],
+        ...             [5, 8, 3, 7],
+        ...             [6, 2, 0, 9],
+        ...             [9, 10, 5, 6]]
         >>> arr
-        a\\b  b0  b1  b2  b3
+        a\b  b0  b1  b2  b3
          a0  10   7   5   9
          a1   5   8   3   7
          a2   6   2   0   9
@@ -5066,7 +5066,7 @@ def ptp(self, *args, **kwargs):
 
     @_decorate_agg_method(np.var, np.nanvar, extra_kwargs=['dtype', 'ddof'], long_name="variance")
     def var(self, *args, **kwargs):
-        """{signature}
+        r"""{signature}
 
         Computes the unbiased variance.
 
@@ -5087,10 +5087,10 @@ def var(self, *args, **kwargs):
         Examples
         --------
         >>> arr = ndtest((2, 8), dtype=float)
-        >>> arr[:,:] = [[0, 3, 5, 6, 4, 2, 1, 3], \
-                        [7, 3, 2, 5, 8, 5, 6, 4]]
+        >>> arr[:,:] = [[0, 3, 5, 6, 4, 2, 1, 3],
+        ...             [7, 3, 2, 5, 8, 5, 6, 4]]
         >>> arr
-        a\\b   b0   b1   b2   b3   b4   b5   b6   b7
+        a\b   b0   b1   b2   b3   b4   b5   b6   b7
          a0  0.0  3.0  5.0  6.0  4.0  2.0  1.0  3.0
          a1  7.0  3.0  2.0  5.0  8.0  5.0  6.0  4.0
         >>> arr.var()
@@ -5111,7 +5111,7 @@ def var(self, *args, **kwargs):
         Split an axis in several parts
 
         >>> arr.var((['b0', 'b1', 'b3'], 'b5:'))
-        a\\b  b0,b1,b3  b5:
+        a\b  b0,b1,b3  b5:
          a0       9.0  1.0
          a1       4.0  1.0
         >>> # or equivalently
@@ -5120,7 +5120,7 @@ def var(self, *args, **kwargs):
         Same with renaming
 
         >>> arr.var((X.b['b0', 'b1', 'b3'] >> 'b013', X.b['b5:'] >> 'b567'))
-        a\\b  b013  b567
+        a\b  b013  b567
          a0   9.0   1.0
          a1   4.0   1.0
         >>> # or equivalently
@@ -5130,7 +5130,7 @@ def var(self, *args, **kwargs):
 
     @_decorate_agg_method(np.var, np.nanvar, by_agg=True, extra_kwargs=['dtype', 'ddof'], long_name="variance")
     def var_by(self, *args, **kwargs):
-        """{signature}
+        r"""{signature}
 
         Computes the unbiased variance.
 
@@ -5151,10 +5151,10 @@ def var_by(self, *args, **kwargs):
         Examples
         --------
         >>> arr = ndtest((2, 8), dtype=float)
-        >>> arr[:,:] = [[0, 3, 5, 6, 4, 2, 1, 3], \
-                        [7, 3, 2, 5, 8, 5, 6, 4]]
+        >>> arr[:,:] = [[0, 3, 5, 6, 4, 2, 1, 3],
+        ...             [7, 3, 2, 5, 8, 5, 6, 4]]
         >>> arr
-        a\\b   b0   b1   b2   b3   b4   b5   b6   b7
+        a\b   b0   b1   b2   b3   b4   b5   b6   b7
          a0  0.0  3.0  5.0  6.0  4.0  2.0  1.0  3.0
          a1  7.0  3.0  2.0  5.0  8.0  5.0  6.0  4.0
         >>> arr.var_by()
@@ -5175,7 +5175,7 @@ def var_by(self, *args, **kwargs):
         Split an axis in several parts
 
         >>> arr.var_by('a', (['b0', 'b1', 'b3'], 'b5:'))
-        a\\b  b0,b1,b3  b5:
+        a\b  b0,b1,b3  b5:
          a0       9.0  1.0
          a1       4.0  1.0
         >>> # or equivalently
@@ -5184,7 +5184,7 @@ def var_by(self, *args, **kwargs):
         Same with renaming
 
         >>> arr.var_by('a', (X.b['b0', 'b1', 'b3'] >> 'b013', X.b['b5:'] >> 'b567'))
-        a\\b  b013  b567
+        a\b  b013  b567
          a0   9.0   1.0
          a1   4.0   1.0
         >>> # or equivalently