added returned type for all aggregation functions and methods (issue larray-project#864)

Author: alixdamman

larray/core/array.py

@@ -63,7 +63,7 @@
 from larray.util.options import _OPTIONS, DISPLAY_MAXLINES, DISPLAY_EDGEITEMS, DISPLAY_WIDTH, DISPLAY_PRECISION
 
 
-def all(values, axis=None):
+def all(values, axis=None) -> 'Array':
     r"""
     Test whether all array elements along a given axis evaluate to True.
 
@@ -77,7 +77,7 @@ def all(values, axis=None):
         return builtins.all(values)
 
 
-def any(values, axis=None):
+def any(values, axis=None) -> 'Array':
     r"""
     Test whether any array elements along a given axis evaluate to True.
 
@@ -92,7 +92,7 @@ def any(values, axis=None):
 
 
 # commutative modulo float precision errors
-def sum(array, *args, **kwargs):
+def sum(array, *args, **kwargs) -> 'Array':
     r"""
     Sum of array elements.
 
@@ -110,7 +110,7 @@ def sum(array, *args, **kwargs):
         return builtins.sum(array, *args, **kwargs)
 
 
-def prod(array, *args, **kwargs):
+def prod(array, *args, **kwargs) -> 'Array':
     r"""
     Product of array elements.
 
@@ -121,7 +121,7 @@ def prod(array, *args, **kwargs):
     return array.prod(*args, **kwargs)
 
 
-def cumsum(array, *args, **kwargs):
+def cumsum(array, *args, **kwargs) -> 'Array':
     r"""
     Returns the cumulative sum of array elements.
 
@@ -132,7 +132,7 @@ def cumsum(array, *args, **kwargs):
     return array.cumsum(*args, **kwargs)
 
 
-def cumprod(array, *args, **kwargs):
+def cumprod(array, *args, **kwargs) -> 'Array':
     r"""
     Returns the cumulative product of array elements.
 
@@ -143,7 +143,7 @@ def cumprod(array, *args, **kwargs):
     return array.cumprod(*args, **kwargs)
 
 
-def min(array, *args, **kwargs):
+def min(array, *args, **kwargs) -> 'Array':
     r"""
     Minimum of array elements.
 
@@ -157,7 +157,7 @@ def min(array, *args, **kwargs):
         return builtins.min(array, *args, **kwargs)
 
 
-def max(array, *args, **kwargs):
+def max(array, *args, **kwargs) -> 'Array':
     r"""
     Maximum of array elements.
 
@@ -171,7 +171,7 @@ def max(array, *args, **kwargs):
         return builtins.max(array, *args, **kwargs)
 
 
-def mean(array, *args, **kwargs):
+def mean(array, *args, **kwargs) -> 'Array':
     r"""
     Computes the arithmetic mean.
 
@@ -182,7 +182,7 @@ def mean(array, *args, **kwargs):
     return array.mean(*args, **kwargs)
 
 
-def median(array, *args, **kwargs):
+def median(array, *args, **kwargs) -> 'Array':
     r"""
     Computes the median.
 
@@ -193,7 +193,7 @@ def median(array, *args, **kwargs):
     return array.median(*args, **kwargs)
 
 
-def percentile(array, *args, **kwargs):
+def percentile(array, *args, **kwargs) -> 'Array':
     r"""
     Computes the qth percentile of the data along the specified axis.
 
@@ -205,7 +205,7 @@ def percentile(array, *args, **kwargs):
 
 
 # not commutative
-def ptp(array, *args, **kwargs):
+def ptp(array, *args, **kwargs) -> 'Array':
     r"""
     Returns the range of values (maximum - minimum).
 
@@ -216,7 +216,7 @@ def ptp(array, *args, **kwargs):
     return array.ptp(*args, **kwargs)
 
 
-def var(array, *args, **kwargs):
+def var(array, *args, **kwargs) -> 'Array':
     r"""
     Computes the variance.
 
@@ -227,7 +227,7 @@ def var(array, *args, **kwargs):
     return array.var(*args, **kwargs)
 
 
-def std(array, *args, **kwargs):
+def std(array, *args, **kwargs) -> 'Array':
     r"""
     Computes the standard deviation.
 
@@ -3978,7 +3978,7 @@ def wrapper(self, *args, **kwargs):
         return decorated
 
     @_decorate_agg_method(np.all, commutative=True, long_name="AND reduction")
-    def all(self, *args, **kwargs):
+    def all(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Test whether all selected elements evaluate to True.
@@ -4049,7 +4049,7 @@ def all(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.all, commutative=True, by_agg=True, long_name="AND reduction")
-    def all_by(self, *args, **kwargs):
+    def all_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Test whether all selected elements evaluate to True.
@@ -4117,7 +4117,7 @@ def all_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.any, commutative=True, long_name="OR reduction")
-    def any(self, *args, **kwargs):
+    def any(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Test whether any selected elements evaluate to True.
@@ -4188,7 +4188,7 @@ def any(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.any, commutative=True, by_agg=True, long_name="OR reduction")
-    def any_by(self, *args, **kwargs):
+    def any_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Test whether any selected elements evaluate to True.
@@ -4258,7 +4258,7 @@ def any_by(self, *args, **kwargs):
     # commutative modulo float precision errors
 
     @_decorate_agg_method(np.sum, np.nansum, commutative=True, extra_kwargs=['dtype'])
-    def sum(self, *args, **kwargs):
+    def sum(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the sum of array elements along given axes/groups.
@@ -4323,7 +4323,7 @@ def sum(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.sum, np.nansum, commutative=True, by_agg=True, extra_kwargs=['dtype'], long_name="sum")
-    def sum_by(self, *args, **kwargs):
+    def sum_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the sum of array elements for the given axes/groups.
@@ -4386,7 +4386,7 @@ def sum_by(self, *args, **kwargs):
 
     # nanprod needs numpy 1.10
     @_decorate_agg_method(np.prod, np_nanprod, commutative=True, extra_kwargs=['dtype'], long_name="product")
-    def prod(self, *args, **kwargs):
+    def prod(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the product of array elements along given axes/groups.
@@ -4452,7 +4452,7 @@ def prod(self, *args, **kwargs):
 
     @_decorate_agg_method(np.prod, np_nanprod, commutative=True, by_agg=True, extra_kwargs=['dtype'],
                           long_name="product")
-    def prod_by(self, *args, **kwargs):
+    def prod_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the product of array elements for the given axes/groups.
@@ -4514,7 +4514,7 @@ def prod_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.min, np.nanmin, commutative=True, long_name="minimum", action_verb="search")
-    def min(self, *args, **kwargs):
+    def min(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Get minimum of array elements along given axes/groups.
@@ -4578,7 +4578,7 @@ def min(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.min, np.nanmin, commutative=True, by_agg=True, long_name="minimum", action_verb="search")
-    def min_by(self, *args, **kwargs):
+    def min_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Get minimum of array elements for the given axes/groups.
@@ -4639,7 +4639,7 @@ def min_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.max, np.nanmax, commutative=True, long_name="maximum", action_verb="search")
-    def max(self, *args, **kwargs):
+    def max(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Get maximum of array elements along given axes/groups.
@@ -4703,7 +4703,7 @@ def max(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.max, np.nanmax, commutative=True, by_agg=True, long_name="maximum", action_verb="search")
-    def max_by(self, *args, **kwargs):
+    def max_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Get maximum of array elements for the given axes/groups.
@@ -4764,7 +4764,7 @@ def max_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.mean, np.nanmean, commutative=True, extra_kwargs=['dtype'])
-    def mean(self, *args, **kwargs):
+    def mean(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the arithmetic mean.
@@ -4830,7 +4830,7 @@ def mean(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.mean, np.nanmean, commutative=True, by_agg=True, extra_kwargs=['dtype'], long_name="mean")
-    def mean_by(self, *args, **kwargs):
+    def mean_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the arithmetic mean.
@@ -4893,7 +4893,7 @@ def mean_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.median, np.nanmedian, commutative=True)
-    def median(self, *args, **kwargs):
+    def median(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the arithmetic median.
@@ -4963,7 +4963,7 @@ def median(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.median, np.nanmedian, commutative=True, by_agg=True, long_name="mediane")
-    def median_by(self, *args, **kwargs):
+    def median_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the arithmetic median.
@@ -5034,7 +5034,7 @@ def median_by(self, *args, **kwargs):
     #      since in this case np.percentile() may be called several times.
     # percentile needs an explicit method because it has not the same
     # signature as other aggregate functions (extra argument)
-    def percentile(self, q, *args, **kwargs):
+    def percentile(self, q, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the qth percentile of the data along the specified axis.
@@ -5122,7 +5122,7 @@ def percentile(self, q, *args, **kwargs):
     _doc_agg_method(percentile, False, "qth percentile", extra_args=['q'],
                     kwargs=['out', 'interpolation', 'skipna', 'keepaxes'])
 
-    def percentile_by(self, q, *args, **kwargs):
+    def percentile_by(self, q, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the qth percentile of the data for the specified axis.
@@ -5208,7 +5208,7 @@ def percentile_by(self, q, *args, **kwargs):
 
     # not commutative
 
-    def ptp(self, *args, **kwargs):
+    def ptp(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Returns the range of values (maximum - minimum).
@@ -5273,7 +5273,7 @@ def ptp(self, *args, **kwargs):
     _doc_agg_method(ptp, False, kwargs=['out'])
 
     @_decorate_agg_method(np.var, np.nanvar, extra_kwargs=['dtype', 'ddof'], long_name="variance")
-    def var(self, *args, **kwargs):
+    def var(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the unbiased variance.
@@ -5337,7 +5337,7 @@ def var(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.var, np.nanvar, by_agg=True, extra_kwargs=['dtype', 'ddof'], long_name="variance")
-    def var_by(self, *args, **kwargs):
+    def var_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the unbiased variance.
@@ -5401,7 +5401,7 @@ def var_by(self, *args, **kwargs):
         pass
 
     @_decorate_agg_method(np.std, np.nanstd, extra_kwargs=['dtype', 'ddof'], long_name="standard deviation")
-    def std(self, *args, **kwargs):
+    def std(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the sample standard deviation.
@@ -5466,7 +5466,7 @@ def std(self, *args, **kwargs):
 
     @_decorate_agg_method(np.std, np.nanstd, by_agg=True, extra_kwargs=['dtype', 'ddof'],
                           long_name="standard deviation")
-    def std_by(self, *args, **kwargs):
+    def std_by(self, *args, **kwargs) -> 'Array':
         r"""{signature}
 
         Computes the sample standard deviation.
@@ -5530,7 +5530,7 @@ def std_by(self, *args, **kwargs):
         pass
 
     # cumulative aggregates
-    def cumsum(self, axis=-1):
+    def cumsum(self, axis=-1) -> 'Array':
         r"""
         Returns the cumulative sum of array elements along an axis.
 
@@ -5578,7 +5578,7 @@ def cumsum(self, axis=-1):
         """
         return self._cum_aggregate(np.cumsum, axis)
 
-    def cumprod(self, axis=-1):
+    def cumprod(self, axis=-1) -> 'Array':
         r"""
         Returns the cumulative product of array elements.