Fixed bad formatting, refactored

Author: seanlaw

docstring.py

@@ -17,9 +17,11 @@ def get_docstring_args(fd, file_name, func_name, class_name=None):
             msg += f"class: {class_name}\n"
         msg += f"function/method: {func_name}\n"
         raise RuntimeError(msg)
-    if class_name is None and len(re.findall(r"Returns", docstring)) != 1:
+    if len(re.findall(r"Returns", docstring)) != 1:
         msg = "Missing required 'Returns' section in docstring in \n"
         msg += f"file: {file_name}\n"
+        if class_name is not None:
+            msg += f"class: {class_name}\n"
         msg += f"function/method: {func_name}\n"
         raise RuntimeError(msg)
 

stumpy/aamp_stimp.py

@@ -189,7 +189,7 @@ def __init__(
             The p-norm to apply for computing the Minkowski distance. Minkowski distance
             is typically used with `p` being 1 or 2, which correspond to the Manhattan
             distance and the Euclidean distance, respectively.
-        
+
         Returns
         -------
         None
@@ -515,7 +515,7 @@ def __init__(
             The p-norm to apply for computing the Minkowski distance. Minkowski distance
             is typically used with `p` being 1 or 2, which correspond to the Manhattan
             distance and the Euclidean distance, respectively.
-        
+
         Returns
         -------
         None
@@ -625,7 +625,7 @@ def __init__(
             The p-norm to apply for computing the Minkowski distance. Minkowski distance
             is typically used with `p` being 1 or 2, which correspond to the Manhattan
             distance and the Euclidean distance, respectively.
-        
+
         Returns
         -------
         None

stumpy/aampi.py

@@ -109,7 +109,7 @@ def __init__(self, T, m, egress=True, p=2.0, k=1, mp=None):
             corresponding indices. The last two columns correspond to the top-1 left
             and top-1 right matrix profile indices. When None (default), this array is
             computed internally using `stumpy.aamp`.
-        
+
         Returns
         -------
         None
@@ -183,7 +183,7 @@ def update(self, t):
         ----------
         t : float
             A single new data point to be appended to `T`
-        
+
         Returns
         -------
         None
@@ -211,7 +211,7 @@ def _update_egress(self, t):
         ----------
         t : float
             A single new data point to be appended to `T`
-        
+
         Returns
         -------
         None
@@ -280,7 +280,7 @@ def _update(self, t):
         ----------
         t : float
             A single new data point to be appended to `T`
-        
+
         Returns
         -------
         None

stumpy/floss.py

@@ -499,7 +499,7 @@ def __init__(
             `functools.partial`. Any subsequence with at least one np.nan/np.inf will
             automatically have its corresponding value set to False in this boolean
             array.
-        
+
         Returns
         -------
         None

stumpy/gpu_aamp_stimp.py

@@ -102,7 +102,7 @@ def __init__(
             The p-norm to apply for computing the Minkowski distance. Minkowski distance
             is typically used with `p` being 1 or 2, which correspond to the Manhattan
             distance and the Euclidean distance, respectively.
-        
+
         Returns
         -------
         None

stumpy/gpu_stimp.py

@@ -164,7 +164,7 @@ def __init__(
             function using  `functools.partial``. Any subsequence with at least one
             ``np.nan``/``np.inf`` will automatically have its corresponding value set
             to ``False`` in this boolean array.
-        
+
         Returns
         -------
         None

stumpy/mparray.py

@@ -68,7 +68,7 @@ def __new__(cls, input_array, m, k, excl_zone_denom):
 
         excl_zone_denom : int
             The denominator used in computing the exclusion zone
-        
+
         Returns
         -------
         obj : mparray
@@ -91,7 +91,7 @@ def __array_finalize__(self, obj):
         ----------
         obj : object
             This is the class object
-        
+
         Returns
         -------
         None

stumpy/scraamp.py

@@ -615,7 +615,7 @@ def __init__(
             The number of top `k` smallest distances used to construct the matrix
             profile. Note that this will increase the total computational time and
             memory usage when k > 1.
-        
+
         Returns
         -------
         None
@@ -804,8 +804,9 @@ def P_(self):
         -------
         out1 : numpy.ndarray
             The updated (top-k) matrix profile. When `k=1` (default), this output is
-            a 1D array consisting of the updated matrix profile. When `k > 1`, the output
-            is a 2D array that has exactly `k` columns consisting of the updated top-k matrix profile.
+            a 1D array consisting of the updated matrix profile. When `k > 1`, the
+            output is a 2D array that has exactly `k` columns consisting of the updated
+            top-k matrix profile.
         """
         if self._k == 1:
             return self._P.flatten().astype(np.float64)

stumpy/scrump.py

@@ -865,7 +865,7 @@ def __init__(
             by currying the user-defined function using `functools.partial`. Any
             subsequence with at least one np.nan/np.inf will automatically have its
             corresponding value set to False in this boolean array.
-        
+
         Returns
         -------
         None

stumpy/stimp.py

@@ -186,7 +186,7 @@ def __init__(
             `functools.partial`. Any subsequence with at least one np.nan/np.inf will
             automatically have its corresponding value set to False in this boolean
             array.
-        
+
         Returns
         -------
         None
@@ -566,7 +566,7 @@ def __init__(
             function using ``functools.partial``. Any subsequence with at least one
             ``np.nan``/``np.inf`` will automatically have its corresponding value set
             to ``False`` in this boolean array.
-        
+
         Returns
         -------
         None
@@ -747,7 +747,7 @@ def __init__(
             function using  `functools.partial  `. Any subsequence with at least one
             ``np.nan``/``np.inf`` will automatically have its corresponding value set
             to ``False`` in this boolean array.
-        
+
         Returns
         -------
         None