Code style #207

Author: dpuenteramirez

semisupervised/DensityPeaks.py

@@ -71,7 +71,7 @@ def __init__(
             self.filter = None
 
         self.y = None
-        self.l = None
+        self.low = None
         self.u = None
         self.classifier_stdpnf = None
         self.order = None
@@ -198,9 +198,13 @@ def __min_neighbor_and_distance(self):
 
         :return: distance vector, nearest neighbor vector
         """
+        if self.rho is None:
+            raise ValueError("Encountered rho as None.")
+
         sort_rho_idx = np.argsort(-self.rho)
         delta, nneigh = [float(self.max_dis)] * self.n_id, [0] * self.n_id
         delta[sort_rho_idx[0]] = -1.0
+
         for i in range(self.n_id):
             for j in range(0, i):
                 old_i, old_j = sort_rho_idx[i], sort_rho_idx[j]
@@ -359,20 +363,20 @@ def __enane(self, fx, nan, r):
 
         return es, es_pred
 
-    def __init_values(self, l, u, y):
+    def __init_values(self, low, u, y):
         """
         It takes in the lower and upper bounds of the data, and the data itself,
          and then calculates the distances between the data points,
          the maximum distance, the minimum distance, the dc value, the rho
          value, the delta value, the number of neighbors, and the structure
          of the data
 
-        :param l: lower bound of the data
+        :param low: lower bound of the data
         :param u: upper bound of the data
         :param y: the labels of the data
         """
         self.y = y
-        self.l = l
+        self.low = low
         self.u = u
         self.data = np.concatenate((l, u), axis=0)
         self.n_id = self.data.shape[0]
@@ -470,7 +474,7 @@ def _fit_stdpnf(self):
         self.classifier_stdpnf = KNeighborsClassifier(
             n_neighbors=self.k, metric=self.distance_metric
         )
-        self.classifier_stdpnf.fit(self.l, self.y)
+        self.classifier_stdpnf.fit(self.low, self.y)
         count = 1
 
         while count <= max(self.order.values()):
@@ -546,7 +550,7 @@ def _if_filter(self, complete, complete_y):
         :return: The result is a dataframe with the filtered data.
         """
         if isinstance(self.filter, ENN):
-            original = pd.DataFrame(self.l)
+            original = pd.DataFrame(self.low)
             original_y = pd.DataFrame(self.y)
             result, _ = self.filter.filter_original_complete(
                 original, original_y, complete, complete_y

utils/arff2dataset.py

@@ -20,7 +20,7 @@ def arff_data(dataset_path, attr=False):
     defaults to False (optional)
     :return: A bunch object with the data, target and attributes.
     """
-    if not ".arff" in str(dataset_path).lower():
+    if ".arff" not in str(dataset_path).lower():
         raise ValueError("File does not an ARFF extension.")
     file = open(dataset_path, "r")
     attrs, data = _read_file(file)