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Format code with yapf, black, autopep8 and isort #208

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merged 1 commit into from
May 8, 2022
Merged

Format code with yapf, black, autopep8 and isort #208

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42 changes: 20 additions & 22 deletions semisupervised/DensityPeaks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
from sklearn.svm import SVC

from instance_selection import ENN

from .utils import split


Expand All @@ -31,19 +32,19 @@ class STDPNF:
"""

def __init__(
self,
dc=None,
distance_metric="euclidean",
k=3,
gauss_cutoff=True,
percent=2.0,
density_threshold=None,
distance_threshold=None,
anormal=True,
filtering=False,
classifier=None,
classifier_params=None,
filter_method=None,
self,
dc=None,
distance_metric="euclidean",
k=3,
gauss_cutoff=True,
percent=2.0,
density_threshold=None,
distance_threshold=None,
anormal=True,
filtering=False,
classifier=None,
classifier_params=None,
filter_method=None,
):
"""Semi Supervised Algorithm based on Density Peaks."""
self.dc = dc
Expand Down Expand Up @@ -121,8 +122,7 @@ def __auto_select_dc(self):

while True:
nneighs = (
sum([1 for v in self.distances.values() if
v < dc]) / self.n_id ** 2
sum([1 for v in self.distances.values() if v < dc]) / self.n_id**2
)
if 0.01 <= nneighs <= 0.02:
break
Expand Down Expand Up @@ -476,7 +476,7 @@ def _fit_stdpnf(self):
while count <= max(self.order.values()):
unlabeled_rows = self.structure_stdnpf.loc[
self.structure_stdnpf["label"] == -1
].index.to_list()
].index.to_list()
unlabeled_indexes = []
for row in unlabeled_rows:
if self.order[row] == count:
Expand All @@ -492,7 +492,7 @@ def _fit_stdpnf(self):
else:
labeled_data = self.structure_stdnpf.loc[
self.structure_stdnpf["label"] != -1
]
]
complete = labeled_data["sample"]
complete_y = labeled_data["label"]

Expand All @@ -502,15 +502,14 @@ def _fit_stdpnf(self):

labeled_data = self.structure_stdnpf.loc[
self.structure_stdnpf["label"] != -1
]
]
self.classifier_stdpnf.fit(
labeled_data["sample"].tolist(), labeled_data["label"].tolist()
)

count += 1

labeled_data = self.structure_stdnpf.loc[
self.structure_stdnpf["label"] != -1]
labeled_data = self.structure_stdnpf.loc[self.structure_stdnpf["label"] != -1]
self.classifier_stdpnf.fit(
labeled_data["sample"].tolist(), labeled_data["label"].tolist()
)
Expand All @@ -533,8 +532,7 @@ def _results_to_structure(self, complete, result):
if not is_in:
results_to_unlabeled.append(r)
for r in results_to_unlabeled:
self.structure_stdnpf.at[
np.array(self.structure_stdnpf["sample"], r)][
self.structure_stdnpf.at[np.array(self.structure_stdnpf["sample"], r)][
"label"
] = -1

Expand Down