Pass flake8

Author: ddomingof

src/diffupy/cli.py

@@ -75,7 +75,6 @@ def kernel(
 
     click.secho(f'{EMOJI} Calculating regulatised Laplacian kernel. This might take a while... {EMOJI}')
 
-
     exe_t_0 = time.time()
     background_mat = regularised_laplacian_kernel(graph)
     exe_t_f = time.time()

src/diffupy/diffuse.py

@@ -37,7 +37,6 @@ def diffuse(
     :return: The diffused scores within the matrix transformation of the network, with the diffusion operation
              [k x input_vector] performed
     """
-
     # Sanity checks
     scores = copy.copy(input_scores)
 

src/diffupy/diffuse_raw.py

@@ -55,7 +55,7 @@ def diffuse_raw(
         scores: Matrix,
         z: bool = False,
         k: Matrix = None,
-    ) -> Matrix:
+) -> Matrix:
     """Compute the score diffusion procedure, given an initial state as a set of scores and a network where diffuse it.
 
     :param graph: background network

src/diffupy/kernels.py

@@ -16,7 +16,6 @@
 
 log = logging.getLogger(__name__)
 
-
 __all__ = [
     'diffusion_kernel',
     'commute_time_kernel',
@@ -25,6 +24,7 @@
     'p_step_kernel',
 ]
 
+
 def commute_time_kernel(graph: nx.Graph, normalized: bool = False) -> Matrix:
     """Compute the commute-time kernel, which is the expected time of going back and forth between a couple of nodes.
 

tests/diffusion_tests.py

@@ -3,12 +3,12 @@
 """Tests checking kernel functions py implementation based on R package computations."""
 
 import logging
+import unittest
+
 import networkx as nx
 import numpy as np
-import unittest
 
 from diffupy.diffuse import diffuse
-
 from diffupy.matrix import Matrix
 from .constants import *
 
@@ -17,9 +17,9 @@
 """Helper functions for testing"""
 
 
-def _run_diffusion_method_test(method, G, input_scores, test_output_scores):
-    """Helper for test class."""
-    computed_output_scores = diffuse(input_scores, method, graph=G)
+def _run_diffusion_method_test(method, g, input_scores, test_output_scores):
+    """Help for test class."""
+    computed_output_scores = diffuse(input_scores, method, graph=g)
 
     if isinstance(computed_output_scores, Matrix):
         computed_output_scores = computed_output_scores.mat
@@ -39,6 +39,7 @@ def _run_diffusion_method_test(method, G, input_scores, test_output_scores):
 
 class DiffuseTest(unittest.TestCase):
     """Test diffusion methods."""
+
     graph = nx.read_gml(GML_FILE_EXAMPLE, label='id')
 
     _run_diffusion_method_test('raw', graph, INPUT_SCORES, OUTPUT_RAW_SCORES)