style: format with isort and black

hypercontagion/__init__.py

@@ -3,4 +3,4 @@
 from hypercontagion import simulation
 from hypercontagion.simulation import *
 
-__version__ = pkg_resources.require("hypercontagion")[0].version
+__version__ = pkg_resources.require("hypercontagion")[0].version

hypercontagion/classes/__init__.py

@@ -1,2 +1,2 @@
 import hypercontagion.classes.epi_contagion
-from hypercontagion.classes import epi_contagion
+from hypercontagion.classes import epi_contagion

hypercontagion/classes/epi_contagion.py

@@ -1,21 +1,26 @@
+from collections import defaultdict
+
+import networkx as nx
 from sklearn import neighbors
+
 from hypercontagion import SamplingDict
-import networkx as nx
-from collections import defaultdict
 from hypercontagion.exception import HyperContagionError
 
+
 class DiscreteStochasticEpiModel:
  def __init__(self):
  self.transition_network = nx.DiGraph()
  self.hypergraph = None
  self.state = None
- 
+
  def add_transition_process(self, start_state, end_state, transition_function):
- self.transition_network.add_edge(start_state, end_state, function=transition_function)
+ self.transition_network.add_edge(
+ start_state, end_state, function=transition_function
+ )
 
  def add_hypergraph(self, H):
  self.hypergraph = H
- 
+
  def set_initial_state(self, state):
  self.state = state
 
@@ -26,16 +31,13 @@ def remaining_transitions(self, state_dict):
  num_trans += state_dict[state][-1]
  return num_trans
 
-
-
  def simulate(self, tmin, tmax, dt=1):
  state = dict(self.state)
  if self.state is None:
  raise HyperContagionError("Initial state was never set!")
  else:
  state_dict = dict(self.state)
 
-
  state_dict = dict()
  for s in self.transition_network.nodes:
  state_dict[s] = [0]
@@ -48,7 +50,6 @@ def simulate(self, tmin, tmax, dt=1):
 
  new_state = state
 
-
  while t <= tmax and self.remaining_transitions(state_dict) != 0:
  for s in self.transition_network.nodes:
  state_dict[s].append(state_dict[s][-1])
@@ -61,20 +62,20 @@ def simulate(self, tmin, tmax, dt=1):
 
  t += dt
 
+
 # # assumes all transitions are Markovian
 # class GillespieStochasticEpiModel:
 # def __init__(self):
 # self.simulate = False
 # self.rates = dict()
 # self.transition_functions = dict()
 # self.hypergraph = None
- 
+
 # def add_transition_process(self, start_state, end_state, transition_function):
 # self.rates[(start_state, end_state)] = SamplingDict(weighted=True)
 # self.transition_functions[(start_state, end_state)] = transition_function
 
 # def add_hypergraph(self, H):
 # self.hypergraph = H
- 
+
 # # def simulate(tmin, tmax, return_events):
-

hypercontagion/simulation/__init__.py

@@ -1,4 +1,5 @@
 from hypercontagion.simulation import epidemics, functions, opinions, utilities
-from .opinions import *
+
 from .functions import *
+from .opinions import *
 from .utilities import *

hypercontagion/simulation/epidemics.py

@@ -1,15 +1,17 @@
 import random
-import numpy as np
 from collections import defaultdict
+
+import numpy as np
+import xgi
+
 from hypercontagion.exception import HyperContagionError
 from hypercontagion.simulation.functions import majority_vote, threshold
 from hypercontagion.simulation.utilities import (
- SamplingDict,
  EventQueue,
+ SamplingDict,
  _process_trans_SIR_,
  _process_trans_SIS_,
 )
-import xgi
 
 
 def discrete_SIR(

hypercontagion/simulation/functions.py

@@ -1,5 +1,6 @@
 import random
 
+
 # built-in functions
 def collective_contagion(node, status, edge):
  for i in set(edge).difference({node}):

hypercontagion/simulation/opinions.py

@@ -1,8 +1,8 @@
-import random
 import heapq
+import random
+from collections import Counter, defaultdict
+
 import numpy as np
-from collections import defaultdict
-from collections import Counter
 
 # built-in functions
 

hypercontagion/simulation/utilities.py

@@ -3,10 +3,11 @@
 github.com/gstonge/SamplableSet but is less efficient.
 """
 
-import numpy as np
-import random
-from collections import defaultdict, Counter
 import heapq
+import random
+from collections import Counter, defaultdict
+
+import numpy as np
 
 
 class EventQueue:

hypercontagion/visualization/__init__.py

@@ -1,6 +1,7 @@
-from .vis import *
+import hypercontagion.visualization.colors
+import hypercontagion.visualization.layout
 import hypercontagion.visualization.vis
+
 from .colors import *
-import hypercontagion.visualization.colors
 from .layout import *
-import hypercontagion.visualization.layout
+from .vis import *

hypercontagion/visualization/vis.py

@@ -2,20 +2,18 @@
 Visualizations of simulations with pyglet.
 """
 
-from sys import platform
-
 from copy import deepcopy
 from itertools import chain
+from sys import platform
 
 import numpy as np
-
 import pyglet
 from pyglet import shapes
-from pyglet.window import key, mouse, Window
 from pyglet.gl import *
+from pyglet.window import Window, key, mouse
 
-from hypercontagion.visualization.colors import colors
 import hypercontagion.visualization.colors as cols
+from hypercontagion.visualization.colors import colors
 
 _colors = list(colors.values())
 

setup.py

@@ -1,7 +1,8 @@
-from setuptools import setup
-import setuptools
 import sys
 
+import setuptools
+from setuptools import setup
+
 __version__ = "0.1"
 
 if sys.version_info < (3, 7):

tests/conftest.py

@@ -1,25 +1,43 @@
 import pytest
 
+
 @pytest.fixture
 def func_args_1():
  return {"node": 1, "status": {1: "S", 2: "S", 3: "I"}, "edge": [1, 2, 3]}
 
+
 @pytest.fixture
 def func_args_2():
  return {"node": 1, "status": {1: "S", 2: "I", 3: "I"}, "edge": [1, 2, 3]}
 
+
 @pytest.fixture
 def func_args_3():
  return {"node": 2, "status": {1: "S", 2: "I", 3: "I", 4: "R"}, "edge": [1, 2, 3, 4]}
 
+
 @pytest.fixture
 def func_args_4():
- return {"node": 5, "status": {1: "S", 2: "I", 3: "I", 4: "R", 5: "S"}, "edge": [1, 2, 3, 4, 5]}
+ return {
+ "node": 5,
+ "status": {1: "S", 2: "I", 3: "I", 4: "R", 5: "S"},
+ "edge": [1, 2, 3, 4, 5],
+ }
+
 
 @pytest.fixture
 def func_args_5():
- return {"node": 3, "status": {1: "I", 2: "I", 3: "S", 4: "I", 5: "I"}, "edge": [1, 2, 3, 4, 5]}
+ return {
+ "node": 3,
+ "status": {1: "I", 2: "I", 3: "S", 4: "I", 5: "I"},
+ "edge": [1, 2, 3, 4, 5],
+ }
+
 
 @pytest.fixture
 def func_args_6():
- return {"node": 3, "status": {1: "S", 2: "S", 3: "S", 4: "R", 5: "R"}, "edge": [1, 2, 3, 4, 5]}
+ return {
+ "node": 3,
+ "status": {1: "S", 2: "S", 3: "S", 4: "R", 5: "R"},
+ "edge": [1, 2, 3, 4, 5],
+ }