Implement Black formatting

Author: PhilipMathieu

.pre-commit-config.yaml

@@ -26,6 +26,12 @@ repos:
     rev: 6.1.0
     hooks:
     - id: flake8
+      args:
+        - --ignore=E501,W503,F841,E203
+        # E501: line too long
+        # W503: line break before binary operator
+        # F841: local variable is assigned to but never used
+        # E203: whitespace before ':'
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.4.0
     hooks:

graphreadability/__init__.py

@@ -2,8 +2,10 @@
 from .core.metricssuite import MetricsSuite
 from .core.readabilitygraph import ReadabilityGraph
 
-from .utils.helpers import *
-from .utils.crosses_promotion import *
+import utils.helpers as helpers
+import utils.crosses_promotion as crosses_promotion
 
 # Import tests
-from .tests import *
+import tests
+
+__all__ = ["MetricsSuite", "ReadabilityGraph", "helpers", "crosses_promotion", "tests"]

graphreadability/core/metricssuite.py

@@ -1,19 +1,23 @@
 import math
 import time
 from typing import Optional, Union, Sequence
-from collections import defaultdict
 import networkx as nx
 from ..metrics import metrics
 
 # Get all the functions in the metrics module
-_metric_functions = [func for func in dir(metrics) if callable(getattr(metrics, func)) and not func.startswith("__")]
+_metric_functions = [
+    func
+    for func in dir(metrics)
+    if callable(getattr(metrics, func)) and not func.startswith("__")
+]
 
 # Generate the DEFAULT_WEIGHTS dictionary
 DEFAULT_WEIGHTS = {func: 1 for func in _metric_functions}
 
 # Generate the METRICS dictionary
 METRICS = {func: {"func": getattr(metrics, func)} for func in _metric_functions}
 
+
 class MetricsSuite:
     """A suite for calculating several metrics for graph drawing aesthetics, as well as methods for combining these into a single cost function.
     Takes as an argument a path to a GML or GraphML file, or a NetworkX Graph object. Also takes as an argument a dictionary of metric:weight key/values.
@@ -38,7 +42,7 @@ def __init__(
         # Dictionary mapping metric names to their functions, values, and weights
         self.metrics = METRICS.copy()
         for k in self.metrics.keys():
-            self.metrics[k].update({"weight":0, "value": None, "is_calculated": False})
+            self.metrics[k].update({"weight": 0, "value": None, "is_calculated": False})
 
         # Check all metrics given are valid and assign weights
         self.initial_weights = self.set_weights(metric_weights)
@@ -62,19 +66,21 @@ def __init__(
             raise TypeError(
                 f"'graph' must be a string representing a path to a GML or GraphML file, or a NetworkX Graph object, not {type(graph)}"
             )
-        
+
         if sym_tolerance < 0:
-            raise ValueError(f"sym_tolerance must be positive.")
+            raise ValueError("sym_tolerance must be positive.")
 
         self.sym_tolerance = sym_tolerance
 
         if sym_threshold < 0:
-            raise ValueError(f"sym_threshold must be positive.")
+            raise ValueError("sym_threshold must be positive.")
 
         self.sym_threshold = sym_threshold
 
     def set_weights(self, metric_weights: Sequence[float]):
-        metrics_to_remove = [metric for metric, weight in metric_weights.items() if weight <= 0]
+        metrics_to_remove = [
+            metric for metric, weight in metric_weights.items() if weight <= 0
+        ]
 
         if any(metric_weights[metric] < 0 for metric in metric_weights):
             raise ValueError("Metric weights must be positive.")
@@ -85,8 +91,10 @@ def set_weights(self, metric_weights: Sequence[float]):
         for metric in metric_weights:
             self.metrics[metric]["weight"] = metric_weights[metric]
 
-        return {metric: weight for metric, weight in metric_weights.items() if weight > 0}
-    
+        return {
+            metric: weight for metric, weight in metric_weights.items() if weight > 0
+        }
+
     def weighted_prod(self):
         """Returns the weighted product of all metrics. Should NOT be used as a cost function - may be useful for comparing graphs."""
         return math.prod(
@@ -114,17 +122,19 @@ def load_graph_test(self, nxg=nx.sedgewick_maze_graph):
 
         nx.set_node_attributes(G, pos)
         return G
-    
+
     def reset_metrics(self):
         for metric in self.metrics:
             self.metrics[metric]["value"] = None
             self.metrics[metric]["is_calculated"] = False
-    
+
     def calculate_metric(self, metric: str = None):
         """Calculate the value of the given metric by calling the associated function."""
         if metric is None:
-            raise ValueError("No metric provided. Did you mean to call calculate_metrics()?")
-        
+            raise ValueError(
+                "No metric provided. Did you mean to call calculate_metrics()?"
+            )
+
         if not self.metrics[metric]["is_calculated"]:
             self.metrics[metric]["value"] = self.metrics[metric]["func"](self._graph)
             self.metrics[metric]["is_calculated"] = True
@@ -141,7 +151,9 @@ def calculate_metrics(self):
                 self.calculate_metric(metric)
                 n_metrics += 1
         end_time = time.perf_counter()
-        print(f"Calculated {n_metrics} metrics in {end_time - start_time:0.3f} seconds.")
+        print(
+            f"Calculated {n_metrics} metrics in {end_time - start_time:0.3f} seconds."
+        )
 
     def combine_metrics(self):
         """Combine several metrics based on the given multiple criteria decision analysis technique."""
@@ -172,4 +184,4 @@ def metric_table(self):
         for k, v in self.metrics.items():
             metrics[k] = v["value"]
         metrics["Combined"] = combined
-        return metrics
+        return metrics

graphreadability/core/readabilitygraph.py

@@ -1,14 +1,19 @@
 """
 This module is based on:
 
-    C. Dunne, S. I. Ross, B. Shneiderman, and M. Martino, “Readability metric feedback for aiding 
-    node-link visualization designers,” IBM Journal of Research and Development, vol. 59, no. 2/3, 
+    C. Dunne, S. I. Ross, B. Shneiderman, and M. Martino, “Readability metric feedback for aiding
+    node-link visualization designers,” IBM Journal of Research and Development, vol. 59, no. 2/3,
     p. 14:1-14:16, Mar. 2015, doi: 10.1147/JRD.2015.2411412.
 """
 
 import networkx as nx
 import numpy as np
-from graphreadability.utils.helpers import divide_or_zero, lines_intersect, calculate_angle_between_vectors
+from graphreadability.utils.helpers import (
+    divide_or_zero,
+    lines_intersect,
+    calculate_angle_between_vectors,
+)
+
 
 class ReadabilityGraph(nx.Graph):
     def __init__(self, data=None, **attr):
@@ -21,12 +26,12 @@ def __init__(self, data=None, **attr):
             None  # Store computed node overlaps to avoid recomputation
         )
 
-    ### HELPER FUNCTIONS ###
+    # HELPER FUNCTIONS #
     def edge_vector(self, edge):
         """Calculate the vector of an edge given its nodes' positions."""
         pos1, pos2 = self.nodes[edge[0]]["pos"], self.nodes[edge[1]]["pos"]
         return np.array(pos2) - np.array(pos1)
-    
+
     def calculate_edge_crossings(self):
         positions = nx.get_node_attributes(
             self, "pos"
@@ -98,7 +103,7 @@ def calculate_node_node_overlap(self):
 
         return overlaps
 
-    ### METRICS ###
+    # METRICS #
     def node_overlap_global(self):
         # Implement computation for global overlap metric
         pass