tensorflow / similarity
Conditional Complexity

The distribution of complexity of units (measured with McCabe index).

Intro
  • Conditional complexity (also called cyclomatic complexity) is a term used to measure the complexity of software. The term refers to the number of possible paths through a program function. A higher value ofter means higher maintenance and testing costs (infosecinstitute.com).
  • Conditional complexity is calculated by counting all conditions in the program that can affect the execution path (e.g. if statement, loops, switches, and/or operators, try and catch blocks...).
  • Conditional complexity is measured at the unit level (methods, functions...).
  • Units are classified in four categories based on the measured McCabe index: 1-5 (simple units), 6-10 (medium complex units), 11-25 (complex units), 26+ (very complex units).
Learn more...
Conditional Complexity Overall
  • There are 393 units with 3,902 lines of code in units (45.3% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 2 medium complex units (192 lines of code)
    • 30 simple units (891 lines of code)
    • 361 very simple units (2,819 lines of code)
0% | 0% | 4% | 22% | 72%
Legend:
51+
26-50
11-25
6-10
1-5
Alternative Visuals
Conditional Complexity per Extension
51+
26-50
11-25
6-10
1-5
py0% | 0% | 5% | 21% | 72%
ts0% | 0% | 0% | 32% | 67%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
benchmark/supervised0% | 0% | 64% | 0% | 35%
tensorflow_similarity/visualization0% | 0% | 10% | 37% | 52%
tensorflow_similarity0% | 0% | 0% | 32% | 67%
tensorflow_similarity/losses0% | 0% | 0% | 20% | 79%
tensorflow_similarity/models0% | 0% | 0% | 17% | 82%
tensorflow_similarity/samplers0% | 0% | 0% | 34% | 65%
scripts0% | 0% | 0% | 40% | 59%
tensorflow_similarity/training_metrics0% | 0% | 0% | 42% | 57%
tensorflow_similarity/evaluators0% | 0% | 0% | 34% | 65%
tensorflow_similarity/matchers0% | 0% | 0% | 9% | 90%
tensorflow_similarity/classification_metrics0% | 0% | 0% | 11% | 88%
tensorflow_similarity/augmenters0% | 0% | 0% | 0% | 100%
tensorflow_similarity/stores0% | 0% | 0% | 0% | 100%
tensorflow_similarity/architectures0% | 0% | 0% | 0% | 100%
tensorflow_similarity/search0% | 0% | 0% | 0% | 100%
tensorflow_similarity/retrieval_metrics0% | 0% | 0% | 0% | 100%
ROOT0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def projector()
in tensorflow_similarity/visualization/projector.py
 74 22 13
def run()
in benchmark/supervised/generate_datasets.py
 118 18 1
def replace_in_file()
in scripts/gen_api_doc.py
 35 10 2
export function createElement()
in tensorflow_similarity/visualization/projector_v2/lib/renderer.ts
 38 10 3
def confusion_matrix()
in tensorflow_similarity/visualization/confusion_matrix_viz.py
 47 10 7
def __init__()
in tensorflow_similarity/samplers/tfdataset_samplers.py
 51 10 15
def visualize_views()
in tensorflow_similarity/visualization/vizualize_views.py
 30 9 8
def update_state()
in tensorflow_similarity/training_metrics/distance_metrics.py
 23 9 4
def calibrate()
in tensorflow_similarity/indexer.py
 39 9 15
constructor()
in tensorflow_similarity/visualization/projector_v2/views/projector.ts
 55 8 1
private updateLabel()
in tensorflow_similarity/visualization/projector_v2/views/projector.ts
 32 8 0
def batch_lookup()
in tensorflow_similarity/indexer.py
 38 8 4
def multisimilarity_loss()
in tensorflow_similarity/losses/multisim_loss.py
 37 8 7
def load_model()
in tensorflow_similarity/models/contrastive_model.py
 38 8 1
def train_step()
in tensorflow_similarity/models/contrastive_model.py
 33 8 2
def compute()
in tensorflow_similarity/classification_metrics/precision.py
 14 7 6
private onMouseMove()
in tensorflow_similarity/visualization/projector_v2/views/projector.ts
 34 7 1
def tensor2images()
in tensorflow_similarity/visualization/projector.py
 20 7 2
def _init_structures()
in tensorflow_similarity/indexer.py
 30 7 1
def match()
in tensorflow_similarity/indexer.py
 30 7 7