aws-samples / amazon-lookout-for-equipment-python-sdk
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 94 units with 1,510 lines of code in units (88.7% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 3 medium complex units (152 lines of code)
    • 15 simple units (475 lines of code)
    • 76 very simple units (883 lines of code)
0% | 0% | 10% | 31% | 58%
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% | 10% | 31% | 58%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
src/lookoutequipment0% | 0% | 10% | 31% | 58%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def delete_dataset()
in src/lookoutequipment/dataset.py
 51 19 3
def compute_bin_edges()
in src/lookoutequipment/plot.py
 25 13 2
def generate_replay_data()
in src/lookoutequipment/dataset.py
 76 12 5
def add_signal()
in src/lookoutequipment/plot.py
 15 10 2
def get_predictions()
in src/lookoutequipment/scheduler.py
 35 10 1
def list_inference_executions()
in src/lookoutequipment/scheduler.py
 33 9 5
def list_datasets()
in src/lookoutequipment/dataset.py
 17 8 2
def load_dataset()
in src/lookoutequipment/dataset.py
 67 8 2
def prepare_inference_data()
in src/lookoutequipment/dataset.py
 49 8 7
def _get_time_ranges()
in src/lookoutequipment/evaluation.py
 14 8 1
def create_data_schema_from_dir()
in src/lookoutequipment/schema.py
 17 7 1
def _create_component_schema()
in src/lookoutequipment/schema.py
 14 7 2
def _extract_series()
in src/lookoutequipment/plot.py
 18 7 2
def set_parameters()
in src/lookoutequipment/scheduler.py
 41 7 11
def plot_histograms_v2()
in src/lookoutequipment/evaluation.py
 56 7 5
def plot_histograms()
in src/lookoutequipment/evaluation.py
 51 7 3
def __init__()
in src/lookoutequipment/dataset.py
 24 6 5
def create()
in src/lookoutequipment/dataset.py
 24 6 1
def _extract_series_timeseries()
in src/lookoutequipment/plot.py
 8 5 2
def _preprocess_timeseries()
in src/lookoutequipment/plot.py
 9 5 2