facebookresearch / CausalSkillLearning
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 464 units with 5,221 lines of code in units (83.1% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 8 medium complex units (366 lines of code)
    • 35 simple units (820 lines of code)
    • 421 very simple units (4,035 lines of code)
0% | 0% | 7% | 15% | 77%
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% | 7% | 15% | 77%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
Experiments0% | 0% | 7% | 16% | 76%
DownstreamRL0% | 0% | 21% | 13% | 64%
DataLoaders0% | 0% | 0% | 8% | 91%
DataGenerator0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def parse_arguments()
in Experiments/Master.py
 94 19 0
def update_networks()
in Experiments/PolicyManagers.py
 20 16 3
def set_joint_pose_return_image()
in Experiments/Visualizers.py
 23 13 4
def __init__()
in Experiments/PolicyNetworks.py
 17 12 6
def __init__()
in Experiments/PolicyManagers.py
 77 11 4
def get_trajectory_segment()
in Experiments/PolicyManagers.py
 43 11 2
def new_update_policies()
in Experiments/PolicyManagers.py
 35 11 22
def run_episode()
in DownstreamRL/TrainZPolicyRL.py
 57 11 2
def evaluate_loglikelihoods()
in Experiments/PolicyManagers.py
 38 10 6
def run_iteration()
in Experiments/PolicyManagers.py
 11 10 3
def reorder_actions()
in DownstreamRL/TrainZPolicyRL.py
 5 10 2
def __init__()
in Experiments/PolicyNetworks.py
 30 9 5
def forward()
in Experiments/PolicyNetworks.py
 53 9 4
def forward()
in Experiments/PolicyNetworks.py
 55 9 4
def __init__()
in Experiments/PolicyNetworks.py
 13 9 6
def evaluate()
in Experiments/PolicyManagers.py
 19 9 2
def __init__()
in Experiments/Roboturk_DataLoader.py
 13 9 2
def run()
in Experiments/Master.py
 27 9 1
def get_prior_value()
in Experiments/PolicyNetworks.py
 22 8 3
def __init__()
in Experiments/PolicyNetworks.py
 22 8 6