aws / amazon-sagemaker-clarify - Conditional Complexity

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 119 units with 776 lines of code in units (51.0% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
3 medium complex units (86 lines of code)
3 simple units (40 lines of code)
113 very simple units (650 lines of code)

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

3D view of all units

Conditional Complexity per Extension

51+

26-50

11-25

6-10

1-5

Conditional Complexity per Logical Component

primary logical decomposition

51+

26-50

11-25

6-10

1-5

Most Complex Units

Top 50 most complex units

Unit	# lines	McCabe index	# params
def FT() in src/smclarify/bias/metrics/posttraining.py	40	20	3
def series_datatype() in src/smclarify/bias/metrics/common.py	23	18	2
def convert_positive_label_values() in src/smclarify/bias/metrics/common.py	23	14	4
def collapse_to_binary() in src/smclarify/util/__init__.py	6	10	2
def pdfs_aligned_nonzero() in src/smclarify/util/__init__.py	19	8	1
def ensure_series_data_type() in src/smclarify/bias/metrics/common.py	15	7	2
def divide() in src/smclarify/bias/metrics/common.py	8	5	2
def fetch_metrics_to_run() in src/smclarify/bias/report.py	6	5	3
def JS() in src/smclarify/bias/metrics/pretraining.py	10	4	2
def __register() in src/smclarify/bias/metrics/registry.py	7	4	2
def _interval_index() in src/smclarify/bias/report.py	9	4	2
def model_performance_report() in src/smclarify/bias/report.py	35	4	3
def CI() in src/smclarify/bias/metrics/pretraining.py	13	3	2
def KL() in src/smclarify/bias/metrics/pretraining.py	10	3	2
def LP_norm() in src/smclarify/bias/metrics/pretraining.py	9	3	3
def all_metrics() in src/smclarify/bias/metrics/registry.py	4	3	0
def FlipSet_pos() in src/smclarify/bias/metrics/posttraining.py	2	3	3
def FlipSet_neg() in src/smclarify/bias/metrics/posttraining.py	2	3	3
def FlipSet() in src/smclarify/bias/metrics/posttraining.py	2	3	3
def DPL() in src/smclarify/bias/metrics/common.py	15	3	3
def GE() in src/smclarify/bias/metrics/common.py	18	3	3
def inf_as_str() in src/smclarify/bias/report.py	4	3	1
def _categorical_data_idx() in src/smclarify/bias/report.py	11	3	2
def url_is_remote() in src/smclarify/util/dataset.py	5	3	1
def ensure_local() in src/smclarify/util/dataset.py	7	3	1
def changed() in src/smclarify/util/dataset.py	7	3	3
def run_examples() in scripts/run_examples.py	5	2	0
def call_metric() in src/smclarify/bias/metrics/__init__.py	2	2	3
def metric_one_vs_all() in src/smclarify/bias/metrics/__init__.py	6	2	4
def require() in src/smclarify/bias/metrics/common.py	3	2	2
def metric_description() in src/smclarify/bias/metrics/common.py	4	2	2
def problem_type() in src/smclarify/bias/report.py	6	2	1
def _column_list_to_str() in src/smclarify/bias/report.py	3	2	1
def label_value_or_threshold() in src/smclarify/bias/report.py	8	2	2
def GaussianFilter() in src/smclarify/util/__init__.py	9	2	2
def test() in src/smclarify/util/dataset.py	2	2	1
def train() in src/smclarify/util/dataset.py	3	2	1
def run_notebook() in scripts/run_examples.py	3	1	1
def script_name() in scripts/run_examples.py	2	1	0
def config_logging() in scripts/run_examples.py	5	1	0
def main() in scripts/run_examples.py	4	1	0
def confusion_matrix() in src/smclarify/bias/metrics/basic_stats.py	5	1	0
def proportion() in src/smclarify/bias/metrics/basic_stats.py	3	1	1
def observed_label_distribution() in src/smclarify/bias/metrics/basic_stats.py	2	1	0
def accuracy() in src/smclarify/bias/metrics/basic_stats.py	3	1	4
def PPL() in src/smclarify/bias/metrics/basic_stats.py	3	1	4
def PNL() in src/smclarify/bias/metrics/basic_stats.py	3	1	4
def recall() in src/smclarify/bias/metrics/basic_stats.py	3	1	2
def specificity() in src/smclarify/bias/metrics/basic_stats.py	3	1	2
def precision() in src/smclarify/bias/metrics/basic_stats.py	3	1	2