apache / sdap-nexus - 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 980 units with 16,057 lines of code in units (72.3% of code).

0 very complex units (0 lines of code)
5 complex units (567 lines of code)
55 medium complex units (3,692 lines of code)
140 simple units (4,314 lines of code)
780 very simple units (7,484 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 parse_args() in analysis/webservice/algorithms/Tomogram.py	88	41	2
def parse_args() in analysis/webservice/algorithms/Tomogram.py	88	41	2
def calc() in analysis/webservice/algorithms_spark/VarianceSpark.py	118	29	3
def pull_source() in tools/build/build.py	165	29	2
def calc() in analysis/webservice/algorithms_spark/MaximaMinimaSpark.py	108	27	3
def calc() in analysis/webservice/algorithms_spark/ClimMapSpark.py	99	25	3
def calc() in analysis/webservice/algorithms/Tomogram.py	116	25	3
def main() in tools/build/build.py	179	25	0
def calc() in analysis/webservice/algorithms_spark/CorrMapSpark.py	98	24	3
def __packValues() in analysis/webservice/algorithms/doms/BaseDomsHandler.py	38	24	2
def parse_args() in analysis/webservice/algorithms/Tomogram.py	75	24	2
def calc() in analysis/webservice/algorithms_spark/TimeAvgMapSpark.py	104	23	3
def _metadata_store_docs_to_tiles() in data-access/nexustiles/backends/nexusproto/backend.py	89	23	2
def _metadata_store_docs_to_tiles() in data-access/nexustiles/nexustiles.py	89	23	2
def calc() in analysis/webservice/algorithms/Tomogram.py	92	22	3
def calc() in analysis/webservice/algorithms/Tomogram.py	92	22	3
def calc() in analysis/webservice/algorithms/CorrelationMap.py	52	22	3
def generate() in analysis/webservice/algorithms/MapFetchHandler.py	82	22	11
def calc() in analysis/webservice/algorithms/DataInBoundsSearch.py	85	20	3
def get_lat_lon_time_data_meta() in data-access/nexustiles/backends/nexusproto/dao/CassandraProxy.py	95	20	1
def writeGroup() in analysis/webservice/algorithms/doms/BaseDomsHandler.py	39	18	1
def __getSatNodeForLatLonAndTime() in analysis/webservice/algorithms/doms/MatchupQuery.py	50	18	7
def parse_args() in analysis/webservice/algorithms/Tomogram3D.py	99	18	2
def getTimeSeriesStatsForBoxSingleDataSet() in analysis/webservice/algorithms/TimeSeries.py	77	18	7
def main() in tools/domspurge/purge.py	61	18	6
def do_subset() in analysis/webservice/algorithms/Tomogram.py	63	17	5
def calc() in analysis/webservice/algorithms/doms/subsetter.py	102	16	3
def calc() in analysis/webservice/algorithms_spark/TimeSeriesSpark.py	107	15	3
def calc_average_on_day() in analysis/webservice/algorithms_spark/TimeSeriesSpark.py	74	15	6
def from_edge_point() in analysis/webservice/algorithms_spark/Matchup.py	99	15	1
def get_elevation_args() in analysis/webservice/webmodel/NexusRequestObject.py	29	15	1
def createTimeSeries() in analysis/webservice/plotting.py	34	15	3
def main() in tools/doms-data-tools/update_doms_data_pk.py	146	15	0
def _merge_kwargs() in data-access/nexustiles/backends/nexusproto/dao/SolrProxy.py	42	15	2
def __getSatNodeForLatLonAndTime__() in analysis/webservice/algorithms/doms/MatchupQuery.py	48	14	6
def tile_data() in data-access/nexustiles/nexustiles.py	35	14	1
def from_edge_point() in analysis/webservice/algorithms_spark/MatchupDoms.py	49	13	1
def calc() in analysis/webservice/algorithms/doms/StacCatalog.py	48	13	3
def __doQuery() in analysis/webservice/algorithms/doms/fetchedgeimpl.py	42	13	10
def toImage() in analysis/webservice/algorithms/Tomogram.py	87	13	2
def __plot_to_images() in analysis/webservice/algorithms/Tomogram.py	87	13	2
def assemble_matches_by_primary() in tools/cdms/cdms_reader.py	43	13	1
def time_series() in integrations/python-client/nexuscli/nexuscli.py	57	13	5
def createLinePlot() in analysis/webservice/algorithms_spark/TimeSeriesSpark.py	41	12	1
def createLinePlot() in analysis/webservice/algorithms/TimeSeriesSolr.py	40	12	1
def calculate_monthly_average() in analysis/webservice/algorithms/TimeSeries.py	52	12	4
def createLinePlot() in analysis/webservice/algorithms/TimeSeries.py	40	12	1
def _find_native_resolution() in analysis/webservice/algorithms/TimeAvgMap.py	31	12	1
def __fetch_data_for_tile() in data-access/nexustiles/backends/zarr/backend.py	46	12	2
def _update_datasets() in data-access/nexustiles/nexustiles.py	48	12	0