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|
| import argparse |
| import os |
| try: |
| import simplejson as json |
| except ImportError: |
| import json |
|
|
| from nab.runner import Runner |
| from nab.util import (detectorNameToClass, checkInputs) |
|
|
|
|
|
|
| def getDetectorClassConstructors(detectors): |
| """ |
| Takes in names of detectors. Collects class names that correspond to those |
| detectors and returns them in a dict. The dict maps detector name to class |
| names. Assumes the detectors have been imported. |
| """ |
| detectorConstructors = { |
| d : globals()[detectorNameToClass(d)] for d in detectors} |
|
|
| return detectorConstructors |
|
|
|
|
| def main(args): |
| |
| root = os.path.dirname(os.path.realpath(__file__)) |
|
|
| numCPUs = int(args.numCPUs) if args.numCPUs is not None else None |
|
|
| dataDir = os.path.join(root, args.dataDir) |
| windowsFile = os.path.join(root, args.windowsFile) |
| resultsDir = os.path.join(root, args.resultsDir) |
| profilesFile = os.path.join(root, args.profilesFile) |
| thresholdsFile = os.path.join(root, args.thresholdsFile) |
| |
| runner = Runner(dataDir=dataDir, |
| labelPath=windowsFile, |
| resultsDir=resultsDir, |
| profilesPath=profilesFile, |
| thresholdPath=thresholdsFile, |
| numCPUs=numCPUs) |
|
|
| runner.initialize() |
|
|
| if args.detect: |
| detectorConstructors = getDetectorClassConstructors(args.detectors) |
| runner.detect(detectorConstructors) |
|
|
| if args.optimize: |
| runner.optimize(args.detectors) |
|
|
| if args.score: |
| with open(args.thresholdsFile) as thresholdConfigFile: |
| detectorThresholds = json.load(thresholdConfigFile) |
| runner.score(args.detectors, detectorThresholds) |
|
|
| if args.normalize: |
| try: |
| runner.normalize() |
| except AttributeError("Error: you must run the scoring step with the " |
| "normalization step."): |
| return |
|
|
|
|
| if __name__ == "__main__": |
|
|
| parser = argparse.ArgumentParser() |
|
|
| parser.add_argument("--detect", |
| help="Generate detector results but do not analyze results " |
| "files.", |
| default=False, |
| action="store_true") |
|
|
| parser.add_argument("--optimize", |
| help="Optimize the thresholds for each detector and user " |
| "profile combination", |
| default=False, |
| action="store_true") |
|
|
| parser.add_argument("--score", |
| help="Analyze results in the results directory", |
| default=False, |
| action="store_true") |
|
|
| parser.add_argument("--normalize", |
| help="Normalize the final scores", |
| default=False, |
| action="store_true") |
| |
| parser.add_argument("--skipConfirmation", |
| help="If specified will skip the user confirmation step", |
| default=False, |
| action="store_true") |
|
|
| parser.add_argument("--dataDir", |
| default="data", |
| help="This holds all the label windows for the corpus.") |
|
|
| parser.add_argument("--resultsDir", |
| default="results", |
| help="This will hold the results after running detectors " |
| "on the data") |
|
|
| parser.add_argument("--windowsFile", |
| default=os.path.join("labels", "combined_windows.json"), |
| help="JSON file containing ground truth labels for the " |
| "corpus.") |
| |
| parser.add_argument("-d", "--detectors", |
| nargs="*", |
| type=str, |
| default=["null", "numenta", "random", "skyline"], |
| help="Comma separated list of detector(s) to use, e.g. " |
| "null,numenta") |
| |
| parser.add_argument("-p", "--profilesFile", |
| default=os.path.join("config", "profiles.json"), |
| help="The configuration file to use while running the " |
| "benchmark.") |
|
|
| parser.add_argument("-t", "--thresholdsFile", |
| default=os.path.join("config", "thresholds.json"), |
| help="The configuration file that stores thresholds for " |
| "each combination of detector and username") |
|
|
| parser.add_argument("-n", "--numCPUs", |
| default=None, |
| help="The number of CPUs to use to run the " |
| "benchmark. If not specified all CPUs will be used.") |
|
|
| args = parser.parse_args() |
| |
| if (not args.detect |
| and not args.optimize |
| and not args.score |
| and not args.normalize): |
| args.detect = True |
| args.optimize = True |
| args.score = True |
| args.normalize = True |
|
|
| if len(args.detectors) == 1: |
| |
| args.detectors = args.detectors[0].split(',') |
|
|
| |
| |
| |
| if "numenta" in args.detectors: |
| from nab.detectors.numenta.numenta_detector import NumentaDetector |
| from nab.detectors.skyline.skyline_detector import SkylineDetector |
| from nab.detectors.random.random_detector import RandomDetector |
| from nab.detectors.null.null_detector import NullDetector |
| from nab.detectors.democratic.democratic_detector import DemocraticDetector |
|
|
| if args.skipConfirmation or checkInputs(args): |
| main(args) |
| |
|
|
