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1# LSST Data Management System
2# Copyright 2008-2019 AURA/LSST.
3#
4# This product includes software developed by the
5# LSST Project (http://www.lsst.org/).
6#
7# This program is free software: you can redistribute it and/or modify
8# it under the terms of the GNU General Public License as published by
9# the Free Software Foundation, either version 3 of the License, or
10# (at your option) any later version.
11#
12# This program is distributed in the hope that it will be useful,
13# but WITHOUT ANY WARRANTY; without even the implied warranty of
14# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15# GNU General Public License for more details.
16#
17# You should have received a copy of the LSST License Statement and
18# the GNU General Public License along with this program. If not,
19# see <https://www.lsstcorp.org/LegalNotices/>.
20"""Main driver functions for metric measurements, plotting, specification
21grading, and persistence.
22"""
24__all__ = ['plot_metrics', 'print_metrics', 'print_pass_fail_summary',
25 'run', 'runOneFilter']
27import json
28import os
29import numpy as np
30import astropy.units as u
32from textwrap import TextWrapper
33import astropy.visualization
35from lsst.verify import Name
36from lsst.verify import Job, MetricSet, SpecificationSet
37from lsst import log
38from lsst.daf.persistence import Butler
40from .util import repoNameToPrefix
41from .matchreduce import build_matched_dataset
42from .photerrmodel import build_photometric_error_model
43from .astromerrmodel import build_astrometric_error_model
44from .calcnonsrd import measure_model_phot_rep
45from .calcsrd import (measurePA1, measurePA2, measurePF1, measureAMx,
46 measureAFx, measureADx, measureTEx)
47from .plot import (plotAMx, plotPA1, plotTEx, plotPhotometryErrorModel,
48 plotAstrometryErrorModel)
51class Bcolors:
52 HEADER = '\033[95m'
53 OKBLUE = '\033[94m'
54 OKGREEN = '\033[92m'
55 WARNING = '\033[93m'
56 FAIL = '\033[91m'
57 ENDC = '\033[0m'
58 BOLD = '\033[1m'
59 UNDERLINE = '\033[4m'
62def load_json_output(filepath, metrics_package='verify_metrics'):
63 """Read JSON from a file into a job object.
65 Currently just does a trivial de-serialization with no checking
66 to make sure that one results with a valid validate.base.job object.
68 Parameters
69 ----------
70 filepath : `str`
71 Source file name for JSON output.
73 Returns
74 -------
75 job : A `validate.base.job` object.
76 """
77 with open(filepath, 'r') as infile:
78 json_data = json.load(infile)
80 job = Job.deserialize(**json_data)
81 metrics = MetricSet.load_metrics_package(metrics_package)
82 job.metrics.update(metrics)
83 specs = SpecificationSet.load_metrics_package(metrics_package)
84 job.specs.update(specs)
85 return job
88def get_filter_name_from_job(job):
89 """Get the filtername from a validate.base.job object
91 Assumes there is only one filter name and that it's the one in
92 the first measurement
94 Parameters
95 ----------
96 job : `validate.base.job` object
98 Returns
99 -------
100 filter_name : `str`
101 """
103 return job.meta['filter_name']
106def run(repo_or_json, outputPrefix=None, makePrint=True, makePlot=True,
107 level='design', metrics_package='verify_metrics', **kwargs):
108 """Main entrypoint from ``validateDrp.py``.
110 Parameters
111 ----------
112 repo_or_json : `str`
113 The repository. This is generally the directory on disk
114 that contains the repository and mapper.
115 This can also be the filepath for a JSON file that contains
116 the cached output from a previous run.
117 makePrint : `bool`, optional
118 Print calculated quantities (to stdout).
119 makePlot : `bool`, optional
120 Create plots for metrics. Saved to current working directory.
121 level : `str`
122 Use <level> E.g., 'design', 'minimum', 'stretch'.
123 """
124 base_name, ext = os.path.splitext(repo_or_json)
125 if ext == '.json':
126 load_json = True
127 else:
128 load_json = False
130 # I think I have to interrogate the kwargs to maintain compatibility
131 # between Python 2 and Python 3
132 # In Python 3 I would have let me mix in a keyword default after *args
133 if outputPrefix is None:
134 outputPrefix = repoNameToPrefix(base_name)
136 if load_json:
137 if not os.path.isfile(repo_or_json):
138 print("Could not find JSON file %s" % (repo_or_json))
139 return
141 json_path = repo_or_json
142 job = load_json_output(json_path, metrics_package)
143 filterName = get_filter_name_from_job(job)
144 jobs = {filterName: job}
145 else:
146 if not os.path.isdir(repo_or_json):
147 print("Could not find repo %s" % (repo_or_json))
148 return
150 repo_path = repo_or_json
151 jobs = runOneRepo(repo_path, outputPrefix=outputPrefix,
152 metrics_package=metrics_package, **kwargs)
154 for filterName, job in jobs.items():
155 if makePrint:
156 print_metrics(job)
157 if makePlot:
158 if outputPrefix is None or outputPrefix == '':
159 thisOutputPrefix = "%s" % filterName
160 else:
161 thisOutputPrefix = "%s_%s" % (outputPrefix, filterName)
162 plot_metrics(job, filterName, outputPrefix=thisOutputPrefix)
164 print_pass_fail_summary(jobs, default_level=level)
167def runOneRepo(repo, dataIds=None, outputPrefix='', verbose=False,
168 instrument=None, dataset_repo_url=None,
169 metrics_package='verify_metrics', **kwargs):
170 r"""Calculate statistics for all filters in a repo.
172 Runs multiple filters, if necessary, through repeated calls to `runOneFilter`.
173 Assesses results against SRD specs at specified `level`.
175 Parameters
176 ---------
177 repo : `str`
178 The repository. This is generally the directory on disk
179 that contains the repository and mapper.
180 dataIds : `list` of `dict`
181 List of butler data IDs of Image catalogs to compare to reference.
182 The calexp cpixel image is needed for the photometric calibration.
183 Tract IDs must be included if "doApplyExternalPhotoCalib" or
184 "doApplyExternalSkyWcs" is True.
185 outputPrefix : `str`, optional
186 Specify the beginning filename for output files.
187 The name of each filter will be appended to outputPrefix.
188 level : `str`, optional
189 The level of the specification to check: "design", "minimum", "stretch".
190 verbose : `bool`
191 Provide detailed output.
192 instrument : `str`
193 Name of the instrument. If None will be extracted from the Butler mapper.
194 dataset_repo_url : `str`
195 Location of the dataset used. If None will be set to the path of the repo.
196 metrics_package : `string`
197 Name of the metrics package to be used in the Jobs created.
199 Notes
200 -----
201 Names of plot files or JSON file are generated based on repository name,
202 unless overriden by specifying `ouputPrefix`.
203 E.g., Analyzing a repository ``CFHT/output``
204 will result in filenames that start with ``CFHT_output_``.
205 The filter name is added to this prefix. If the filter name has spaces,
206 there will be annoyance and sadness as those spaces will appear in the filenames.
207 """
209 def extract_instrument_from_repo(repo):
210 """Extract the last part of the mapper name from a Butler repo.
211 'lsst.obs.lsstSim.lsstSimMapper.LsstSimMapper' -> 'LSSTSIM'
212 'lsst.obs.cfht.megacamMapper.MegacamMapper' -> 'CFHT'
213 'lsst.obs.decam.decamMapper.DecamMapper' -> 'DECAM'
214 'lsst.obs.hsc.hscMapper.HscMapper' -> 'HSC'
215 """
216 mapper_class = Butler.getMapperClass(repo)
217 instrument = mapper_class.getCameraName()
218 return instrument.upper()
220 if instrument is None:
221 instrument = extract_instrument_from_repo(repo)
222 if dataset_repo_url is None:
223 dataset_repo_url = repo
225 allFilters = set([d['filter'] for d in dataIds])
227 jobs = {}
228 for filterName in allFilters:
229 # Do this here so that each outputPrefix will have a different name for each filter.
230 if outputPrefix is None or outputPrefix == '':
231 thisOutputPrefix = "%s" % filterName
232 else:
233 thisOutputPrefix = "%s_%s" % (outputPrefix, filterName)
234 theseVisitDataIds = [v for v in dataIds if v['filter'] == filterName]
235 job = runOneFilter(repo, theseVisitDataIds,
236 outputPrefix=thisOutputPrefix,
237 verbose=verbose, filterName=filterName,
238 instrument=instrument,
239 dataset_repo_url=dataset_repo_url,
240 metrics_package=metrics_package, **kwargs)
241 jobs[filterName] = job
243 return jobs
246def runOneFilter(repo, visitDataIds, brightSnrMin=None, brightSnrMax=None,
247 makeJson=True, filterName=None, outputPrefix='',
248 doApplyExternalPhotoCalib=False, externalPhotoCalibName=None,
249 doApplyExternalSkyWcs=False, externalSkyWcsName=None,
250 skipTEx=False, verbose=False,
251 metrics_package='verify_metrics',
252 instrument='Unknown', dataset_repo_url='./',
253 skipNonSrd=False, **kwargs):
254 r"""Main executable for the case where there is just one filter.
256 Plot files and JSON files are generated in the local directory
257 prefixed with the repository name (where '_' replace path separators),
258 unless overriden by specifying `outputPrefix`.
259 E.g., Analyzing a repository ``CFHT/output``
260 will result in filenames that start with ``CFHT_output_``.
262 Parameters
263 ----------
264 repo : string or Butler
265 A Butler or a repository URL that can be used to construct one.
266 dataIds : list of dict
267 List of `butler` data IDs of Image catalogs to compare to reference.
268 The `calexp` pixel image is needed for the photometric calibration
269 unless doApplyExternalPhotoCalib is True such
270 that the appropriate `photoCalib` dataset is used. Note that these
271 have data IDs that include the tract number.
272 brightSnrMin : float, optional
273 Minimum median SNR for a source to be considered bright; passed to
274 `lsst.validate.drp.matchreduce.build_matched_dataset`.
275 brightSnrMax : float, optional
276 Maximum median SNR for a source to be considered bright; passed to
277 `lsst.validate.drp.matchreduce.build_matched_dataset`.
278 makeJson : bool, optional
279 Create JSON output file for metrics. Saved to current working directory.
280 outputPrefix : str, optional
281 Specify the beginning filename for output files.
282 filterName : str, optional
283 Name of the filter (bandpass).
284 doApplyExternalPhotoCalib : bool, optional
285 Apply external photoCalib to calibrate fluxes.
286 externalPhotoCalibName : str, optional
287 Type of external `PhotoCalib` to apply. Currently supported are jointcal,
288 fgcm, and fgcm_tract. Must be set if doApplyExternalPhotoCalib is True.
289 doApplyExternalSkyWcs : bool, optional
290 Apply external wcs to calibrate positions.
291 externalSkyWcsName : str, optional
292 Type of external `wcs` to apply. Currently supported is jointcal.
293 Must be set if "doApplyExternalSkyWcs" is True.
294 skipTEx : bool, optional
295 Skip TEx calculations (useful for older catalogs that don't have
296 PsfShape measurements).
297 verbose : bool, optional
298 Output additional information on the analysis steps.
299 skipNonSrd : bool, optional
300 Skip any metrics not defined in the LSST SRD.
302 Raises
303 ------
304 RuntimeError:
305 Raised if "doApplyExternalPhotoCalib" is True and "externalPhotoCalibName"
306 is None, or if "doApplyExternalSkyWcs" is True and "externalSkyWcsName" is
307 None.
308 """
310 if kwargs:
311 log.warn(f"Extra kwargs - {kwargs}, will be ignored. Did you add extra things to your config file?")
313 if doApplyExternalPhotoCalib and externalPhotoCalibName is None:
314 raise RuntimeError("Must set externalPhotoCalibName if doApplyExternalPhotoCalib is True.")
315 if doApplyExternalSkyWcs and externalSkyWcsName is None:
316 raise RuntimeError("Must set externalSkyWcsName if doApplyExternalSkyWcs is True.")
318 job = Job.load_metrics_package(meta={'instrument': instrument,
319 'filter_name': filterName,
320 'dataset_repo_url': dataset_repo_url},
321 subset='validate_drp',
322 package_name_or_path=metrics_package)
324 matchedDataset = build_matched_dataset(repo, visitDataIds,
325 doApplyExternalPhotoCalib=doApplyExternalPhotoCalib,
326 externalPhotoCalibName=externalPhotoCalibName,
327 doApplyExternalSkyWcs=doApplyExternalSkyWcs,
328 externalSkyWcsName=externalSkyWcsName,
329 skipTEx=skipTEx, skipNonSrd=skipNonSrd,
330 brightSnrMin=brightSnrMin, brightSnrMax=brightSnrMax)
332 photomModel = build_photometric_error_model(matchedDataset)
333 astromModel = build_astrometric_error_model(matchedDataset)
335 linkedBlobs = [matchedDataset, photomModel, astromModel]
337 metrics = job.metrics
338 specs = job.specs
340 def add_measurement(measurement):
341 for blob in linkedBlobs:
342 measurement.link_blob(blob)
343 job.measurements.insert(measurement)
345 for x, D in zip((1, 2, 3), (5., 20., 200.)):
346 amxName = 'AM{0:d}'.format(x)
347 afxName = 'AF{0:d}'.format(x)
348 adxName = 'AD{0:d}'.format(x)
350 amx = measureAMx(metrics['validate_drp.'+amxName], matchedDataset, D*u.arcmin, verbose=verbose)
351 add_measurement(amx)
353 afx_spec_set = specs.subset(required_meta={'instrument': 'HSC'}, spec_tags=[afxName, ])
354 adx_spec_set = specs.subset(required_meta={'instrument': 'HSC'}, spec_tags=[adxName, ])
355 for afx_spec_key, adx_spec_key in zip(afx_spec_set, adx_spec_set):
356 afx_spec = afx_spec_set[afx_spec_key]
357 adx_spec = adx_spec_set[adx_spec_key]
358 adx = measureADx(metrics[adx_spec.metric_name], amx, afx_spec)
359 add_measurement(adx)
360 afx = measureAFx(metrics[afx_spec.metric_name], amx, adx, adx_spec)
361 add_measurement(afx)
363 pa1 = measurePA1(
364 metrics['validate_drp.PA1'], filterName, matchedDataset.matchesBright, matchedDataset.magKey)
365 add_measurement(pa1)
367 pf1_spec_set = specs.subset(required_meta={'instrument': instrument, 'filter_name': filterName},
368 spec_tags=['PF1', ])
369 pa2_spec_set = specs.subset(required_meta={'instrument': instrument, 'filter_name': filterName},
370 spec_tags=['PA2', ])
371 # I worry these might not always be in the right order. Sorting...
372 pf1_spec_keys = list(pf1_spec_set.keys())
373 pa2_spec_keys = list(pa2_spec_set.keys())
374 pf1_spec_keys.sort()
375 pa2_spec_keys.sort()
376 for pf1_spec_key, pa2_spec_key in zip(pf1_spec_keys, pa2_spec_keys):
377 pf1_spec = pf1_spec_set[pf1_spec_key]
378 pa2_spec = pa2_spec_set[pa2_spec_key]
380 pa2 = measurePA2(metrics[pa2_spec.metric_name], pa1, pf1_spec.threshold)
381 add_measurement(pa2)
383 pf1 = measurePF1(metrics[pf1_spec.metric_name], pa1, pa2_spec)
384 add_measurement(pf1)
386 if not skipTEx:
387 for x, D, bin_range_operator in zip((1, 2), (1.0, 5.0), ("<=", ">=")):
388 texName = 'TE{0:d}'.format(x)
389 tex = measureTEx(metrics['validate_drp.'+texName], matchedDataset, D*u.arcmin,
390 bin_range_operator, verbose=verbose)
391 add_measurement(tex)
393 if not skipNonSrd:
394 model_phot_reps = measure_model_phot_rep(metrics, filterName, matchedDataset)
395 for measurement in model_phot_reps:
396 add_measurement(measurement)
398 if makeJson:
399 job.write(outputPrefix+'.json')
401 return job
404def get_metric(level, metric_label, in_specs):
405 for spec in in_specs:
406 if level in str(spec) and metric_label in str(spec):
407 break
408 return Name(package=spec.package, metric=spec.metric)
411def plot_metrics(job, filterName, outputPrefix=''):
412 """Plot AM1, AM2, AM3, PA1 plus related informational plots.
414 Parameters
415 ----------
416 job : `lsst.validate.base.Job`
417 The job to load data from.
418 filterName : `str`
419 string identifying the filter.
420 """
421 astropy.visualization.quantity_support()
423 specs = job.specs
424 measurements = job.measurements
425 spec_name = 'design'
426 for x in (1, 2, 3):
427 amxName = 'AM{0:d}'.format(x)
428 afxName = 'AF{0:d}'.format(x)
429 # ADx is included on the AFx plots
431 amx = measurements[get_metric(spec_name, amxName, specs)]
432 afx = measurements[get_metric(spec_name, afxName, specs)]
434 if amx.quantity is not None:
435 try:
436 plotAMx(job, amx, afx, filterName, amxSpecName=spec_name,
437 outputPrefix=outputPrefix)
438 except RuntimeError as e:
439 print(e)
440 print('\tSkipped plot{}'.format(amxName))
442 try:
443 pa1 = measurements[get_metric(spec_name, 'PA1', specs)]
444 plotPA1(pa1, outputPrefix=outputPrefix)
445 except RuntimeError as e:
446 print(e)
447 print('\tSkipped plotPA1')
449 try:
450 matchedDataset = pa1.blobs['MatchedMultiVisitDataset']
451 photomModel = pa1.blobs['PhotometricErrorModel']
452 filterName = pa1.extras['filter_name']
453 plotPhotometryErrorModel(matchedDataset, photomModel,
454 filterName=filterName,
455 outputPrefix=outputPrefix)
456 except KeyError as e:
457 print(e)
458 print('\tSkipped plotPhotometryErrorModel')
460 try:
461 am1 = measurements[get_metric(spec_name, 'AM1', specs)]
462 matchedDataset = am1.blobs['MatchedMultiVisitDataset']
463 astromModel = am1.blobs['AnalyticAstrometryModel']
464 plotAstrometryErrorModel(matchedDataset, astromModel,
465 outputPrefix=outputPrefix)
466 except KeyError as e:
467 print(e)
468 print('\tSkipped plotAstrometryErrorModel')
470 for x in (1, 2):
471 texName = 'TE{0:d}'.format(x)
473 try:
474 measurement = measurements[get_metric(spec_name, texName, specs)]
475 plotTEx(job, measurement, filterName,
476 texSpecName='design',
477 outputPrefix=outputPrefix)
478 except (RuntimeError, KeyError) as e:
479 print(e)
480 print('\tSkipped plot{}'.format(texName))
483def get_specs_metrics(job):
484 # Get specs for this filter
485 subset = job.specs.subset(required_meta={'instrument': job.meta['instrument'],
486 'filter_name': job.meta['filter_name']},
487 spec_tags=['chromatic'])
488 # Get specs that don't depend on filter
489 subset.update(job.specs.subset(required_meta={'instrument': job.meta['instrument']},
490 spec_tags=['achromatic']))
491 metrics = {}
492 specs = {}
493 for spec in subset:
494 metric_name = spec.metric.split('_')[0] # Take first part for linked metrics
495 if metric_name in metrics:
496 metrics[metric_name].append(Name(package=spec.package, metric=spec.metric))
497 specs[metric_name].append(spec)
498 else:
499 metrics[metric_name] = [Name(package=spec.package, metric=spec.metric), ]
500 specs[metric_name] = [spec, ]
501 return specs, metrics
504def print_metrics(job, levels=('minimum', 'design', 'stretch')):
505 specs, metrics = get_specs_metrics(job)
507 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
508 print(Bcolors.BOLD + Bcolors.HEADER +
509 '{band} band metric measurements'.format(band=job.meta['filter_name']) +
510 Bcolors.ENDC)
511 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
513 wrapper = TextWrapper(width=65)
514 for metric_name, metric_set in metrics.items():
515 metric = job.metrics[metric_set[0]] # Pick the first one for the description
516 print(Bcolors.HEADER + '{name} - {reference}'.format(
517 name=metric.name, reference=metric.reference))
518 print(wrapper.fill(Bcolors.ENDC + '{description}'.format(
519 description=metric.description).strip()))
521 for spec_key, metric_key in zip(specs[metric_name], metrics[metric_name]):
522 level = None
523 if 'release' in job.specs[spec_key].tags:
524 # Skip release specs
525 continue
526 for l in levels:
527 if l in str(spec_key):
528 level = l
529 try:
530 m = job.measurements[metric_key]
531 except KeyError:
532 print('\tSkipped {metric_key:12s} with spec {spec}: no such measurement'.format(
533 metric_key=metric_name, spec=level))
534 continue
536 if np.isnan(m.quantity):
537 print('\tSkipped {metric_key:12s} no measurement'.format(
538 metric_key=".".join([metric_name, level])))
539 continue
541 spec = job.specs[spec_key]
542 passed = spec.check(m.quantity)
543 if passed:
544 prefix = Bcolors.OKBLUE + '\tPassed '
545 else:
546 prefix = Bcolors.FAIL + '\tFailed '
547 infoStr = '{specName:12s} {meas:.4g} {op} {spec:.4g}'.format(
548 specName=level,
549 meas=m.quantity,
550 op=spec.operator_str,
551 spec=spec.threshold)
552 print(prefix + infoStr + Bcolors.ENDC)
555def print_pass_fail_summary(jobs, levels=('minimum', 'design', 'stretch'), default_level='design'):
556 currentTestCount = 0
557 currentFailCount = 0
558 currentSkippedCount = 0
560 for filterName, job in jobs.items():
561 specs, metrics = get_specs_metrics(job)
562 print('')
563 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
564 print(Bcolors.BOLD + Bcolors.HEADER + '{0} band summary'.format(filterName) + Bcolors.ENDC)
565 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
567 for specName in levels:
568 measurementCount = 0
569 failCount = 0
570 skippedCount = 0
571 for key, m in job.measurements.items():
572 metric = key.metric.split("_") # For compound metrics
573 len_metric = len(metric)
574 if len_metric > 1:
575 if metric[1] != specName:
576 continue
577 if len_metric > 2 and filterName not in metric[2]:
578 continue
579 spec_set = specs.get(metric[0], None)
580 if spec_set is None:
581 continue
582 spec = None
583 for spec_key in spec_set:
584 if specName in spec_key.spec:
585 spec = job.specs[spec_key]
586 if spec is None:
587 for spec_key in spec_set:
588 if specName in spec_key.metric: # For dependent metrics
589 spec = job.specs[spec_key]
590 if spec is not None:
591 measurementCount += 1
592 if np.isnan(m.quantity):
593 skippedCount += 1
594 if not spec.check(m.quantity):
595 failCount += 1
597 if specName == default_level:
598 currentTestCount += measurementCount
599 currentFailCount += failCount
600 currentSkippedCount += skippedCount
602 if failCount == 0:
603 print('Passed {level:12s} {count:d} measurements ({skipped:d} skipped)'.format(
604 level=specName, count=measurementCount, skipped=skippedCount))
605 else:
606 msg = 'Failed {level:12s} {failCount} of {count:d} failed ({skipped:d} skipped)'.format(
607 level=specName, failCount=failCount, count=measurementCount, skipped=skippedCount)
608 print(Bcolors.FAIL + msg + Bcolors.ENDC)
610 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC + '\n')
612 # print summary against current spec level
613 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
614 print(Bcolors.BOLD + Bcolors.HEADER + '{0} level summary'.format(default_level) + Bcolors.ENDC)
615 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)
616 if currentFailCount > 0:
617 msg = 'FAILED ({failCount:d}/{count:d} measurements, ({skipped:d} skipped))'.format(
618 failCount=currentFailCount, count=currentTestCount, skipped=currentSkippedCount)
619 print(Bcolors.FAIL + msg + Bcolors.ENDC)
620 else:
621 print('PASSED ({count:d}/{count:d} measurements ({skipped:d} skipped))'.format(
622 count=currentTestCount, skipped=currentSkippedCount))
624 print(Bcolors.BOLD + Bcolors.HEADER + "=" * 65 + Bcolors.ENDC)