def _postAnalyze(self):
""" Write the logs. """
self._paths = []
self.logger.write(
'%s\nFRACTIONAL ERROR (Measured vs Entered)' % ('='*80))
self._process('Error', 'wDev', 'lDev', self.trackDeviations)
self.logger.write('%s\nFRACTIONAL UNCERTAINTY ERROR' % ('='*80))
self._process(
'Uncertainty Error', 'wDelta', 'lDelta', None, absoluteOnly=True)
csv = CsvWriter(
path=self.getPath('Length-Width-Deviations.csv'),
autoIndexFieldName='Index',
fields=[
('uid', 'UID'),
('fingerprint', 'Fingerprint'),
('wDelta', 'Width Deviation'),
('lDelta', 'Length Deviation') ])
for entry in self.entries:
track = entry['track']
csv.createRow(
uid=track.uid,
fingerprint=track.fingerprint,
wDelta=entry.get('wDelta', -1.0),
lDelta=entry.get('lDelta', -1.0) )
csv.save()
self._processAspectRatios()
self.mergePdfs(self._paths)
def _postAnalyze(self):
self.logger.write('%s gauge calculated tracks' % self._count)
self._trackwayCsv.save()
csv = CsvWriter(
path=self.getPath('Simple-Gauge-Errors.csv', isFile=True),
autoIndexFieldName='Index',
fields=[
('uid', 'UID'),
('fingerprint', 'Fingerprint') ])
for track in self._errorTracks:
csv.createRow(uid=track.uid, fingerprint=track.fingerprint)
csv.save()
if self._errorTracks:
self.logger.write('Failed to calculate gauge for %s tracks' % len(self._errorTracks))
csv = CsvWriter(
path=self.getPath('Simple-Gauge-Ignores.csv', isFile=True),
autoIndexFieldName='Index',
fields=[
('uid', 'UID'),
('fingerprint', 'Fingerprint') ])
for track in self._ignoreTracks:
csv.createRow(uid=track.uid, fingerprint=track.fingerprint)
csv.save()
if self._ignoreTracks:
self.logger.write('%s tracks lacked suitability for gauge calculation' % len(
self._ignoreTracks))
plotData = [
('stride', 'red', 'AU', 'Stride-Normalized Weighted'),
('pace', 'green', 'AU', 'Pace-Normalized Weighted'),
('width', 'blue', 'AU', 'Width-Normalized Weighted'),
('abs', 'purple', 'm', 'Absolute Unweighted') ]
for data in plotData:
out = []
source = ListUtils.sortListByIndex(
source=getattr(self._trackwayGauges, StringUtils.toStr2(data[0])),
index=0,
inPlace=True)
for item in source:
out.append(PositionValue2D(x=len(out), y=item[1].value, yUnc=item[1].uncertainty))
self._plotTrackwayGauges(out, *data[1:])
self.mergePdfs(self._paths, 'Gauges.pdf')
def _process(
self, label, widthKey, lengthKey, trackDeviations,
absoluteOnly =False
):
"""_process doc..."""
pl = self.plot
ws = []
ls = []
w2D = []
l2D = []
for entry in self.entries:
if widthKey in entry:
ws.append(entry[widthKey])
if lengthKey in entry:
w2D.append(entry[widthKey])
if lengthKey in entry:
ls.append(entry[lengthKey])
if widthKey in entry:
l2D.append(entry[lengthKey])
plotList = [
('widths', ws, 'Width', 'b'),
('lengths', ls, 'Length', 'r')]
wRes = NumericUtils.getMeanAndDeviation(ws)
self.logger.write('Width %ss' % wRes.label)
lRes = NumericUtils.getMeanAndDeviation(ls)
self.logger.write('Length %ss' % lRes.label)
for data in plotList:
if not absoluteOnly:
d = data[1]
self._paths.append(
self._makePlot(
label, d, data,
histRange=(-1.0, 1.0)))
self._paths.append(
self._makePlot(
label, d, data,
isLog=True,
histRange=(-1.0, 1.0)))
# noinspection PyUnresolvedReferences
d = np.absolute(np.array(data[1]))
self._paths.append(
self._makePlot(
'Absolute ' + label, d, data,
histRange=(0.0, 1.0)))
self._paths.append(
self._makePlot(
'Absolute ' + label, d, data,
isLog=True,
histRange=(0.0, 1.0)))
self.owner.createFigure('twoD')
pl.hist2d(w2D, l2D, bins=20, range=([-1, 1], [-1, 1]))
pl.title('2D %s Distribution' % label)
pl.xlabel('Width %s' % label)
pl.ylabel('Length %s' % label)
pl.xlim(-1.0, 1.0)
pl.ylim(-1.0, 1.0)
path = self.getTempPath(
'%s.pdf' % StringUtils.getRandomString(16),
isFile=True)
self.owner.saveFigure('twoD', path)
self._paths.append(path)
csv = CsvWriter()
csv.path = self.getPath(
'%s-Deviations.csv' % label.replace(' ', '-'),
isFile=True)
csv.addFields(
('uid', 'UID'),
('fingerprint', 'Fingerprint'),
('wSigma', 'Width Deviation'),
('lSigma', 'Length Deviation') )
count = 0
for entry in self.entries:
widthDevSigma = NumericUtils.roundToOrder(
abs(entry.get(widthKey, 0.0)/wRes.uncertainty), -2)
lengthDevSigma = NumericUtils.roundToOrder(
abs(entry.get(lengthKey, 0.0)/lRes.uncertainty), -1)
if widthDevSigma > 2.0 or lengthDevSigma > 2.0:
count += 1
track = entry['track']
data = dict(
wSigma=widthDevSigma,
lSigma=lengthDevSigma)
if trackDeviations is not None:
trackDeviations[track.uid] = data
csv.createRow(
uid=track.uid,
fingerprint=track.fingerprint,
**data)
if not csv.save():
self.logger.write(
'[ERROR]: Failed to save CSV file to %s' % csv.path)
percentage = NumericUtils.roundToOrder(
100.0*float(count)/float(len(self.entries)), -2)
self.logger.write('%s significant %ss (%s%%)' % (
count, label.lower(), percentage))
if percentage > (100.0 - 95.45):
self.logger.write(
'[WARNING]: Large deviation count exceeds' +
'normal distribution expectations.')
def write_to_file(trackway, tracks_data):
"""
@param trackway:
@param tracks_data:
@return:
"""
csv = CsvWriter(
path="{}.csv".format(trackway.name),
autoIndexFieldName="Index",
fields=[
"lp_name",
"lp_uid",
"lp_x",
"lp_dx",
"lp_y",
"lp_dy",
"lp_w",
"lp_dw",
"lp_l",
"lp_dl",
"rp_name",
"rp_uid",
"rp_x",
"rp_dx",
"rp_y",
"rp_dy",
"rp_w",
"rp_dw",
"rp_l",
"rp_dl",
"lm_name",
"lm_uid",
"lm_x",
"lm_dx",
"lm_y",
"lm_dy",
"lm_w",
"lm_dw",
"lm_l",
"lm_dl",
"rm_name",
"rm_uid",
"rm_x",
"rm_dx",
"rm_y",
"rm_dy",
"rm_w",
"rm_dw",
"rm_l",
"rm_dl",
],
)
count = max([len(ts) if ts else 0 for ts in tracks_data.values()])
for i in range(count):
entry = {}
for key in ["lp", "rp", "lm", "rm"]:
data = tracks_data[key][i] if i < len(tracks_data[key]) else None
track = data["track"] if data else None
entry.update(
{
"{}_name".format(key): track.fingerprint if track else "",
"{}_uid".format(key): track.uid if track else "",
}
)
point = track.positionValue if track else None
entry.update(
{
"{}_x".format(key): point.x if point else "",
"{}_dx".format(key): point.xUnc if point else "",
"{}_y".format(key): point.y if point else "",
"{}_dy".format(key): point.yUnc if point else "",
}
)
length = track.widthValue if track else None
entry.update(
{
"{}_l".format(key): length.value if length else "",
"{}_dl".format(key): length.uncertainty if length else "",
}
)
width = track.widthValue if track else None
entry.update(
{
"{}_w".format(key): width.value if width else "",
"{}_dw".format(key): width.uncertainty if width else "",
}
)
csv.createRow(**entry)
csv.save()