def _processSparsenessResults(self, key):
"""_processSparsenessResults doc..."""
index = 0
means = []
totals = []
twValues = []
tsValues = []
lows = dict(x=[], y=[], error=[], color='#666666')
mids = dict(x=[], y=[], error=[], color='#33CC33')
highs = dict(x=[], y=[], error=[], color='#CC3333')
for uid, entry in DictUtils.iter(self.data):
# For each test list in track ratings process the data and filter it into the correct
# segments for plotting.
data = (entry['pes'] + entry['manus']) if not key else entry[key]
data = ListUtils.sortObjectList(data, 'value')
index += 1
if len(data) < 2:
continue
average = NumericUtils.weightedAverage(*data[1:])
means.append(average)
totals.extend(data[1:])
twValues.append(average.value)
maxVal = data[0]
for v in data[1:]:
if v.value > maxVal.value:
maxVal = v
if maxVal.value < 15.0:
target = lows
elif maxVal.value < 50.0:
target = mids
else:
target = highs
for v in data[1:]:
tsValues.append(v.value)
target['x'].append(index)
target['y'].append(v.value)
target['error'].append(v.uncertainty)
return lows, mids, highs, tsValues, twValues, totals
def _calculateSparseness(cls, spacings, reference):
""" Calculates the relative sparseness from the series spacings list and the reference
spacing. """
out = []
for data in spacings:
# For each entry in the tests, normalize that value to the most complete (highest
# track count) series to create a relative sparseness rating
diff = data.value - reference.value
absDiff = abs(diff)
dVal = reference.value
sign = 0.0 if absDiff == 0.0 else diff/absDiff
unc = abs(data.uncertainty/dVal) + abs(dVal*sign - absDiff)/(dVal*dVal)
out.append(NumericUtils.toValueUncertainty(
value=100.0*absDiff/dVal,
uncertainty=100.0*unc))
return ListUtils.sortObjectList(out, 'value')
def _plotTrackwayGauges(self, points, color, unit, heading):
histData = []
for p in points:
histData.append(p.yValue.value)
plot = Histogram(
data=histData,
title='%s Trackway Gauges' % heading,
xLabel='Averaged Trackway Gauge (%s)' % unit,
yLabel='Frequency',
color=color)
self._paths.insert(0, plot.save(self.getTempFilePath(extension='pdf')))
plot = ScatterPlot(
data=ListUtils.sortObjectList(points, 'y', inPlace=True),
title='%s Trackway Gauges' % heading,
xLabel='Trackway Pes Count (#)',
yLabel='Averaged Trackway Gauge (%s)' % unit,
color=color)
self._paths.insert(0, plot.save(self.getTempFilePath(extension='pdf')))
