#==================================================================================================
# CREATE A GROUP CONTAINING A RECT, SHOWING HOW TO USE (INSTANCE) IT ROTATED AND TRANSLATED
drawing.createGroup('r1')
drawing.rect((0, 0), 10, 30, scene=False, groupId='r1') # add this rect to the group
drawing.use('r1', (400, 100), rotation=10, fill='blue')
drawing.use('r1', (400, 200), rotation=20, fill='blue')
drawing.use('r1', (400, 300), rotation=30, fill='blue')
drawing.use('r1', (400, 400), rotation=40, fill='blue')
drawing.use('r1', (400, 500), rotation=50, fill='blue')
#==================================================================================================
drawing.save()
#==================================================================================================
""" The general format for the command line invocation of inkscape is:
for PDF export:
inkscape -f sourceFile.svg -A destinationFile.pdf
or with the standard installation (without inkscape addd to the search path:
/Applications/Inkscape.app/Content/Resources/bin/inkscape -f sourceFile.svg -A destinationFile.pdf
for PNG export:
inkscape -f sourceFile.svg -e destinationFile.png
rot = math.radians(trackRotation)
z1 = lengthRatio*l
z2 = z1 - l
# draw the length line
drawing.line(
(x + z1*math.sin(rot), z + z1*math.cos(rot)),
(x + z2*math.sin(rot), z + z2*math.cos(rot)),
scene=True,
stroke='red',
stroke_width=2.0)
# draw the width line
x1 = w/2.0
x2 = -w/2.0
drawing.line(
(x + x1*math.cos(rot), z - x1*math.sin(rot)),
(x + x2*math.cos(rot), z - x2*math.sin(rot)),
scene=True,
stroke='blue',
stroke_width=2.0)
#drawing.federalCoordinates()
# drawing.grid(0.5)
drawing.save(toPDF=True)
session.close()
print 'Test Complete'
def _postAnalyze(self):
h = Histogram(
data=self._uncs,
binCount=80,
xLimits=(0, max(*self._uncs)),
color='r',
title='Distribution of Spatial (X, Z) Uncertainties',
xLabel='Uncertainty Value (m)',
yLabel='Frequency')
p1 = h.save(self.getTempFilePath(extension='pdf'))
h.isLog = True
h.title += ' (log)'
p2 = h.save(self.getTempFilePath(extension='pdf'))
self.mergePdfs([p1, p2], self.getPath('Spatial-Uncertainty-Distribution.pdf'))
average = NumericUtils.getMeanAndDeviation(self._uncs)
self.logger.write('Average spatial uncertainty: %s' % average.label)
#-------------------------------------------------------------------------------------------
# FIND LARGE UNCERTAINTY TRACKS
largeUncertaintyCount = 0
drawing = None
sitemap = None
# If track uncertainty is 2x average, add that track to the spreadsheet and map overlay
for t in self._tracks:
# if the tracksite has changed, save previous map and make a new one
if sitemap != t.trackSeries.trackway.sitemap:
# save the last site map drawing (if there was one)
if drawing:
drawing.save()
# then start a new drawing for this new site map
sitemap = t.trackSeries.trackway.sitemap
fileName = sitemap.name + "_" + sitemap.level + '_uncertainty.svg'
path = self.getPath(self.DRAWING_FOLDER_NAME, fileName, isFile=True)
drawing = CadenceDrawing(path, sitemap)
# create a group to be instanced for the spreadsheet values
drawing.createGroup('rect1')
# create a rectangle of 100x100 cm that is to be scaled by fractional meters
drawing.rect((0, 0), 100, 100, scene=True, groupId='rect1')
# create another group to be instanced for the mapped values.
drawing.createGroup('rect2')
# create a rectangle of 100x100 cm that is to be scaled by fractional meters
drawing.rect((0, 0), 100, 100, scene=True, groupId='rect2')
# and place a grid and the federal coordinates in the drawing file
drawing.grid()
drawing.federalCoordinates()
# now examine the positional uncertainties for this track
x = t.xValue
z = t.zValue
if x.uncertainty > 0.15 or z.uncertainty > 0.15:
# s = '%s%s %s%s: %s %s'% (
# t.site, t.level, t.trackwayType, t.trackwayNumber, t.name, t.uid)
# print('%s: (%s and %s)' % (s, x.uncertainty, z.uncertainty))
print('%s\t%s' % (t.uid, t.fingerprint))
if max(x.uncertainty, z.uncertainty) <= 2.0*average.uncertainty:
# then just indicate that this track has low uncertainty
self._drawLowUncertaintyMarker(drawing, t)
# label this track with green
drawing.text(
t.name,
(t.x - 20, t.z),
scene=True,
stroke='green',
stroke_width='0.25',
font_size='8px',
font_family='Arial')
continue
# else, since the uncertainty is high, first write that track in the spreadsheet
largeUncertaintyCount += 1
self._largeUncCsv.createRow(
uid=t.uid,
fingerprint=t.fingerprint,
x=x.label,
z=z.label)
# if either the measured width or length is 0, mark with a yellow disk with red outline
if t.widthMeasured == 0 or t.lengthMeasured == 0:
drawing.circle(
(t.x, t.z),
100*(t.widthUncertainty + t.lengthUncertainty)/2.0,
scene=True,
fill='yellow',
stroke='red')
drawing.text(
t.name,
(t.x - 20, t.z),
scene=True,
stroke='black',
stroke_width='0.25',
font_size='6px',
font_family='Arial')
continue
self._drawHighUncertaintyMarker(drawing, t)
# label this track with red
drawing.text(
t.name,
(t.x - 20, t.z),
scene=True,
stroke='red',
stroke_width='0.25',
font_size='6px',
font_family='Arial')
#
# # draw this track indicating it has high uncertainty
# drawing.use(
# 'rect1',
# (t.x, t.z),
# scene=True,
# rotation=t.rotation,
# opacity='0.5',
# scale=t.widthMeasured,
# scaleY=t.lengthMeasured,
# fill='red',
# stroke='red')
#
# # draw the map dimensions with an outline gray rectangle
# drawing.use(
# 'rect2',
# (t.x, t.z),
# scene=True,
# rotation=t.rotation,
# scale=t.width,
# scaleY=t.length,
# fill='none',
# stroke='gray')
# and close off with a final save of the drawing file
if drawing:
drawing.save()
self.logger.write('%s Tracks with large spatial uncertainties found (%s%%)' % (
largeUncertaintyCount, NumericUtils.roundToOrder(
100.0*float(largeUncertaintyCount)/float(len(self._tracks)), -1) ))
self._largeUncCsv.save()
self._tracks = []
def _postAnalyze(self):
h = Histogram(
data=self._uncs,
binCount=80,
xLimits=(0, max(*self._uncs)),
color="r",
title="Distribution of Rotational Uncertainties",
xLabel="Uncertainty Value (degrees)",
yLabel="Frequency",
)
p1 = h.save(self.getTempFilePath(extension="pdf"))
h.isLog = True
h.title += " (log)"
p2 = h.save(self.getTempFilePath(extension="pdf"))
self.mergePdfs([p1, p2], self.getPath("Rotational-Uncertainty-Distribution.pdf"))
average = NumericUtils.getMeanAndDeviation(self._uncs)
self.logger.write("Average rotational uncertainty: %s" % average.label)
# -------------------------------------------------------------------------------------------
# FIND LARGE UNCERTAINTY TRACKS
largeUncertaintyCount = 0
drawing = None
sitemap = None
# If track uncertainty is 2x average, add that track to the spreadsheet and map overlay
for t in self._tracks:
# if the tracksite has changed, save previous map and make a new one
if sitemap != t.trackSeries.trackway.sitemap:
# save the last site map drawing (if there was one)
if drawing:
drawing.save()
# then start a new drawing for this new site map
sitemap = t.trackSeries.trackway.sitemap
fileName = "%s-%s-ROTATION_UNC.svg" % (sitemap.name, sitemap.level)
path = self.getPath(self.DRAWING_FOLDER_NAME, fileName, isFile=True)
drawing = CadenceDrawing(path, sitemap)
# create a group to be instanced for the spreadsheet values
drawing.createGroup("rect1")
# create a rectangle of 100x100 cm that is to be scaled by fractional meters
drawing.rect((0, 0), 100, 100, scene=True, groupId="rect1")
# create another group to be instanced for the mapped values.
drawing.createGroup("rect2")
# create a rectangle of 100x100 cm that is to be scaled by fractional meters
drawing.rect((0, 0), 100, 100, scene=True, groupId="rect2")
# and place a grid and the federal coordinates in the drawing file
drawing.grid()
drawing.federalCoordinates()
# now examine the positional uncertainties for this track
rotation = t.rotationAngle.valueDegrees
if rotation.uncertainty <= 2.0 * average.uncertainty:
# then just indicate that this track has low uncertainty
self._drawLowUncertaintyMarker(drawing, t)
# label this track green
# drawing.text(
# t.name,
# (t.x - 20, t.z),
# scene=True,
# stroke='green',
# stroke_width='0.25',
# font_size='8px',
# font_family='Arial')
continue
# else, since the uncertainty is high, first write that track in the spreadsheet
largeUncertaintyCount += 1
self._largeUncCsv.createRow(uid=t.uid, fingerprint=t.fingerprint, r=rotation.label)
# if either the measured width or length is 0, mark with a yellow disk with red outline
if t.rotationMeasured == 0:
drawing.circle(
(t.x, t.z),
100 * (t.widthUncertainty + t.lengthUncertainty) / 2.0,
scene=True,
fill="yellow",
stroke="red",
)
# drawing.text(
# t.name,
# (t.x - 20, t.z),
# scene=True,
# stroke='black',
# stroke_width='0.25',
# font_size='6px',
# font_family='Arial')
continue
self._drawHighUncertaintyMarker(drawing, t)
# label this track with red
# drawing.text(
# t.name,
# (t.x - 20, t.z),
# scene=True,
# stroke='red',
# stroke_width='0.25',
# font_size='6px',
# font_family='Arial')
# and close off with a final save of the drawing file
if drawing:
drawing.save()
self.logger.write(
"%s Tracks with large rotational uncertainties found (%s%%)"
% (
largeUncertaintyCount,
NumericUtils.roundToOrder(100.0 * float(largeUncertaintyCount) / float(len(self._tracks)), -1),
)
)
self._largeUncCsv.save()
self._tracks = []
class RotationStage(AnalysisStage):
""" Compares the rotational values from the field measurements, where they
exist, with the measurements entered digitally determine the level of
equivalence between the data sets.
"""
DRAWING_FOLDER_NAME = 'Rotation-Comparison-Maps'
#___________________________________________________________________________
def __init__(self, key, owner, **kwargs):
"""Creates a new instance of RotationStage."""
super(RotationStage, self).__init__(
key, owner,
label='Rotation Comparison',
**kwargs)
self._paths = []
self._diffs = []
self._data = []
self._csv = None
self._currentDrawing = None
#===========================================================================
# G E T / S E T
#___________________________________________________________________________
@property
def deviations(self):
return self.cache.get('trackDeviations')
#===========================================================================
# P R O T E C T E D
#___________________________________________________________________________
def _preAnalyze(self):
"""_preAnalyze doc..."""
self.cache.set('trackDeviations', {})
self._diffs = []
self._data = []
self._currentDrawing = None
csv = CsvWriter()
csv.path = self.getPath('Rotation-Report.csv', isFile=True)
csv.addFields(
('uid', 'UID'),
('fingerprint', 'Fingerprint'),
('delta', 'Discrepancy'),
('entered', 'Entered'),
('measured', 'Measured'),
('deviation', 'Deviation'),
('relative', 'Relative'),
('axis', 'Axis'),
('axisPairing', 'Axis Pairing'))
self._csv = csv
#___________________________________________________________________________
def _analyzeSitemap(self, sitemap):
# start a drawing for the SVG and PDF files
fileName = sitemap.name + "_" + sitemap.level + '_rotation.svg'
path = self.getPath(self.DRAWING_FOLDER_NAME, fileName, isFile=True)
self._currentDrawing = CadenceDrawing(path, sitemap)
# create a group to be instanced for the map annotations
self._currentDrawing.createGroup('pointer')
self._currentDrawing.line(
p1=(0, 0),
p2=(0, -10),
scene=False,
groupId='pointer')
# and place a grid and the federal coordinates in the drawing file
self._currentDrawing.grid()
self._currentDrawing.federalCoordinates()
super(RotationStage, self)._analyzeSitemap(sitemap)
if self._currentDrawing:
self._currentDrawing.save()
#___________________________________________________________________________
def _analyzeTrackSeries(self, series, trackway, sitemap):
if len(series.tracks) < 2:
# At least two tracks are required to make the comparison
return
for track in series.tracks:
fieldAngle = Angle(
degrees=track.rotationMeasured \
if track.rotationMeasured \
else 0.0)
dataAngle = Angle(degrees=track.rotation)
strideLine = StrideLine(track=track, series=series)
if track.hidden or strideLine.pairTrack.hidden:
continue
try:
strideLine.vector.normalize()
except ZeroDivisionError:
pair = strideLine.pairTrack
self.logger.write([
'[ERROR]: Stride line was a zero length vector',
'TRACK: %s (%s, %s) [%s]' % (
track.fingerprint,
NumericUtils.roundToSigFigs(track.x, 3),
NumericUtils.roundToSigFigs(track.z, 3),
track.uid),
'PAIRING: %s (%s, %s) [%s]' % (
pair.fingerprint,
NumericUtils.roundToSigFigs(pair.x, 3),
NumericUtils.roundToSigFigs(pair.z, 3),
pair.uid) ])
continue
axisAngle = strideLine.angle
if track.left:
fieldAngle.radians += axisAngle.radians
else:
fieldAngle.radians = axisAngle.radians - fieldAngle.radians
# Adjust field angle into range [-180, 180]
fieldAngle.constrainToRevolution()
if fieldAngle.degrees > 180.0:
fieldAngle.degrees -= 360.0
fieldAngleUnc = Angle(degrees=5.0)
fieldAngleUnc.radians += \
0.03/math.sqrt(1.0 - math.pow(strideLine.vector.x, 2))
fieldDeg = NumericUtils.toValueUncertainty(
value=fieldAngle.degrees,
uncertainty=fieldAngleUnc.degrees)
# Adjust data angle into range [-180, 180]
dataAngle.constrainToRevolution()
if dataAngle.degrees > 180.0:
dataAngle.degrees -= 360.0
dataAngleUnc = Angle(degrees=track.rotationUncertainty)
dataDeg = NumericUtils.toValueUncertainty(
value=dataAngle.degrees,
uncertainty=dataAngleUnc.degrees)
angle1 = Angle(degrees=dataDeg.value)
angle2 = Angle(degrees=fieldDeg.value)
# fill color for the disks to be added to the map are based on
# diffDeg
diffDeg = NumericUtils.toValueUncertainty(
value=angle1.differenceBetween(angle2).degrees,
uncertainty=min(90.0, math.sqrt(
math.pow(dataAngleUnc.degrees, 2) +
math.pow(fieldAngleUnc.degrees, 2))) )
self._diffs.append(diffDeg.value)
deviation = diffDeg.value/diffDeg.uncertainty
self.deviations[track.uid] = diffDeg
# for now, convert +/- 180 headings to 0-360, using e and m
# comment the next four lines toggle comments for entered and
# measured below to revert
e = dataDeg.value
m = fieldDeg.value
if e < 0.0:
e += 360.0
if m < 0.0:
m += 360.0
data = dict(
uid=track.uid,
fingerprint=track.fingerprint,
entered=str(e),
measured=str(m),
delta=abs(diffDeg.value),
deviation=deviation,
relative=NumericUtils.roundToOrder(track.rotationMeasured, -2),
axis=NumericUtils.roundToOrder(axisAngle.degrees, -2),
axisPairing='NEXT' if strideLine.isNext else 'PREV')
self._csv.createRow(**data)
data['track'] = track
self._data.append(data)
# draw the stride line pointer for reference in green
self._currentDrawing.use(
'pointer',
(track.x, track.z),
scene=True,
rotation=axisAngle.degrees,
stroke_width=1,
scale=0.5,
stroke='green')
# indicate in blue the map-derived estimate of track rotation
self._currentDrawing.use(
'pointer',
(track.x, track.z),
scene=True,
rotation=dataDeg.value,
stroke_width=1,
stroke='blue')
# add the measured (spreadsheet) estimate of rotation
self._currentDrawing.use(
'pointer',
(track.x, track.z),
scene=True,
rotation=fieldDeg.value,
stroke_width=1,
stroke='red')
# place a translucent disk of radius proportional to the difference
# in degrees
radius = 100.0*diffDeg.value/180.0
self._currentDrawing.circle(
(track.x, track.z),
radius,
scene=True,
fill='red',
stroke_width=0.5,
stroke='red',
fill_opacity='0.5')
#_______________________________________________________________________________
def _postAnalyze(self):
"""_postAnalyze doc..."""
self._csv.save()
meanDiff = NumericUtils.getMeanAndDeviation(self._diffs)
self.logger.write('Rotation %s' % meanDiff.label)
self._paths.append(self._makePlot(
label='Rotation Differences',
data=self._diffs,
histRange=[-180, 180]))
self._paths.append(self._makePlot(
label='Rotation Differences',
data=self._diffs,
histRange=[-180, 180],
isLog=True))
circs = []
circsUnc = []
diffs = []
diffsUnc = []
entries = self.owner.getStage('lengthWidth').entries
for entry in entries:
track = entry['track']
if track.uid not in self.deviations:
# Skip those tracks with no deviation value (solo tracks)
continue
diffDeg = self.deviations[track.uid]
diffs.append(abs(diffDeg.value))
diffsUnc.append(diffDeg.uncertainty)
# Compute the circularity of the track from its aspect ratio. If
# the aspect is less than or equal to 1.0 use the aspect value
# directly. However, if the value is greater than one, take the
# reciprocal so that large and small aspect ratios can be compared
# equally.
aspect = entry['aspect']
if aspect.value > 1.0:
a = 1.0/aspect.raw
aspect = NumericUtils.toValueUncertainty(a, a*(aspect.rawUncertainty/aspect.raw))
circs.append(abs(aspect.value - 1.0))
circsUnc.append(aspect.uncertainty)
pl = self.plot
self.owner.createFigure('circular')
pl.errorbar(x=circs, y=diffs, xerr=circsUnc, yerr=diffsUnc, fmt='.')
pl.xlabel('Aspect Circularity')
pl.ylabel('Rotation Deviation')
pl.title('Rotation Deviation and Aspect Circularity')
self._paths.append(self.owner.saveFigure('circular'))
self.mergePdfs(self._paths)
self._paths = []
#_______________________________________________________________________________
def _makePlot(self, label, data, isLog =False, histRange =None, color ='r', binCount = 72):
"""_makePlot doc..."""
pl = self.plot
self.owner.createFigure('histogram')
pl.hist(data, binCount, range=histRange, log=isLog, facecolor=color, alpha=0.75)
pl.title('%s Distribution%s' % (label, ' (log)' if isLog else ''))
pl.xlabel('Difference (Degrees)')
pl.ylabel('Frequency')
pl.grid(True)
axis = pl.gca()
xlims = axis.get_xlim()
pl.xlim((max(histRange[0], xlims[0]), min(histRange[1], xlims[1])))
path = self.getTempPath('%s.pdf' % StringUtils.getRandomString(16), isFile=True)
self.owner.saveFigure('histogram', path)
return path