print 'in siteMap, xFederal = %s and yFederal = %s' % fMap
print 'in scene, xFederal = %s and yFederal = %s' % (xScene, yScene)
pScene = drawing.projectToMap((xScene, yScene))
print 'and back again, to siteMap, p = (%s, %s)' % pScene
print 'scaling to scene, siteMap.xFederal maps to %s' % drawing.scaleToScene(xFed)
print 'and this maps back to %s' % drawing.scaleToMap(drawing.scaleToScene(xFed))
#===============================================================================
# place a circle of radius 5 at (100.0, 100.0) in scene coordinates
# drawing.circle((100, 100), 5, scene=True, stroke='red', fill='green')
# label it with text at (100, 10)
drawing.text("circle of radius 5 at (200, 10)", (100, 10), scene=True, stroke='blue')
# now place another circle and rect in map (not scene) coordinates below the federal marker
drawing.rect((xScene, yScene - 100), 4, 10, scene=False, fill='red')
# and another at (100, 200), also in map coordinates
drawing.rect((100, 200), 10, 4, scene=False)
#==================================================================================================
# 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')
x = -100
z = 100
lengthRatio = 0.5
trackLength = 1.0
trackWidth = 1.0
trackRotation = 15.0
# place a circle of radius 5 at (10.0, 10.0) in scene coordinates
drawing.circle((10, 10), 5, fill='none')
drawing.line((100,100), (200, 100), scene=True, stroke='red', stroke_width=4)
# label it with text at (20, 10)
drawing.text("circle of radius 5", (20, 10), scene=True)
# now place another circle and rect in map coordinates (not scene coordinates) at the federal marker
drawing.rect((xFed + 40, yFed), 20, 20, fill='none', scene=False)
# now overlay onto the above measured-dimension bars the corresponding length indicators
drawing.use(
'bar',
(100, 200),
scale=1.0,
scaleY=lengthRatio*trackLength,
rotation=trackRotation,
scene=True,
stroke='red',
xFed = siteMap.xFederal
yFed = siteMap.yFederal
fMap = (xFed, yFed)
fScene = drawing.projectToScene((xFed, yFed))
print "siteMap.index = %s and siteMap.name = %s" % (siteMap.index, siteMap.filename)
print 'in siteMap, the federal marker is (%s, %s)' % fMap
print 'which projects into the scene as (%s, %s)' % (fScene[0], fScene[1])
print 'and projecting back to the map gives (%s, %s)' % drawing.projectToMap((fScene[0], fScene[1]))
# place a circle of radius 5 at (10.0, 10.0) in scene coordinates
drawing.circle((10, 10), 5)
# label it with text at (20, 10)
drawing.text("circle of radius 5", (20, 10), scene=True)
# now place a 20x40 rect in map coordinates (not scene coordinates) at the federal marker
drawing.rect((xFed + 40, yFed), 20, 40, scene=False)
# and another smaller one at (10, 20) in map coordinates
drawing.rect((10, 20), 4, 8, scene=False)
# place the federal coordinates as a text string 20 cm above the marker
text = "(%s, %s)" % (drawing.siteMap.federalEast, drawing.siteMap.federalNorth)
drawing.text(text, (0, 20), scene=True, stroke='green')
# place a 2 cm green unfilled circle atop the federal coordinate marker
drawing.circle((0, 0), 2, scene=True, fill='none', stroke='green', stroke_width=1)
# place a grid in registration with the 10m grid in the site map, and illustrates the use of a
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 = []
