def similarityMatrixForExpandingCirclesHighDim():
print "Reading data..."
bar = progressbar.ProgressBar(maxval=12, widgets=[progressbar.Bar('=', '[', ']'), ' ', progressbar.Percentage()])
bar.start(); progress = 0
data0a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius0cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data5a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius5cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data10a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius10cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data15a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius15cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data20a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius20cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data25a=m.readRaw("captures/mechanicalArm/ArmLength60cm/Anticlockwise/radius25cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data0b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius0cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data5b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius5cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data10b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius10cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data15b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius15cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data20b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius20cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
data25b=m.readRaw("captures/mechanicalArm/ArmLength60cm/Clockwise/radius25cmHorizontal.txt")[26:,4:]; progress += 1; bar.update(progress)
bar.finish()
print "Calculating segments..."
bar = progressbar.ProgressBar(maxval=12, widgets=[progressbar.Bar('=', '[', ']'), ' ', progressbar.Percentage()])
bar.start(); progress = 0
segs0a=m.getHighDimensionalSegments(data0a); progress += 1; bar.update(progress)
segs5a=m.getHighDimensionalSegments(data5a); progress += 1; bar.update(progress)
segs10a=m.getHighDimensionalSegments(data10a); progress += 1; bar.update(progress)
segs15a=m.getHighDimensionalSegments(data15a); progress += 1; bar.update(progress)
segs20a=m.getHighDimensionalSegments(data20a)[:-1]; progress += 1; bar.update(progress)
segs25a=m.getHighDimensionalSegments(data25a)[1:]; progress += 1; bar.update(progress)
segs0b=m.getHighDimensionalSegments(data0b)[1:-1]; progress += 1; bar.update(progress)
segs5b=m.getHighDimensionalSegments(data5b)[1:]; progress += 1; bar.update(progress)
segs10b=m.getHighDimensionalSegments(data10b)[:-1]; progress += 1; bar.update(progress)
segs15b=m.getHighDimensionalSegments(data15b)[1:-1]; progress += 1; bar.update(progress)
segs20b=m.getHighDimensionalSegments(data20b)[1:-1]; progress += 1; bar.update(progress)
segs25b=m.getHighDimensionalSegments(data25b)[1:-1]; progress += 1; bar.update(progress)
bar.finish()
names = ["0a"]*len(segs0a)+["5a"]*len(segs5a)+["10a"]*len(segs10a)+["15a"]*len(segs15a)+["20a"]*len(segs20a)+["25a"]*len(segs25a)+["0c"]*len(segs0b)+["5c"]*len(segs5b)+["10c"]*len(segs10b)+["15c"]*len(segs15b)+["20c"]*len(segs20b)+["25c"]*len(segs25b)
#names = ["0a"]*len(segs0a)+["0c"]*len(segs0b)+["5a"]*len(segs5a)+["5c"]*len(segs5b)+["10a"]*len(segs10a)+["10c"]*len(segs10b)+["15a"]*len(segs15a)+["15c"]*len(segs15b)+["20a"]*len(segs20a)+["20c"]*len(segs20b)+["25a"]*len(segs25a)+["25c"]*len(segs25b)
weights = [1]*np.shape((segs0a+segs0b+segs5a+segs5b+segs10a+segs10b+segs15a+segs15b+segs20a+segs20b+segs25a+segs25b)[0])[1]
#names = [0]*len(segs0a)+[10]*len(segs10a)+[20]*len(segs20a)
#weights = [1]*np.shape((segs0a+segs10a+segs20a)[0])[1]
print "Calculating similarities..."
m.similarityMatrix(segs0a+segs5a+segs10a+segs15a+segs20a+segs25a+segs0b+segs5b+segs10b+segs15b+segs20b+segs25b,names,weights,"Similarity Matrix using high dimensional raw sensor data",savePlot=True)
def highDimRawSimilarity():
raw_h_large=m.getHighDimensionalSegments(m.readCSVfile("captures/HorizontalArmSpin-Jibran.csv"))
raw_h_small=m.getHighDimensionalSegments(m.readCSVfile("captures/HorizontalArmSpinLittleCircles-Jibran.csv"))
names = ['Big','Big','Big','Big','Big','Big','Big','Small','Small','Small','Small','Small','Small','Small','Small','Small']
weights = [1]*np.shape((raw_h_large+raw_h_small)[0])[1]
m.similarityMatrix(raw_h_large+raw_h_small,names,weights,"Similarity Matrix using high dimensional raw sensor data")
