def highDimQuaternionSimilarity(euler=False):
quats_h_large=m.getQuaternionSegmentsByRawData(m.readCSVfile("captures/HorizontalArmSpin-Jibran.csv"),quats.rearrangeQuatsForLatentSpaceAlgorithm(quats.rawDataFileToQuats("captures/raw/HorizontalArmSpin-Jibran"),euler))
quats_h_small=m.getQuaternionSegmentsByRawData(m.readCSVfile("captures/HorizontalArmSpinLittleCircles-Jibran.csv"),quats.rearrangeQuatsForLatentSpaceAlgorithm(quats.rawDataFileToQuats("captures/raw/HorizontalArmSpinLittleCircles-Jibran"),euler))
names = ['Big','Big','Big','Big','Big','Big','Big','Small','Small','Small','Small','Small','Small','Small','Small','Small']
weights = [1]*np.shape((quats_h_large+quats_h_small)[0])[1]
if euler:
title="Similarity Matrix using high dimensional euler angle data"
else:
title="Similarity Matrix using high dimensional quaternion data"
m.similarityMatrix(quats_h_large+quats_h_small,names,weights,"Similarity Matrix using high dimensional euler angle data")
def lowDimQuaternionSimilarity(n_components=3,euler=False):
(quats_h_large,weights_large)=quats.doPCAonQuats("captures/raw/HorizontalArmSpin-Jibran",euler,n_components=n_components)
(quats_h_small,weights_small)=quats.doPCAonQuats("captures/raw/HorizontalArmSpinLittleCircles-Jibran",euler,n_components=n_components)
segments_quats_h_large=m.getQuaternionSegmentsByRawData(m.readCSVfile("captures/HorizontalArmSpin-Jibran.csv"),quats_h_large)
segments_quats_h_small=m.getQuaternionSegmentsByRawData(m.readCSVfile("captures/HorizontalArmSpinLittleCircles-Jibran.csv"),quats_h_small)
names = ['Big','Big','Big','Big','Big','Big','Big','Small','Small','Small','Small','Small','Small','Small','Small','Small']
weights = [1]*np.shape((segments_quats_h_large+segments_quats_h_small)[0])[1] #TODO: AVERAGE THE WEIGHTS!!
if euler:
title="Similarity Matrix using low dimensional euler angle data"
else:
title="Similarity Matrix using low dimensional quaternion data"
m.similarityMatrix(segments_quats_h_large+segments_quats_h_small,names,weights,title)
