def simMatrixAverageClassDistancesHighDimArmEx(db=None): if db is None: db = armExercisesDatabase.db(True) classes = {key:value[1] for (key,value) in zip(db.data,db.segs.values())} classes = {key[:-1]:classes[key] for key in classes.keys() if 'l' in key} # Left hand motions only weights = {key:[[1]*np.shape(segments[0])[1]]*len(segments) for (key,segments) in zip(classes.keys(),classes.values())} m.averageSimilarityMatrix(classes, weights, "Distances between clusters of exercises with left arm", savePlot=True)
def armExercisesHDsimMatrix(db=None): if db is None: db = armExercisesDatabase.db(True) LRclasses = {key:random.sample(value,1) for (key,value) in zip(db.HDsegs.keys(),[sum(l,[]) for l in db.HDsegs.values()])} classes = {} for key,value in LRclasses.iteritems(): for segment in value: classes.setdefault(key[:-1], []).append(segment) # Merge left and right hand motions together weights = {key:[[1]*np.shape(segments[0])[1]]*len(segments) for (key,segments) in zip(classes.keys(),classes.values())} m.averageSimilarityMatrix(classes, weights, "Distances between clusters of exercises", savePlot=True)