def main():
with open('pitch-type.csv', 'r') as f:
reader = csv.reader(f)
for type in reader:
# read data
AlignedDataLists = [] # [csvfile index][joint index][time][dim]
csvfiles = type[2:]
Dir = type[0]
name = Dir.split('/')[-2]
# read all data and hold it to DataList
refpath = referenceReader(name + '-' + type[1] + '.csv',
Dir,
superDir=name)
#print(refpath)
refData = csvReader(refpath, type[0])
#refData.show()
#exit()
for csvfile in csvfiles:
if csvfile == refpath:
continue
inpData = csvReader(csvfile, Dir)
DP_ = DP(refData, inpData, verbose=False, ignoreWarning=True)
DP_.calc()
# aligned
alignedData = DP_.aligned()
AlignedDataLists.append(np.array(list(alignedData.values())))
AlignedDataLists = np.array(AlignedDataLists)
#print(AlignedDataLists.shape) (9, 39, 1587, 3)
# calculate mean
mean = np.mean(AlignedDataLists, axis=0) #(39, 1587, 3)
meanData = Data(interpolate='linear')
meanData.setvalues('mean movement',
x=mean[:, :, 0],
y=mean[:, :, 1],
z=mean[:, :, 2],
jointNames=list(refData.joints.keys()))
variance = np.var(AlignedDataLists, axis=0) #(39, 1587, 3)
std = np.std(AlignedDataLists, axis=0)
colors = std2color(std)
#meanData.show(colors=colors)
# save file and bone
meanData.save(os.path.join(
'result', name, '{0}-{1}-mean.MP4'.format(name, type[1])),
fps=240,
colors=colors,
saveonly=True)
def csvReader(csvfile, dir):
tmplists = []
with open(dir + csvfile, "r") as f:
reader = csv.reader(f)
for row in reader:
tmplists.append(row)
time = len(tmplists) - 7
data = Data(interpolate='linear')
jointNames = []
X = []
Y = []
Z = []
index = 2
while index < len(tmplists[6]):
if tmplists[5][index] == 'Position':
if tmplists[2][index] == 'Bone Marker' and tmplists[3][index].find('Unlabeled') < 0:
x = np.array(
[tmplists[i][index] if tmplists[i][index] != '' else np.nan for i in
range(7, len(tmplists))],
dtype='float')
y = np.array([tmplists[i][index + 1] if tmplists[i][index + 1] != '' else np.nan for i in
range(7, len(tmplists))], dtype='float')
z = np.array([tmplists[i][index + 2] if tmplists[i][index + 2] != '' else np.nan for i in
range(7, len(tmplists))], dtype='float')
X.append(x)
Y.append(y)
Z.append(z)
jointNames.append(tmplists[3][index])
index += 3
elif tmplists[5][index] == 'Rotation':
index += 4
data.setvalues(csvfile, np.array(X), np.array(Y), np.array(Z), jointNames, dir=dir, lines='baseball')
return data