def test_plot(hdf5_filename):
#extract center data from HDF5
c_feat,c_data = get_hdf5_data(hdf5_filename,fields=['center'])
#compute speed features
s_feat,s_data = speed_feature_extraction(c_data)
print s_feat
print s_data
#compute directional features
d_feat,d_data = direction_feature_extraction(c_data)
print d_feat
print d_data
#plot data
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, aspect='equal')
rank = npy.argsort(d_data[:,0])
for i,r in enumerate(rank):
xy = c_data[r]['center']
p_length = s_data[r,0]
x0 = xy[0,0]
y0 = xy[0,1]
offset_x = s_data[r,6]*10000
# offset_x = p_length*10
# offset_x = s_data[r,3]*100
# offset_x = d_data[r,3]*10
offset_y = d_data[r,3]*10
plt.plot(xy[:,0]-x0+offset_x,xy[:,1]-y0+offset_y)
fxy = filter(xy,sigma=1.)
plt.plot(fxy[:,0]-x0+offset_x,fxy[:,1]-y0+offset_y)
plt.plot(offset_x,offset_y,'+k')
def test_measures():
import matplotlib.pyplot as plt
from hdf5_read import get_hdf5_data
from measurement import speed_feature_extraction
hdf5_filename = '../test/data/test_rev.hdf5'
c_feat,c_data = get_hdf5_data(hdf5_filename,fields=['center'])
#compute speed features
feat,data = speed_feature_extraction(c_data)
print feat
plt.scatter(data[:,1],data[:,3])
plt.xlabel('avg speed')
plt.ylabel('hull speed')
plt.draw()
plt.figure()
plt.hist(data[:,1:4])
plt.legend(['avg','mrdo','hull speed'])
plt.show()
