def _pathcount(template_ink, ink, alpha=0.5, penup_z=10.0):
m = template_ink.shape[0]
n = ink.shape[0]
u = np.zeros(m)
v = np.zeros(m)
peak_count = np.zeros(m)
d = _compute_combined_distance(ink, template_ink, alpha, penup_z)
for i in xrange(n):
new_u = np.zeros(m)
new_v = np.zeros(m)
new_u[0] = u[0] + d[i,0]
new_v[0] = v[0] + 1
for j in xrange(1,m):
t1 = u[j]
t2 = u[j-1]
if (t2 < t1) and (t2 < new_u[j-1]):
new_u[j] = t2 + d[i,j]
new_v[j] = v[j-1] + 1
elif (t1 < t2) and (t1 < new_u[j-1]):
new_u[j] = t1 + d[i,j]
new_v[j] = v[j] + 1
else:
new_u[j] = new_u[j-1] + d[i,j]
new_v[j] = new_v[j-1] + 1
max_ind = np.argmax(-new_u / new_v)
peak_count[max_ind] += 1
u = new_u
v = new_v
return peak_count
def compute_dtw_vector(center_ink, ink_array, alpha=0.5, penup_z=1000.0):
"""Returns a vector representing the difference between
`center_ink` and time-warped `ink_array`. The output vector
always has the same length as `center_ink`."""
n = center_ink.shape[0]
m = ink_array.shape[0]
if (n <= 0 or m <= 0):
raise ValueError('Both input arrays must have length > 0')
combined_d = _compute_combined_distance(center_ink,
ink_array,
alpha,
penup_z)
dtw = np.zeros((n,m))
path = np.zeros((n,m))
_LEFT, _DIAG, _UP = 1, 2, 3
for i in xrange(1,n):
dtw[i,0] = dtw[i-1,0] + combined_d[i,0]
path[i,0] = _UP
for j in xrange(1,m):
dtw[0,j] = dtw[0,j-1] + combined_d[0,j]
path[0,j] = _LEFT
for i in xrange(1,n):
for j in xrange(1,m):
dtw[i,j] = combined_d[i,j] + min(dtw[i-1,j],
dtw[i-1,j-1],
dtw[i,j-1])
if (dtw[i-1,j-1] < dtw[i-1,j] and dtw[i-1,j-1] < dtw[i,j-1]):
path[i,j] = _DIAG
elif (dtw[i-1,j] < dtw[i-1,j-1] and dtw[i-1,j] < dtw[i,j-1]):
path[i,j] = _UP
else:
path[i,j] = _LEFT
# trace backwards
i, j = n-1, m-1
mapping = np.zeros(n, dtype=np.int)
while i >= 0 and j >= 0:
mapping[i] = j
if path[i,j] == _UP: i -= 1
elif path[i,j] == _LEFT: j -= 1
else:
i -= 1
j -= 1
diff_array = ink_array[mapping,:] - center_ink
return diff_array.reshape(-1)
def compute_dtw_distance(ink_array1, ink_array2, alpha=0.5, penup_z=10.0):
"""Returns the DTW distance between two trajectories."""
n = ink_array1.shape[0]
m = ink_array2.shape[0]
if (n <= 0 or m <= 0):
raise ValueError('Both input arrays must have length > 0')
combined_d = _compute_combined_distance(ink_array1,
ink_array2,
alpha,
penup_z)
return _execute_dtw_in_c(combined_d, m , n)
