def find_init_pts(init_coords, dist=25, min_angle=10):
n_p = init_coords.shape[0]
As = np.zeros(n_p)
for k in range(n_p):
p0 = init_coords[k, :]
p1, p2 = find_neighbors(p0, init_coords, 2)
if (norm(p1 - p0) < dist) and (norm(p2 - p0) < dist):
As[k] = angle(p1 - p0, p2 - p0)
elif (sum(p1 == p0) == 3) or (sum(p2 == p0) == 3):
As[k] = 400
else:
As[k] = 500
As[np.where(np.isnan(As))] = np.inf
if np.abs(As - 90).min() < min_angle:
p0 = init_coords[np.abs(As - 90).argmin(), :]
p1, p2 = find_neighbors(p0, init_coords, 2)
return [p0, p1, p2]
else:
return -1
def find_init_pts(init_coords, dist=25, min_angle=10):
n_p = init_coords.shape[0]
As = np.zeros(n_p)
for k in range(n_p):
p0 = init_coords[k, :]
p1, p2 = find_neighbors(p0, init_coords, 2)
if (norm(p1 - p0) < dist) and (norm(p2 - p0) < dist):
As[k] = angle(p1 - p0, p2 - p0)
elif (sum(p1 == p0) == 3) or (sum(p2 == p0) == 3):
As[k] = 400
else:
As[k] = 500
As[np.where(np.isnan(As))]=np.inf
if np.abs(As - 90).min() < min_angle:
p0 = init_coords[np.abs(As - 90).argmin(), :]
p1, p2 = find_neighbors(p0, init_coords, 2)
return [p0, p1, p2]
else:
return -1
def find_init_angles(all_elecs, mindist=10, maxdist=25):
''' Takes the set of all electrodes and some constraint parameters.
Returns angle for each electrode's best match as Nx1 vector'''
n = all_elecs.shape[0]
angles = np.zeros(n)
dists = np.zeros((n, 2))
actual_points = np.zeros((n, 3, 3))
for k in xrange(n):
p0 = all_elecs[k, :]
p1, p2 = find_neighbors(p0, all_elecs, 2)
if ((mindist < norm(p1 - p0) < maxdist)
and (mindist < norm(p2 - p0) < maxdist)):
angles[k] = angle(p1 - p0, p2 - p0)
dists[k] = norm(p1 - p0), norm(p2 - p0)
actual_points[k] = (p0, p1, p2)
else:
angles[k] = np.inf
dists[k] = (np.inf, np.inf)
actual_points[k] = (p0, p1, p2)
return angles, dists, actual_points
def find_init_angles(all_elecs, mindist=10, maxdist=25):
''' Takes the set of all electrodes and some constraint parameters.
Returns angle for each electrode's best match as Nx1 vector'''
n = all_elecs.shape[0]
angles = np.zeros(n)
dists = np.zeros((n,2))
actual_points = np.zeros((n,3,3))
for k in xrange(n):
p0 = all_elecs[k,:]
p1, p2 = find_neighbors(p0, all_elecs, 2)
if ((mindist < norm(p1-p0) < maxdist) and (mindist
< norm(p2-p0) < maxdist)):
angles[k] = angle(p1-p0, p2-p0)
dists[k] = norm(p1-p0), norm(p2-p0)
actual_points[k] = (p0,p1,p2)
else:
angles[k] = np.inf
dists[k] = (np.inf, np.inf)
actual_points[k] = (p0,p1,p2)
return angles, dists, actual_points
