def affpoints(xk, D, theta, delta):
m = len(D)
n = len(D[0].x)
Y = [Point(n)]
Y2 = [xk]
index = [-1]
Z = np.matrix(np.identity(n))
p = int(round(m*random()+0.5))
if p > 1.0:
## indexes check properly
vec = range(p, m)
vec.extend(range(0, p-1))
else:
vec = range(m)
if DEBUG:
print vec
for i in vec:
if np.linalg.norm(D[i].x - xk.x) <= delta:
Z = np.matrix(Z)
proj_z = Z*np.linalg.inv(Z.transpose()*Z)*Z.transpose()*np.matrix(D[i].x-xk.x).transpose()
if np.linalg.norm(proj_z) >= delta*theta:
point = Point(n)
point.x = D[i].x - xk.x
Y.append(point)
Y_matrix = array([])
for j in range(len(Y)):
Y_matrix = np.concatenate((Y_matrix, Y[j].x), 1)
Z = null(Y_matrix)
Y2.append(D[i])
index.append(i)
print "here"
if len(Y) == n + 1:
linear = True
else:
linear = False
return Y2, linear, Z, index
def _run(self, command) : utils.run( command%self.__dict__, message = None if self._verbose else "", log = utils.null(), )
def x(self, command) : return utils.run( command%self.defs, message="" if _quiet else None, log = utils.null(), )
def x(self, command):
return utils.run(
command % self.defs,
message="" if _quiet else None,
log=utils.null(),
)
