def fun2_xy(xx, ct, bt):
x_n, y_n, a_k, b_k = xx[:NN], xx[NN:2 * NN], xx[2 * NN:2 * NN + K**2 -
2], xx[2 * NN + K**2 -
2:]
a_k = np.concatenate(([
0,
], a_k[:K - 1], [
0,
], a_k[K - 1:])).reshape((K, K))
b_k = np.concatenate(([0, 0], b_k)).reshape((K, K))
# cost:
# (features[k] = n, xi, yi, m, xj, yj)
# x_m - x_n + x_i - x_j + ux(x_i, y_i) - ux(x_j, y_j) = 0
# y_m - y_n + y_i - y_j + uy(x_i, y_i) - uy(x_j, y_j) = 0
temp1 = x_n[pos_inv[fes[:, 3].astype(np.int)]] - x_n[pos_inv[fes[:, 0].astype(np.int)]] \
+ fes[:, 1] - fes[:, 4] \
+ polyval2d((fes[:, 1]+xmin)/float(xmax-xmin), (fes[:, 2]+ymin)/float(ymax-ymin), a_k) \
- polyval2d((fes[:, 4]+xmin)/float(xmax-xmin), (fes[:, 5]+ymin)/float(ymax-ymin), a_k)
temp2 = y_n[pos_inv[fes[:, 3].astype(np.int)]] - y_n[pos_inv[fes[:, 0].astype(np.int)]] \
+ fes[:, 2] - fes[:, 5] \
+ polyval2d((fes[:, 1]+xmin)/float(xmax-xmin), (fes[:, 2]+ymin)/float(ymax-ymin), b_k) \
- polyval2d((fes[:, 4]+xmin)/float(xmax-xmin), (fes[:, 5]+ymin)/float(ymax-ymin), b_k)
cost = np.sum(temp1**2 + temp2**2)
# integrate:
ct = poly_utils.polymul2d(a_k, a_k, ct)
cost += str_sm * poly_utils.polyint2d(ct, bt, -1., 1., -1., 1.)
ct = poly_utils.polymul2d(b_k, b_k, ct)
cost += str_sm * poly_utils.polyint2d(ct, bt, -1., 1., -1., 1.)
return cost
def fun2_xy(xx, ct, bt, ax, ay, a, dist):
x_n, y_n, a_k = xx[:NN], xx[NN:2 * NN], xx[2 * NN:]
a[mask] = xx[2 * NN:]
ax = poly_utils.polyder2d(a, ax, 0)
ay = poly_utils.polyder2d(a, ay, 1)
# cost:
# (features[k] = n, xi, yi, m, xj, yj)
# x_m - x_n + x_i - x_j + ux(x_i, y_i) - ux(x_j, y_j) = 0
# y_m - y_n + y_i - y_j + uy(x_i, y_i) - uy(x_j, y_j) = 0
temp1 = x_n[pos_inv[fes[:, 3].astype(np.int)]] - x_n[pos_inv[fes[:, 0].astype(np.int)]] \
+ fes[:, 1] - fes[:, 4] \
+ polyval2d((fes[:, 1]+xmin)/float(xmax), (fes[:, 2]+ymin)/float(ymax), ax) \
- polyval2d((fes[:, 4]+xmin)/float(xmax), (fes[:, 5]+ymin)/float(ymax), ax)
temp2 = y_n[pos_inv[fes[:, 3].astype(np.int)]] - y_n[pos_inv[fes[:, 0].astype(np.int)]] \
+ fes[:, 2] - fes[:, 5] \
+ polyval2d((fes[:, 1]+xmin)/float(xmax), (fes[:, 2]+ymin)/float(ymax), ay) \
- polyval2d((fes[:, 4]+xmin)/float(xmax), (fes[:, 5]+ymin)/float(ymax), ay)
cost = np.sum((temp1**2 + temp2**2) * reg)
# integrate:
ct = poly_utils.polymul2d(a, a, ct)
cost += str_sm * poly_utils.polyint2d(ct, bt, -1., 1., -1., 1.)
return cost
def err_poly(xx, ct, bt, ax, ay, a):
x_n, y_n, a_k = xx[:NN], xx[NN:2 * NN], xx[2 * NN:]
a[mask] = xx[2 * NN:]
ax = poly_utils.polyder2d(a, ax, 0)
ay = poly_utils.polyder2d(a, ay, 1)
ct = poly_utils.polymul2d(a, a, ct)
cost = str_sm * poly_utils.polyint2d(ct, bt, -1., 1., -1., 1.)
return cost