diff options
| -rw-r--r-- | ot/bregman.py | 14 | ||||
| -rw-r--r-- | ot/utils.py | 4 |
2 files changed, 14 insertions, 4 deletions
diff --git a/ot/bregman.py b/ot/bregman.py index b017c1a..55c44f6 100644 --- a/ot/bregman.py +++ b/ot/bregman.py @@ -344,8 +344,13 @@ def sinkhorn_knopp(a, b, M, reg, numItermax=1000, # print(reg) - K = np.exp(-M / reg) + K = np.empty(M.shape, dtype=M.dtype) + np.divide(M, -reg, out=K) + np.exp(K, out=K) + # print(np.min(K)) + tmp = np.empty(K.shape, dtype=M.dtype) + tmp2 = np.empty(b.shape, dtype=M.dtype) Kp = (1 / a).reshape(-1, 1) * K cpt = 0 @@ -373,8 +378,11 @@ def sinkhorn_knopp(a, b, M, reg, numItermax=1000, err = np.sum((u - uprev)**2) / np.sum((u)**2) + \ np.sum((v - vprev)**2) / np.sum((v)**2) else: - transp = u.reshape(-1, 1) * (K * v) - err = np.linalg.norm((np.sum(transp, axis=0) - b))**2 + np.multiply(u.reshape(-1, 1), K, out=tmp) + np.multiply(tmp, v.reshape(1, -1), out=tmp) + np.sum(tmp, axis=0, out=tmp2) + tmp2 -= b + err = np.linalg.norm(tmp2)**2 if log: log['err'].append(err) diff --git a/ot/utils.py b/ot/utils.py index 7dac283..5b052ac 100644 --- a/ot/utils.py +++ b/ot/utils.py @@ -13,6 +13,7 @@ import time import numpy as np from scipy.spatial.distance import cdist +from sklearn.metrics.pairwise import euclidean_distances import sys import warnings try: @@ -104,7 +105,8 @@ def dist(x1, x2=None, metric='sqeuclidean'): """ if x2 is None: x2 = x1 - + if metric == "sqeuclidean": + return euclidean_distances(x1, x2, squared=True) return cdist(x1, x2, metric=metric) |