Clean references in documentation

RELEASES.md

@@ -15,6 +15,7 @@
 - Add version number to the documentation (PR #696)
 - Update doc for default regularization in `ot.unbalanced` sinkhorn solvers (Issue #691, PR #700)
 - Clean documentation for `gromov`, `lp` and `unbalanced` folders (PR #710)
+- Clean references in documentation (PR #722)
 
 ## 0.9.5
 

ot/bregman/_barycenter.py

@@ -336,6 +336,7 @@ def free_support_sinkhorn_barycenter(
  ot.bregman.sinkhorn : Entropic regularized OT solver
  ot.lp.free_support_barycenter : Barycenter solver based on Linear Programming
 
+
  .. _references-free-support-barycenter:
  References
  ----------

ot/bregman/_sinkhorn.py

@@ -129,10 +129,10 @@ def sinkhorn(
  array([[0.36552929, 0.13447071],
  [0.13447071, 0.36552929]])
 
+
  .. _references-sinkhorn:
  References
  ----------
-
  .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation
  of Optimal Transport, Advances in Neural Information Processing
  Systems (NIPS) 26, 2013
@@ -1460,6 +1460,7 @@ def sinkhorn_epsilon_scaling(
  array([[0.36552929, 0.13447071],
  [0.13447071, 0.36552929]])
 
+
  .. _references-sinkhorn-epsilon-scaling:
  References
  ----------

ot/da.py

@@ -132,13 +132,13 @@ def sinkhorn_lpl1_mm(
  References
  ----------
  .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
- "Optimal Transport for Domain Adaptation," in IEEE
- Transactions on Pattern Analysis and Machine Intelligence ,
- vol.PP, no.99, pp.1-1
+  "Optimal Transport for Domain Adaptation," in IEEE
+  Transactions on Pattern Analysis and Machine Intelligence ,
+  vol.PP, no.99, pp.1-1
 
  .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
- Generalized conditional gradient: analysis of convergence
- and applications. arXiv preprint arXiv:1510.06567.
+  Generalized conditional gradient: analysis of convergence
+  and applications. arXiv preprint arXiv:1510.06567.
 
  See Also
  --------
@@ -276,12 +276,12 @@ def sinkhorn_l1l2_gl(
  References
  ----------
  .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
- "Optimal Transport for Domain Adaptation," in IEEE Transactions
- on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
+  "Optimal Transport for Domain Adaptation," in IEEE Transactions
+  on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
  .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
- Generalized conditional gradient: analysis of convergence and
- applications. arXiv preprint arXiv:1510.06567.
+  Generalized conditional gradient: analysis of convergence and
+  applications. arXiv preprint arXiv:1510.06567.
 
  See Also
  --------
@@ -423,9 +423,9 @@ def emd_laplace(
  References
  ----------
  .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
- "Optimal Transport for Domain Adaptation," in IEEE
- Transactions on Pattern Analysis and Machine Intelligence,
- vol.PP, no.99, pp.1-1
+  "Optimal Transport for Domain Adaptation," in IEEE
+  Transactions on Pattern Analysis and Machine Intelligence,
+  vol.PP, no.99, pp.1-1
 
  .. [30] R. Flamary, N. Courty, D. Tuia, A. Rakotomamonjy,
  "Optimal transport with Laplacian regularization: Applications to domain adaptation and shape matching,"
@@ -743,8 +743,8 @@ def transform_labels(self, ys=None):
  References
  ----------
  .. [27] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
- "Optimal transport for multi-source domain adaptation under target shift",
- International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
+  "Optimal transport for multi-source domain adaptation under target shift",
+  International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
 
  """
  nx = self.nx
@@ -1073,8 +1073,8 @@ class LinearGWTransport(LinearTransport):
  References
  ----------
  .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-  distances between Gaussian distributions. Journal of Applied Probability,
-  59(4), 1178-1198.
+ distances between Gaussian distributions. Journal of Applied Probability,
+ 59(4), 1178-1198.
 
  """
 
@@ -1580,17 +1580,17 @@ class SinkhornLpl1Transport(BaseTransport):
  References
  ----------
  .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
- "Optimal Transport for Domain Adaptation," in IEEE
- Transactions on Pattern Analysis and Machine Intelligence ,
- vol.PP, no.99, pp.1-1
+  "Optimal Transport for Domain Adaptation," in IEEE
+  Transactions on Pattern Analysis and Machine Intelligence ,
+  vol.PP, no.99, pp.1-1
 
  .. [2] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
- Generalized conditional gradient: analysis of convergence
- and applications. arXiv preprint arXiv:1510.06567.
+  Generalized conditional gradient: analysis of convergence
+  and applications. arXiv preprint arXiv:1510.06567.
 
  .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
-  Regularized discrete optimal transport. SIAM Journal on Imaging
-  Sciences, 7(3), 1853-1882.
+ Regularized discrete optimal transport. SIAM Journal on Imaging
+ Sciences, 7(3), 1853-1882.
  """
 
  def __init__(
@@ -1724,8 +1724,8 @@ class EMDLaplaceTransport(BaseTransport):
  References
  ----------
  .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-  "Optimal Transport for Domain Adaptation," in IEEE Transactions
-  on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
+ "Optimal Transport for Domain Adaptation," in IEEE Transactions
+ on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
  .. [2] R. Flamary, N. Courty, D. Tuia, A. Rakotomamonjy,
  "Optimal transport with Laplacian regularization: Applications to domain adaptation and shape matching,"
@@ -1873,13 +1873,13 @@ class SinkhornL1l2Transport(BaseTransport):
  References
  ----------
  .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
- "Optimal Transport for Domain Adaptation," in IEEE
- Transactions on Pattern Analysis and Machine Intelligence ,
- vol.PP, no.99, pp.1-1
+  "Optimal Transport for Domain Adaptation," in IEEE
+  Transactions on Pattern Analysis and Machine Intelligence ,
+  vol.PP, no.99, pp.1-1
 
  .. [2] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
- Generalized conditional gradient: analysis of convergence
- and applications. arXiv preprint arXiv:1510.06567.
+  Generalized conditional gradient: analysis of convergence
+  and applications. arXiv preprint arXiv:1510.06567.
 
  .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
  Regularized discrete optimal transport. SIAM Journal on Imaging
@@ -2352,14 +2352,13 @@ class JCPOTTransport(BaseTransport):
  References
  ----------
  .. [1] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
- "Optimal transport for multi-source domain adaptation under target shift",
- International Conference on Artificial Intelligence and Statistics (AISTATS),
- vol. 89, p.849-858, 2019.
+  "Optimal transport for multi-source domain adaptation under target shift",
+  International Conference on Artificial Intelligence and Statistics (AISTATS),
+  vol. 89, p.849-858, 2019.
 
  .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
- Regularized discrete optimal transport. SIAM Journal on Imaging
- Sciences, 7(3), 1853-1882.
-
+ Regularized discrete optimal transport. SIAM Journal on Imaging
+ Sciences, 7(3), 1853-1882.
 
  """
 
@@ -2524,8 +2523,8 @@ def transform_labels(self, ys=None):
  References
  ----------
  .. [27] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
- "Optimal transport for multi-source domain adaptation under target shift",
- International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
+  "Optimal transport for multi-source domain adaptation under target shift",
+  International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
  """
  nx = self.nx
 

ot/dr.py

@@ -208,7 +208,7 @@ def wda(
  References
  ----------
  .. [11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).
-  Wasserstein Discriminant Analysis. arXiv preprint arXiv:1608.08063.
+ Wasserstein Discriminant Analysis. arXiv preprint arXiv:1608.08063.
  """ # noqa
 
  if sinkhorn_method.lower() == "sinkhorn":
@@ -348,8 +348,8 @@ def projection_robust_wasserstein(
  References
  ----------
  .. [32] Huang, M. , Ma S. & Lai L. (2021).
-  A Riemannian Block Coordinate Descent Method for Computing
-  the Projection Robust Wasserstein Distance, ICML.
+ A Riemannian Block Coordinate Descent Method for Computing
+ the Projection Robust Wasserstein Distance, ICML.
  """ # noqa
 
  # initialization
@@ -489,7 +489,7 @@ def ewca(
  References
  ----------
  .. [52] Collas, A., Vayer, T., Flamary, F., & Breloy, A. (2023).
-  Entropic Wasserstein Component Analysis.
+ Entropic Wasserstein Component Analysis.
  """ # noqa
  n, d = X.shape
  X = X - X.mean(0)

ot/gaussian.py

@@ -566,8 +566,8 @@ def gaussian_gromov_wasserstein_distance(Cov_s, Cov_t, log=False):
  References
  ----------
  .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
- distances between Gaussian distributions. Journal of Applied Probability,
- 59(4), 1178-1198.
+  distances between Gaussian distributions. Journal of Applied Probability,
+  59(4), 1178-1198.
  """
 
  nx = get_backend(Cov_s, Cov_t)
@@ -630,8 +630,8 @@ def empirical_gaussian_gromov_wasserstein_distance(xs, xt, ws=None, wt=None, log
  References
  ----------
  .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
- distances between Gaussian distributions. Journal of Applied Probability,
- 59(4), 1178-1198.
+  distances between Gaussian distributions. Journal of Applied Probability,
+  59(4), 1178-1198.
  """
  xs, xt = list_to_array(xs, xt)
  nx = get_backend(xs, xt)
@@ -698,8 +698,8 @@ def gaussian_gromov_wasserstein_mapping(
  References
  ----------
  .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
- distances between Gaussian distributions. Journal of Applied Probability,
- 59(4), 1178-1198.
+  distances between Gaussian distributions. Journal of Applied Probability,
+  59(4), 1178-1198.
  """
 
  nx = get_backend(mu_s, mu_t, Cov_s, Cov_t)
@@ -788,12 +788,13 @@ def empirical_gaussian_gromov_wasserstein_mapping(
  b : (1, dt) array-like
  bias
 
+
  .. _references-empirical_gaussian_gromov_wasserstein_mapping:
  References
  ----------
  .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
- distances between Gaussian distributions. Journal of Applied Probability,
- 59(4), 1178-1198.
+  distances between Gaussian distributions. Journal of Applied Probability,
+  59(4), 1178-1198.
  """
 
  xs, xt = list_to_array(xs, xt)

ot/gromov/_gw.py

@@ -911,7 +911,6 @@ def solve_gromov_linesearch(
 
 
  .. _references-solve-linesearch:
-
  References
  ----------
  .. [24] Vayer Titouan, Chapel Laetitia, Flamary Rémi, Tavenard Romain and Courty Nicolas
@@ -1293,6 +1292,7 @@ def fgw_barycenters(
  - :math:`(\mathbf{M}_s)_s`: all distance matrices between the feature of the barycenter and the other features :math:`(dist(\mathbf{X}, \mathbf{Y}_s))_s` shape (`N`, `ns`)
  - values used in convergence evaluation.
 
+
  .. _references-fgw-barycenters:
  References
  ----------

ot/gromov/_partial.py

@@ -611,6 +611,7 @@ def partial_fused_gromov_wasserstein(
  log : dict
  Convergence information and loss.
 
+
  .. _references-partial-gromov-wasserstein:
  References
  ----------
@@ -907,6 +908,7 @@ def partial_fused_gromov_wasserstein2(
  log : dict
  log dictionary returned only if `log` is `True`
 
+
  .. _references-partial-gromov-wasserstein2:
  References
  ----------

ot/gromov/_semirelaxed.py

@@ -474,12 +474,12 @@ def semirelaxed_fused_gromov_wasserstein(
  (ICML). 2019.
 
  .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-  "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-  International Conference on Learning Representations (ICLR), 2022.
+ "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+ International Conference on Learning Representations (ICLR), 2022.
 
  .. [62] H. Van Assel, C. Vincent-Cuaz, T. Vayer, R. Flamary, N. Courty.
-  "Interpolating between Clustering and Dimensionality Reduction with
-  Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
+ "Interpolating between Clustering and Dimensionality Reduction with
+ Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
  """
  arr = [M, C1, C2]
  if p is not None:
@@ -688,12 +688,12 @@ def semirelaxed_fused_gromov_wasserstein2(
  (ICML). 2019.
 
  .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-  "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-  International Conference on Learning Representations (ICLR), 2022.
+ "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+ International Conference on Learning Representations (ICLR), 2022.
 
  .. [62] H. Van Assel, C. Vincent-Cuaz, T. Vayer, R. Flamary, N. Courty.
-  "Interpolating between Clustering and Dimensionality Reduction with
-  Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
+ "Interpolating between Clustering and Dimensionality Reduction with
+ Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
  """
  # partial get_backend as the full one will be handled in gromov_wasserstein
  nx = get_backend(C1, C2)
@@ -1244,8 +1244,8 @@ def entropic_semirelaxed_fused_gromov_wasserstein(
  References
  ----------
  .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-  "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-  International Conference on Learning Representations (ICLR), 2022.
+ "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+ International Conference on Learning Representations (ICLR), 2022.
  """
  arr = [M, C1, C2]
  if p is not None:
@@ -1437,8 +1437,8 @@ def entropic_semirelaxed_fused_gromov_wasserstein2(
  References
  ----------
  .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-  "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-  International Conference on Learning Representations (ICLR), 2022.
+ "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+ International Conference on Learning Representations (ICLR), 2022.
  """
  T, log_srfgw = entropic_semirelaxed_fused_gromov_wasserstein(
  M,

ot/gromov/_utils.py

@@ -428,9 +428,9 @@ def init_matrix_semirelaxed(C1, C2, p, loss_fun="square_loss", nx=None):
  "Gromov-Wasserstein averaging of kernel and distance matrices."
  International Conference on Machine Learning (ICML). 2016.
 
- .. [48]  Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-  "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-  International Conference on Learning Representations (ICLR), 2022.
+ .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
+ "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+ International Conference on Learning Representations (ICLR), 2022.
  """
  if nx is None:
  C1, C2, p = list_to_array(C1, C2, p)