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Update _gw.py (#637)
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doc typos

Co-authored-by: Cédric Vincent-Cuaz <[email protected]>
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simon-forb and cedricvincentcuaz authored Jun 22, 2024
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36 changes: 18 additions & 18 deletions ot/gromov/_gw.py
Original file line number Diff line number Diff line change
Expand Up @@ -43,11 +43,11 @@ def gromov_wasserstein(C1, C2, p=None, q=None, loss_fun='square_loss', symmetric
Where :
- :math:`\mathbf{C_1}`: Metric cost matrix in the source space
- :math:`\mathbf{C_2}`: Metric cost matrix in the target space
- :math:`\mathbf{p}`: distribution in the source space
- :math:`\mathbf{q}`: distribution in the target space
- `L`: loss function to account for the misfit between the similarity matrices
- :math:`\mathbf{C_1}`: Metric cost matrix in the source space.
- :math:`\mathbf{C_2}`: Metric cost matrix in the target space.
- :math:`\mathbf{p}`: Distribution in the source space.
- :math:`\mathbf{q}`: Distribution in the target space.
- `L`: Loss function to account for the misfit between the similarity matrices.
.. note:: This function is backend-compatible and will work on arrays
from all compatible backends. But the algorithm uses the C++ CPU backend
Expand All @@ -62,39 +62,39 @@ def gromov_wasserstein(C1, C2, p=None, q=None, loss_fun='square_loss', symmetric
Parameters
----------
C1 : array-like, shape (ns, ns)
Metric cost matrix in the source space
Metric cost matrix in the source space.
C2 : array-like, shape (nt, nt)
Metric cost matrix in the target space
Metric cost matrix in the target space.
p : array-like, shape (ns,), optional
Distribution in the source space.
If let to its default value None, uniform distribution is taken.
q : array-like, shape (nt,), optional
Distribution in the target space.
If let to its default value None, uniform distribution is taken.
loss_fun : str, optional
loss function used for the solver either 'square_loss' or 'kl_loss'
Loss function used for the solver either 'square_loss' or 'kl_loss'.
symmetric : bool, optional
Either C1 and C2 are to be assumed symmetric or not.
If let to its default None value, a symmetry test will be conducted.
Else if set to True (resp. False), C1 and C2 will be assumed symmetric (resp. asymmetric).
verbose : bool, optional
Print information along iterations
Print information along iterations.
log : bool, optional
record log if True
Record log if True.
armijo : bool, optional
If True the step of the line-search is found via an armijo research. Else closed form is used.
If there are convergence issues use False.
If True, the step of the line-search is found via an armijo search. Else closed form is used.
If there are convergence issues, use False.
G0: array-like, shape (ns,nt), optional
If None the initial transport plan of the solver is pq^T.
If None, the initial transport plan of the solver is pq^T.
Otherwise G0 must satisfy marginal constraints and will be used as initial transport of the solver.
max_iter : int, optional
Max number of iterations
Max number of iterations.
tol_rel : float, optional
Stop threshold on relative error (>0)
Stop threshold on relative error (>0).
tol_abs : float, optional
Stop threshold on absolute error (>0)
Stop threshold on absolute error (>0).
**kwargs : dict
parameters can be directly passed to the ot.optim.cg solver
Parameters can be directly passed to the ot.optim.cg solver.
Returns
-------
Expand Down Expand Up @@ -175,7 +175,7 @@ def line_search(cost, G, deltaG, Mi, cost_G, **kwargs):

if not nx.is_floating_point(C10):
warnings.warn(
"Input structure matrix consists of integer. The transport plan will be "
"Input structure matrix consists of integers. The transport plan will be "
"casted accordingly, possibly resulting in a loss of precision. "
"If this behaviour is unwanted, please make sure your input "
"structure matrix consists of floating point elements.",
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