base

DiffPaSS base classes

Type aliases

BootstrapList = list  # List indexed by bootstrap iteration
GradientDescentList = list  # List indexed by gradient descent iteration
GroupByGroupList = list  # List indexed by group index

IndexPair = tuple[int, int]  # Pair of indices
IndexPairsInGroup = list[IndexPair]  # Pairs of indices in a group of sequences
IndexPairsInGroups = list[IndexPairsInGroup]  # Pairs of indices in groups of sequences

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make_pbar

 make_pbar (epochs:int, show_pbar:bool)

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dccn

 dccn (x:torch.Tensor)

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DiffPaSSResults

 DiffPaSSResults (log_alphas:Union[list[list[numpy.ndarray]],list[list[lis
                  t[numpy.ndarray]]],NoneType], soft_perms:Union[list[list
                  [numpy.ndarray]],list[list[list[numpy.ndarray]]],NoneTyp
                  e], hard_perms:Union[list[list[numpy.ndarray]],list[list
                  [list[numpy.ndarray]]]], hard_losses:Union[list[list[flo
                  at]],list[list[list[float]]]], soft_losses:Union[list[li
                  st[float]],list[list[list[float]]],NoneType])

Container for results of DiffPaSS fits.

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DiffPaSSModel

 DiffPaSSModel (*args, **kwargs)

Base class for DiffPaSS models.

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DiffPaSSModel.fit

 DiffPaSSModel.fit (x:torch.Tensor, y:torch.Tensor, epochs:int=1,
                    optimizer_name:Optional[str]='SGD',
                    optimizer_kwargs:Optional[dict[str,Any]]=None,
                    mean_centering:bool=False, show_pbar:bool=False,
                    compute_final_soft:bool=False,
                    record_log_alphas:bool=False,
                    record_soft_perms:bool=False,
                    record_soft_losses:bool=False)

Fit permutations to data using gradient descent.

	Type	Default	Details
x	Tensor		The object (MSA or adjacency matrix of graphs) to be permuted
y	Tensor		The target object (MSA or adjacency matrix of graphs), that the objects represented by x should be paired with. Not acted upon by soft/hard permutations
epochs	int	1
optimizer_name	Optional	SGD
optimizer_kwargs	Optional	None
mean_centering	bool	False
show_pbar	bool	False
compute_final_soft	bool	False
record_log_alphas	bool	False
record_soft_perms	bool	False
record_soft_losses	bool	False
Returns	DiffPaSSResults

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DiffPaSSModel.fit_bootstrap

 DiffPaSSModel.fit_bootstrap (x:torch.Tensor, y:torch.Tensor,
                              n_start:int=1, n_end:Optional[int]=None,
                              step_size:int=1, n_repeats:int=1,
                              show_pbar:bool=True,
                              single_fit_cfg:Optional[dict]=None)

*Fit permutations to data using the DiffPaSS bootstrap.

The DiffPaSS bootstrap consists of a sequence of short gradient descent runs (default: one epoch per run). At the end of each run, a subset of the found pairings is chosen uniformly at random and fixed for the next run. The number of pairings fixed at each iteration ranges between n_start (default: 1) and n_end (default: total number of pairs), with a step size of step_size.*

	Type	Default	Details
x	Tensor		The object (MSA or adjacency matrix of graphs) to be permuted
y	Tensor		The target object (MSA or adjacency matrix of graphs), that the objects represented by x should be paired with. Not acted upon by soft/hard permutations
n_start	int	1
n_end	Optional	None
step_size	int	1
n_repeats	int	1
show_pbar	bool	True
single_fit_cfg	Optional	None
Returns	DiffPaSSResults