scirpy.ir_dist.metrics.DistanceCalculator#

class scirpy.ir_dist.metrics.DistanceCalculator(cutoff)#

Abstract base class for a CDR3-sequence distance calculator.

Parameters:: cutoff (Optional[int]) – Distances > cutoff will be eliminated to make efficient use of sparse matrices. If None, the default cutoff shall be used.

Attributes table#

The sparse matrix dtype.

`calc_dist_mat`(seqs[, seqs2])	Calculate pairwise distance matrix of all sequences in `seqs` and `seqs2`.
`squarify`(triangular_matrix)	Mirror a triangular matrix at the diagonal to make it a square matrix.

DistanceCalculator.DTYPE = 'uint8'#: The sparse matrix dtype. Defaults to uint8, constraining the max distance to 255.

abstract DistanceCalculator.calc_dist_mat(seqs, seqs2=None)#

Calculate pairwise distance matrix of all sequences in seqs and seqs2.

When seqs2 is omitted, computes the pairwise distance of seqs against itself.

Calculates the full pairwise distance matrix.

Important

Distances are offset by 1 to allow efficient use of sparse matrices (\(d' = d+1\)).
That means, a distance > cutoff is represented as 0, a distance == 0 is represented as 1, a distance == 1 is represented as 2 and so on.
Only returns distances <= cutoff. Larger distances are eliminated from the sparse matrix.
Distances are non-negative.

Parameters:

seqs (Sequence[str]) – array containing CDR3 sequences. Must not contain duplicates.
seqs2 (Optional[Sequence[str]] (default: None)) – second array containing CDR3 sequences. Must not contain duplicates either.

Return type:

csr_matrix

Returns:

Sparse pairwise distance matrix.

static DistanceCalculator.squarify(triangular_matrix)#

Mirror a triangular matrix at the diagonal to make it a square matrix.

The input matrix must be upper triangular to begin with, otherwise the results will be incorrect. No guard rails!