-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
- [ ] Make edit distances a single shared structure, rather than owned individually by each word.
This might not actually reduce memory usage at all, because I still need to store the distance be…
-
Hi Raja,
I try to use `accalign` to align short reads (single-end 50) to human reference for host DNA clearance. The mapping rate is too high with lots of reads badly mapped. These reads are left u…
-
One of the advantage of the Levenshtein library is that the distance function works on any iterable like list and tuple.
```
from Levenshtein import distance
distance([0,1,2,3,4,5], [5,4,1,2,3])
…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…
-
```
The edit distance facet in the Reconcile->Facets->Best candidates edit distance
thinks these two strings have an edit distance of 8:
>What We Talk About When We Talk About Love
What we talk a…