Use of presamples in LCA and index advancement could be improved

[PascalLesage]

Use of presamples in LCA and index advancement could be improved

[PascalLesage]

The simple fix above has tests failing in bw.LCA.

[PascalLesage]

Tests in LCA show that the expected behaviour is not what would be allowed by the change described above.

Indeed, the expected behaviour is that:

• an LCA object whose presamples have not had their matrices updated via lca.presamples.update_matrices will use the values in the first column (this is also how things work with the change above). This is good, because LCA will often use presamples with a single column (scenario)
• the first call of update_matrices moves the index from 0 to 1. This is because the  indexer.count is 1 when loaded. In the suggestion above, the  indexer.count is reset to 0, so the first call of update_matrices actually moves the  indexer.count to 1 but the index itself remains at 0.

So the expected usage is sequentially seeded presample packages in LCA would be something like this:

>>> lca = bw.LCA({some_act:1}, presamples=[pp_dirpath])
>>> print("iteration\tindex")
>>> for i in range(5):
...     if i != 0:
...         lca.presamples.update_matrices()
...     lca.lci()
...     print(i, "\t", lca.presamples.matrix_indexer[0].index)

iteration	index
0 		 0
1 		 1
2 		 2
3 		 3
4 		 4

The if clause is a bit annoying, so we need to decide what approach is better:

• Weirdness because the index remains at 0 after calling update_indices for the first time (suggestion above); or
• Only calling update_indices on runs beyond the first.

@cmutel any preference?