vector (in tdata) so that NNLS can be used instead of BVLS.

Fixed bug when ValueError excepted in rebinning

negative legendre terms.  Refactored a little to clean up.

For archetypes with legendre terms, NNLS is now actually used with
additional terms of -1*each legendre term so that we can use the faster
NNLS to get the same result as BVLS.

because on CPU, the additional computation time for the larger array
sizes dominates any time savings of NNLS vs BVLS

negative legendre terms on the GPU in lieu of BVLS into
per_camera_coeff_with_least_square_batch.  Moved prior_on_coeffs into
zscan.py, called from within per_camera_coeff_with_least_square_batch.
Pass prior_sigma, a scalar, insted of the array from fitz to archetypes.

Bug fix on case where only some object types, not all, have an
archetype.

terms with 0 coefficients and make the coeffs negative for negative
terms.

Refactored to remove the last bit of the BVLS-NNLS trick from
archetypes.py and zfind.py by passing binned instead of tdata to
per_camera_coeff_with_least_square_batch.

involve using a list of bands instead of ncam to be more general.