SparseCoder uses Lasso if the algorithm is set to lasso_cd. It sets some of the Lasso's parameters, but not max_iter, and that by default is 1000. This results in a warning in examples/decomposition/plot_sparse_coding.py complaining that the estimator has not converged.
I guess there should be a way for the user to specify other parameters of the estimator used in SparseCoder other than the ones provided in the SparseCoder.__init__ right now.
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yeah, more like algorithm_kwargs I suppose, to cover Lasso, LassoLars, and Lars
But I was looking at the code to figure how many parameters are not covered by what's already given to SparseCoder, and there's not many. In fact, max_iter is a parameter to SparseCoder, not passed to LassoLars (hence the warning I saw in the example), and yet used when Lasso is used.
Looks like the intention has been to cover the union of parameters, but some may be missing, or forgotten to be passed to the underlying models.