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src/m/o/modred-1.0.2/src/bpod.py   modred(Download)
        raise RuntimeError('Cannot run in parallel.')
    vec_space = VectorSpaceMatrices(weights=inner_product_weights)
    direct_vecs = util.make_mat(direct_vecs)
    adjoint_vecs = util.make_mat(adjoint_vecs)
 

src/m/o/modred-1.0.2/src/dmd.py   modred(Download)
        raise RuntimeError('Cannot run in parallel.')
    vec_space = VectorSpaceMatrices(weights=inner_product_weights)
    vecs = util.make_mat(vecs)
    # Sequential dataset
    if adv_vecs is None:
    # Non-sequential data
    else:
        adv_vecs = util.make_mat(adv_vecs)
        if vecs.shape != adv_vecs.shape:
            raise ValueError(('vecs and adv_vecs are not the same shape.'))
        raise RuntimeError('Cannot run in parallel.')
    vec_space = VectorSpaceMatrices(weights=inner_product_weights)
    vecs = util.make_mat(vecs)
    if adv_vecs is not None:
        adv_vecs = util.make_mat(adv_vecs)

src/m/o/modred-1.0.2/src/pod.py   modred(Download)
    vec_space = VectorSpaceMatrices(weights=inner_product_weights)
    # compute decomp
    vecs = util.make_mat(vecs)
    correlation_mat = \
        vec_space.compute_symmetric_inner_product_mat(vecs)
    if _parallel.is_distributed():
        raise RuntimeError('Cannot run in parallel.')
    vecs = util.make_mat(vecs)
    if inner_product_weights is None:
        modes, sing_vals, eigen_vecs = util.svd(vecs)