dseuss/mpnum

File mparray.py has 1490 lines of code (exceeds 250 allowed). Consider refactoring.

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# encoding: utf-8
""" Core MPArray data structure & general purpose functions

  .. todo:: single site MPAs -- what is left?
  .. todo:: Local tensor ownership -- see MPArray class comment

File mppovm.py has 1229 lines of code (exceeds 250 allowed). Consider refactoring.

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# encoding: utf-8


r'''Matrix-product representation of POVMs

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def _adapt_to_add_l(leftvec, compr_lten, tgt_lten):
    """Add one column to the left vector.

    :param leftvec: existing left vector
        It has two indices: `compr_mps_bond` and `tgt_mps_bond`

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def _adapt_to_add_r(rightvec, compr_lten, tgt_lten):
    """Add one column to the right vector.

    :param rightvec: existing right vector
        It has two indices: `compr_mps_bond` and `tgt_mps_bond`

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            if relerr is None:
                u, sv, v = svdfunc(ltens.reshape(matshape), rank)
                rank_t = len(sv)
            else:
                u, sv, v = svd(ltens.reshape(matshape))

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            if relerr is None:
                u, sv, v = svdfunc(ltens.reshape(matshape), rank)
                rank_t = len(sv)
            else:
                u, sv, v = svd(ltens.reshape(matshape))

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MPArray has 53 functions (exceeds 20 allowed). Consider refactoring.

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class MPArray(object):
    r"""Efficient representation of a general N-partite array :math:`A` in
    matrix product form with open boundary conditions:

    .. math::

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    if isinstance(axes[0], Sequence):
        axes = tuple(tuple(ax + 1 if ax >= 0 else ax - 1 for ax in axes2)
                     for axes2 in axes)
    else:
        axes = tuple(ax + 1 if ax >= 0 else ax - 1 for ax in axes)

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    if isinstance(axes[0], Sequence):
        axes = tuple(tuple(ax + 1 if ax >= 0 else ax - 1 for ax in axes2)
                     for axes2 in axes)
    else:
        axes = tuple(ax + 1 if ax >= 0 else ax - 1 for ax in axes)

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File linalg.py has 454 lines of code (exceeds 250 allowed). Consider refactoring.

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# encoding: utf-8

"""Linear algebra with matrix product arrays

Currently, we support computing extremal eigenvalues and eigenvectors

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    for i, mpa, ndims, lv in zip(it.count(), mpas, mpas_ndims, leftvec):
        if ndims == 2:
            leftvec_out[i] = _eig_leftvec_add(lv, mpa.lt[pos], mps_lten)
        elif ndims == 1:
            leftvec_out[i] = _eig_leftvec_add_mps(lv, mpa.lt[pos], mps_lten)

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    for i, mpa, ndims, rv in zip(it.count(), mpas, mpas_ndims, rightvec):
        if ndims == 2:
            rightvec_out[i] = _eig_rightvec_add(rv, mpa.lt[pos], mps_lten)
        elif ndims == 1:
            rightvec_out[i] = _eig_rightvec_add_mps(rv, mpa.lt[pos], mps_lten)

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    for i in range(dim - 1):
        for j in range(i + 1, dim):
            vectors[k, i], vectors[k, j] = 1.0, 1.0
            k += 1
            vectors[k, i], vectors[k, j] = 1.0, -1.0

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    for i in range(dim - 1):
        for j in range(i + 1, dim):
            vectors[k, i], vectors[k, j] = 1.0, 1.0j
            k += 1
            vectors[k, i], vectors[k, j] = 1.0, -1.0j

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            if pos > 0:
                eigvec.canonicalize(left=pos)
                rightvecs[pos - 1] = None
                leftvecs[pos] = _eig_leftvec_add(
                    leftvecs[pos - 1], mpo.lt[pos - 1], eigvec.lt[pos - 1])

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                if pos > 0:
                    self.canonicalize(left=pos)
                    rvecs[pos - 1] = None
                    lvecs[pos] = _adapt_to_add_l(lvecs[pos - 1], self._lt[pos - 1],
                                                 target.lt[pos - 1])

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            if pos < nr_sites - var_sites:
                # We always do this, because we don't do the last site again.
                eigvec.canonicalize(right=pos_end)
                leftvecs[pos + 1] = None
                rightvecs[pos] = _eig_rightvec_add(

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                if pos < nr_sites - var_sites:
                    # We always do this, because we don't do the last site again.
                    self.canonicalize(right=pos_end)
                    lvecs[pos + 1] = None
                    rvecs[pos] = _adapt_to_add_r(rvecs[pos + 1], self._lt[pos_end],

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MPPovm has 34 functions (exceeds 20 allowed). Consider refactoring.

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class MPPovm(mp.MPArray):
    """MPArray representation of multipartite POVM

    There are two different ways to write down a POVM in matrix product form

File factory.py has 322 lines of code (exceeds 250 allowed). Consider refactoring.

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# encoding: utf-8
"""Module to create random test instances of matrix product arrays"""

from __future__ import division, print_function