contact_hist_refcmp_diff_selcmp

mdtools.structure.contact_hist_refcmp_diff_selcmp(cm, natms_per_refcmp=1, natms_per_selcmp=1, minlength=0, dtype=int)[source]

Bin the number of contacts that reference compounds establish to different selection compounds into a histogram.

A compound is usually a chemically meaningful subgroup of an AtomGroup. This can e.g. be a Segment, Residue, fragment or a single Atom. Refer to the MDAnalysis’ user guide for an explanation of these terms. Note that in any case, only Atoms belonging to the original AtomGroup are taken into account, even if the compound might comprise additional Atoms that are not contained in the original AtomGroup.

Parameters:

cm (array_like) – (Boolean) contact matrix of shape (m, n) as e.g. generated by mdtools.structure.contact_matrix(), where m is the number of reference Atoms and n is the number of selection Atoms. Alternatively, cm can already be a compound contact matrix as e.g. generated by mdtools.structure.cmp_contact_matrix(). In this case, you probably want to set natms_per_refcmp and natms_per_selcmp to 1, to keep cm unaltered. It is also possible to parse a compound contact count matrix as e.g. generated by mdtools.structure.cmp_contact_count_matrix().
natms_per_refcmp (int or array_like, optional) – Number of Atoms per reference compound. Can be a single integer or an array of integers. If natms_per_refcmp is a single integer, all reference compounds are assumed to contain the same number of Atoms. In this case, natms_per_refcmp must be an integer divisor of cm.shape[0]. If natms_per_refcmp is an array of integers, it must contain the number of reference Atoms for each single reference compound. In this case, sum(natms_per_refcmp) must be equal to cm.shape[0].
natms_per_selcmp (int or array_like, optional) – Same for selection compounds (natms_per_selcmp is checked against cm.shape[1]).
minlength (int, optional) – A minimum number of bins for the output array. The output array will have at least this number of elements, though it will be longer if necessary. See numpy.bincount() for further information.
dtype (dtype, optional) – Data type of the output array.

Returns:

hist_refcmp_diff_selcmp (numpy.ndarray) – Histogram of the number of contacts that reference compounds establish to different selection compounds. Multiple contacts with the same selection compound are not taken into account.

See also

mdtools.structure.contact_matrix(): Construct a boolean contact matrix for two MDAnalysis AtomGroups
mdtools.structure.natms_per_cmp(): Get the number of Atoms of each compound in an MDAnalysis AtomGroup
mdtools.structure.contact_hists(): Bin the number of contacts between reference and selection compounds into histograms.
mdtools.structure.contact_hist_refcmp_same_selcmp(): Bin the number of contacts that reference compounds establish to the same selection compound into a histogram.
mdtools.structure.contact_hist_refcmp_selcmp_tot(): Bin the total number of contacts that reference compounds establish to selection compounds into a histogram.
mdtools.structure.contact_hist_refcmp_selcmp_pair(): Bin the number of “bonds” (Atom- Atom contacts) between pairs of reference and selection compounds
numpy.count_nonzero(): Count the number of non-zero values in an array
numpy.bincount(): Count the number of occurrences of each value in an array of non-negative ints

Notes

Atoms belonging to the same compound must form a contiguous set in the input contact matrix, otherwise the result will be wrong.

About the output array:

hist_refcmp_diff_selcmp: The first element is the number of reference compounds having no contact with any selection compound, the second element is the number of reference compounds having contact with exactly one selection compound, the third element is the number of reference compounds having contact with exactly two different selection compounds, and so on.

If both natms_per_refcmp and natms_per_selcmp are 1 and cm is a true boolean contact matrix, mdtools.structure.contact_hist_refcmp_diff_selcmp() and mdtools.structure.contact_hist_refcmp_selcmp_tot() return the same result.

Examples

>>> cm = np.tril(np.ones((5,4), dtype=bool), -1)
>>> cm[3, 0] = 0
>>> cm
array([[False, False, False, False],
       [ True, False, False, False],
       [ True,  True, False, False],
       [False,  True,  True, False],
       [ True,  True,  True,  True]])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(cm)
array([1, 1, 2, 0, 1])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(cm=cm, minlength=7)
array([1, 1, 2, 0, 1, 0, 0])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(cm=cm, minlength=3)
array([1, 1, 2, 0, 1])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(cm=cm, dtype=np.uint32)
array([1, 1, 2, 0, 1], dtype=uint32)

>>> mdt.strc.cmp_contact_matrix(cm=cm, natms_per_refcmp=[2, 2, 1])
array([[ True, False, False, False],
       [ True,  True,  True, False],
       [ True,  True,  True,  True]])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm=cm, natms_per_refcmp=[2, 2, 1]
... )
array([0, 1, 0, 1, 1])

>>> mdt.strc.cmp_contact_matrix(cm=cm, natms_per_selcmp=2)
array([[False, False],
       [ True, False],
       [ True, False],
       [ True,  True],
       [ True,  True]])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm=cm, natms_per_selcmp=2
... )
array([1, 2, 2])

>>> mdt.strc.cmp_contact_matrix(
...     cm=cm, natms_per_refcmp=[2, 2, 1], natms_per_selcmp=2
... )
array([[ True, False],
       [ True,  True],
       [ True,  True]])
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm=cm, natms_per_refcmp=[2, 2, 1], natms_per_selcmp=2
... )
array([0, 1, 2])

Edge cases:

>>> cm = np.array([], dtype=bool).reshape(0, 4)
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm, natms_per_refcmp=[]
... )
array([], dtype=int64)
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(cm, natms_per_refcmp=1)
array([], dtype=int64)
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm, natms_per_refcmp=[], minlength=2, dtype=np.uint32
... )
array([0, 0], dtype=uint32)

>>> cm = np.array([], dtype=bool).reshape(6, 0)
>>> mdt.strc.contact_hist_refcmp_diff_selcmp(
...     cm, natms_per_refcmp=3, natms_per_selcmp=[]
... )
array([2])