contact_hist_refcmp_same_selcmp
- mdtools.structure.contact_hist_refcmp_same_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 the same selection compound into a histogram.
A compound is usually a chemically meaningful subgroup of an
AtomGroup
. This can e.g. be aSegment
,Residue
,fragment
or a singleAtom
. Refer to the MDAnalysis’ user guide for an explanation of these terms. Note that in any case, onlyAtoms
belonging to the originalAtomGroup
are taken into account, even if the compound might comprise additionalAtoms
that are not contained in the originalAtomGroup
.- Parameters:
cm (
array_like
) – (Boolean) contact matrix of shape(m, n)
as e.g. generated bymdtools.structure.contact_matrix()
, wherem
is the number of referenceAtoms
andn
is the number of selectionAtoms
. Alternatively, cm can already be a compound contact count matrix as e.g. generated bymdtools.structure.cmp_contact_count_matrix()
. In this case, you probably want to set natms_per_refcmp and natms_per_selcmp to1
, to keep cm unaltered.natms_per_refcmp (
int
orarray_like
, optional) – Number ofAtoms
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 ofAtoms
. In this case, natms_per_refcmp must be an integer divisor ofcm.shape[0]
. If natms_per_refcmp is an array of integers, it must contain the number of referenceAtoms
for each single reference compound. In this case,sum(natms_per_refcmp)
must be equal tocm.shape[0]
.natms_per_selcmp (
int
orarray_like
, optional) – Same for selection compounds (natms_per_selcmp is checked againstcm.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.dtype (
dtype
, optional) – Data type of the output array.
- Returns:
hist_refcmp_same_selcmp (
numpy.ndarray
) – Histogram of the number of contacts that reference compounds establish to the same selection compound. Different selection compounds that are connected to the same reference compound via the same number of “bonds” (Atom
-Atom
contacts) 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 MDAnalysisAtomGroup
mdtools.structure.contact_hists()
Bin the number of contacts between reference and selection compounds into histograms.
mdtools.structure.contact_hist_refcmp_diff_selcmp()
Bin the number of contacts that reference compounds establish to different selection compounds 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
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_same_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 at least one selection compound via exactly one “bond”, the third element is the number of reference compounds having contact with at least one selection compound via exactly two “bonds”, and so on.
Important: Different selection compounds that are connected to the same reference compound via the same number of “bonds” are not taken into account. For instance, if a reference compound is connected to two different selection compounds via one “bond”, respectively, only the first selection compound is counted. However, if the reference compound is connected to the first selection compound via one “bond” and to the second selection compound via two “bonds”, both selection compounds are counted.
The sum of all histogram elements might therefore exceed the number of reference compounds, because a single reference compound can be connected to different selection compounds with different numbers of “bonds”. However, each histogram element on its own cannot exceed the number of reference compounds, because different selection compounds that are connected to the same reference compound via the same number of “bonds” are not taken into account.
Hence it is e.g. possible to say that 100 % of the reference compounds are coordinated monodentately by selection compounds while at the same time 50 % of the reference compounds are additionally coordinated bidentately.
This behavior is complementary to the histogram returned by
mdtools.structure.contact_hist_refcmp_selcmp_pair()
.
If both natms_per_refcmp and natms_per_selcmp are
1
and cm is a true boolean contact matrix, hist_refcmp_same_selcmp is equal to[x, cm.shape[0]-x]
, wherex
is the number of reference compounds having no contact with any selection compound.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_same_selcmp(cm) array([1, 4]) >>> mdt.strc.contact_hist_refcmp_same_selcmp(cm=cm, minlength=4) array([1, 4, 0, 0]) >>> mdt.strc.contact_hist_refcmp_same_selcmp(cm=cm, minlength=1) array([1, 4]) >>> mdt.strc.contact_hist_refcmp_same_selcmp(cm=cm, dtype=np.uint32) array([1, 4], dtype=uint32) >>> hist = mdt.strc.contact_hist_refcmp_same_selcmp(cm) >>> hist[1] == cm.shape[0] - hist[0] True
>>> mdt.strc.cmp_contact_count_matrix( ... cm=cm, natms_per_refcmp=[2, 2, 1] ... ) array([[1, 0, 0, 0], [1, 2, 1, 0], [1, 1, 1, 1]]) >>> mdt.strc.contact_hist_refcmp_same_selcmp( ... cm=cm, natms_per_refcmp=[2, 2, 1] ... ) array([0, 3, 1])
>>> mdt.strc.cmp_contact_count_matrix(cm=cm, natms_per_selcmp=2) array([[0, 0], [1, 0], [2, 0], [1, 1], [2, 2]]) >>> mdt.strc.contact_hist_refcmp_same_selcmp( ... cm=cm, natms_per_selcmp=2 ... ) array([1, 2, 2])
>>> mdt.strc.cmp_contact_count_matrix( ... cm=cm, natms_per_refcmp=[2, 2, 1], natms_per_selcmp=2 ... ) array([[1, 0], [3, 1], [2, 2]]) >>> mdt.strc.contact_hist_refcmp_same_selcmp( ... cm=cm, natms_per_refcmp=[2, 2, 1], natms_per_selcmp=2 ... ) array([0, 2, 1, 1])
Edge cases:
>>> cm = np.array([], dtype=bool).reshape(0, 4) >>> mdt.strc.contact_hist_refcmp_same_selcmp( ... cm, natms_per_refcmp=[] ... ) array([], dtype=int64) >>> mdt.strc.contact_hist_refcmp_same_selcmp(cm, natms_per_refcmp=1) array([], dtype=int64) >>> mdt.strc.contact_hist_refcmp_same_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_same_selcmp( ... cm, natms_per_refcmp=3, natms_per_selcmp=[] ... ) array([2])