The MultiMolecule Class
The API of the FOX.MultiMolecule
class.
API FOX.MultiMolecule
- class FOX.MultiMolecule(coords, atoms=None, bonds=None, properties=None, atoms_alias=None, lattice=None)[source]
A class designed for handling a and manipulating large numbers of molecules.
More specifically, different conformations of a single molecule as derived from, for example, an intrinsic reaction coordinate calculation (IRC) or a molecular dymanics trajectory (MD). The class has access to four attributes (further details are provided under parameters):
- Parameters
coords (
np.ndarray[np.float64]
, shape \((m, n, 3)\)) – A 3D array with the cartesian coordinates of \(m\) molecules with \(n\) atoms.atoms (
dict[str, list[str]]
) – A dictionary with atomic symbols as keys and matching atomic indices as values. Stored in theMultiMolecule.atoms
attribute.bonds (
np.ndarray[np.int64]
, shape \((k, 3)\)) – A 2D array with indices of the atoms defining all \(k\) bonds (columns 1 & 2) and their respective bond orders multiplied by 10 (column 3). Stored in theMultiMolecule.bonds
attribute.properties (
plams.Settings
) – A Settings instance for storing miscellaneous user-defined (meta-)data. Is devoid of keys by default. Stored in theMultiMolecule.properties
attribute.lattice (
np.ndarray[np.float64]
, shape \((m, 3, 3)\) or \((3, 3)\), optional) – Lattice vectors for periodic systems. For non-periodic systems this value should beNone
.
- atoms
A dictionary with atomic symbols as keys and matching atomic indices as values.
- Type
- bonds
A 2D array with indices of the atoms defining all \(k\) bonds (columns 1 & 2) and their respective bond orders multiplied by 10 (column 3).
- Type
np.ndarray[np.int64]
, shape \((k, 3)\)
- properties
A Settings instance for storing miscellaneous user-defined (meta-)data. Is devoid of keys by default.
- Type
- lattice
Lattice vectors for periodic systems. For non-periodic systems this value should be
None
.- Type
np.ndarray[np.float64]
, shape \((m, 3, 3)\) or \((3, 3)\), optional
- round(decimals=0, *, inplace=False)[source]
Round the Cartesian coordinates of this instance to a given number of decimals.
- delete_atoms(atom_subset)[source]
Create a copy of this instance with all atoms in atom_subset removed.
- Parameters
atom_subset (
Sequence[str]
) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.- Returns
A new molecule with all atoms in atom_subset removed.
- Return type
- Raises
- get_supercell(supercell_size)[source]
Construct a new supercell by duplicating the molecule.
- Parameters
supercell_size (
tuple[int, int, int]
) – The number of new unit cells along each of the three Cartesian axes.- Returns
The new supercell constructed from self.
- Return type
- concatenate(other, lattice=None, axis=1)[source]
Concatenate one or more molecules along the user-specified axis.
- Parameters
other (
Iterable[FOX.MultiMolecule]
) – The to-be concatenated molecules.lattice (
np.ndarray
, optional) – The lattice of the new molecule.
- Returns
The newly concatenated molecule.
- Return type
- add_atoms(coords, symbols='Xx')[source]
Create a copy of this instance with all atoms in atom_subset appended.
Examples
>>> import numpy as np >>> from FOX import MultiMolecule, example_xyz >>> mol = MultiMolecule.from_xyz(example_xyz) >>> coords: np.ndarray = np.random.rand(73, 3) # Add 73 new atoms with random coords >>> symbols = 'Br' >>> mol_new: MultiMolecule = mol.add_atoms(coords, symbols) >>> print(repr(mol)) MultiMolecule(..., shape=(4905, 227, 3), dtype='float64') >>> print(repr(mol_new)) MultiMolecule(..., shape=(4905, 300, 3), dtype='float64')
- Parameters
coords (array-like) – A \((3,)\), \((n, 3)\), \((m, 3)\) or \((m, n, 3)\) array-like object with
m == len(self)
. Represents the Cartesian coordinates of the to-be added atoms.symbols (
str
orIterable[str]
) – One or more atomic symbols of the to-be added atoms.
- Returns
A new molecule with all atoms in atom_subset appended.
- Return type
- guess_bonds(atom_subset=None)[source]
Guess bonds within the molecules based on atom type and inter-atomic distances.
Bonds are guessed based on the first molecule in this instance Performs an inplace modification of self.bonds
- Parameters
atom_subset (
Sequence[str]
, optional) – A tuple of atomic symbols. Bonds are guessed between all atoms whose atomic symbol is in atom_subset. IfNone
, guess bonds for all atoms in this instance.
- random_slice(start=0, stop=None, p=0.5, inplace=False)[source]
Construct a new
MultiMolecule
instance by randomly slicing this instance.The probability of including a particular element is equivalent to p.
- Parameters
start (
int
) – Start of the interval.stop (
int
, optional) – End of the interval.p (
float
) – The probability of including each particular molecule in this instance. Values must be between0
(0%) and1
(100%).inplace (
bool
) – Instead of returning the new coordinates, perform an inplace update of this instance.
- Returns
If inplace is
True
, return a new molecule.- Return type
- Raises
ValueError – Raised if p is smaller than
0.0
or larger than1.0
.
- reset_origin(mol_subset=None, atom_subset=None, inplace=True, rot_ref=None)[source]
Reallign all molecules in this instance.
All molecules in this instance are rotating and translating, by performing a partial partial Procrustes superimposition with respect to the first molecule in this instance.
The superimposition is carried out with respect to the first molecule in this instance.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.inplace (
bool
) – Instead of returning the new coordinates, perform an inplace update of this instance.
- Returns
If inplace is
True
, return a newMultiMolecule
instance.- Return type
- sort(sort_by='symbol', reverse=False, inplace=True)[source]
Sort the atoms in this instance and self.atoms, performing in inplace update.
- Parameters
sort_by (
str
orSequence[int]
) – The property which is to be used for sorting. Accepted values:"symbol"
(i.e. alphabetical),"atnum"
,"mass"
,"radius"
or"connectors"
. See the plams.PeriodicTable module for more details. Alternatively, a user-specified sequence of indices can be provided for sorting.reverse (
bool
) – Sort in reversed order.inplace (
bool
) – Instead of returning the new coordinates, perform an inplace update of this instance.
- Returns
If inplace is
True
, return a newMultiMolecule
instance.- Return type
- residue_argsort(concatenate=True)[source]
Return the indices that would sort this instance by residue number.
Residues are defined based on moleculair fragments based on self.bonds.
- Parameters
concatenate (
bool
) – IfFalse
, returned a nested list with atomic indices. Each sublist contains the indices of a single residue.- Returns
A 1D array of indices that would sort \(n\) atoms this instance.
- Return type
np.ndarray[np.int64]
, shape \((n,)\)
- get_center_of_mass(mol_subset=None, atom_subset=None)[source]
Get the center of mass.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A 2D array with the centres of mass of \(m\) molecules with \(n\) atoms.
- Return type
np.ndarray[np.float64]
, shape \((m, 3)\)
- get_bonds_per_atom(atom_subset=None)[source]
Get the number of bonds per atom in this instance.
- Parameters
atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.- Returns
A 1D array with the number of bonds per atom, for all \(n\) atoms in this instance.
- Return type
\(n\) np.ndarray [np.int64]
- init_average_velocity(timestep=1.0, rms=False, mol_subset=None, atom_subset=None)[source]
Calculate the average atomic velocty.
The average velocity (in fs/A) is calculated for all atoms in atom_subset over the course of a trajectory.
The velocity is averaged over all atoms in a particular atom subset.
- Parameters
timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.rms (
bool
) – Calculate the root-mean squared average velocity instead.mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A dataframe holding \(m-1\) velocities averaged over one or more atom subsets.
- Return type
- init_time_averaged_velocity(timestep=1.0, rms=False, mol_subset=None, atom_subset=None)[source]
Calculate the time-averaged velocty.
The time-averaged velocity (in fs/A) is calculated for all atoms in atom_subset over the course of a trajectory.
- Parameters
timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.rms (
bool
) – Calculate the root-mean squared time-averaged velocity instead.mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A dataframe holding \(m-1\) time-averaged velocities.
- Return type
- init_rmsd(mol_subset=None, atom_subset=None, reset_origin=True)[source]
Initialize the RMSD calculation, returning a dataframe.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.reset_origin (
bool
) – Reset the origin of each molecule in this instance by means of a partial Procrustes superimposition, translating and rotating the molecules.
- Returns
A dataframe of RMSDs with one column for every string or list of ints in atom_subset. Keys consist of atomic symbols (e.g.
"Cd"
) if atom_subset contains strings, otherwise a more generic ‘series ‘ + str(int) scheme is adopted (e.g."series 2"
). Molecular indices are used as index.- Return type
- init_rmsf(mol_subset=None, atom_subset=None, reset_origin=True)[source]
Initialize the RMSF calculation, returning a dataframe.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.reset_origin (
bool
) – Reset the origin of each molecule in this instance by means of a partial Procrustes superimposition, translating and rotating the molecules.
- Returns
A dataframe of RMSFs with one column for every string or list of ints in atom_subset. Keys consist of atomic symbols (e.g.
"Cd"
) if atom_subset contains strings, otherwise a more generic ‘series ‘ + str(int) scheme is adopted (e.g."series 2"
). Molecular indices are used as indices.- Return type
- get_average_velocity(timestep=1.0, rms=False, mol_subset=None, atom_subset=None)[source]
Return the mean or root-mean squared velocity.
- Parameters
timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.rms (
bool
) – Calculate the root-mean squared average velocity instead.mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A 1D array holding \(m-1\) velocities averaged over one or more atom subsets.
- Return type
np.ndarray[np.float64]
, shape \((m-1,)\)
- get_time_averaged_velocity(timestep=1.0, rms=False, mol_subset=None, atom_subset=None)[source]
Return the mean or root-mean squared velocity (mean = time-averaged).
- Parameters
timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.rms (
bool
) – Calculate the root-mean squared average velocity instead.mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A 1D array holding \(n\) time-averaged velocities.
- Return type
np.ndarray[np.float64]
, shape \((n,)\)
- get_velocity(timestep=1.0, norm=True, mol_subset=None, atom_subset=None)[source]
Return the atomic velocties.
The velocity (in fs/A) is calculated for all atoms in atom_subset over the course of a trajectory.
- Parameters
timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.norm (
bool
) – IfTrue
return the norm of the \(x\), \(y\) and \(z\) velocity components.mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A 2D or 3D array of atomic velocities, the number of dimensions depending on the value of norm (
True
= 2D;False
= 3D).- Return type
np.ndarray[np.float64]
, shape \((m, n)\) or \((m, n, 3)\)
- get_rmsd(mol_subset=None, atom_subset=None)[source]
Calculate the root mean square displacement (RMSD).
The RMSD is calculated with respect to the first molecule in this instance.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A dataframe with the RMSD as a function of the XYZ frame numbers.
- Return type
- get_rmsf(mol_subset=None, atom_subset=None)[source]
Calculate the root mean square fluctuation (RMSF).
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A dataframe with the RMSF as a function of atomic indices.
- Return type
- init_shell_search(mol_subset=None, atom_subset=None, rdf_cutoff=0.5)[source]
Calculate and return properties which can help determining shell structures.
Warning
Depercated.
- static get_at_idx(rmsf, idx_series, dist_dict)[source]
Create subsets of atomic indices.
Warning
Depercated.
- init_rdf(mol_subset=None, atom_subset=None, *, dr=0.05, r_max=12.0, periodic=None, atom_pairs=None)[source]
Initialize the calculation of radial distribution functions (RDFs).
RDFs are calculated for all possible atom-pairs in atom_subset and returned as a dataframe.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.dr (
float
) – The integration step-size in Ångström, i.e. the distance between concentric spheres.r_max (
float
) – The maximum to be evaluated interatomic distance in Ångström.periodic (
str
, optional) – If specified, correct for the systems periodicity ifself.lattice is not None
. Accepts"x"
,"y"
and/or"z"
.atom_pairs (
Iterable[tuple[str, str]]
) – An explicit list of atom-pairs for the to-be calculated distances. Note that atom_pairs and atom_subset are mutually exclusive.
- Returns
A dataframe of radial distribution functions, averaged over all conformations in xyz_array. Keys are of the form: at_symbol1 + ‘ ‘ + at_symbol2 (e.g.
"Cd Cd"
). Radii are used as index.- Return type
- get_dist_mat(mol_subset=None, atom_subset=(None, None), lattice=None, periodicity=range(0, 3))[source]
Create and return a distance matrix for all molecules and atoms in this instance.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.lattice (
np.ndarray[np.float64]
, shape \((3, 3)\) or \((m, 3, 3)\), optional) – If notNone
, use the specified lattice vectors for correcting periodic effects.periodicty (
str
) – The axes along which the system’s periodicity extends; accepts"x"
,"y"
and/or"z"
. Only relevant iflattice is not None
.
- Returns
A 3D distance matrix of \(m\) molecules, created out of two sets of \(n\) and \(k\) atoms.
- Return type
np.ndarray[np.float64]
, shape \((m, n, k)\)
- get_pair_dict(atom_subset, r=2)[source]
Take a subset of atoms and return a dictionary.
- Parameters
atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.r (
int
) – The length of the to-be returned subsets.
- init_power_spectrum(mol_subset=None, atom_subset=None, freq_max=4000, timestep=1)[source]
Calculate and return the power spectrum associated with this instance.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.freq_max (
int
) – The maximum to be returned wavenumber (cm**-1).timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.
- Returns
A DataFrame containing the power spectrum for each set of atoms in atom_subset.
- Return type
- get_vacf(mol_subset=None, atom_subset=None, timestep=1)[source]
Calculate and return the velocity autocorrelation function (VACF).
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.timestep (
float
) – The stepsize, in femtoseconds, between subsequent frames.
- Returns
A DataFrame containing the power spectrum for each set of atoms in atom_subset.
- Return type
- T
The transposed array.
Same as
self.transpose()
.Examples
>>> x = np.array([[1.,2.],[3.,4.]]) >>> x array([[ 1., 2.], [ 3., 4.]]) >>> x.T array([[ 1., 3.], [ 2., 4.]]) >>> x = np.array([1.,2.,3.,4.]) >>> x array([ 1., 2., 3., 4.]) >>> x.T array([ 1., 2., 3., 4.])
See also
- all(axis=None, out=None, keepdims=False, *, where=True)
Returns True if all elements evaluate to True.
Refer to numpy.all for full documentation.
See also
numpy.all
equivalent function
- any(axis=None, out=None, keepdims=False, *, where=True)
Returns True if any of the elements of a evaluate to True.
Refer to numpy.any for full documentation.
See also
numpy.any
equivalent function
- argmax(axis=None, out=None)
Return indices of the maximum values along the given axis.
Refer to numpy.argmax for full documentation.
See also
numpy.argmax
equivalent function
- argmin(axis=None, out=None)
Return indices of the minimum values along the given axis.
Refer to numpy.argmin for detailed documentation.
See also
numpy.argmin
equivalent function
- argpartition(kth, axis=- 1, kind='introselect', order=None)
Returns the indices that would partition this array.
Refer to numpy.argpartition for full documentation.
New in version 1.8.0.
See also
numpy.argpartition
equivalent function
- argsort(axis=- 1, kind=None, order=None)
Returns the indices that would sort this array.
Refer to numpy.argsort for full documentation.
See also
numpy.argsort
equivalent function
- astype(dtype, order='K', casting='unsafe', subok=True, copy=True)
Copy of the array, cast to a specified type.
- Parameters
dtype (str or dtype) – Typecode or data-type to which the array is cast.
order ({'C', 'F', 'A', 'K'}, optional) – Controls the memory layout order of the result. ‘C’ means C order, ‘F’ means Fortran order, ‘A’ means ‘F’ order if all the arrays are Fortran contiguous, ‘C’ order otherwise, and ‘K’ means as close to the order the array elements appear in memory as possible. Default is ‘K’.
casting ({'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional) –
Controls what kind of data casting may occur. Defaults to ‘unsafe’ for backwards compatibility.
’no’ means the data types should not be cast at all.
’equiv’ means only byte-order changes are allowed.
’safe’ means only casts which can preserve values are allowed.
’same_kind’ means only safe casts or casts within a kind, like float64 to float32, are allowed.
’unsafe’ means any data conversions may be done.
subok (bool, optional) – If True, then sub-classes will be passed-through (default), otherwise the returned array will be forced to be a base-class array.
copy (bool, optional) – By default, astype always returns a newly allocated array. If this is set to false, and the dtype, order, and subok requirements are satisfied, the input array is returned instead of a copy.
- Returns
arr_t – Unless copy is False and the other conditions for returning the input array are satisfied (see description for copy input parameter), arr_t is a new array of the same shape as the input array, with dtype, order given by dtype, order.
- Return type
ndarray
Notes
Changed in version 1.17.0: Casting between a simple data type and a structured one is possible only for “unsafe” casting. Casting to multiple fields is allowed, but casting from multiple fields is not.
Changed in version 1.9.0: Casting from numeric to string types in ‘safe’ casting mode requires that the string dtype length is long enough to store the max integer/float value converted.
- Raises
ComplexWarning – When casting from complex to float or int. To avoid this, one should use
a.real.astype(t)
.
Examples
>>> x = np.array([1, 2, 2.5]) >>> x array([1. , 2. , 2.5])
>>> x.astype(int) array([1, 2, 2])
- property atnum
Get the atomic numbers of all atoms in
MultiMolecule.atoms
as 1D array.
- property atom1
Get or set the indices of the first atoms in all bonds of
MultiMolecule.bonds
as 1D array.
- property atom12
Get or set the indices of the atoms for all bonds in
MultiMolecule.bonds
as 2D array.
- property atom2
Get or set the indices of the second atoms in all bonds of
MultiMolecule.bonds
as 1D array.
- base
Base object if memory is from some other object.
Examples
The base of an array that owns its memory is None:
>>> x = np.array([1,2,3,4]) >>> x.base is None True
Slicing creates a view, whose memory is shared with x:
>>> y = x[2:] >>> y.base is x True
- byteswap(inplace=False)
Swap the bytes of the array elements
Toggle between low-endian and big-endian data representation by returning a byteswapped array, optionally swapped in-place. Arrays of byte-strings are not swapped. The real and imaginary parts of a complex number are swapped individually.
- Parameters
inplace (bool, optional) – If
True
, swap bytes in-place, default isFalse
.- Returns
out – The byteswapped array. If inplace is
True
, this is a view to self.- Return type
ndarray
Examples
>>> A = np.array([1, 256, 8755], dtype=np.int16) >>> list(map(hex, A)) ['0x1', '0x100', '0x2233'] >>> A.byteswap(inplace=True) array([ 256, 1, 13090], dtype=int16) >>> list(map(hex, A)) ['0x100', '0x1', '0x3322']
Arrays of byte-strings are not swapped
>>> A = np.array([b'ceg', b'fac']) >>> A.byteswap() array([b'ceg', b'fac'], dtype='|S3')
A.newbyteorder().byteswap()
produces an array with the same valuesbut different representation in memory
>>> A = np.array([1, 2, 3]) >>> A.view(np.uint8) array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0], dtype=uint8) >>> A.newbyteorder().byteswap(inplace=True) array([1, 2, 3]) >>> A.view(np.uint8) array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3], dtype=uint8)
- choose(choices, out=None, mode='raise')
Use an index array to construct a new array from a set of choices.
Refer to numpy.choose for full documentation.
See also
numpy.choose
equivalent function
- clip(min=None, max=None, out=None, **kwargs)
Return an array whose values are limited to
[min, max]
. One of max or min must be given.Refer to numpy.clip for full documentation.
See also
numpy.clip
equivalent function
- compress(condition, axis=None, out=None)
Return selected slices of this array along given axis.
Refer to numpy.compress for full documentation.
See also
numpy.compress
equivalent function
- conj()
Complex-conjugate all elements.
Refer to numpy.conjugate for full documentation.
See also
numpy.conjugate
equivalent function
- conjugate()
Return the complex conjugate, element-wise.
Refer to numpy.conjugate for full documentation.
See also
numpy.conjugate
equivalent function
- property connectors
Get the atomic connectors of all atoms in
MultiMolecule.atoms
as 1D array.
- copy(order='C', *, deep=True)
Create a copy of this instance.
- Parameters
order (
str
) – Controls the memory layout of the copy. Seendarray.copy
for details.copy_attr (
bool
) – Whether or not the attributes of this instance should be returned as copies or views.
- Returns
A copy of this instance.
- Return type
- ctypes
An object to simplify the interaction of the array with the ctypes module.
This attribute creates an object that makes it easier to use arrays when calling shared libraries with the ctypes module. The returned object has, among others, data, shape, and strides attributes (see Notes below) which themselves return ctypes objects that can be used as arguments to a shared library.
- Parameters
None –
- Returns
c – Possessing attributes data, shape, strides, etc.
- Return type
Python object
See also
Notes
Below are the public attributes of this object which were documented in “Guide to NumPy” (we have omitted undocumented public attributes, as well as documented private attributes):
- _ctypes.data
A pointer to the memory area of the array as a Python integer. This memory area may contain data that is not aligned, or not in correct byte-order. The memory area may not even be writeable. The array flags and data-type of this array should be respected when passing this attribute to arbitrary C-code to avoid trouble that can include Python crashing. User Beware! The value of this attribute is exactly the same as
self._array_interface_['data'][0]
.Note that unlike
data_as
, a reference will not be kept to the array: code likectypes.c_void_p((a + b).ctypes.data)
will result in a pointer to a deallocated array, and should be spelt(a + b).ctypes.data_as(ctypes.c_void_p)
- _ctypes.shape
A ctypes array of length self.ndim where the basetype is the C-integer corresponding to
dtype('p')
on this platform. This base-type could be ctypes.c_int, ctypes.c_long, or ctypes.c_longlong depending on the platform. The c_intp type is defined accordingly in numpy.ctypeslib. The ctypes array contains the shape of the underlying array.- Type
(c_intp*self.ndim)
- _ctypes.strides
A ctypes array of length self.ndim where the basetype is the same as for the shape attribute. This ctypes array contains the strides information from the underlying array. This strides information is important for showing how many bytes must be jumped to get to the next element in the array.
- Type
(c_intp*self.ndim)
- _ctypes.data_as(obj)
Return the data pointer cast to a particular c-types object. For example, calling
self._as_parameter_
is equivalent toself.data_as(ctypes.c_void_p)
. Perhaps you want to use the data as a pointer to a ctypes array of floating-point data:self.data_as(ctypes.POINTER(ctypes.c_double))
.The returned pointer will keep a reference to the array.
- _ctypes.shape_as(obj)
Return the shape tuple as an array of some other c-types type. For example:
self.shape_as(ctypes.c_short)
.
- _ctypes.strides_as(obj)
Return the strides tuple as an array of some other c-types type. For example:
self.strides_as(ctypes.c_longlong)
.
If the ctypes module is not available, then the ctypes attribute of array objects still returns something useful, but ctypes objects are not returned and errors may be raised instead. In particular, the object will still have the
as_parameter
attribute which will return an integer equal to the data attribute.Examples
>>> import ctypes >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32) >>> x array([[0, 1], [2, 3]], dtype=int32) >>> x.ctypes.data 31962608 # may vary >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)) <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents c_uint(0) >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents c_ulong(4294967296) >>> x.ctypes.shape <numpy.core._internal.c_long_Array_2 object at 0x7ff2fc1fce60> # may vary >>> x.ctypes.strides <numpy.core._internal.c_long_Array_2 object at 0x7ff2fc1ff320> # may vary
- cumprod(axis=None, dtype=None, out=None)
Return the cumulative product of the elements along the given axis.
Refer to numpy.cumprod for full documentation.
See also
numpy.cumprod
equivalent function
- cumsum(axis=None, dtype=None, out=None)
Return the cumulative sum of the elements along the given axis.
Refer to numpy.cumsum for full documentation.
See also
numpy.cumsum
equivalent function
- data
Python buffer object pointing to the start of the array’s data.
- diagonal(offset=0, axis1=0, axis2=1)
Return specified diagonals. In NumPy 1.9 the returned array is a read-only view instead of a copy as in previous NumPy versions. In a future version the read-only restriction will be removed.
Refer to
numpy.diagonal()
for full documentation.See also
numpy.diagonal
equivalent function
- dot(b, out=None)
Dot product of two arrays.
Refer to numpy.dot for full documentation.
See also
numpy.dot
equivalent function
Examples
>>> a = np.eye(2) >>> b = np.ones((2, 2)) * 2 >>> a.dot(b) array([[2., 2.], [2., 2.]])
This array method can be conveniently chained:
>>> a.dot(b).dot(b) array([[8., 8.], [8., 8.]])
- dtype
Data-type of the array’s elements.
- Parameters
None –
- Returns
d
- Return type
numpy dtype object
See also
Examples
>>> x array([[0, 1], [2, 3]]) >>> x.dtype dtype('int32') >>> type(x.dtype) <type 'numpy.dtype'>
- dump(file)
Dump a pickle of the array to the specified file. The array can be read back with pickle.load or numpy.load.
- Parameters
file (str or Path) –
A string naming the dump file.
Changed in version 1.17.0: pathlib.Path objects are now accepted.
- dumps()
Returns the pickle of the array as a string. pickle.loads or numpy.loads will convert the string back to an array.
- Parameters
None –
- fill(value)
Fill the array with a scalar value.
- Parameters
value (scalar) – All elements of a will be assigned this value.
Examples
>>> a = np.array([1, 2]) >>> a.fill(0) >>> a array([0, 0]) >>> a = np.empty(2) >>> a.fill(1) >>> a array([1., 1.])
- flags
Information about the memory layout of the array.
- C_CONTIGUOUS(C)
The data is in a single, C-style contiguous segment.
- F_CONTIGUOUS(F)
The data is in a single, Fortran-style contiguous segment.
- OWNDATA(O)
The array owns the memory it uses or borrows it from another object.
- WRITEABLE(W)
The data area can be written to. Setting this to False locks the data, making it read-only. A view (slice, etc.) inherits WRITEABLE from its base array at creation time, but a view of a writeable array may be subsequently locked while the base array remains writeable. (The opposite is not true, in that a view of a locked array may not be made writeable. However, currently, locking a base object does not lock any views that already reference it, so under that circumstance it is possible to alter the contents of a locked array via a previously created writeable view onto it.) Attempting to change a non-writeable array raises a RuntimeError exception.
- ALIGNED(A)
The data and all elements are aligned appropriately for the hardware.
- WRITEBACKIFCOPY(X)
This array is a copy of some other array. The C-API function PyArray_ResolveWritebackIfCopy must be called before deallocating to the base array will be updated with the contents of this array.
- UPDATEIFCOPY(U)
(Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array. When this array is deallocated, the base array will be updated with the contents of this array.
- FNC
F_CONTIGUOUS and not C_CONTIGUOUS.
- FORC
F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).
- BEHAVED(B)
ALIGNED and WRITEABLE.
- CARRAY(CA)
BEHAVED and C_CONTIGUOUS.
- FARRAY(FA)
BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.
Notes
The flags object can be accessed dictionary-like (as in
a.flags['WRITEABLE']
), or by using lowercased attribute names (as ina.flags.writeable
). Short flag names are only supported in dictionary access.Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be changed by the user, via direct assignment to the attribute or dictionary entry, or by calling ndarray.setflags.
The array flags cannot be set arbitrarily:
UPDATEIFCOPY can only be set
False
.WRITEBACKIFCOPY can only be set
False
.ALIGNED can only be set
True
if the data is truly aligned.WRITEABLE can only be set
True
if the array owns its own memory or the ultimate owner of the memory exposes a writeable buffer interface or is a string.
Arrays can be both C-style and Fortran-style contiguous simultaneously. This is clear for 1-dimensional arrays, but can also be true for higher dimensional arrays.
Even for contiguous arrays a stride for a given dimension
arr.strides[dim]
may be arbitrary ifarr.shape[dim] == 1
or the array has no elements. It does not generally hold thatself.strides[-1] == self.itemsize
for C-style contiguous arrays orself.strides[0] == self.itemsize
for Fortran-style contiguous arrays is true.
- flat
A 1-D iterator over the array.
This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object.
Examples
>>> x = np.arange(1, 7).reshape(2, 3) >>> x array([[1, 2, 3], [4, 5, 6]]) >>> x.flat[3] 4 >>> x.T array([[1, 4], [2, 5], [3, 6]]) >>> x.T.flat[3] 5 >>> type(x.flat) <class 'numpy.flatiter'>
An assignment example:
>>> x.flat = 3; x array([[3, 3, 3], [3, 3, 3]]) >>> x.flat[[1,4]] = 1; x array([[3, 1, 3], [3, 1, 3]])
- flatten(order='C')
Return a copy of the array collapsed into one dimension.
- Parameters
order ({'C', 'F', 'A', 'K'}, optional) – ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.
- Returns
y – A copy of the input array, flattened to one dimension.
- Return type
ndarray
Examples
>>> a = np.array([[1,2], [3,4]]) >>> a.flatten() array([1, 2, 3, 4]) >>> a.flatten('F') array([1, 3, 2, 4])
- getfield(dtype, offset=0)
Returns a field of the given array as a certain type.
A field is a view of the array data with a given data-type. The values in the view are determined by the given type and the offset into the current array in bytes. The offset needs to be such that the view dtype fits in the array dtype; for example an array of dtype complex128 has 16-byte elements. If taking a view with a 32-bit integer (4 bytes), the offset needs to be between 0 and 12 bytes.
- Parameters
Examples
>>> x = np.diag([1.+1.j]*2) >>> x[1, 1] = 2 + 4.j >>> x array([[1.+1.j, 0.+0.j], [0.+0.j, 2.+4.j]]) >>> x.getfield(np.float64) array([[1., 0.], [0., 2.]])
By choosing an offset of 8 bytes we can select the complex part of the array for our view:
>>> x.getfield(np.float64, offset=8) array([[1., 0.], [0., 4.]])
- imag
The imaginary part of the array.
Examples
>>> x = np.sqrt([1+0j, 0+1j]) >>> x.imag array([ 0. , 0.70710678]) >>> x.imag.dtype dtype('float64')
- init_adf(mol_subset=None, atom_subset=None, *, r_max=8.0, weight=<function neg_exp>, periodic=None, atom_pairs=None)[source]
Initialize the calculation of distance-weighted angular distribution functions (ADFs).
ADFs are calculated for all possible atom-pairs in atom_subset and returned as a dataframe.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.r_max (
float
) – The maximum inter-atomic distance (in Angstrom) for which angles are constructed. The distance cuttoff can be disabled by settings this value tonp.inf
,"np.inf"
or"inf"
.weight (
Callable[[np.ndarray], np.ndarray]
, optional) – A callable for creating a weighting factor from inter-atomic distances. The callable should take an array as input and return an array. Given an angle \(\phi_{ijk}\), to the distance \(r_{ijk}\) is defined as \(max[r_{ij}, r_{jk}]\). Set toNone
to disable distance weighting.periodic (
str
, optional) – If specified, correct for the systems periodicity ifself.lattice is not None
. Accepts"x"
,"y"
and/or"z"
.atom_pairs (
Iterable[tuple[str, str, str]]
) – An explicit list of atom-triples for the to-be calculated angles. Note that atom_pairs and atom_subset are mutually exclusive.
- Returns
A dataframe of angular distribution functions, averaged over all conformations in this instance.
- Return type
Note
Disabling the distance cuttoff is strongly recommended (i.e. it is faster) for large values of r_max. As a rough guideline,
r_max="inf"
is roughly as fast asr_max=15.0
(though this is, of course, system dependant).Note
The ADF construction will be conducted in parralel if the DASK package is installed. DASK can be installed, via anaconda, with the following command:
conda install -n FOX -y -c conda-forge dask
.
- item(*args)
Copy an element of an array to a standard Python scalar and return it.
- Parameters
*args (Arguments (variable number and type)) –
none: in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned.
int_type: this argument is interpreted as a flat index into the array, specifying which element to copy and return.
tuple of int_types: functions as does a single int_type argument, except that the argument is interpreted as an nd-index into the array.
- Returns
z – A copy of the specified element of the array as a suitable Python scalar
- Return type
Standard Python scalar object
Notes
When the data type of a is longdouble or clongdouble, item() returns a scalar array object because there is no available Python scalar that would not lose information. Void arrays return a buffer object for item(), unless fields are defined, in which case a tuple is returned.
item is very similar to a[args], except, instead of an array scalar, a standard Python scalar is returned. This can be useful for speeding up access to elements of the array and doing arithmetic on elements of the array using Python’s optimized math.
Examples
>>> np.random.seed(123) >>> x = np.random.randint(9, size=(3, 3)) >>> x array([[2, 2, 6], [1, 3, 6], [1, 0, 1]]) >>> x.item(3) 1 >>> x.item(7) 0 >>> x.item((0, 1)) 2 >>> x.item((2, 2)) 1
- itemset(*args)
Insert scalar into an array (scalar is cast to array’s dtype, if possible)
There must be at least 1 argument, and define the last argument as item. Then,
a.itemset(*args)
is equivalent to but faster thana[args] = item
. The item should be a scalar value and args must select a single item in the array a.- Parameters
*args (Arguments) – If one argument: a scalar, only used in case a is of size 1. If two arguments: the last argument is the value to be set and must be a scalar, the first argument specifies a single array element location. It is either an int or a tuple.
Notes
Compared to indexing syntax, itemset provides some speed increase for placing a scalar into a particular location in an ndarray, if you must do this. However, generally this is discouraged: among other problems, it complicates the appearance of the code. Also, when using itemset (and item) inside a loop, be sure to assign the methods to a local variable to avoid the attribute look-up at each loop iteration.
Examples
>>> np.random.seed(123) >>> x = np.random.randint(9, size=(3, 3)) >>> x array([[2, 2, 6], [1, 3, 6], [1, 0, 1]]) >>> x.itemset(4, 0) >>> x.itemset((2, 2), 9) >>> x array([[2, 2, 6], [1, 0, 6], [1, 0, 9]])
- itemsize
Length of one array element in bytes.
Examples
>>> x = np.array([1,2,3], dtype=np.float64) >>> x.itemsize 8 >>> x = np.array([1,2,3], dtype=np.complex128) >>> x.itemsize 16
- property loc
A getter and setter for atom-type-based slicing.
Get, set and del operations are performed using the list(s) of atomic indices associated with the provided atomic symbol(s). Accepts either one or more atomic symbols.
Examples
>>> mol = MultiMolecule(...) >>> mol.atoms = { ... 'Cd': [0, 1, 2, 3, 4, 5], ... 'Se': [6, 7, 8, 9, 10, 11], ... 'O': [12, 13, 14], ... } >>> (mol.loc['Cd'] == mol[mol.atoms['Cd']]).all() True >>> idx = [] >>> for atom in ["Cd", "Se", "O"]: ... idx += mol.atoms[atom].tolist() >>> (mol.loc['Cd', 'Se', 'O'] == mol[idx]).all() True >>> mol.loc['Cd'] = 1 >>> print((mol.loc['Cd'] == 1).all()) True >>> del mol.loc['Cd'] ValueError: cannot delete array elements
- Parameters
mol (
FOX.MultiMolecule
) – A MultiMolecule instance; see_MolLoc.mol
.
- mol
A MultiMolecule instance.
- Type
- atoms_view
A read-only view of
_MolLoc.mol.atoms
.- Type
- property mass
Get the atomic masses of all atoms in
MultiMolecule.atoms
as 1D array.
- max(axis=None, out=None, keepdims=False, initial=<no value>, where=True)
Return the maximum along a given axis.
Refer to numpy.amax for full documentation.
See also
numpy.amax
equivalent function
- mean(axis=None, dtype=None, out=None, keepdims=False, *, where=True)
Returns the average of the array elements along given axis.
Refer to numpy.mean for full documentation.
See also
numpy.mean
equivalent function
- min(axis=None, out=None, keepdims=False, initial=<no value>, where=True)
Return the minimum along a given axis.
Refer to numpy.amin for full documentation.
See also
numpy.amin
equivalent function
- nbytes
Total bytes consumed by the elements of the array.
Notes
Does not include memory consumed by non-element attributes of the array object.
Examples
>>> x = np.zeros((3,5,2), dtype=np.complex128) >>> x.nbytes 480 >>> np.prod(x.shape) * x.itemsize 480
- ndim
Number of array dimensions.
Examples
>>> x = np.array([1, 2, 3]) >>> x.ndim 1 >>> y = np.zeros((2, 3, 4)) >>> y.ndim 3
- newbyteorder(new_order='S', /)
Return the array with the same data viewed with a different byte order.
Equivalent to:
arr.view(arr.dtype.newbytorder(new_order))
Changes are also made in all fields and sub-arrays of the array data type.
- Parameters
new_order (string, optional) –
Byte order to force; a value from the byte order specifications below. new_order codes can be any of:
’S’ - swap dtype from current to opposite endian
{‘<’, ‘little’} - little endian
{‘>’, ‘big’} - big endian
’=’ - native order, equivalent to sys.byteorder
{‘|’, ‘I’} - ignore (no change to byte order)
The default value (‘S’) results in swapping the current byte order.
- Returns
new_arr – New array object with the dtype reflecting given change to the byte order.
- Return type
array
- nonzero()
Return the indices of the elements that are non-zero.
Refer to numpy.nonzero for full documentation.
See also
numpy.nonzero
equivalent function
- property order
Get or set the bond orders for all bonds in
MultiMolecule.bonds
as 1D array.
- partition(kth, axis=- 1, kind='introselect', order=None)
Rearranges the elements in the array in such a way that the value of the element in kth position is in the position it would be in a sorted array. All elements smaller than the kth element are moved before this element and all equal or greater are moved behind it. The ordering of the elements in the two partitions is undefined.
New in version 1.8.0.
- Parameters
kth (int or sequence of ints) – Element index to partition by. The kth element value will be in its final sorted position and all smaller elements will be moved before it and all equal or greater elements behind it. The order of all elements in the partitions is undefined. If provided with a sequence of kth it will partition all elements indexed by kth of them into their sorted position at once.
axis (int, optional) – Axis along which to sort. Default is -1, which means sort along the last axis.
kind ({'introselect'}, optional) – Selection algorithm. Default is ‘introselect’.
order (str or list of str, optional) – When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need to be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties.
See also
numpy.partition
Return a parititioned copy of an array.
argpartition
Indirect partition.
sort
Full sort.
Notes
See
np.partition
for notes on the different algorithms.Examples
>>> a = np.array([3, 4, 2, 1]) >>> a.partition(3) >>> a array([2, 1, 3, 4])
>>> a.partition((1, 3)) >>> a array([1, 2, 3, 4])
- prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)
Return the product of the array elements over the given axis
Refer to numpy.prod for full documentation.
See also
numpy.prod
equivalent function
- ptp(axis=None, out=None, keepdims=False)
Peak to peak (maximum - minimum) value along a given axis.
Refer to numpy.ptp for full documentation.
See also
numpy.ptp
equivalent function
- put(indices, values, mode='raise')
Set
a.flat[n] = values[n]
for all n in indices.Refer to numpy.put for full documentation.
See also
numpy.put
equivalent function
- property radius
Get the atomic radii of all atoms in
MultiMolecule.atoms
as 1d array.
- ravel([order])
Return a flattened array.
Refer to numpy.ravel for full documentation.
See also
numpy.ravel
equivalent function
ndarray.flat
a flat iterator on the array.
- real
The real part of the array.
Examples
>>> x = np.sqrt([1+0j, 0+1j]) >>> x.real array([ 1. , 0.70710678]) >>> x.real.dtype dtype('float64')
See also
numpy.real
equivalent function
- repeat(repeats, axis=None)
Repeat elements of an array.
Refer to numpy.repeat for full documentation.
See also
numpy.repeat
equivalent function
- reshape(shape, order='C')
Returns an array containing the same data with a new shape.
Refer to numpy.reshape for full documentation.
See also
numpy.reshape
equivalent function
Notes
Unlike the free function numpy.reshape, this method on ndarray allows the elements of the shape parameter to be passed in as separate arguments. For example,
a.reshape(10, 11)
is equivalent toa.reshape((10, 11))
.
- resize(new_shape, refcheck=True)
Change shape and size of array in-place.
- Parameters
new_shape (tuple of ints, or n ints) – Shape of resized array.
refcheck (bool, optional) – If False, reference count will not be checked. Default is True.
- Returns
- Return type
- Raises
ValueError – If a does not own its own data or references or views to it exist, and the data memory must be changed. PyPy only: will always raise if the data memory must be changed, since there is no reliable way to determine if references or views to it exist.
SystemError – If the order keyword argument is specified. This behaviour is a bug in NumPy.
See also
resize
Return a new array with the specified shape.
Notes
This reallocates space for the data area if necessary.
Only contiguous arrays (data elements consecutive in memory) can be resized.
The purpose of the reference count check is to make sure you do not use this array as a buffer for another Python object and then reallocate the memory. However, reference counts can increase in other ways so if you are sure that you have not shared the memory for this array with another Python object, then you may safely set refcheck to False.
Examples
Shrinking an array: array is flattened (in the order that the data are stored in memory), resized, and reshaped:
>>> a = np.array([[0, 1], [2, 3]], order='C') >>> a.resize((2, 1)) >>> a array([[0], [1]])
>>> a = np.array([[0, 1], [2, 3]], order='F') >>> a.resize((2, 1)) >>> a array([[0], [2]])
Enlarging an array: as above, but missing entries are filled with zeros:
>>> b = np.array([[0, 1], [2, 3]]) >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple >>> b array([[0, 1, 2], [3, 0, 0]])
Referencing an array prevents resizing…
>>> c = a >>> a.resize((1, 1)) Traceback (most recent call last): ... ValueError: cannot resize an array that references or is referenced ...
Unless refcheck is False:
>>> a.resize((1, 1), refcheck=False) >>> a array([[0]]) >>> c array([[0]])
- searchsorted(v, side='left', sorter=None)
Find indices where elements of v should be inserted in a to maintain order.
For full documentation, see numpy.searchsorted
See also
numpy.searchsorted
equivalent function
- setfield(val, dtype, offset=0)
Put a value into a specified place in a field defined by a data-type.
Place val into a’s field defined by dtype and beginning offset bytes into the field.
- Parameters
- Returns
- Return type
See also
Examples
>>> x = np.eye(3) >>> x.getfield(np.float64) array([[1., 0., 0.], [0., 1., 0.], [0., 0., 1.]]) >>> x.setfield(3, np.int32) >>> x.getfield(np.int32) array([[3, 3, 3], [3, 3, 3], [3, 3, 3]], dtype=int32) >>> x array([[1.0e+000, 1.5e-323, 1.5e-323], [1.5e-323, 1.0e+000, 1.5e-323], [1.5e-323, 1.5e-323, 1.0e+000]]) >>> x.setfield(np.eye(3), np.int32) >>> x array([[1., 0., 0.], [0., 1., 0.], [0., 0., 1.]])
- setflags(write=None, align=None, uic=None)
Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY), respectively.
These Boolean-valued flags affect how numpy interprets the memory area used by a (see Notes below). The ALIGNED flag can only be set to True if the data is actually aligned according to the type. The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set to True. The flag WRITEABLE can only be set to True if the array owns its own memory, or the ultimate owner of the memory exposes a writeable buffer interface, or is a string. (The exception for string is made so that unpickling can be done without copying memory.)
- Parameters
Notes
Array flags provide information about how the memory area used for the array is to be interpreted. There are 7 Boolean flags in use, only four of which can be changed by the user: WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.
WRITEABLE (W) the data area can be written to;
ALIGNED (A) the data and strides are aligned appropriately for the hardware (as determined by the compiler);
UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;
WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced by .base). When the C-API function PyArray_ResolveWritebackIfCopy is called, the base array will be updated with the contents of this array.
All flags can be accessed using the single (upper case) letter as well as the full name.
Examples
>>> y = np.array([[3, 1, 7], ... [2, 0, 0], ... [8, 5, 9]]) >>> y array([[3, 1, 7], [2, 0, 0], [8, 5, 9]]) >>> y.flags C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True WRITEBACKIFCOPY : False UPDATEIFCOPY : False >>> y.setflags(write=0, align=0) >>> y.flags C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : False ALIGNED : False WRITEBACKIFCOPY : False UPDATEIFCOPY : False >>> y.setflags(uic=1) Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: cannot set WRITEBACKIFCOPY flag to True
- shape
Tuple of array dimensions.
The shape property is usually used to get the current shape of an array, but may also be used to reshape the array in-place by assigning a tuple of array dimensions to it. As with numpy.reshape, one of the new shape dimensions can be -1, in which case its value is inferred from the size of the array and the remaining dimensions. Reshaping an array in-place will fail if a copy is required.
Examples
>>> x = np.array([1, 2, 3, 4]) >>> x.shape (4,) >>> y = np.zeros((2, 3, 4)) >>> y.shape (2, 3, 4) >>> y.shape = (3, 8) >>> y array([[ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.]]) >>> y.shape = (3, 6) Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: total size of new array must be unchanged >>> np.zeros((4,2))[::2].shape = (-1,) Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: Incompatible shape for in-place modification. Use `.reshape()` to make a copy with the desired shape.
See also
numpy.reshape
similar function
ndarray.reshape
similar method
- size
Number of elements in the array.
Equal to
np.prod(a.shape)
, i.e., the product of the array’s dimensions.Notes
a.size returns a standard arbitrary precision Python integer. This may not be the case with other methods of obtaining the same value (like the suggested
np.prod(a.shape)
, which returns an instance ofnp.int_
), and may be relevant if the value is used further in calculations that may overflow a fixed size integer type.Examples
>>> x = np.zeros((3, 5, 2), dtype=np.complex128) >>> x.size 30 >>> np.prod(x.shape) 30
- squeeze(axis=None)
Remove axes of length one from a.
Refer to numpy.squeeze for full documentation.
See also
numpy.squeeze
equivalent function
- std(axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, where=True)
Returns the standard deviation of the array elements along given axis.
Refer to numpy.std for full documentation.
See also
numpy.std
equivalent function
- strides
Tuple of bytes to step in each dimension when traversing an array.
The byte offset of element
(i[0], i[1], ..., i[n])
in an array a is:offset = sum(np.array(i) * a.strides)
A more detailed explanation of strides can be found in the “ndarray.rst” file in the NumPy reference guide.
Notes
Imagine an array of 32-bit integers (each 4 bytes):
x = np.array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], dtype=np.int32)
This array is stored in memory as 40 bytes, one after the other (known as a contiguous block of memory). The strides of an array tell us how many bytes we have to skip in memory to move to the next position along a certain axis. For example, we have to skip 4 bytes (1 value) to move to the next column, but 20 bytes (5 values) to get to the same position in the next row. As such, the strides for the array x will be
(20, 4)
.See also
Examples
>>> y = np.reshape(np.arange(2*3*4), (2,3,4)) >>> y array([[[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]], [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]) >>> y.strides (48, 16, 4) >>> y[1,1,1] 17 >>> offset=sum(y.strides * np.array((1,1,1))) >>> offset/y.itemsize 17
>>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0) >>> x.strides (32, 4, 224, 1344) >>> i = np.array([3,5,2,2]) >>> offset = sum(i * x.strides) >>> x[3,5,2,2] 813 >>> offset / x.itemsize 813
- sum(axis=None, dtype=None, out=None, keepdims=False, initial=0, where=True)
Return the sum of the array elements over the given axis.
Refer to numpy.sum for full documentation.
See also
numpy.sum
equivalent function
- swapaxes(axis1, axis2)
Return a view of the array with axis1 and axis2 interchanged.
Refer to numpy.swapaxes for full documentation.
See also
numpy.swapaxes
equivalent function
- property symbol
Get the atomic symbols of all atoms in
MultiMolecule.atoms
as 1D array.
- take(indices, axis=None, out=None, mode='raise')
Return an array formed from the elements of a at the given indices.
Refer to numpy.take for full documentation.
See also
numpy.take
equivalent function
- tobytes(order='C')
Construct Python bytes containing the raw data bytes in the array.
Constructs Python bytes showing a copy of the raw contents of data memory. The bytes object is produced in C-order by default. This behavior is controlled by the
order
parameter.New in version 1.9.0.
- Parameters
order ({'C', 'F', 'A'}, optional) – Controls the memory layout of the bytes object. ‘C’ means C-order, ‘F’ means F-order, ‘A’ (short for Any) means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. Default is ‘C’.
- Returns
s – Python bytes exhibiting a copy of a’s raw data.
- Return type
Examples
>>> x = np.array([[0, 1], [2, 3]], dtype='<u2') >>> x.tobytes() b'\x00\x00\x01\x00\x02\x00\x03\x00' >>> x.tobytes('C') == x.tobytes() True >>> x.tobytes('F') b'\x00\x00\x02\x00\x01\x00\x03\x00'
- tofile(fid, sep='', format='%s')
Write array to a file as text or binary (default).
Data is always written in ‘C’ order, independent of the order of a. The data produced by this method can be recovered using the function fromfile().
- Parameters
fid (file or str or Path) –
An open file object, or a string containing a filename.
Changed in version 1.17.0: pathlib.Path objects are now accepted.
sep (str) – Separator between array items for text output. If “” (empty), a binary file is written, equivalent to
file.write(a.tobytes())
.format (str) – Format string for text file output. Each entry in the array is formatted to text by first converting it to the closest Python type, and then using “format” % item.
Notes
This is a convenience function for quick storage of array data. Information on endianness and precision is lost, so this method is not a good choice for files intended to archive data or transport data between machines with different endianness. Some of these problems can be overcome by outputting the data as text files, at the expense of speed and file size.
When fid is a file object, array contents are directly written to the file, bypassing the file object’s
write
method. As a result, tofile cannot be used with files objects supporting compression (e.g., GzipFile) or file-like objects that do not supportfileno()
(e.g., BytesIO).
- tolist()
Return the array as an
a.ndim
-levels deep nested list of Python scalars.Return a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible builtin Python type, via the ~numpy.ndarray.item function.
If
a.ndim
is 0, then since the depth of the nested list is 0, it will not be a list at all, but a simple Python scalar.- Parameters
none –
- Returns
y – The possibly nested list of array elements.
- Return type
object, or list of object, or list of list of object, or …
Notes
The array may be recreated via
a = np.array(a.tolist())
, although this may sometimes lose precision.Examples
For a 1D array,
a.tolist()
is almost the same aslist(a)
, except thattolist
changes numpy scalars to Python scalars:>>> a = np.uint32([1, 2]) >>> a_list = list(a) >>> a_list [1, 2] >>> type(a_list[0]) <class 'numpy.uint32'> >>> a_tolist = a.tolist() >>> a_tolist [1, 2] >>> type(a_tolist[0]) <class 'int'>
Additionally, for a 2D array,
tolist
applies recursively:>>> a = np.array([[1, 2], [3, 4]]) >>> list(a) [array([1, 2]), array([3, 4])] >>> a.tolist() [[1, 2], [3, 4]]
The base case for this recursion is a 0D array:
>>> a = np.array(1) >>> list(a) Traceback (most recent call last): ... TypeError: iteration over a 0-d array >>> a.tolist() 1
- tostring(order='C')
A compatibility alias for tobytes, with exactly the same behavior.
Despite its name, it returns bytes not strs.
Deprecated since version 1.19.0.
- trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)
Return the sum along diagonals of the array.
Refer to numpy.trace for full documentation.
See also
numpy.trace
equivalent function
- transpose(*axes)
Returns a view of the array with axes transposed.
For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is a standard matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and
a.shape = (i[0], i[1], ... i[n-2], i[n-1])
, thena.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])
.- Parameters
axes (None, tuple of ints, or n ints) –
None or no argument: reverses the order of the axes.
tuple of ints: i in the j-th place in the tuple means a’s i-th axis becomes a.transpose()’s j-th axis.
n ints: same as an n-tuple of the same ints (this form is intended simply as a “convenience” alternative to the tuple form)
- Returns
out – View of a, with axes suitably permuted.
- Return type
ndarray
See also
transpose
Equivalent function
ndarray.T
Array property returning the array transposed.
ndarray.reshape
Give a new shape to an array without changing its data.
Examples
>>> a = np.array([[1, 2], [3, 4]]) >>> a array([[1, 2], [3, 4]]) >>> a.transpose() array([[1, 3], [2, 4]]) >>> a.transpose((1, 0)) array([[1, 3], [2, 4]]) >>> a.transpose(1, 0) array([[1, 3], [2, 4]])
- var(axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, where=True)
Returns the variance of the array elements, along given axis.
Refer to numpy.var for full documentation.
See also
numpy.var
equivalent function
- view([dtype][, type])
New view of array with the same data.
Note
Passing None for
dtype
is different from omitting the parameter, since the former invokesdtype(None)
which is an alias fordtype('float_')
.- Parameters
dtype (data-type or ndarray sub-class, optional) – Data-type descriptor of the returned view, e.g., float32 or int16. Omitting it results in the view having the same data-type as a. This argument can also be specified as an ndarray sub-class, which then specifies the type of the returned object (this is equivalent to setting the
type
parameter).type (Python type, optional) – Type of the returned view, e.g., ndarray or matrix. Again, omission of the parameter results in type preservation.
Notes
a.view()
is used two different ways:a.view(some_dtype)
ora.view(dtype=some_dtype)
constructs a view of the array’s memory with a different data-type. This can cause a reinterpretation of the bytes of memory.a.view(ndarray_subclass)
ora.view(type=ndarray_subclass)
just returns an instance of ndarray_subclass that looks at the same array (same shape, dtype, etc.) This does not cause a reinterpretation of the memory.For
a.view(some_dtype)
, ifsome_dtype
has a different number of bytes per entry than the previous dtype (for example, converting a regular array to a structured array), then the behavior of the view cannot be predicted just from the superficial appearance ofa
(shown byprint(a)
). It also depends on exactly howa
is stored in memory. Therefore ifa
is C-ordered versus fortran-ordered, versus defined as a slice or transpose, etc., the view may give different results.Examples
>>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])
Viewing array data using a different type and dtype:
>>> y = x.view(dtype=np.int16, type=np.matrix) >>> y matrix([[513]], dtype=int16) >>> print(type(y)) <class 'numpy.matrix'>
Creating a view on a structured array so it can be used in calculations
>>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)]) >>> xv = x.view(dtype=np.int8).reshape(-1,2) >>> xv array([[1, 2], [3, 4]], dtype=int8) >>> xv.mean(0) array([2., 3.])
Making changes to the view changes the underlying array
>>> xv[0,1] = 20 >>> x array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])
Using a view to convert an array to a recarray:
>>> z = x.view(np.recarray) >>> z.a array([1, 3], dtype=int8)
Views share data:
>>> x[0] = (9, 10) >>> z[0] (9, 10)
Views that change the dtype size (bytes per entry) should normally be avoided on arrays defined by slices, transposes, fortran-ordering, etc.:
>>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16) >>> y = x[:, 0:2] >>> y array([[1, 2], [4, 5]], dtype=int16) >>> y.view(dtype=[('width', np.int16), ('length', np.int16)]) Traceback (most recent call last): ... ValueError: To change to a dtype of a different size, the array must be C-contiguous >>> z = y.copy() >>> z.view(dtype=[('width', np.int16), ('length', np.int16)]) array([[(1, 2)], [(4, 5)]], dtype=[('width', '<i2'), ('length', '<i2')])
- property x
Get or set the x coordinates for all atoms in instance as 2D array.
- property y
Get or set the y coordinates for all atoms in this instance as 2D array.
- property z
Get or set the z coordinates for all atoms in this instance as 2D array.
- as_pdb(filename, mol_subset=0)[source]
Convert a MultiMolecule object into one or more Protein DataBank files (.pdb).
Utilizes the
plams.Molecule.write
method.- Parameters
filename (path-like object) – The path+filename (including extension) of the to be created file.
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.
- as_mol2(filename, mol_subset=0)[source]
Convert a
FOX.MultiMolecule
object into one or more .mol2 files.Utilizes the
plams.Molecule.write
method.- Parameters
filename (path-like object) – The path+filename (including extension) of the to be created file.
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.
- as_mol(filename, mol_subset=0)[source]
Convert a MultiMolecule object into one or more .mol files.
Utilizes the
plams.Molecule.write
method.- Parameters
filename (path-like object) – The path+filename (including extension) of the to be created file.
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.
- as_xyz(filename, mol_subset=None)[source]
Create an .xyz file out of this instance.
Comments will be constructed by iteration through
MultiMolecule.properties["comments"]
if the following two conditions are fulfilled:The
"comments"
key is actually present inMultiMolecule.properties
.MultiMolecule.properties["comments"]
is an iterable.
- Parameters
filename (path-like object) – The path+filename (including extension) of the to be created file.
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.
- as_mass_weighted(mol_subset=None, atom_subset=None, inplace=False)[source]
Transform the Cartesian of this instance into mass-weighted Cartesian coordinates.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.inplace (
bool
) – Instead of returning the new coordinates, perform an inplace update of this instance.
- Returns
if inplace =
False
return a newMultiMolecule
instance with the mass-weighted Cartesian coordinates of \(m\) molecules with \(n\) atoms.- Return type
np.ndarray[np.float64]
, shape \((m, n, 3)\), optional
- from_mass_weighted(mol_subset=None, atom_subset=None)[source]
Transform this instance from mass-weighted Cartesian into Cartesian coordinates.
Performs an inplace update of this instance.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- as_Molecule(mol_subset=None, atom_subset=None)[source]
Convert this instance into a list of plams.Molecule.
- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A list of \(m\) PLAMS molecules constructed from this instance.
- Return type
- classmethod from_Molecule(mol_list, subset=frozenset({'atoms'}))[source]
Construct a
MultiMolecule
instance from one or more PLAMS molecules.- Parameters
mol_list (
plams.Molecule
orSequence[plams.Molecule]
) – A PLAMS molecule or list of PLAMS molecules.subset (
Container[str]
, optional) – Transfer a subset of plams.Molecule attributes to this instance. IfNone
, transfer all attributes. Accepts one or more of the following values as strings:"properties"
,"atoms"
,"lattice"
and/or"bonds"
.
- Returns
A molecule constructed from mol_list.
- Return type
- as_ase(mol_subset=None, atom_subset=None, **kwargs)[source]
Convert this instance into a list of ASE
Atoms
.- Parameters
mol_subset (
slice
, optional) – Perform the calculation on a subset of molecules in this instance, as determined by their moleculair index. Include all \(m\) molecules in this instance ifNone
.atom_subset (
Sequence[str]
, optional) – Perform the calculation on a subset of atoms in this instance, as determined by their atomic index or atomic symbol. Include all \(n\) atoms per molecule in this instance ifNone
.
- Returns
A list of ASE Atoms constructed from this instance.
- Return type
- classmethod from_ase(mol_list)[source]
Construct a
MultiMolecule
instance from one or more ASE Atoms.- Parameters
mol_list (
ase.Atoms
orSequence[ase.Atoms]
) – An ASE Atoms instance or a list thereof.- Returns
A molecule constructed from mol_list.
- Return type
- classmethod from_xyz(filename, bonds=None, properties=None, read_comment=False)[source]
Construct a
MultiMolecule
instance from a (multi) .xyz file.Comment lines extracted from the .xyz file are stored, as array, under
MultiMolecule.properties["comments"]
.- Parameters
filename (path-like object) – The path+filename of an .xyz file.
bonds (
np.ndarray[np.int64]
, shape \((k, 3)\)) – An optional 2D array with indices of the atoms defining all \(k\) bonds (columns 1 & 2) and their respective bond orders multiplied by 10 (column 3). Stored in the MultieMolecule.bonds attribute.properties (
dict
, optional) – A Settings object (subclass of dictionary) intended for storing miscellaneous user-defined (meta-)data. Is devoid of keys by default. Stored in the MultiMolecule.properties attribute.read_comments (
bool
) – IfTrue
, extract all comment lines from the passed .xyz file and store them underproperties.comments
.
- Returns
A molecule constructed from filename.
- Return type
- classmethod from_kf(filename, bonds=None, properties=None)[source]
Construct a
MultiMolecule
instance from a KF binary file.- Parameters
filename (path-like object) – The path+filename of an KF binary file.
bonds (
np.ndarray[np.int64]
, shape \((k, 3)\)) – An optional 2D array with indices of the atoms defining all \(k\) bonds (columns 1 & 2) and their respective bond orders multiplied by 10 (column 3). Stored in the MultieMolecule.bonds attribute.properties (
dict
) – A Settings object (subclass of dictionary) intended for storing miscellaneous user-defined (meta-)data. Is devoid of keys by default. Stored in the MultiMolecule.properties attribute.
- Returns
A molecule constructed from filename.
- Return type