Module with Node sub classes for array based data structures.
aiida.orm.nodes.data.array.
ArrayData
Bases: aiida.orm.nodes.data.data.Data
aiida.orm.nodes.data.data.Data
Store a set of arrays on disk (rather than on the database) in an efficient way using numpy.save() (therefore, this class requires numpy to be installed).
Each array is stored within the Node folder as a different .npy file.
Before storing, no caching is done: if you perform a get_array() call, the array will be re-read from disk. If instead the ArrayData node has already been stored, the array is cached in memory after the first read, and the cached array is used thereafter. If too much RAM memory is used, you can clear the cache with the clear_internal_cache() method.
get_array()
clear_internal_cache()
__abstractmethods__
__module__
_abc_impl
_arraynames_from_files
Return a list of all arrays stored in the node, listing the files (and not relying on the properties).
_arraynames_from_properties
Return a list of all arrays stored in the node, listing the attributes starting with the correct prefix.
_cached_arrays
_logger
_plugin_type_string
_query_type_string
_validate
Check if the list of .npy files stored inside the node and the list of properties match. Just a name check, no check on the size since this would require to reload all arrays and this may take time and memory.
array_prefix
clear_internal_cache
Clear the internal memory cache where the arrays are stored after being read from disk (used in order to reduce at minimum the readings from disk). This function is useful if you want to keep the node in memory, but you do not want to waste memory to cache the arrays in RAM.
delete_array
Delete an array from the node. Can only be called before storing.
name – The name of the array to delete from the node.
get_array
Return an array stored in the node
name – The name of the array to return.
get_arraynames
New in version 0.7: Renamed from arraynames
get_iterarrays
Iterator that returns tuples (name, array) for each array stored in the node.
New in version 1.0: Renamed from iterarrays
get_shape
Return the shape of an array (read from the value cached in the properties for efficiency reasons).
name – The name of the array.
initialize
Initialize internal variables for the backend node
This needs to be called explicitly in each specific subclass implementation of the init.
set_array
Store a new numpy array inside the node. Possibly overwrite the array if it already existed.
Internally, it stores a name.npy file in numpy format.
array – The numpy array to store.
BandsData
Bases: aiida.orm.nodes.data.array.kpoints.KpointsData
aiida.orm.nodes.data.array.kpoints.KpointsData
Class to handle bands data
_custom_export_format_replacements
_get_band_segments
_get_bandplot_data
Get data to plot a band structure
cartesian – if True, distances (for the x-axis) are computed in cartesian coordinates, otherwise they are computed in reciprocal coordinates. cartesian=True will fail if no cell has been set.
prettify_format – by default, strings are not prettified. If you want to prettify them, pass a valid prettify_format string (see valid options in the docstring of :py:func:prettify_labels).
join_symbols – by default, strings are not joined. If you pass a string, this is used to join strings that are much closer than a given threshold. The most typical string is the pipe symbol: |.
|
get_segments – if True, also computes the band split into segments
y_origin – if present, shift bands so to set the value specified at y=0
y=0
a plot_info dictiorary, whose keys are x (array of distances for the x axis of the plot); y (array of bands), labels (list of tuples in the format (float x value of the label, label string), band_type_idx (array containing an index for each band: if there is only one spin, then it’s an array of zeros, of length equal to the number of bands at each point; if there are two spins, then it’s an array of zeros or ones depending on the type of spin; the length is always equalt to the total number of bands per kpoint).
x
y
labels
band_type_idx
_get_mpl_body_template
paths – paths of k-points
_matplotlib_get_dict
Prepare the data to send to the python-matplotlib plotting script.
comments – if True, print comments (if it makes sense for the given format)
plot_info – a dictionary
setnumber_offset – an offset to be applied to all set numbers (i.e. s0 is replaced by s[offset], s1 by s[offset+1], etc.)
color_number – the color number for lines, symbols, error bars and filling (should be less than the parameter max_num_agr_colors defined below)
title – the title
legend – the legend (applied only to the first of the set)
legend2 – the legend for second-type spins (applied only to the first of the set)
y_max_lim – the maximum on the y axis (if None, put the maximum of the bands)
y_min_lim – the minimum on the y axis (if None, put the minimum of the bands)
y_origin – the new origin of the y axis -> all bands are replaced by bands-y_origin
prettify_format – if None, use the default prettify format. Otherwise specify a string with the prettifier to use.
kwargs – additional customization variables; only a subset is accepted, see internal variable ‘valid_additional_keywords
_prepare_agr
Prepare an xmgrace agr file.
color_number2 – the color number for lines, symbols, error bars and filling for the second-type spins (should be less than the parameter max_num_agr_colors defined below)
legend – the legend (applied only to the first set)
y_max_lim – the maximum on the y axis (if None, put the maximum of the bands); applied after shifting the origin by y_origin
y_origin
y_min_lim – the minimum on the y axis (if None, put the minimum of the bands); applied after shifting the origin by y_origin
_prepare_agr_batch
Prepare two files, data and batch, to be plot with xmgrace as: xmgrace -batch file.dat
main_file_name – if the user asks to write the main content on a file, this contains the filename. This should be used to infer a good filename for the additional files. In this case, we remove the extension, and add ‘_data.dat’
_prepare_dat_blocks
Format suitable for gnuplot using blocks. Columns with x and y (path and band energy). Several blocks, separated by two empty lines, one per energy band.
_prepare_dat_multicolumn
Write an N x M matrix. First column is the distance between kpoints, The other columns are the bands. Header contains number of kpoints and the number of bands (commented).
_prepare_gnuplot
Prepare an gnuplot script to plot the bands, with the .dat file returned as an independent file.
title – if specified, add a title to the plot
_prepare_json
Prepare a json file in a format compatible with the AiiDA band visualizer
_prepare_mpl_pdf
Prepare a python script using matplotlib to plot the bands, with the JSON returned as an independent file.
For the possible parameters, see documentation of _matplotlib_get_dict()
_matplotlib_get_dict()
_prepare_mpl_png
_prepare_mpl_singlefile
Prepare a python script using matplotlib to plot the bands
_prepare_mpl_withjson
_set_pbc
validate the pbc, then store them
_validate_bands_occupations
Validate the list of bands and of occupations before storage. Kpoints must be set in advance. Bands and occupations must be convertible into arrays of Nkpoints x Nbands floats or Nspins x Nkpoints x Nbands; Nkpoints must correspond to the number of kpoints.
array_labels
Get the labels associated with the band arrays
get_bands
Returns an array (nkpoints x num_bands or nspins x nkpoints x num_bands) of energies. :param also_occupations: if True, returns also the occupations array. Default = False
set_bands
Set an array of band energies of dimension (nkpoints x nbands). Kpoints must be set in advance. Can contain floats or None. :param bands: a list of nkpoints lists of nbands bands, or a 2D array of shape (nkpoints x nbands), with band energies for each kpoint :param units: optional, energy units :param occupations: optional, a 2D list or array of floats of same shape as bands, with the occupation associated to each band
set_kpointsdata
Load the kpoints from a kpoint object. :param kpointsdata: an instance of KpointsData class
show_mpl
Call a show() command for the band structure using matplotlib. This uses internally the ‘mpl_singlefile’ format, with empty main_file_name.
Other kwargs are passed to self._exportcontent.
units
Units in which the data in bands were stored. A string
KpointsData
Bases: aiida.orm.nodes.data.array.array.ArrayData
aiida.orm.nodes.data.array.array.ArrayData
Class to handle array of kpoints in the Brillouin zone. Provide methods to generate either user-defined k-points or path of k-points along symmetry lines. Internally, all k-points are defined in terms of crystal (fractional) coordinates. Cell and lattice vector coordinates are in Angstroms, reciprocal lattice vectors in Angstrom^-1 . :note: The methods setting and using the Bravais lattice info assume the PRIMITIVE unit cell is provided in input to the set_cell or set_cell_from_structure methods.
_change_reference
Change reference system, from cartesian to crystal coordinates (units of b1,b2,b3) or viceversa. :param kpoints: a list of (3) point coordinates :return kpoints: a list of (3) point coordinates in the new reference
_dimension
Dimensionality of the structure, found from its pbc (i.e. 1 if it’s a 1D structure, 2 if its 2D, 3 if it’s 3D …). :return dimensionality: 0, 1, 2 or 3 :note: will return 3 if pbc has not been set beforehand
_set_cell
Validate if ‘value’ is a allowed crystal unit cell :param value: something compatible with a 3x3 tuple of floats
_set_labels
set label names. Must pass in input a list like: [[0,'X'],[34,'L'],... ]
[[0,'X'],[34,'L'],... ]
_validate_kpoints_weights
Validate the list of kpoints and of weights before storage. Kpoints and weights must be convertible respectively to an array of N x dimension and N floats
cell
The crystal unit cell. Rows are the crystal vectors in Angstroms. :return: a 3x3 numpy.array
get_description
Returns a string with infos retrieved from kpoints node’s properties. :param node: :return: retstr
get_kpoints
Return the list of kpoints
also_weights – if True, returns also the list of weights. Default = False
cartesian – if True, returns points in cartesian coordinates, otherwise, returns in crystal coordinates. Default = False.
get_kpoints_mesh
Get the mesh of kpoints.
print_list – default=False. If True, prints the mesh of kpoints as a list
AttributeError – if no mesh has been set
(if print_list=False) a list of 3 integers and a list of three floats 0<x<1, representing the mesh and the offset of kpoints
(if print_list = True) an explicit list of kpoints coordinates, similar to what returned by get_kpoints()
Labels associated with the list of kpoints. List of tuples with kpoint index and kpoint name: [(0,'G'),(13,'M'),...]
[(0,'G'),(13,'M'),...]
pbc
The periodic boundary conditions along the vectors a1,a2,a3.
a tuple of three booleans, each one tells if there are periodic boundary conditions for the i-th real-space direction (i=1,2,3)
reciprocal_cell
Compute reciprocal cell from the internally set cell.
reciprocal cell in units of 1/Angstrom with cell vectors stored as rows. Use e.g. reciprocal_cell[0] to access the first reciprocal cell vector.
set_cell
Set a cell to be used for symmetry analysis. To set a cell from an AiiDA structure, use “set_cell_from_structure”.
cell – 3x3 matrix of cell vectors. Orientation: each row represent a lattice vector. Units are Angstroms.
pbc – list of 3 booleans, True if in the nth crystal direction the structure is periodic. Default = [True,True,True]
set_cell_from_structure
Set a cell to be used for symmetry analysis from an AiiDA structure. Inherits both the cell and the pbc’s. To set manually a cell, use “set_cell”
structuredata – an instance of StructureData
set_kpoints
Set the list of kpoints. If a mesh has already been stored, raise a ModificationNotAllowed
kpoints –
a list of kpoints, each kpoint being a list of one, two or three coordinates, depending on self.pbc: if structure is 1D (only one True in self.pbc) one allows singletons or scalars for each k-point, if it’s 2D it can be a length-2 list, and in all cases it can be a length-3 list. Examples:
[[0.,0.,0.],[0.1,0.1,0.1],…] for 1D, 2D or 3D [[0.,0.],[0.1,0.1,],…] for 1D or 2D [[0.],[0.1],…] for 1D [0., 0.1, …] for 1D (list of scalars)
[[0.,0.,0.],[0.1,0.1,0.1],…] for 1D, 2D or 3D
[[0.,0.],[0.1,0.1,],…] for 1D or 2D
[[0.],[0.1],…] for 1D
[0., 0.1, …] for 1D (list of scalars)
For 0D (all pbc are False), the list can be any of the above or empty - then only Gamma point is set. The value of k for the non-periodic dimension(s) is set by fill_values
cartesian – if True, the coordinates given in input are treated as in cartesian units. If False, the coordinates are crystal, i.e. in units of b1,b2,b3. Default = False
labels – optional, the list of labels to be set for some of the kpoints. See labels for more info
weights – optional, a list of floats with the weight associated to the kpoint list
fill_values – scalar to be set to all non-periodic dimensions (indicated by False in self.pbc), or list of values for each of the non-periodic dimensions.
set_kpoints_mesh
Set KpointsData to represent a uniformily spaced mesh of kpoints in the Brillouin zone. This excludes the possibility of set/get kpoints
mesh – a list of three integers, representing the size of the kpoint mesh along b1,b2,b3.
offset – (optional) a list of three floats between 0 and 1. [0.,0.,0.] is Gamma centered mesh [0.5,0.5,0.5] is half shifted [1.,1.,1.] by periodicity should be equivalent to [0.,0.,0.] Default = [0.,0.,0.].
set_kpoints_mesh_from_density
Set a kpoints mesh using a kpoints density, expressed as the maximum distance between adjacent points along a reciprocal axis
distance – distance (in 1/Angstrom) between adjacent kpoints, i.e. the number of kpoints along each reciprocal axis i is \(|b_i|/distance\) where \(|b_i|\) is the norm of the reciprocal cell vector.
offset – (optional) a list of three floats between 0 and 1. [0.,0.,0.] is Gamma centered mesh [0.5,0.5,0.5] is half shifted Default = [0.,0.,0.].
force_parity – (optional) if True, force each integer in the mesh to be even (except for the non-periodic directions).
a cell should be defined first.
the number of kpoints along non-periodic axes is always 1.
ProjectionData
Bases: aiida.orm.nodes.data.orbital.OrbitalData, aiida.orm.nodes.data.array.array.ArrayData
aiida.orm.nodes.data.orbital.OrbitalData
A class to handle arrays of projected wavefunction data. That is projections of a orbitals, usually an atomic-hydrogen orbital, onto a given bloch wavefunction, the bloch wavefunction being indexed by s, n, and k. E.g. the elements are the projections described as < orbital | Bloch wavefunction (s,n,k) >
_check_projections_bands
Checks to make sure that a reference bandsdata is already set, and that projection_array is of the same shape of the bands data
projwfc_arrays – nk x nb x nwfc array, to be checked against bands
AttributeError if energy is not already set
AttributeError if input_array is not of same shape as dos_energy
_find_orbitals_and_indices
Finds all the orbitals and their indicies associated with kwargs essential for retrieving the other indexed array parameters
kwargs – kwargs that can call orbitals as in get_orbitals()
retrieve_indexes, list of indicicies of orbitals corresponding to the kwargs
all_orbitals, list of orbitals to which the indexes correspond
_from_index_to_arrayname
Used internally to determine the array names.
get_pdos
Retrieves all the pdos arrays corresponding to the input kwargs
kwargs – inputs describing the orbitals associated with the pdos arrays
a list of tuples containing the orbital, energy array and pdos array associated with all orbitals that correspond to kwargs
get_projections
a list of tuples containing the orbital, and projection arrays associated with all orbitals that correspond to kwargs
get_reference_bandsdata
Returns the reference BandsData, using the set uuid via set_reference_bandsdata
a BandsData instance
AttributeError – if the bandsdata has not been set yet
exceptions.NotExistent – if the bandsdata uuid did not retrieve bandsdata
set_orbitals
This method is inherited from OrbitalData, but is blocked here. If used will raise a NotImplementedError
set_projectiondata
Stores the projwfc_array using the projwfc_label, after validating both.
list_of_orbitals – list of orbitals, of class orbital data. They should be the ones up on which the projection array corresponds with.
list_of_projections – list of arrays of projections of a atomic wavefunctions onto bloch wavefunctions. Since the projection is for every bloch wavefunction which can be specified by its spin (if used), band, and kpoint the dimensions must be nspin x nbands x nkpoints for the projwfc array. Or nbands x nkpoints if spin is not used.
energy_axis – list of energy axis for the list_of_pdos
list_of_pdos – a list of projected density of states for the atomic wavefunctions, units in states/eV
tags – A list of tags, not supported currently.
bands_check – if false, skips checks of whether the bands has been already set, and whether the sizes match. For use in parsers, where the BandsData has not yet been stored and therefore get_reference_bandsdata cannot be called
set_reference_bandsdata
Sets a reference bandsdata, creates a uuid link between this data object and a bandsdata object, must be set before any projection arrays
value – a BandsData instance, a uuid or a pk
exceptions.NotExistent if there was no BandsData associated with uuid or pk
TrajectoryData
Stores a trajectory (a sequence of crystal structures with timestamps, and possibly with velocities).
__init__
backend_entity (aiida.orm.implementation.BackendEntity) – the backend model supporting this entity
aiida.orm.implementation.BackendEntity
_internal_validate
Internal function to validate the type and shape of the arrays. See the documentation of py:meth:.set_trajectory for a description of the valid shape and type of the parameters.
_parse_xyz_pos
Load positions from a XYZ file.
Note
The steps and symbols must be set manually before calling this import function as a consistency measure. Even though the symbols and steps could be extracted from the XYZ file, the data present in the XYZ file may or may not be correct and the same logic would have to be present in the XYZ-velocities function. It was therefore decided not to implement it at all but require it to be set explicitly.
Usage:
from aiida.orm.nodes.data.array.trajectory import TrajectoryData t = TrajectoryData() # get sites and number of timesteps t.set_array('steps', arange(ntimesteps)) t.set_array('symbols', array([site.kind for site in s.sites])) t.importfile('some-calc/AIIDA-PROJECT-pos-1.xyz', 'xyz_pos')
_parse_xyz_vel
Load velocities from a XYZ file.
The steps and symbols must be set manually before calling this import function as a consistency measure. See also comment for _parse_xyz_pos()
_parse_xyz_pos()
_prepare_cif
Write the given trajectory to a string of format CIF.
_prepare_xsf
Write the given trajectory to a string of format XSF (for XCrySDen).
Verify that the required arrays are present and that their type and dimension are correct.
get_cells
Return the array of cells, if it has already been set.
KeyError – if the trajectory has not been set yet.
get_cif
Creates aiida.orm.nodes.data.cif.CifData
aiida.orm.nodes.data.cif.CifData
New in version 1.0: Renamed from _get_cif
get_index_from_stepid
Given a value for the stepid (i.e., a value among those of the steps array), return the array index of that stepid, that can be used in other methods such as get_step_data() or get_step_structure().
steps
get_step_data()
get_step_structure()
New in version 0.7: Renamed from get_step_index
Note that this function returns the first index found (i.e. if multiple steps are present with the same value, only the index of the first one is returned).
ValueError – if no step with the given value is found.
get_positions
Return the array of positions, if it has already been set.
get_step_data
Return a tuple with all information concerning the stepid with given index (0 is the first step, 1 the second step and so on). If you know only the step value, use the get_index_from_stepid() method to get the corresponding index.
get_index_from_stepid()
If no velocities were specified, None is returned as the last element.
A tuple in the format (stepid, time, cell, symbols, positions, velocities), where stepid is an integer, time is a float, cell is a \(3 \times 3\) matrix, symbols is an array of length n, positions is a \(n \times 3\) array, and velocities is either None or a \(n \times 3\) array
(stepid, time, cell, symbols, positions, velocities)
stepid
time
symbols
n
None
index – The index of the step that you want to retrieve, from 0 to self.numsteps - 1.
self.numsteps - 1
IndexError – if you require an index beyond the limits.
KeyError – if you did not store the trajectory yet.
get_step_structure
Return an AiiDA aiida.orm.nodes.data.structure.StructureData node (not stored yet!) with the coordinates of the given step, identified by its index. If you know only the step value, use the get_index_from_stepid() method to get the corresponding index.
aiida.orm.nodes.data.structure.StructureData
The periodic boundary conditions are always set to True.
New in version 0.7: Renamed from step_to_structure
index – The index of the step that you want to retrieve, from 0 to self.numsteps- 1.
self.numsteps- 1
custom_kinds – (Optional) If passed must be a list of aiida.orm.nodes.data.structure.Kind objects. There must be one kind object for each different string in the symbols array, with kind.name set to this string. If this parameter is omitted, the automatic kind generation of AiiDA aiida.orm.nodes.data.structure.StructureData nodes is used, meaning that the strings in the symbols array must be valid chemical symbols.
aiida.orm.nodes.data.structure.Kind
kind.name
get_stepids
Return the array of steps, if it has already been set.
New in version 0.7: Renamed from get_steps
get_structure
Creates aiida.orm.nodes.data.structure.StructureData.
New in version 1.0: Renamed from _get_aiida_structure
converter – specify the converter. Default ‘ase’.
store – If True, intermediate calculation gets stored in the AiiDA database for record. Default False.
aiida.orm.nodes.data.structure.StructureData node.
get_times
Return the array of times (in ps), if it has already been set.
get_velocities
Return the array of velocities, if it has already been set.
This function (differently from all other get_* functions, will not raise an exception if the velocities are not set, but rather return None (both if no trajectory was not set yet, and if it the trajectory was set but no velocities were specified).
get_*
numsites
Return the number of stored sites, or zero if nothing has been stored yet.
numsteps
Return the number of stored steps, or zero if nothing has been stored yet.
set_structurelist
Create trajectory from the list of aiida.orm.nodes.data.structure.StructureData instances.
structurelist – a list of aiida.orm.nodes.data.structure.StructureData instances.
ValueError – if symbol lists of supplied structures are different
set_trajectory
Store the whole trajectory, after checking that types and dimensions are correct.
Parameters stepids, cells and velocities are optional variables. If nothing is passed for cells or velocities nothing will be stored. However, if no input is given for stepids a consecutive sequence [0,1,2,…,len(positions)-1] will be assumed.
stepids
cells
velocities
symbols – string list with dimension n, where n is the number of atoms (i.e., sites) in the structure. The same list is used for each step. Normally, the string should be a valid chemical symbol, but actually any unique string works and can be used as the name of the atomic kind (see also the get_step_structure() method).
positions – float array with dimension \(s \times n \times 3\), where s is the length of the stepids array and n is the length of the symbols array. Units are angstrom. In particular, positions[i,j,k] is the k-th component of the j-th atom (or site) in the structure at the time step with index i (identified by step number step[i] and with timestamp times[i]).
s
positions[i,j,k]
k
j
i
step[i]
times[i]
stepids – integer array with dimension s, where s is the number of steps. Typically represents an internal counter within the code. For instance, if you want to store a trajectory with one step every 10, starting from step 65, the array will be [65,75,85,...]. No checks are done on duplicate elements or on the ordering, but anyway this array should be sorted in ascending order, without duplicate elements. (If not specified, stepids will be set to numpy.arange(s) by default) It is internally stored as an array named ‘steps’.
[65,75,85,...]
numpy.arange(s)
cells – if specified float array with dimension \(s \times 3 \times 3\), where s is the length of the stepids array. Units are angstrom. In particular, cells[i,j,k] is the k-th component of the j-th cell vector at the time step with index i (identified by step number stepid[i] and with timestamp times[i]).
cells[i,j,k]
stepid[i]
times – if specified, float array with dimension s, where s is the length of the stepids array. Contains the timestamp of each step in picoseconds (ps).
velocities – if specified, must be a float array with the same dimensions of the positions array. The array contains the velocities in the atoms.
positions
show_mpl_heatmap
Show a heatmap of the trajectory with matplotlib.
show_mpl_pos
Shows the positions as a function of time, separate for XYZ coordinates
stepsize (int) – The stepsize for the trajectory, set higher than 1 to reduce number of points
mintime (int) – Time to start from
maxtime (int) – Maximum time
elements (list) – A list of atomic symbols that should be displayed. If not specified, all atoms are displayed.
indices (list) – A list of indices of that atoms that can be displayed. If not specified, all atoms of the correct species are displayed.
dont_block (bool) – If True, interpreter is not blocked when figure is displayed.
Return the array of symbols, if it has already been set.
XyData
A subclass designed to handle arrays that have an “XY” relationship to each other. That is there is one array, the X array, and there are several Y arrays, which can be considered functions of X.
_arrayandname_validator
Validates that the array is an numpy.ndarray and that the name is of type str. Raises InputValidationError if this not the case.
get_x
Tries to retrieve the x array and x name raises a NotExistent exception if no x array has been set yet. :return x_name: the name set for the x_array :return x_array: the x array set earlier :return x_units: the x units set earlier
get_y
Tries to retrieve the y arrays and the y names, raises a NotExistent exception if they have not been set yet, or cannot be retrieved :return y_names: list of strings naming the y_arrays :return y_arrays: list of y_arrays :return y_units: list of strings giving the units for the y_arrays
set_x
Sets the array and the name for the x values.
x_array – A numpy.ndarray, containing only floats
x_name – a string for the x array name
x_units – the units of x
set_y
Set array(s) for the y part of the dataset. Also checks if the x_array has already been set, and that, the shape of the y_arrays agree with the x_array. :param y_arrays: A list of y_arrays, numpy.ndarray :param y_names: A list of strings giving the names of the y_arrays :param y_units: A list of strings giving the units of the y_arrays
AiiDA ORM data class storing (numpy) arrays
aiida.orm.nodes.data.array.array.
This module defines the classes related to band structures or dispersions in a Brillouin zone, and how to operate on them.
aiida.orm.nodes.data.array.bands.
find_bandgap
Tries to guess whether the bandsdata represent an insulator. This method is meant to be used only for electronic bands (not phonons) By default, it will try to use the occupations to guess the number of electrons and find the Fermi Energy, otherwise, it can be provided explicitely. Also, there is an implicit assumption that the kpoints grid is “sufficiently” dense, so that the bandsdata are not missing the intersection between valence and conduction band if present. Use this function with care!
number_electrons – (optional, float) number of electrons in the unit cell
fermi_energy – (optional, float) value of the fermi energy.
By default, the algorithm uses the occupations array to guess the number of electrons and the occupied bands. This is to be used with care, because the occupations could be smeared so at a non-zero temperature, with the unwanted effect that the conduction bands might be occupied in an insulator. Prefer to pass the number_of_electrons explicitly
Only one between number_electrons and fermi_energy can be specified at the same time.
(is_insulator, gap), where is_insulator is a boolean, and gap a float. The gap is None in case of a metal, zero when the homo is equal to the lumo (e.g. in semi-metals).
prepare_header_comment
Module of the KpointsData class, defining the AiiDA data type for storing lists and meshes of k-points (i.e., points in the reciprocal space of a periodic crystal structure).
aiida.orm.nodes.data.array.kpoints.
aiida.orm.nodes.data.array.projection.
AiiDA class to deal with crystal structure trajectories.
aiida.orm.nodes.data.array.trajectory.
plot_positions_XYZ
Plot with matplotlib the positions of the coordinates of the atoms over time for a trajectory
times – array of times
positions – array of positions
indices_to_show – list of indices of to show (0, 1, 2 for X, Y, Z)
color_list – list of valid color specifications for matplotlib
label – label for this plot to put in the title
positions_unit – label for the units of positions (for the x label)
times_unit – label for the units of times (for the y label)
dont_block – passed to plt.show() as block=not dont_block
block=not dont_block
mintime – if specified, cut the time axis at the specified min value
maxtime – if specified, cut the time axis at the specified max value
label_sparsity – how often to put a label with the pair (t, coord)
This module defines the classes related to Xy data. That is data that contains collections of y-arrays bound to a single x-array, and the methods to operate on them.
aiida.orm.nodes.data.array.xy.
check_convert_single_to_tuple
Checks if the item is a list or tuple, and converts it to a list if it is not already a list or tuple
item – an object which may or may not be a list or tuple
item_list: the input item unchanged if list or tuple and [item] otherwise