aiida.restapi.translator.nodes.data package

Translator for data node

class aiida.restapi.translator.nodes.data.DataTranslator(Class=None, **kwargs)[source]

Bases: aiida.restapi.translator.nodes.node.NodeTranslator

Translator relative to resource ‘data’ and aiida class ~aiida.orm.nodes.data.data.Data

class Data(backend=None, user=None, computer=None, **kwargs)

Bases: aiida.orm.nodes.node.Node

This class is base class for all data objects.

Specifications of the Data class: AiiDA Data objects are subclasses of Node and should have

Multiple inheritance must be supported, i.e. Data should have methods for querying and be able to inherit other library objects such as ASE for structures.

Architecture note: The code plugin is responsible for converting a raw data object produced by code to AiiDA standard object format. The data object then validates itself according to its method. This is done independently in order to allow cross-validation of plugins.

__abstractmethods__ = frozenset()
__copy__()

Copying a Data node is not supported, use copy.deepcopy or call Data.clone().

__deepcopy__(memo)

Create a clone of the Data node by pipiong through to the clone method and return the result.

Returns:an unstored clone of this Data node
__module__ = 'aiida.orm.nodes.data.data'
_abc_impl = <_abc_data object>
_export_format_replacements = {}
_exportcontent(fileformat, main_file_name='', **kwargs)

Converts a Data node to one (or multiple) files.

Note: Export plugins should return utf8-encoded bytes, which can be directly dumped to file.

Parameters:
  • fileformat (str) – the extension, uniquely specifying the file format.
  • main_file_name (str) – (empty by default) Can be used by plugin to infer sensible names for additional files, if necessary. E.g. if the main file is ‘../myplot.gnu’, the plugin may decide to store the dat file under ‘../myplot_data.dat’.
  • kwargs – other parameters are passed down to the plugin
Returns:

a tuple of length 2. The first element is the content of the otuput file. The second is a dictionary (possibly empty) in the format {filename: filecontent} for any additional file that should be produced.

Return type:

(bytes, dict)

_get_converters()

Get all implemented converter formats. The convention is to find all _get_object_… methods. Returns a list of strings.

_get_exporters()

Get all implemented export formats. The convention is to find all _prepare_… methods. Returns a dictionary of method_name: method_function

_get_importers()

Get all implemented import formats. The convention is to find all _parse_… methods. Returns a list of strings.

_logger = <Logger aiida.orm.nodes.data.data.Data (REPORT)>
_plugin_type_string = 'data.data.Data.'
_query_type_string = 'data.data.'
_source_attributes = ['db_name', 'db_uri', 'uri', 'id', 'version', 'extras', 'source_md5', 'description', 'license']
_storable = True
_unstorable_message = 'storing for this node has been disabled'
_validate()

Perform validation of the Data object.

Note

validation of data source checks license and requires attribution to be provided in field ‘description’ of source in the case of any CC-BY* license. If such requirement is too strict, one can remove/comment it out.

clone()

Create a clone of the Data node.

Returns:an unstored clone of this Data node
convert(object_format=None, *args)

Convert the AiiDA StructureData into another python object

Parameters:object_format – Specify the output format
creator

Return the creator of this node or None if it does not exist.

Returns:the creating node or None
export(path, fileformat=None, overwrite=False, **kwargs)

Save a Data object to a file.

Parameters:
  • fname – string with file name. Can be an absolute or relative path.
  • fileformat – kind of format to use for the export. If not present, it will try to use the extension of the file name.
  • overwrite – if set to True, overwrites file found at path. Default=False
  • kwargs – additional parameters to be passed to the _exportcontent method
Returns:

the list of files created

classmethod get_export_formats()

Get the list of valid export format strings

Returns:a list of valid formats
importfile(fname, fileformat=None)

Populate a Data object from a file.

Parameters:
  • fname – string with file name. Can be an absolute or relative path.
  • fileformat – kind of format to use for the export. If not present, it will try to use the extension of the file name.
importstring(inputstring, fileformat, **kwargs)

Converts a Data object to other text format.

Parameters:fileformat – a string (the extension) to describe the file format.
Returns:a string with the structure description.
set_source(source)

Sets the dictionary describing the source of Data object.

source

Gets the dictionary describing the source of Data object. Possible fields:

  • db_name: name of the source database.
  • db_uri: URI of the source database.
  • uri: URI of the object’s source. Should be a permanent link.
  • id: object’s source identifier in the source database.
  • version: version of the object’s source.
  • extras: a dictionary with other fields for source description.
  • source_md5: MD5 checksum of object’s source.
  • description: human-readable free form description of the object’s source.
  • license: a string with a type of license.

Note

some limitations for setting the data source exist, see _validate method.

Returns:dictionary describing the source of Data object.
__init__(Class=None, **kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'data'
__module__ = 'aiida.restapi.translator.nodes.data'
_aiida_class

alias of aiida.orm.nodes.data.data.Data

_aiida_type = 'data.Data'
_result_type = 'data'

Submodules

Translator for bands data

class aiida.restapi.translator.nodes.data.bands.BandsDataTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘bands’ and aiida class BandsData

class BandsData(backend=None, user=None, computer=None, **kwargs)

Bases: aiida.orm.nodes.data.array.kpoints.KpointsData

Class to handle bands data

__abstractmethods__ = frozenset()
__module__ = 'aiida.orm.nodes.data.array.bands'
_abc_impl = <_abc_data object>
_custom_export_format_replacements = {'dat': 'dat_multicolumn', 'gnu': 'gnuplot', 'pdf': 'mpl_pdf', 'png': 'mpl_png', 'py': 'mpl_singlefile'}
_get_band_segments(cartesian)
_get_bandplot_data(cartesian, prettify_format=None, join_symbol=None, get_segments=False, y_origin=0.0)

Get data to plot a band structure

Parameters:
  • 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
Returns:

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).

_logger = <Logger aiida.orm.nodes.data.array.bands.BandsData (REPORT)>
_matplotlib_get_dict(main_file_name='', comments=True, title='', legend=None, legend2=None, y_max_lim=None, y_min_lim=None, y_origin=0.0, prettify_format=None, **kwargs)

Prepare the data to send to the python-matplotlib plotting script.

Parameters:
  • 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
_plugin_type_string = 'data.array.bands.BandsData.'
_prepare_agr(main_file_name='', comments=True, setnumber_offset=0, color_number=1, color_number2=2, legend='', title='', y_max_lim=None, y_min_lim=None, y_origin=0.0, prettify_format=None)

Prepare an xmgrace agr file.

Parameters:
  • 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)
  • 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)
  • title – the title
  • 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_min_lim – the minimum on the y axis (if None, put the minimum of the bands); applied after shifting the origin by y_origin
  • 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.
_prepare_agr_batch(main_file_name='', comments=True, prettify_format=None)

Prepare two files, data and batch, to be plot with xmgrace as: xmgrace -batch file.dat

Parameters:
  • 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’
  • comments – if True, print comments (if it makes sense for the given format)
  • prettify_format – if None, use the default prettify format. Otherwise specify a string with the prettifier to use.
_prepare_dat_blocks(main_file_name='', comments=True)

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.

Parameters:comments – if True, print comments (if it makes sense for the given format)
_prepare_dat_multicolumn(main_file_name='', comments=True)

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).

Parameters:comments – if True, print comments (if it makes sense for the given format)
_prepare_gnuplot(main_file_name='', title='', comments=True, prettify_format=None, y_max_lim=None, y_min_lim=None, y_origin=0.0)

Prepare an gnuplot script to plot the bands, with the .dat file returned as an independent file.

Parameters:
  • 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’
  • title – if specified, add a title to the plot
  • comments – if True, print comments (if it makes sense for the given format)
  • prettify_format – if None, use the default prettify format. Otherwise specify a string with the prettifier to use.
_prepare_json(main_file_name='', comments=True)

Prepare a json file in a format compatible with the AiiDA band visualizer

Parameters:comments – if True, print comments (if it makes sense for the given format)
_prepare_mpl_pdf(main_file_name='', *args, **kwargs)

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()

_prepare_mpl_png(main_file_name='', *args, **kwargs)

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()

_prepare_mpl_singlefile(*args, **kwargs)

Prepare a python script using matplotlib to plot the bands

For the possible parameters, see documentation of _matplotlib_get_dict()

_prepare_mpl_withjson(main_file_name='', *args, **kwargs)

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()

_query_type_string = 'data.array.bands.'
_set_pbc(value)

validate the pbc, then store them

_validate_bands_occupations(bands, occupations=None, labels=None)

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(also_occupations=False, also_labels=False)

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(bands, units=None, occupations=None, labels=None)

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(kpointsdata)

Load the kpoints from a kpoint object. :param kpointsdata: an instance of KpointsData class

show_mpl(**kwargs)

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

__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'bands'
__module__ = 'aiida.restapi.translator.nodes.data.bands'
_aiida_class

alias of aiida.orm.nodes.data.array.bands.BandsData

_aiida_type = 'data.array.bands.BandsData'
_result_type = 'bands'
static get_downloadable_data(node, download_format=None)[source]

Generic function extented for kpoints data. Currently it is not implemented.

Parameters:
  • node – node object that has to be visualized
  • download_format – file extension format
Returns:

raise RestFeatureNotAvailable exception

static get_visualization_data(node, visformat=None)[source]

Returns: data in a format required by dr.js to visualize a 2D plot with multiple data series.

Strategy: I take advantage of the export functionality of BandsData objects. The raw export has to be filtered for string escape characters. this is done by decoding the string returned by node._exportcontent.

TODO: modify the function exportstring (or add another function in BandsData) so that it returns a python object rather than a string.

Translator for CifData

class aiida.restapi.translator.nodes.data.cif.CifDataTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘structures’ and aiida class CifData

class CifData(ase=None, file=None, values=None, source=None, scan_type='standard', parse_policy='eager', **kwargs)

Bases: aiida.orm.nodes.data.singlefile.SinglefileData

Wrapper for Crystallographic Interchange File (CIF)

Note

the file (physical) is held as the authoritative source of information, so all conversions are done through the physical file: when setting ase or values, a physical CIF file is generated first, the values are updated from the physical CIF file.

__abstractmethods__ = frozenset()
__init__(ase=None, file=None, values=None, source=None, scan_type='standard', parse_policy='eager', **kwargs)

Construct a new instance and set the contents to that of the file.

Parameters:file – an absolute filepath or filelike object whose contents to copy
__module__ = 'aiida.orm.nodes.data.cif'
_abc_impl = <_abc_data object>
_ase = None
_get_object_ase()

Converts CifData to ase.Atoms

Returns:an ase.Atoms object
_get_object_pycifrw()

Converts CifData to PyCIFRW.CifFile

Returns:a PyCIFRW.CifFile object
_logger = <Logger aiida.orm.nodes.data.cif.CifData (REPORT)>
_parse_policies = ('eager', 'lazy')
_plugin_type_string = 'data.cif.CifData.'
_prepare_cif(main_file_name='')

Return CIF string of CifData object.

If parsed values are present, a CIF string is created and written to file. If no parsed values are present, the CIF string is read from file.

_query_type_string = 'data.cif.'
_scan_types = ('standard', 'flex')
_set_incompatibilities = [('ase', 'file'), ('ase', 'values'), ('file', 'values')]
_validate()

Validates MD5 hash of CIF file.

_values = None
ase

ASE object, representing the CIF.

Note

requires ASE module.

classmethod from_md5(md5)

Return a list of all CIF files that match a given MD5 hash.

Note

the hash has to be stored in a _md5 attribute, otherwise the CIF file will not be found.

generate_md5()

Computes and returns MD5 hash of the CIF file.

get_ase(**kwargs)

Returns ASE object, representing the CIF. This function differs from the property ase by the possibility to pass the keyworded arguments (kwargs) to ase.io.cif.read_cif().

Note

requires ASE module.

get_formulae(mode='sum')

Return chemical formulae specified in CIF file.

Note: This does not compute the formula, it only reads it from the appropriate tag. Use refine_inline to compute formulae.

classmethod get_or_create(filename, use_first=False, store_cif=True)

Pass the same parameter of the init; if a file with the same md5 is found, that CifData is returned.

Parameters:
  • filename – an absolute filename on disk
  • use_first – if False (default), raise an exception if more than one CIF file is found. If it is True, instead, use the first available CIF file.
  • store_cif (bool) – If false, the CifData objects are not stored in the database. default=True.
Return (cif, created):
 

where cif is the CifData object, and create is either True if the object was created, or False if the object was retrieved from the DB.

get_spacegroup_numbers()

Get the spacegroup international number.

get_structure(converter='pymatgen', store=False, **kwargs)

Creates aiida.orm.nodes.data.structure.StructureData.

New in version 1.0: Renamed from _get_aiida_structure

Parameters:
  • converter – specify the converter. Default ‘pymatgen’.
  • store – if True, intermediate calculation gets stored in the AiiDA database for record. Default False.
  • primitive_cell – if True, primitive cell is returned, conventional cell if False. Default False.
  • occupancy_tolerance – If total occupancy of a site is between 1 and occupancy_tolerance, the occupancies will be scaled down to 1. (pymatgen only)
  • site_tolerance – This tolerance is used to determine if two sites are sitting in the same position, in which case they will be combined to a single disordered site. Defaults to 1e-4. (pymatgen only)
Returns:

aiida.orm.nodes.data.structure.StructureData node.

has_atomic_sites

Returns whether there are any atomic sites defined in the cif data. That is to say, it will check all the values for the _atom_site_fract_* tags and if they are all equal to ? that means there are no relevant atomic sites defined and the function will return False. In all other cases the function will return True

Returns:False when at least one atomic site fractional coordinate is not equal to ? and True otherwise
has_attached_hydrogens

Check if there are hydrogens without coordinates, specified as attached to the atoms of the structure.

Returns:True if there are attached hydrogens, False otherwise.
has_partial_occupancies

Return if the cif data contains partial occupancies

A partial occupancy is defined as site with an occupancy that differs from unity, within a precision of 1E-6

Returns:True if there are partial occupancies, False otherwise
has_undefined_atomic_sites

Return whether the cif data contains any undefined atomic sites.

An undefined atomic site is defined as a site where at least one of the fractional coordinates specified in the _atom_site_fract_* tags, cannot be successfully interpreted as a float. If the cif data contains any site that matches this description, or it does not contain any atomic site tags at all, the cif data is said to have undefined atomic sites.

Returns:boolean, True if no atomic sites are defined or if any of the defined sites contain undefined positions and False otherwise
has_unknown_species

Returns whether the cif contains atomic species that are not recognized by AiiDA.

The known species are taken from the elements dictionary in aiida.common.constants, with the exception of the “unknown” placeholder element with symbol ‘X’, as this could not be used to construct a real structure. If any of the formula of the cif data contain species that are not in that elements dictionary, the function will return True and False in all other cases. If there is no formulae to be found, it will return None

Returns:True when there are unknown species in any of the formulae, False if not, None if no formula found
parse(scan_type=None)

Parses CIF file and sets attributes.

Parameters:scan_type – See set_scan_type
static read_cif(fileobj, index=-1, **kwargs)

A wrapper method that simulates the behavior of the old function ase.io.cif.read_cif by using the new generic ase.io.read function.

Somewhere from 3.12 to 3.17 the tag concept was bundled with each Atom object. When reading a CIF file, this is incremented and signifies the atomic species, even though the CIF file do not have specific tags embedded. On reading CIF files we thus force the ASE tag to zero for all Atom elements.

set_ase(aseatoms)

Set the contents of the CifData starting from an ASE atoms object

Parameters:aseatoms – the ASE atoms object
set_file(file)

Set the file.

If the source is set and the MD5 checksum of new file is different from the source, the source has to be deleted.

set_parse_policy(parse_policy)

Set the parse policy.

Parameters:parse_policy – Either ‘eager’ (parse CIF file on set_file) or ‘lazy’ (defer parsing until needed)
set_scan_type(scan_type)

Set the scan_type for PyCifRW.

The ‘flex’ scan_type of PyCifRW is faster for large CIF files but does not yet support the CIF2 format as of 02/2018. See the CifFile.ReadCif function

Parameters:scan_type – Either ‘standard’ or ‘flex’ (see _scan_types)
set_values(values)

Set internal representation to values.

Warning: This also writes a new CIF file.

Parameters:values – PyCifRW CifFile object

Note

requires PyCifRW module.

store(*args, **kwargs)

Store the node.

values

PyCifRW structure, representing the CIF datablocks.

Note

requires PyCifRW module.

__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'cifs'
__module__ = 'aiida.restapi.translator.nodes.data.cif'
_aiida_class

alias of aiida.orm.nodes.data.cif.CifData

_aiida_type = 'data.cif.CifData'
_result_type = 'cifs'
static get_downloadable_data(node, download_format=None)[source]

Return cif string for download

Parameters:node – node representing cif file to be downloaded
Returns:cif file
static get_visualization_data(node, visformat=None)[source]

Returns: data in specified format. If format is not specified returns data in a format required by chemdoodle to visualize a structure.

Translator for code

class aiida.restapi.translator.nodes.data.code.CodeTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘codes’ and aiida class Code

class Code(remote_computer_exec=None, local_executable=None, input_plugin_name=None, files=None, **kwargs)

Bases: aiida.orm.nodes.data.data.Data

A code entity. It can either be ‘local’, or ‘remote’.

  • Local code: it is a collection of files/dirs (added using the add_path() method), where one file is flagged as executable (using the set_local_executable() method).
  • Remote code: it is a pair (remotecomputer, remotepath_of_executable) set using the set_remote_computer_exec() method.

For both codes, one can set some code to be executed right before or right after the execution of the code, using the set_preexec_code() and set_postexec_code() methods (e.g., the set_preexec_code() can be used to load specific modules required for the code to be run).

HIDDEN_KEY = 'hidden'
__abstractmethods__ = frozenset()
__init__(remote_computer_exec=None, local_executable=None, input_plugin_name=None, files=None, **kwargs)
Parameters:backend_entity (aiida.orm.implementation.BackendEntity) – the backend model supporting this entity
__module__ = 'aiida.orm.nodes.data.code'
__str__()

Return str(self).

_abc_impl = <_abc_data object>
_logger = <Logger aiida.orm.nodes.data.code.Code (REPORT)>
_plugin_type_string = 'data.code.Code.'
_query_type_string = 'data.code.'
_set_local()

Set the code as a ‘local’ code, meaning that all the files belonging to the code will be copied to the cluster, and the file set with set_exec_filename will be run.

It also deletes the flags related to the local case (if any)

_set_remote()

Set the code as a ‘remote’ code, meaning that the code itself has no files attached, but only a location on a remote computer (with an absolute path of the executable on the remote computer).

It also deletes the flags related to the local case (if any)

_validate()

Perform validation of the Data object.

Note

validation of data source checks license and requires attribution to be provided in field ‘description’ of source in the case of any CC-BY* license. If such requirement is too strict, one can remove/comment it out.

can_run_on(computer)

Return True if this code can run on the given computer, False otherwise.

Local codes can run on any machine; remote codes can run only on the machine on which they reside.

TODO: add filters to mask the remote machines on which a local code can run.

full_label

Get full label of this code.

Returns label of the form <code-label>@<computer-name>.

classmethod get(pk=None, label=None, machinename=None)

Get a Computer object with given identifier string, that can either be the numeric ID (pk), or the label (and computername) (if unique).

Parameters:
  • pk – the numeric ID (pk) for code
  • label – the code label identifying the code to load
  • machinename – the machine name where code is setup
Raises:
get_append_text()

Return the postexec_code, or an empty string if no post-exec code was defined.

get_builder()

Create and return a new ProcessBuilder for the default Calculation plugin, as obtained by the self.get_input_plugin_name() method.

Note:

it also sets the builder.code value.

Raises:
Returns:

classmethod get_code_helper(label, machinename=None)
Parameters:
  • label – the code label identifying the code to load
  • machinename – the machine name where code is setup
Raises:
get_computer_name()

Get name of this code’s computer.

get_description()

Return a string description of this Code instance.

Returns:string description of this Code instance
get_execname()

Return the executable string to be put in the script. For local codes, it is ./LOCAL_EXECUTABLE_NAME For remote codes, it is the absolute path to the executable.

classmethod get_from_string(code_string)

Get a Computer object with given identifier string in the format label@machinename. See the note below for details on the string detection algorithm.

Note

the (leftmost) ‘@’ symbol is always used to split code and computername. Therefore do not use ‘@’ in the code name if you want to use this function (‘@’ in the computer name are instead valid).

Parameters:

code_string – the code string identifying the code to load

Raises:
get_full_text_info(verbose=False)

Return a (multiline) string with a human-readable detailed information on this computer

get_input_plugin_name()

Return the name of the default input plugin (or None if no input plugin was set.

get_local_executable()
get_prepend_text()

Return the code that will be put in the scheduler script before the execution, or an empty string if no pre-exec code was defined.

get_remote_computer()
get_remote_exec_path()
hidden

Determines whether the Code is hidden or not

hide()

Hide the code (prevents from showing it in the verdi code list)

is_local()

Return True if the code is ‘local’, False if it is ‘remote’ (see also documentation of the set_local and set_remote functions).

classmethod list_for_plugin(plugin, labels=True)

Return a list of valid code strings for a given plugin.

Parameters:
  • plugin – The string of the plugin.
  • labels – if True, return a list of code names, otherwise return the code PKs (integers).
Returns:

a list of string, with the code names if labels is True, otherwise a list of integers with the code PKs.

relabel(new_label, raise_error=True)

Relabel this code.

Parameters:
  • new_label – new code label
  • raise_error – Set to False in order to return a list of errors instead of raising them.
reveal()

Reveal the code (allows to show it in the verdi code list) By default, it is revealed

set_append_text(code)

Pass a string of code that will be put in the scheduler script after the execution of the code.

set_files(files)

Given a list of filenames (or a single filename string), add it to the path (all at level zero, i.e. without folders). Therefore, be careful for files with the same name!

Todo:decide whether to check if the Code must be a local executable to be able to call this function.
set_input_plugin_name(input_plugin)

Set the name of the default input plugin, to be used for the automatic generation of a new calculation.

set_local_executable(exec_name)

Set the filename of the local executable. Implicitly set the code as local.

set_prepend_text(code)

Pass a string of code that will be put in the scheduler script before the execution of the code.

set_remote_computer_exec(remote_computer_exec)

Set the code as remote, and pass the computer on which it resides and the absolute path on that computer.

Parameters:remote_computer_exec – a tuple (computer, remote_exec_path), where computer is a aiida.orm.Computer and remote_exec_path is the absolute path of the main executable on remote computer.
classmethod setup(**kwargs)
__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'codes'
__module__ = 'aiida.restapi.translator.nodes.data.code'
_aiida_class

alias of aiida.orm.nodes.data.code.Code

_aiida_type = 'data.code.Code'
_result_type = 'codes'
static get_downloadable_data(node, download_format=None)[source]

Generic function extented for codes data. Currently it is not implemented.

Parameters:
  • node – node object that has to be downloaded
  • download_format – file extension format
Returns:

raise RestFeatureNotAvailable exception

static get_visualization_data(node, visformat=None)[source]

Generic function extented for codes data. Currently it is not implemented.

Parameters:
  • node – node object that has to be visualized
  • visformat – visualization format
Returns:

raise RestFeatureNotAvailable exception

Translator for kpoints data

class aiida.restapi.translator.nodes.data.kpoints.KpointsDataTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘kpoints’ and aiida class KpointsData

class KpointsData(backend=None, user=None, computer=None, **kwargs)

Bases: 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.

__abstractmethods__ = frozenset()
__module__ = 'aiida.orm.nodes.data.array.kpoints'
_abc_impl = <_abc_data object>
_change_reference(kpoints, to_cartesian=True)

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

_logger = <Logger aiida.orm.nodes.data.array.kpoints.KpointsData (REPORT)>
_plugin_type_string = 'data.array.kpoints.KpointsData.'
_query_type_string = 'data.array.kpoints.'
_set_cell(value)

Validate if ‘value’ is a allowed crystal unit cell :param value: something compatible with a 3x3 tuple of floats

_set_labels(value)

set label names. Must pass in input a list like: [[0,'X'],[34,'L'],... ]

_set_pbc(value)

validate the pbc, then store them

_validate_kpoints_weights(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(also_weights=False, cartesian=False)

Return the list of kpoints

Parameters:
  • 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(print_list=False)

Get the mesh of kpoints.

Parameters:print_list – default=False. If True, prints the mesh of kpoints as a list
Raises:AttributeError – if no mesh has been set
Return mesh,offset:
 (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
Return kpoints:(if print_list = True) an explicit list of kpoints coordinates, similar to what returned by get_kpoints()
labels

Labels associated with the list of kpoints. List of tuples with kpoint index and kpoint name: [(0,'G'),(13,'M'),...]

pbc

The periodic boundary conditions along the vectors a1,a2,a3.

Returns: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

Return the reciprocal cell in units of 1/Angstrom from the internally set cell

set_cell(cell, pbc=None)

Set a cell to be used for symmetry analysis. To set a cell from an AiiDA structure, use “set_cell_from_structure”.

Parameters:
  • 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(structuredata)

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”

Parameters:structuredata – an instance of StructureData
set_kpoints(kpoints, cartesian=False, labels=None, weights=None, fill_values=0)

Set the list of kpoints. If a mesh has already been stored, raise a ModificationNotAllowed

Parameters:
  • 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)

    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(mesh, offset=None)

Set KpointsData to represent a uniformily spaced mesh of kpoints in the Brillouin zone. This excludes the possibility of set/get kpoints

Parameters:
  • 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(distance, offset=None, force_parity=False)

Set a kpoints mesh using a kpoints density, expressed as the maximum distance between adjacent points along a reciprocal axis

Parameters:
  • 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).
Note:

a cell should be defined first.

Note:

the number of kpoints along non-periodic axes is always 1.

__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'kpoints'
__module__ = 'aiida.restapi.translator.nodes.data.kpoints'
_aiida_class

alias of aiida.orm.nodes.data.array.kpoints.KpointsData

_aiida_type = 'data.array.kpoints.KpointsData'
_result_type = 'kpoints'
static get_downloadable_data(node, download_format=None)[source]

Generic function extented for kpoints data. Currently it is not implemented.

Parameters:
  • node – node object that has to be visualized
  • download_format – file extension format
Returns:

raise RestFeatureNotAvailable exception

static get_visualization_data(node, visformat=None)[source]

Returns: data in a format required by dr.js to visualize a 2D plot with multiple data series.

Strategy: For the time being rely on the function implemented in seekpath to calculate brillouin zone faces, and triangulate them. The other fielsd of the response are retrieved by ordniary kpointsdata methods, except the logic to create an list of explicit keypoints from the mesh and the cell vectors.

Translator for structure data

class aiida.restapi.translator.nodes.data.structure.StructureDataTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘structures’ and aiida class StructureData

class StructureData(cell=None, pbc=None, ase=None, pymatgen=None, pymatgen_structure=None, pymatgen_molecule=None, **kwargs)

Bases: aiida.orm.nodes.data.data.Data

This class contains the information about a given structure, i.e. a collection of sites together with a cell, the boundary conditions (whether they are periodic or not) and other related useful information.

__abstractmethods__ = frozenset()
__init__(cell=None, pbc=None, ase=None, pymatgen=None, pymatgen_structure=None, pymatgen_molecule=None, **kwargs)
Parameters:backend_entity (aiida.orm.implementation.BackendEntity) – the backend model supporting this entity
__module__ = 'aiida.orm.nodes.data.structure'
_abc_impl = <_abc_data object>
_adjust_default_cell(vacuum_factor=1.0, vacuum_addition=10.0, pbc=(False, False, False))

If the structure was imported from an xyz file, it lacks a defined cell, and the default cell is taken ([[1,0,0], [0,1,0], [0,0,1]]), leading to an unphysical definition of the structure. This method will adjust the cell

_dimensionality_label = {0: '', 1: 'length', 2: 'surface', 3: 'volume'}
_get_object_ase()

Converts StructureData to ase.Atoms

Returns:an ase.Atoms object
_get_object_phonopyatoms()

Converts StructureData to PhonopyAtoms

Returns:a PhonopyAtoms object
_get_object_pymatgen(**kwargs)

Converts StructureData to pymatgen object

Returns:a pymatgen Structure for structures with periodic boundary conditions (in three dimensions) and Molecule otherwise

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

_get_object_pymatgen_molecule(**kwargs)

Converts StructureData to pymatgen Molecule object

Returns:a pymatgen Molecule object corresponding to this StructureData object.

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors)

_get_object_pymatgen_structure(**kwargs)

Converts StructureData to pymatgen Structure object :param add_spin: True to add the spins to the pymatgen structure. Default is False (no spin added).

Note

The spins are set according to the following rule:

  • if the kind name ends with 1 -> spin=+1
  • if the kind name ends with 2 -> spin=-1
Returns:a pymatgen Structure object corresponding to this StructureData object
Raises:ValueError – if periodic boundary conditions does not hold in at least one dimension of real space; if there are partial occupancies together with spins (defined by kind names ending with ‘1’ or ‘2’).

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors)

_logger = <Logger aiida.orm.nodes.data.structure.StructureData (REPORT)>
_parse_xyz(inputstring)

Read the structure from a string of format XYZ.

_plugin_type_string = 'data.structure.StructureData.'
_prepare_chemdoodle(main_file_name='')

Write the given structure to a string of format required by ChemDoodle.

_prepare_cif(main_file_name='')

Write the given structure to a string of format CIF.

_prepare_xsf(main_file_name='')

Write the given structure to a string of format XSF (for XCrySDen).

_prepare_xyz(main_file_name='')

Write the given structure to a string of format XYZ.

_query_type_string = 'data.structure.'
_set_incompatibilities = [('ase', 'cell'), ('ase', 'pbc'), ('ase', 'pymatgen'), ('ase', 'pymatgen_molecule'), ('ase', 'pymatgen_structure'), ('cell', 'pymatgen'), ('cell', 'pymatgen_molecule'), ('cell', 'pymatgen_structure'), ('pbc', 'pymatgen'), ('pbc', 'pymatgen_molecule'), ('pbc', 'pymatgen_structure'), ('pymatgen', 'pymatgen_molecule'), ('pymatgen', 'pymatgen_structure'), ('pymatgen_molecule', 'pymatgen_structure')]
_validate()

Performs some standard validation tests.

append_atom(**kwargs)

Append an atom to the Structure, taking care of creating the corresponding kind.

Parameters:
  • ase – the ase Atom object from which we want to create a new atom (if present, this must be the only parameter)
  • position – the position of the atom (three numbers in angstrom)
  • symbols – passed to the constructor of the Kind object.
  • weights – passed to the constructor of the Kind object.
  • name – passed to the constructor of the Kind object. See also the note below.

Note

Note on the ‘name’ parameter (that is, the name of the kind):

  • if specified, no checks are done on existing species. Simply, a new kind with that name is created. If there is a name clash, a check is done: if the kinds are identical, no error is issued; otherwise, an error is issued because you are trying to store two different kinds with the same name.
  • if not specified, the name is automatically generated. Before adding the kind, a check is done. If other species with the same properties already exist, no new kinds are created, but the site is added to the existing (identical) kind. (Actually, the first kind that is encountered). Otherwise, the name is made unique first, by adding to the string containing the list of chemical symbols a number starting from 1, until an unique name is found

Note

checks of equality of species are done using the compare_with() method.

append_kind(kind)

Append a kind to the StructureData. It makes a copy of the kind.

Parameters:kind – the site to append, must be a Kind object.
append_site(site)

Append a site to the StructureData. It makes a copy of the site.

Parameters:site – the site to append. It must be a Site object.
cell

Returns the cell shape.

Returns:a 3x3 list of lists.
cell_angles

Get the angles between the cell lattice vectors in degrees.

cell_lengths

Get the lengths of cell lattice vectors in angstroms.

clear_kinds()

Removes all kinds for the StructureData object.

Note

Also clear all sites!

clear_sites()

Removes all sites for the StructureData object.

get_ase()

Get the ASE object. Requires to be able to import ase.

Returns:an ASE object corresponding to this StructureData object.

Note

If any site is an alloy or has vacancies, a ValueError is raised (from the site.get_ase() routine).

get_cell_volume()

Returns the cell volume in Angstrom^3.

Returns:a float.
get_cif(converter='ase', store=False, **kwargs)

Creates aiida.orm.nodes.data.cif.CifData.

New in version 1.0: Renamed from _get_cif

Parameters:
  • converter – specify the converter. Default ‘ase’.
  • store – If True, intermediate calculation gets stored in the AiiDA database for record. Default False.
Returns:

aiida.orm.nodes.data.cif.CifData node.

get_composition()

Returns the chemical composition of this structure as a dictionary, where each key is the kind symbol (e.g. H, Li, Ba), and each value is the number of occurences of that element in this structure. For BaZrO3 it would return {‘Ba’:1, ‘Zr’:1, ‘O’:3}. No reduction with smallest common divisor!

Returns:a dictionary with the composition
get_description()

Returns a string with infos retrieved from StructureData node’s properties

Parameters:self – the StructureData node
Returns:retsrt: the description string
get_dimensionality()

This function checks the dimensionality of the structure and calculates its length/surface/volume :return: returns the dimensionality and length/surface/volume

get_formula(mode='hill', separator='')

Return a string with the chemical formula.

Parameters:
  • mode

    a string to specify how to generate the formula, can assume one of the following values:

    • ’hill’ (default): count the number of atoms of each species, then use Hill notation, i.e. alphabetical order with C and H first if one or several C atom(s) is (are) present, e.g. ['C','H','H','H','O','C','H','H','H'] will return 'C2H6O' ['S','O','O','H','O','H','O'] will return 'H2O4S' From E. A. Hill, J. Am. Chem. Soc., 22 (8), pp 478–494 (1900)
    • ’hill_compact’: same as hill but the number of atoms for each species is divided by the greatest common divisor of all of them, e.g. ['C','H','H','H','O','C','H','H','H','O','O','O'] will return 'CH3O2'
    • ’reduce’: group repeated symbols e.g. ['Ba', 'Ti', 'O', 'O', 'O', 'Ba', 'Ti', 'O', 'O', 'O', 'Ba', 'Ti', 'Ti', 'O', 'O', 'O'] will return 'BaTiO3BaTiO3BaTi2O3'
    • ’group’: will try to group as much as possible parts of the formula e.g. ['Ba', 'Ti', 'O', 'O', 'O', 'Ba', 'Ti', 'O', 'O', 'O', 'Ba', 'Ti', 'Ti', 'O', 'O', 'O'] will return '(BaTiO3)2BaTi2O3'
    • ’count’: same as hill (i.e. one just counts the number of atoms of each species) without the re-ordering (take the order of the atomic sites), e.g. ['Ba', 'Ti', 'O', 'O', 'O','Ba', 'Ti', 'O', 'O', 'O'] will return 'Ba2Ti2O6'
    • ’count_compact’: same as count but the number of atoms for each species is divided by the greatest common divisor of all of them, e.g. ['Ba', 'Ti', 'O', 'O', 'O','Ba', 'Ti', 'O', 'O', 'O'] will return 'BaTiO3'
  • separator – a string used to concatenate symbols. Default empty.
Returns:

a string with the formula

Note

in modes reduce, group, count and count_compact, the initial order in which the atoms were appended by the user is used to group and/or order the symbols in the formula

get_kind(kind_name)

Return the kind object associated with the given kind name.

Parameters:kind_name – String, the name of the kind you want to get
Returns:The Kind object associated with the given kind_name, if a Kind with the given name is present in the structure.
Raise:ValueError if the kind_name is not present.
get_kind_names()

Return a list of kind names (in the same order of the self.kinds property, but return the names rather than Kind objects)

Note

This is NOT necessarily a list of chemical symbols! Use get_symbols_set for chemical symbols

Returns:a list of strings.
get_pymatgen(**kwargs)

Get pymatgen object. Returns Structure for structures with periodic boundary conditions (in three dimensions) and Molecule otherwise. :param add_spin: True to add the spins to the pymatgen structure. Default is False (no spin added).

Note

The spins are set according to the following rule:

  • if the kind name ends with 1 -> spin=+1
  • if the kind name ends with 2 -> spin=-1

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

get_pymatgen_molecule()

Get the pymatgen Molecule object.

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

Returns:a pymatgen Molecule object corresponding to this StructureData object.
get_pymatgen_structure(**kwargs)

Get the pymatgen Structure object. :param add_spin: True to add the spins to the pymatgen structure. Default is False (no spin added).

Note

The spins are set according to the following rule:

  • if the kind name ends with 1 -> spin=+1
  • if the kind name ends with 2 -> spin=-1

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

Returns:a pymatgen Structure object corresponding to this StructureData object.
Raises:ValueError – if periodic boundary conditions do not hold in at least one dimension of real space.
get_site_kindnames()

Return a list with length equal to the number of sites of this structure, where each element of the list is the kind name of the corresponding site.

Note

This is NOT necessarily a list of chemical symbols! Use [ self.get_kind(s.kind_name).get_symbols_string() for s in self.sites] for chemical symbols

Returns:a list of strings
get_symbols_set()

Return a set containing the names of all elements involved in this structure (i.e., for it joins the list of symbols for each kind k in the structure).

Returns:a set of strings of element names.
has_vacancies

Return whether the structure has vacancies in the structure.

Returns:a boolean, True if at least one kind has a vacancy
is_alloy

Return whether the structure contains any alloy kinds.

Returns:a boolean, True if at least one kind is an alloy
kinds

Returns a list of kinds.

pbc

Get the periodic boundary conditions.

Returns: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)
reset_cell(new_cell)

Reset the cell of a structure not yet stored to a new value.

Parameters:new_cell – list specifying the cell vectors
Raises:ModificationNotAllowed: if object is already stored
reset_sites_positions(new_positions, conserve_particle=True)

Replace all the Site positions attached to the Structure

Parameters:
  • new_positions – list of (3D) positions for every sites.
  • conserve_particle – if True, allows the possibility of removing a site. currently not implemented.
Raises:

Note

it is assumed that the order of the new_positions is given in the same order of the one it’s substituting, i.e. the kind of the site will not be checked.

set_ase(aseatoms)

Load the structure from a ASE object

set_cell(value)
set_cell_angles(value)
set_cell_lengths(value)
set_pbc(value)
set_pymatgen(obj, **kwargs)

Load the structure from a pymatgen object.

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

set_pymatgen_molecule(mol, margin=5)

Load the structure from a pymatgen Molecule object.

Parameters:margin – the margin to be added in all directions of the bounding box of the molecule.

Note

Requires the pymatgen module (version >= 3.0.13, usage of earlier versions may cause errors).

set_pymatgen_structure(struct)

Load the structure from a pymatgen Structure object.

Note

periodic boundary conditions are set to True in all three directions.

Note

Requires the pymatgen module (version >= 3.3.5, usage of earlier versions may cause errors).

Raises:ValueError – if there are partial occupancies together with spins.
sites

Returns a list of sites.

__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'structures'
__module__ = 'aiida.restapi.translator.nodes.data.structure'
_aiida_class

alias of aiida.orm.nodes.data.structure.StructureData

_aiida_type = 'data.structure.StructureData'
_result_type = 'structures'
static get_downloadable_data(node, download_format='cif')[source]

Generic function extented for structure data

Parameters:
  • node – node object that has to be visualized
  • download_format – file extension format
Returns:

data in selected format to download

static get_visualization_data(node, visformat='xsf')[source]

Returns: data in specified format. If visformat is not specified returns data in xsf format in order to visualize the structure with JSmol.

Translator for upf data

class aiida.restapi.translator.nodes.data.upf.UpfDataTranslator(**kwargs)[source]

Bases: aiida.restapi.translator.nodes.data.DataTranslator

Translator relative to resource ‘upfs’ and aiida class UpfData

class UpfData(file=None, source=None, **kwargs)

Bases: aiida.orm.nodes.data.singlefile.SinglefileData

Function not yet documented.

__abstractmethods__ = frozenset()
__init__(file=None, source=None, **kwargs)

Construct a new instance and set the contents to that of the file.

Parameters:file – an absolute filepath or filelike object whose contents to copy
__module__ = 'aiida.orm.nodes.data.upf'
_abc_impl = <_abc_data object>
_logger = <Logger aiida.orm.nodes.data.upf.UpfData (REPORT)>
_plugin_type_string = 'data.upf.UpfData.'
_query_type_string = 'data.upf.'
_validate()

Ensure that there is one object stored in the repository, whose key matches value set for filename attr.

element
classmethod from_md5(md5)

Return a list of all UPF pseudopotentials that match a given MD5 hash.

Note that the hash has to be stored in a _md5 attribute, otherwise the pseudo will not be found.

classmethod get_or_create(filepath, use_first=False, store_upf=True)

Pass the same parameter of the init; if a file with the same md5 is found, that UpfData is returned.

Parameters:
  • filepath – an absolute filepath on disk
  • use_first – if False (default), raise an exception if more than one potential is found. If it is True, instead, use the first available pseudopotential.
  • store_upf (bool) – If false, the UpfData objects are not stored in the database. default=True.
Return (upf, created):
 

where upf is the UpfData object, and create is either True if the object was created, or False if the object was retrieved from the DB.

get_upf_family_names()

Get the list of all upf family names to which the pseudo belongs.

classmethod get_upf_group(group_label)

Return the UpfFamily group with the given name.

classmethod get_upf_groups(filter_elements=None, user=None)

Return all names of groups of type UpfFamily, possibly with some filters.

Parameters:
  • filter_elements – A string or a list of strings. If present, returns only the groups that contains one Upf for every element present in the list. Default=None, meaning that all families are returned.
  • user – if None (default), return the groups for all users. If defined, it should be either a DbUser instance, or a string for the username (that is, the user email).
md5sum
set_file(file)

I pre-parse the file to store the attributes.

store(*args, **kwargs)

Store the node, reparsing the file so that the md5 and the element are correctly reset.

upffamily_type_string = 'data.upf'
__init__(**kwargs)[source]

Initialise the parameters. Create the basic query_help

__label__ = 'upfs'
__module__ = 'aiida.restapi.translator.nodes.data.upf'
_aiida_class

alias of aiida.orm.nodes.data.upf.UpfData

_aiida_type = 'data.upf.UpfData'
_result_type = 'upfs'
static get_downloadable_data(node, download_format=None)[source]

Generic function extended for upf data

Parameters:
  • node – node object that has to be downloaded
  • download_format – file extension format
Returns:

data in selected format to download

static get_visualization_data(node, visformat=None)[source]

Returns: data in a format required by dr.js to visualize a 2D plot with multiple data series.