schrodinger.application.matsci.espresso.utils module

Copyright Schrodinger, LLC. All rights reserved.

class schrodinger.application.matsci.espresso.utils.MagElement(mag, hubb_u, hubb_j0, zval)

Bases: tuple

__contains__

Return key in self.

__init__

Initialize self. See help(type(self)) for accurate signature.

__len__

Return len(self).

count(value) → integer -- return number of occurrences of value
hubb_j0

Alias for field number 2

hubb_u

Alias for field number 1

index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

mag

Alias for field number 0

zval

Alias for field number 3

schrodinger.application.matsci.espresso.utils.get_null_mag_element()
schrodinger.application.matsci.espresso.utils.get_shell_runner(check_only=False, write_orig=False)

Get path to the shell runner script.

Parameters:
  • check_only (bool) – If True, only check if runner exists and return
  • write_orig (bool) – If True, create original shell runner even if runner exists
Return type:

(str, bool)

Returns:

Path to shell runner and True if shell runner has been just created, otherwise False

class schrodinger.application.matsci.espresso.utils.ArgumentParserNoExit(prog=None, usage=None, description=None, epilog=None, parents=[], formatter_class=<class 'argparse.HelpFormatter'>, prefix_chars='-', fromfile_prefix_chars=None, argument_default=None, conflict_handler='error', add_help=True, allow_abbrev=True)

Bases: argparse.ArgumentParser

Subclass that raises instead of exiting on error.

error(message)

From python docs: If you override this in a subclass, it should not return – it should either exit or raise an exception.

__init__(prog=None, usage=None, description=None, epilog=None, parents=[], formatter_class=<class 'argparse.HelpFormatter'>, prefix_chars='-', fromfile_prefix_chars=None, argument_default=None, conflict_handler='error', add_help=True, allow_abbrev=True)

Initialize self. See help(type(self)) for accurate signature.

add_argument(dest, ..., name=value, ...)

add_argument(option_string, option_string, …, name=value, …)

add_argument_group(*args, **kwargs)
add_mutually_exclusive_group(**kwargs)
add_subparsers(**kwargs)
convert_arg_line_to_args(arg_line)
exit(status=0, message=None)
format_help()
format_usage()
get_default(dest)
parse_args(args=None, namespace=None)
parse_known_args(args=None, namespace=None)
print_help(file=None)
print_usage(file=None)
register(registry_name, value, object)
set_defaults(**kwargs)
schrodinger.application.matsci.espresso.utils.add_qe_parallel_parser_arguments(parser)

Add QE parallel arguments to the parser.

Parameters:parser (argparse.ArgumentParser) – The parser to add arguments to
schrodinger.application.matsci.espresso.utils.get_pkeywords(options, ncpus, npools=None)

Validate and get string of parallel keywords for QE binaries (pw.x, etc.).

Parameters:
  • options (argparse Namespace object) – The input options
  • ncpus (int) – Number of total requested CPUs
  • npools (int) – npools value, None for default passed in options
Return type:

bool, str or list

Returns:

If converted successfully, True and a list of [keyword, value] are returned, otherwise, False and error message are returned

schrodinger.application.matsci.espresso.utils.get_mag_hubbu(atom, decimals=10)

Get starting magnetization and Hubbard U parameters from atom property. If not present, return the default.

Parameters:
Return type:

MagElement namedtuple

Returns:

Tuple of starting magnetization and Hubbard parameters

schrodinger.application.matsci.espresso.utils.set_mag_hubbu(atom, mag_element)

Set starting magnetization and Hubbard U parameters in atom property.

Parameters:
schrodinger.application.matsci.espresso.utils.sync_pbc(struct, lattice_params=None, chorus_params=None, prioritize_cparams=False)

Sync PBC properties in place (without creating a new structure) for struct. If all PBC properties are absent (both chorus and PDB) return False. It is possible to provide new lattice or chorus parameters and to prioritize one of the sets.

Type:

schrodinger.structure.Structure

Param:

Structure to be modified

Parameters:
  • lattice_params (list or numpy.array or None) – contains the a, b, c, alpha, beta, and gamma lattice parameters or None. These will be used instead of ones possibly obtained from the struct
  • chorus_params (list or numpy.array or None) – contains the nine chorus properties, i.e. ax, ay, az, bx, …, cz or None. These will be used instead of ones possibly obtained from the struct
Param:

Prioritize chorus params over lattice params if True. If False, lattice params have priority

Return type:

bool

Returns:

True on syncing success, False if both sets were not provided or empty

schrodinger.application.matsci.espresso.utils.get_mpircores_from_environ()

Get -MPICORES flag value from SCHRODINGER_COMMANDLINE environment variable. If not found, return 1.

Return type:int
Returns:MPICORES value or 1 (if not defined)
schrodinger.application.matsci.espresso.utils.set_smart_distribution_from_environ(jobq)

Set smart distribution of the queue to on/off based on the environment variable.

Parameters:jobq (schrodinger.job.queue.JobDJ) – The JobDJ object
schrodinger.application.matsci.espresso.utils.get_element(element)

Get element name with the removed digits from atom type. Those might be present to due starting magnetization.

Parameters:element (str) – Element
Return type:str
Returns:Element without digits
class schrodinger.application.matsci.espresso.utils.PPHeaderHTMLParser(*args, **kwargs)

Bases: html.parser.HTMLParser

Parse and store pp_header tag attributes.

PP_HEADER_TAG = 'pp_header'
__init__(*args, **kwargs)

Initialize object. See parent class for documentation.

handle_starttag(tag, attrs)

Save PP_HEADER attributes in dictionary.

CDATA_CONTENT_ELEMENTS = ('script', 'style')
check_for_whole_start_tag(i)
clear_cdata_mode()
close()

Handle any buffered data.

error(message)
feed(data)

Feed data to the parser.

Call this as often as you want, with as little or as much text as you want (may include ‘n’).

get_starttag_text()

Return full source of start tag: ‘<…>’.

getpos()

Return current line number and offset.

goahead(end)
handle_charref(name)
handle_comment(data)
handle_data(data)
handle_decl(decl)
handle_endtag(tag)
handle_entityref(name)
handle_pi(data)
handle_startendtag(tag, attrs)
parse_bogus_comment(i, report=1)
parse_comment(i, report=1)
parse_declaration(i)
parse_endtag(i)
parse_html_declaration(i)
parse_marked_section(i, report=1)
parse_pi(i)
parse_starttag(i)
reset()

Reset this instance. Loses all unprocessed data.

set_cdata_mode(elem)
unescape(s)
unknown_decl(data)
updatepos(i, j)
class schrodinger.application.matsci.espresso.utils.UPFParser(path, file_fh=None, binary=False)

Bases: object

Class that handles UPF parsing.

PP_TYPE_NC = 'NC'
PP_TYPE_PAW = 'PAW'
PP_TYPES = ('1/r', 'US', 'NC', 'PAW')
FULLY_REL = 'full'
__init__(path, file_fh=None, binary=False)

Initialize UPFParser.

Parameters:path (str) – Path to the UPF file
class schrodinger.application.matsci.espresso.utils.HighSymmetryKPath(struct)

Bases: object

Based on symmetry/bandstructure.py :: HighSymmKpath (MIT license)

This class looks for path along high symmetry lines in the Brillouin Zone. It is based on Setyawan, W., & Curtarolo, S. (2010). High-throughput electronic band structure calculations: Challenges and tools. Computational Materials Science, 49(2), 299-312. doi:10.1016/j.commatsci.2010.05.010

__init__(struct)

Initialize kpath class. self.kpath will contain ‘edge’ points.

Parameters:struct (structure.Structure) – Structure that has space group / unit cell data
cubic()

Generate ‘edge’ k-points for the cubic lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
fcc()

Generate ‘edge’ k-points for the FCC cubic lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
bcc()

Generate ‘edge’ k-points for the BCC cubic lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
tet()

Generate ‘edge’ k-points for the tetrahedral lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
bctet1(c, a)

Generate ‘edge’ k-points for the tetrahedral lattice with I setting.

Parameters:
  • c (float) – C length
  • a (float) – A length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

bctet2(c, a)

Generate ‘edge’ k-points for the tetrahedral lattice with I setting.

Parameters:
  • c (float) – C length
  • a (float) – A length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

orc()

Generate ‘edge’ k-points for the orthorhombic lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
orcf1(a, b, c)

Generate ‘edge’ k-points for the orthorhombic lattice with F setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

orcf2(a, b, c)

Generate ‘edge’ k-points for the orthorhombic lattice with F setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

orcf3(a, b, c)

Generate ‘edge’ k-points for the orthorhombic lattice with F setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

orci(a, b, c)

Generate ‘edge’ k-points for the orthorhombic lattice with I setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

orcc(a, b, c)

Generate ‘edge’ k-points for the orthorhombic lattice with C setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

hex()

Generate ‘edge’ k-points for the hexagonal lattice.

Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ - a list of labels from the ‘kpoints’.
rhl1(alpha)

Generate ‘edge’ k-points for the rhombohedral lattice with alpha < 90.

Parameters:alpha (float) – Alpha cell angle in radians
Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
rhl2(alpha)

Generate ‘edge’ k-points for the rhombohedral lattice with alpha > 90.

Parameters:alpha (float) – Alpha cell angle in radians
Return type:dict
Returns:keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.
mcl(b, c, beta)

Generate ‘edge’ k-points for the monoclinic lattice.

Parameters:
  • b (float) – B length
  • c (float) – C length
  • beta (float) – Beta cell angle in radians
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

mclc1(a, b, c, alpha)

Generate ‘edge’ k-points for the monoclinic lattice with C setting.

Parameters:
  • a (float) – A length
  • b (float) – B length
  • c (float) – C length
  • alpha (float) – Alpha cell angle in radians
Return type:

dict

Returns:

keys: ‘kpoints’ is a dict with labels as keys and coordinates as values, ‘path’ is a list of labels from the ‘kpoints’ dict.

tria()
class schrodinger.application.matsci.espresso.utils.MemoryEstimator(vecs, ecutwfc, ecutrho, nproc, nks, nspin, nbnd, ntyp, nmix, lscf)

Bases: object

Class to estimate RAM memory for a PW (QE) job.

COMPLEX_SIZE = 16.0
REAL_SIZE = 8.0
INT_SIZE = 4.0
MBYTE = 1048576.0
NFFTX = 2049
__init__(vecs, ecutwfc, ecutrho, nproc, nks, nspin, nbnd, ntyp, nmix, lscf)

Initialize MemoryEstimator object and set several attributes.

Parameters:
  • vecs (3 list of 3 floats) – Lattice vectors
  • ecutwfc (float) – Wavefunction cutoff (Ry)
  • ecutrho (float) – Density cutoff (Ry)
  • nproc (int) – Number of processors
  • nks (int) – Number of k-points
  • nspin (int) – 1 for closed-shell, 2 for spin-polarized
  • nbnd (int) – Number of bands
  • ntyp (int) – Number of atom types
  • nmix (int) – Beta mixing
  • lscf (bool) – True if the calculation is scf/relax, False if it is nscf
realSpaceGridInit(at_vecs, bg_vecs, gcutm)

Gets minimal 3D real-space FFT grid.

Parameters:
  • at_vecs (3 x 3 table of floats) – Lattice vectors in the units of alat
  • bg_vecs (3 x 3 table of floats) – Reciprocal lattice vectors in the units of 1/alat
  • gctum – Radius of the sphere to fit the FFT grid
Return type:

list of 3 floats

Returns:

FFT grid sizes

getGoodFFTDim(fft_dim)

Get a good FFT dimension.

Parameters:fft_dim (int) – FFT dimension
Return type:int
Returns:Good FFT dimension, if exists
isGoodDim(fft_dim)

Check if FFT dimension is good.

Parameters:fft_dim (int) – FFT dimension

:rtype bool :return: True, if FFT dimension is good, False otherwise

class schrodinger.application.matsci.espresso.utils.MagSpecies(struct=None)

Bases: object

Class that defines species with starting magnetization.

__init__(struct=None)

Initialize MagSpecies class.

createUniqueElement(element, mag_element)

Fill self.data dict. Keys of the self.data are elements. Values are dicts with magnetization as key and unique element as value. Unique element is just the atomic symbol plus (if element has more than one magnetization value) a unique integer. Example: {‘C’: {0.0: ‘C’}, ‘H’: {0.0: ‘H’, 0.1: ‘H1’}}

self.species is a dict where unique elements are keys and elements are values. Example (based on the example above): {‘C’: ‘C’, ‘H’: ‘H’, ‘H1’: ‘H’}

Parameters:
  • element (str) – Element
  • mag (float) – Starting magnetization
  • hubb_u (float) – Hubbard U parameter
Return type:

str

Returns:

Unique element

getMag(element, unique_element)

Get magnetization given element and unique element values.

Parameters:
  • element (str) – Element
  • unique_element (str) – Unique element
Return type:

tuple

Returns:

Starting magnetization and Hubbard U

Raises:

ValueError – If element, unique_element combination is not found

fromStructure(struct)

Set data from the structure.

Parameters:struct (structure.Structure) – Input structure