Utilities¶
Presented here is a small set of useful utility tools that can come handy in various contexts in your scripts. They are simple, standalone objects always present in the main namespace.
What is characteristic for the PeriodicTable
and Units
classes described below is that they are meant to be used in a bit different way than all other PLAMS classes.
Usually one takes a class (like DiracJob
), creates an instance of it (myjob = DiracJob(...)
) and executes some of its methods (r = myjob.run()
).
In contrast, utility classes are designed in a way similar to so called singleton design pattern.
That means it is not possible to create any instances of these classes.
The class itself serves for “one and only instance” and all methods should be called using the class as the calling object:
>>> x = PeriodicTable()
PTError: Instances of PeriodicTable cannot be created
>>> s = PeriodicTable.get_symbol(20)
>>> print(s)
Ca
Periodic Table¶
- class PeriodicTable[source]¶
A singleton class for the periodic table of elements.
For each element the following properties are stored: atomic symbol, atomic mass, atomic radius and number of connectors.
Atomic mass is, strictly speaking, atomic weight, as present in Mathematica’s ElementData function.
Atomic radius and number of connectors are used by
guess_bonds()
. Note that values of radii are neither atomic radii nor covalent radii. They are somewhat “emprically optimized” for the bond guessing algorithm.Note
This class is visible in the main namespace as both
PeriodicTable
andPT
.- classmethod get_connectors(arg)[source]¶
Convert atomic symbol or atomic number to number of connectors.
- classmethod get_metallic(arg)[source]¶
Convert atomic symbol or atomic number to number of connectors.
- classmethod get_electronegative(arg)[source]¶
Convert atomic symbol or atomic number to number of connectors.
- classmethod set_connectors(element, value)[source]¶
Set the number of connectors of element to value.
- classmethod _get_property(arg, prop)[source]¶
Get property of element described by either symbol or atomic number. Skeleton method for
get_radius()
,get_mass()
andget_connectors()
.
Units¶
- class Units[source]¶
A singleton class for unit converter.
All values are based on 2014 CODATA recommended values.
The following constants and units are supported:
constants:
speed_of_light
(alsoc
)electron_charge
(alsoe
)Avogadro_constant
(alsoNA
)Bohr_radius
distance:
Angstrom
,A
,Ang
Bohr
,au
,a.u.
nm
pm
reciprocal distance:
1/Angstrom
,1/A
,Angstrom^-1
,A^-1
,1/Bohr
,Bohr^-1
angle:
degree
,deg
radian
,rad
grad
circle
charge:
coulomb
,C
e
energy:
au
,a.u.
,Hartree
eV
kcal/mol
kJ/mol
cm^-1
,cm-1
K
,Kelvin
dipole moment:
au
,a.u.
,e*bohr
Debye
,D
All charge units multiplied by distance units, for example
eA
,e*A
Cm
,C*m
molecular polarizability:
au
,a.u.
,(e*bohr)^2/hartree
e*A^2/V
C*m^2/V
cm^3
bohr^3
A^3
,angstrom^3
,Ang^3
forces:
All energy units divided by angstrom or bohr, for example
eV/angstrom
hartree/bohr
hessian:
All energy units divided by angstrom^2 or bohr^2, for example
eV/angstrom^2
hartree/bohr^2
pressure:
All energy units divided by angstrom^3 or bohr^3, for example
eV/angstrom^3
hartree/bohr^3
And some more:
Pa
GPa
bar
atm
Example:
>>> print(Units.constants['speed_of_light']) 299792458 >>> print(Units.constants['e']) 1.6021766208e-19 >>> print(Units.convert(123, 'angstrom', 'bohr')) 232.436313431 >>> print(Units.convert([23.32, 145.0, -34.7], 'kJ/mol', 'kcal/mol')) [5.573613766730401, 34.655831739961755, -8.293499043977056] >>> print(Units.conversion_ratio('kcal/mol', 'kJ/mol')) 4.184
- classmethod convert(value, inp, out)[source]¶
Convert value from unit inp to out.
value can be a single number or a container (list, tuple, numpy.array etc.). In the latter case a container of the same type and length is returned. Conversion happens recursively, so this method can be used to convert, for example, a list of lists of numbers, or any other hierarchical container structure. Conversion is applied on all levels, to all values that are numbers (also numpy number types). All other values (strings, bools etc.) remain unchanged.
Geometry tools¶
A small module with simple functions related to 3D geometry operations.
- rotation_matrix(vec1, vec2)[source]¶
Calculate the rotation matrix rotating vec1 to vec2. Vectors can be any containers with 3 numerical values. They don’t need to be normalized. Returns 3x3 numpy array.
- axis_rotation_matrix(vector, angle, unit='radian')[source]¶
Calculate the rotation matrix rotating along the vector by angle expressed in unit.
vector can be any container with 3 numerical values. They don’t need to be normalized. A positive angle denotes counterclockwise rotation, when looking along vector. Returns 3x3 numpy array.
- distance_array(array1, array2)[source]¶
Calculates distance between each pair of points in array1 and array2. Returns 2D
numpy
array.Uses fast
cdist
function ifscipy
is present, otherwise falls back to slightly slowernumpy
loop. Arguments should be 2-dimensionalnumpy
arrays with the same second dimension. If array1 is A x N and array2 is B x N, the returned array is A x B.
- angle(vec1, vec2, result_unit='radian')[source]¶
Calculate an angle between vectors vec1 and vec2.
vec1 and vec2 should be iterable containers of length 3 (for example: tuple, list, numpy array). Values stored in them are expressed in Angstrom. Returned value is expressed in result_unit.
This method requires all atomic coordinates to be numerical values,
TypeError
is raised otherwise.
- dihedral(p1, p2, p3, p4, unit='radian')[source]¶
Calculate the value of diherdal angle formed by points p1, p2, p3 and p4 in a 3D space. Arguments can be any containers with 3 numerical values, also instances of
Atom
. Returned value is always non-negative, measures the angle clockwise (looking along p2-p3 vector) and is expressed in unit.
File format conversion tools¶
A small module for converting VASP output to AMS-like output, and for converting ASE .traj trajectory files to the .rkf format.
- traj_to_rkf(trajfile, rkftrajectoryfile, task=None, timestep=0.25)[source]¶
Convert ase .traj file to .rkf file. NOTE: The order of atoms (or the number of atoms) cannot change between frames!
- trajfilestr
path to a .traj file
- rkftrajectoryfilestr
path to the output .rkf file (will be created)
- taskstr
Which task to write. If None it is auto-determined.
- timestep: float
Which timestep to write when task == ‘moleculardynamics’
- Returns2-tuple (coords, cell)
The final coordinates and cell in angstrom
- vasp_output_to_ams(vasp_folder, wdir=None, overwrite=False, write_engine_rkf=True, task=None, timestep=0.25)[source]¶
Converts VASP output (OUTCAR, …) to AMS output (ams.rkf, vasp.rkf)
Returns: a string containing the directory where ams.rkf was written
- vasp_folderstr
path to a directory with an OUTCAR, INCAR, POTCAR etc. files
- wdirstr or None
directory in which to write the ams.rkf and vasp.rkf files If None, a subdirectory “AMSJob” of vasp_folder will be created
- overwritebool
if False, first check if wdir already contains ams.rkf and vasp.rkf, in which case do nothing if True, overwrite if exists
- write_engine_rkfbool
If True, also write vasp.rkf alongside ams.rkf. The vasp.rkf file will only contain an AMSResults section (energy, gradients, stress tensor). It will not contain the DOS or the band structure.
- taskstr
Which task to write to ams.rkf. If None it is auto-determined (probably set to ‘geometryoptimization’)
- timestepfloat
If task=’moleculardynamics’, which timestep (in fs) between frames to write
- qe_output_to_ams(qe_outfile, wdir=None, overwrite=False, write_engine_rkf=True)[source]¶
Converts a qe .out file to ams.rkf and qe.rkf.
Returns: a string containing the directory where ams.rkf was written
If the filename ends in .out, check if a .results directory exists. In that case, place the AMSJob subdirectory in the .results directory.
Otherwise, create a new directory called filename.AMSJob
- qe_outfilestr
path to the qe output file
- gaussian_output_to_ams(outfile, wdir=None, overwrite=False, write_engine_rkf=True)[source]¶
Converts a Gaussian .out file to ams.rkf and gaussian.rkf.
Returns: a string containing the directory where ams.rkf was written
If the filename ends in .out, check if a .results directory exists. In that case, place the AMSJob subdirectory in the .results directory.
Otherwise, create a new directory called filename.AMSJob
- outfilestr
path to the gaussian output file
- rkf_to_ase_traj(rkf_file, out_file, get_results=True)[source]¶
Convert an ams.rkf trajectory to a different trajectory format (.xyz, .traj, anything supported by ASE)
- rkf_file: str
Path to an ams.rkf file
- out_file: str
Path to the .traj or .xyz file that will be created. If the file exists it will be overwritten. If a .xyz file is specified it will use the normal ASE format (not the AMS format).
- get_results: bool
Whether to include results like energy, forces, and stress in the trajectory.
Reaction energies¶
- balance_equation(reactants, products, normalization='r0', normalization_value=1.0)[source]¶
Calculate stoichiometric coefficients This only works if * number_of_chemical_elements == len(reactants)+len(products), OR * number_of_chemical_elements == len(reactants)+len(products)-1
- Returns: a 2-tuple (coeffs_reactants, coeffs_products)
coeffs_reactants is a list with length == len(reactants) coeffs_products is a list with length == len(products)
- reactants: a list of amsjobs, or a list of paths to ams.results folders or ams.rkf files or .xyz files, or a list of Molecules, or a list of stoichiometry dicts, or a list of Molecules
The reactants
- products: a list of amsjobs, or a list of paths to ams.results folders or ams.rkf files, or a list of Molecules or .xyz files, or a list of stoichiometry dicts, or a list of Molecules
The products
- normalization: str
‘r0’ for the first reactant, ‘r1’ for the second reactant, etc. ‘p0’ for the first product, ‘p1’ for the second product, etc. This normalizes the chemical equation such that the coefficient in front of the specified species is normalization_value
- normalization_valuefloat
The coefficient to normalize to
EXAMPLE:
balance_equation( reactants=[ {'N': 2, 'H': 8, 'Cr': 2, 'O': 7} ], products=[ {'Cr': 2, 'O': 3}, {'N': 2}, {'H': 2, 'O': 1} ])
The above returns a tuple
([1.0], [1.0, 1.0, 1.0, 4.0])
- reaction_energy(reactants, products, normalization='r0', unit='hartree')[source]¶
Calculates a reaction energy from an unbalanced chemical equation (the equation is first balanced)
- reactants: a list of amsjobs or paths to ams results folders,
The recatnts
- products: a list of amsjobs or paths to ams results folders
The products
- normalization: str
normalize the chemical equation by setting the corresponding coefficient to 1.
‘r0’: first reactant
‘r1’: second reactant, …
‘p0: first product,
‘p1’: second product, …
- unit: str
Unit of the reaction energy
Returns: a 3-tuple (coeffs_reactants, coeffs_products, reaction_energy)
Plotting tools¶
See also
Tools for creating plots with matplotlib.
- plot_band_structure(x, y_spin_up, y_spin_down=None, labels=None, fermi_energy=None, zero=None, ax=None)[source]¶
Plots an electronic band structure from DFTB or BAND with matplotlib.
To control the appearance of the plot you need to call
plt.ylim(bottom, top)
,plt.title(title)
, etc. manually outside this function.- x: list of float
Returned by AMSResults.get_band_structure()
- y_spin_up: 2D numpy array of float
Returned by AMSResults.get_band_structure()
- y_spin_down: 2D numpy array of float. If None, the spin down bands are not plotted.
Returned by AMSResults.get_band_structure()
- labels: list of str
Returned by AMSResults.get_band_structure()
- fermi_energy: float
Returned by AMSResults.get_band_structure(). Should have the same unit as
y
.- zero: None or float or one of ‘fermi’, ‘vbmax’, ‘cbmin’
Shift the curves so that y=0 is at the specified value. If None, no shift is performed. ‘fermi’, ‘vbmax’, and ‘cbmin’ require that the
fermi_energy
is not None. Note: ‘vbmax’ and ‘cbmin’ calculate the zero as the highest (lowest) eigenvalue smaller (greater) than or equal tofermi_energy
. This is NOT necessarily equal to the valence band maximum or conduction band minimum as calculated by the compute engine.
Additional parameters:
ax
: matplotlib axisThe axis. If None, one will be created
- plot_molecule(molecule, figsize=None, ax=None, keep_axis=False, **kwargs)[source]¶
Show a molecule in a Jupyter notebook
- plot_correlation(job1, job2, section, variable, alt_section=None, alt_variable=None, file='ams', multiplier=1.0, unit=None, save_txt=None, ax=None, show_xy=True, show_linear_fit=True, show_mad=True, show_rmsd=True, xlabel=None, ylabel=None)[source]¶
Plot a correlation plot from AMS .rkf files
- job1: AMSJob or List[AMSJob]
Job(s) plotted on x-axis
- job2: AMSJob or List[AMSJob]
job2: Job(s) plotted on y-axis
- section: str
section: section to read on .rkf files
- variable: str
variable: variable to read
- alt_section: str
Section to read on .rkf files for job2. If not specified it will be the same as
section
- alt_variablestr
Variable to read for job2. If not specified it will be the same as
variable
.- file: str, optional
file: “ams” or “engine”, defaults to “ams”
- multiplier: float, optional
multiplier: Numbers will be multiplied by this number, defaults to 1.0
- unit: str, optional
unit: unit will be shown in the plot, defaults to None
- save_txt: str, optional
save_txt: If not None, save the xy data to this text file, defaults to None
- ax: matplotlib axis, optional
ax: matplotlib axis, defaults to None
- show_xy: bool, optional
show_xy: Whether to show y=x line, defaults to True
- show_linear_fit: bool, optional
show_linear_fit: Whether to perform and show a linear fit, defaults to True
- show_mad: bool, optional
show_mad: Whether to show mean absolute deviation, defaults to True
- show_rmsd: bool, optional
show_rmsd: Whether to show root-mean-square deviation, defaults to True
- xlabel: str, optional
xlabel: The x-label. If not given will be a list of job names, defaults to None
- ylabel: str, optional
ylabel: THe y-label. If not given will be al ist of job names, defaults to None
Returns: A matplotlib axis
- plot_msd(job, start_time_fit_fs=None, ax=None)[source]¶
- job: AMSMSDJob
The job for which to plot the results
- start_time_fit_fs: float
The start time (in fs) for which to perform the linear fit
- ax: matplotlib axis
The axis. If None, one will be created
Returns: matplotlib axis
- plot_work_function(coordinate, planarAverage, macroscopicAverage, Efermi, Vbulk, Vvacuum, WF, ax=None)[source]¶
Plots an Electrostatic Potential Profile from AMS-QE with matplotlib.
To control the appearance of the plot you need to call
plt.ylim(bottom, top)
,plt.title(title)
, etc. manually outside this function.coordinate
: 1D array of float.Returned by AMSResults.get_work_function_results().
planarAverage
: 1D array of float.Returned by AMSResults.get_work_function_results().
macroscopicAverage
: 1D array of float.Returned by AMSResults.get_work_function_results(). Should have the same unit as
planarAverage
.Efermi
: float.Returned by AMSResults.get_work_function_results(). Should have the same unit as
planarAverage
.Vbulk
: float.Returned by AMSResults.get_work_function_results(). Should have the same unit as
planarAverage
.Vvacuum
: Tuple[float,float].Returned by AMSResults.get_work_function_results(). Should have the same unit as
planarAverage
.WF
: Tuple[float,float].Returned by AMSResults.get_work_function_results(). Should have the same unit as
planarAverage
.
Additional parameters:
ax
: matplotlib axisThe axis. If None, one will be created
Returns: matplotlib axis
Postprocess results¶
Tools for postprocessing the results.
- broaden_results(centers, areas, broadening_width=40, broadening_type='gaussian', x_data=(0, 4000, 0.5), post_process=None)[source]¶
convenient function for create xy curve with gaussian or lorentzian peaks. Used to obtain IR or Raman spectra for example.
- Parameters:
centers (np.ndarray) – x positions of the centers of the peaks
areas (np.ndarray) – areas of the peaks
broadening_width (Union[float, np.ndarray], optional) – if is np.ndarray each peak broadening is assigned otherwise apply the same value for all the peaks, defaults to 40
broadening_type (Literal['gaussian', 'lorentzian'], optional) – the line shape of the peak, defaults to “gaussian”
x_data (Union[np.ndarray, Tuple[float, float, float]], optional) – it can be a np.ndarray or you can set a tuple with (min,max,step_size), defaults to (0, 4000, 0.5)
post_process (Literal['max_to_1'], optional) – if max_to_1 the resulted spectrum has the max peak height =1, defaults to None
- Returns:
the x and y arrays
- Return type:
Tuple[np.ndarray, np.ndarray]