carmm.analyse package

Subpackages

Submodules

carmm.analyse.angles module

carmm.analyse.angles.analyse_all_angles(model, verbose=True)

Returns a table of bond angle analysis for the supplied model.

Parameters:

model: Atoms object

The structure that needs to be interrogated

verbose: Boolean

Whether to print information to screen

Returns:

  • list of all elemental combinations

  • list of indices for each elemental combination

  • list of all angle values for each combination of indices

carmm.analyse.angles.analyse_angles(model, A, B, C, verbose=True, multirow=False)

Check A-B-C angles present in the model.

Parameters: model: Atoms object

The ASE atoms object that needs to be considered

A: string, chemical symbol, e.g. “O” B: string, chemical symbol, e.g. “C” C: string, chemical symbol, e.g. “O” verbose: Boolean

Whether to print information to screen

multirow: Boolean

Whether we are returning multiple sets of results in a Table

carmm.analyse.angles.print_angles_table_header()

carmm.analyse.bonds module

carmm.analyse.bonds.analyse_all_bonds(model, verbose=True, abnormal=True)

Analyse bonds and return all abnormal bond types and list of these TODO: Make this more bullet proof - what happens if abnormal bonds aren’t requested. A table of bond distance analysis for the supplied model is also possible

Parameters:

model: Atoms object

Structure for which the analysis is to be conducted

verbose: Boolean

Determines whether the output should be printed to screen

abnormal: Boolean

Collect information about rogue looking bond lengths. (Does enabling this by default add a large time overhead?)

carmm.analyse.bonds.analyse_bonds(model, A, B, verbose=True, multirow=False)

Check A-B distances present in the model.

Parameters: model: Atoms object

XXX

A: string, chemical symbol, e.g. “H” B: string, chemical symbol, e.g. “H” verbose: Boolean

Whether to print information to screen

multirow: Boolean

Whether we are working with analyse_all_bonds, so the output is multirow, or just one specific analysis of a bond, in which case the table header is needed.

carmm.analyse.bonds.analyse_chelation(atoms, metal, ligand_atoms, mult=1)

Returns information on the ligands in a mononuclear complex and their chelation type. TODO: rework so script can account for multiple separate metal atoms (ie: polynuclear complexes)

Parameters: atoms: Atoms object

Input structure from which to calculate molecular information

Mult: float value

Multiplier for the bond cutoffs. Set to 1 as default but can be adjusted depending on application

metal: String

Metal cation to characterise the coordination environment around

ligand_atom: list

Element symbol of the atom coordinating with the metal cation

carmm.analyse.bonds.compare_structures(atoms1, atoms2, label=None)

Comparison of two input structures to identify equivalent atoms but incorrect index ordering

Parameters:

atoms1: Atoms object or trajectory of individual atoms

An atoms object

atoms2: Atoms object or trajectory of individual atoms

Another atoms object

label: String of elemental character

Only necessary to limit search to specific atomic species

carmm.analyse.bonds.comparing_bonds_lengths(atoms1, atoms2)

description: this function allows to compare difference in bonds lengths between two structures, :type atoms1: :param atoms1: Atoms object or trajectory of individual atoms :type atoms2: :param atoms2: a second atom object

carmm.analyse.bonds.get_indices_of_elements(list_of_symbols, symbol)

Check an atoms object for occurences of symbols given and return indices

Parameters:

list_of_symbols: List of strings

Symbols from an atoms object in structural order

symbol:

Symbol to search for

carmm.analyse.bonds.get_sorted_distances(model, atoms_to_include=None)

Returns a sorted list of atomic distances in the model, selecting only those atoms of interest Current usage is for molecules and periodic solids (through mic).

Parameters:

model: Atoms objects

The model from which the RDF is to be plotted

atoms_to_include: Integer or List of Integers

Atoms that you want included in the RDF

Returns:

individual_lengths: List of floats

An sorted list of all lengths of bonds between all atoms in the model

carmm.analyse.bonds.print_bond_table_header()
carmm.analyse.bonds.search_abnormal_bonds(model, verbose=True)

Check all bond lengths in the model for abnormally short ones.

Parameters: model: Atoms object or string. If string it will read a file

in the same folder, e.g. “name.traj”

carmm.analyse.colormaps module

carmm.analyse.colormaps.color_bar(width, height, bottom, vmin, vmax, orientation, label, cmapcolour, resolution)

Basic Colour Bar figsize= y axis how tallbottom = <0.8 - size of bar (cannot be bigger than top)vmin/vmax = x axis valuesorientation = horizontal,verticallabel = units

cmapcolour = [(‘Perceptually Uniform Sequential’, [

‘viridis’, ‘plasma’, ‘inferno’, ‘magma’, ‘cividis’]),

(‘Sequential’, [

‘Greys’, ‘Purples’, ‘Blues’, ‘Greens’, ‘Oranges’, ‘Reds’, ‘YlOrBr’, ‘YlOrRd’, ‘OrRd’, ‘PuRd’, ‘RdPu’, ‘BuPu’, ‘GnBu’, ‘PuBu’, ‘YlGnBu’, ‘PuBuGn’, ‘BuGn’, ‘YlGn’]),

(‘Sequential (2)’, [

‘binary’, ‘gist_yarg’, ‘gist_gray’, ‘gray’, ‘bone’, ‘pink’, ‘spring’, ‘summer’, ‘autumn’, ‘winter’, ‘cool’, ‘Wistia’, ‘hot’, ‘afmhot’, ‘gist_heat’, ‘copper’]),

(‘Diverging’, [

‘PiYG’, ‘PRGn’, ‘BrBG’, ‘PuOr’, ‘RdGy’, ‘RdBu’, ‘RdYlBu’, ‘RdYlGn’, ‘Spectral’, ‘coolwarm’, ‘bwr’, ‘seismic’]),

(‘Cyclic’, [‘twilight’, ‘twilight_shifted’, ‘hsv’]), (‘Qualitative’, [

‘Pastel1’, ‘Pastel2’, ‘Paired’, ‘Accent’, ‘Dark2’, ‘Set1’, ‘Set2’, ‘Set3’, ‘tab10’, ‘tab20’, ‘tab20b’, ‘tab20c’]),

(‘Miscellaneous’, [

‘flag’, ‘prism’, ‘ocean’, ‘gist_earth’, ‘terrain’, ‘gist_stern’, ‘gnuplot’, ‘gnuplot2’, ‘CMRmap’, ‘cubehelix’, ‘brg’, ‘gist_rainbow’, ‘rainbow’, ‘jet’, ‘turbo’, ‘nipy_spectral’, ‘gist_ncar’])]

resolution = the level of segmentation on the map

carmm.analyse.counterpoise_onepot module

carmm.analyse.counterpoise_onepot.calculate_energy_ghost_compatible(calc, atoms=None, properties=['energy'], system_changes=['positions', 'numbers', 'cell', 'pbc', 'initial_charges', 'initial_magmoms'], ghosts=None, dry_run=False)

This is a modified version of ase.calculators.calculator.FileIOCalculator.calculate to make ghost atoms work Do the calculation and read the results.

This is a workaround. The same could be done easily if we were using the same version of ASE on Gitlab. The Aims calculator were rewritten where ghosts can be specified while constructing the calculator (not available in current release)

Parameters:

  • calc – fhi_aims calculator constructed by ASE

  • atoms – ASE atoms object

  • properties – list of str. properties to be calculated, default is energy. See original function

  • system_changes – list of str. See original function.

  • ghosts – bool list. Ghost is Ture and Atom is False. The length is the same as atoms.

  • dry_run – flag for CI-test.

carmm.analyse.counterpoise_onepot.check_and_convert_id(complex_struc, a_id, b_id)

This function checks if a_id and b_id are supplied correctly (lists of indices or lists of strings), and convert symbols to indices. :type complex_struc: :param complex_struc: see counterpoise_calc :type a_id: :param a_id: see counterpoise_calc :type b_id: :param b_id: see counterpoise_calc

Returns:

a_id, b_id. Two lists of indices for A and B, respectively.

carmm.analyse.counterpoise_onepot.counterpoise_calc(complex_struc, a_id, b_id, fhi_calc=None, a_name=None, b_name=None, verbose=False, dry_run=False)

This function does counterpoise (CP) correction for basis set super position error (BSSE) in one go, assuming a binding complex AB.

CP correction = A_only + B_only - A_plus_ghost - B_plus_ghost A_only has A in the geometry of the binding complex with its own basis A_plus_ghost has A in the same geometry as in the complex with B replaced by ghost atoms This value should be positive by this definition and should be added to the energy change of interest, such as adsorption energy.

Some references: 1. Szalewicz, K., & Jeziorski, B. (1998). The Journal of Chemical Physics, 109(3), 1198–1200. https://doi.org/10.1063/1.476667

2. Galano, A., & Alvarez-Idaboy, J. R. (2006). Journal of Computational Chemistry, 27(11), 1203–1210. https://doi.org/10.1002/JCC.20438 (See the second paragraph in the introduction for a good explanation of why BSSE arises)

Parameters:

  • complex_struc – ASE Atoms This is the Atoms object which stores the optimized structure of the binding complex

  • a_id – list of atom symbols or atom indices for species A

  • b_id – list of atom symbols or atom indices for species B Please use both symbols or both indices for a_id and b_id.

  • fhi_calc – ase.calculators.aims.Aims object A FHI_aims calculator constructed with ase Aims

  • a_name – string. optional.

  • b_name – string. optional. The name of the two species for your counterpoise correction, which has symbol (or index) a_id and b_id.

  • verbose – Flag for printing output.

  • dry_run – bool Flag for test run (CI-test)

Returns: float. counterpoise correction value for basis set superposition error

carmm.analyse.counterpoise_onepot.gather_info_for_write_input(complex_struc, a_id, b_id)

This function collects info for writing input files for A_only, A_plus_ghost, B_only, and B_plus_ghost The geometry.in files are written with ase.io.aims.write_aims. For species with ghost atoms, write_aims needs a bool list for the keyword argument “ghosts”, where a ghost atom is True and a normal atom is False. :type complex_struc: :param complex_struc: The complex. See counterpoise_calc. :type a_id: :param a_id: indices for A :type b_id: :param b_id: indices for B

Returns:

A list of four bool lists (Ghost atom is True; Real atom is False) A list of atoms objects Both in the order of A_only, A_plus_ghost, B_only, B_plus_ghost.

carmm.analyse.counterpoise_onepot.get_energy_dryrun(dir, outputname)

Parse the energy from the aims.out file

carmm.analyse.distribution_functions module

carmm.analyse.distribution_functions.average_distribution_function(trajectory, samples=10)

Plots the average distribution function of the last N steps of an MD trajectory TODO: -This is distance based - can we adapt it to also allow radial?

  • Seems like constraints are removed below but this causes error

when no constraints are present in the system. Need to make this a condition.

Parameters:

trajectory: List of Atoms objects

The pathway from which the ensemble RDF is to be plotted

samples: Integer

The number of samples to include in the ensemble, starting from the final image of the trajectory.

Returns:

all_data: List of floats

A list containing _all_ of the distances encountered in the sampled trajectories

snapshots: List of list of floats

A list containing the list of floats for distances measured in each specific snapshot analysed

carmm.analyse.distribution_functions.element_radial_distribution_function(model, radius, element, position=None, verbose=False)

Returns a plot of the distribution of the distance between atoms of a specific element up to given radius Plot is currently a frequency vs distance. Current usage is for periodic solids

Parameters:

model: Atoms objects

The model from which the RDF is to be plotted

radius: float

The distance around the atom of interest to plot the RDF

position: integer

The atom index of interest (i.e. centre of RDF). Default is 0

Returns:

distances: List of floats

An sorted list of all lengths of bonds between the central atom and others in the desired radius

carmm.analyse.distribution_functions.plot_distribution_function(data, bins=None, bin_sampling=0.1, title=None, density=False, **kwargs)

Generic plotter

Parameters:

data: List of floats

The values to be plotted on the histogram

bins: Int

Number of separate bins on the histogram

bin_sampling: Float

The separation between bin boundaries

title: String

Name to place at the top of the plot

**kwargs: Additional arguments

These are passed straight through to the plotting function

TODO: We should edit the axes object, not the plot itself (see graphs.py, specifically mulliken related)

carmm.analyse.distribution_functions.radial_distribution_function(model, radius, position, verbose=False)

Returns a plot of the distribution of the distance between atoms up to given radius Plot is currently a frequency vs distance. Current usage is for periodic solids

Parameters:

model: Atoms objects

The model from which the RDF is to be plotted

radius: float

The distance around the atom of interest to plot the RDF

position: integer

The atom index of interest (i.e. centre of RDF)

Returns:

distances: List of floats

An sorted list of all lengths of bonds between the central atom and others in the desired radius

carmm.analyse.distribution_functions.radius_of_gyration(model)

creates a radius of gyration for input file of a molecule. A radius of gyration is a measurement of the distribution of atoms in a molecular structure with respect to it’s centre of mass:

radius_of_gyration^2 = SUM(mass_atom(atom_position - centre_mass_position)) / mass_of_molecule

TODO: - further tidying up

carmm.analyse.forces module

carmm.analyse.forces.is_converged(atoms, fmax=0.01)

This function takes an atoms object and a force convergence criterion and returns True if stored forces are below fmax convergence criterion or False if forces are above fmax or there is no stored calculator. Useful for multiple geometry optimisations and automated restarts from .traj files to avoid unnecessary calculations.

atoms: Atoms object fmax: float

Convergence criterion in eV/Angstrom, usually 0.01

carmm.analyse.graphs module

carmm.analyse.graphs.get_graph_colour(choice=0)

Return some nice graph colours

Parameters:

choice: Integer

The colour choice to return from the colours array

carmm.analyse.graphs.get_graph_linetype(choice=0)

Return linetypes that match the matplotlib options

Parameters:

choice: Integer

The linetype choice to return from the array of options

carmm.analyse.graphs.load_xyz_data_from_csv(fname)

Read in x, y and z-axis data from a CSV file for plotting (3D)

Parameters:

fname: String

filename for the CSV that is to be read in

carmm.analyse.graphs.plot_energy_profile(data, x_labels, **kwargs)

This function is used for plotting solid+dashed line style reaction energy profiles, which often require manual tweaking using other software.

Parameters:

  • data – dict A dictionary of key-value pairs, where the keys are used as the title of the data series, and the values are lists of floats to be plotted on the y-axis.

  • x_labels – list A list of strings containing x-axis labels - intermediates, reaction steps etc.

  • **kwargs – dict %% These variables should be optional in the function call. Then the defaults are clear. This is passthrough for all other variables. The following are pulled from if they exist (otherwise defaults are used): font_size; figsize; colours; linestyles; linestyle; x_labels_rotation; x_axis_title; y_axis_title; legend_xy_offset

Returns:

matplotlib.pyplot

carmm.analyse.graphs.set_graph_axes_heatmap(plt, x, y)

Construct a suitable axes for displating a 3D heatmap

Parameters:

plt: Matplotlib structure

Incoming plot containing data and for which the axes need adjustment

x: List of Floats

X-axis data

y: List of Floats

Y-axis data

carmm.analyse.graphs.set_graph_axes_mulliken(axis, x, y, homo, xlabel='$\\epsilon$ (eV)', ylabel='Density of States (1/eV)')

Function to automate setting up the plot axes for a DOS

Parameters:

plt: Matplotlib plot object or Axes

This has data predrawn from the x- and y-axis data also provided

x: list of Floats

The x-axis data object (i.e. range of x-axis values)

y: list of Floats

The y-axis data objects, corresponding to the plotted data

homo: Float

Reference level for the HOMO, which is the middle point of the x-axis

xlabel: String

Label for x-axis

ylabel: String

Label for y-axis

carmm.analyse.hirshfeld module

carmm.analyse.hirshfeld.extract_hirshfeld(fname, natoms, data, write=True, outname='hirshfeld.txt')
Parameters:

  • fname – Input file name, usually aims.out. str

  • natoms – number of atoms to extract charge from. int

  • data – type of output requested. str Can be ‘charge’, ‘volume’, ‘volume f’, ‘dipole vector’, ‘dipole moment’ or ‘second’

  • write – bool of whether to write the hirshfeld data to a new file called hirshfeld.txt

Returns: hirsh. List of requested data

carmm.analyse.hirshfeld.get_hirshfeld_line(text)
carmm.analyse.hirshfeld.read_hirshfeld(fname, identifier)
Parameters:

  • fname – Input filename. str

  • identifier – regex to pull data from file. str

Returns: label. list of data

carmm.analyse.hirshfeld.vmd_out(array, fname='vmd_chrgs.txt')
carmm.analyse.hirshfeld.write_hirshfeld(text, natoms, start, outname)

carmm.analyse.images module

carmm.analyse.images.write_to_povray()

Saves the incoming atoms object to a povray file

TODO: As the povray file generation and rendering have been reworked in recent ASE version this function is no longer necessary. A jupyter notebook would be more suitable to explain write_pov().render() syntax.

carmm.analyse.molecules module

carmm.analyse.molecules.calculate_formula(atoms, mult=1)

What it does Determines the chemical formula for each molecule in the system.

Parameters: atoms: Atoms object

Input structure from which to calculate molecular information.

Returns: molecule_formula: List of strings.

TO DO: Molecules such as CO2 are returned as C1O2. Preferable to make consistent with Hill’s notation (CO2).

carmm.analyse.molecules.calculate_molecules(atoms, mult=1, print_output=False)

Returns information on the molecules in the system. Needs refinement!

Parameters: atoms: Atoms object

Input structure from which to calculate molecular information

Mult: a multiplier for the cutoffs

Set to 1 as default, but can be adjusted depending on application

print_output: Boolean

Whether to print any information whilst working out molecules

Returns: molecules: List of list of integers

Indices of atoms involved in each molecule can view individual molecules via atoms[molecules[0]] ect

carmm.analyse.mulliken module

class carmm.analyse.mulliken.Atom(nspin, nkpts, nstates)

Bases: object

Description # TODO: Needs changing the name of the class as it might interfere with the ‘Atom’ class of ASE Class to represent data for a each atom. Data includes the number of spin-channel, k-points and eigenstates for each atom

class carmm.analyse.mulliken.Kpt(nstates)

Bases: object

Description Class to represent data for a particular k-point. Data includes the number eigenstates for a given k-point, spin channel and atom.

class carmm.analyse.mulliken.MullikenData(natoms, nspin, nkpts, nstates)

Bases: object

Description Class representing the Mulliken data and store information pertinent to eigenvalues, occupation numbers, and angular momentas for each atom, spin-channel, k-point and eigenstate

Parameters:

  • natoms – Integer Number of atoms in the Mulliken data object

  • nspin – Integer Number of spin channels in the data object

  • nkpts – Integer Number of k-points in the model

  • nstates – Integer Number of electronic states to be stored in the data object

get_all_plot_data()

Description Obtains the arrays of data (x –> energy and y –> density) for plotting the total density of states (dos). Basically uses the get_plot_data() function with angular=’all’.

Returns:

1D array of x (energy) and 2D array of y (density). The density data is 2D to account for both spin-up and spin-down channels

get_data_integrity()

Description

get_graph_xlabel()

Return label for the x-axis depending on whether the model is periodic or not

get_homo()

Description

get_natoms()

Description Computes the number of atoms

get_nkpts()

Description Computes the number of k-points

get_nspin()

Description Computes the number of spin channels. For spin paired the value is 1 whereas for spin polarised the value is 2

get_nstates()

Description Computes the number of eigenstates

get_orbital_plot_data(orbital, atoms=None, spin=None, kpts=None)

Description Obtains the arrays of data (x –> energy and y –> density) for plotting the individual density of states (dos) for a desired orbital Basically uses the get_plot_data() function with orbital (‘s’,’p’,’d’,’f’) of user’s choice.

Returns:

1D array of x (energy) and 2D array of y (density). The density data is 2D to account for both spin-up and spin-down channels

Parameters:

orbital: String

Choices are ‘s’,’p’,’d’,’f’,’g’ for obtaining the corresponding plots for a desired orbital.

atoms: List of Integers

Indices of atoms that are to be included in the data acquisition

spin: List of Integers

Indices of spins that are to be included - either [0] or [0,1] for none or collinear

kpts: List of Integers

Indices of kpts to be included

get_plot_data(atom_ind, spin, kpts, angular, xmin=-20, xmax=20, npoints=1000, variance=0.02)

Description Obtains the arrays of data (x –> energy and y –> density) for plotting the density of states (dos). Can obtain data for total and individual contribution from the ‘s’, ‘p’, ‘d’, and ‘f’ orbitals using the ‘angular’ keyword.

Parameters:

atom_ind: List of Integers

Indices of atoms that are to be included in the data acquisition

spin: List of Integers

Indices of spins that are to be included - either [0] or [0,1] for none or collinear

kpts: List of Integers

Indices of kpts to be included

angular: String

Letters for angular momenta to be returned (any combination from spdfg) or ‘all’ for everything

xmin: Float

Minimum on the x-axis for the energy range

xmax: Float

Maximum on the x-axis for the energy range

npoints: Integer

Number of ‘bins’ on the x-axis when expanding Gaussians on the eigenvalues

variance: Float

Variance for the Gaussian when added to each eigenfunction

Returns:

1D array of x (energy) and 2D array of y (density). The density data is 2D to account for both spin-up and spin-down channels

class carmm.analyse.mulliken.Spin(nkpts, nstates)

Bases: object

Description Class to represent data for a spin channel. Data includes the number of k-points and eigenstates for a given spin channel and atom.

carmm.analyse.mulliken.extract_mulliken_charge(fn, natoms)

Function to extract and return the Mulliken charges from an FHI-aims output. A list of relative charges is returned, with +q meaning charge depletion and -q meaning charge accummulation

Parameters:

fn: string

Filename from which the Mulliken data should be extracted

natoms: int

Number of atoms in the calculation

Returns:

List of charges.

carmm.analyse.mulliken.extract_mulliken_spin(fn, natoms)

Function to extract and return the Mulliken spin from an FHI-aims output. A list of spin moments on is returned. The value at each index corresponds to the spin moment of each the atom at that particular index

Parameters:

fn: string

Filename from which the Mulliken data should be extracted

natoms: int

Number of atoms in the calculation

Returns:

List of spin moments.

carmm.analyse.mulliken.parse_mulliken_file(fname)

Description Extracting data from a Mulliken.out file. Iterates through each atom, spin-channel, k-points and eigenstates to extract the values of eigenvalues (energies), occupancies (occupation number), total angular momenta.

Parameters:

fname: String

Filename of the Mulliken.out file we are reading in and parsing.

Returns:

A MullikenData object containing the values of eigenvalues (energies), occupancies (occupation number), total angular momenta for each atom, spin-channel, k-point and eigenstate.

carmm.analyse.mulliken.write_dos_to_csv(fname, x, y)

Description Function to write the density of states (dos) data to a csv file. In case of spin-unpolarised calculations, there will be only two columns in the csv file corresponding to the x and y values whereas in case of a spin-polarised calculation, we will have 3 columns viz x, y(spin-up) and y(spin-down).

Parameters: fname: String

Filename to save the CSV data in too.

x: 1D array of floats

Array of x-axis values

y: 2D array of floats

2D array of y-axis values, possibly spin-paired or spin-polarised

carmm.analyse.neighbours module

carmm.analyse.neighbours.neighbour_cutout_sphere(atoms, centre, distance_cutoff=5.0)

Returns a spherical cutout of a structure TODO: This doesn’t work with periodic boundary conditions. TODO:Could probably integrate this with the neighbor function bellow

Parameters:

atoms: Atoms object

Input structure to cutout from

centre: Integer

Index of central atom in cutout

distance_cutoff: Float

Distance which inside atoms are counted as neighbours

carmm.analyse.neighbours.neighbours(atoms, centre, shell, cutoff=None, verbose=False)

Returns a list of indices of atomic neighbors from a central atom

Parameters: atoms : Atoms object

Input structure to count neighbours

centrelist of integers

Indices of atom(s) to start counting from

shellInteger

Size of the nearest neighbour shell, 1st neighbours, 2nd neighbours ….

cutoff: list of floats or None

Bond length cutoff distance in Angstrom can be set for each atom individually The list must contain exactly len(atoms) floats. If None, natural_cutoffs are used by default.

verbose: boolean

If True, information about the cutoffs and selected neighbors is printed

Returns:

List of all atoms within specified neighbour distances List of lists containing indices of atoms that make 0th, 1st (…) shell

carmm.analyse.neighbours.surface_coordination(atoms, cutoff=None, verbose=True)

This function allows to extract the following data from the supplied Atoms object in the form of a dictionary: Per atom: - number of neighbouring atoms of specific chemical symbol

Per atomic layer (based on tag): - average coordination number for all M-M combinations of all chemical species,

e.g. for CuAu alloy slab an average number of Cu-Cu, Cu-Au, Au-Cu and Au-Au

bonds with surrounding atoms i.e. Cu-Cu_neighbors_per_layer etc.

  • concentration of atoms per layer

Parameters:

  • atoms – Atoms object Surface slab containing tagged atomic layers e.g. using carmm.build.neb.symmetry.sort_z

  • cutoff – list of floats or None Bond length cutoff distance in Angstrom can be set for each atom individually The list must contain exactly len(atoms) floats. If None, natural_cutoffs are used by default.

  • verbose – boolean If True, analysed data that is contained in the dictionary will be printed as a table TODO: make table neater

Returns:

dict_CN, dict_surf_CN

TODO: proper description of dictionary structure, writing csv files

carmm.analyse.pickle_dos module

carmm.analyse.pickle_dos.read_dos_from_old_pickle(filename)

Method to read in DOS data from pickle files (GPAW, outdated)

Parameters:

filename: String

Name of the pickle file we are reading

carmm.analyse.planes module

carmm.analyse.planes.distance_between_centers_of_mass(A_mol, B_mol)

TODO: @Jack Warren :type A_mol: :param A_mol: molecule A :type B_mol: :param B_mol: molecule B :return: distance between 2 centers of mass

carmm.analyse.planes.establish_planes(Atom1, Atom2, Atom3)

Using 3 points to calculate 3 vectors and establish a plane…

@Jack Warren: Please complete :type Atom1: :param Atom1: (x,y,z coordinates of Atom1) :type Atom2: :param Atom2: :type Atom3: :param Atom3:

#TODO: This should just return the plot, not show it. :return: Graphical Representation of planes

carmm.analyse.planes.get_close_contacts(A_mol, B_mol)

Uses molecules.py to separate fn into molecules then measures the shortest distances between. Indented for Periodic systems

Parameters: A_mol: Atoms object created by molecules the one you want to measure from B_mol: Same as A_mol, however its the molecule you’re measuring to

Returns: The closest contact for each atom on A_mol to their closest contact on B_mol

Still very much a work in progress so go easy on it

carmm.analyse.planes.get_interplane_distances(atoms)

A function that combines the molecules script and get_lowest distances to separate molecules out in a system and measure the distances inbetween.

Returns: interplane distance

carmm.analyse.planes.plane_of_best_fit(model)

Using the xyz coordinates of a molecule or atoms object to calculate the plane of best fit and plot it for visualizing model: Atoms object

  • The atoms object that has been previously loaded (note the IO is not done here)

# TODO: @Jack Warren what are these variables? xs = all x coordinates ys = all y zs = all z

Returns - plt of the plane and the atoms as well as the equation of plane and the errors from atoms that vary from the plane

carmm.analyse.surface_area module

carmm.analyse.surface_area.surface_area(atoms)

A function to calculate the surface of a slab (based on cell vectors)

Parameters:

atoms: ASE Atoms object holding slab information

Returns: Surface area, in same units as cell vector lengths (^2)

carmm.analyse.vibrations module

Module contents