xdatbus

Submodules

Attributes

`BPY_AVAILABLE`
`PDB_AVAILABLE`
`MN_AVAILABLE`
`YAML_AVAILABLE`

Functions

`update_folder`(folder)	Delete the folder and create a new one.
`remove_file`(file_path)	Delete the file.
`filter_files`(files, pattern)
`xdc_aggregate`([xdc_dir, output_dir, del_temp, ...])	Aggregate XDATCAR files from an AIMD simulation.
`main`()
`unwrap_pbc_dis`(coord_1, coord_2, box_length)	Unwrap the distance between two coordinates.
`xdc_unwrap`([xdc_path, output_path, show_progress])	Unwrap the coordinates in the XDATCAR file (to .xyz).
`main`()
`unwrap_pbc_dis`(coord_1, coord_2, box_length)	Unwrap the distance between two coordinates.
`xyz_unwrap`(xyz_path, lattice)	Unwrap the coordinates in the xyz file. The unwrapped coordinates will be written to a new xyz file.
`filter_files`(files, pattern)
`thermal_report`([osz_dir, output_path, show_progress])	Generate a thermal report from the OSZICAR files.
`main`()
`filter_files`(files, pattern)
`xml2xyz`([xml_dir, output_path, train_ratio, ...])	Convert the vasprun.xml files to extended xyz files.
`main`()
`sum_hills`(plumed_hills, plumed_outfile, plumed_min, ...)
`main`()
`com_drift`(xyz_path[, frame_start, frame_end, ...])	Calculate the center of mass (COM) drift velocity for a xyz file.
`com_contcar`(poscar_path, contcar_path[, del_inter])	Correct the CONTCAR file by adding the COM drift to the coordinates of the CONTCAR file.
`gauss_pot_1d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`gauss_pot_2d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`gauss_pot_3d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`fes_1d`(hillspot_path, hills_count, cv_range[, resolution])	Calculate the 1D free energy profile from a HILLSPOT file.
`fes_2d`(hillspot_path, hills_count, cv_1_range, cv_2_range)	Calculate the 2D free energy profile from a HILLSPOT file.
`fes_3d`(hillspot_path, hills_count, cv_1_range, ...[, ...])	Calculate the 2D free energy profile from a HILLSPOT file.
`hillspot2hills`(hillspot_dir, hills_dir, cv[, ...])	Convert HILLSPOT file to HILLS file
`report_loader`(aimd_path[, load_pre_report, ...])	Initialize a trajectory writer instance for filename.
`xdc2xtc`(xdc_path)	Convert a VASP XDATCAR file to an XTC trajectory file.
`reweight`(fes, cv, nv, kb, t, grid_min, grid_max, grid_num)	Reweight a metadynamics simulation to the unbiased ensemble using histogram reweighting.
`pmf_321`(fes3d, axis1, axis2)	project 3d free energy surface to 1d
`neb_2d`(fes, minima_1, minima_2, n_images, n_steps, ...)
`local_minima`(data[, size])
`read_lat_vec`(xdatcar_dir)	Read the lattice vectors from the first image of the XDATCAR file.
`unwrap_pbc_dis`(coord_1, coord_2, box_length)	Unwrap the distance between two coordinates.
`update_folder`(folder)	Delete the folder and create a new one.
`remove_file`(file_path)	Delete the file.
`skip_comments`(file)
`filter_files`(files, pattern)
`gauss_pot_1d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`gauss_pot_2d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`gauss_pot_3d`(→ numpy.ndarray)	Calculate the Gaussian potential energy.
`realize_instances`(obj, bond_radius)	Realize instances of the given object. This function requires bpy.
`remove_nodes`(obj, node_names)	Remove nodes with given names from the object's node tree.
`get_template_node`(node_name, nodes)	Get a node from a template blend file.
`set_color4element`(obj, atomic_number, color, ...[, ...])	Add a custom node and connect it to the specified input of the target node.
`apply_yaml`(obj, yaml_path)	Set the color of the given object. This function requires bpy and molecularnodes.
`clear_scene`([mesh, lights, geometry_nodes])	Clear the scene of all objects. This function requires bpy.
`render_image`([engine, x, y, output_path])	Render an image. This function requires bpy.
`apply_modifiers_to_mesh`(obj)	Apply modifiers to the given object. This function requires bpy.
`yaml_gen`(pdb_file_path)	This function generates a YAML file for the elements in the PDB file, with a common bond_radius.
`yaml_loader`(yaml_path)	This function loads a YAML file and returns element data and bond radius.
`main`()

Package Contents

xdatbus.update_folder(folder)

Delete the folder and create a new one.

folderstr
The path of the folder

xdatbus.remove_file(file_path)

Delete the file.

file_pathstr
The path of the file

xdatbus.filter_files(files, pattern)

xdatbus.xdc_aggregate(xdc_dir='./', output_dir='./', del_temp=True, show_progress=False)

Aggregate XDATCAR files from an AIMD simulation.

xdc_dirstr (optional)
Input path of the AIMD simulation, which contains the XDATCAR files

output_dirstr (optional)
Output path of the XDATBUS file

del_tempbool (optional)
If False, the intermediate folders will be deleted

show_progressbool (optional)
Whether to show the progress bar

xdatbus.main()

xdatbus.unwrap_pbc_dis(coord_1, coord_2, box_length)

Unwrap the distance between two coordinates.

coord_1ndarray
The first coordinate

coord_2ndarray
The second coordinate

box_length :
The length of the box

float
The unwrapped distance between the two coordinates

xdatbus.xdc_unwrap(xdc_path='./XDATBUS', output_path='./XDATBUS_unwrap.xyz', show_progress=False)

Unwrap the coordinates in the XDATCAR file (to .xyz).

xdc_pathstr
Input path of the XDATCAR file

output_pathstr
Output path of the xyz file

show_progressbool (optional)
Show the progress bar or not

xdatbus.main()

xdatbus.unwrap_pbc_dis(coord_1, coord_2, box_length)

Unwrap the distance between two coordinates.

coord_1ndarray
The first coordinate

coord_2ndarray
The second coordinate

box_length :
The length of the box

float
The unwrapped distance between the two coordinates

xdatbus.xyz_unwrap(xyz_path, lattice)

Unwrap the coordinates in the xyz file. The unwrapped coordinates will be written to a new xyz file.

xyz_pathstr
Input path of the xyz file

latticelist
Lattice vectors of the system

xdatbus.filter_files(files, pattern)

xdatbus.thermal_report(osz_dir='./', output_path='./', show_progress=False)

Generate a thermal report from the OSZICAR files.

osz_dirstr
Input path of the OSZICAR files

output_pathstr
Output path of the thermal report

show_progressbool
Whether to show the progress bar

xdatbus.main()

xdatbus.filter_files(files, pattern)

xdatbus.xml2xyz(xml_dir='./', output_path='./', train_ratio=1.0, free_energy=True, show_progress=False)

Convert the vasprun.xml files to extended xyz files.

xml_dirstr
Input path of the vasprun.xml files

output_pathstr
Output path of the extended xyz files

train_ratiofloat (optional)
The ratio of training set

free_energybool (optional)
Whether to keep the free energy from the xml files

show_progressbool (optional)
Show the progress bar or not

xdatbus.main()

xdatbus.sum_hills(plumed_hills, plumed_outfile, plumed_min, plumed_max, plumed_bin, plumed_eachstep)

xdatbus.main()

xdatbus.com_drift(xyz_path, frame_start=0, frame_end=None, save_csv=True, timestep=1)

Calculate the center of mass (COM) drift velocity for a xyz file.

Parameters

xyz_pathstr: Path to the XYZ file.
frame_startint: The first frame to consider.
frame_endint: The last frame to consider. If None, considers all frames.
save_csvbool: Whether to save the COM to a csv file.
timestepint: The time difference between each frame, in appropriate time units. Default is 1.

Returns

np.ndarray: The COM drift velocity, represented as a 3-element numpy array.

xdatbus.com_contcar(poscar_path, contcar_path, del_inter=False)

Correct the CONTCAR file by adding the COM drift to the coordinates of the CONTCAR file. The COM drift is calculated by fcom01_drift().

Parameters

poscar_pathstr: Path to the POSCAR path.
contcar_pathstr: Path to the CONTCAR file.
del_interbool: Delete the intermediate files created by this function.

xdatbus.gauss_pot_1d(x: numpy.ndarray, x0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of positions at which to evaluate the potential. - x0 (float): The position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position x.

xdatbus.gauss_pot_2d(x: numpy.ndarray, y: numpy.ndarray, x0: float, y0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of x positions at which to evaluate the potential. - y (np.ndarray): Array of y positions at which to evaluate the potential. - x0 (float): The x position of the potential minimum. - y0 (float): The y position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position (x, y).

xdatbus.gauss_pot_3d(x: numpy.ndarray, y: numpy.ndarray, z: numpy.ndarray, x0: float, y0: float, z0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of x positions at which to evaluate the potential. - y (np.ndarray): Array of y positions at which to evaluate the potential. - z (np.ndarray): Array of z positions at which to evaluate the potential. - x0 (float): The x position of the potential minimum. - y0 (float): The y position of the potential minimum. - z0 (float): The z position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position (x, y, z).

xdatbus.fes_1d(hillspot_path, hills_count, cv_range, resolution=100)

Calculate the 1D free energy profile from a HILLSPOT file.

hillspot_pathstr
The path of the HILLSPOT file

hills_countint
The number of hills to be read

cv_rangelist
The range of the collective variable

resolutionint (optional)
The resolution of the free energy profile

xdatbus.fes_2d(hillspot_path, hills_count, cv_1_range, cv_2_range, resolution=100)

Calculate the 2D free energy profile from a HILLSPOT file.

hillspot_pathstr
The path of the HILLSPOT file

hills_countint
The number of hills to be read

cv_1_rangelist
The range of the first collective variable

cv_2_rangelist
The range of the second collective variable

resolutionint (optional)
The resolution of the free energy profile

xdatbus.fes_3d(hillspot_path, hills_count, cv_1_range, cv_2_range, cv_3_range, resolution=100)

Calculate the 2D free energy profile from a HILLSPOT file.

hillspot_pathstr
The path of the HILLSPOT file

hills_countint
The number of hills to be read

cv_1_rangelist
The range of the first collective variable

cv_2_rangelist
The range of the second collective variable

cv_3_rangelist
The range of the third collective variable

resolutionint (optional)
The resolution of the free energy profile

xdatbus.hillspot2hills(hillspot_dir, hills_dir, cv, height_conversion=1, sigma_conversion=1, del_inter=False)

Convert HILLSPOT file to HILLS file

hillspot_dirstr: Path to HILLSPOT file
hills_dirstr: Path to the directory where the HILLS file will be created
cvstr or list: Name of the collective variable(s)
height_conversionfloat(optional): Conversion factor to convert the unit of the height from eV to kJ/mol
sigma_conversionfloat(optional): Conversion factor to convert the unit of the sigma based on the lattice in Angstrom
del_interbool(optional): Delete the intermediate files created by this function.

xdatbus.report_loader(aimd_path, load_pre_report=True, load_last_report=False, delete_intermediate_folders=True)

Initialize a trajectory writer instance for filename.

aimd_pathstr
Output filename of the trajectory; the extension determines the format.

load_pre_reportbool (optional)
If True, the trajectory will contain the previous frames (before the current run)

load_last_reportbool (optional)
If True, the trajectory will contain the last frame

delete_intermediate_foldersbool (optional)
If True, the intermediate folders will be deleted

xdatbus.xdc2xtc(xdc_path)

Convert a VASP XDATCAR file to an XTC trajectory file.

Parameters

xdc_pathstr: Path to the XDATCAR file

xdatbus.reweight(fes, cv, nv, kb, t, grid_min, grid_max, grid_num)

Reweight a metadynamics simulation to the unbiased ensemble using histogram reweighting.

In many cases you might decide which variable should be analyzed after having performed a metadynamics simulation. For example, you might want to calculate the free energy as a function of CVs other than those biased during the metadynamics simulation. At variance with standard MD simulations, you cannot simply calculate histograms of other variables directly from your metadynamics trajectory, because the presence of the metadynamics bias potential has altered the statistical weight of each frame. To remove the effect of this bias and thus be able to calculate properties of the system in the unbiased ensemble, you must reweight (unbias) your simulation.

fesnp.ndarray
The free energy surface calculated from the metadynamics simulation.

cvnp.ndarray
The collective variable used in the metadynamics simulation.

nvnp.ndarray
The new collective variable for which the potential of mean force will be calculated.

kbfloat
The Boltzmann constant.

tfloat
The temperature of the simulation.

grid_minfloat
The minimum value of the collective variable.

grid_maxfloat
The maximum value of the collective variable.

grid_numint
The number of bins in the histogram.

Returns

np.ndarray: The unbiased free energy surface.

xdatbus.pmf_321(fes3d, axis1, axis2)

project 3d free energy surface to 1d

Parameters

fes3dnp.ndarray: The 3d free energy surface.
axis1int: The axis to be projected.
axis2int: The axis to be projected.

Returns

np.ndarray: The 2d free energy surface.

xdatbus.neb_2d(fes, minima_1, minima_2, n_images, n_steps, spring_constant)

xdatbus.local_minima(data, size=3)

xdatbus.read_lat_vec(xdatcar_dir): Read the lattice vectors from the first image of the XDATCAR file.

xdatbus.unwrap_pbc_dis(coord_1, coord_2, box_length)

Unwrap the distance between two coordinates.

coord_1ndarray
The first coordinate

coord_2ndarray
The second coordinate

box_length :
The length of the box

float
The unwrapped distance between the two coordinates

xdatbus.update_folder(folder)

Delete the folder and create a new one.

folderstr
The path of the folder

xdatbus.remove_file(file_path)

Delete the file.

file_pathstr
The path of the file

xdatbus.skip_comments(file)

xdatbus.filter_files(files, pattern)

xdatbus.gauss_pot_1d(x: numpy.ndarray, x0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of positions at which to evaluate the potential. - x0 (float): The position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position x.

xdatbus.gauss_pot_2d(x: numpy.ndarray, y: numpy.ndarray, x0: float, y0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of x positions at which to evaluate the potential. - y (np.ndarray): Array of y positions at which to evaluate the potential. - x0 (float): The x position of the potential minimum. - y0 (float): The y position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position (x, y).

xdatbus.gauss_pot_3d(x: numpy.ndarray, y: numpy.ndarray, z: numpy.ndarray, x0: float, y0: float, z0: float, height: float, width: float) → numpy.ndarray

Calculate the Gaussian potential energy.

Parameters: - x (np.ndarray): Array of x positions at which to evaluate the potential. - y (np.ndarray): Array of y positions at which to evaluate the potential. - z (np.ndarray): Array of z positions at which to evaluate the potential. - x0 (float): The x position of the potential minimum. - y0 (float): The y position of the potential minimum. - z0 (float): The z position of the potential minimum. - height (float): The height of the Gaussian potential. - width (float): The standard deviation (controls the width of the Gaussian).

Returns: - np.ndarray: The potential energy at each position (x, y, z).

xdatbus.BPY_AVAILABLE = True

xdatbus.PDB_AVAILABLE = True

xdatbus.MN_AVAILABLE = True

xdatbus.YAML_AVAILABLE = True

xdatbus.realize_instances(obj, bond_radius)

Realize instances of the given object. This function requires bpy.

objbpy.types.Object
The object to realize instances of

bond_radiusfloat
The radius of the bonds

xdatbus.remove_nodes(obj, node_names)

Remove nodes with given names from the object’s node tree.

objbpy.types.Object
The object from which to remove nodes.

node_nameslist of str
The names of the nodes to remove.

xdatbus.get_template_node(node_name, nodes)

Get a node from a template blend file.

node_namestr
The name of the node to get.

nodesbpy.types.NodeTree.nodes
The nodes from the node tree to add the node to.

nodebpy.types.Node
The node from the template blend file.

xdatbus.set_color4element(obj, atomic_number, color, atomic_scale, bonded, bonded_count=0)

Add a custom node and connect it to the specified input of the target node.

objbpy.types.Object
The object with the Geometry Nodes modifier whose node tree we’re editing.

atomic_numberint
The atomic number of the element to set the color of.

colortuple
The color to set the node to.

atomic_scalefloat
The size of the atoms.

bondedbool
Whether the atoms are bonded.

bonded_countint
The number of elements forming a bond.

xdatbus.apply_yaml(obj, yaml_path)

Set the color of the given object. This function requires bpy and molecularnodes.

Parameters

objbpy.types.Object: The object to set the color of
yaml_pathstr: The path to the YAML file to use

xdatbus.clear_scene(mesh=True, lights=True, geometry_nodes=True)

Clear the scene of all objects. This function requires bpy.

meshbool
Clear mesh objects

lightsbool
Clear light objects

geometry_nodesbool
Clear geometry node groups

xdatbus.render_image(engine='eevee', x=1000, y=500, output_path='render.png')

Render an image. This function requires bpy.

enginestr
The render engine to use. Either ‘eevee’ or ‘cycles’

xint
The x resolution of the image

yint
The y resolution of the image

output_pathstr
The path to save the image to

xdatbus.apply_modifiers_to_mesh(obj)

Apply modifiers to the given object. This function requires bpy.

objbpy.types.Object
The object to apply modifiers to

xdatbus.yaml_gen(pdb_file_path)

This function generates a YAML file for the elements in the PDB file, with a common bond_radius.

Parameters

pdb_file_pathstr: Input path of the PDB file

xdatbus.yaml_loader(yaml_path)

This function loads a YAML file and returns element data and bond radius.

Parameters

yaml_pathstr: Input path of the YAML file

Returns

tuple: A tuple containing a dictionary of elements with their properties and the common bond radius.

xdatbus.main()