pcasuite package

Submodules

pcasuite.pcz_zip module

Module containing the PCAzip class and the command line interface.

class pcasuite.pcz_zip.PCZzip(input_pdb_path: str, input_crd_path: str, output_pcz_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZzip
Wrapper of the pcazip tool from the PCAsuite FlexServ module.
Compress Molecular Dynamics (MD) trajectories using Principal Component Analysis (PCA) algorithms.
Parameters:

  • input_pdb_path (str) – Input PDB file. File type: input. Sample file. Accepted formats: pdb (edam:format_1476).

  • input_crd_path (str) –

    Input Trajectory file. File type: input. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878).

  • output_pcz_path (str) –

    Output compressed trajectory. File type: output. Sample file. Accepted formats: pcz (edam:format_3874).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pcazip”) pcazip binary path to be used.

    • neigenv (int) - (0) Number of generated eigenvectors

    • variance (int) - (90) Percentage of variance captured by the final set of eigenvectors

    • verbose (bool) - (False) Make output verbose

    • gauss_rmsd (bool) - (False) Use a gaussian RMSd for fitting

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_zip import pcz_zip
prop = {
    'variance': 90
}
pcz_zip( input_pdb_path='/path/to/pcazip_input.pdb',
        input_crd_path='/path/to/pcazip_input.crd',
        output_pcz_path='/path/to/pcazip_traj.pcz',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcazip module.

pcasuite.pcz_zip.main()[source]
pcasuite.pcz_zip.pcz_zip(input_pdb_path: str, input_crd_path: str, output_pcz_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZzip method

pcasuite.pcz_unzip module

Module containing the PCZunzip class and the command line interface.

class pcasuite.pcz_unzip.PCZunzip(input_pcz_path: str, output_crd_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZunzip
Wrapper of the pcaunzip tool from the PCAsuite FlexServ module.
Uncompress Molecular Dynamics (MD) trajectories compressed using Principal Component Analysis (PCA) algorithms.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_crd_path (str) –

    Output uncompressed trajectory. File type: output. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878), pdb (edam:format_1476).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pcaunzip”) pcaunzip binary path to be used.

    • verbose (bool) - (False) Make output verbose

    • pdb (bool) - (False) Use PDB format for output trajectory

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_unzip import pcz_unzip
prop = {
    'pdb': False
}
pcz_unzip( input_pcz_path='/path/to/pcazip_input.pcz',
        output_crd_path='/path/to/pcazip_traj.crd',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcaunzip module.

pcasuite.pcz_unzip.main()[source]
pcasuite.pcz_unzip.pcz_unzip(input_pcz_path: str, output_crd_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZunzip method

pcasuite.pcz_animate module

Module containing the PCZanimate class and the command line interface.

class pcasuite.pcz_animate.PCZanimate(input_pcz_path: str, output_crd_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZanimate
Extract PCA animations from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_crd_path (str) –

    Output PCA animated trajectory file. File type: output. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878), pdb (edam:format_1476).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • eigenvector (int) - (1) Eigenvector to be used for the animation

    • pdb (bool) - (False) Use PDB format for output trajectory

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_animate import pcz_animate
prop = {
    'eigenvector': 1,
    'pdb': True
}
pcz_animate( input_pcz_path='/path/to/pcazip_input.pcz',
        output_crd_path='/path/to/animated_traj.pdb',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_animate module.

pcasuite.pcz_animate.main()[source]
pcasuite.pcz_animate.pcz_animate(input_pcz_path: str, output_crd_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZanimate method

pcasuite.pcz_bfactor module

Module containing the PCZbfactor class and the command line interface.

class pcasuite.pcz_bfactor.PCZbfactor(input_pcz_path: str, output_dat_path: str, output_pdb_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZbfactor
Extract residue bfactors x PCA mode from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_dat_path (str) –

    Output Bfactor x residue x PCA mode file. File type: output. Sample file. Accepted formats: dat (edam:format_1637), txt (edam:format_2330), csv (edam:format_3752).

  • output_pdb_path (str) (Optional) –

    Output PDB with Bfactor x residue x PCA mode file. File type: output. Sample file. Accepted formats: pdb (edam:format_1476).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • eigenvector (int) - (0) PCA mode (eigenvector) from which to extract bfactor values per residue (0 means average over all modes).

    • pdb (bool) - (False) Generate a PDB file with the computed bfactors (to be easily represented with colour scale)

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_bfactor import pcz_bfactor
prop = {
    'eigenvector': 1,
    'pdb': True
}
pcz_bfactor( input_pcz_path='/path/to/pcazip_input.pcz',
        output_dat_path='/path/to/bfactors_mode1.dat',
        output_pdb_path='/path/to/bfactors_mode1.pdb',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_bfactor module.

pcasuite.pcz_bfactor.main()[source]
pcasuite.pcz_bfactor.pcz_bfactor(input_pcz_path: str, output_dat_path: str, output_pdb_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZbfactor method

pcasuite.pcz_collectivity module

Module containing the PCZcollectivity class and the command line interface.

class pcasuite.pcz_collectivity.PCZcollectivity(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZcollectivity
Extract PCA collectivity (numerical measure of how many atoms are affected by a given mode) from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA Collectivity indexes per mode. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • eigenvector (int) - (0) PCA mode (eigenvector) from which to extract stiffness.

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_collectivity import pcz_collectivity

prop = {
    'eigenvector': 1
}

pcz_collectivity( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/pcz_collectivity.json',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_collectivity module.

pcasuite.pcz_collectivity.main()[source]
pcasuite.pcz_collectivity.pcz_collectivity(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZcollectivity method

pcasuite.pcz_evecs module

Module containing the PCZevecs class and the command line interface.

class pcasuite.pcz_evecs.PCZevecs(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZevecs
Extract PCA Eigen Vectors from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA Eigen Vectors. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • eigenvector (int) - (1) PCA mode (eigenvector) from which to extract eigen vectors.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_evecs import pcz_evecs

prop = {
    'eigenvector': 1
}

pcz_evecs( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/pcz_evecs.json',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_evecs module.

pcasuite.pcz_evecs.main()[source]
pcasuite.pcz_evecs.pcz_evecs(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZevecs method

pcasuite.pcz_hinges module

Module containing the PCZhinges class and the command line interface.

class pcasuite.pcz_hinges.PCZhinges(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZhinges
Compute possible hinge regions (residues around which large protein movements are organized) of a molecule from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output hinge regions x PCA mode file. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • eigenvector (int) - (0) PCA mode (eigenvector) from which to extract bfactor values per residue (0 means average over all modes).

    • method (str) - (“Dynamic_domain”) Method to compute the hinge regions (Options: Bfactor_slope, Force_constant, Dynamic_domain)

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_hinges import pcz_hinges
prop = {
    'eigenvector': 1,
    'pdb': True
}
pcz_hinges( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/hinges.json',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_hinges module.

parse_output(output_file)[source]

Parses FlexServ hinges methods output file report

pcasuite.pcz_hinges.main()[source]
pcasuite.pcz_hinges.pcz_hinges(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZhinges method

pcasuite.pcz_info module

Module containing the PCZinfo class and the command line interface.

class pcasuite.pcz_info.PCZinfo(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZinfo
Extract PCA info (variance, Dimensionality) from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA info such as number of components, variance and dimensionality. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_info import pcz_info

pcz_info( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/pcz_info.json')
Info:
launch()[source]

Launches the execution of the FlexServ pcz_info module.

pcasuite.pcz_info.main()[source]
pcasuite.pcz_info.pcz_info(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZinfo method

pcasuite.pcz_lindemann module

Module containing the PCZlindemann class and the command line interface.

class pcasuite.pcz_lindemann.PCZlindemann(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZlindemann
Extract Lindemann coefficient (an estimate of the solid-liquid behaviour of a protein) from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA Eigen Vectors. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • mask (str) - (“all atoms”) Residue mask, in the format “:resnum1, resnum2, resnum3” (e.g. “:10,21,33”). See https://mmb.irbbarcelona.org/software/pcasuite/ for the complete format specification.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_lindemann import pcz_lindemann
prop = {
    'mask': ':10,12,15'
}
pcz_lindemann( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/lindemann_report.json',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_lindemann module.

pcasuite.pcz_lindemann.main()[source]
pcasuite.pcz_lindemann.pcz_lindemann(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZlindemann method

pcasuite.pcz_similarity module

Module containing the PCZsimilarity class and the command line interface.

class pcasuite.pcz_similarity.PCZsimilarity(input_pcz_path1: str, input_pcz_path2: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZsimilarity
Compute PCA similarity between two given compressed PCZ files.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path1 (str) –

    Input compressed trajectory file 1. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • input_pcz_path2 (str) –

    Input compressed trajectory file 2. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA Similarity results. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • amplifying_factor (float) - (“0.0”) common displacement (dx) along the different eigenvectors. If 0, the result is the absolute similarity index (dot product).

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_similarity import pcz_similarity

pcz_similarity( input_pcz_path1='/path/to/pcazip_input1.pcz',
        input_pcz_path2='/path/to/pcazip_input2.pcz',
        output_json_path='/path/to/pcz_similarity.json',
        properties=prop)
Info:
are_compatible(eigenvectors_1, eigenvectors_2)[source]
dot_product(eigenvectors_1, eigenvectors_2)[source]
dot_product_accum(eigenvectors_1, eigenvectors_2)[source]
eigenmsip(eigenvalues_1, eigenvectors_1, eigenvalues_2, eigenvectors_2, dx=None)[source]
get_rmsip(eigenvectors_1, eigenvectors_2)[source]
get_rwsip(eigenvalues_1, eigenvectors_1, eigenvalues_2, eigenvectors_2)[source]
get_similarity_index(eigenvalues_1, eigenvectors_1, eigenvalues_2, eigenvectors_2, dx=None)[source]
get_subspace_overlap(eigenvectors_1, eigenvectors_2)[source]
launch()[source]

Launches the execution of the FlexServ pcz_similarity module.

pcasuite.pcz_similarity.main()[source]
pcasuite.pcz_similarity.pcz_similarity(input_pcz_path1: str, input_pcz_path2: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZsimilarity method

pcasuite.pcz_stiffness module

Module containing the PCZstiffness class and the command line interface.

class pcasuite.pcz_stiffness.PCZstiffness(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv PCZstiffness
Extract PCA stiffness from a compressed PCZ file.
Wrapper of the pczdump tool from the PCAsuite FlexServ module.
Parameters:

  • input_pcz_path (str) –

    Input compressed trajectory file. File type: input. Sample file. Accepted formats: pcz (edam:format_3874).

  • output_json_path (str) –

    Output json file with PCA Stiffness. File type: output. Sample file. Accepted formats: json (edam:format_3464).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“pczdump”) pczdump binary path to be used.

    • eigenvector (int) - (0) PCA mode (eigenvector) from which to extract stiffness.

    • temperature (int) - (300) Temperature with which compute the apparent stiffness.

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

    • sandbox_path (str) - (“./”) [WF property] Parent path to the sandbox directory.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.pcasuite.pcz_stiffness import pcz_stiffness

prop = {
    'eigenvector': 1
}

pcz_stiffness( input_pcz_path='/path/to/pcazip_input.pcz',
        output_json_path='/path/to/pcz_stiffness.json',
        properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ pcz_stiffness module.

pcasuite.pcz_stiffness.main()[source]
pcasuite.pcz_stiffness.pcz_stiffness(input_pcz_path: str, output_json_path: str, properties: dict | None = None, **kwargs) → int[source]

Create PCZstiffness method