mouse2


Namemouse2 JSON
Version 0.2.23 PyPI version JSON
download
home_pagehttps://github.com/mglagolev/mouse2
SummaryA toolkit for processing molecular dynamics simulation data
upload_time2024-03-28 13:36:15
maintainerNone
docs_urlNone
authorMikhail Glagolev, Anna Glagoleva
requires_pythonNone
licenseGNU GPL v3
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # mouse2
Scripts for molecular ordering analysis - new version based on NumPy and MDAnalysis.

This repository contains the utilities to quantitatively assess the results of molecular dynamics simulations by calculating numeric ordering parameters.  
The focus is the chirality of the systems and the local ordering arising from it.

The NumPy and MDAnalysis libraries need to be installed to use the scripts, and the
NetworkX library is additionaly required to use the aggregates.py.  
Matplotlib and SciPy are required to use the plotting and fitting options in some of the scripts.

## Quick installation: ##

	pip install mouse2

PyPI installation should add the following commands:

**aggregates**			-	determine the aggregates in the system based on inter-particle distances

**bond_autocorrelations**	-	calculate the autocorrelation function of the backbone bonds of a polymer
	
**backbone_twist**			-	calculate the list of dihedral angles formed by the segments of polymer backbone	
	
**local_alignment**	- 	calculate the angles between the bonds, if their midpoints are located within specified distance range from each other
	
**lamellar_alignment**		-	calculate the molecular ordering parameters for lamellae containing tilted copolymer blocks

**data2pdb**			-	convert the LAMMPS data file to Protein Databank (pdb) format

## Quick reference: ##

	aggregates.py [-h] [--r_neigh [R_neigh]] [--selection [QUERY]] INPUT [INPUT ...]

This utility returns a data structure containing list of aggregates for all of the timesteps in the MDAnalysis universe.  
Each aggregate is determined as a complete graph of neighbors.  
The atoms are considered neighbors if the distance between their centers does not exceed r_neigh.  
Each aggregate is represented as a list of MDAnalysis atom indices.

###### positional arguments: ###### 

	INPUT		input file(s), the format will be guessed by MDAnalysis based on file extension

For the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1

###### options: ###### 

	-h, --help	show this help message and exit  
	--r_neigh [R_neigh]	
			neighbor cutoff  
	--selection [QUERY]
			consider only selected atoms, use MDAnalysis selection language  

***

	bond_autocorrelations.py [-h] [--k_max [k_max]] 
					[--selection [QUERY]] 
					[--different-molecules] 
					[--plot] 
					[--fit] 
					[--p_guess [NUMBER]] 
					INPUT [INPUT ...]


Calculate the autocorrelation function of the polymer bonds.  
The formula is presented in https://doi.org/10.1134/S0965545X10070102.  
Application to all-atom simulations: https://doi.org/10.3390/polym11122056.


###### positional arguments: ###### 

	INPUT		input file(s), the format will be guessed by MDAnalysis based on file extension

For the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1

###### options: ###### 

	-h, --help	show this help message and exit  
	--k_max [k_max]	
			maximum distance between the bonds along the backbone  
	--selection [QUERY]	
			consider only selected atoms, use MDAnalysis selection language  
	--different-molecules	
			calculate correlations based on particle index number, 
			even if the bonds belong to different molecules  
	--plot		plot the averaged results  
	--fit		fit the averaged results with a modulated exponential function  
	--p_guess [NUMBER]	
			initial guess for the number of monomer units per turn  
                        
***

	backbone_twist.py [-h] [--selection [QUERY]] 
				[--k VECTOR_LENGTHS [VECTOR_LENGTHS ...]] 
				[--different-molecules] [--plot] 
				INPUT [INPUT ...]

Calculate the list of dihedral angles, formed by the following vectors:
(r<sub>*i*</sub>, r<sub>*i+k*</sub>), (r<sub>*i+k*</sub>, r<sub>*i+2k*</sub>), (r<sub>*i+2k*</sub>, r<sub>*i+3k*</sub>),
where *i* is the index of a monomer unit.  
The example of the analysis is provided in the Supplementary Information for
https://doi.org/10.1016/j.polymer.2022.124974.


###### positional arguments: ###### 

	INPUT		input file(s), the format will be guessed by MDAnalysis based on file extension
			
For the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1

###### options: ###### 

	-h, --help	show this help message and exit
	--selection [QUERY]	
			consider only selected atoms, use MDAnalysis selection language
	--k VECTOR_LENGTHS [VECTOR_LENGTHS ...]
			list of vector lengths along the backbone
	--different-molecules
			consider the angles spanning different molecules
	--plot		plot the results
  
***  

	local_alignment.py [-h] [--r_max [R_max]] [--r_min [R_min]] 
					[--selection [QUERY]]
					[--same-molecule] 
					[--histogram] 
					[--n_bins [N_bins]] 
					[--plot] 
					[--pairs-file [PAIRS_FILE]]
					INPUT [INPUT ...]

This utility calculates the angles between the bonds, if their midpoints are located within the range of [r<sub>min</sub>, r<sub>max</sub>].  
The local ordering parameter is then calculated as S = 3/2<(cos<sup>2</sup>(gamma)> - 1/2,
where "gamma" is the angle between the bond vectors. The distributions are stored if the --histogram flag is provided.  
The example applications are https://doi.org/10.1016/j.polymer.2020.122232
and https://doi.org/10.1016/j.polymer.2022.124974.


###### positional arguments: ###### 

	INPUT		input file(s), the format will be guessed by MDAnalysis based on file extension
			
For the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1

###### options: ###### 

	-h, --help	show this help message and exit  
	--r_max [R_max]	outer cutoff radius  
	--r_min [R_min]	inner cutoff radius  
	--selection [QUERY]  
			consider only selected atoms, use MDAnalysis selection language
	--same-molecule	take into account bonds from the same molecule  
	--histogram	store and optionally plot the distribution of the angles  
	--n_bins [N_bins]  	
			number of bins of the distribution histogram  
	--plot			
			plot the distribution histogram 
	--pairs-file [PAIRS_FILE]  
                        CSV file with pairs of indices, corresponding to vector ends 

***

	lamellar_alignment.py [-h] [--block-types TYPES TYPES] 
						[--A] [--B] 
						[--verbose] 
						INPUT [INPUT ...]

Calculate the molecular ordering parameters for lamellae containing tilted copolymer blocks, as described in the paper by 
M. A. Osipov, M. V. Gorkunov, A. V. Berezkin, A. A. Antonov and Y. V. Kudryavtsev
"Molecular theory of the tilting transition and computer simulations of the tilted lamellar phase of rod–coil diblock copolymers"
https://doi.org/10.1063/5.0005854.  
A use case is also presented in https://doi.org/10.1039/D1SM00759A.


###### positional arguments: ###### 

	INPUT		input file(s), the format will be guessed by MDAnalysis based on file extension

For the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1

###### options: ###### 

	-h, --help	show this help message and exit  
	--block-types TYPES TYPES	
			bead types for the blocks A and B 
			(provide 2 arguments, without the option default values 1 and 2 are used)  
	--A		calculate the values for block A  
	--B		calculate the values for block B  
	--verbose	store the values for individual molecules
  
***

	data2pdb.py [-h] [--hide-pbc-bonds] LAMMPS_DATA PDB
	
This utility reads LAMMPS data file, and writes out the configuration in the PDB format.

###### positional arguments: ###### 

	LAMMPS_DATA	input
	PDB		output

###### options: ###### 

	--no-pbc-bonds	hide the bonds which are not between the nearest images
    			of the particles, used for visualisation
    
***

The algorithms were used in the following publications:

Abramova A. A., Glagolev M. K., Vasilevskaya V. V. Structured globules with twisted arrangement of helical blocks: Computer simulation // Polymer. — 2022. — Vol. 253. - P. 124974.

Glagolev M. K., Glagoleva A. A., Vasilevskaya V. V. Microphase separation in helix-coil block copolymer melts: computer simulation // Soft Matter. — 2021. — Vol. 17, no. 36. — P. 8331–8342.

Glagolev M. K., Vasilevskaya V. V. Coarse-grained simulation of molecular ordering in polylactic blends under uniaxial strain // Polymer. — 2020. — Vol. 190. — P. 122232.

Glagolev M. K., Vasilevskaya V. V. Liquid-crystalline ordering of filaments formed by bidisperse amphiphilic macromolecules // Polymer Science, Series C. — 2018. — Vol. 60, no. 1. — P. 39–47.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Domains in mixtures of amphiphilic macromolecules with different stiffness of backbone // Polymer. — 2017. — Vol. 125. — P. 234–240.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Induced liquid-crystalline ordering in solutions of stiff and flexible amphiphilic macromolecules: Effect of mixture composition // Journal of Chemical Physics. — 2016. — Vol. 145, no. 4. — P. 044904.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Effect of induced self-organization in mixtures of amphiphilic macromolecules with different stiffness // Macromolecules. — 2015. — Vol. 48, no. 11. — P. 3767–3774.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Self-organization of amphiphilic macromolecules with local helix structure in concentrated solutions // Journal of Chemical Physics. — 2012. — Vol. 137, no. 8. - P. 084091.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Formation of fibrillar aggregates in concentrated solutions of rigid-chain amphiphilic macromolecules with fixed torsion and bend angles // Polymer Science, Series A. — 2011. — Vol. 53, no. 8. — P. 733–743.

Glagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Compactization of rigid-chain amphiphilic macromolecules with local helical structure // Polymer Science, Series A. — 2010. — Vol. 52, no. 7. — P. 761–774.

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/mglagolev/mouse2",
    "name": "mouse2",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": null,
    "author": "Mikhail Glagolev, Anna Glagoleva",
    "author_email": "mikhail.glagolev@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/42/7f/1cdc21665ea63a2f6dbbf053309db51ebc9798106710f8b0b1f44d8f2276/mouse2-0.2.23.tar.gz",
    "platform": null,
    "description": "# mouse2\nScripts for molecular ordering analysis - new version based on NumPy and MDAnalysis.\n\nThis repository contains the utilities to quantitatively assess the results of molecular dynamics simulations by calculating numeric ordering parameters.  \nThe focus is the chirality of the systems and the local ordering arising from it.\n\nThe NumPy and MDAnalysis libraries need to be installed to use the scripts, and the\nNetworkX library is additionaly required to use the aggregates.py.  \nMatplotlib and SciPy are required to use the plotting and fitting options in some of the scripts.\n\n## Quick installation: ##\n\n\tpip install mouse2\n\nPyPI installation should add the following commands:\n\n**aggregates**\t\t\t-\tdetermine the aggregates in the system based on inter-particle distances\n\n**bond_autocorrelations**\t-\tcalculate the autocorrelation function of the backbone bonds of a polymer\n\t\n**backbone_twist**\t\t\t-\tcalculate the list of dihedral angles formed by the segments of polymer backbone\t\n\t\n**local_alignment**\t- \tcalculate the angles between the bonds, if their midpoints are located within specified distance range from each other\n\t\n**lamellar_alignment**\t\t-\tcalculate the molecular ordering parameters for lamellae containing tilted copolymer blocks\n\n**data2pdb**\t\t\t-\tconvert the LAMMPS data file to Protein Databank (pdb) format\n\n## Quick reference: ##\n\n\taggregates.py [-h] [--r_neigh [R_neigh]] [--selection [QUERY]] INPUT [INPUT ...]\n\nThis utility returns a data structure containing list of aggregates for all of the timesteps in the MDAnalysis universe.  \nEach aggregate is determined as a complete graph of neighbors.  \nThe atoms are considered neighbors if the distance between their centers does not exceed r_neigh.  \nEach aggregate is represented as a list of MDAnalysis atom indices.\n\n###### positional arguments: ###### \n\n\tINPUT\t\tinput file(s), the format will be guessed by MDAnalysis based on file extension\n\nFor the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1\n\n###### options: ###### \n\n\t-h, --help\tshow this help message and exit  \n\t--r_neigh [R_neigh]\t\n\t\t\tneighbor cutoff  \n\t--selection [QUERY]\n\t\t\tconsider only selected atoms, use MDAnalysis selection language  \n\n***\n\n\tbond_autocorrelations.py [-h] [--k_max [k_max]] \n\t\t\t\t\t[--selection [QUERY]] \n\t\t\t\t\t[--different-molecules] \n\t\t\t\t\t[--plot] \n\t\t\t\t\t[--fit] \n\t\t\t\t\t[--p_guess [NUMBER]] \n\t\t\t\t\tINPUT [INPUT ...]\n\n\nCalculate the autocorrelation function of the polymer bonds.  \nThe formula is presented in https://doi.org/10.1134/S0965545X10070102.  \nApplication to all-atom simulations: https://doi.org/10.3390/polym11122056.\n\n\n###### positional arguments: ###### \n\n\tINPUT\t\tinput file(s), the format will be guessed by MDAnalysis based on file extension\n\nFor the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1\n\n###### options: ###### \n\n\t-h, --help\tshow this help message and exit  \n\t--k_max [k_max]\t\n\t\t\tmaximum distance between the bonds along the backbone  \n\t--selection [QUERY]\t\n\t\t\tconsider only selected atoms, use MDAnalysis selection language  \n\t--different-molecules\t\n\t\t\tcalculate correlations based on particle index number, \n\t\t\teven if the bonds belong to different molecules  \n\t--plot\t\tplot the averaged results  \n\t--fit\t\tfit the averaged results with a modulated exponential function  \n\t--p_guess [NUMBER]\t\n\t\t\tinitial guess for the number of monomer units per turn  \n                        \n***\n\n\tbackbone_twist.py [-h] [--selection [QUERY]] \n\t\t\t\t[--k VECTOR_LENGTHS [VECTOR_LENGTHS ...]] \n\t\t\t\t[--different-molecules] [--plot] \n\t\t\t\tINPUT [INPUT ...]\n\nCalculate the list of dihedral angles, formed by the following vectors:\n(r<sub>*i*</sub>, r<sub>*i+k*</sub>), (r<sub>*i+k*</sub>, r<sub>*i+2k*</sub>), (r<sub>*i+2k*</sub>, r<sub>*i+3k*</sub>),\nwhere *i* is the index of a monomer unit.  \nThe example of the analysis is provided in the Supplementary Information for\nhttps://doi.org/10.1016/j.polymer.2022.124974.\n\n\n###### positional arguments: ###### \n\n\tINPUT\t\tinput file(s), the format will be guessed by MDAnalysis based on file extension\n\t\t\t\nFor the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1\n\n###### options: ###### \n\n\t-h, --help\tshow this help message and exit\n\t--selection [QUERY]\t\n\t\t\tconsider only selected atoms, use MDAnalysis selection language\n\t--k VECTOR_LENGTHS [VECTOR_LENGTHS ...]\n\t\t\tlist of vector lengths along the backbone\n\t--different-molecules\n\t\t\tconsider the angles spanning different molecules\n\t--plot\t\tplot the results\n  \n***  \n\n\tlocal_alignment.py [-h] [--r_max [R_max]] [--r_min [R_min]] \n\t\t\t\t\t[--selection [QUERY]]\n\t\t\t\t\t[--same-molecule] \n\t\t\t\t\t[--histogram] \n\t\t\t\t\t[--n_bins [N_bins]] \n\t\t\t\t\t[--plot] \n\t\t\t\t\t[--pairs-file [PAIRS_FILE]]\n\t\t\t\t\tINPUT [INPUT ...]\n\nThis utility calculates the angles between the bonds, if their midpoints are located within the range of [r<sub>min</sub>, r<sub>max</sub>].  \nThe local ordering parameter is then calculated as S = 3/2<(cos<sup>2</sup>(gamma)> - 1/2,\nwhere \"gamma\" is the angle between the bond vectors. The distributions are stored if the --histogram flag is provided.  \nThe example applications are https://doi.org/10.1016/j.polymer.2020.122232\nand https://doi.org/10.1016/j.polymer.2022.124974.\n\n\n###### positional arguments: ###### \n\n\tINPUT\t\tinput file(s), the format will be guessed by MDAnalysis based on file extension\n\t\t\t\nFor the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1\n\n###### options: ###### \n\n\t-h, --help\tshow this help message and exit  \n\t--r_max [R_max]\touter cutoff radius  \n\t--r_min [R_min]\tinner cutoff radius  \n\t--selection [QUERY]  \n\t\t\tconsider only selected atoms, use MDAnalysis selection language\n\t--same-molecule\ttake into account bonds from the same molecule  \n\t--histogram\tstore and optionally plot the distribution of the angles  \n\t--n_bins [N_bins]  \t\n\t\t\tnumber of bins of the distribution histogram  \n\t--plot\t\t\t\n\t\t\tplot the distribution histogram \n\t--pairs-file [PAIRS_FILE]  \n                        CSV file with pairs of indices, corresponding to vector ends \n\n***\n\n\tlamellar_alignment.py [-h] [--block-types TYPES TYPES] \n\t\t\t\t\t\t[--A] [--B] \n\t\t\t\t\t\t[--verbose] \n\t\t\t\t\t\tINPUT [INPUT ...]\n\nCalculate the molecular ordering parameters for lamellae containing tilted copolymer blocks, as described in the paper by \nM. A. Osipov, M. V. Gorkunov, A. V. Berezkin, A. A. Antonov and Y. V. Kudryavtsev\n\"Molecular theory of the tilting transition and computer simulations of the tilted lamellar phase of rod\u2013coil diblock copolymers\"\nhttps://doi.org/10.1063/5.0005854.  \nA use case is also presented in https://doi.org/10.1039/D1SM00759A.\n\n\n###### positional arguments: ###### \n\n\tINPUT\t\tinput file(s), the format will be guessed by MDAnalysis based on file extension\n\nFor the formats overview in MDAnalysis see https://userguide.mdanalysis.org/1.0.0/formats/index.html#id1\n\n###### options: ###### \n\n\t-h, --help\tshow this help message and exit  \n\t--block-types TYPES TYPES\t\n\t\t\tbead types for the blocks A and B \n\t\t\t(provide 2 arguments, without the option default values 1 and 2 are used)  \n\t--A\t\tcalculate the values for block A  \n\t--B\t\tcalculate the values for block B  \n\t--verbose\tstore the values for individual molecules\n  \n***\n\n\tdata2pdb.py [-h] [--hide-pbc-bonds] LAMMPS_DATA PDB\n\t\nThis utility reads LAMMPS data file, and writes out the configuration in the PDB format.\n\n###### positional arguments: ###### \n\n\tLAMMPS_DATA\tinput\n\tPDB\t\toutput\n\n###### options: ###### \n\n\t--no-pbc-bonds\thide the bonds which are not between the nearest images\n    \t\t\tof the particles, used for visualisation\n    \n***\n\nThe algorithms were used in the following publications:\n\nAbramova A. A., Glagolev M. K., Vasilevskaya V. V. Structured globules with twisted arrangement of helical blocks: Computer simulation // Polymer. \u2014 2022. \u2014 Vol. 253. - P. 124974.\n\nGlagolev M. K., Glagoleva A. A., Vasilevskaya V. V. Microphase separation in helix-coil block copolymer melts: computer simulation // Soft Matter. \u2014 2021. \u2014 Vol. 17, no. 36. \u2014 P. 8331\u20138342.\n\nGlagolev M. K., Vasilevskaya V. V. Coarse-grained simulation of molecular ordering in polylactic blends under uniaxial strain // Polymer. \u2014 2020. \u2014 Vol. 190. \u2014 P. 122232.\n\nGlagolev M. K., Vasilevskaya V. V. Liquid-crystalline ordering of filaments formed by bidisperse amphiphilic macromolecules // Polymer Science, Series C. \u2014 2018. \u2014 Vol. 60, no. 1. \u2014 P. 39\u201347.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Domains in mixtures of amphiphilic macromolecules with different stiffness of backbone // Polymer. \u2014 2017. \u2014 Vol. 125. \u2014 P. 234\u2013240.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Induced liquid-crystalline ordering in solutions of stiff and flexible amphiphilic macromolecules: Effect of mixture composition // Journal of Chemical Physics. \u2014 2016. \u2014 Vol. 145, no. 4. \u2014 P. 044904.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Effect of induced self-organization in mixtures of amphiphilic macromolecules with different stiffness // Macromolecules. \u2014 2015. \u2014 Vol. 48, no. 11. \u2014 P. 3767\u20133774.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Self-organization of amphiphilic macromolecules with local helix structure in concentrated solutions // Journal of Chemical Physics. \u2014 2012. \u2014 Vol. 137, no. 8. - P. 084091.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Formation of fibrillar aggregates in concentrated solutions of rigid-chain amphiphilic macromolecules with fixed torsion and bend angles // Polymer Science, Series A. \u2014 2011. \u2014 Vol. 53, no. 8. \u2014 P. 733\u2013743.\n\nGlagolev M. K., Vasilevskaya V. V., Khokhlov A. R. Compactization of rigid-chain amphiphilic macromolecules with local helical structure // Polymer Science, Series A. \u2014 2010. \u2014 Vol. 52, no. 7. \u2014 P. 761\u2013774.\n",
    "bugtrack_url": null,
    "license": "GNU GPL v3",
    "summary": "A toolkit for processing molecular dynamics simulation data",
    "version": "0.2.23",
    "project_urls": {
        "Homepage": "https://github.com/mglagolev/mouse2"
    },
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "427f1cdc21665ea63a2f6dbbf053309db51ebc9798106710f8b0b1f44d8f2276",
                "md5": "2b01f910dc2d308ce2824c3c8c313ca8",
                "sha256": "0a5b617b7bf4864c242eca8ae4771a7a395f7e0f93e2bda9d377e6e74cdea0bf"
            },
            "downloads": -1,
            "filename": "mouse2-0.2.23.tar.gz",
            "has_sig": false,
            "md5_digest": "2b01f910dc2d308ce2824c3c8c313ca8",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 44807,
            "upload_time": "2024-03-28T13:36:15",
            "upload_time_iso_8601": "2024-03-28T13:36:15.748257Z",
            "url": "https://files.pythonhosted.org/packages/42/7f/1cdc21665ea63a2f6dbbf053309db51ebc9798106710f8b0b1f44d8f2276/mouse2-0.2.23.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-03-28 13:36:15",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "mglagolev",
    "github_project": "mouse2",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "mouse2"
}
        
Elapsed time: 0.23859s