twodanalysis.Memb2D

class twodanalysis.Memb2D(obj, lipid_list=None, guess_chain_l=True, chain_info=None, v_min=None, v_max=None, add_radii=False, verbose=False)[source]
__init__(obj, lipid_list=None, guess_chain_l=True, chain_info=None, v_min=None, v_max=None, add_radii=False, verbose=False)[source]

__init__ _summary_

_extended_summary_

Parameters:

  • top (_type_) – _description_

  • traj (_type_) – _description_

  • lipid_list (_type_, optional) – _description_, by default None

  • tpr (_type_, optional) – _description_, by default None

  • info (bool, optional) – _description_, by default False

  • guess_chain_l (bool, optional) – _description_, by default True

  • chain_info (_type_, optional) – _description_, by default None

  • v_min (_type_, optional) – _description_, by default None

  • v_max (_type_, optional) – _description_, by default None

  • add_radii (bool, optional) – _description_, by default False

  • verbose (bool, optional) – _description_, by default False

Methods

__init__(obj[, lipid_list, guess_chain_l, ...])

__init__ _summary_

add_small_matrix(big_matrix, small_matrix, ...)

Add smmall matrix to a big matrix

all_lip_order(layer, nbins[, edges, ...])

all_lip_order Find the 2D order parameters for all lipids

build_name(resnames_list)

build_resname(resnames_list)

build_resname_head(resnames_list)

count_order(data, min_lenght, n_chain)

Function used to count and average the order parameter in each grid square

create_circle_array(grid_size, radius_A[, ...])

Create a small matrix with a inner circle of the size of radius_A

extend_data(data, dimensions, percentage[, ...])

Function to extent data for periodicity purposes

get_highest(data, min_lenght)

Code to get the highest value given two columns that are to be ordered in a 2D grid :Parameters: * data ((ndarray(:,2))) -- Array with two columns (column1: map to a 2D grid, column2: values) * min_lenght ((int)) -- Size of squares in the 2D grid

get_indexes(data[, bins, edges, matrix_height])

given data in 2D, the code returns the indexes to locate the data in the 2D grid defined by edges and bins

get_individual(lista)

This function gets a list with a specific carbon (e.g. C34 or C22) and its respective hidrogens (e.g. H4X, H4Y).

grid_apl([layer, start, final, step, ...])

Function to compute and map the grid APL for several frames, map them to a 2D grid and average them

guess_minmax_space([all])

Check the minimun and max position in x,y

height_matrix(lipids, layer[, edges, start, ...])

Code to divide the space in a 2D grid and compute the height referenced to zmean

histogram2D(sample1, weights, n_chain[, ...])

Computes the 2D histogram of 2D data with various values taking an average of them

individual_order_sn1(sel, lipid, n_chain)

Code to loop over the number of carbons_summary_ in the lipid tail and get a list with the carbon and its hydrogens for each carbon in the lipid tail: \([C3i, HiX, HiY, ...]\).

individual_order_sn2(sel, lipid, n_chain)

Code to loop over the number of carbons in the lipid tail and get a list with the carbon and its hydrogens for each carbon in the lipid tail: \([C2i, HiX, HiY, ...]\).

map_voronoi(voronoi_points, voronoi_areas, ...)

Function to map voronoi APL to a 2D plane

map_voronoitest(voronoi_vertices, ...)

numpyhistogram2D(sample1, weights, n_chain)

Computes the 2D histogram of 2D data with various values taking an average of them

order_histogram(lipid, layer, n_grid, n_chain)

Method that allows for the computation of order parameters in 2D fashion

packing_defects([layer, nbins, height, ...])

Compute packing defects based on packmem: https://doi.org/10.1016/j.bpj.2018.06.025

print_dict(dictio)

process_point(point, tree, polygons, values)

surface([start, final, step, lipids, layer, ...])

Code to loop over the trajectory and print [x,y,z(referenced to zmean), charge] in a file.

thickness(nbins[, edges, lipids, start, ...])

Find the thichness mapped in a 2d grid

visualize_polarity([lipids])

This function is used to visualize what atoms are considered in polarity

voronoi_apl([layer, working_lip, lipid_list])

Computes the APL for membranes with different lipids

windows_apl([layer, start, final, step, ...])

Function to compute APL and map it to a 2D grid in windows of time defined by the user.