webng.analysis package

Submodules

webng.analysis.analysis module

class webng.analysis.analysis.weAnalysis(opts)[source]

Bases: object

Base class for all analysis classes.

set_names(names)[source]

webng.analysis.average module

class webng.analysis.average.weAverage(opts)[source]

Bases: weAnalysis

Class for the averaging analysis.

This tool creates a N by N matrix-like plot where N is the number of observables in the BNGL tool (unless overridden by the dimensions option). The diagonal will contain 1D probability distributions and off diagonals will contain 2D probability heatmaps of each dimension vs each other dimension.

This tool uses w_pdist WESTPA tool to calculate probabilty distributions hence it needs w_pdist to be accessible directly from the commandline.

get_mapper(mapper_iter)[source]
open_pdist_file(fdim, sdim)[source]
run(ext=None)[source]
save_fig()[source]
set_dims(dims=None)[source]
set_iter_range(first_iter, last_iter)[source]
set_names(names)[source]
setup_figure()[source]

webng.analysis.cluster module

class webng.analysis.cluster.weCluster(opts)[source]

Bases: weAnalysis

cluster()[source]
get_mstable_assignments()[source]
load_bin_arrays()[source]
preprocess_tm()[source]
print_mstable_states()[source]
print_pcca_results()[source]
row_normalize()[source]
run()[source]
save_full_mstabs()[source]
save_mstable_assignments()[source]
save_pcca()[source]

webng.analysis.evolution module

class webng.analysis.evolution.weEvolution(opts)[source]

Bases: weAnalysis

Class for the evolution analysis.

This tool creates N plots where N is the number of observables (unless overridden by the dimensions option). Each plot contains the evolution of the 1D probability distirubion over WE iterations.

This tool uses w_pdist WESTPA tool to calculate probabilty distributions hence it needs w_pdist to be accessible directly from the commandline.

open_pdist_file(fdim)[source]
run(ext=None)[source]
save_fig()[source]
set_dims(dims=None)[source]
set_names(names)[source]
setup_figure()[source]

webng.analysis.network module

class webng.analysis.network.weNetwork(opts)[source]

Bases: weAnalysis

get_coarse_network()[source]
get_full_network()[source]
run()[source]
save_network()[source]

webng.analysis.utils module

webng.analysis.utils.assign_cluster()[source]
webng.analysis.utils.assign_pcca()[source]
webng.analysis.utils.assign_voronoi()[source]
webng.analysis.utils.avg(hist, midpoints, binbounds)[source]
webng.analysis.utils.circumcircle(P1, P2, P3)[source]

Used for plotting voronoi center in average analysis.

Adapted from: http://local.wasp.uwa.edu.au/~pbourke/geometry/circlefrom3/Circle.cpp

webng.analysis.utils.load_mapper(h, iter_no)[source]
webng.analysis.utils.pull_all_data(n_iter, iter_group)[source]

This function reshapes the progress coordinate and auxiliary data for each iteration and retuns it to the tool.

webng.analysis.utils.pull_data(n_iter, iter_group)[source]

This function reshapes the progress coordinate and auxiliary data for each iteration and retuns it to the tool.

webng.analysis.utils.pull_weight(n_iter, iter_group)[source]

Custom weight puller for a custom version of w_pdist. This will probably eventually make it into the main repo

webng.analysis.utils.voronoi(X, Y)[source]

Used for plotting voronoi center in average analysis.

class webng.analysis.utils.wrapped_clusterer(clusterer)[source]

Bases: NopMapper

assign(coords, mask=None, output=None)[source]
class webng.analysis.utils.wrapped_mapper(mapper)[source]

Bases: NopMapper

assign(coords, mask=None, output=None)[source]
load_pcca_labels(label_file)[source]

Module contents