Man pages for momeara/RosettaFeatures
Tools for analyzing macromolecular feature distributions with Rosetta

compute_quantilesCompute quantiles for specified 'variable' grouping by 'ids'...
cross_validate_statisticsEvaluate a two sample tests between different classes of...
date_codecreate date code of the form YYMMDD inputs: d (optional):...
estimate_primary_modes_1dFor each set of rows grouped by the columns in ids, binary...
find_modes_in_densityprovides estimate_primary_mode_1d, which estimates the...
kolmogorov_smirnov_testPrefer to use the anderson_darling_2_sample comparison cf...
major_long_coordsThese the coordinates for the Lambert-Azmuthal plots:...
prepare_feature_instancesprepare instances to be viewed in PyMol script to look at...
save_tablesSave a data.frame as a table. For each output format,...
save_treesSave a data.frame as a table. For each output format,...
sliding_windowsExtract multiple, overlapping subsets of the data based on...
smooth_comparison_statisticsEvaluate a two sample tests between different classes of...
smooth_kl_divergenceHere the inputs are probabilities over the sample space...
spherical_normalizationnormalize according to spherical volume unit r, radial...
vector_crossprodinput: Two arrays each of dimension c(n, 3) output: An array...
vector_dihedralinput: 4 arrays each of dimension c(n, 3) output: An array of...
vector_distanceinput: two arrays each of dimension c(n, d) each representing...
vector_dotprodinput: Two arrays of dimension c(n, d) output: An array of...
vector_normalizeinput: An array of dimensions c(n, d) output: An array of...
momeara/RosettaFeatures documentation built on May 22, 2017, 12:04 p.m.