This documentation is for version 2.0.dev, which is not released yet.
Basic class for calculations using the TreBor method.
Parameters : | dataset : string
tree : {None, string}
paps : string (default=”pap”)
cognates : string (default=”cogid”)
verbose : bool (default=False)
tree_calc : {‘neighbor’,’upgma’} (default=’neighbor’)
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Methods
add_entries(entry, source, function[, override]) | Add new entry-types to the word list by modifying given ones. |
analyze([runs, mixed, verbose, output_gml, ...]) | Carry out a full analysis using various parameters. |
calculate(data[, taxa, concepts, cognates, ...]) | Function calculates specific data. |
get_AVSD(glm[, verbose, write]) | Function retrieves all paps for ancestor languages in a given tree. |
get_CVSD([verbose]) | Calculate the Contemporary Vocabulary Size Distribution (CVSD). |
get_GLS([mode, ratio, restriction, ...]) | Create gain-loss-scenarios for all non-singleton paps in the data. |
get_IVSD([verbose, output_gml, output_plot, tar]) | Calculate VSD on the basis of each item. |
get_MLN(glm[, threshold, verbose, colormap, ...]) | Compute an Minimal Lateral Network for a given model. |
get_PDC(glm[, verbose]) | Calculate Patchily Distributed Cognates. |
get_dict([col, row, entry]) | Function returns dictionaries of the cells matched by the indices. |
get_entries(entry) | Return all entries matching the given entry-type as a two-dimensional list. |
get_etymdict([ref, entry, loans]) | Return an etymological dictionary representation of the word list. |
get_list([row, col, entry, flat]) | Function returns lists of rows and columns specified by their name. |
get_paps([ref, entry, missing]) | Function returns a list of present-absent-patterns of a given word list. |
output(fileformat, **keywords) | Write wordlist to file. |
pickle() | Store a dump of the data in a binary file. |
plot_MLN([glm, filename, fileformat, ...]) | Plot the MLN with help of Matplotlib. |
plot_MSN([glm, verbose, filename, ...]) | Plot the Minimal Spatial Network. |
plot_concepts(concept, cogA, cogB[, labels, ...]) | Plot the Minimal Spatial Network. |
tokenize([ortho_profile, source, target]) | Tokenize the data with help of orthography profiles. |