eigenspectrum_SCA_positional_coevolution_matrix_plot: Plot the eigenspectrum of the SCA positional coevolution...
In currocam/toolkit4pySCA: A set of useful functions for performing an Statistical Coupling Analysis from scratch in R and using pySCA
View source: R/SCA_positional_coevolution_matrix_eigenvalues_data.R
eigenspectrum_SCA_positional_coevolution_matrix_plot R Documentation
Plot the eigenspectrum of the SCA positional coevolution matrix (Cij~)
and 10 trials of matrix randomization for comparison. This graph is used
to choose the number of significant eigenmodes
Description
Plot the eigenspectrum of the SCA positional coevolution matrix (Cij~)
and 10 trials of matrix randomization for comparison. This graph is used
to choose the number of significant eigenmodes
Usage
eigenspectrum_SCA_positional_coevolution_matrix_plot(db)
Arguments
db
Pickle pySCA
currocam/toolkit4pySCA documentation built on April 7, 2022, 8:17 p.m.
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View source: R/SCA_positional_coevolution_matrix_eigenvalues_data.R
| eigenspectrum_SCA_positional_coevolution_matrix_plot | R Documentation |
Plot the eigenspectrum of the SCA positional coevolution matrix (Cij~) and 10 trials of matrix randomization for comparison. This graph is used to choose the number of significant eigenmodes
Description
Plot the eigenspectrum of the SCA positional coevolution matrix (Cij~) and 10 trials of matrix randomization for comparison. This graph is used to choose the number of significant eigenmodes
Usage
eigenspectrum_SCA_positional_coevolution_matrix_plot(db)
Arguments
db |
Pickle pySCA |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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