View source: R/localization_score.R

Given the adjacency matrix of a graph and a set of features on that graph, ranks those features (f) by the equation f((e^kA-I)/k)f, which measures how much those features are localized in the graph. Calculates the p-value of this score by permuting the columns of the feature matrix.

1 2 | ```
localization_score(adj_matrix, f, num_perms = 1000, num_cores = 1,
perm_estimate = F)
``` |

`adj_matrix` |
a (preferrably sparse) binary matrix of adjacency between the columns of f |

`f` |
a numeric vector or matrix specifying one or more functions with support on the set of points whose significance will be assesed in the simplicial complex. Each column corresponds to a point and each row specifies a different function. |

`num_perms` |
number of permutations used to build the null distribution for each feature. By default is set to 1000. |

`num_cores` |
integer specifying the number of cores to be used in the computation. By default only one core is used. |

`perm_estimate` |
boolean indicating whether normal distribution parameters should be determined from num_perms permutations to estimate the p-value. By default is set to FALSE. |

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