Generating Surrogate Brain Maps

Base Implementation

Base(x, D[, deltas, kernel, pv, nh, …])

Base implementation of map generator.

Sampled Implementation

Sampled(x, D, index[, ns, pv, nh, knn, b, …])

Sampling implementation of map generator.

Variogram Evaluation

base_fit(x, D[, nsurr, return_data])	Evaluate variogram fits for Base class.
sampled_fit(x, D, index[, nsurr, return_data])	Evaluate variogram fits for Sampled class.

Smoothing Kernels

exp(d)	Exponentially decaying kernel which truncates at e^{-1}.
gaussian(d)	Gaussian kernel which truncates at one standard deviation.
invdist(d)	Inverse distance kernel.
uniform(d)	Uniform (i.e., distance independent) kernel.

Creating Memory-Mapped Arrays

txt2memmap(dist_file, output_dir[, …])	Export distance matrix to memory-mapped array.
load_memmap(filename)	Load a memory-mapped array.

Statistical Methods

pearsonr(X, Y)	Multi-dimensional Pearson correlation between rows of X and Y.
pairwise_r(X[, flatten])	Compute pairwise Pearson correlations between rows of X.
nonparp(stat, dist)	Compute two-sided non-parametric p-value.