Introducing PowerSpectrumAnalysis of hypercolumn structure
Introducing PowerSpectrumAnalysis of hypercolumn structure

A new file hypercolumns.py has been introduced for analysis hypercolumn
structure in preference maps. Currently, there is a single class,
PowerSpectrumAnalysis that uses the FFT power spectrum to estimate the
hypercolumn distance. Given the output of PinwheelAnalysis, this
function will also compute the pinwheel density and pi-pinwheel density
map metric. Together with imagen.analysis.cyclic_similarity_index, this
implements the analysis used in Stevens et al. (J. Neuroscience 2013).

ioam/featuremapper