mango.application.shale.convertShaleHist2dToTernary

mango.application.shale.convertShaleHist2dToTernary(histData, invalidProportionMethod=0, cropRange=None, cropIndex=None)

Returns a (N,4) shaped numpy.array of ternary (mineral,pore,organic,frequency) data. The input histData is 2D histogram data generated from a pair of micro-porosity segmented images. The x-axis data is assumed to be the CH2I2 differenced data.

Parameters:

• histData (mango.application.io.HistData) – 2D histogram data of micro-porosity segmentation image pair (micro-porosity segmentation of CH2I2-image minus dry-after-image image and micro-porosity segmentation of I2-image minus dry-image). Assumes that the CH2I2 data is the x-axis of the histData.
• invalidProportionMethod (int) – Method used to resolve data points where pore_percent+organic_percent exceeds 100%.

Return type:

numpy.ndarray

Return type:

A (N,4) shaped numpy.ndarray, where N=num_x_bins*num_y_bins. Each row of the returned array is (mineral-percent, pore-percent, organic-percent, count).