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Doing stereology
Doing stereology












doing stereology

The method lacks a formulation for estimating errors during the unfolding procedure.The use of the histogram also implies that we cannot obtain a complete description of the grain size distribution. The issue is that no method exists to find an optimal number of classes and this has to be set by the user.

doing stereology

There is a trade-off here because the smaller the number of classes, the better the numerical stability of the method, but the worse the approximation of the targeted distribution and vice versa.

  • Due to the use of the histogram, the number of classes determines the accuracy and success of the method.
  • To apply the method, the grains should be at least approximately equiaxed, which is normally fulfilled in recrystallized grains. This never holds for polycrystalline rocks.
  • It assumes that grains are non-touching spheres uniformly distributed in a matrix (e.g.
  • The method presents several limitations for its use in rocks Its main use (in geosciences) is to estimate the volume fraction of a specific range of grain sizes. The method is distribution-free, meaning that no assumption is made upon the type of statistical distribution, making the method very versatile. It is a stereological method that approximates the actual grain size distribution from the histogram of the apparent grain size distribution.

    doing stereology

    read_csv( filepath, sep = ' \t')ĭataset = 2 * np. # Import the example dataset filepath = 'C:/Users/marco/Documents/GitHub/GrainSizeTools/grain_size_tools/DATA/data_set.txt' dataset = pd.














    Doing stereology