If True the function will return the position of the midpoints and With that name containing the Saltykov output. If the user specifies a name, the function will store a csv file Occupied by the grain fraction up to that diameter. If the user specifies a diameter, the function will return the volume If not declared,Ĭalc_vol : positive scalar or None, optional The number of bins/classes of the histogram. The actual 3D grain size population, either in uni- or multimodal populations. Size fraction as well as to obtain a qualitative view of the appearance of The Saltykov method is optimal to estimate the volume of a particular grain Of apparent diameters measured in a thin section using a Saltykov-typeĪlgorithm (Saltykov 1967 Sahagian and Proussevitch 1998). """ Estimate the actual (3D) distribution of grain size from the population The Saltykov method reconstructs the 3D histogram, not every apparent diameter in the actual one as this is mathematically impossible). You cannot obtain an estimate of the actual average grain size (3D) as individual data is lost when using the histogram (i.e.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. 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. 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.
0 kommentar(er)
