This example demonstrates the clustering of different textures in the Ti-64 alloy system using GSH to quantify orientation in 2-point statistics. Microstructures were synthetically generated using DREAM.3D.
Contributors: Noah Paulson, Matthew Priddy, David Brough, Dipen Patel
%matplotlib inline
%load_ext autoreload
%autoreload 2
import plot_pc_map as pltmap
import plot_linkage_check as plc
from constants import constC = const()
names_cal = C['names_cal']
set_id_cal = C['set_id_cal']
strt_cal = C['strt_cal']
ns_cal = C['ns_cal']
dir_cal = C['dir_cal']
names_val = C['names_val']
set_id_val = C['set_id_val']
strt_val = C['strt_val']
ns_val = C['ns_val']
dir_val = C['dir_val']
bc = 'bc1'
prop = 'stiffness'The plot below demonstrates the clustering of 8 Ti-64 textures in the first two principal components.
pcA = 0
pcB = 1
pltmap.pltmap(ns_val, set_id_val, pcA, pcB)
For other examples and implementation details check out PyMKS.