Script demonstrating the characterization of strain localization.

It reads the second example microstructure and an HDF5 file, the latter containing the displacement field measurements at discrete time steps.
That HDF5 file is huge, so it is not added to the git repository.

scripts/run_simulation_geometry.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import os
+from os import path
+from os.path import join
+
+import numpy as np
+from scipy.stats import kurtosis
+import matplotlib.pyplot as plt
+from skimage.io import imread
+from skimage.morphology import dilation
+
+from grains.simulation import nature_of_deformation
+from grains.dic import DIC
+from grains import HAS_TABLES
+
+
+# Directory where we read from and write to
+script_dir = os.path.dirname(__file__)  # absolute path to the directory the script is in
+data_dir = join(script_dir, 'data')
+
+################################################################################
+#  Determine the ratio of intergranular and intragranular strain localization  #
+################################################################################
+
+# Crop data which belongs to the testing device (the indices were obtained using:
+# `selected = plt.ginput(-1, timeout=-1))`
+cropped_region = np.s_[800:2175, 860:3000]
+
+# 1) Load the segmented image, representing the grains of the microstructure
+microstructure = imread(join(data_dir, '2_labelimage.tiff'))
+microstructure = microstructure[cropped_region]
+
+# 2) Bands in the neighborhood of the interfaces
+band_width = 3
+microstructure = dilation(microstructure)
+
+# 3) Process a series of full-field measurements (DIC)
+dic_data = join(data_dir, 'FULLTEST_fields.hdf')
+MEASUREMENT_COUNT = 382
+PERCENTILE_COUNT = 10
+
+# 4) User settings
+show_plots = True
+save_plots = False
+time_instances = range(MEASUREMENT_COUNT)
+
+# Analysis
+matrix = np.zeros((PERCENTILE_COUNT+1, MEASUREMENT_COUNT))
+kurt_band = []
+kurt_bulk = []
+visualize = show_plots or save_plots
+if not path.isfile(dic_data):
+    raise Exception('Measurement dataset {0} not found.'.format(dic_data))
+if not HAS_TABLES:
+    raise ImportError('The PyTables package is needed to load the dataset.')
+import tables
+measurement = tables.open_file(dic_data).root.res
+for time_instance in time_instances:
+    print('Time instance:', time_instance)
+    # a) Load the displacement field
+    displacement_field = measurement[time_instance, cropped_region[0], cropped_region[1], :]
+    u = displacement_field[:, :, 0]
+    v = displacement_field[:, :, 1]
+    # b) Obtain the equivalent strain field
+    dic = DIC(u, v)
+    strain_tensor = dic.strain('Green-Lagrange')
+    vonMises_strain = DIC.equivalent_strain(strain_tensor, 'von Mises')
+    # c) Characterize the deformation in the current time step
+    boundary_strain, bulk_strain, bands = nature_of_deformation(microstructure,
+                                                                vonMises_strain,
+                                                                band_width, visualize=visualize)
+    if save_plots:
+        plt.savefig(join(data_dir, 't_' + str(time_instance) + '.png'), dpi=500)
+    if show_plots:
+        plt.show(block=True)
+    normalized_boundary_strain = boundary_strain[bands] / max(boundary_strain[bands])
+    normalized_bulk_strain = bulk_strain[~bands] / max(bulk_strain[~bands])
+    quantiles = np.percentile(normalized_boundary_strain, range(0, 101, PERCENTILE_COUNT))
+    matrix[:, time_instance] = quantiles
+    kurt_band.append(kurtosis(normalized_boundary_strain))
+    kurt_bulk.append(kurtosis(normalized_bulk_strain))