How magnesium accommodates local deformation incompatibility: a high-resolution digital image correlation study

Companion python jupyter notebook for interactive data visualization and exploration

This notebook is made available to facilitate the visualization and exploration of the HRDIC data in the manuscript "How magnesium accommodates local deformation incompatibility: a high-resolution digital image correlation study", accepted for publication in Acta Materialia in May 2017.

The dataset can be downloaded from Zenodo as either a text file or a NumPy binary file.

This notebook uses a helper module called hrdic_analysis_short.py which can be downloaded from the same GitHub repository. In addition the notebook requires numpy and matplotlib. This notebook was created using python 3.5.0 numpy 1.11.3 and matplotlib 2.0.0 and it worked well when we used it.

Loading data



In [1]:

    
import numpy as np
import matplotlib.pyplot as plt
import hrdic_analysis_short as hrdic
from ipywidgets import interact, interactive, fixed
%matplotlib notebook

The dataset is loaded with the command hrdic.DeformationMapFast which requires a data directory and filename as inputs. Below we have used './' for current directory and the name of the datafile in Zenodo. The datafile is available as a text file (AZ31.txt) or a NumpPy binary file (AZ31.npy). The '.npy' file loads faster but there is also an alternative function for reading the '.txt' file instead.



In [2]:

    
#using the .txt is much slower than the binary .npy
#def_map=hrdic.DeformationMap('./','AZ31.txt')
def_map=hrdic.DeformationMapFast('./','AZ31.npy')

The edges of the map can be cropped to remove edge artifacts:



In [3]:

    
du11_cropped= def_map.du11[220:-10,30:-175]
du22_cropped= def_map.du22[220:-10,30:-175]
max_shear_cropped= def_map.max_shear[220:-10,30:-175]

Interactive visualization



In [4]:

    
f,ax=plt.subplots(1,1,figsize=(9,5))
image_map=ax.imshow(du11_cropped,
                    vmin=0,
                    vmax=0.09,
                    cmap='viridis',
                    interpolation='bilinear')
plt.colorbar(image_map);

The interactive view of the displacement gradient components:



In [7]:

    
interactive(hrdic.scrub, fig=fixed(image_map), fmap=fixed(def_map),
            component=('du11','du22','du12','du21','Max shear'),
            colourmap= ('viridis','bwr'),
            cmin=(-0.5,1.9,0.01),
            cmax=(0.0,2.0,0.01))