Installation & Usage

Installation: aloe

The Jupyter notebooks used for making this documentation depend on the aloe package, which supplies some basic utilities for Kikuchi pattern analysis.

For normal installation of the aloe package, run the following command in the aloebsd directory:

python setup.py

Installation of the development version, i.e. python links to the code directly in the downloaded aloebsd directory:

python setup.py develop

Uninstall development version:

python setup.py develop --uninstall

Jupyter Notebooks Tips & Tricks

https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/

http://arogozhnikov.github.io/2015/11/29/using-fortran-from-python.html

We often use some standard initialization code in almost all files of this documentation. This includes matplotlib, numpy and image display.

[1]:

%matplotlib inline
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np

# display images from www or local dir
from IPython.core.display import Image, display

[2]:

# display image from www https://xkcd.com/353/
display(Image(url='https://imgs.xkcd.com/comics/python.png', width=400))

[3]:

# example for image display from a local directory, make the image larger than screen
display(Image(filename='../data/patterns/GaN_HX_2.png', width=600, unconfined=True))
../_images/usage_usage_4_0.png

pythreejs Installation

git clone https://github.com/jovyan/pythreejs.git
cd pythreejs
pip install -e .
jupyter nbextension install --py --sys-prefix pythreejs
jupyter nbextension enable --py --sys-prefix pythreejs

Numpy

Column Vectors vs. Row Vectors

Rememeber, in numpy the innermost array is the fastest changing. Written like below, we have a vector as a 3x1 matrix (column) or 1x3 matrix (row) with shapes (3,1) and (1,3), repsectively. In an n x m matrix, we have n rows of m columns, so n corresponds to “y” (vertical in an image) and m corresponds to “x” (horizontal in image).

https://docs.scipy.org/doc/numpy-1.13.0/reference/internals.html#multidimensional-array-indexing-order-issues

[4]:

column_vector = np.array([[1,2,3]]).T
print(column_vector.shape)

(3, 1)

[5]:

row_vector = np.array([[1,2,3]])
print(row_vector.shape)

(1, 3)

GitHub

Workflow: make private fork and contribute via pull requests:

https://stackoverflow.com/questions/10065526/github-how-to-make-a-fork-of-public-repository-private