Tools of the Modeling trade (QM, not catwalk)

Shyue Ping Ong

It’s not just about quantum mechanics

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The four levels of attainment

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Jedi Master

Jedi Knight

Padawan

Youngling

Does things “manually”. Lots of mistakes (e.g., typos, calculations that need to be repeated, etc. Takes months to do a basic project.

Knows way around the command line. Use some basic shell scripting. Maybe even a little programming to make some tasks easier.

Mastered most of the tools of the trade. Can write sophisticated shell/programming scripts to automate calculations, plot results, etc. Most PhDs get to this level (hopefully).

Conceptualizes entire software frameworks that are reusable and extendable by other users.

The most important command in Unix

•  man sed •  man awk •  man find •  man grep •  man head •  man tail •  man less •  man …

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“man” is short for manual

Some common Unix commands (other than your typical cp, mv, cd, ls)

grep Searches any given input files, selecting lines that match one or more patterns.

cat Reads files sequentially, writing them to the standard output

sed Reads the specified files, modifying the input as specified by a list of commands.

tail Displays last part of a file head Displays start of a file find Recursively descends the directory

tree, evaluating an expression in terms of each file in the tree.

less View file in terminal

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Unix shells

Many types of Unix shell available, but broadly falls into

•  Bourne shell – de facto standard •  C shell – uses C-like syntax

Pick one that suits you and just set all your resources to go into that shell by default.

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Shell scripts

Next level beyond just typing commands in the terminal

Writing scripts to execute sequence of commands, with some control flow where necessary

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# Descending into a directory structure # and running some commands in each directory cwd=`pwd` for dir in `find . –type d` do cd $dir <execute some other commands> cd $cwd done

Control flow

Specification of the order in which the individual statements, instructions or function calls of an imperative program are executed or evaluated.

Two broad-types: •  Conditional: if-else, case-switch, etc. •  Loops: for, while, etc.

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Pros and Cons of Shell Scripts

Pros •  Ubiquitous •  Quick and dirty •  Useful for short programs / scripts with

a little bit of control flow

Cons

•  Very error-prone, especially with more complex programs

•  Doing even simple math is ugly (don’t even bother trying to do matrix math or anything more complex)

•  Difficult to extend and build on

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Beyond shell scripts

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Pros and Cons of Programming Languages

Pros •  Far more powerful than shell •  Popular ones come with extensive libraries that makes complex math

and plotting etc. easier •  Usually comes with support tools (compilers, debuggers, IDEs, etc.)

that helps reduce bugs, or at the very least, make them easier to find. •  Proper use allows the development of extensible packages and

libraries

Cons

•  Compiled languages require an additional compilation step •  Additional learning curve •  Not all languages are supported on all systems (though this is usually

not an issue with the popular ones)

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Which programming language should I choose?

Short answer – Whichever one you are most comfortable with. Long answer – Depends on what you need it for.

•  If performance is critical (e.g., a DFT code), you probably have to go with compiled languages like C and Fortran.

•  If speed of development and prototyping outweighs raw performance, interpreted / scripting languages like Python and Perl are generally easier to get into.

For this class, we will exclusively use Python.

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What is ?

General-purpose, high-level programming language Design emphasizes code readability Supports multiple programming paradigms (OOP, imperative, functional, procedural) Dynamically typed, automatic memory management and large standard library Available on almost all platforms

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public class Hello { public static void main(String[] args) { System.out.println("Hello World!"); } }

#include <iostream> int main() { std::cout << "Hello World!" << std::endl; return 0; }

Java

C++

print("Hello World!”)

Python

Scientific computing with Python

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User-friendly and efficient numerical routines such as routines for numerical integration and optimization.

Fundamental package for numerical computation. Defines array and matrix types and basic operations on them.

High-performance, easy to use data structures.

Publication-quality 2D plotting as well as rudimentary 3D plotting

Rich interactive interface, letting you quickly process data and test ideas.

Python Resources

Python documentation https://www.python.org/doc/

Numpy docs http://docs.scipy.org/doc/numpy/reference/

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Beyond simple scripts – Libraries for Computational Materials Science

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https://wiki.fysik.dtu.dk/ase/ https://www.pymatgen.org

http://www.aflowlib.org/

Python Materials Genomics (pymatgen)

Core materials analysis powering the Materials Project

• Defines core extensible Python objects for materials data representation.

• Provides a robust and well-documented set of structure and thermodynamic analysis tools relevant to many applications.

• Establishes an open platform for researchers to collaboratively develop sophisticated analyses of materials data.

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Overview of Pymatgen

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Example usage

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Final word on Programming

A little investment in learning a programming language can yield big dividends in your efficiency as a materials modeler.

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Prep for Lab2

In Lab2, you will come face-to-face with a practical example of how using a programming language can make performing a sizable number of calculations much easier. The scripts are relatively simple and makes use of only Python’s standard library. They offer but a small glimpse of what is possible. Start your journey by going through the simple Python tutorial at http://www.python.org.

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