Apr 24, 2014 · 2:00 p.m.– 3:30 p.m. · 130 Lewis Library, New Media Center
Instructor: Eliot Feibush, Computational Scientist, PPPL
Thursday, April 24, 2014 ∙ 2:00-3:30 pm ∙ New Media Center, 130 Lewis Science Library
Overview: This mini-course will introduce participants to array programming and math functions within Python's NumPy module.
NumPy implements efficient multi-dimensional arrays for Python. The mini-course will present elements and features of NumPy and how it can be used in numerical applications. The course includes hands-on exercises so participants can become familiar with programming techniques. We will use the workstations in the New Media Center. Emphasis will be on getting started with NumPy and understanding its fundamentals so attendees can continue on their own.
The course is intended for researchers working with data generated by simulations or acquired from experiments and other studies. Experience with Python Lists, Tuples, and the Math module is strongly recommended background for the session.
Eliot Feibush is a Computational Scientist in the Computational Plasma Physics Group at the Princeton Plasma Physics Laboratory. He specializes in developing scientific visualizations and graphics software. He has written many python programs to select, analyze, convert, and display data from various applications and disciplines. Prior to PPPL, he has worked in medical imaging, architectural design, and geo-spatial analysis.
Space is limited to 25 participants, so register today at the Training website, www.princeton.edu/training or contact Andrea Rubinstein either by email, firstname.lastname@example.org or at 258-1397.
May 16, 2014 · 8:00 a.m.– 6:00 p.m. · 120 Lewis Science Library
The PICSciE Symposium on Big Data Science aims to engage Princeton's research computing community in sharing their experiences and research results which are computational- and data-intensive in nature.
This one-day symposium is also an opportunity to address various "big data" challenges at Princeton and its institutional partners as well as to identify common resources such as hardware, software, and support that could be shared across campus to enable progress. It will bring together computational scientists and researchers from different disciplines working on topics ranging from neurosciences to digital humanities.
There will be presentations, poster sessions and open discussion forums during the symposium.
Keynote Speaker: David W. Hogg, Center for Cosmology and Particle Physics, New York University
More information can be found at:
May 19, 2014 · 10:00 a.m.– 4:30 p.m. · Room 346, Visualization Lab
Python is an open-source, general-purpose programming language that is widely used in scientific and numeric computing. This six-hour course will introduce Python from the ground up, starting with the installation of a scientific distribution onto your laptop. We will introduce Python's syntax, language style, and its fundamental scientific toolkit : Numpy, Scipy, and Matplotlib via a series of exercises and demos. We will then import real data, visualise it, and perform analyses to help you really start to use these packages for your scientific work. In the space of six hours, we aim to take you from discussion of Python's basic principles, to writing functional, productive code. Please bring your laptop - the aim is to use a familiar computer, and to leave with a fully operational Python stack.