Tutorial slides (PDF) - Clemson University

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Upload DNA Seq. {{=form}} web2py and Views {{=form}}
web2py and Authentication authenticatio n
Page 1 and 2:
Python for Scientific and High Perf
Page 3 and 4:
Overview We seek to cover: Python l
Page 5 and 6:
1. Introduction Introductions Tutor
Page 7 and 8:
Why Use Python for Scientific Compu
Page 9 and 10:
Please login to the Tutorial Enviro
Page 11 and 12:
Interpreters CPython Standard pytho
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CPython Interpreter Notes Compilati
Page 15 and 16:
Built-in Numeric Types int, float,
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Gotchas with Built-in Numeric Types
Page 19 and 20:
Built-in Sequence Types str, unicod
Page 21 and 22:
Built-in Sequence & Mapping Type Go
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Control Structures for - iterative
Page 25 and 26:
List Comprehensions List Comprehens
Page 27 and 28:
File I/O Basics Most I/O in Python
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Let's write ten integers to disk wi
Page 31 and 32:
Modules import - load module, defin
Page 33 and 34:
N-dimensional homogeneous arrays (n
Page 35 and 36:
Slicing Arrays >>> a = np.array([[1
Page 37 and 38:
SciPy Extends NumPy with common sci
Page 39 and 40:
Python Threading Python threads rea
Page 41 and 42:
Implementation Example: Calculating
Page 43 and 44:
Subprocess The subprocess module al
Page 45 and 46:
Calculating pi with multiprocessing
Page 47 and 48:
mpi4py wraps your native mpi prefer
Page 49 and 50:
from mpi4py import MPI import numpy
Page 51 and 52:
Python Best Practices for Performan
Page 53 and 54: Outline a massively parallel Python
Page 55 and 56: GPAW Strong-scaling Results
Page 57 and 58: KS-DFT is a complex algorithm!
Page 59 and 60: Performance Mantra People are able
Page 61 and 62: NumPy - Memory How big is your bina
Page 63 and 64: NumPy - FLOPS WARNING: If you make
Page 65 and 66: Profiling Mixed Python-C code Numbe
Page 67 and 68: Parallel Python Interpreter and Deb
Page 69 and 70: Profiling Mixed Python-C code Flat
Page 71 and 72: Python Interface to BLACS and ScaLA
Page 79 and 80: Python Interface in BLACS and ScaLA
Page 81 and 82: Python Interface in BLACS and ScaLA
Page 83 and 84: The Bad & Ugly: NumPy cross-compile
Page 85 and 86: Python for plotting and visualizati
Page 87 and 88: From Lib to App (overview) Numerica
Page 89 and 90: From Lib to App (overview) Storage
Page 91 and 92: Ruby on Rails Django TurboGears Pyl
Page 93 and 94: matplotlib gallery
Page 95 and 96: application1 application 2 applicat
Page 97 and 98: application 1 application=” dna
Page 99 and 100: web2py and Dispatching hostnam e
Page 101 and 102: web2py and Dispatching controller
Page 103: Upload DNA Seq. {{=form}} web2py a
Page 107 and 108: web2py web based IDE web based IDE
Page 109 and 110: Before we start download web2py fro
Page 111 and 112: Define some algorithms def find_gen
Page 113 and 114: Define actions in controllers/defau
Page 115 and 116: Try it
Page 117 and 118: Define Actions in controllers/defau
Page 119 and 120: Try it
Page 121 and 122: Yet More Resources Tau http://www.c
Page 123 and 124: Let's review!
Page 125: This work is supported in part by t
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