Numerical Computing in Python - Cornell University
[Pages:47]Numpy and Scipy
Numerical Computing in Python
1
What is Numpy?
? Numpy, Scipy, and Matplotlib provide MATLABlike functionality in python.
? Numpy Features:
Typed multidimentional arrays (matrices) Fast numerical computations (matrix math) High-level math functions
2
Why do we need NumPy
Let's see for ourselves!
3
Why do we need NumPy
? Python does numerical computations slowly. ? 1000 x 1000 matrix multiply
Python triple loop takes > 10 min. Numpy takes ~0.03 seconds
4
Logistics: Versioning
? In this class, your code will be tested with:
Python 2.7.6 Numpy version: 1.8.2 Scipy version: 0.13.3 OpenCV version: 2.4.8
? Two easy options:
Class virtual machine (always test on the VM) Anaconda 2 (some assembly required)
5
NumPy Overview
1. Arrays 2. Shaping and transposition 3. Mathematical Operations 4. Indexing and slicing 5. Broadcasting
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Arrays
Structured lists of numbers.
? Vectors ? Matrices ? Images ? Tensors ? ConvNets
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Arrays
Structured lists of numbers.
? Vectors ? Matrices ? Images ? Tensors ? ConvNets
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