Physics 212, 2017: Lab 4
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Back to Physics 212, 2017: Computational Modeling.
We are playing even more with Python now!
- Python Student Guide, Ch 2.4, 2.5, 2.6, 2.7, and 3.all
- Python Student Guide, Ch 5.1 and 5.8
- Python Student Guide, Ch 4 -- first lab
If you have completed this, convince yourself that memory pre-allocation and vector math make things faster. For this:
- Try to calculate sine of a very long array element by element in a for loop, or on a whole array at once. Which one is faster and why?
- Create a 1000x1000 matrix of numbers from 1 to 1,000,000 three different ways: (i) a single range, sliced as a matrix, (ii) a pre-allocated matrix, filled up by a double for loop, and (iii) 1000 bumpy arrays created as ranges (1...1000), (1001...2000), etc. and stacked on top of each other as a vstack in a for loop. Which one is faster and why?
Finally also check what is faster: using np.arange vs. range when defining a for loop. For this, make a very long for loop that does nothing, and see how long it takes. What is faster and why?
