1. Numerical Python
Tom LeFebvre

2. Numerical Python
Since Python is an interpreted language, we need better performance particularly when crunching numbers.
Advantages: High-level language allows very fast development
Disadvantages: Not always intuitive
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Numerical Python

3. Numerical Python Numerical Python operates on “multiarrays”
One line of Numerical Python processes one or more whole arrays, not just one number.
Currently NumPy is implemented as an “extension” to Python. But soon it will be an intrinsic part of Python
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Numerical Python

4. Importing Numeric >>> from Numeric import *
You must import the Numeric module before using Numerical Python
import Numeric or
>>> from Numeric import *
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Numerical Python

5. Making Numeric Arrays >>> a = array ([0, 1, -2, 6, -5])
>>> b = arrayrange(10)
>>> b
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Numerical Python

6. Multi-dimensional Arrays
>>> a = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
>>> a
>>> a.shape
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Numerical Python

7. Creating Special Arrays
>>> BunchaZeros = zeros((4, 4))
>>> BunchaZeros
>>> BunchaOnes = ones((4, 4))
>>> BunchaOnes
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Numerical Python

8. Manipulating Arrays >>> BunchaThrees = BunchaOnes * 3
>>> f = arrayrange(0, 100, 5)
>>> c = (f - 32) * 5 / 9
>>> c
>>> c = (f - 32) * 5 / 9.0
>>> c
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Numerical Python

9. Array Slicing Slicing Operator “[:]” array[start : stop : increment]
array - a Numeric Python array
start - begin here including this index
stop - end here but do not include this index
increment - skip this many
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Numerical Python

10. Slicing Arrays >>> a = arrayrange(10) >>> a
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Numerical Python

11. Slicing Multi-dimensional Arrays
>>> b = reshape(arrayrange(9), (3, 3))
>>> b
>>> b[0, 0]
>>> b [2, 1]
>>> b[-1, -1]
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Numerical Python

12. Slicing Multi-dimensional Arrays
>>> b
>>> b[0:1, 0]
>>> b[0:2, 0:2]
>>> b [:]
>>> b[::2]
>>> b[::-1]
>>> b[::-1, ::-1]
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Numerical Python

13. Some Useful Functions >>> a = arrayrange(10) >>> a
>>> add.reduce(a)
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Numerical Python

14. Logical Functions - makes 0s or 1s
>>> b = reshape(arrayrange(25), (5, 5))
>>> b
>>> less (b, 12)
>>> greater(b, 7)
>>> less_equal(b, 10)
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Numerical Python

15. Array Functions - where()
“where” is the Numerical Python “if” statement
where(condition, true value, false value)
>>> b
>>> c = where (less(b, 12), 0, b)
>>> c
Note: 0 is false, everything else is true
Sept , 2002
Numerical Python

16. Array Functions - clip()
clip(array, min, max)
>>> b
>>> d = clip(b, 5, 15)
>>> d
Sept , 2002
Numerical Python