miscellaneous factZ - The online home of Rufus Pollock

Stuff I’ve found useful for numpy/scipy:

• http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/python/arrays.html
• http://www.scipy.org/Cookbook/Recarray
• http://www.scipy.org/NumPy_for_Matlab_Users
• http://www.scipy.org/Tentative_NumPy_Tutorial

Ways of Storing and Accessing Data

recarray

From docs:

numpy.recarray: Construct an ndarray that allows field access using attributes.

Arrays may have a data-types containing fields, analagous to columns in a spread sheet. An example is [(x, int), (y, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr[’x'] and arr[’y']. Record arrays allow the fields to be accessed as members of the array, using arr.x and arr.y.

>>> from numpy import *
>>> num = 2
>>> a = recarray(num, formats='i4,f8,f8',names='id,x,y')
>>> a['id'] = [3,4]
>>> a['id']
array([3, 4])
>>> a = rec.fromrecords([(35,1.2,7.3),(85,9.3,3.2)], names='id,x,y')       # fromrecords is in the numpy.rec submodule
>>> a['id']
array([35, 85])

HDF5, PYTables and h5py

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