rvect 0.1.0.0

Examples

To illustrate the usage of Rvect objects, the following examples contrast operations on Python lists and on Rvect objects.

1. Multiplying by a scalar

   >>> [1, 2, 3] * 2
   [1, 2, 3, 1, 2, 3]
   >>> Rvect([1, 2, 3]) * 2
   [2, 4, 6]

2. Adding a scalar

   >>> [1, 2, 3] + 2
   TypeError
   >>> Rvect([1, 2, 3]) + 2
   [3, 4, 5]

3. Multiplying two lists or vectors

   >>> [1, 2, 3] * [4, 5, 6]
   TypeError
   >>> Rvect([1, 2, 3]) * Rvect([4, 5, 6])
   [4, 10, 18]

4. Adding two lists or vectors

   >>> [1, 2, 3] + [4, 5, 6]
   [1, 2, 3, 4, 5, 6]
   >>> Rvect([1, 2, 3]) + Rvect([4, 5, 6])
   [5, 7, 9]

5. Binary logical operations on two lists or vectors

   >>> [True, True, False, False] and [True, False, True, False]
   [True, False, True, False]
   >>> list_and( [True, True, False, False], [True, False, True, False] )
   [True, False, False, False]
   >>> Rvect([True, True, False, False]).logical_and( Rvect([True, False, True, False]) )
   [True, False, False, False]

Notes

1. This module contains several functions that implement basic listwise operations (e.g., and, or, sum, product) on lists or tuples, in addition to the class (Rvect) that defines overloaded operators for these and other functions.

2. Whereas elements of an R vector must all be of the same type, the Rvect class has no such constraint–Rvect elements may be of any type, as with a Python list. The class does contain methods to coerce all elements to several specific types, however.

3. Because Python does not allow a class to define its own __not__ method, the command

   not Rvect()

   does not work as might be expected (that is, not as in R). Instead, there is a method named

   .logical_not()

   of an Rvect object that must be called instead.

4. Because Python implements the logical binary infix operations ‘and’, ‘or’, and ‘xor’ by calling __nonzero__ or __len__ on each object and then executing the Boolean logic itself, logical binary combination of Rvect objects cannot be done using the ‘and’, ‘or’, and ‘xor’ infix operators. Instead, the following functions are defined

   .logical_and(Rvect1, Rvect2, ...)
   .logical_or(Rvect1, Rvect2, ...)
   .logical_xor(...)

5. The special methods __and__, __or__, and __xor__, which correspond to the binary infix operators ‘&’, ‘|’, and ‘^’,are for binary, not logical, comparisons. In R, however, these infix operators peform logical comparisons. Therefore, the special methods have been implemented so that they convert their arguments to booleans, and therefore correspond to logical operators, and so operate similarly to the equivalent R operators. Thus, for Rvects a and b, the following two expressions are equivalent

   a.logical_and(b) a & b

   Both return a vector of booleans. As per the previous note, these are not equivalent to

   a and b

   which returns a single boolean value.

6. The 'list_...()' functions in this module allow operation on multiple lists, whereas the binary infix mathematical operators implemented for Rvect instances only allow operation on two objects. For example, multiple lists can be summed in parallel with

   list_sum(list1, list2, list3,...)

   However, the arguments to the 'list_...()' functions must all be lists of the same length, whereas the arguments to the Rvect methods may be other Rvect objects, lists, or scalars.