Python in a Nutshell, 2nd Edition

Array Objects

Numeric supplies a type array that represents a grid of items. An array object a has a given number of dimensions, known as its rank, up to some arbitrarily high limit (normally 30, when Numeric is built with default options). A scalar (i.e., a single number) has rank 0, a vector has rank 1, a matrix has rank 2, and so forth.

Typecodes

The values in the grid cells of an array object, known as the elements of the array, are homogeneous, meaning they are all of the same type, and all element values are stored within one memory area. This contrasts with a list, where items may be of different types, each stored as a separate Python object. This means a Numeric array occupies far less memory than a Python list with the same number of items. The type of a’s elements is encoded as a’s typecode, a one-character string, as shown in Table 16-2. Factory functions that build array instances (covered in Factory Functions) take a typecode argument that is one of the values in Table 16-2.

Table 16-2. Typecodes for Numeric arrays

Typecode	C type	Python type	Synonym
'c'	char	str (length 1)	Character
'b'	unsigned char	int	UnsignedInt8
'1'	signed char	int	Int8
's'	short	int	Int16
'w'	unsigned short	int	UnsignedInt16
'i'	int	int	Int32
'u'	unsigned	int	UnsignedInt32
'l'	long	int	Int
'f'	float	float	Float32
'F'	Two floats	complex	Complex32
'd'	double	float	Float
'D'	Two doubles	complex	Complex
'O'	PyObject*	any	PyObject

Numeric supplies readable attribute names for each typecode, as shown in the last column of Table 16-2. Numeric also supplies, ...