a collection of generally useful routines (and experimental algorithms :)

INCLUDING:

• general maths (most functions support both scalars and list/array-likes)
  • factorials
  • fast sum of series 1,2,3,4,5 ... N
  • number of sequences of N size taken from a set of K size
  • number of places a sequence of length N can be subdivided
  • round N to nearest power of B
  • convert a power of B, N, to an exponent of B, such that B**E == N
  • find common denominator
  • find all integers that divide evenly into N
  • linear/spline interpolation of a 1d series of values
  • binary representation of a number
• spatial maths
  • subclassable Grid type
  • grid snapping and 'is-in-cell'
  • polar/cartesian transform
  • polar distance
  • calculate triple of weights based on position in triangle
• randomization
  • return true P% of the time
  • weighted sampling from a set of items
  • fill weighted boxes in a roughly even way
  • randomly dispense contents of a box
  • convert nested percentage weights to flat 0..1 weights
  • dice roll (single, and iterative/infinite)
  • chain iterator, which yields values while percentage chance of success rolls succeed, and stops as soon as they fail. Like OHRRPGCE 'chain attack/ chain %' option
• misc
  • find numeric limits of data types (builtin types or simple numpy types)
  • sort sequence according to template
  • reverse of zip (flat sequence a,b,c,a,b,c,a,b,c -> a,b,c tuples)
  • easily read every line or every byte of a file
  • calculate minimum number of bits required to store a given integer.
  • quickly set multiple attributes on an object
  • Metadata class for easy management of metadata, with yaml serialization support.

REQUIREMENTS:

just Python 2.5, as far as I know.

pyYAML is required if you want to de/serialize metadata from/to YAML.

having NumPy installed will make certain parts of the API more flexible and much faster, though. (eg. sum of series 1,2,3,4,5...N can be calculated using a single polynomial evaluation)

Matplotlib might be eventually required for generating function plots in docs. it will not be required for just using ion.