spacepy.toolbox.dist_to_list

spacepy.toolbox.dist_to_list(func, length, min=None, max=None)

Convert a probability distribution function to a list of values

This is a deterministic way to produce a known-length list of values matching a certain probability distribution. It is likely to be a closer match to the distribution function than a random sampling from the distribution.

Parameters:

funccallable

function to call for each possible value, returning

probability density at that value (does not need to be normalized.)

lengthint

number of elements to return

minfloat

minimum value to possibly include

maxfloat

maximum value to possibly include

Examples

>>> import matplotlib
>>> import numpy
>>> import spacepy.toolbox as tb
>>> gauss = lambda x: math.exp(-(x ** 2) / (2 * 5 ** 2)) / (5 * math.sqrt(2 * math.pi))
>>> vals = tb.dist_to_list(gauss, 1000, -numpy.inf, numpy.inf)
>>> print vals[0]
-16.45263...
>>> p1 = matplotlib.pyplot.hist(vals, bins=[i - 10 for i in range(21)], facecolor='green')
>>> matplotlib.pyplot.hold(True)
>>> x = [i / 100.0 - 10.0 for i in range(2001)]
>>> p2 = matplotlib.pyplot.plot(x, [gauss(i) * 1000 for i in x], 'red')
>>> matplotlib.pyplot.draw()