When counting integers in binary, if you put a (binary) point to the right of the count then the column immediately to the left denotes a digit with a multiplier of <math>2^0</math>; the digit in the next column to the left has a multiplier of <math>2^1</math>; and so on.
You can also have binary digits to the right of the “point”, just as in the decimal number system. In that case, the digit in the place immediately to the right of the point has a weight of <math>2^{-1}</math>, or <math>1/2</math>.
If you take the integer binary count of the first table, and ''reflect'' the digits about the binary point, you end up with '''the van der Corput sequence of numbers in base 2'''.
<br> [[File:Van der corput distribution.png|400|thumb|right|Distribution of 2500 points each: Van der Corput (top) vs pseudorandom]] Members of the sequence lie within the interval <math>0 \leq x < 1</math>. Points within the sequence tend to be evenly distributed which is a useful trait to have for [[wp:Monte Carlo method|Monte Carlo simulations]].
This sequence is also a superset of the numbers representable by the "fraction" field of [[wp:IEEE 754-1985|an old IEEE floating point standard]]. In that standard, the "fraction" field represented the fractional part of a binary number beginning with "1." e.g. 1.101001101.
'''Hint'''
A ''hint'' at a way to generate members of the sequence is to modify a routine used to change the base of an integer:
<lang python>>>> def base10change(n, base):
digits = []
while n:
n,remainder = divmod(n, base)
digits.insert(0, remainder)
return digits
>>> base10change(11, 2)
[1, 0, 1, 1]</lang>
the above showing that <code>11</code> in decimal is <math>1\times 2^3 + 0\times 2^2 + 1\times 2^1 + 1\times 2^0</math>.<br>
Reflected this would become <code>.1101</code> or <math>1\times 2^{-1} + 1\times 2^{-2} + 0\times 2^{-3} + 1\times 2^{-4}</math>