An even distribution number is a number such that if you select any of it's digits at random the probability of it being any particular value (e.g. 0
or 6
) is the same, \$\frac1{10}\$. A precise definition is given later on.
Here are a few examples:
- \$\frac{137174210}{1111111111} =0.\overline{1234567890}\$ is an even distribution number.
- \$2.3\$ is not an even distribution number since 7 of the digits
1456789
never appear and all but two of the digits are0
. - \$1.023456789\$ may look like it's an even distribution number, but for this challenge we count all the digits after the decimal point, including all the
0
s. So nearly all the digits are0
, and the probability of selecting anything else is \$0\$.
Precisely speaking if we have a sequence of digits \$\{d_0^\infty\}\$ then the "probability" of a particular digit \$k\$ in that sequence is:
\$ \displaystyle P(\{d_0^\infty\},k) = \lim_{n\rightarrow\infty}\dfrac{\left|\{i\in[0\dots n], d_i=k\}\right|}{n} \$
That is if we take the prefixes of size \$n\$ and determine the probability that a digit selected uniformly from that prefix is \$k\$, then the overall probability is the limit as \$n\$ goes to infinity.
Thus an even distribution number is a number where all the probabilities for each \$k\$, converge and give \$\frac1{10}\$.
Now a super fair number is a number \$x\$ such that for any rational number \$r\$, \$x+r\$ is an even distribution number.
Task
Output a super fair number. Since super fair numbers are irrational you should output as an infinite sequence of digits. You can do this using any of the sequence defaults.
This is code-golf so the goal is to minimize the size of your source code as measured in bytes.