the code below outputs 0.0. is this because of the overflow? how to avoid it? if not, why?
p ((1..100000).map {rand}).reduce :*
I was hoping to speed up this code:
p r.reduce(0) {|m, v| m + (Math.log10 v)}
and use this instead:
p Math.log10 (r.reduce :*)
but apparently this is not always possible...
The values produced by rand are all between 0.0 and 1.0. This means that on each multiplication, your number gets smaller. So by the time you have multiplied 1000 of them, it is probably indistinguishable from 0.
At some point, ruby will take your number to be so small that it is 0. for instance: 2.0e-1000 # => 0
Every multiplication reduces your number by about 1/21, so after about 50 of them, you are down 1/250, and after 100000 (actually, after about 700) you have underflowed the FP format itself, see here.
Ruby provides the BigDecimal class, which implements accurate floating point arithmetic.
require 'bigdecimal'
n = 100
decimals = n.times.map { BigDecimal.new rand.to_s }
result = decimals.reduce :*
result.nonzero?.nil? # returns nil if zero, self otherwise
# => false
result.precs # [significant_digits, maximum_significant_digits]
# => [1575, 1764]
Math.log10 result
# => -46.8031931083014
It is a lot slower than native floating point numbers, however. With n = 100_000, the decimals.reduce :* call went on for minutes on my computer before I finally interrupted it.
Related
So I was running some benchmarks in Ruby 2.4.0 and realized that
(1...1000000000000000000000000000000).sum
calculates immediately whereas
(1...1000000000000000000000000000000).inject(:+)
takes so long that I just aborted the operation. I was under the impression that Range#sum was an alias for Range#inject(:+) but it seems like that is not true. So how does sum work, and why is it so much faster than inject(:+)?
N.B. The documentation for Enumerable#sum (which is implemented by Range) does not say anything about lazy evaluation or anything along those lines.
Short answer
For an integer range :
Enumerable#sum returns (range.max-range.min+1)*(range.max+range.min)/2
Enumerable#inject(:+) iterates over every element.
Theory
The sum of integers between 1 and n is called a triangular number, and is equal to n*(n+1)/2.
The sum of integers between n and m is the triangular number of m minus the triangular number of n-1, which is equal to m*(m+1)/2-n*(n-1)/2, and can be written (m-n+1)*(m+n)/2.
Enumerable#sum in Ruby 2.4
This property in used in Enumerable#sum for integer ranges :
if (RTEST(rb_range_values(obj, &beg, &end, &excl))) {
if (!memo.block_given && !memo.float_value &&
(FIXNUM_P(beg) || RB_TYPE_P(beg, T_BIGNUM)) &&
(FIXNUM_P(end) || RB_TYPE_P(end, T_BIGNUM))) {
return int_range_sum(beg, end, excl, memo.v);
}
}
int_range_sum looks like this :
VALUE a;
a = rb_int_plus(rb_int_minus(end, beg), LONG2FIX(1));
a = rb_int_mul(a, rb_int_plus(end, beg));
a = rb_int_idiv(a, LONG2FIX(2));
return rb_int_plus(init, a);
which is equivalent to:
(range.max-range.min+1)*(range.max+range.min)/2
the aforementioned equality!
Complexity
Thanks a lot to #k_g and #Hynek-Pichi-Vychodil for this part!
sum
(1...1000000000000000000000000000000).sum
requires three additions, a multiplication, a substraction and a division.
It's a constant number of operations, but multiplication is O((log n)²), so Enumerable#sum is O((log n)²) for an integer range.
inject
(1...1000000000000000000000000000000).inject(:+)
requires 999999999999999999999999999998 additions!
Addition is O(log n), so Enumerable#inject is O(n log n).
With 1E30 as input, inject with never return. The sun will explode long before!
Test
It's easy to check if Ruby Integers are being added :
module AdditionInspector
def +(b)
puts "Calculating #{self}+#{b}"
super
end
end
class Integer
prepend AdditionInspector
end
puts (1..5).sum
#=> 15
puts (1..5).inject(:+)
# Calculating 1+2
# Calculating 3+3
# Calculating 6+4
# Calculating 10+5
#=> 15
Indeed, from enum.c comments :
Enumerable#sum method may not respect method redefinition of "+"
methods such as Integer#+.
In ruby, some large numbers are larger than infinity. Through binary search, I discovered:
(1.0/0) > 10**9942066.000000001 # => false
(1.0/0) > 10**9942066 # => true
RUBY_VERSION # => "2.3.0"
Why is this? What is special about 109942066? It doesn't seem to be an arbitrary number like 9999999, it is not close to any power of two (it's approximately equivelent to 233026828.36662442).
Why isn't ruby's infinity infinite? How is 109942066 involved?
I now realize, any number greater than 109942066 will overflow to infinity:
10**9942066.000000001 #=> Infinity
10**9942067 #=> Infinity
But that still leaves the question: Why 109942066?
TL;DR
I did the calculations done inside numeric.c's int_pow manually, checking where an integer overflow (and a propagation to Bignum's, including a call to rb_big_pow) occurs. Once the call to rb_big_pow happens there is a check whether the two intermediate values you've got in int_pow are too large or not, and the cutoff value seems to be just around 9942066 (if you're using a base of 10 for the power). Approximately this value is close to
BIGLEN_LIMIT / ceil(log2(base^n)) * n ==
32*1024*1024 / ceil(log2(10^16)) * 16 ==
32*1024*1024 / 54 * 16 ~=
9942054
where BIGLEN_LIMIT is an internal limit in ruby which is used as a constant to check if a power calculation would be too big or not, and is defined as 32*1024*1024. base is 10, and n is the largest power-of-2 exponent for the base that would still fit inside a Fixnum.
Unfortunately I can't find a better way than this approximation, due to the algorithm used to calculate powers of big numbers, but it might be good enough to use as an upper limit if your code needs to check validity before doing exponentiation on big numbers.
Original question:
The problem is not with 9942066, but that with one of your number being an integer, the other one being a float. So
(10**9942066).class # => Bignum
(10**9942066.00000001).class # => Float
The first one is representable by a specific number internally, which is smaller than Infinity. The second one, as it's still a float is not representable by an actual number, and is simply replaced by Infinity, which is of course not larger than Infinity.
Updated question:
You are right that there seem to be some difference around 9942066 (if you're using a 64-bit ruby under Linux, as the limits might be different under other systems). While ruby does use the GMP library to handle big numbers, it does some precheck before even going to GMP, as shown by the warnings you can receive. It will also do the exponentiation manually using GMP's mul commands, without calling GMP's pow functions.
Fortunately the warnings are easy to catch:
irb(main):010:0> (10**9942066).class
=> Bignum
irb(main):005:0> (10**9942067).class
(irb):5: warning: in a**b, b may be too big
=> Float
And then you can actually check where these warnings are emitted inside ruby's bignum.c library.
But first we need to get to the Bignum realm, as both of our numbers are simple Fixnums. The initial part of the calculation, and the "upgrade" from fixnum to bignum is done inside numeric.c. Ruby does quick exponentiation, and at every step it checks whether the result would still fit into a Fixnum (which is 2 bits less than the system bitsize: 62 bits on a 64 bit machine). If not, it will then convert the values to the Bignum realm, and continues the calculations there. We are interested at the point where this conversion happens, so let's try to figure out when it does in our 10^9942066 example (I'm using x,y,z variables as present inside the ruby's numeric.c code):
x = 10^1 z = 10^0 y = 9942066
x = 10^2 z = 10^0 y = 4971033
x = 10^2 z = 10^2 y = 4971032
x = 10^4 z = 10^2 y = 2485516
x = 10^8 z = 10^2 y = 1242758
x = 10^16 z = 10^2 y = 621379
x = 10^16 z = 10^18 y = 621378
x = OWFL
At this point x will overflow (10^32 > 2^62-1), so the process will continue on the Bignum realm by calculating x**y, which is (10^16)^621378 (which are actually still both Fixnums at this stage)
If you now go back to bignum.c and check how it determines if a number is too large or not, you can see that it will check the number of bits required to hold x, and multiply this number with y. If the result is larger than 32*1024*1024, it will then fail (emit a warning and does the calculations using basic floats).
(10^16) is 54 bits (ceil(log_2(10^16)) == 54), 54*621378 is 33554412. This is only slightly smaller than 33554432 (by 20), the limit after which ruby will not do Bignum exponentiation, but simply convert y to double, and hope for the best (which will obviously fail, and just return Infinity)
Now let's try to check this with 9942067:
x = 10^1 z = 10^0 y = 9942067
x = 10^1 z = 10^1 y = 9942066
x = 10^2 z = 10^1 y = 4971033
x = 10^2 z = 10^3 y = 4971032
x = 10^4 z = 10^3 y = 2485516
x = 10^8 z = 10^3 y = 1242758
x = 10^16 z = 10^3 y = 621379
x = 10^16 z = OWFL
Here, at the point z overflows (10^19 > 2^62-1), the calculation will continue on the Bignum realm, and will calculate x**y. Note that here it will calculate (10^16)^621379, and while (10^16) is still 54 bits, 54*621379 is 33554466, which is larger than 33554432 (by 34). As it's larger you'll get the warning, and ruby will only to calculations using double, hence the result is Infinity.
Note that these checks are only done if you are using the power function. That's why you can still do (10**9942066)*10, as similar checks are not present when doing plain multiplication, meaning you could implement your own quick exponentiation method in ruby, in which case it will still work with larger values, although you won't have this safety check anymore. See for example this quick implementation:
def unbounded_pow(x,n)
if n < 0
x = 1.0 / x
n = -n
end
return 1 if n == 0
y = 1
while n > 1
if n.even?
x = x*x
n = n/2
else
y = x*y
x = x*x
n = (n-1)/2
end
end
x*y
end
puts (10**9942066) == (unbounded_pow(10,9942066)) # => true
puts (10**9942067) == (unbounded_pow(10,9942067)) # => false
puts ((10**9942066)*10) == (unbounded_pow(10,9942067)) # => true
But how would I know the cutoff for a specific base?
My math is not exactly great, but I can tell a way to approximate where the cutoff value will be. If you check the above calls you can see the conversion between Fixnum and Bignum happens when the intermediate base reaches the limit of Fixnum. The intermediate base at this stage will always have an exponent which is a power of 2, so you just have to maximize this value. For example let's try to figure out the maximum cutoff value for 12.
First we have to check what is the highest base we can store in a Fixnum:
ceil(log2(12^1)) = 4
ceil(log2(12^2)) = 8
ceil(log2(12^4)) = 15
ceil(log2(12^8)) = 29
ceil(log2(12^16)) = 58
ceil(log2(12^32)) = 115
We can see 12^16 is the max we can store in 62 bits, or if we're using a 32 bit machine 12^8 will fit into 30 bits (ruby's Fixnums can store values up to two bits less than the machine size limit).
For 12^16 we can easily determine the cutoff value. It will be 32*1024*1024 / ceil(log2(12^16)), which is 33554432 / 58 ~= 578525. We can easily check this in ruby now:
irb(main):004:0> ((12**16)**578525).class
=> Bignum
irb(main):005:0> ((12**16)**578526).class
(irb):5: warning: in a**b, b may be too big
=> Float
Now we hate to go back to our original base of 12. There the cutoff will be around 578525*16 (16 being the exponent of the new base), which is 9256400. If you check in ruby, the values are actually quite close to this number:
irb(main):009:0> (12**9256401).class
=> Bignum
irb(main):010:0> (12**9256402).class
(irb):10: warning: in a**b, b may be too big
=> Float
Note that the problem is not with the number but with the operation, as told by the warning you get.
$ ruby -e 'puts (1.0/0) > 10**9942067'
-e:1: warning: in a**b, b may be too big
false
The problem is 10**9942067 breaks Ruby's power function. Instead of throwing an exception, which would be a better behavior, it erroneously results in infinity.
$ ruby -e 'puts 10**9942067'
-e:1: warning: in a**b, b may be too big
Infinity
The other answer explains why this happens near 10e9942067.
10**9942067 is not greater than infinity, it is erroneously resulting in infinity. This is a bad habit of a lot of math libraries that makes mathematicians claw their eyeballs out in frustration.
Infinity is not greater than infinity, they're equal, so your greater than check is false. You can see this by checking if they're equal.
$ ruby -e 'puts (1.0/0) == 10**9942067'
-e:1: warning: in a**b, b may be too big
true
Contrast this with specifying the number directly using scientific notation. Now Ruby doesn't have to do math on huge numbers, it just knows that any real number is less than infinity.
$ ruby -e 'puts (1.0/0) > 10e9942067'
false
Now you can put on as big an exponent as you like.
$ ruby -e 'puts (1.0/0) > 10e994206700000000000000000000000000000000'
false
I'm trying to write a method that returns the nth prime number.
I've worked out a solution but the problem is in my method. I create a large array of numbers that seems to process super slow. (1..104729).to_a to be exact. I chose 104729 because the max n can be is 10000 and the 10000th integer is 104729. I'm looking for a way to optimize my method.
Is 104729 is too large a value? Is there a way to write this so that I'm not creating a large array?
Here's the method:
def PrimeMover(num)
def is_prime(x)
i = 0
nums = (2..x).to_a
while nums[i] < nums.max
if x % nums[i] != 0
i += 1
else
return false
end
end
return true
end
primes_arr = (3..104729).to_a.select {|y| is_prime(y)}
primes_arr[num]
end
require "prime"
def find_prime(nth)
Prime.take(nth).last
end
Combine Ruby's built-in prime library, and a lazy enumerator for performance:
require 'prime'
(1...100_000).lazy.select(&:prime?).take(100).to_a
Or simply, as highlighted by Arturo:
Prime.take(100)
You can use Ruby's built in #prime? method, which seems pretty efficient.
The code:
require 'prime'
primes_arr = (3..104729).to_a.select &:prime?
runs in 2-3 seconds on my machine, which I find somewhat acceptable.
If you need even better performance or if you really need to write your own method, try implementing the Sieve of Erathostenes. Here are some Ruby samples of that: http://rosettacode.org/wiki/Sieve_of_Eratosthenes#Ruby
Here's an optimal a trial division implementation of is_prime without relying on the Prime class:
A prime number is a whole number divisible only by 1 and itself, and 1 is not prime. So we want to know if x divides into anything less than x and greater than 1. So we start the count at 2, and we end at x - 1.
def prime?(x)
return false if x < 2
2.upto(x - 1) do |n|
return false if (x % n).zero?
end
true
end
As soon as x % n has a remainder, we can break the loop and say this number is not prime. This saves you from looping over the entire range. If all the possible numbers were exhausted, we know the number is prime.
This is still not optimal. For that you would need a sieve, or a different detection algorithm to trial division. But it's a big improvement on your code. Taking the nth up to you.
I am trying to create a program that will test whether a value is prime, but I don't know how. This is my code:
class DetermineIfPrime
def initialize (nth_value)
#nth_value = nth_value
primetest
end
def primetest
if Prime.prime?(#nth_value)
puts ("#{#nth_value} is prime")
else
puts ("This is not a prime number.")
end
rescue Exception
puts ("#{$!.class}")
puts ("#{$!}")
end
end
And every time I run that it returns this.
NameError
uninitialized constant DetermineIfPrime::Prime
I tried other ways to do the job, but I think this is the closest I can get.
I also tried this:
class DetermineIfPrime
def initialize (nth_value)
#nth_value = nth_value
primetest
end
def primetest
for test_value in [2, 3, 5, 7, 9, 11, 13] do
if (#nth_value % test_value) == 0
puts ("#{#nth_value} is not divisible by #{test_value}")
else
puts ("This is not a prime number since this is divisible by #{test_value}")
break
end
end
end
end
Or am I just doing something wrong?
Ruby has built in method to check if number is prime or not.
require 'prime'
Prime.prime?(2) #=> true
Prime.prime?(4) #=> false
def is_prime?(num)
return false if num <= 1
Math.sqrt(num).to_i.downto(2).each {|i| return false if num % i == 0}
true
end
First, we check for 0 and 1, as they're not prime. Then we basically just check every number less than num to see if it divides. However, as explained here, for every factor greater than the square root of num, there's one that's less, so we only look between 2 and the square root.
Update
def is_prime?(num)
return if num <= 1
(2..Math.sqrt(num)).none? { |i| (num % i).zero? }
end
The error you are getting is because you haven't required Primein your code, You need to do require Prime in your file.
One cool way I found here, to check whether a number is prime or not is following:
class Fixnum
def prime?
('1' * self) !~ /^1?$|^(11+?)\1+$/
end
end
10.prime?
From an algorithmic standpoint, checking if a number is prime can be done by checking all numbers up to and including (rounding down to previous integer) said number's square root.
For example, checking if 100 is prime involves checking everything up to 10.
Checking 99 means only going to 9.
** Another way to think about it **
Each factor has a pair (3 is a factor of 36, and 3's pair is 12).
The pair is on the other side of the square root (square root of 6 is 36, 3 < 6, 12 > 6).
So by checking everything until the square root (and not going over) ensures you check all possible factors.
You can make it quicker by having a list of prime numbers to compare, as you are doing. If you have a maximum limit that's reasonably small, you could just have a list of primes and do a direct lookup to see if that number is prime.
def is_prime?(num)
Math.sqrt(num).floor.downto(2).each {|i| return false if num % i == 0}
true
end
lol sorry for resurrecting a super old questions, but it's the first one that came up in google.
Basically, it loops through possible divisors, using the square root as the max number to check to save time on very large numbers.
In response to your question, while you can approach the problem by using Ruby's Prime I am going to write code to answer it on its own.
Consider that all you need to do is determine a factor that is smaller than the integer's square root. Any number larger than the integer's square root as a factor requires a second factor to render the number as the product. (e.g. square root of 15 is approx 3.8 so if you find 5 as a factor it is only a factor with the factor pair 3 and 5!!)
def isPrime?(num)
(2..Math.sqrt(num)).each { |i| return false if num % i == 0}
true
end
Hope that helps!!
(To first answer the question: yes, you are doing something wrong. As BLUEPIXY mentions, you need to put require 'prime' somewhere above the line that calls Prime.prime?. Typically on line 1.)
Now, a lot of answers have been given that don't use Prime.prime?, and I thought it might be interesting to benchmark some of them, along with a possible improvement of my own that I had in mind.
###TL;DR
I benchmarked several solutions, including a couple of my own; using a while loop and skipping even numbers performs best.
Methods tested
Here are the methods I used from the answers:
require 'prime'
def prime1?(num)
return if num <= 1
(2..Math.sqrt(num)).none? { |i| (num % i).zero? }
end
def prime2?(num)
return false if num <= 1
Math.sqrt(num).to_i.downto(2) {|i| return false if num % i == 0}
true
end
def prime3?(num)
Prime.prime?(num)
end
def prime4?(num)
('1' * num) !~ /^1?$|^(11+?)\1+$/
end
prime1? is AndreiMotinga's updated version. prime2? is his original version (with the superfluous each method removed). prime3? is Reboot's, using prime library. prime4? is Saurabh's regex version (minus the Fixnum monkey-patch).
A couple more methods to test
The improvement I had in mind was to leverage the fact that even numbers can't be prime, and leave them out of the iteration loop. So, this method uses the #step method to iterate over only odd numbers, starting with 3:
def prime5?(num)
return true if num == 2
return false if num <= 1 || num.even?
3.step(Math.sqrt(num).floor, 2) { |i| return false if (num % i).zero? }
true
end
I thought as well that it might be interesting to see how a "primitive" implementation of the same algorithm, using a while loop, might perform. So, here's one:
def prime6?(num)
return true if num == 2
return false if num <= 1 || num.even?
i = 3
top = Math.sqrt(num).floor
loop do
return false if (num % i).zero?
i += 2
break if i > top
end
true
end
Benchmarks
I did a simple benchmark on each of these, timing a call to each method with the prime number 67,280,421,310,721. For example:
start = Time.now
prime1? 67280421310721
puts "prime1? #{Time.now - start}"
start = Time.now
prime2? 67280421310721
puts "prime2? #{Time.now - start}"
# etc.
As I suspected I would have to do, I canceled prime4? after about 60 seconds. Presumably, it takes quite a bit longer than 60 seconds to assign north of 6.7 trillion '1''s to memory, and then apply a regex filter to the result — assuming it's possible on a given machine to allocate the necessary memory in the first place. (On mine, it would seem that there isn't: I went into irb, put in '1' * 67280421310721, made and ate dinner, came back to the computer, and found Killed: 9 as the response. That looks like a SignalException raised when the process got killed.)
The other results are:
prime1? 3.085434
prime2? 1.149405
prime3? 1.236517
prime5? 0.748564
prime6? 0.377235
Some (tentative) conclusions
I suppose that isn't really surprising that the primitive solution with the while loop is fastest, since it's probably closer than the others to what's going on under the hood. It is a bit surprising that it's three times faster than Prime.prime?, though. (After looking at the source code in the doc it is less so. There are lots of bells and whistles in the Prime object.)
AndreiMotinga's updated version is nearly three times as slow as his original, which suggests that the #none? method isn't much of a performer, at least in this context.
Finally, the regex version might be cool, but it certainly doesn't appear to have much practical value, and using it in a monkey-patch of a core class looks like something to avoid entirely.
If you are going to use any Prime functions you must include the Prime library. This problem can be solved without the use of the prime library however.
def isPrime?(num)
(2..Math.sqrt(num)).each { |i|
if num % i == 0 && i < num
return false
end
}
true
end
Something like this would work.
Try this
def prime?(num)
2.upto(Math.sqrt(num).ceil) do |i|
break if num%i==0
return true if i==Math.sqrt(num).ceil
end
return false
end
So most of the answers here are doing the same thing in slightly different ways which is one of the cool things about Ruby, but I'm a pretty new student (which is why I was looking this up in the first place) and so here's my version with comment explanations in the code:
def isprime n # starting with 2 because testing for a prime means you don't want to test division by 1
2.upto(Math.sqrt(n)) do |x| # testing up to the square root of the number because going past there is excessive
if n % x == 0
# n is the number being called from the program
# x is the number we're dividing by, counting from 2 up to the square root of the number
return false # this means the number is not prime
else
return true # this means the number is prime
end
end
end
What's the best way to calculate if a byte has odd or even parity in Ruby? I've got a version working:
result = "AB".to_i(16).to_s(2).count('1').odd?
=> true
Converting a number to a string and counting the "1"s seems a poor way of calculating parity though. Any better methods?
I want to be able to calculate the parity of a 3DES key. Eventually, I'll want to convert even bytes to odd.
Thanks,
Dan
Unless what you have is not fast enough, keep it. It's clear and succinct, and its performance is better than you think.
We'll benchmark everything against array lookup, the fastest method I tested:
ODD_PARITY = [
false,
true,
true,
...
true,
false,
]
def odd_parity?(hex_string)
ODD_PARITY[hex_string.to_i(16)]
end
Array lookup computes the parity at a rate of 640,000 bytes per second.
Bowsersenior's C code computes parity at a rate of 640,000 bytes per second.
Your code computes parity at a rate of 284,000 bytes per second.
Bowsersenior's native code computes parity at a rate of 171,000 bytes per second.
Theo's shortened code computes parity at a rate of 128,000 bytes per second.
Have you taken a look at the RubyDES library? That may remove the need to write your own implementation.
To calculate parity, you can use something like the following:
require 'rubygems'
require 'inline' # RubyInline (install with `gem install RubyInline`)
class Fixnum
# native ruby version: simpler but slow
# algorithm from:
# http://graphics.stanford.edu/~seander/bithacks.html#ParityParallel
def parity_native
(((self * 0x0101010101010101) & 0x8040201008040201) % 0x1FF) & 1
end
class << self
# inline c version using RubyInline to create c extension
# 4-5 times faster than native version
# use as class method:
# Fixnum.parity(0xAB)
inline :C do |builder|
builder.c <<-EOC
int parity_c(int num) {
return (
((num * 0x0101010101010101ULL) & 0x8040201008040201ULL) % 0x1FF
) & 1;
}
EOC
end
end
def parity
self.class.parity_c(self)
end
def parity_odd?
1 == parity
end
def parity_even?
0 == parity
end
end
0xAB.parity # => 1
0xAB.parity_odd? # => true
0xAB.parity_even? # => false
(0xAB + 1).parity # => 0
According to simple benchmarks, the inline c version is 3-4 times faster than the native ruby version
require 'benchmark'
n = 10000
Benchmark.bm do |x|
x.report("inline c") do
n.times do
(0..255).map{|num| num.parity}
end
end
x.report("native ruby") do
n.times do
(0..255).map{|num| num.parity_native}
end
end
end
# inline c 1.982326s
# native ruby 7.044330s
Probably a lookup table of an Array with 255 entries would be fastest "In Ruby" solution.
In C I would mask and shift. Or if I have SSE4 I would use the POPCNT instruction with inline assembler. If you need this to be high performance write a native extension in C which does either of the above.
http://en.wikipedia.org/wiki/SSE4
How about using your original solution with memoization? This will only calculate once for each integer value.
class Fixnum
# Using a class variable for simplicity, and because subclasses of
# Fixnum—while very uncommon—would likely want to share it.
##parity = ::Hash.new{ |h,i| h[i] = i.to_s(2).count('1').odd? }
def odd_parity?
##parity[self]
end
def even_parity?
!##parity[self]
end
end
"AB".to_i(16).odd_parity?
#=> true
x = 'AB'.to_i(16)
p = 0
until x == 0
p += x & 1
x = x >> 1
end
puts p # => 5
which can be shortened to
x = 'AB'.to_i(16)
p = x & 1
p += x & 1 until (x >>= 1) == 0
if you want something that is unreadable ☺
I would construct a single table of 16 entries (as a 16 character table), corresponding to each nibble (half) of a bytes. Entries are 0,1,1,2,1,2,....4
To test your byte,
Mask out the left nibble and do a lookup, memorizing the number.
Do. a shift to the right by 4 and do a second lookup, adding the result number to the previous one to provide a sum.
Then test the low order bit from the sum. If it is 1, the byte is odd, if it is a 0, the byte is even. If result is even, you flip the high order bit, using the xor instruction.
THis lookup method is much faster than adding up the bits in a byte by single shifts.
email me for a simple function to do the parity for 8 bytes. 3DES uses 3 groups of 8 bytes.