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defmodule Fib do | |
def fib(0) do 0 end | |
def fib(1) do 1 end | |
def fib(n) do fib(n-1) + fib(n-2) end | |
end | |
IO.puts Fib.fib(10) |
defmodule Fib do
defp fib(0) do 0 end
defp fib(1) do 1 end
defp fib(n) when n>=0 do
fib(n-1) + fib(n-2)
end
def fibo(x) do
for n<-0..x-1 , do: fib(n)
end
end
Output:
iex(1)>Fib.fibo(4)
[0, 1, 1, 2]
An idiomatic take on this topic :)
defmodule Fib do
def fib(a, b, n) do
case n do
0 ->
a
_ ->
fib(b, a+b, n-1)
end
end
end
# Console Output
IO.puts Fib.fib(1,1,7)
Another approach that returns the entire sequence as a list.
defmodule Fibonacci do
def find(nth) do
list = [1, 1]
fib(list, nth)
end
def fib(list, 2) do
Enum.reverse(list)
end
def fib(list, n) do
fib([hd(list) + hd(tl(list))] ++ list, n - 1)
end
end
Usage:
> find 7
[1, 1, 2, 3, 5, 8, 13]
A little optimization to @dhc02's approach, which removes ++
operation to list as it's less performant and uses pattern matching for finding the first two elements of the list.
defmodule Fibonacci do
def find(nth) do
list = [1, 1]
fib(list, nth)
end
def fib(list, 2) do
Enum.reverse(list)
end
def fib(list, n) do
[first_elem, second_elem | _] = list
fib([first_elem + second_elem | list], n - 1)
end
end
My two takes using dynamic programming:
defmodule FibDynamicProgramming do
def fib(n) do
cache = %{0 => 0, 1 => 1}
cache =
Enum.reduce(2..n, cache, fn
i, acc ->
Map.put(acc, i, acc[i-2] + acc[i-1])
end)
cache[n]
end
end
IO.inspect(FibDynamicProgramming.fib(10))
55
defmodule FibDynamicProgrammingAgent do
use Agent
def start_link(_) do
Agent.start_link(fn -> %{} end, name: __MODULE__)
end
def fib(n) do
put(0, 0)
put(1, 1)
for i <- 2..n do
put(i, get(i-2) + get(i-1))
end
get(n)
end
defp get(n), do: Agent.get(__MODULE__, fn state -> state[n] end)
defp put(n, val), do: Agent.update(__MODULE__, fn state -> Map.put(state, n, val) end)
end
FibDynamicProgrammingAgent.start_link(nil)
IO.inspect(FibDynamicProgrammingAgent.fib(10))
55
My take on the issue, heavily inspired by @luizdamim:
defmodule Fibonacci.Map do
def compute(n) do
compute(2, n, %{0 => 0, 1 => 1})
end
def compute(n, target, map) when n == target do
map[n - 1] + map[n - 2]
end
def compute(n, target, map) do
value = map[n - 1] + map[n - 2]
newMap = Map.put(map, n, value)
compute(n + 1, target, newMap)
end
end
@edoardocostantinidev in your examples, does Map function works as same in python or c++? i never try Elixir and im learning from scratch.
My take with tail call optimization:
defmodule Fibonacci do
def nth(n) when n <= 1, do: n
def nth(n) do
fib(n - 2, 1, 0)
end
defp fib(0, minus_1, minus_2) do
minus_1 + minus_2
end
defp fib(n, minus_1, minus_2) do
fib(n - 1, minus_1 + minus_2, minus_1)
end
end
I'd never put my version in lol
#!/usr/bin/env elixir
defmodule Fibonacci do
def nth([n]) when is_binary(n), do: nth(String.to_integer(n))
def nth(n) when n < 1, do: {:error, :undefined}
def nth(1), do: 0
def nth(n), do: nth(1, 0, n - 2)
def nth(last, _last_last, 0), do: last
def nth(last, last_last, current), do: nth(last + last_last, last, current - 1)
end
# inline "tests"
0 = Fibonacci.nth(1)
2 = Fibonacci.nth(4)
21 = Fibonacci.nth(9)
IO.puts Fibonacci.nth(System.argv())
defmodule Fibonacci do
def find(n) do
list = [1, 0]
fib(list, n)
end
def fib(_list, n) when n < 0 do
[]
end
def fib(_list, 0) do
[0]
end
def fib(list, 1) do
list
end
def fib(list, n) do
[first_elem, second_elem | _] = list
fib([first_elem + second_elem | list], n - 1)
end
end
10 |> Fibonacci.find() |> IO.inspect()
defmodule Fib do
def run(a, b, n) do
case n do
1 ->
b
_ ->
run(b, a + b, n - 1)
end
end
end
Fib.run(0,1,10) |> IO.puts()
This one is tail call optimized :)