Richard O'Keefe r@oknz @end|ng |rom gm@||@com
Mon Dec 16 05:06:12 CET 2019

```The obvious question is "why?"
If you just want to sort stuff, ?sort and ?order tell you about the
sorting methods available in R.
If you want to translate this specific algorithm into R for some reason,
(a) if you don't know enough about array processing in R to do this yourself,
how are you going to know enough to *use* it?
(b) There is a fundamental difference between arrays in Python and R which
means that the algorithm as presented cannot possibly work in R.

Here's the difference.
>>> def f(x): x[1] = 5
...
>>> a = [1,2,3]
>>> f(a)
>>> a
[1, 5, 3]

Arrays in Python are collections of *variables* and if you pass one to
a function,
the function can *change* the very same array that you passed in.

> f <- function (x) x[2] <- 5
> a <- c(1,2,3)
> f(a)
> a
[1] 1 2 3

This is a completely different result.
Arrays in R are collections of *values*.  R acts *as if*
x[i] <- e
really meant
x <- get("[<-")(x, i, e)
computing a whole new array and assigning it to x.
There is in fact an actual function that does this update,
and get("[<-") returns it.
I said "as if", because there are things you can do to make the actual
implementation much more efficient, but the *observable behaviour*
is as if the entire array were replaced.
Note that this has nothing to do with how the two languages pass
arguments to functions,
it's about what an array *is* and how you work with them.

The bottom line is that if you *could* translate this algorithm from
Python to R,
you *shouldn't*.

321

On Sun, 15 Dec 2019 at 14:56, Александр Дубровский
<dubrovvsskkyy using gmail.com> wrote:
>
> # Iterative Merge sort (Bottom Up)
>
> # Iterative mergesort function to
> # sort arr[0...n-1]
> def mergeSort(a):
>
>     current_size = 1
>
>     # Outer loop for traversing Each
>     # sub array of current_size
>     while current_size < len(a) - 1:
>
>         left = 0
>         # Inner loop for merge call
>         # in a sub array
>         # Each complete Iteration sorts
>         # the iterating sub array
>         while left < len(a)-1:
>
>             # mid index = left index of
>             # sub array + current sub
>             # array size - 1
>             mid = left + current_size - 1
>
>             # (False result,True result)
>             # [Condition] Can use current_size
>             # if 2 * current_size < len(a)-1
>             # else len(a)-1
>             right = ((2 * current_size + left - 1,
>                     len(a) - 1)[2 * current_size
>                           + left - 1 > len(a)-1])
>
>             # Merge call for each sub array
>             merge(a, left, mid, right)
>             left = left + current_size*2
>
>         # Increasing sub array size by
>         # multiple of 2
>         current_size = 2 * current_size
>
> # Merge Function
> def merge(a, l, m, r):
>     n1 = m - l + 1
>     n2 = r - m
>     L = [0] * n1
>     R = [0] * n2
>     for i in range(0, n1):
>         L[i] = a[l + i]
>     for i in range(0, n2):
>         R[i] = a[m + i + 1]
>
>     i, j, k = 0, 0, l
>     while i < n1 and j < n2:
>         if L[i] > R[j]:
>             a[k] = R[j]
>             j += 1
>         else:
>             a[k] = L[i]
>             i += 1
>         k += 1
>
>     while i < n1:
>         a[k] = L[i]
>         i += 1
>         k += 1
>
>     while j < n2:
>         a[k] = R[j]
>         j += 1
>         k += 1
>
>
> # Driver code
> a = [12, 11, 13, 5, 6, 7]
> print("Given array is ")
> print(a)
>
> mergeSort(a)
>
> print("Sorted array is ")
> print(a)
>
> # Contributed by Madhur Chhangani [RCOEM]
>
>         [[alternative HTML version deleted]]
>
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