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Transform the following C implementation into R, maintaining the same output and logic.
#include <stdio.h> #include <stdlib.h> #include <math.h> #define foreach(a, b, c) for (int a = b; a < c; a++) #define for_i foreach(i, 0, n) #define for_j foreach(j, 0, n) #define for_k foreach(k, 0, n) #define for_ij for_i for_j #define for_ijk for_ij for_k #define _dim int n #define _swap(x, y) { typeof(x) tmp = x; ...
library(Matrix) A <- matrix(c(1, 3, 5, 2, 4, 7, 1, 1, 0), 3, 3, byrow=T) dim(A) <- c(3, 3) expand(lu(A))
Maintain the same structure and functionality when rewriting this code in R.
#include <stdlib.h> #include <stdarg.h> #include <stdio.h> #include <ctype.h> #include <string.h> typedef const char * String; typedef struct sTable { String * *rows; int n_rows,n_cols; } *Table; typedef int (*CompareFctn)(String a, String b); struct { CompareFctn compare; int column; int ...
tablesort <- function(x, ordering="lexicographic", column=1, reverse=false) { } tablesort(mytable, column=3)
Write the same algorithm in R as shown in this C implementation.
#include<math.h> #include<stdio.h> int main () { double inputs[11], check = 400, result; int i; printf ("\nPlease enter 11 numbers :"); for (i = 0; i < 11; i++) { scanf ("%lf", &inputs[i]); } printf ("\n\n\nEvaluating f(x) = |x|^0.5 + 5x^3 for the given inputs :"); for (i = 10; i >= 0; i-...
S <- scan(n=11) f <- function(x) sqrt(abs(x)) + 5*x^3 for (i in rev(S)) { res <- f(i) if (res > 400) print("Too large!") else print(res) }
Ensure the translated R code behaves exactly like the original C snippet.
#include<graphics.h> #include<stdlib.h> #include<stdio.h> #include<time.h> typedef struct{ double x,y; }point; void pythagorasTree(point a,point b,int times){ point c,d,e; c.x = b.x - (a.y - b.y); c.y = b.y - (b.x - a.x); d.x = a.x - (a.y - b.y); d.y = a.y - (b.x - a.x); e.x = d.x + ( b.x - a.x - (a...
pythtree <- function(ax,ay,bx,by,d) { if(d<0) {return()}; clr="darkgreen"; dx=bx-ax; dy=ay-by; x3=bx-dy; y3=by-dx; x4=ax-dy; y4=ay-dx; x5=x4+(dx-dy)/2; y5=y4-(dx+dy)/2; segments(ax,-ay,bx,-by, col=clr); segments(bx,-by,x3,-y3, col=clr); segments(x3,-y3,x4,-y4, col=clr); segments(x4,-y4,ax,-ay, col=cl...
Port the following code from C to R with equivalent syntax and logic.
#include <stdio.h> #include <string.h> typedef struct { char v[16]; } deck; typedef unsigned int uint; uint n, d, best[16]; void tryswaps(deck *a, uint f, uint s) { # define A a->v # define B b.v if (d > best[n]) best[n] = d; while (1) { if ((A[s] == s || (A[s] == -1 && !(f & 1U << s))) && (d + best[s] >= bes...
topswops <- function(x){ i <- 0 while(x[1] != 1){ first <- x[1] if(first == length(x)){ x <- rev(x) } else{ x <- c(x[first:1], x[(first+1):length(x)]) } i <- i + 1 } return(i) } library(iterpc) result <- NULL for(i in 1:10){ I <- iterpc(i, labels = 1:i, ordered = T) A <- ...
Rewrite the snippet below in R so it works the same as the original C code.
#include <stdio.h> unsigned int lpd(unsigned int n) { if (n<=1) return 1; int i; for (i=n-1; i>0; i--) if (n%i == 0) return i; } int main() { int i; for (i=1; i<=100; i++) { printf("%3d", lpd(i)); if (i % 10 == 0) printf("\n"); } return 0; }
largest_proper_divisor <- function(n){ if(n == 1) return(1) lpd = 1 for(i in seq(1, n-1, 1)){ if(n %% i == 0) lpd = i } message(paste0("The largest proper divisor of ", n, " is ", lpd)) return(lpd) } for (i in 1:100){ largest_proper_divisor(i) }
Can you help me rewrite this code in R instead of C, keeping it the same logically?
#include<stdio.h> #include<stdlib.h> int isprime( int p ) { int i; if(p==2) return 1; if(!(p%2)) return 0; for(i=3; i*i<=p; i+=2) { if(!(p%i)) return 0; } return 1; } int prime( int n ) { int p, pn=1; if(n==1) return 2; for(p=3;pn<n;p+=2) { if(isprime(p)) pn++; }...
library(primes) nth_prime(10001)
Write a version of this C function in R with identical behavior.
#include<stdio.h> #include<stdlib.h> int isprime( int p ) { int i; if(p==2) return 1; if(!(p%2)) return 0; for(i=3; i*i<=p; i+=2) { if(!(p%i)) return 0; } return 1; } int prime( int n ) { int p, pn=1; if(n==1) return 2; for(p=3;pn<n;p+=2) { if(isprime(p)) pn++; }...
library(primes) nth_prime(10001)
Translate the given C code snippet into R without altering its behavior.
#include<stdio.h> int main() { int num = 9876432,diff[] = {4,2,2,2},i,j,k=0; char str[10]; start:snprintf(str,10,"%d",num); for(i=0;str[i+1]!=00;i++){ if(str[i]=='0'||str[i]=='5'||num%(str[i]-'0')!=0){ num -= diff[k]; k = (k+1)%4; goto start; } for(j=i+1;str[j]!=00;j++) if(str[i]==str...
largest_LynchBell_number <- function(from, to){ from = round(from) to = round(to) to_chosen = to if(to > 9876432) to = 9876432 LynchBell = NULL range <- to:from range <- range[range %% 5 != 0] for(n in range){ splitted <- strsplit(toString(n), "")[[1]] if("0" %in% splitted | "5" ...
Generate a R translation of this C snippet without changing its computational steps.
#include<stdio.h> int main() { int num = 9876432,diff[] = {4,2,2,2},i,j,k=0; char str[10]; start:snprintf(str,10,"%d",num); for(i=0;str[i+1]!=00;i++){ if(str[i]=='0'||str[i]=='5'||num%(str[i]-'0')!=0){ num -= diff[k]; k = (k+1)%4; goto start; } for(j=i+1;str[j]!=00;j++) if(str[i]==str...
largest_LynchBell_number <- function(from, to){ from = round(from) to = round(to) to_chosen = to if(to > 9876432) to = 9876432 LynchBell = NULL range <- to:from range <- range[range %% 5 != 0] for(n in range){ splitted <- strsplit(toString(n), "")[[1]] if("0" %in% splitted | "5" ...
Maintain the same structure and functionality when rewriting this code in R.
#include <stdio.h> #include <stdlib.h> typedef struct func_t *func; typedef struct func_t { func (*fn) (func, func); func _; int num; } func_t; func new(func(*f)(func, func), func _) { func x = malloc(sizeof(func_t)); x->fn = f; x->_ = _; x->num = 0; ...
Y <- function(f) { (function(x) { (x)(x) })( function(y) { f( (function(a) {y(y)})(a) ) } ) }
Write the same code in R as shown below in C.
#include <stdio.h> #include <stdlib.h> #include <locale.h> int locale_ok = 0; wchar_t s_suits[] = L"♠♥♦♣"; const char *s_suits_ascii[] = { "S", "H", "D", "C" }; const char *s_nums[] = { "WHAT", "A", "2", "3", "4", "5", "6", "7", "8", "9", "10", "J", "Q", "K", "OVERFLOW" }; typedef struct { int suit, number, _s;...
pips <- c("2", "3", "4", "5", "6", "7", "8", "9", "10", "Jack", "Queen", "King", "Ace") suit <- c("Clubs", "Diamonds", "Hearts", "Spades") deck <- data.frame(pips=rep(pips, 4), suit=rep(suit, each=13)) shuffle <- function(deck) { n <- nrow(deck) ord <- sample(seq_len(n), size=n) deck[ord,] } deal <- functio...
Rewrite this program in R while keeping its functionality equivalent to the C version.
main(){printf("Code Golf");}
cat("Code Golf") cat(rlang::string(c(0x43, 0x6F, 0x64, 0x65, 0x20, 0x47, 0x6F, 0x6C, 0x66)))
Translate the given C code snippet into R without altering its behavior.
main(){printf("Code Golf");}
cat("Code Golf") cat(rlang::string(c(0x43, 0x6F, 0x64, 0x65, 0x20, 0x47, 0x6F, 0x6C, 0x66)))
Rewrite this program in R while keeping its functionality equivalent to the C version.
#include <stdint.h> #include <stdio.h> uint64_t factorial(uint64_t n) { uint64_t res = 1; if (n == 0) return res; while (n > 0) res *= n--; return res; } uint64_t lah(uint64_t n, uint64_t k) { if (k == 1) return factorial(n); if (k == n) return 1; if (k > n) return 0; if (k < 1 || n < ...
Lah_numbers <- function(n, k, type = "unsigned") { if (n == k) return(1) if (n == 0 | k == 0) return(0) if (k == 1) return(factorial(n)) if (k > n) return(NA) if (type == "unsigned") return((factorial(n) * factorial(n - 1)) / (factorial(k) * fac...
Please provide an equivalent version of this C code in R.
#include <stdint.h> #include <stdio.h> uint64_t factorial(uint64_t n) { uint64_t res = 1; if (n == 0) return res; while (n > 0) res *= n--; return res; } uint64_t lah(uint64_t n, uint64_t k) { if (k == 1) return factorial(n); if (k == n) return 1; if (k > n) return 0; if (k < 1 || n < ...
Lah_numbers <- function(n, k, type = "unsigned") { if (n == k) return(1) if (n == 0 | k == 0) return(0) if (k == 1) return(factorial(n)) if (k > n) return(NA) if (type == "unsigned") return((factorial(n) * factorial(n - 1)) / (factorial(k) * fac...
Change the programming language of this snippet from C to R without modifying what it does.
#include<stdlib.h> #include<stdio.h> int main () { int i; char *str = getenv ("LANG"); for (i = 0; str[i + 2] != 00; i++) { if ((str[i] == 'u' && str[i + 1] == 't' && str[i + 2] == 'f') || (str[i] == 'U' && str[i + 1] == 'T' && str[i + 2] == 'F')) { printf ("Uni...
if (any(grepl("UTF", toupper(Sys.getenv(c("LANG", "LC_ALL", "LC_CTYPE")))))) { cat("Unicode is supported on this terminal and U+25B3 is : \u25b3\n") } else { cat("Unicode is not supported on this terminal.") }
Keep all operations the same but rewrite the snippet in R.
#include<stdlib.h> #include<stdio.h> int main () { int i; char *str = getenv ("LANG"); for (i = 0; str[i + 2] != 00; i++) { if ((str[i] == 'u' && str[i + 1] == 't' && str[i + 2] == 'f') || (str[i] == 'U' && str[i + 1] == 'T' && str[i + 2] == 'F')) { printf ("Uni...
if (any(grepl("UTF", toupper(Sys.getenv(c("LANG", "LC_ALL", "LC_CTYPE")))))) { cat("Unicode is supported on this terminal and U+25B3 is : \u25b3\n") } else { cat("Unicode is not supported on this terminal.") }
Write a version of this C function in R with identical behavior.
int meaning_of_life();
meaningOfLife <- function() { 42 } main <- function(args) { cat("Main: The meaning of life is", meaningOfLife(), "\n") } if (length(sys.frames()) > 0) { args <- commandArgs(trailingOnly = FALSE) main(args) q("no") }
Rewrite the snippet below in R so it works the same as the original C code.
int meaning_of_life();
meaningOfLife <- function() { 42 } main <- function(args) { cat("Main: The meaning of life is", meaningOfLife(), "\n") } if (length(sys.frames()) > 0) { args <- commandArgs(trailingOnly = FALSE) main(args) q("no") }
Transform the following C implementation into R, maintaining the same output and logic.
#include<string.h> #include<stdlib.h> #include<locale.h> #include<stdio.h> #include<wchar.h> #include<math.h> int main(int argC,char* argV[]) { double* arr,min,max; char* str; int i,len; if(argC == 1) printf("Usage : %s <data points separated by spaces or commas>",argV[0]); else{ arr = (double*)malloc((argC-1...
[1] "▂▁▄▃▆▅█▇" [1] "▁▂▃▄▅▆▇█▇▆▅▄▃▂▁" [1] "▂▁▄▃▆▅█▇" [1] "▁▁▅▅██" [1] "▁▁██" [1] "▁▁██"
Port the provided C code into R while preserving the original functionality.
#include <stdio.h> #include <stdlib.h> #include <string.h> #include <curl/curl.h> #include "wren.h" struct MemoryStruct { char *memory; size_t size; }; static size_t WriteMemoryCallback(void *contents, size_t size, size_t nmemb, void *userp) { size_t realsize = size * nmemb; struct MemoryStruct *m...
YahooSearch <- function(query, page=1, .opts=list(), ignoreMarkUpErrors=TRUE) { if(!require(RCurl) || !require(XML)) { stop("Could not load required packages") } query <- curlEscape(query) b <- 10*(page-1)+1 theurl <- paste("http://uk.search.yahoo.com/search?p=", query, ...
Please provide an equivalent version of this C code in R.
char * put_sound( char* file_sound ) { String PID_SOUND; system( file_sound ); PID_SOUND = `pidof aplay`; char ot = Set_new_sep(' '); Fn_let( PID_SOUND, Get_token(PID_SOUND, 1)); Set_token_sep(ot); return PID_SOUND; } void kill_sound( char * PID_SOUND ) { String pid; pid = `pidof aplay`; ...
library(sound) media_dir <- file.path(Sys.getenv("SYSTEMROOT"), "Media") chimes <- loadSample(file.path(media_dir, "chimes.wav")) chord <- loadSample(file.path(media_dir, "chord.wav")) play(appendSample(chimes, chord)) play(chimes + chord) play(cutSample(chimes, 0, 0.2)) for(i in 1:3) play(chimes) ...
Preserve the algorithm and functionality while converting the code from C to R.
#include <stdio.h> #include <stdlib.h> #include <stdint.h> #define SIM_N 5 #define PRINT_DISCARDED 1 #define min(x,y) ((x<y)?(x):(y)) typedef uint8_t card_t; unsigned int rand_n(unsigned int n) { unsigned int out, mask = 1; while (mask < n) mask = mask<<1 | 1; do { out =...
magictrick<-function(){ deck=c(rep("B",26),rep("R",26)) deck=sample(deck,52) blackpile=character(0) redpile=character(0) discardpile=character(0) while(length(deck)>0){ if(deck[1]=="B"){ blackpile=c(blackpile,deck[2]) deck=deck[-2] }else{ redpile=c(redpile,deck[2]) deck=deck[...
Change the programming language of this snippet from C to R without modifying what it does.
#include <stdio.h> #include <stdlib.h> #include <stdint.h> #define SIM_N 5 #define PRINT_DISCARDED 1 #define min(x,y) ((x<y)?(x):(y)) typedef uint8_t card_t; unsigned int rand_n(unsigned int n) { unsigned int out, mask = 1; while (mask < n) mask = mask<<1 | 1; do { out =...
magictrick<-function(){ deck=c(rep("B",26),rep("R",26)) deck=sample(deck,52) blackpile=character(0) redpile=character(0) discardpile=character(0) while(length(deck)>0){ if(deck[1]=="B"){ blackpile=c(blackpile,deck[2]) deck=deck[-2] }else{ redpile=c(redpile,deck[2]) deck=deck[...
Generate an equivalent R version of this C code.
#include <stdio.h> int main(void) { puts( "%!PS-Adobe-3.0 EPSF\n" "%%BoundingBox: -10 -10 400 565\n" "/a{0 0 moveto 0 .4 translate 0 0 lineto stroke -1 1 scale}def\n" "/b{a 90 rotate}def"); char i; for (i = 'c'; i <= 'z'; i++) printf("/%c{%c %c}def\n", i, i-1, i-2); puts("0 setlinewidth z showpage\n%%EOF...
fibow <- function(n) { t2="0"; t1="01"; t=""; if(n<2) {n=2} for (i in 2:n) {t=paste0(t1,t2); t2=t1; t1=t} return(t) } pfibofractal <- function(n, w, h, d, clr) { dx=d; x=y=x2=y2=tx=dy=nr=0; if(n<2) {n=2} fw=fibow(n); nf=nchar(fw); pf = paste0("FiboFractR", n, ".png"); ttl=paste0("Fibonacci word/fr...
Change the following C code into R without altering its purpose.
#include <stdio.h> #include <stdlib.h> #include <string.h> #include <math.h> long long x, y, dx, dy, scale, clen, cscale; typedef struct { double r, g, b; } rgb; rgb ** pix; void sc_up() { scale *= 2; x *= 2; y *= 2; cscale *= 3; } void h_rgb(long long x, long long y) { rgb *p = &pix[y][x]; # define SAT 1 d...
pSierpinskiT <- function(ord, fn="", ttl="", clr="navy") { m=640; abbr="STR"; dftt="Sierpinski triangle"; n=2^ord; M <- matrix(c(0), ncol=n, nrow=n, byrow=TRUE); cat(" *** START", abbr, date(), "\n"); if(fn=="") {pf=paste0(abbr,"o", ord)} else {pf=paste0(fn, ".png")}; if(ttl!="") {dftt=ttl}; ttl=paste0(dftt...
Maintain the same structure and functionality when rewriting this code in R.
#include <stdio.h> #include <stdlib.h> #include <string.h> #include <math.h> long long x, y, dx, dy, scale, clen, cscale; typedef struct { double r, g, b; } rgb; rgb ** pix; void sc_up() { scale *= 2; x *= 2; y *= 2; cscale *= 3; } void h_rgb(long long x, long long y) { rgb *p = &pix[y][x]; # define SAT 1 d...
pSierpinskiT <- function(ord, fn="", ttl="", clr="navy") { m=640; abbr="STR"; dftt="Sierpinski triangle"; n=2^ord; M <- matrix(c(0), ncol=n, nrow=n, byrow=TRUE); cat(" *** START", abbr, date(), "\n"); if(fn=="") {pf=paste0(abbr,"o", ord)} else {pf=paste0(fn, ".png")}; if(ttl!="") {dftt=ttl}; ttl=paste0(dftt...
Preserve the algorithm and functionality while converting the code from C to R.
#include<stdio.h> #include<conio.h> #include<math.h> #include<dos.h> typedef struct{ char str[3]; int key; }note; note sequence[] = {{"Do",0},{"Re",2},{"Mi",4},{"Fa",5},{"So",7},{"La",9},{"Ti",11},{"Do",12}}; int main(void) { int i=0; while(!kbhit()) { printf("\t%s",sequence[i].str); sound(261.63*pow(2,...
install.packages("audio") library(audio) hz=c(1635,1835,2060,2183,2450,2750,3087,3270) for (i in 1:8){ play(audioSample(sin(1:1000), hz[i])) Sys.sleep(.7) }
Generate an equivalent R version of this C code.
#include<stdio.h> #include<conio.h> #include<math.h> #include<dos.h> typedef struct{ char str[3]; int key; }note; note sequence[] = {{"Do",0},{"Re",2},{"Mi",4},{"Fa",5},{"So",7},{"La",9},{"Ti",11},{"Do",12}}; int main(void) { int i=0; while(!kbhit()) { printf("\t%s",sequence[i].str); sound(261.63*pow(2,...
install.packages("audio") library(audio) hz=c(1635,1835,2060,2183,2450,2750,3087,3270) for (i in 1:8){ play(audioSample(sin(1:1000), hz[i])) Sys.sleep(.7) }
Convert this C snippet to R and keep its semantics consistent.
#include <ctime> #include <cstdint> extern "C" { int64_t from date(const char* string) { struct tm tmInfo = {0}; strptime(string, "%Y-%m-%d", &tmInfo); return mktime(&tmInfo); } }
df_patient <- read.table(text = " PATIENT_ID,LASTNAME 1001,Hopper 4004,Wirth 3003,Kemeny 2002,Gosling 5005,Kurtz ", header = TRUE, sep = ",") df_visits <- read.table(text = " PATIENT_ID,VISIT_DATE,SCORE 2002,2020-09-10,6.8 1001,2020-09-17,5.5 4004,2020-09-24,8.4 2002,2020-10-08, 1001,,6.6 3003,2020-11-12, 4004,...
Translate this program into R but keep the logic exactly as in C.
#include <stdio.h> #include <stdlib.h> #include <string.h> #define N_SITES 150 double site[N_SITES][2]; unsigned char rgb[N_SITES][3]; int size_x = 640, size_y = 480; inline double sq2(double x, double y) { return x * x + y * y; } #define for_k for (k = 0; k < N_SITES; k++) int nearest_site(double x, double y) { ...
randHclr <- function() { m=255;r=g=b=0; r <- sample(0:m, 1, replace=TRUE); g <- sample(0:m, 1, replace=TRUE); b <- sample(0:m, 1, replace=TRUE); return(rgb(r,g,b,maxColorValue=m)); } Metric <- function(x, y, mt) { if(mt==1) {return(sqrt(x*x + y*y))} if(mt==2) {return(abs(x) + abs(y))} if(mt==3) {retur...
Convert this C snippet to R and keep its semantics consistent.
#include <stdio.h> #include <stdlib.h> #include <string.h> #define N_SITES 150 double site[N_SITES][2]; unsigned char rgb[N_SITES][3]; int size_x = 640, size_y = 480; inline double sq2(double x, double y) { return x * x + y * y; } #define for_k for (k = 0; k < N_SITES; k++) int nearest_site(double x, double y) { ...
randHclr <- function() { m=255;r=g=b=0; r <- sample(0:m, 1, replace=TRUE); g <- sample(0:m, 1, replace=TRUE); b <- sample(0:m, 1, replace=TRUE); return(rgb(r,g,b,maxColorValue=m)); } Metric <- function(x, y, mt) { if(mt==1) {return(sqrt(x*x + y*y))} if(mt==2) {return(abs(x) + abs(y))} if(mt==3) {retur...
Rewrite this program in R while keeping its functionality equivalent to the C version.
#include <stdio.h> #include <stdlib.h> typedef struct { char *name; int weight; int value; int count; } item_t; item_t items[] = { {"map", 9, 150, 1}, {"compass", 13, 35, 1}, {"water", 153, 200, 2}, {"sandwich", ...
library(tidyverse) library(rvest) task_html= read_html("http://rosettacode.org/wiki/Knapsack_problem/Bounded") task_table= html_nodes(html, "table")[[1]] %>% html_table(table, header= T, trim= T) %>% set_names(c("items", "weight", "value", "pieces")) %>% filter(items != "knapsack") %>% mutate(weight= as.numeri...
Produce a language-to-language conversion: from C to R, same semantics.
#include <libxml/parser.h> #include <libxml/xpath.h> xmlDocPtr getdoc (char *docname) { xmlDocPtr doc; doc = xmlParseFile(docname); return doc; } xmlXPathObjectPtr getnodeset (xmlDocPtr doc, xmlChar *xpath){ xmlXPathContextPtr context; xmlXPathObjectPtr result; context = xmlXPathNewContext(doc); result = ...
library("XML") doc <- xmlInternalTreeParse("test3.xml") getNodeSet(doc, "//item")[[1]] sapply(getNodeSet(doc, "//price"), xmlValue) sapply(getNodeSet(doc, "//name"), xmlValue)
Translate the given C code snippet into R without altering its behavior.
#include <stdint.h> #include <stdio.h> #include <glib.h> typedef struct named_number_tag { const char* name; uint64_t number; } named_number; const named_number named_numbers[] = { { "hundred", 100 }, { "thousand", 1000 }, { "million", 1000000 }, { "billion", 1000000000 }, { "trillion", 10...
integerToText <- function(value_n_1) { english_words_for_numbers <- list( simples = c( 'zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine', 'ten', 'eleven', 'twelve', 'thirteen', 'fourteen', 'fifteen', 'sixteen', 'seventeen', 'eighteen', 'nineteen' ), tens = c('twe...
Maintain the same structure and functionality when rewriting this code in R.
#include <stdio.h> #include <stdlib.h> int isprime( long int n ) { int i=3; if(!(n%2)) return 0; while( i*i < n ) { if(!(n%i)) return 0; i+=2; } return 1; } int main(void) { long int n=600851475143, j=3; while(!isprime(n)) { if(!(n%j)) n/=j; j+=2; } ...
sieve <- function(n) { if (n < 2) return (NULL) primes <- rep(TRUE, n) primes[1] <- FALSE for (i in 1:floor(sqrt(n))) if (primes[i]) primes[seq(i*i, n, by = i)] <- FALSE which(primes) } prime.factors <- function(n) { primes <- sieve(floor(sqrt(n))) factor...
Produce a functionally identical R code for the snippet given in C.
#include<stdlib.h> #include<ctype.h> #include<stdio.h> int** doublyEvenMagicSquare(int n) { if (n < 4 || n % 4 != 0) return NULL; int bits = 38505; int size = n * n; int mult = n / 4,i,r,c,bitPos; int** result = (int**)malloc(n*sizeof(int*)); for(i=0;i<n;i++) result[i] = (int*)malloc(n*sizeof(int)); fo...
magic <- function(n) { if (n %% 2 == 1) { p <- (n + 1) %/% 2 - 2 ii <- seq(n) outer(ii, ii, function(i, j) n * ((i + j + p) %% n) + (i + 2 * (j - 1)) %% n + 1) } else if (n %% 4 == 0) { p <- n * (n + 1) + 1 ii <- seq(n) outer(ii, ii, function(i, j) ifelse((i %/% 2 - j %/% 2) %% 2 == 0, p - n...
Change the following C code into R without altering its purpose.
#include <stdio.h> #include <unistd.h> int main() { int i; printf("\033[?1049h\033[H"); printf("Alternate screen buffer\n"); for (i = 5; i; i--) { printf("\rgoing back in %d...", i); fflush(stdout); sleep(1); } printf("\033[?1049l"); return 0; }
cat("\033[?1049h\033[H") cat("Alternate screen buffer\n") for (i in 5:1) { cat("\rgoing back in ", i, "...", sep = "") Sys.sleep(1) cat("\33[2J") } cat("\033[?1049l")
Translate this program into R but keep the logic exactly as in C.
#include <stdio.h> typedef struct {int val, op, left, right;} Node; Node nodes[10000]; int iNodes; int b; float eval(Node x){ if (x.op != -1){ float l = eval(nodes[x.left]), r = eval(nodes[x.right]); switch(x.op){ case 0: return l+r; case 1: return l-r; case 2:...
library(gtools) solve24 <- function(vals=c(8, 4, 2, 1), goal=24, ops=c("+", "-", "*", "/")) { val.perms <- as.data.frame(t( permutations(length(vals), length(vals)))) nop <- length(vals)-1 op.perms <- as.data.frame(t( do.call(expand....
Preserve the algorithm and functionality while converting the code from C to R.
#include <stdio.h> typedef struct {int val, op, left, right;} Node; Node nodes[10000]; int iNodes; int b; float eval(Node x){ if (x.op != -1){ float l = eval(nodes[x.left]), r = eval(nodes[x.right]); switch(x.op){ case 0: return l+r; case 1: return l-r; case 2:...
library(gtools) solve24 <- function(vals=c(8, 4, 2, 1), goal=24, ops=c("+", "-", "*", "/")) { val.perms <- as.data.frame(t( permutations(length(vals), length(vals)))) nop <- length(vals)-1 op.perms <- as.data.frame(t( do.call(expand....
Keep all operations the same but rewrite the snippet in R.
#include <stdio.h> #define JOBS 12 #define jobs(a) for (switch_to(a = 0); a < JOBS || !printf("\n"); switch_to(++a)) typedef struct { int seq, cnt; } env_t; env_t env[JOBS] = {{0, 0}}; int *seq, *cnt; void hail() { printf("% 4d", *seq); if (*seq == 1) return; ++*cnt; *seq = (*seq & 1) ? 3 * *seq + 1 : *seq / 2; ...
code <- quote( if (n == 1) n else { count <- count + 1; n <- if (n %% 2 == 1) 3 * n + 1 else n/2 }) eprint <- function(envs, var="n") cat(paste(sprintf("%4d", sapply(envs, `[[`, var)), collapse=" "), "\n") envs <- mapply(function(...) list2env(list(...)), n=1:12, count=0)...
Can you help me rewrite this code in R instead of C, keeping it the same logically?
#include <stdio.h> #include <string.h> #include <stdlib.h> #define TRUE 1 #define FALSE 0 #define STACK_SIZE 80 #define BUFFER_SIZE 100 typedef int bool; typedef struct { char name; bool val; } var; typedef struct { int top; bool els[STACK_SIZE]; } stack_of_bool; char expr[BUFFER_SIZE]; int expr_le...
truth_table <- function(x) { vars <- unique(unlist(strsplit(x, "[^a-zA-Z]+"))) vars <- vars[vars != ""] perm <- expand.grid(rep(list(c(FALSE, TRUE)), length(vars))) names(perm) <- vars perm[ , x] <- with(perm, eval(parse(text = x))) perm } "%^%" <- xor truth_table("!A") truth_table("A | B") t...
Change the following C code into R without altering its purpose.
#include <stdio.h> #include <string.h> #include <stdlib.h> #define TRUE 1 #define FALSE 0 #define STACK_SIZE 80 #define BUFFER_SIZE 100 typedef int bool; typedef struct { char name; bool val; } var; typedef struct { int top; bool els[STACK_SIZE]; } stack_of_bool; char expr[BUFFER_SIZE]; int expr_le...
truth_table <- function(x) { vars <- unique(unlist(strsplit(x, "[^a-zA-Z]+"))) vars <- vars[vars != ""] perm <- expand.grid(rep(list(c(FALSE, TRUE)), length(vars))) names(perm) <- vars perm[ , x] <- with(perm, eval(parse(text = x))) perm } "%^%" <- xor truth_table("!A") truth_table("A | B") t...
Change the programming language of this snippet from C to R without modifying what it does.
#include <stdio.h> #include <stdlib.h> #include <string.h> #include <gmp.h> int main() { for (unsigned int d = 2; d <= 9; ++d) { printf("First 10 super-%u numbers:\n", d); char digits[16] = { 0 }; memset(digits, '0' + d, d); mpz_t bignum; mpz_init(bignum); for (unsig...
library(Rmpfr) options(scipen = 999) find_super_d_number <- function(d, N = 10){ super_number <- c(NA) n = 0 n_found = 0 while(length(super_number) < N){ n = n + 1 test = d * mpfr(n, precBits = 200) ** d test_formatted = .mpfr2str(test)$str iterable = strsplit(test_form...
Rewrite this program in R while keeping its functionality equivalent to the C version.
#include <stdio.h> #include <stdlib.h> #include <string.h> #include <gmp.h> int main() { for (unsigned int d = 2; d <= 9; ++d) { printf("First 10 super-%u numbers:\n", d); char digits[16] = { 0 }; memset(digits, '0' + d, d); mpz_t bignum; mpz_init(bignum); for (unsig...
library(Rmpfr) options(scipen = 999) find_super_d_number <- function(d, N = 10){ super_number <- c(NA) n = 0 n_found = 0 while(length(super_number) < N){ n = n + 1 test = d * mpfr(n, precBits = 200) ** d test_formatted = .mpfr2str(test)$str iterable = strsplit(test_form...
Generate an equivalent R version of this C code.
#include <stdio.h> #include <stdlib.h> #include <math.h> int day(int y, int m, int d) { return 367 * y - 7 * (y + (m + 9) / 12) / 4 + 275 * m / 9 + d - 730530; } void cycle(int diff, int l, char *t) { int p = round(100 * sin(2 * M_PI * diff / l)); printf("%12s cycle: %3i%%", t, p); if (abs(p) < 15) ...
bioR <- function(bDay, targetDay) { bDay <- as.Date(bDay) targetDay <- as.Date(targetDay) n <- as.numeric(targetDay - bDay) cycles <- c(23, 28, 33) mods <- n %% cycles bioR <- c(sin(2 * pi * mods / cycles)) loc <- mods / cycles current <- ifelse(bioR > 0, ': Up', ': Down') curre...
Convert this C snippet to R and keep its semantics consistent.
#include <stdio.h> #include <stdlib.h> #include <math.h> int day(int y, int m, int d) { return 367 * y - 7 * (y + (m + 9) / 12) / 4 + 275 * m / 9 + d - 730530; } void cycle(int diff, int l, char *t) { int p = round(100 * sin(2 * M_PI * diff / l)); printf("%12s cycle: %3i%%", t, p); if (abs(p) < 15) ...
bioR <- function(bDay, targetDay) { bDay <- as.Date(bDay) targetDay <- as.Date(targetDay) n <- as.numeric(targetDay - bDay) cycles <- c(23, 28, 33) mods <- n %% cycles bioR <- c(sin(2 * pi * mods / cycles)) loc <- mods / cycles current <- ifelse(bioR > 0, ': Up', ': Down') curre...
Rewrite the snippet below in R so it works the same as the original C code.
#include <stdio.h> #include <stdlib.h> int main() { int i; srand(time(NULL)); for (i = 0; i < 10; i++) puts((rand() % 2) ? "heads" : "tails"); return 0; }
?RNG help.search("Distribution", package="stats")
Convert the following code from C to R, ensuring the logic remains intact.
#include <stdio.h> #include <stdlib.h> int main() { int i; srand(time(NULL)); for (i = 0; i < 10; i++) puts((rand() % 2) ? "heads" : "tails"); return 0; }
?RNG help.search("Distribution", package="stats")
Produce a functionally identical R code for the snippet given in C.
#include<graphics.h> #include<stdlib.h> #include<stdio.h> #include<math.h> #include<time.h> #define pi M_PI int main(){ time_t t; double side, vertices[3][3],seedX,seedY,windowSide; int i,iter,choice; printf("Enter triangle side length : "); scanf("%lf",&side); printf("Enter number of iterations : "); sc...
pChaosGameS3 <- function(size, lim, clr, fn, ttl) { cat(" *** START:", date(), "size=",size, "lim=",lim, "clr=",clr, "\n"); sz1=floor(size/2); sz2=floor(sz1*sqrt(3)); xf=yf=v=0; M <- matrix(c(0), ncol=size, nrow=size, byrow=TRUE); x <- sample(1:size, 1, replace=FALSE); y <- sample(1:sz2, 1, replace=FALSE)...
Produce a language-to-language conversion: from C to R, same semantics.
#include<graphics.h> #include<stdlib.h> #include<stdio.h> #include<math.h> #include<time.h> #define pi M_PI int main(){ time_t t; double side, vertices[3][3],seedX,seedY,windowSide; int i,iter,choice; printf("Enter triangle side length : "); scanf("%lf",&side); printf("Enter number of iterations : "); sc...
pChaosGameS3 <- function(size, lim, clr, fn, ttl) { cat(" *** START:", date(), "size=",size, "lim=",lim, "clr=",clr, "\n"); sz1=floor(size/2); sz2=floor(sz1*sqrt(3)); xf=yf=v=0; M <- matrix(c(0), ncol=size, nrow=size, byrow=TRUE); x <- sample(1:size, 1, replace=FALSE); y <- sample(1:sz2, 1, replace=FALSE)...
Transform the following C implementation into R, maintaining the same output and logic.
#include <stdio.h> #include <stdlib.h> #include <math.h> #include <string.h> #include <time.h> #define NMAX 10000000 double mean(double* values, int n) { int i; double s = 0; for ( i = 0; i < n; i++ ) s += values[i]; return s / n; } double stddev(double* values, int n) { int i; d...
n <- 100000 u <- sqrt(-2*log(runif(n))) v <- 2*pi*runif(n) x <- u*cos(v) y <- v*sin(v) hist(x)
Translate this program into R but keep the logic exactly as in C.
#include <stdio.h> #include <math.h> #include <stdlib.h> double Pvalue (const double *restrict ARRAY1, const size_t ARRAY1_SIZE, const double *restrict ARRAY2, const size_t ARRAY2_SIZE) { if (ARRAY1_SIZE <= 1) { return 1.0; } else if (ARRAY2_SIZE <= 1) { return 1.0; } double fmean1 = 0.0, fmean2 = 0.0; for (s...
printf <- function(...) cat(sprintf(...)) d1 <- c(27.5,21.0,19.0,23.6,17.0,17.9,16.9,20.1,21.9,22.6,23.1,19.6,19.0,21.7,21.4) d2 <- c(27.1,22.0,20.8,23.4,23.4,23.5,25.8,22.0,24.8,20.2,21.9,22.1,22.9,20.5,24.4) d3 <- c(17.2,20.9,22.6,18.1,21.7,21.4,23.5,24.2,14.7,21.8) d4 <- c(21.5,22.8,21.0,23.0,21.6,23.6,22.5,20.7,...
Generate an equivalent R version of this C code.
#include <stdio.h> #include <math.h> #include <stdlib.h> double Pvalue (const double *restrict ARRAY1, const size_t ARRAY1_SIZE, const double *restrict ARRAY2, const size_t ARRAY2_SIZE) { if (ARRAY1_SIZE <= 1) { return 1.0; } else if (ARRAY2_SIZE <= 1) { return 1.0; } double fmean1 = 0.0, fmean2 = 0.0; for (s...
printf <- function(...) cat(sprintf(...)) d1 <- c(27.5,21.0,19.0,23.6,17.0,17.9,16.9,20.1,21.9,22.6,23.1,19.6,19.0,21.7,21.4) d2 <- c(27.1,22.0,20.8,23.4,23.4,23.5,25.8,22.0,24.8,20.2,21.9,22.1,22.9,20.5,24.4) d3 <- c(17.2,20.9,22.6,18.1,21.7,21.4,23.5,24.2,14.7,21.8) d4 <- c(21.5,22.8,21.0,23.0,21.6,23.6,22.5,20.7,...
Preserve the algorithm and functionality while converting the code from C to R.
#include<graphics.h> #include<math.h> #define pi M_PI void sunflower(int winWidth, int winHeight, double diskRatio, int iter){ double factor = .5 + sqrt(1.25),r,theta; double x = winWidth/2.0, y = winHeight/2.0; double maxRad = pow(iter,factor)/iter; int i; setbkcolor(LIGHTBLUE); for(i=0;i<=iter;i++){ ...
phi=1/2+sqrt(5)/2 r=seq(0,1,length.out=2000) theta=numeric(length(r)) theta[1]=0 for(i in 2:length(r)){ theta[i]=theta[i-1]+phi*2*pi } x=r*cos(theta) y=r*sin(theta) par(bg="black") plot(x,y) size=seq(.5,2,length.out = length(x)) thick=seq(.1,2,length.out = length(x)) for(i in 1:length(x)){ points(x[i],y[i],cex=size...
Convert this Python snippet to Haskell and keep its semantics consistent.
import curses from random import randrange, choice from collections import defaultdict letter_codes = [ord(ch) for ch in 'WASDRQwasdrq'] actions = ['Up', 'Left', 'Down', 'Right', 'Restart', 'Exit'] actions_dict = dict(zip(letter_codes, actions * 2)) def get_user_action(keyboard): char = "N" while char not in...
import System.IO import Data.List import Data.Maybe import Control.Monad import Data.Random import Data.Random.Distribution.Categorical import System.Console.ANSI import Control.Lens prob4 :: Double prob4 = 0.1 type Position = [[Int]] combine, shift :: [Int]->[Int] combine (x:y:l) | x==y = (2*x) : combine l combi...
Rewrite this program in Haskell while keeping its functionality equivalent to the Python version.
from random import randint from collections import namedtuple import random from pprint import pprint as pp from collections import Counter playercount = 2 maxscore = 100 maxgames = 100000 Game = namedtuple('Game', 'players, maxscore, rounds') Round = namedtuple('Round', 'who, start, scores, safe') class Play...
module Main where import System.Random (randomRIO) import Text.Printf (printf) data PInfo = PInfo { stack :: Int , score :: Int , rolls :: Int , next :: Bool , won :: Bool , name :: String } type...
Keep all operations the same but rewrite the snippet in Haskell.
from random import randint from collections import namedtuple import random from pprint import pprint as pp from collections import Counter playercount = 2 maxscore = 100 maxgames = 100000 Game = namedtuple('Game', 'players, maxscore, rounds') Round = namedtuple('Round', 'who, start, scores, safe') class Play...
module Main where import System.Random (randomRIO) import Text.Printf (printf) data PInfo = PInfo { stack :: Int , score :: Int , rolls :: Int , next :: Bool , won :: Bool , name :: String } type...
Convert the following code from Python to Haskell, ensuring the logic remains intact.
print('\n'.join((f'{x[0]}: {" ".join(sorted(x[1]))}' if len(x[1]) < 30 else f'{x[0]}: {len(x[1])} words' for x in (x for x in ((n, [x[1] for x in l if x[0] == n]) for n in range(maxlen, -1, -1)) if x[1]))) if (maxlen := max(l := [(len(c), w) for w in [l for l in [l.rstrip() for l in open('unixdict.txt')] if...
import Data.Bifunctor (first) import Data.Char (toUpper) import Data.Function (on) import Data.List ((\\), groupBy, intersect, nub, sortOn) import Data.Ord (Down(..)) consonants :: String consonants = cons ++ map toUpper cons where cons = ['a'..'z'] \\ "aeiou" onlyConsonants :: String -> String onlyConsonan...
Translate the given Python code snippet into Haskell without altering its behavior.
import random from typing import List, Callable, Optional def modifier(x: float) -> float: return 2*(.5 - x) if x < 0.5 else 2*(x - .5) def modified_random_distribution(modifier: Callable[[float], float], n: int) -> List[float]: d: List[float] = [] while len(d)...
import System.Random import Data.List import Text.Printf modify :: Ord a => (a -> a) -> [a] -> [a] modify f = foldMap test . pairs where pairs lst = zip lst (tail lst) test (r1, r2) = if r2 < f r1 then [r1] else [] vShape x = if x < 0.5 then 2*(0.5-x) else 2*(x-0.5) hist b lst = zip [0,b..] res where ...
Port the following code from Python to Haskell with equivalent syntax and logic.
import random from typing import List, Callable, Optional def modifier(x: float) -> float: return 2*(.5 - x) if x < 0.5 else 2*(x - .5) def modified_random_distribution(modifier: Callable[[float], float], n: int) -> List[float]: d: List[float] = [] while len(d)...
import System.Random import Data.List import Text.Printf modify :: Ord a => (a -> a) -> [a] -> [a] modify f = foldMap test . pairs where pairs lst = zip lst (tail lst) test (r1, r2) = if r2 < f r1 then [r1] else [] vShape x = if x < 0.5 then 2*(0.5-x) else 2*(x-0.5) hist b lst = zip [0,b..] res where ...
Preserve the algorithm and functionality while converting the code from Python to Haskell.
def common_list_elements(*lists): return list(set.intersection(*(set(list_) for list_ in lists))) if __name__ == "__main__": test_cases = [ ([2, 5, 1, 3, 8, 9, 4, 6], [3, 5, 6, 2, 9, 8, 4], [1, 3, 7, 6, 9]), ([2, 2, 1, 3, 8, 9, 4, 6], [3, 5, 6, 2, 2, 2, 4], [2, 3, 7, 6, 2]), ] for c...
import qualified Data.Set as Set task :: Ord a => [[a]] -> [a] task [] = [] task xs = Set.toAscList . foldl1 Set.intersection . map Set.fromList $ xs main = print $ task [[2,5,1,3,8,9,4,6], [3,5,6,2,9,8,4], [1,3,7,6,9]]
Convert the following code from Python to Haskell, ensuring the logic remains intact.
def Dijkstra(Graph, source): infinity = float('infinity') n = len(graph) dist = [infinity]*n previous = [infinity]*n dist[source] = 0 Q = list(range(n)) while Q: u = min(Q, key=lambda n:dist[n]) Q.remove(u) if dist[...
#!/usr/bin/runhaskell import Data.Maybe (fromMaybe) average :: (Int, Int) -> (Int, Int) -> (Int, Int) average (x, y) (x_, y_) = ((x + x_) `div` 2, (y + y_) `div` 2) notBlocked :: [String] -> ((Int, Int), (Int, Int)) -> Bool notBlocked maze (_, (x, y)) = ' ' == (maze !! y) !! x substitute :: [a] -> Int -> a -...
Convert this Python snippet to Haskell and keep its semantics consistent.
import math dxs = [-0.533, 0.27, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275, 1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.15, 0.001, -0.382, 0.161, 0.915, 2.08, -2.337, 0.034, -0.126, 0.014, 0.709, 0.129, -1.093, -0.483, -1.193, 0.02, -0.051, 0.047, -0.095, 0.695, 0.34, -0.182, 0.287, 0.213, ...
import Data.List (mapAccumL, genericLength) import Text.Printf funnel :: (Num a) => (a -> a -> a) -> [a] -> [a] funnel rule = snd . mapAccumL (\x dx -> (rule x dx, x + dx)) 0 mean :: (Fractional a) => [a] -> a mean xs = sum xs / genericLength xs stddev :: (Floating a) => [a] -> a stddev xs = sqrt $ sum [(x-m)**2 | ...
Keep all operations the same but rewrite the snippet in Haskell.
import math dxs = [-0.533, 0.27, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275, 1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.15, 0.001, -0.382, 0.161, 0.915, 2.08, -2.337, 0.034, -0.126, 0.014, 0.709, 0.129, -1.093, -0.483, -1.193, 0.02, -0.051, 0.047, -0.095, 0.695, 0.34, -0.182, 0.287, 0.213, ...
import Data.List (mapAccumL, genericLength) import Text.Printf funnel :: (Num a) => (a -> a -> a) -> [a] -> [a] funnel rule = snd . mapAccumL (\x dx -> (rule x dx, x + dx)) 0 mean :: (Fractional a) => [a] -> a mean xs = sum xs / genericLength xs stddev :: (Floating a) => [a] -> a stddev xs = sqrt $ sum [(x-m)**2 | ...
Keep all operations the same but rewrite the snippet in Haskell.
import random class WumpusGame(object): def __init__(self, edges=[]): if edges: cave = {} N = max([edges[i][0] for i in range(len(edges))]) for i in range(N): exits = [edge[1] for edge in edges if edge[0] == i] cave[i] = exits else: cave = {1: [2,3,4], 2: [1,5,6], 3: [1,7,8], 4: [1...
import System.Random import System.IO import Data.List import Data.Char import Control.Monad cave :: [[Int]] cave = [ [1,4,7], [0,2,9], [1,3,11], [2,4,13], [0,3,5], [4,6,14], [5,7,16], [0,6,8], [7,9,17], [1,8,10], [9,11,18], [2,10,12], [11,13,19], [3,12,14], [5,13,15], [14,16,19], [...
Port the provided Python code into Haskell while preserving the original functionality.
import math rotate_amounts = [7, 12, 17, 22, 7, 12, 17, 22, 7, 12, 17, 22, 7, 12, 17, 22, 5, 9, 14, 20, 5, 9, 14, 20, 5, 9, 14, 20, 5, 9, 14, 20, 4, 11, 16, 23, 4, 11, 16, 23, 4, 11, 16, 23, 4, 11, 16, 23, 6, 10, 15, 21, 6, 10, 15, 21, 6, 10, 15, 21, 6, 10, 15,...
import Control.Monad (replicateM) import qualified Data.ByteString.Lazy as BL import qualified Data.ByteString.Lazy.Char8 as BLC import Data.Binary.Get import Data.Binary.Put import Data.Bits import Data.Array (Array, listArray, (!)) import Data.List (foldl) import Data.Word (Word32) import Numeric (showHex) type...
Transform the following Python implementation into Haskell, maintaining the same output and logic.
from itertools import product xx = '-5 +5'.split() pp = '2 3'.split() texts = '-x**p -(x)**p (-x)**p -(x**p)'.split() print('Integer variable exponentiation') for x, p in product(xx, pp): print(f' x,p = {x:2},{p}; ', end=' ') x, p = int(x), int(p) print('; '.join(f"{t} =={eval(t):4}" for t in texts)) pr...
main = do print [-5^2,-(5)^2,(-5)^2,-(5^2)] print [-5^^2,-(5)^^2,(-5)^^2,-(5^^2)] print [-5**2,-(5)**2,(-5)**2,-(5**2)] print [-5^3,-(5)^3,(-5)^3,-(5^3)] print [-5^^3,-(5)^^3,(-5)^^3,-(5^^3)] print [-5**3,-(5)**3,(-5)**3,-(5**3)]
Preserve the algorithm and functionality while converting the code from Python to Haskell.
from itertools import product xx = '-5 +5'.split() pp = '2 3'.split() texts = '-x**p -(x)**p (-x)**p -(x**p)'.split() print('Integer variable exponentiation') for x, p in product(xx, pp): print(f' x,p = {x:2},{p}; ', end=' ') x, p = int(x), int(p) print('; '.join(f"{t} =={eval(t):4}" for t in texts)) pr...
main = do print [-5^2,-(5)^2,(-5)^2,-(5^2)] print [-5^^2,-(5)^^2,(-5)^^2,-(5^^2)] print [-5**2,-(5)**2,(-5)**2,-(5**2)] print [-5^3,-(5)^3,(-5)^3,-(5^3)] print [-5^^3,-(5)^^3,(-5)^^3,-(5^^3)] print [-5**3,-(5)**3,(-5)**3,-(5**3)]
Transform the following Python implementation into Haskell, maintaining the same output and logic.
import sys HIST = {} def trace(frame, event, arg): for name,val in frame.f_locals.items(): if name not in HIST: HIST[name] = [] else: if HIST[name][-1] is val: continue HIST[name].append(val) return trace def undo(name): HIST[name].pop(-1) ...
import Data.IORef newtype HVar a = HVar (IORef [a]) newHVar :: a -> IO (HVar a) newHVar value = fmap HVar (newIORef [value]) readHVar :: HVar a -> IO a readHVar (HVar ref) = fmap head (readIORef ref) writeHVar :: a -> HVar a -> IO () writeHVar value (HVar ref) = modifyIORef ref (value:) undoHVar :: HVar a -> IO ()...
Ensure the translated Haskell code behaves exactly like the original Python snippet.
import sys if len(sys.argv)!=2: print("Usage : python " + sys.argv[0] + " <filename>") exit() dataFile = open(sys.argv[1],"r") fileData = dataFile.read().split('\n') dataFile.close() [print(i) for i in fileData[::-1]]
import qualified Data.Text as T import qualified Data.Text.IO as TIO main :: IO () main = TIO.interact $ T.unlines . reverse . T.lines
Convert this Python block to Haskell, preserving its control flow and logic.
LIST = ["1a3c52debeffd", "2b6178c97a938stf", "3ycxdb1fgxa2yz"] print(sorted([ch for ch in set([c for c in ''.join(LIST)]) if all(w.count(ch) == 1 for w in LIST)]))
import qualified Data.Map.Strict as M import Data.Maybe (fromJust) import qualified Data.Set as S onceInEach :: [String] -> String onceInEach [] = [] onceInEach ws@(x : xs) = S.elems $ S.filter ((wordCount ==) . fromJust . flip M.lookup freq) ( foldr (S.intersection . S.fromList) ...
Port the following code from Python to Haskell with equivalent syntax and logic.
from math import floor, pow def isPrime(n): for i in range(2, int(n**0.5) + 1): if n % i == 0: return False return True def odd(n): return n and 1 != 0 def jacobsthal(n): return floor((pow(2,n)+odd(n))/3) def jacobsthal_lucas(n): return int(pow(2,n)+pow(-1,n)) d...
jacobsthal :: [Integer] jacobsthal = 0 : 1 : zipWith (\x y -> 2 * x + y) jacobsthal (tail jacobsthal) jacobsthalLucas :: [Integer] jacobsthalLucas = 2 : 1 : zipWith (\x y -> 2 * x + y) jacobsthalLucas (tail jacobsthalLucas) jacobsthalOblong :: [Integer] jacobsthalOblong = zipWith (*) jacobsthal (tail jacobsthal) isP...
Port the provided Python code into Haskell while preserving the original functionality.
from math import floor, pow def isPrime(n): for i in range(2, int(n**0.5) + 1): if n % i == 0: return False return True def odd(n): return n and 1 != 0 def jacobsthal(n): return floor((pow(2,n)+odd(n))/3) def jacobsthal_lucas(n): return int(pow(2,n)+pow(-1,n)) d...
jacobsthal :: [Integer] jacobsthal = 0 : 1 : zipWith (\x y -> 2 * x + y) jacobsthal (tail jacobsthal) jacobsthalLucas :: [Integer] jacobsthalLucas = 2 : 1 : zipWith (\x y -> 2 * x + y) jacobsthalLucas (tail jacobsthalLucas) jacobsthalOblong :: [Integer] jacobsthalOblong = zipWith (*) jacobsthal (tail jacobsthal) isP...
Ensure the translated Haskell code behaves exactly like the original Python snippet.
from sympy import Sieve def nsuccprimes(count, mx): "return tuple of <count> successive primes <= mx (generator)" sieve = Sieve() sieve.extend(mx) primes = sieve._list return zip(*(primes[n:] for n in range(count))) def check_value_diffs(diffs, values): "Differences between successive values ...
import Data.Numbers.Primes (primes) type Result = [(String, [Int])] oneMillionPrimes :: Integral p => [p] oneMillionPrimes = takeWhile (<1_000_000) primes getGroups :: [Int] -> Result getGroups [] = [] getGroups ps@(n:x:y:z:xs) | x-n == 6 && y-x == 4 && z-y == 2 = ("(6 4 2)", [n, x, y, z]) : getGroups...
Please provide an equivalent version of this Python code in Haskell.
def digitSumsPrime(n): def go(bases): return all( isPrime(digitSum(b)(n)) for b in bases ) return go def digitSum(base): def go(n): q, r = divmod(n, base) return go(q) + r if n else 0 return go def main(): xs = [ ...
import Data.Bifunctor (first) import Data.List.Split (chunksOf) import Data.Numbers.Primes (isPrime) digitSumsPrime :: Int -> [Int] -> Bool digitSumsPrime n = all (isPrime . digitSum n) digitSum :: Int -> Int -> Int digitSum n base = go n where go 0 = 0 go n = uncurry (+) (first go $ quotRem n base) mai...
Rewrite this program in Haskell while keeping its functionality equivalent to the Python version.
from itertools import accumulate, chain, takewhile def primeSums(): return ( x for x in enumerate( accumulate( chain([(0, 0)], primes()), lambda a, p: (p, p + a[1]) ) ) if isPrime(x[1][1]) ) def main(): for x in take...
import Data.List (scanl) import Data.Numbers.Primes (isPrime, primes) indexedPrimeSums :: [(Integer, Integer, Integer)] indexedPrimeSums = filter (\(_, _, n) -> isPrime n) $ scanl (\(i, _, m) p -> (succ i, p, p + m)) (0, 0, 0) primes main :: IO () main = mapM_ print $ takeWhile (\(_, ...
Translate this program into Haskell but keep the logic exactly as in Python.
from itertools import accumulate, chain, takewhile def primeSums(): return ( x for x in enumerate( accumulate( chain([(0, 0)], primes()), lambda a, p: (p, p + a[1]) ) ) if isPrime(x[1][1]) ) def main(): for x in take...
import Data.List (scanl) import Data.Numbers.Primes (isPrime, primes) indexedPrimeSums :: [(Integer, Integer, Integer)] indexedPrimeSums = filter (\(_, _, n) -> isPrime n) $ scanl (\(i, _, m) p -> (succ i, p, p + m)) (0, 0, 0) primes main :: IO () main = mapM_ print $ takeWhile (\(_, ...
Produce a language-to-language conversion: from Python to Haskell, same semantics.
from itertools import (chain, permutations) from functools import (reduce) from math import (gcd) def main(): digits = [1, 2, 3, 4, 6, 7, 8, 9] lcmDigits = reduce(lcm, digits) sevenDigits = ((delete)(digits)(x) for x in [1, 4, 7]) print( max( ( ...
import Data.List (maximumBy, permutations, delete) import Data.Ord (comparing) import Data.Bool (bool) unDigits :: [Int] -> Int unDigits = foldl ((+) . (10 *)) 0 ds :: [Int] ds = [1, 2, 3, 4, 6, 7, 8, 9] lcmDigits :: Int lcmDigits = foldr1 lcm ds sevenDigits :: [[Int]] sevenDigits = (`delete` ds) <$> [1, 4, 7] ...
Convert this Python snippet to Haskell and keep its semantics consistent.
from itertools import (chain, permutations) from functools import (reduce) from math import (gcd) def main(): digits = [1, 2, 3, 4, 6, 7, 8, 9] lcmDigits = reduce(lcm, digits) sevenDigits = ((delete)(digits)(x) for x in [1, 4, 7]) print( max( ( ...
import Data.List (maximumBy, permutations, delete) import Data.Ord (comparing) import Data.Bool (bool) unDigits :: [Int] -> Int unDigits = foldl ((+) . (10 *)) 0 ds :: [Int] ds = [1, 2, 3, 4, 6, 7, 8, 9] lcmDigits :: Int lcmDigits = foldr1 lcm ds sevenDigits :: [[Int]] sevenDigits = (`delete` ds) <$> [1, 4, 7] ...
Please provide an equivalent version of this Python code in Haskell.
def jacobi(a, n): if n <= 0: raise ValueError("'n' must be a positive integer.") if n % 2 == 0: raise ValueError("'n' must be odd.") a %= n result = 1 while a != 0: while a % 2 == 0: a /= 2 n_mod_8 = n % 8 if n_mod_8 in (3, 5): ...
jacobi :: Integer -> Integer -> Integer jacobi 0 1 = 1 jacobi 0 _ = 0 jacobi a n = let a_mod_n = rem a n in if even a_mod_n then case rem n 8 of 1 -> jacobi (div a_mod_n 2) n 3 -> negate $ jacobi (div a_mod_n 2) n 5 -> negate $ jacobi (div a_mod_n 2) n ...
Can you help me rewrite this code in Haskell instead of Python, keeping it the same logically?
def jacobi(a, n): if n <= 0: raise ValueError("'n' must be a positive integer.") if n % 2 == 0: raise ValueError("'n' must be odd.") a %= n result = 1 while a != 0: while a % 2 == 0: a /= 2 n_mod_8 = n % 8 if n_mod_8 in (3, 5): ...
jacobi :: Integer -> Integer -> Integer jacobi 0 1 = 1 jacobi 0 _ = 0 jacobi a n = let a_mod_n = rem a n in if even a_mod_n then case rem n 8 of 1 -> jacobi (div a_mod_n 2) n 3 -> negate $ jacobi (div a_mod_n 2) n 5 -> negate $ jacobi (div a_mod_n 2) n ...
Produce a functionally identical Haskell code for the snippet given in Python.
from itertools import permutations from operator import mul from math import fsum from spermutations import spermutations def prod(lst): return reduce(mul, lst, 1) def perm(a): n = len(a) r = range(n) s = permutations(r) return fsum(prod(a[i][sigma[i]] for i in r) for sigma in s) def det(a): ...
sPermutations :: [a] -> [([a], Int)] sPermutations = flip zip (cycle [1, -1]) . foldl aux [[]] where aux items x = do (f, item) <- zip (cycle [reverse, id]) items f (insertEv x item) insertEv x [] = [[x]] insertEv x l@(y:ys) = (x : l) : ((y :) <$>) (insertEv x ys) elemPos :: [[a]] -> Int -> I...
Keep all operations the same but rewrite the snippet in Haskell.
from itertools import permutations from operator import mul from math import fsum from spermutations import spermutations def prod(lst): return reduce(mul, lst, 1) def perm(a): n = len(a) r = range(n) s = permutations(r) return fsum(prod(a[i][sigma[i]] for i in r) for sigma in s) def det(a): ...
sPermutations :: [a] -> [([a], Int)] sPermutations = flip zip (cycle [1, -1]) . foldl aux [[]] where aux items x = do (f, item) <- zip (cycle [reverse, id]) items f (insertEv x item) insertEv x [] = [[x]] insertEv x l@(y:ys) = (x : l) : ((y :) <$>) (insertEv x ys) elemPos :: [[a]] -> Int -> I...
Translate this program into Haskell but keep the logic exactly as in Python.
Python 3.9.0 (tags/v3.9.0:9cf6752, Oct 5 2020, 15:34:40) [MSC v.1927 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license()" for more information. >>> x = [n for n in range(1000) if str(sum(int(d) for d in str(n))) in str(n)] >>> len(x) 48 >>> for i in range(0, len(x), (stride:= 10)): print(str(x[i...
import Data.Char (digitToInt) import Data.List (isInfixOf) import Data.List.Split (chunksOf) digitSumIsSubString :: String -> Bool digitSumIsSubString = isInfixOf =<< show . foldr ((+) . digitToInt) 0 main :: IO () main = mapM_ putStrLn $ showMatches digitSumIsSubString <$> [999, 10000] showMatches :...
Write a version of this Python function in Haskell with identical behavior.
Python 3.9.0 (tags/v3.9.0:9cf6752, Oct 5 2020, 15:34:40) [MSC v.1927 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license()" for more information. >>> x = [n for n in range(1000) if str(sum(int(d) for d in str(n))) in str(n)] >>> len(x) 48 >>> for i in range(0, len(x), (stride:= 10)): print(str(x[i...
import Data.Char (digitToInt) import Data.List (isInfixOf) import Data.List.Split (chunksOf) digitSumIsSubString :: String -> Bool digitSumIsSubString = isInfixOf =<< show . foldr ((+) . digitToInt) 0 main :: IO () main = mapM_ putStrLn $ showMatches digitSumIsSubString <$> [999, 10000] showMatches :...
Translate this program into Haskell but keep the logic exactly as in Python.
>>> from random import randrange >>> def sattoloCycle(items): for i in range(len(items) - 1, 0, -1): j = randrange(i) items[j], items[i] = items[i], items[j] >>> >>> for _ in range(10): lst = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] sattoloCycle(lst) print(lst) [5, 8, 1, 2, 6, 4, 3, 9, 10, 7] [5, 9, 8, 10, 4, ...
import Control.Monad ((>=>), (>>=), forM_) import Control.Monad.Primitive import qualified Data.Vector as V import qualified Data.Vector.Mutable as M import System.Random.MWC type MutVec m a = M.MVector (PrimState m) a cyclicPermM :: PrimMonad m => Gen (PrimState m) -> MutVec m a -> m (MutVec m a) cyclicPermM rand...
Transform the following Python implementation into Haskell, maintaining the same output and logic.
>>> from random import randrange >>> def sattoloCycle(items): for i in range(len(items) - 1, 0, -1): j = randrange(i) items[j], items[i] = items[i], items[j] >>> >>> for _ in range(10): lst = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] sattoloCycle(lst) print(lst) [5, 8, 1, 2, 6, 4, 3, 9, 10, 7] [5, 9, 8, 10, 4, ...
import Control.Monad ((>=>), (>>=), forM_) import Control.Monad.Primitive import qualified Data.Vector as V import qualified Data.Vector.Mutable as M import System.Random.MWC type MutVec m a = M.MVector (PrimState m) a cyclicPermM :: PrimMonad m => Gen (PrimState m) -> MutVec m a -> m (MutVec m a) cyclicPermM rand...
Rewrite this program in Haskell while keeping its functionality equivalent to the Python version.
from ftplib import FTP ftp = FTP('kernel.org') ftp.login() ftp.cwd('/pub/linux/kernel') ftp.set_pasv(True) print ftp.retrlines('LIST') print ftp.retrbinary('RETR README', open('README', 'wb').write) ftp.quit()
module Main (main) where import Control.Exception (bracket) import Control.Monad (void) import Data.Foldable (for_) import Network.FTP.Client ( cwd , easyConnectFTP , getbinary , loginAnon ...
Ensure the translated Haskell code behaves exactly like the original Python snippet.
>>> import sqlite3 >>> conn = sqlite3.connect(':memory:') >>> conn.execute() <sqlite3.Cursor object at 0x013265C0> >>>
import Database.SQLite.Simple main = do db <- open "postal.db" execute_ db "\ \CREATE TABLE address (\ \addrID INTEGER PRIMARY KEY AUTOINCREMENT, \ \addrStreet TEXT NOT NULL, \ \addrCity TEXT NOT NULL, \ \addrState TEXT NOT NULL, \ \addrZIP TEXT NOT N...
Convert this Python block to Haskell, preserving its control flow and logic.
from itertools import count, islice def isBrazil(n): return 7 <= n and ( 0 == n % 2 or any( map(monoDigit(n), range(2, n - 1)) ) ) def monoDigit(n): def go(base): def g(b, n): (q, d) = divmod(n, b) def p(qr): retu...
import Data.Numbers.Primes (primes) isBrazil :: Int -> Bool isBrazil n = 7 <= n && (even n || any (monoDigit n) [2 .. n - 2]) monoDigit :: Int -> Int -> Bool monoDigit n b = let (q, d) = quotRem n b in d == snd (until (uncurry (flip ((||) . (d /=)) . (0 ==))) ((`quotRem` b) . fst) ...
Produce a functionally identical Haskell code for the snippet given in Python.
from itertools import count, islice def isBrazil(n): return 7 <= n and ( 0 == n % 2 or any( map(monoDigit(n), range(2, n - 1)) ) ) def monoDigit(n): def go(base): def g(b, n): (q, d) = divmod(n, b) def p(qr): retu...
import Data.Numbers.Primes (primes) isBrazil :: Int -> Bool isBrazil n = 7 <= n && (even n || any (monoDigit n) [2 .. n - 2]) monoDigit :: Int -> Int -> Bool monoDigit n b = let (q, d) = quotRem n b in d == snd (until (uncurry (flip ((||) . (d /=)) . (0 ==))) ((`quotRem` b) . fst) ...
Produce a functionally identical Haskell code for the snippet given in Python.
>>> with open('/dev/tape', 'w') as t: t.write('Hi Tape!\n') ... >>>
module Main (main) where main :: IO () main = writeFile "/dev/tape" "Hello from Rosetta Code!"
Keep all operations the same but rewrite the snippet in Haskell.
from itertools import islice class Recamans(): "Recamán's sequence generator callable class" def __init__(self): self.a = None self.n = None def __call__(self): "Recamán's sequence generator" nxt = 0 a, n = {nxt}, 0 self.a = a self.n = n ...
recaman :: Int -> [Int] recaman n = fst <$> reverse (go n) where go 0 = [] go 1 = [(0, 1)] go x = let xs@((r, i):_) = go (pred x) back = r - i in ( if 0 < back && not (any ((back ==) . fst) xs) then back else r + i , succ i) : ...
Transform the following Python implementation into Haskell, maintaining the same output and logic.
from itertools import islice class Recamans(): "Recamán's sequence generator callable class" def __init__(self): self.a = None self.n = None def __call__(self): "Recamán's sequence generator" nxt = 0 a, n = {nxt}, 0 self.a = a self.n = n ...
recaman :: Int -> [Int] recaman n = fst <$> reverse (go n) where go 0 = [] go 1 = [(0, 1)] go x = let xs@((r, i):_) = go (pred x) back = r - i in ( if 0 < back && not (any ((back ==) . fst) xs) then back else r + i , succ i) : ...
Change the programming language of this snippet from Python to Haskell without modifying what it does.
>>> Y = lambda f: (lambda x: x(x))(lambda y: f(lambda *args: y(y)(*args))) >>> fac = lambda f: lambda n: (1 if n<2 else n*f(n-1)) >>> [ Y(fac)(i) for i in range(10) ] [1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880] >>> fib = lambda f: lambda n: 0 if n == 0 else (1 if n == 1 else f(n-1) + f(n-2)) >>> [ Y(fib)(i) for i i...
newtype Mu a = Roll { unroll :: Mu a -> a } fix :: (a -> a) -> a fix = g <*> (Roll . g) where g = (. (>>= id) unroll) - this version is not in tail call position... fac :: Integer -> Integer fac = (fix $ \f n i -> if i <= 0 then n else f (i * n) (i - 1)) 1 { fibs :: () -> [Integer] fibs() = f...
Preserve the algorithm and functionality while converting the code from Python to Haskell.
from collections import namedtuple Circle = namedtuple("Circle", "x y r") circles = [ Circle( 1.6417233788, 1.6121789534, 0.0848270516), Circle(-1.4944608174, 1.2077959613, 1.1039549836), Circle( 0.6110294452, -0.6907087527, 0.9089162485), Circle( 0.3844862411, 0.2923344616, 0.2375743054), Circ...
data Circle = Circle { cx :: Double, cy :: Double, cr :: Double } isInside :: Double -> Double -> Circle -> Bool isInside x y c = (x - cx c) ^ 2 + (y - cy c) ^ 2 <= (cr c ^ 2) isInsideAny :: Double -> Double -> [Circle] -> Bool isInsideAny x y = any (isInside x y) approximatedArea :: [Circle] -> Int -> Double approx...
Transform the following Python implementation into Haskell, maintaining the same output and logic.
from collections import namedtuple Circle = namedtuple("Circle", "x y r") circles = [ Circle( 1.6417233788, 1.6121789534, 0.0848270516), Circle(-1.4944608174, 1.2077959613, 1.1039549836), Circle( 0.6110294452, -0.6907087527, 0.9089162485), Circle( 0.3844862411, 0.2923344616, 0.2375743054), Circ...
data Circle = Circle { cx :: Double, cy :: Double, cr :: Double } isInside :: Double -> Double -> Circle -> Bool isInside x y c = (x - cx c) ^ 2 + (y - cy c) ^ 2 <= (cr c ^ 2) isInsideAny :: Double -> Double -> [Circle] -> Bool isInsideAny x y = any (isInside x y) approximatedArea :: [Circle] -> Int -> Double approx...
Convert this Python snippet to Haskell and keep its semantics consistent.
fact = [1] for n in range(1, 12): fact.append(fact[n-1] * n) for b in range(9, 12+1): print(f"The factorions for base {b} are:") for i in range(1, 1500000): fact_sum = 0 j = i while j > 0: d = j % b fact_sum += fact[d] j = j//b if fact_su...
import Text.Printf (printf) import Data.List (unfoldr) import Control.Monad (guard) factorion :: Int -> Int -> Bool factorion b n = f b n == n where f b = sum . map (product . enumFromTo 1) . unfoldr (\x -> guard (x > 0) >> pure (x `mod` b, x `div` b)) main :: IO () main = mapM_ (uncurry (printf "Factorions for ba...