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We're actively looking for ideas on how to improve Weekly Challenges and would love to hear what you think!
Submit FeedbackCan anyone's flow solve this one?
000000190230000600000240000000000960000160070048070000001003405009008000006005800
(Mine can't! Fails with max iterations for the macro, even if set to 1000)
I just tested - this R solution gets it: https://community.alteryx.com/t5/Weekly-Challenge/Challenge-200-Sudoku-Solver/td-p/519517
@JohnJPS I guess you can't link to an individual reply on this forum. Your link just points to the first page of the topic.
EDIT: Ah! its the one you posted on the first page:
#
# This ianswer is taken from: https://www.kaggle.com/dmartin0409/sudoku-solver-in-r
#
library(stringr)
library(dplyr,warn.conflicts = FALSE)
sudoku <- read.Alteryx("#1", mode="data.frame")
# Define functions
# Convert the input data into a matrix
sudoku.matrix<-function(l) {
matrix(unlist(str_extract_all(l,'.')),nrow=9,ncol=9,byrow=TRUE)
}
# Perform the search for a value of an empty square
sudoku.square<-function(m,r,c) {
nums<-c(1:9)
# Quick search row and column and 3x3 square
rs <- 3 * ((r-1) %/% 3)
cs <- 3 * ((c-1) %/% 3) + 1:3
list <- sort(unique(c(m[r,],m[,c],m[rs+1,cs],m[rs+2,cs],m[rs+3,cs])))
miss <- ! (nums %in% list)
if (sum(miss) == 1) { # Return the value
return(nums[miss])
}
# Search square and eliminate cross values
for (k in nums[miss]) { # Step through each possible value
hit<-0
for (i in rs+1:3) {
for (j in cs) { # For each spot in the 3x3 square
if (! (i == r & j == c)) { # ...except for my spot
if (m[i,j] == 0 & hit >= 0) { # Find all open spots
if (k %in% m[i,] || k %in% m[,j]) { # This value is eliminated by criss-cross
hit<-k # So we found a possibile match
}
else {
hit<-0-1 # Force the loop to end because this value could be in the criss-cross
}
}
}
}
}
if (hit > 0 ) { # Return the value
return(hit)
}
}
# Search row and eliminate cross values
list <- sort(unique(c(m[r,])))
miss <- ! (nums %in% list)
for (k in nums[miss]) {
hit<-0
for (j in 1:9) { # For each column in my row
if (! j == c) { # ..except for my column
if (m[r,j] == 0 & hit >=0) { # Find all open spots
if (k %in% m[,j]) { # This value is eliminated
hit<-k # Found a possible match, keep going
}
else {
hit<-0-1 # Force the loop to end
}
}
}
}
if (hit > 0 ) { # Return the value
return(hit)
}
}
# Search column and eliminate cross values
list <- sort(unique(c(m[,c])))
miss <- ! (nums %in% list)
for (k in nums[miss]) {
hit<-0
for (i in 1:9) { # For each row in my column
if (! i == r) { # ..except for my row
if (m[i,c] == 0 & hit >=0) { # Find all open spots
if (k %in% m[i,]) { # This value is eliminated
hit<-k # Found a possible match, keep going
}
else {
hit<-0-1 # Force the loop to end
}
}
}
}
if (hit > 0 ) { # Return the value
return(hit)
}
}
# No value found
return(NULL)
}
sudoku.solve<-function(m,detail=FALSE,format.matrix=FALSE) {
scan<-1
while (scan == 1) {
scan<-0
for (i in sample(1:9)) {
for (j in 1:9) {
if (m[i,j] == 0) { # If the value is unknown "0"
a<-sudoku.square(m,i,j) # Search for possible values
if (! is.null(a)) {
scan<-1 # Force another scan
m[i,j]=as.character(a) # Set the value in the matrix
if (detail) { # Print the positio and number, and display the matrix
print(str_c("Position ",i,"x",j," == ",a))
print(m)
}
}
}
}
}
}
if (format.matrix) { # Return the matrix for easy display
return(m)
}
else { # Return the sting version for comparison to the data set
r<-NULL
for (i in 1:9) {
for (j in 1:9) {
r<-str_c(r,m[i,j])
}
}
return(r)
}
}
# Bulk quizes
# Convert the quizzes to a liset of matrices
q.matrix<-lapply(sudoku$quizzes,sudoku.matrix)
# Solve the quizzes and display the running time
system.time(SOL<-lapply(q.matrix,sudoku.solve))
# Sum up the matching solutions
SOL.matches<-sum(sudoku$solutions == SOL)
SOL.matches
SOL <- as.data.frame(SOL)
names(SOL) <- c("solutions")
write.Alteryx(SOL, 1)
I've coded in many languages in my career, but not R-code and I find quite cryptic! I've read through it a couple of times. but can't yet see what cleverness it is doing that my flow does not do...
@JohnJPS I found the R code in your posted solution on page 1. I replied asking a question and re-posted your R-code in my post using the
code sample markup
but my message must have got deleted. Perhaps I broke a rule and a moderator deleted it, do you think?
Anyway, reading your R-code, I can't spot what it is doing to solve the puzzle that my iterative macro is not doing, and wanted to discuss it with you.
My iterative macro loops infinitely if it can't solve at least one more cell in the puzzle on each iteration. How does your R-code avoid that problem?
@PaulRB, I can't be sure. If within the macro, making this example the first row of your macro input template, we put a sort between the final Join and the Summary tool, and sort on all columns, then look at the data at that stage: there are several rows for each row of quizzes/position/row/col/region/cell...so it's almost like at that stage, there are simply too many possibilities, such that grabbing "First" in the Summary tool is not reliable. I don't have a handy fix top of mind, but I wager some other solution thus far can do it.