I have written an algorithm which iteratively solves the problem. The first iteration consists of 6 steps and all the following iterations consist of 5 steps (first step is skipped).
What I want to calculate is the current (local) step in the iteration from current global step.
For example if there are 41 steps in total which means there are 8 iterations:
indices from 1 to 6 belong to 1st iteration
indices from 7 to 11 belong to second iteration
...
For calculating the current iteration I have written the following code:
if(currentStep <= 6)
iteration = 1;
else
iteration = floor((currentStep - 7)/5) + 2;
end
The problem remains in calculating local steps.
in first iteration the performed steps are: 1, 2, 3, 4, 5, 6
in all the following iterations the performing steps are 2, 3, 4, 5, 6
So what has to be done is to transform the array of global steps
[1 2 3 4 5 6 7 8 9 10 11 12 13 ... 41]
into array of local steps
[1 2 3 4 5 6 2 3 4 5 6 2 3 ... 6].
I would appreciate if anyone could help in finding the solution to a given problem.
Thank you!
local_step = [1 mod([0:39],5)+2]
Here is the solution in python:
L = range(1,42) # so L = [1,2,...,41]
s = [(i-2)%5+2 for i in L]
# adjust for the first step:
s[0]=1
# now s = [1,2,3,4,5,6,2,3,4,...,5,6]
Check this :
if(currentStep <= 6)
{localStep = currentStep;}
else
{localStep = currentStep - ((iteration - 1) * 5);}
Related
I am still pretty new at programming and I would appreciate any help on how to approach the following problem:
Given a matrix (3x5)
a = [1 2 3 4 5;
6 7 8 9 10;
11 12 13 14 15;]
I want to iterate through every row
For each row, I want each element to be checked
With each element, I want to store a separate array that holds the element and the next 2 elements.
Ex:
Row 1 = [1 2 3 4 5]
For element 1
return newArray = [1 2 3]
For element 2
return newArray = [2 3 4]
Getting stuck on part 3. How to make the for loop check only up to the next 2 elements and then continue to the next element in the row.
I took a shot at solving what you asked for, but I agree with the others that you need to think more about what you are trying to do and what you want your output to look like. Your request does not sound like something a beginner programmer would realistically use. I am not sure what shape you want to store your "separate array"s in. I have options below for keeping them in a vector or in the original shape of a.
function nexttwo(row, i)
newarray::Vector{Any} = [row[i]]
for j=1:2
i+=1
if length(row) >= i
push!(newarray, row[i])
else
push!(newarray, nothing)
end
end
return newarray
end
function collectnexttwo(a)
result_collection = []
for i in axes(a,1)
for j in axes(a,2)
row = a[i,:]
newarray = nexttwo(row, j)
push!(result_collection, newarray)
end
end
return result_collection
end
function restoreshape(v, a)
permutedims(reshape(v, reverse(size(a))))
end
julia> a = [1 2 3 4 5; 6 7 8 9 10; 11 12 13 14 15;]
3×5 Matrix{Int64}:
1 2 3 4 5
6 7 8 9 10
11 12 13 14 15
julia> result = restoreshape(collectnexttwo(a), a)
3×5 Matrix{Any}:
Any[1, 2, 3] Any[2, 3, 4] Any[3, 4, 5] Any[4, 5, nothing] Any[5, nothing, nothing]
Any[6, 7, 8] Any[7, 8, 9] Any[8, 9, 10] Any[9, 10, nothing] Any[10, nothing, nothing]
Any[11, 12, 13] Any[12, 13, 14] Any[13, 14, 15] Any[14, 15, nothing] Any[15, nothing, nothing]
I think that you have some problems with the statement of what you want to achieve. That can often make a programming assignment much harder.
Restating what you have already:
I want to iterate through every row
This is pretty easy
for row = 1:size(a)[1]
...
end
For each row, I want each element to be checked
This is where things begin to get squishy? What do you mean by "checked". Let's assume you have some function called checkElement.
With each element, I want to store a separate array that holds the element and the next 2 elements.
How long do you want that separate array to live? Do you just want to hold 3 elements? Or three elements for every cell of the original (i.e. have a 3x5x3 result for a 3x5 input like you show)
Also, what do you want to do about elements 4 and 5 in each row? What values do you want to use for their "next" elements? You could use missing as a value or NaN. Or you could make the result just not contain the problematic inputs.
If you answer these questions, you are likely to find it much easier to write the code you need.
I have a problem with coming up with an algorithm for the "graph" :(
Maybe one of you would be so kind and direct me somehow <3
The task is as follows:
We have a board of at least 3x3 (it doesn't have to be a square, it can be 4x5 for example). The user specifies a sequence of moves (as in Android lock pattern). The task is to check how many points he has given are adjacent to each other horizontally or vertically.
Here is an example:
Matrix:
1 2 3 4
5 6 7 8
9 10 11 12
The user entered the code: 10,6,7,3
The algorithm should return the number 3 because:
10 is a neighbor of 6
6 is a neighbor of 7
7 is a neighbor of 3
Eventually return 3
Second example:
Matrix:
1 2 3
4 5 6
7 8 9
The user entered the code: 7,8,6,3
The algorithm should return 2 because:
7 is a neighbor of 8
8 is not a neighbor of 6
6 is a neighbor of 3
Eventually return 2
Ofc number of operations equal length of array - 1
Sorry for "ile" and "tutaj", i'm polish
If all the codes are unique, use them as keys to a dictionary (with (row/col) pairs as values). Loop thru the 2nd item in user input to the end, check if math.Abs(cur.row-prev.row)+math.Abs(cur.col-prev.col)==1. This is not space efficient but deal with user input in linear complexity.
The idea is you have 4 conditions, one for each direction. Given any matrix of the shape n,m which is made of a sequence of integers AND given any element:
The element left or right will always be + or - 1 to the given element.
The element up or down will always be + or - m to the given element.
So, if abs(x-y) is 1 or m, then x and y are neighbors.
I demonstrate this in python.
def get_neighbors(seq,matrix):
#Conditions
check = lambda x,y,m: np.abs(x-y)==1 or np.abs(x-y)==m
#Pairs of sequences appended with m
params = zip(seq, seq[1:], [matrix.shape[1]]*(len(seq)-1))
neighbours = [check(*i) for i in params]
count = sum(neighbours)
return neighbours, count
seq = [7,8,6,3]
matrix = np.arange(1,10).reshape((3,3))
neighbours, count = get_neighbors(seq, matrix)
print('Matrix:')
print(matrix)
print('')
print('Sequence:', seq)
print('')
print('Count of neighbors:',count)
Matrix:
[[ 1 2 3 4]
[ 5 6 7 8]
[ 9 10 11 12]]
Sequence: [10, 6, 7, 3]
Count of neighbors: 3
Another example -
seq = [7,8,6,3]
matrix = np.arange(1,10).reshape((3,3))
neighbours, count = get_neighbors(seq, matrix)
Matrix:
[[1 2 3]
[4 5 6]
[7 8 9]]
Sequence: [7, 8, 6, 3]
Count of neighbors: 2
So your input is the width of a table, the height of a table, and a list of numbers.
W = 4, H = 3, list = [10,6,7,3]
There are two steps:
Convert the list of numbers into a list of row/column coordinates (1 to [1,1], 5 to [2,1], 12 to [3,4]).
In the new list of coordinates, find consequent pairs, which have one coordinate identical, and the other one has a difference of 1.
Both steps are quite simple ("for" loops). Do you have problems with 1 or 2?
Working on a dicegame for school and I have trouble figuring out how to do automatic calculation of the result. (we don't have to do it automatically, so I could just let the player choose which dice to use and then just check that the user choices are valid) but now that I have started to think about it I can't stop...
the problem is as follows:
I have six dice, the dice are normal dice with the value of 1-6.
In this example I have already roled the dice and they have the following values:
[2, 2, 2, 1, 1, 1]
But I don't know how to calulate all combinations so that as many dicecombinations as possible whose value combined(addition) are 3 (in this example) are used.
The values should be added together (for example a die with value 1 and another die with the value 2 are together 3) then there are different rounds in the game where the aim is to get different values (which can be a combination(addition) of die-values for example
dicevalues: [2, 2, 2, 2, 2, 2]
could give the user a total of 12 points if 4 is the goal for the current round)
2 + 2 = 4
2 + 2 = 4
2 + 2 = 4
if the goal of the round instead where 6 then the it would be
2 + 2 + 2 = 6
2 + 2 + 2 = 6
instead which would give the player 12 points (6 + 6)
[1, 3, 6, 6, 6, 6]
with the goal of 3 would only use the dice with value 3 and discard the rest since there is no way to add them up to get three.
2 + 1 = 3
2 + 1 = 3
2 + 1 = 3
would give the user 9 points.
but if it where calculated the wrong way and the ones where used up together instead of each 1 getting apierd with a two 1 + 1 + 1 which would only give the player 3 points och the twos couldn't be used.
Another example is:
[1, 2, 3, 4, 5, 6]
and all combinations that are equal to 6 gives the user points
[6], [5, 1], [4 ,2]
user gets 18 points (3 * 6)
[1 ,2 ,3], [6]
user gets 12 points (2 * 6) (Here the user gets six points less due to adding upp 1 + 2 + 3 instead of doing like in the example above)
A dice can have a value between 1 and 6.
I haven't really done much more than think about it and I'm pretty sure that I could do it right now, but it would be a solution that would scale really bad if I for example wanted to use 8 dices instead and every time I start programming on it I start to think that have to be a better/easier way of doing it... Anyone have any suggestion on where to start? I tried searching for an answer and I'm sure it's out there but I have problem forumulating a query that gives me relevant result...
With problems that look confusing like this, it is a really good idea to start with some working and examples. We have 6 die, with range [1 to 6]. The possible combinations we could make therefore are:
target = 2
1 combination: 2
2 combination: 1+1
target = 3
1 combination: 3
2 combination: 2+1
3 combination: 1+1+1
target = 4
1 combination: 4
2 combination: 3+1
2+2
3 combination: 2+1+1
4 combination: 1+1+1+1
target = 5
1 combination: 5
2 combination: 4+1
3+2
3 combination: 2+2+1
4 combination: 2+1+1+1
5 combination: 1+1+1+1+1
See the pattern? Hint, we go backwards from target to 1 for the first number we can add, and then given this first number, and the size of the combination, there is a limit to how big subsequent numbers can be!
There is a finite list of possible combinations. You can by looking for 1 combination scores, and remove these from the die available. Then move on to look for 2 combination scores, etc.
If you want to read more about this sub-field of mathematics, the term you need to look for is "Combinatorics". Have fun!
I'm working on a code using Matlab in which I need to find the least number lists (in some set of given lists) necessary to cover all the elements of a reference list.
For example, say my reference list is
X = [0 1 2 3 4 5 6 7 8 9]
And I have a given set of lists as follows:
A = [0 1 3 5 6 7 9]
B = [0 1 2 3 4]
C = [5 6 7 8 9]
D = [1 2 3 4]
E = [1 5 7 8]
The smallest number of lists needed to cover every element in X is 2 (B and C), however, if I initially only search for the list that covers the most elements (A) and then try to find other lists that will cover the remaining elements, I'll end up using at least 3 lists. What would be the best way to write a code that can search for the smallest number of lists necessary for this (it would give me an output of B and C)? Any help at all would be greatly appreciated...even just a conceptual explanation (not actual code) of how to best approach this problem would be a huge help!
Approach #1: Iterative "brute-force" of all possible combinations
Below is one possible algorithm that illustrates how to solve the problem. The code itself should be self-explanatory, but the idea is that we test all possible combinations of lists until a valid one is found (hence we don't encounter the problem you described where we mistakenly choose lists based on their length).
function varargout = q36323802
R = [0 1 2 3 4 5 6 7 8 9]; %// Reference List
L = {... // As per Dan's suggestion:
[0 1 3 5 6 7 9]
[0 1 2 3 4]
[5 6 7 8 9]
[1 2 3 4]
[1 5 7 8]
};
out = []; %// Initialize output
%% // Brute-force approach:
nLists = numel(L);
for indN = 1:nLists
setCombinationsToCheck = nchoosek(1:nLists,indN);
for indC = 1:size(setCombinationsToCheck,1)
u = unique(cat(2,L{setCombinationsToCheck(indC,:)}));
if all(ismember(R,u))
out = setCombinationsToCheck(indC,:);
disp(['The minimum number of required sets is ' num2str(indN) ...
', and their indices are: ' num2str(out)]);
return;
end
end
end
disp('No amount of lists found to cover the reference.');
if nargout > 0
varargout{1} = out;
end
For your example the output is:
The minimum number of required sets is 2, and their indices are: 2 3
Note(s):
This method does some redundant computations by not using lists of length n-1 in iteration n, which were already found in previous iterations (when applicable). A recursive solution may work in this case.
There is probably a way to vectorize this, which I did not really think about in depth.
I assumed all inputs are row vectors. There would have to be some extra steps if this is not the case.
Thanks go to Adiel for suggesting some improvements, and for Amro for finding some bugs!
Approach #2: Tree search Experimental
I've attempted to also build a recursive solver. Now it finds a solution, but it's not general enough (actually the problem is that it only returns the first result, not necessarily the best result). The reasoning behind this approach is that we can treat your question as a tree search problem, and so we can employ search/pathfinding algorithms (see BFS, DFS, IDS etc.). I think the algorithm below is closest to DFS. As before, this should mainly illustrate an approach to solving your problem.
function q36323802_DFS(R,L)
%% //Input checking:
if nargin < 2 || isempty(L)
L = {... // As per Dan's suggestion:
[0 1 3 5 6 7 9]
[0 1 2 3 4]
[5 6 7 8 9]
[1 2 3 4]
[1 5 7 8]
};
end
if nargin < 1 || isempty(R)
R = [0 1 2 3 4 5 6 7 8 9]; %// Reference List
end
%% // Algorithm (DFS: breadth-first search):
out = DFS_search(R,L,0);
if isempty(out)
disp('No amount of lists found to cover the reference.');
else
disp(['The minimum number of required sets is ' num2str(numel(out)) ...
', and their indices are: ' num2str(out)]);
end
end
function out = DFS_search(R,L,depth)
%// Check to see if we should stop:
if isempty(R) || isempty(L)
% // Backtrack here?
out = [];
return;
end
if isnan(R)
out = [];
return;
end
nLists = numel(L);
reducedR = cellfun(#(R,L)setdiff(R,L),repmat({R},[nLists,1]),L,'UniformOutput',false)';
%'// We consider a case where the reduction had no effect as "hopeless" and
%// "drop" it.
isFullCoverage = cellfun(#isempty,reducedR);
isHopeless = cellfun(#(R)all(isnan(R)),reducedR) | cellfun(#(rR)isequal(rR,R),reducedR);
reducedR(isHopeless) = deal({NaN});
if all(isHopeless) && ~any(isFullCoverage)
out = [];
return
end
if any(isFullCoverage) %// Check current "breadth level"
out = find(isFullCoverage,1,'first');
return
else
for indB = 1:nLists
out = DFS_search(reducedR{indB},L,depth+1);
if ~isempty(out)
out = [indB out]; %#ok
%// TODO: test if one of the sets is covered by the others and remove it
%// from the list "out".
%// Also, keep track of the best path and only return (finally) if shortest
return
end
end
end
end
A similar solution to Dev-iL's 1st approach, by Amro:
function varargout = q36323802A
R = [0 1 2 3 4 5 6 7 8 9];
names = {'A' 'B' 'C' 'D' 'E'};
L = {...
[0 1 3 5 6 7 9]
[0 1 2 3 4]
[5 6 7 8 9]
[1 2 3 4]
[1 5 7 8]
};
N = numel(L);
%// powerset of L: set of all subsets (excluding empty set)
powerset = cell(1,N);
for k=1:N
sets = nchoosek(1:N, k);
powerset{k} = num2cell(sets,2);
end
powerset = cat(1, powerset{:});
%// for each possible subset, check if it covers the target R
mask = false(size(powerset));
for i=1:numel(powerset)
elems = unique([L{powerset{i}}]);
mask(i) = all(ismember(R, elems));
end
if ~any(mask), error('cant cover target'); end
%// from candidates, choose the one with least amount of sets
candidates = powerset(mask);
len = cellfun(#numel, candidates);
[~,idx] = min(len);
out = candidates{idx};
varargout{1} = names(out);
I'm looking for the best way to accomplish the following tasks:
Given 4 non-repeatable numbers between 1 and 9.
Given 2 numbers between 1 and 6.
Adding up the two numbers (1 to 6), check to see if there is a way make that same number using the four non-repeatable numbers (1 to 9), plus you may not even have to use all four numbers.
Example:
Your four non-repeatable (1 to 9) numbers are: 2, 4, 6, and 7
Your two numbers between 1 and 6 are: 3 and 3
The total for the two numbers is 3 + 3 = 6.
Looking at the four non-repeatable (1 to 9) numbers, you can make a 6 in two different ways:
2 + 4 = 6
6 = 6
So, this example returns "yes, there is a possible solution".
How do I accomplish this task in the most efficient, cleanest way possible, algorithmic-ally.
enter code hereSince the number of elements here is 4 so we should not worry about efficiency.
Just loop over 0 to 15 and use it as a bit mask to check what are the valid results that can be generated.
Here is a code in python to give you idea.
a = [2,4,6,7]
for i in range(16):
x = i
ans = 0
for j in range(4):
if(x%2):
ans += a[j]
x /= 2
print ans,
0 2 4 6 6 8 10 12 7 9 11 13 13 15 17 19