There is this question which cut the ropes using length from the sets (a,b,c) and return the maximum number of ropes that can be cut from the larger rope .I want a function to print the length which is cut. for example if n=5 and the set is (2,1,3). I want to print all the ways to cut the rope like (2,3) ,(1,2,2) etc.I would know how do you choose using recursion the path to 1 leaf .Like here we need to print the maximize the number of ropes that are cut.like (1,1,1,1,1).
print the rope
int func(n){
if(n==0)return 0;
if(n<0)return -1;
return 1+max(func(n-a),func(n-b),func(n-c);
}
It is this question Find the maximum number of pieces a rod can be cut but the added part is to print the segments also.
Related
I have a contiguous set of numbers up to a maximum (1...y). Im trying to find in which increment (defined by another value x) a given number (z) falls within that set.
Below is an image that best describes what I'm trying to find.
Is there a formula I can use with the available information to achieve this?
n = ceil(z*x/y);
In your example, the size of the range is divisible by the number of bins, so that all bins have equal size. If that condition does not hold then there may be some further questions about edge cases.
I have graphs of sets of points like:-
There are up to 1 million points on each graph. You can see that the points are scattered over a grid of cells, each sized 200 x 100 units. So there are 35 cells shown.
Is there an efficient way to count how many points there are in each cell? The brute force approach seems to be to parse the data 35 times with a whole load of combined is less or greater than statements.
Some of the steps below could be optimized in the sense that you could perform some of these as you build up the data set. However I'll assume you are just given a series of points and you have to find which cells they fit into. If you can inject your own code into the step that builds up the graph, you could do the stuff I wrote below along side of building the graph instead of after the fact.
You're stuck with brute force in the case of just being given the data, there's no way you can know otherwise since you have to visit each point at least once to figure out what cell it is in. Therefore we are stuck with O(n). If you have some other knowledge you could exploit, that would be up to you to utilize - but since it wasn't mentioned in the OP I will assume we're stuck with brute force.
The high level strategy would be as follows:
// 1) Set rectangle bounds to have minX/Y at +inf, and maxX/Y to be -inf
// or initialize it with the first point
// 2) For each point:
// Set the set the min with min(point.x, bounds.min.x)
// Same for the max as well
// 3) Now you have your bounds, you divide it by how many cells fit onto each
// axis while taking into account that you might need to round up with division
// truncating the results, unless you cast to float and ceil()
int cols = ceil(float(bounds.max.x - bounds.min.x) / CELL_WIDTH);
int rows = ceil(float(bounds.max.y - bounds.min.y) / CELL_HEIGHT);
// 4) You have the # of cells for the width and height, so make a 2D array of
// some sort that is w * h cells (each cell contains 32-bit int at least) and
// initialize to zero if this is C or C++
// 5) Figure out the cell number by subtracting the bottom left corner of our
// bounds (which should be the min point on the x/y axis that we found from (1))
for (Point p in points):
int col = (p.x - minX) / cellWidth;
int row = (p.y - minY) / cellHeight;
data[row][col]++;
Optimizations:
There are some ways we might be able to speed this up off the top of my head:
If you have powers of two with the cell width/height, you could do some bit shifting. If it's a multiple of ten, this might possibly speed things up if you aren't using C or C++, but I haven't profiled this so maybe hotspot in Java and the like would do this for you anyways (and no idea about Python). Then again 1 million points should be pretty fast.
We don't need to go over the whole range at the beginning, we could just keep resizing our table and adding new rows and columns if we find a bigger value. This way we'd only do one iteration over all the points instead of two.
If you don't care about the extra space usage and your numbers are positive only, you could avoid the "translate to origin" subtraction step by just assuming everything is already relative to the origin and not subtract at all. You could get away with this by modifying step (1) of the code to have the min start at 0 instead of inf (or the first point if you chose that). This might be bad however if your points are really far out on the axis and you end up creating a ton of empty slots. You'd know your data and whether this is possible or not.
There's probably a few more things that can be done but this would get you on the right track to being efficient with it. You'd be able to work back to which cell it is as well.
EDIT: This assumes you won't have some really small cell width compared to the grid size (like your width being 100 units, but your graph could span by 2 million units). If so then you'd need to look into possibly sparse matrices.
Given some points in plane (upto 500 points), no 3 collinear. We have to determine the number of triangles whose vertices are from the given points and that contain exactly N points inside them. How to efficiently solve this problem? The naive O(n^4) algorithm is too slow. Any better approach?
You could try thinking of the triangle as the intersection of three half-spaces. To find the number of points inside a triangle A, B, C first consider the set of points on one side of the infinite line in direction AB. Let these sets L(AB) and R(AB) for points of the left and right. Similarly you the same with other two edges and build sets L(AC) and R(AC) and sets L(BC) and R(BC).
So the number of points in ABC will be the number of points in the intersection of L(AB), L(AC) and L(BC). (You might want to consider R(AB) instead depending on the orientation of the triangle).
Now if we want to consider the full set of 500 points. First take all pairs of points AB and construct the sets L(AB) and R(AB). This will take O(n^3) operations.
Next we test all triangles and find the intersections of the three sets. If we use some hash table structure for the sets then to find the intersection points is like a hashtable lookups. If L(AB) has l elements, L(AC) has m elements and L(BC) n elements. Say l > m > n. For each point in L(BC) we need to do a lookup in L(AC) and L(BC) so thats a maximum of 2n hashtable lookups.
It might be faster to consider a geometric lookup table.
Divide your whole domain into a coarse grid say a 10 by 10 grid. We can then put each point into a set G(i,j). We can then split the sets L(AB) into each grid cell. Say call these sets L(AB,i,j) and R(AB,i,j). In testing for intersections first workout which grid cells lie in the intersection. This dramatically reduces the search space and as each set L(AB,i,j) contain fewer members there will be fewer hashtable lookups.
Actually I happened to encounter similar problem recently but the only difference was that there were around 300 pts and I solved it using bitset (C++ STL). For every pair of points, say (x[i],y[i]) and (x[j],y[j]), I formed a bitset<302>B[i][j] and B[i][j][k] stores 1 if k-th point is above line segment from point i to point j else I would store 0.
Now in a brute force manner I get three points so as to form a triangle, lets say (x[i],y[i]), (x[j],y[j]) and (x[k],y[k]), then a point,say z-th point ,would be inside triangle if B[i][j][z]==B[i][j][k] && B[j][k][z]==B[j][k][i] && B[k][i][z]==B[k][i][j] because a point inside triangle would show similar sign w.r.t. a side of triangle as the third point of triangle(one which is not on this side).
So i get three bitset variables P=B[i][j], Q=B[j][k] and R=B[k][i] and there taking there bitwise AND then applying count() function to give me the active number of bits and hence the number of points within the triangle. But make sure you change variable P such that it gives B[i][j][k]=1 if not then take bitwise not (~) of this variable.
Though the above solution is problem specific, i hope it helps. This is the problem link: http://usaco.org/current/index.php?page=viewproblem&cpid=660
I am new to using PsychoPy and I have programmed a few simple tasks. I am currently really struggling to program a word dot probe. I do not want to use coder, simply because the rest of my research team need to be able to easily edit the program, and work and use it.
In case anyone is wondering what my specific problem is, I cannot seem to get the pictures to load at the same time correctly and do not know how to get a probe to appear behind one of the pictures once the pictures have disappeared.
Timing
The timing issue can be solved by inserting an ISI period in the beginning of the trial, e.g. during a fixation cross. This allows psychopy to load the images in the background so that they are ready for presentation.
Truly random dot position
In your case, you want the dot position to be random, independently of image. This is one of the cases that TrialHandler does not handle and I suspect you need to insert a code component to make this work. For true randomness but only 50% probability in the limit of infinite trials, simply put this in a code component under "begin routine":
x = (np.random.binomial(1, prob) - 0.5) * xdist
y = 0
dot.pos = [x, y]
and change dot to the name of your dot stimulus, y is the vertical offset, x is the horizontal offset (here varying between trials), xdist is the distance between the dot positions, and prob is the chance of the dot appearing to the right. You probably want to set this to 0.5, i.e. 50 %.
Balanced dot position
If you want the dot to appear at each side exactly the same number of times, you can do the following in the code component:
Under "begin experiment", make a list with the exact length of the number of trials:
dotPos = [0, 1] * int(round(numberOfTrials/2)) # create the correct number of left/right (coded as 0 and 1). [0,1] yields 50%. [0,0,0,1] and /4 would yield 25 % etc.
np.random.shuffle(dotPos) # randomize order
Then under "begin routine" do something akin to what we did above:
x = (dotPos.pop() - 0.5) * xdist # dotPos.pop() takes returns the last element while removing it from the list.
y = 0
dot.pos = [x, y]
Naturally, if the number of trials is uneven, one position will be occupied one more time than the other.
Two dot positions for each condition
For the record, if the dot position is to be shown at each position for each image-combination, simply count each of these situations as conditions, i.e. give them a separate rows in the conditions file.
The question is, is there a straightforward mechanistic way to know which stars (gold, 1/2 gold, grey) to draw without using conditional logic, for example using a pointer to the correct star based on the result of a simple math function to generate star ratings in a five star display.
The point of this question is not Ratings Systems, but graphic display
I have a rating value of 0-100, floating point.
For example, in pseudocode:
bitmap1="http://myserver.com/goldstar.png"
bitmap2="http://myserver.com/halfstar.png"
bitmap3="http://myserver.com/greystar.png"
rating=89.003
possible=100
quantized=int(rating/possible)
imagearray=[bitmap1,bitmap2,bitmap3]
for i=0 to 4
selector=<compute which star to draw based on available data>
drawstars(25*i,100,imagearray[selector])
end for
Hopefully that will give you an idea of what i'm trying to do.
Think of the display as a scale, but in integers, so work in half stars. For example, if we have 5 stars, and can display half stars, our real scale is from 0 to 10. So, what we need to do is divide the original scale (0 to 100) down to give us 0 to 10. Then we do integer division by 2. The quotient of that will give us the number of complete stars to draw, and the remainder the number (0 or 1) of half stars to draw.
You may want to do some rounding first though -- otherwise, a rating of 5 stars will be essentially impossible to get (e.g., even an input score of 99 will still only give 4.5 stars).
Hm, if I were to take a stab at it...
In the for loop, go from i=1 to 5.
if (rating > i*20){ draw a gold star }
else{
if (rating > (i-1)*20 +10) {draw a half star }
else {draw a grey star}
}
This of course would give you the floor rating