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  • Millions of 3D points: How to find the 10 of them closest to a given point?

    - by Kazoom
    A point in 3-d is defined by (x,y,z). Distance d between any two points (X,Y,Z) and (x,y,z) is d= Sqrt[(X-x)^2 + (Y-y)^2 + (Z-z)^2]. Now there are a million entries in a file, each entry is some point in space, in no specific order. Given any point (a,b,c) find the nearest 10 points to it. How would you store the million points and how would you retrieve those 10 points from that data structure.

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  • millions of 3d points how to 10 closest to origin

    - by Kazoom
    A point in 3-d is defined by (x,y,z). Distance d between any two points (X,Y,Z) and (x,y,z) is d= Sqrt[(X-x)^2 + (Y-y)^2 + (Z-z)^2]. Now there are a million entries in a file, each entry is some point in space, in no specific order. Given any point (a,b,c) find the nearest 10 points to it. How would you store the million points and how would you retrieve those 10 points from that data structure.

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  • How do I print out objects in an array in python?

    - by Jonathan
    I'm writing a code which performs a k-means clustering on a set of data. I'm actually using the code from a book called collective intelligence by O'Reilly. Everything works, but in his code he uses the command line and i want to write everything in notepad++. As a reference his line is >>>kclust=clusters.kcluster(data,k=10) >>>[rownames[r] for r in k[0]] Here is my code: from PIL import Image,ImageDraw def readfile(filename): lines=[line for line in file(filename)] # First line is the column titles colnames=lines[0].strip( ).split('\t')[1:] rownames=[] data=[] for line in lines[1:]: p=line.strip( ).split('\t') # First column in each row is the rowname rownames.append(p[0]) # The data for this row is the remainder of the row data.append([float(x) for x in p[1:]]) return rownames,colnames,data from math import sqrt def pearson(v1,v2): # Simple sums sum1=sum(v1) sum2=sum(v2) # Sums of the squares sum1Sq=sum([pow(v,2) for v in v1]) sum2Sq=sum([pow(v,2) for v in v2]) # Sum of the products pSum=sum([v1[i]*v2[i] for i in range(len(v1))]) # Calculate r (Pearson score) num=pSum-(sum1*sum2/len(v1)) den=sqrt((sum1Sq-pow(sum1,2)/len(v1))*(sum2Sq-pow(sum2,2)/len(v1))) if den==0: return 0 return 1.0-num/den class bicluster: def __init__(self,vec,left=None,right=None,distance=0.0,id=None): self.left=left self.right=right self.vec=vec self.id=id self.distance=distance def hcluster(rows,distance=pearson): distances={} currentclustid=-1 # Clusters are initially just the rows clust=[bicluster(rows[i],id=i) for i in range(len(rows))] while len(clust)>1: lowestpair=(0,1) closest=distance(clust[0].vec,clust[1].vec) # loop through every pair looking for the smallest distance for i in range(len(clust)): for j in range(i+1,len(clust)): # distances is the cache of distance calculations if (clust[i].id,clust[j].id) not in distances: distances[(clust[i].id,clust[j].id)]=distance(clust[i].vec,clust[j].vec) #print 'i' #print i #print #print 'j' #print j #print d=distances[(clust[i].id,clust[j].id)] if d<closest: closest=d lowestpair=(i,j) # calculate the average of the two clusters mergevec=[ (clust[lowestpair[0]].vec[i]+clust[lowestpair[1]].vec[i])/2.0 for i in range(len(clust[0].vec))] # create the new cluster newcluster=bicluster(mergevec,left=clust[lowestpair[0]], right=clust[lowestpair[1]], distance=closest,id=currentclustid) # cluster ids that weren't in the original set are negative currentclustid-=1 del clust[lowestpair[1]] del clust[lowestpair[0]] clust.append(newcluster) return clust[0] def kcluster(rows,distance=pearson,k=4): # Determine the minimum and maximum values for each point ranges=[(min([row[i] for row in rows]),max([row[i] for row in rows])) for i in range(len(rows[0]))] # Create k randomly placed centroids clusters=[[random.random( )*(ranges[i][1]-ranges[i][0])+ranges[i][0] for i in range(len(rows[0]))] for j in range(k)] lastmatches=None for t in range(100): print 'Iteration %d' % t bestmatches=[[] for i in range(k)] # Find which centroid is the closest for each row for j in range(len(rows)): row=rows[j] bestmatch=0 for i in range(k): d=distance(clusters[i],row) if d<distance(clusters[bestmatch],row): bestmatch=i bestmatches[bestmatch].append(j) # If the results are the same as last time, this is complete if bestmatches==lastmatches: break lastmatches=bestmatches # Move the centroids to the average of their members for i in range(k): avgs=[0.0]*len(rows[0]) if len(bestmatches[i])>0: for rowid in bestmatches[i]: for m in range(len(rows[rowid])): avgs[m]+=rows[rowid][m] for j in range(len(avgs)): avgs[j]/=len(bestmatches[i]) clusters[i]=avgs return bestmatches

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  • how to determine base of a number?

    - by evil.coder
    Given a integer number and its reresentation in some arbitrary number system. The purpose is to find the base of the number system. For example, number is 10 and representation is 000010, then the base should be 10. Another example: number 21 representation is 0010101 then base is 2. One more example is: number is 6 and representation os 10100 then base is sqrt(2). Does anyone have any idea how to solve such problem?

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  • Solve math question in PHP

    - by Koning WWWWWWWWWWWWWWWWWWWWWWW
    The user can enter a math problem like 5 + 654, 6 ^ 24, 2!, sqrt(543), log(54), sin 5, sin(50). After some reformatting (e.g. change sin 5 into sin(5)), and doing an eval, PHP gives me the right result. However, this is quite unsafe. Can anyone point me in the right direction parsing and solving a math question like the examples above, which is safe? Thanks.

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  • Steganography Experiment - Trouble hiding message bits in DCT coefficients

    - by JohnHankinson
    I have an application requiring me to be able to embed loss-less data into an image. As such I've been experimenting with steganography, specifically via modification of DCT coefficients as the method I select, apart from being loss-less must also be relatively resilient against format conversion, scaling/DSP etc. From the research I've done thus far this method seems to be the best candidate. I've seen a number of papers on the subject which all seem to neglect specific details (some neglect to mention modification of 0 coefficients, or modification of AC coefficient etc). After combining the findings and making a few modifications of my own which include: 1) Using a more quantized version of the DCT matrix to ensure we only modify coefficients that would still be present should the image be JPEG'ed further or processed (I'm using this in place of simply following a zig-zag pattern). 2) I'm modifying bit 4 instead of the LSB and then based on what the original bit value was adjusting the lower bits to minimize the difference. 3) I'm only modifying the blue channel as it should be the least visible. This process must modify the actual image and not the DCT values stored in file (like jsteg) as there is no guarantee the file will be a JPEG, it may also be opened and re-saved at a later stage in a different format. For added robustness I've included the message multiple times and use the bits that occur most often, I had considered using a QR code as the message data or simply applying the reed-solomon error correction, but for this simple application and given that the "message" in question is usually going to be between 10-32 bytes I have plenty of room to repeat it which should provide sufficient redundancy to recover the true bits. No matter what I do I don't seem to be able to recover the bits at the decode stage. I've tried including / excluding various checks (even if it degrades image quality for the time being). I've tried using fixed point vs. double arithmetic, moving the bit to encode, I suspect that the message bits are being lost during the IDCT back to image. Any thoughts or suggestions on how to get this working would be hugely appreciated. (PS I am aware that the actual DCT/IDCT could be optimized from it's naive On4 operation using row column algorithm, or an FDCT like AAN, but for now it just needs to work :) ) Reference Papers: http://www.lokminglui.com/dct.pdf http://arxiv.org/ftp/arxiv/papers/1006/1006.1186.pdf Code for the Encode/Decode process in C# below: using System; using System.Collections.Generic; using System.Linq; using System.Text; using System.Drawing.Imaging; using System.Drawing; namespace ImageKey { public class Encoder { public const int HIDE_BIT_POS = 3; // use bit position 4 (1 << 3). public const int HIDE_COUNT = 16; // Number of times to repeat the message to avoid error. // JPEG Standard Quantization Matrix. // (to get higher quality multiply by (100-quality)/50 .. // for lower than 50 multiply by 50/quality. Then round to integers and clip to ensure only positive integers. public static double[] Q = {16,11,10,16,24,40,51,61, 12,12,14,19,26,58,60,55, 14,13,16,24,40,57,69,56, 14,17,22,29,51,87,80,62, 18,22,37,56,68,109,103,77, 24,35,55,64,81,104,113,92, 49,64,78,87,103,121,120,101, 72,92,95,98,112,100,103,99}; // Maximum qauality quantization matrix (if all 1's doesn't modify coefficients at all). public static double[] Q2 = {1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1}; public static Bitmap Encode(Bitmap b, string key) { Bitmap response = new Bitmap(b.Width, b.Height, PixelFormat.Format32bppArgb); uint imgWidth = ((uint)b.Width) & ~((uint)7); // Maximum usable X resolution (divisible by 8). uint imgHeight = ((uint)b.Height) & ~((uint)7); // Maximum usable Y resolution (divisible by 8). // Start be transferring the unmodified image portions. // As we'll be using slightly less width/height for the encoding process we'll need the edges to be populated. for (int y = 0; y < b.Height; y++) for (int x = 0; x < b.Width; x++) { if( (x >= imgWidth && x < b.Width) || (y>=imgHeight && y < b.Height)) response.SetPixel(x, y, b.GetPixel(x, y)); } // Setup the counters and byte data for the message to encode. StringBuilder sb = new StringBuilder(); for(int i=0;i<HIDE_COUNT;i++) sb.Append(key); byte[] codeBytes = System.Text.Encoding.ASCII.GetBytes(sb.ToString()); int bitofs = 0; // Current bit position we've encoded too. int totalBits = (codeBytes.Length * 8); // Total number of bits to encode. for (int y = 0; y < imgHeight; y += 8) { for (int x = 0; x < imgWidth; x += 8) { int[] redData = GetRedChannelData(b, x, y); int[] greenData = GetGreenChannelData(b, x, y); int[] blueData = GetBlueChannelData(b, x, y); int[] newRedData; int[] newGreenData; int[] newBlueData; if (bitofs < totalBits) { double[] redDCT = DCT(ref redData); double[] greenDCT = DCT(ref greenData); double[] blueDCT = DCT(ref blueData); int[] redDCTI = Quantize(ref redDCT, ref Q2); int[] greenDCTI = Quantize(ref greenDCT, ref Q2); int[] blueDCTI = Quantize(ref blueDCT, ref Q2); int[] blueDCTC = Quantize(ref blueDCT, ref Q); HideBits(ref blueDCTI, ref blueDCTC, ref bitofs, ref totalBits, ref codeBytes); double[] redDCT2 = DeQuantize(ref redDCTI, ref Q2); double[] greenDCT2 = DeQuantize(ref greenDCTI, ref Q2); double[] blueDCT2 = DeQuantize(ref blueDCTI, ref Q2); newRedData = IDCT(ref redDCT2); newGreenData = IDCT(ref greenDCT2); newBlueData = IDCT(ref blueDCT2); } else { newRedData = redData; newGreenData = greenData; newBlueData = blueData; } MapToRGBRange(ref newRedData); MapToRGBRange(ref newGreenData); MapToRGBRange(ref newBlueData); for(int dy=0;dy<8;dy++) { for(int dx=0;dx<8;dx++) { int col = (0xff<<24) + (newRedData[dx+(dy*8)]<<16) + (newGreenData[dx+(dy*8)]<<8) + (newBlueData[dx+(dy*8)]); response.SetPixel(x+dx,y+dy,Color.FromArgb(col)); } } } } if (bitofs < totalBits) throw new Exception("Failed to encode data - insufficient cover image coefficients"); return (response); } public static void HideBits(ref int[] DCTMatrix, ref int[] CMatrix, ref int bitofs, ref int totalBits, ref byte[] codeBytes) { int tempValue = 0; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { if ( (u != 0 || v != 0) && CMatrix[v+(u*8)] != 0 && DCTMatrix[v+(u*8)] != 0) { if (bitofs < totalBits) { tempValue = DCTMatrix[v + (u * 8)]; int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); byte value = (byte)((codeBytes[bytePos] & mask) >> bitPos); // 0 or 1. if (value == 0) { int a = DCTMatrix[v + (u * 8)] & (1 << HIDE_BIT_POS); if (a != 0) DCTMatrix[v + (u * 8)] |= (1 << HIDE_BIT_POS) - 1; DCTMatrix[v + (u * 8)] &= ~(1 << HIDE_BIT_POS); } else if (value == 1) { int a = DCTMatrix[v + (u * 8)] & (1 << HIDE_BIT_POS); if (a == 0) DCTMatrix[v + (u * 8)] &= ~((1 << HIDE_BIT_POS) - 1); DCTMatrix[v + (u * 8)] |= (1 << HIDE_BIT_POS); } if (DCTMatrix[v + (u * 8)] != 0) bitofs++; else DCTMatrix[v + (u * 8)] = tempValue; } } } } } public static void MapToRGBRange(ref int[] data) { for(int i=0;i<data.Length;i++) { data[i] += 128; if(data[i] < 0) data[i] = 0; else if(data[i] > 255) data[i] = 255; } } public static int[] GetRedChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x,y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 16) & 0xff) - 128; } } return (data); } public static int[] GetGreenChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x, y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 8) & 0xff) - 128; } } return (data); } public static int[] GetBlueChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x, y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 0) & 0xff) - 128; } } return (data); } public static int[] Quantize(ref double[] DCTMatrix, ref double[] Q) { int[] DCTMatrixOut = new int[8*8]; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { DCTMatrixOut[v + (u * 8)] = (int)Math.Round(DCTMatrix[v + (u * 8)] / Q[v + (u * 8)]); } } return(DCTMatrixOut); } public static double[] DeQuantize(ref int[] DCTMatrix, ref double[] Q) { double[] DCTMatrixOut = new double[8*8]; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { DCTMatrixOut[v + (u * 8)] = (double)DCTMatrix[v + (u * 8)] * Q[v + (u * 8)]; } } return(DCTMatrixOut); } public static double[] DCT(ref int[] data) { double[] DCTMatrix = new double[8 * 8]; for (int v = 0; v < 8; v++) { for (int u = 0; u < 8; u++) { double cu = 1; if (u == 0) cu = (1.0 / Math.Sqrt(2.0)); double cv = 1; if (v == 0) cv = (1.0 / Math.Sqrt(2.0)); double sum = 0.0; for (int y = 0; y < 8; y++) { for (int x = 0; x < 8; x++) { double s = data[x + (y * 8)]; double dctVal = Math.Cos((2 * y + 1) * v * Math.PI / 16) * Math.Cos((2 * x + 1) * u * Math.PI / 16); sum += s * dctVal; } } DCTMatrix[u + (v * 8)] = (0.25 * cu * cv * sum); } } return (DCTMatrix); } public static int[] IDCT(ref double[] DCTMatrix) { int[] Matrix = new int[8 * 8]; for (int y = 0; y < 8; y++) { for (int x = 0; x < 8; x++) { double sum = 0; for (int v = 0; v < 8; v++) { for (int u = 0; u < 8; u++) { double cu = 1; if (u == 0) cu = (1.0 / Math.Sqrt(2.0)); double cv = 1; if (v == 0) cv = (1.0 / Math.Sqrt(2.0)); double idctVal = (cu * cv) / 4.0 * Math.Cos((2 * y + 1) * v * Math.PI / 16) * Math.Cos((2 * x + 1) * u * Math.PI / 16); sum += (DCTMatrix[u + (v * 8)] * idctVal); } } Matrix[x + (y * 8)] = (int)Math.Round(sum); } } return (Matrix); } } public class Decoder { public static string Decode(Bitmap b, int expectedLength) { expectedLength *= Encoder.HIDE_COUNT; uint imgWidth = ((uint)b.Width) & ~((uint)7); // Maximum usable X resolution (divisible by 8). uint imgHeight = ((uint)b.Height) & ~((uint)7); // Maximum usable Y resolution (divisible by 8). // Setup the counters and byte data for the message to decode. byte[] codeBytes = new byte[expectedLength]; byte[] outBytes = new byte[expectedLength / Encoder.HIDE_COUNT]; int bitofs = 0; // Current bit position we've decoded too. int totalBits = (codeBytes.Length * 8); // Total number of bits to decode. for (int y = 0; y < imgHeight; y += 8) { for (int x = 0; x < imgWidth; x += 8) { int[] blueData = ImageKey.Encoder.GetBlueChannelData(b, x, y); double[] blueDCT = ImageKey.Encoder.DCT(ref blueData); int[] blueDCTI = ImageKey.Encoder.Quantize(ref blueDCT, ref Encoder.Q2); int[] blueDCTC = ImageKey.Encoder.Quantize(ref blueDCT, ref Encoder.Q); if (bitofs < totalBits) GetBits(ref blueDCTI, ref blueDCTC, ref bitofs, ref totalBits, ref codeBytes); } } bitofs = 0; for (int i = 0; i < (expectedLength / Encoder.HIDE_COUNT) * 8; i++) { int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); List<int> values = new List<int>(); int zeroCount = 0; int oneCount = 0; for (int j = 0; j < Encoder.HIDE_COUNT; j++) { int val = (codeBytes[bytePos + ((expectedLength / Encoder.HIDE_COUNT) * j)] & mask) >> bitPos; values.Add(val); if (val == 0) zeroCount++; else oneCount++; } if (oneCount >= zeroCount) outBytes[bytePos] |= mask; bitofs++; values.Clear(); } return (System.Text.Encoding.ASCII.GetString(outBytes)); } public static void GetBits(ref int[] DCTMatrix, ref int[] CMatrix, ref int bitofs, ref int totalBits, ref byte[] codeBytes) { for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { if ((u != 0 || v != 0) && CMatrix[v + (u * 8)] != 0 && DCTMatrix[v + (u * 8)] != 0) { if (bitofs < totalBits) { int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); int value = DCTMatrix[v + (u * 8)] & (1 << Encoder.HIDE_BIT_POS); if (value != 0) codeBytes[bytePos] |= mask; bitofs++; } } } } } } } UPDATE: By switching to using a QR Code as the source message and swapping a pair of coefficients in each block instead of bit manipulation I've been able to get the message to survive the transform. However to get the message to come through without corruption I have to adjust both coefficients as well as swap them. For example swapping (3,4) and (4,3) in the DCT matrix and then respectively adding 8 and subtracting 8 as an arbitrary constant seems to work. This survives a re-JPEG'ing of 96 but any form of scaling/cropping destroys the message again. I was hoping that by operating on mid to low frequency values that the message would be preserved even under some light image manipulation.

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  • Problem running code with JML2 in Eclipse

    - by devoured elysium
    I'm having trouble running JML2 in Eclipse. I have the foolowing code: public class MainClass { public static void main(String[] args) { System.out.println(-9.0); } //@requires x >= 7.0 public static double getSquare(double x) { return Math.sqrt(x); } } The error I'm getting is: Is there anything wrong with the syntax I've used? Thanks

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  • Can my loop be optimized any more? (C++)

    - by Sagekilla
    Below is one of my inner loops that's run several thousand times, with input sizes of 20 - 1000 or more. Is there anything I can do to help squeeze any more performance out of this? I'm not looking to move this code to something like using tree codes (Barnes-Hut), but towards optimizing the actual calculations happening inside, since the same calculations occur in the Barnes-Hut algorithm. Any help is appreciated! typedef double real; struct Particle { Vector pos, vel, acc, jerk; Vector oldPos, oldVel, oldAcc, oldJerk; real mass; }; class Vector { private: real vec[3]; public: // Operators defined here }; real Gravity::interact(Particle *p, size_t numParticles) { PROFILE_FUNC(); real tau_q = 1e300; for (size_t i = 0; i < numParticles; i++) { p[i].jerk = 0; p[i].acc = 0; } for (size_t i = 0; i < numParticles; i++) { for (size_t j = i+1; j < numParticles; j++) { Vector r = p[j].pos - p[i].pos; Vector v = p[j].vel - p[i].vel; real r2 = lengthsq(r); real v2 = lengthsq(v); // Calculate inverse of |r|^3 real r3i = Constants::G * pow(r2, -1.5); // da = r / |r|^3 // dj = (v / |r|^3 - 3 * (r . v) * r / |r|^5 Vector da = r * r3i; Vector dj = (v - r * (3 * dot(r, v) / r2)) * r3i; // Calculate new acceleration and jerk p[i].acc += da * p[j].mass; p[i].jerk += dj * p[j].mass; p[j].acc -= da * p[i].mass; p[j].jerk -= dj * p[i].mass; // Collision estimation // Metric 1) tau = |r|^2 / |a(j) - a(i)| // Metric 2) tau = |r|^4 / |v|^4 real mij = p[i].mass + p[j].mass; real tau_est_q1 = r2 / (lengthsq(da) * mij * mij); real tau_est_q2 = (r2*r2) / (v2*v2); if (tau_est_q1 < tau_q) tau_q = tau_est_q1; if (tau_est_q2 < tau_q) tau_q = tau_est_q2; } } return sqrt(sqrt(tau_q)); }

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  • finding "distance" between two pixel's colors.

    - by igor
    Once more something relatively simple, but confused as to what they want. the method to find distance on cartesian coordinate system is distance=sqrt[(x2-x1)^2 + (y2-y1)^2] but how do i apply it here? //Requires: testColor to be a valid Color //Effects: returns the "distance" between the current Pixel's color and // the passed color // uses the standard method to calculate "distance" // uses the same formula as finding distance on a // Cartesian coordinate system double colorDistance(Color testColor) const;

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  • Mathematical problem

    - by coolboycsaba
    I have the following function: function getLevel(points) { var level = -1 + Math.sqrt(4 + points/20); // Round down to nearest level return Math.floor(level); } The above function calculates the level of a player based on their points, my problem is that I need a function like this to calculate the points needed for a given level.

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  • any faster alternative??

    - by kaushik
    cost=0 for i in range(12): cost=cost+math.pow(float(float(q[i])-float(w[i])),2) cost=(math.sqrt(cost)) Any faster alternative to this? i am need to improve my entire code so trying to improve each statements performance. thanking u

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  • Polar and Cartesian calculations not completely working?

    - by Smoka
    double testx, testy, testdeg, testrad, endx, endy; testx = 1; testy = 1; testdeg = atan2( testx, testy) / Math::PI* 180; testrad = sqrt(pow(testx,2) + pow(testy,2)); endx = testrad * cos(testdeg); endy = testrad * sin(testdeg); All parts of this seem to equate properly, except endx and endy should = testx and testy they do when calculating by hand.

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  • Android library to get pitch from WAV file

    - by Sakura
    I have a list of sampled data from the WAV file. I would like to pass in these values into a library and get the frequency of the music played in the WAV file. For now, I will have 1 frequency in the WAV file and I would like to find a library that is compatible with Android. I understand that I need to use FFT to get the frequency domain. Is there any good libraries for that? I found that [KissFFT][1] is quite popular but I am not very sure how compatible it is on Android. Is there an easier and good library that can perform the task I want? EDIT: I tried to use JTransforms to get the FFT of the WAV file but always failed at getting the correct frequency of the file. Currently, the WAV file contains sine curve of 440Hz, music note A4. However, I got the result as 441. Then I tried to get the frequency of G4, I got the result as 882Hz which is incorrect. The frequency of G4 is supposed to be 783Hz. Could it be due to not enough samples? If yes, how much samples should I take? //DFT DoubleFFT_1D fft = new DoubleFFT_1D(numOfFrames); double max_fftval = -1; int max_i = -1; double[] fftData = new double[numOfFrames * 2]; for (int i = 0; i < numOfFrames; i++) { // copying audio data to the fft data buffer, imaginary part is 0 fftData[2 * i] = buffer[i]; fftData[2 * i + 1] = 0; } fft.complexForward(fftData); for (int i = 0; i < fftData.length; i += 2) { // complex numbers -> vectors, so we compute the length of the vector, which is sqrt(realpart^2+imaginarypart^2) double vlen = Math.sqrt((fftData[i] * fftData[i]) + (fftData[i + 1] * fftData[i + 1])); //fd.append(Double.toString(vlen)); // fd.append(","); if (max_fftval < vlen) { // if this length is bigger than our stored biggest length max_fftval = vlen; max_i = i; } } //double dominantFreq = ((double)max_i / fftData.length) * sampleRate; double dominantFreq = (max_i/2.0) * sampleRate / numOfFrames; fd.append(Double.toString(dominantFreq)); Can someone help me out? EDIT2: I manage to fix the problem mentioned above by increasing the number of samples to 100000, however, sometimes I am getting the overtones as the frequency. Any idea how to fix it? Should I use Harmonic Product Frequency or Autocorrelation algorithms?

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  • Project Euler #9 (Pythagorean triplets) in Clojure

    - by dbyrne
    My answer to this problem feels too much like these solutions in C. Does anyone have any advice to make this more lispy? (use 'clojure.test) (:import 'java.lang.Math) (with-test (defn find-triplet-product ([target] (find-triplet-product 1 1 target)) ([a b target] (let [c (Math/sqrt (+ (* a a) (* b b)))] (let [sum (+ a b c)] (cond (> a target) "ERROR" (= sum target) (reduce * (list a b (int c))) (> sum target) (recur (inc a) 1 target) (< sum target) (recur a (inc b) target)))))) (is (= (find-triplet-product 1000) 31875000)))

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  • NZEC Run time Error Occured

    - by madan
    import math def gen_caller(a): for z in a: x,y=z if x==1: x=2 if y>=x and y-x<=100000: for i in range(x,y+1): flag=0 for j in range(2,(long(math.sqrt(i))+1)): if(i%j==0): flag=1 break if flag==0: print i print "" n=(int(raw_input())) gen_caller([[(long(raw_input())) for j in range(0,2)] for i in range(0,n) if n<=10])

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  • Should we use temporary variables for the returned values of functions?

    - by totymedli
    I thought about this: Is there a performance difference in these two practices: Store the return value of a function in a temporary variable than give that variable as a parameter to another function. Put the function into the other function. Specification Assuming all classes and functions are written correctly. Case 1. ClassA a = function1(); ClassB b = function2(a); function3(b); Case 2. function3(function2(function1())); I know there aren't a big difference with only one run, but supposed that we could run this a lot of times in a loop, I created some tests. Test #include <iostream> #include <ctime> #include <math.h> using namespace std; int main() { clock_t start = clock(); clock_t ends = clock(); // Case 1. start = clock(); for (int i=0; i<10000000; i++) { double a = cos(1); double b = pow(a, 2); sqrt(b); } ends = clock(); cout << (double) (ends - start) / CLOCKS_PER_SEC << endl; // Case 2. start = clock(); for (int i=0; i<10000000; i++) sqrt(pow(cos(1),2)); ends = clock(); cout << (double) (ends - start) / CLOCKS_PER_SEC << endl; return 0; } Results Case 1 = 6.375 Case 2 = 0.031 Why is the first one is much slower, and if the second one is faster why dont we always write code that way? Anyway does the second pratice has a name? I also wondered what happens if I create the variables outside the for loop in the first case, but the result was the same. Why?

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  • Describe relative angles between points (like driving directions)

    - by aan234g
    I have a list of points with x, y coordinates. I know how to get the distance between points with sqrt(pow($x2 - $x1, 2) + pow($y2 - $y1, 2)) and the angle between points with atan2(y1 - y2, x1 - x2). How can I calculate the relative angle between the points (left, right, straight)? So, if I'm at point 1, what is the relative direction to point 2, then 2 to 3, 3 to 4, etc... Thanks for any help!

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  • Numpy/Python performing terribly vs. Matlab

    - by Nissl
    Novice programmer here. I'm writing a program that analyzes the relative spatial locations of points (cells). The program gets boundaries and cell type off an array with the x coordinate in column 1, y coordinate in column 2, and cell type in column 3. It then checks each cell for cell type and appropriate distance from the bounds. If it passes, it then calculates its distance from each other cell in the array and if the distance is within a specified analysis range it adds it to an output array at that distance. My cell marking program is in wxpython so I was hoping to develop this program in python as well and eventually stick it into the GUI. Unfortunately right now python takes ~20 seconds to run the core loop on my machine while MATLAB can do ~15 loops/second. Since I'm planning on doing 1000 loops (with a randomized comparison condition) on ~30 cases times several exploratory analysis types this is not a trivial difference. I tried running a profiler and array calls are 1/4 of the time, almost all of the rest is unspecified loop time. Here is the python code for the main loop: for basecell in range (0, cellnumber-1): if firstcelltype == np.array((cellrecord[basecell,2])): xloc=np.array((cellrecord[basecell,0])) yloc=np.array((cellrecord[basecell,1])) xedgedist=(xbound-xloc) yedgedist=(ybound-yloc) if xloc>excludedist and xedgedist>excludedist and yloc>excludedist and yedgedist>excludedist: for comparecell in range (0, cellnumber-1): if secondcelltype==np.array((cellrecord[comparecell,2])): xcomploc=np.array((cellrecord[comparecell,0])) ycomploc=np.array((cellrecord[comparecell,1])) dist=math.sqrt((xcomploc-xloc)**2+(ycomploc-yloc)**2) dist=round(dist) if dist>=1 and dist<=analysisdist: arraytarget=round(dist*analysisdist/intervalnumber) addone=np.array((spatialraw[arraytarget-1])) addone=addone+1 targetcell=arraytarget-1 np.put(spatialraw,[targetcell,targetcell],addone) Here is the matlab code for the main loop: for basecell = 1:cellnumber; if firstcelltype==cellrecord(basecell,3); xloc=cellrecord(basecell,1); yloc=cellrecord(basecell,2); xedgedist=(xbound-xloc); yedgedist=(ybound-yloc); if (xloc>excludedist) && (yloc>excludedist) && (xedgedist>excludedist) && (yedgedist>excludedist); for comparecell = 1:cellnumber; if secondcelltype==cellrecord(comparecell,3); xcomploc=cellrecord(comparecell,1); ycomploc=cellrecord(comparecell,2); dist=sqrt((xcomploc-xloc)^2+(ycomploc-yloc)^2); if (dist>=1) && (dist<=100.4999); arraytarget=round(dist*analysisdist/intervalnumber); spatialsum(1,arraytarget)=spatialsum(1,arraytarget)+1; end end end end end end Thanks!

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