Search Results

Search found 2093 results on 84 pages for 'sparse matrix'.

Page 19/84 | < Previous Page | 15 16 17 18 19 20 21 22 23 24 25 26  | Next Page >

  • Coordinate spaces and transformation matrices

    - by Belgin
    I'm trying to get an object from object space, into projected space using these intermediate matrices: The first matrix (I) is the one that transforms from object space into inertial space, but since my object is not rotated or translated in any way inside the object space, this matrix is the 4x4 identity matrix. The second matrix (W) is the one that transforms from inertial space into world space, which is just a scale transform matrix of factor a = 14.1 on all coordinates, since the inertial space origin coincides with the world space origin. /a 0 0 0\ W = |0 a 0 0| |0 0 a 0| \0 0 0 1/ The third matrix (C) is the one that transforms from world space, into camera space. This matrix is a translation matrix with a translation of (0, 0, 10), because I want the camera to be located behind the object, so the object must be positioned 10 units into the z axis. /1 0 0 0\ C = |0 1 0 0| |0 0 1 10| \0 0 0 1/ And finally, the fourth matrix is the projection matrix (P). Bearing in mind that the eye is at the origin of the world space and the projection plane is defined by z = 1, the projection matrix is: /1 0 0 0\ P = |0 1 0 0| |0 0 1 0| \0 0 1/d 0/ where d is the distance from the eye to the projection plane, so d = 1. I'm multiplying them like this: (((P x C) x W) x I) x V, where V is the vertex' coordinates in column vector form: /x\ V = |y| |z| \1/ After I get the result, I divide x and y coordinates by w to get the actual screen coordinates. Apparenly, I'm doing something wrong or missing something completely here, because it's not rendering properly. Here's a picture of what is supposed to be the bottom side of the Stanford Dragon: Also, I should add that this is a software renderer so no DirectX or OpenGL stuff here.

    Read the article

  • Using pthread to perform matrix multiplication

    - by shadyabhi
    I have both matrices containing only ones and each array has 500 rows and columns. So, the resulting matrix should be a matrix of all elements having value 500. But, I am getting res_mat[0][0]=5000. Even other elements are also 5000. Why? #include<stdio.h> #include<pthread.h> #include<unistd.h> #include<stdlib.h> #define ROWS 500 #define COLUMNS 500 #define N_THREADS 10 int mat1[ROWS][COLUMNS],mat2[ROWS][COLUMNS],res_mat[ROWS][COLUMNS]; void *mult_thread(void *t) { /*This function calculates 50 ROWS of the matrix*/ int starting_row; starting_row = *((int *)t); starting_row = 50 * starting_row; int i,j,k; for (i = starting_row;i<starting_row+50;i++) for (j=0;j<COLUMNS;j++) for (k=0;k<ROWS;k++) res_mat[i][j] += (mat1[i][k] * mat2[k][j]); return; } void fill_matrix(int mat[ROWS][COLUMNS]) { int i,j; for(i=0;i<ROWS;i++) for(j=0;j<COLUMNS;j++) mat[i][j] = 1; } int main() { int n_threads = 10; //10 threads created bcos we have 500 rows and one thread calculates 50 rows int j=0; pthread_t p[n_threads]; fill_matrix(mat1); fill_matrix(mat2); for (j=0;j<10;j++) pthread_create(&p[j],NULL,mult_thread,&j); for (j=0;j<10;j++) pthread_join(p[j],NULL); printf("%d\n",res_mat[0][0]); return 0; }

    Read the article

  • OpenCL Matrix Multiplication - Getting wrong answer

    - by Yash
    here's a simple OpenCL Matrix Multiplication kernel which is driving me crazy: __kernel void matrixMul( __global int* C, __global int* A, __global int* B, int wA, int wB){ int row = get_global_id(1); //2D Threas ID x int col = get_global_id(0); //2D Threas ID y //Perform dot-product accumulated into value int value; for ( int k = 0; k < wA; k++ ){ value += A[row*wA + k] * B[k*wB+col]; } C[row*wA+col] = value; //Write to the device memory } Where (inputs) A = [72 45 75 61] B = [26 53 46 76] Output I am getting: C = [3942 7236 3312 5472] But the output should be: C = [3943 7236 4756 8611] The problem I am facing here is that for any dimension array the elements of the first row of the resulting matrix is correct. The elements of all the other rows of the resulting matrix is wrong. By the way I am using pyopencl. I don't know what I mistake I am doing here. I have spent the entire day with no luck. Please help me with this

    Read the article

  • Optimizing a "set in a string list" to a "set as a matrix" operation

    - by Eric Fournier
    I have a set of strings which contain space-separated elements. I want to build a matrix which will tell me which elements were part of which strings. For example: "" "A B C" "D" "B D" Should give something like: A B C D 1 2 1 1 1 3 1 4 1 1 Now I've got a solution, but it runs slow as molasse, and I've run out of ideas on how to make it faster: reverseIn <- function(vector, value) { return(value %in% vector) } buildCategoryMatrix <- function(valueVector) { allClasses <- c() for(classVec in unique(valueVector)) { allClasses <- unique(c(allClasses, strsplit(classVec, " ", fixed=TRUE)[[1]])) } resMatrix <- matrix(ncol=0, nrow=length(valueVector)) splitValues <- strsplit(valueVector, " ", fixed=TRUE) for(cat in allClasses) { if(cat=="") { catIsPart <- (valueVector == "") } else { catIsPart <- sapply(splitValues, reverseIn, cat) } resMatrix <- cbind(resMatrix, catIsPart) } colnames(resMatrix) <- allClasses return(resMatrix) } Profiling the function gives me this: $by.self self.time self.pct total.time total.pct "match" 31.20 34.74 31.24 34.79 "FUN" 30.26 33.70 74.30 82.74 "lapply" 13.56 15.10 87.86 97.84 "%in%" 12.92 14.39 44.10 49.11 So my actual questions would be: - Where are the 33% spent in "FUN" coming from? - Would there be any way to speed up the %in% call? I tried turning the strings into factors prior to going into the loop so that I'd be matching numbers instead of strings, but that actually makes R crash. I've also tried going for partial matrix assignment (IE, resMatrix[i,x] <- 1) where i is the number of the string and x is the vector of factors. No dice there either, as it seems to keep on running infinitely.

    Read the article

  • Weird appearance for a 3D XNA ground

    - by Belos
    I wanted to add a ground so I can know the position of a helicopter in the world. But the ground appeared in a weird way: http://i.stack.imgur.com/yTSuW.jpg The ground had the following texture: http://i.stack.imgur.com/pdpxB.png EDIT: Sorry, I forgot to post the code: public class ImportModel { public Vector3 Position { get; set; } public Vector3 Rotation { get; set; } public Vector3 Scale { get; set; } Model Model; Matrix[] modeltransforms; GraphicsDevice GraphicDevice; ContentManager Content; BoundingSphere sphere; bool boundingimplemented = false; public ImportModel(string model, GraphicsDevice gd, ContentManager cm, Vector3 position, Vector3 rot, Vector3 sca) { GraphicDevice = gd; Content = cm; Position = position; Rotation = rot; Scale = sca; Model = Content.Load<Model>(model); modeltransforms = new Matrix[Model.Bones.Count]; Model.CopyAbsoluteBoneTransformsTo(modeltransforms); } public void Draw(Camera camera) { Matrix baseworld = Matrix.CreateScale(Scale) * Matrix.CreateFromYawPitchRoll(Rotation.Y, Rotation.X, Rotation.Z) * Matrix.CreateTranslation(Position); foreach (ModelMesh mesh in Model.Meshes) { Matrix localworld = modeltransforms[mesh.ParentBone.Index] * baseworld; foreach (ModelMeshPart meshpart in mesh.MeshParts) { BasicEffect effect = (BasicEffect)meshpart.Effect; effect.World = localworld; effect.View = camera.View; effect.Projection = camera.Projection; effect.EnableDefaultLighting(); } mesh.Draw(); } } public BoundingSphere BoundingSphere { get { if (!boundingimplemented) { foreach (ModelMesh mesh in Model.Meshes) { BoundingSphere transformed = mesh.BoundingSphere.Transform( modeltransforms[mesh.ParentBone.Index]); sphere = BoundingSphere.CreateMerged(sphere, transformed); } Matrix worldTransform = Matrix.CreateScale(Scale) * Matrix.CreateTranslation(Position); BoundingSphere transforme = sphere; transforme = transforme.Transform(worldTransform); return transforme; } else { Matrix worldTransform = Matrix.CreateScale(Scale) * Matrix.CreateTranslation(Position); BoundingSphere transformed = sphere; transformed = transformed.Transform(worldTransform); return transformed; } } } } Then I call the class from the Game1 class: ImportModel ground = new ImportModel("ground", GraphicsDevice, Content, Vector3.Zero, Vector3.Zero, new Vector3(20f)); EDIT2:This is how the scene looks from top: i.stack.imgur.com/Hs983.jpg

    Read the article

  • Transpose matrix-style table to 3 columns in Excel

    - by polarbear2k
    I have a matrix-style table in excel where B1:Z1 are column headings and A2:A99 are row headings. I would like to convert this table to a 3 column table (column heading, row heading, cell value). It does not matter in what order the new table is. A B C D A B C A B C 1 H1 H2 H3 1 H1 R1 V1 1 H1 R1 V1 2 R1 V1 V2 V3 => 2 H1 R2 V4 or 2 H2 R1 V2 3 R2 V4 V5 V6 3 H1 R3 V7 3 H3 R1 V3 4 R3 V7 V8 V9 4 H2 R1 V2 4 H1 R2 V4 5 H2 R2 V5 5 H2 R2 V5 6 H2 R3 V8 6 H3 R2 V6 7 H3 R1 V3 7 H1 R3 V7 8 H3 R2 V6 8 H2 R3 V8 9 H3 R3 V9 9 H3 R3 V8 I've been playing around with the OFFSET function to create the whole table but I feel like a combination of TRANSPOSE and V/HLOOKUP is required. Thanks EDIT I have managed to come up with the correct formulas. If the data is in Sheet1 like in my example above, the formulas go in Sheet2: [A1] =IF(ROW() <= COUNTA(Sheet1!$B$1:$Z$1)*COUNTA(Sheet1!$A$2:$A$99), OFFSET(Sheet1!$A$1,0,IF(MOD(ROW(),COUNTA(Sheet1!$B$1:$Z$1))=0,COUNTA(Sheet1!$B$1:$Z$1),MOD(ROW(),COUNTA(Sheet1!$B$1:$Z$1)))),"") [B1] =IF(ROW() <= COUNTA(Sheet1!$B$1:$Z$1)*COUNTA(Sheet1!$A$2:$A$99),OFFSET(Sheet1!$A$1,IF(MOD(ROW(),COUNTA(Sheet1!$A$2:$A$99))=0,COUNTA(Sheet1!$A$2:$A$99),MOD(ROW(),COUNTA(Sheet1!$A$2:$A$99))),0),"") [C1] =IF(ROW() <= COUNTA(Sheet1!$B$1:$Z$1)*COUNTA(Sheet1!$A$2:$A$99),OFFSET(Sheet1!$A$1,IF(MOD(ROW(),COUNTA(Sheet1!$A$2:$A$99))=0,COUNTA(Sheet1!$A$2:$A$99),MOD(ROW(),COUNTA(Sheet1!$A$2:$A$99))),IF(MOD(ROW(),COUNTA(Sheet1!$B$1:$Z$1))=0,COUNTA(Sheet1!$B$1:$Z$1),MOD(ROW(),COUNTA(Sheet1!$B$1:$Z$1)))),"") The formulas are limited to B1:Z1 for the headings and A2:A99 for the rows (these can be increased to their maximums if required). The COUNTA() formula returns the number of cells that actually have values, which limits the number of rows returned to headings*rows. Otherwise the formulas would could go on for infinity because of the MOD function.

    Read the article

  • How to use onSensorChanged sensor data in combination with OpenGL

    - by Sponge
    I have written a TestSuite to find out how to calculate the rotation angles from the data you get in SensorEventListener.onSensorChanged(). I really hope you can complete my solution to help people who will have the same problems like me. Here is the code, i think you will understand it after reading it. Feel free to change it, the main idea was to implement several methods to send the orientation angles to the opengl view or any other target which would need it. method 1 to 4 are working, they are directly sending the rotationMatrix to the OpenGl view. all other methods are not working or buggy and i hope someone knows to get them working. i think the best method would be method 5 if it would work, because it would be the easiest to understand but i'm not sure how efficient it is. the complete code isn't optimized so i recommend to not use it as it is in your project. here it is: import java.nio.ByteBuffer; import java.nio.ByteOrder; import java.nio.FloatBuffer; import javax.microedition.khronos.egl.EGL10; import javax.microedition.khronos.egl.EGLConfig; import javax.microedition.khronos.opengles.GL10; import static javax.microedition.khronos.opengles.GL10.*; import android.app.Activity; import android.content.Context; import android.content.pm.ActivityInfo; import android.hardware.Sensor; import android.hardware.SensorEvent; import android.hardware.SensorEventListener; import android.hardware.SensorManager; import android.opengl.GLSurfaceView; import android.opengl.GLSurfaceView.Renderer; import android.os.Bundle; import android.util.Log; import android.view.WindowManager; /** * This class provides a basic demonstration of how to use the * {@link android.hardware.SensorManager SensorManager} API to draw a 3D * compass. */ public class SensorToOpenGlTests extends Activity implements Renderer, SensorEventListener { private static final boolean TRY_TRANSPOSED_VERSION = false; /* * MODUS overview: * * 1 - unbufferd data directly transfaired from the rotation matrix to the * modelview matrix * * 2 - buffered version of 1 where both acceleration and magnetometer are * buffered * * 3 - buffered version of 1 where only magnetometer is buffered * * 4 - buffered version of 1 where only acceleration is buffered * * 5 - uses the orientation sensor and sets the angles how to rotate the * camera with glrotate() * * 6 - uses the rotation matrix to calculate the angles * * 7 to 12 - every possibility how the rotationMatrix could be constructed * in SensorManager.getRotationMatrix (see * http://www.songho.ca/opengl/gl_anglestoaxes.html#anglestoaxes for all * possibilities) */ private static int MODUS = 2; private GLSurfaceView openglView; private FloatBuffer vertexBuffer; private ByteBuffer indexBuffer; private FloatBuffer colorBuffer; private SensorManager mSensorManager; private float[] rotationMatrix = new float[16]; private float[] accelGData = new float[3]; private float[] bufferedAccelGData = new float[3]; private float[] magnetData = new float[3]; private float[] bufferedMagnetData = new float[3]; private float[] orientationData = new float[3]; // private float[] mI = new float[16]; private float[] resultingAngles = new float[3]; private int mCount; final static float rad2deg = (float) (180.0f / Math.PI); private boolean mirrorOnBlueAxis = false; private boolean landscape; public SensorToOpenGlTests() { } /** Called with the activity is first created. */ @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE); openglView = new GLSurfaceView(this); openglView.setRenderer(this); setContentView(openglView); } @Override protected void onResume() { // Ideally a game should implement onResume() and onPause() // to take appropriate action when the activity looses focus super.onResume(); openglView.onResume(); if (((WindowManager) getSystemService(WINDOW_SERVICE)) .getDefaultDisplay().getOrientation() == 1) { landscape = true; } else { landscape = false; } mSensorManager.registerListener(this, mSensorManager .getDefaultSensor(Sensor.TYPE_ACCELEROMETER), SensorManager.SENSOR_DELAY_GAME); mSensorManager.registerListener(this, mSensorManager .getDefaultSensor(Sensor.TYPE_MAGNETIC_FIELD), SensorManager.SENSOR_DELAY_GAME); mSensorManager.registerListener(this, mSensorManager .getDefaultSensor(Sensor.TYPE_ORIENTATION), SensorManager.SENSOR_DELAY_GAME); } @Override protected void onPause() { // Ideally a game should implement onResume() and onPause() // to take appropriate action when the activity looses focus super.onPause(); openglView.onPause(); mSensorManager.unregisterListener(this); } public int[] getConfigSpec() { // We want a depth buffer, don't care about the // details of the color buffer. int[] configSpec = { EGL10.EGL_DEPTH_SIZE, 16, EGL10.EGL_NONE }; return configSpec; } public void onDrawFrame(GL10 gl) { // clear screen and color buffer: gl.glClear(GL10.GL_COLOR_BUFFER_BIT | GL10.GL_DEPTH_BUFFER_BIT); // set target matrix to modelview matrix: gl.glMatrixMode(GL10.GL_MODELVIEW); // init modelview matrix: gl.glLoadIdentity(); // move camera away a little bit: if ((MODUS == 1) || (MODUS == 2) || (MODUS == 3) || (MODUS == 4)) { if (landscape) { // in landscape mode first remap the rotationMatrix before using // it with glMultMatrixf: float[] result = new float[16]; SensorManager.remapCoordinateSystem(rotationMatrix, SensorManager.AXIS_Y, SensorManager.AXIS_MINUS_X, result); gl.glMultMatrixf(result, 0); } else { gl.glMultMatrixf(rotationMatrix, 0); } } else { //in all other modes do the rotation by hand: gl.glRotatef(resultingAngles[1], 1, 0, 0); gl.glRotatef(resultingAngles[2], 0, 1, 0); gl.glRotatef(resultingAngles[0], 0, 0, 1); if (mirrorOnBlueAxis) { //this is needed for mode 6 to work gl.glScalef(1, 1, -1); } } //move the axis to simulate augmented behaviour: gl.glTranslatef(0, 2, 0); // draw the 3 axis on the screen: gl.glVertexPointer(3, GL_FLOAT, 0, vertexBuffer); gl.glColorPointer(4, GL_FLOAT, 0, colorBuffer); gl.glDrawElements(GL_LINES, 6, GL_UNSIGNED_BYTE, indexBuffer); } public void onSurfaceChanged(GL10 gl, int width, int height) { gl.glViewport(0, 0, width, height); float r = (float) width / height; gl.glMatrixMode(GL10.GL_PROJECTION); gl.glLoadIdentity(); gl.glFrustumf(-r, r, -1, 1, 1, 10); } public void onSurfaceCreated(GL10 gl, EGLConfig config) { gl.glDisable(GL10.GL_DITHER); gl.glClearColor(1, 1, 1, 1); gl.glEnable(GL10.GL_CULL_FACE); gl.glShadeModel(GL10.GL_SMOOTH); gl.glEnable(GL10.GL_DEPTH_TEST); gl.glEnableClientState(GL10.GL_VERTEX_ARRAY); gl.glEnableClientState(GL10.GL_COLOR_ARRAY); // load the 3 axis and there colors: float vertices[] = { 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1 }; float colors[] = { 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1 }; byte indices[] = { 0, 1, 0, 2, 0, 3 }; ByteBuffer vbb; vbb = ByteBuffer.allocateDirect(vertices.length * 4); vbb.order(ByteOrder.nativeOrder()); vertexBuffer = vbb.asFloatBuffer(); vertexBuffer.put(vertices); vertexBuffer.position(0); vbb = ByteBuffer.allocateDirect(colors.length * 4); vbb.order(ByteOrder.nativeOrder()); colorBuffer = vbb.asFloatBuffer(); colorBuffer.put(colors); colorBuffer.position(0); indexBuffer = ByteBuffer.allocateDirect(indices.length); indexBuffer.put(indices); indexBuffer.position(0); } public void onAccuracyChanged(Sensor sensor, int accuracy) { } public void onSensorChanged(SensorEvent event) { // load the new values: loadNewSensorData(event); if (MODUS == 1) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); } if (MODUS == 2) { rootMeanSquareBuffer(bufferedAccelGData, accelGData); rootMeanSquareBuffer(bufferedMagnetData, magnetData); SensorManager.getRotationMatrix(rotationMatrix, null, bufferedAccelGData, bufferedMagnetData); } if (MODUS == 3) { rootMeanSquareBuffer(bufferedMagnetData, magnetData); SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, bufferedMagnetData); } if (MODUS == 4) { rootMeanSquareBuffer(bufferedAccelGData, accelGData); SensorManager.getRotationMatrix(rotationMatrix, null, bufferedAccelGData, magnetData); } if (MODUS == 5) { // this mode uses the sensor data recieved from the orientation // sensor resultingAngles = orientationData.clone(); if ((-90 > resultingAngles[1]) || (resultingAngles[1] > 90)) { resultingAngles[1] = orientationData[0]; resultingAngles[2] = orientationData[1]; resultingAngles[0] = orientationData[2]; } } if (MODUS == 6) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); final float[] anglesInRadians = new float[3]; SensorManager.getOrientation(rotationMatrix, anglesInRadians); if ((-90 < anglesInRadians[2] * rad2deg) && (anglesInRadians[2] * rad2deg < 90)) { // device camera is looking on the floor // this hemisphere is working fine mirrorOnBlueAxis = false; resultingAngles[0] = anglesInRadians[0] * rad2deg; resultingAngles[1] = anglesInRadians[1] * rad2deg; resultingAngles[2] = anglesInRadians[2] * -rad2deg; } else { mirrorOnBlueAxis = true; // device camera is looking in the sky // this hemisphere is mirrored at the blue axis resultingAngles[0] = (anglesInRadians[0] * rad2deg); resultingAngles[1] = (anglesInRadians[1] * rad2deg); resultingAngles[2] = (anglesInRadians[2] * rad2deg); } } if (MODUS == 7) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in x y z * order Rx*Ry*Rz */ resultingAngles[2] = (float) (Math.asin(rotationMatrix[2])); final float cosB = (float) Math.cos(resultingAngles[2]); resultingAngles[2] = resultingAngles[2] * rad2deg; resultingAngles[0] = -(float) (Math.acos(rotationMatrix[0] / cosB)) * rad2deg; resultingAngles[1] = (float) (Math.acos(rotationMatrix[10] / cosB)) * rad2deg; } if (MODUS == 8) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in z y x */ resultingAngles[2] = (float) (Math.asin(-rotationMatrix[8])); final float cosB = (float) Math.cos(resultingAngles[2]); resultingAngles[2] = resultingAngles[2] * rad2deg; resultingAngles[1] = (float) (Math.acos(rotationMatrix[9] / cosB)) * rad2deg; resultingAngles[0] = (float) (Math.asin(rotationMatrix[4] / cosB)) * rad2deg; } if (MODUS == 9) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in z x y * * note z axis looks good at this one */ resultingAngles[1] = (float) (Math.asin(rotationMatrix[9])); final float minusCosA = -(float) Math.cos(resultingAngles[1]); resultingAngles[1] = resultingAngles[1] * rad2deg; resultingAngles[2] = (float) (Math.asin(rotationMatrix[8] / minusCosA)) * rad2deg; resultingAngles[0] = (float) (Math.asin(rotationMatrix[1] / minusCosA)) * rad2deg; } if (MODUS == 10) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in y x z */ resultingAngles[1] = (float) (Math.asin(-rotationMatrix[6])); final float cosA = (float) Math.cos(resultingAngles[1]); resultingAngles[1] = resultingAngles[1] * rad2deg; resultingAngles[2] = (float) (Math.asin(rotationMatrix[2] / cosA)) * rad2deg; resultingAngles[0] = (float) (Math.acos(rotationMatrix[5] / cosA)) * rad2deg; } if (MODUS == 11) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in y z x */ resultingAngles[0] = (float) (Math.asin(rotationMatrix[4])); final float cosC = (float) Math.cos(resultingAngles[0]); resultingAngles[0] = resultingAngles[0] * rad2deg; resultingAngles[2] = (float) (Math.acos(rotationMatrix[0] / cosC)) * rad2deg; resultingAngles[1] = (float) (Math.acos(rotationMatrix[5] / cosC)) * rad2deg; } if (MODUS == 12) { SensorManager.getRotationMatrix(rotationMatrix, null, accelGData, magnetData); rotationMatrix = transpose(rotationMatrix); /* * this assumes that the rotation matrices are multiplied in x z y */ resultingAngles[0] = (float) (Math.asin(-rotationMatrix[1])); final float cosC = (float) Math.cos(resultingAngles[0]); resultingAngles[0] = resultingAngles[0] * rad2deg; resultingAngles[2] = (float) (Math.acos(rotationMatrix[0] / cosC)) * rad2deg; resultingAngles[1] = (float) (Math.acos(rotationMatrix[5] / cosC)) * rad2deg; } logOutput(); } /** * transposes the matrix because it was transposted (inverted, but here its * the same, because its a rotation matrix) to be used for opengl * * @param source * @return */ private float[] transpose(float[] source) { final float[] result = source.clone(); if (TRY_TRANSPOSED_VERSION) { result[1] = source[4]; result[2] = source[8]; result[4] = source[1]; result[6] = source[9]; result[8] = source[2]; result[9] = source[6]; } // the other values in the matrix are not relevant for rotations return result; } private void rootMeanSquareBuffer(float[] target, float[] values) { final float amplification = 200.0f; float buffer = 20.0f; target[0] += amplification; target[1] += amplification; target[2] += amplification; values[0] += amplification; values[1] += amplification; values[2] += amplification; target[0] = (float) (Math .sqrt((target[0] * target[0] * buffer + values[0] * values[0]) / (1 + buffer))); target[1] = (float) (Math .sqrt((target[1] * target[1] * buffer + values[1] * values[1]) / (1 + buffer))); target[2] = (float) (Math .sqrt((target[2] * target[2] * buffer + values[2] * values[2]) / (1 + buffer))); target[0] -= amplification; target[1] -= amplification; target[2] -= amplification; values[0] -= amplification; values[1] -= amplification; values[2] -= amplification; } private void loadNewSensorData(SensorEvent event) { final int type = event.sensor.getType(); if (type == Sensor.TYPE_ACCELEROMETER) { accelGData = event.values.clone(); } if (type == Sensor.TYPE_MAGNETIC_FIELD) { magnetData = event.values.clone(); } if (type == Sensor.TYPE_ORIENTATION) { orientationData = event.values.clone(); } } private void logOutput() { if (mCount++ > 30) { mCount = 0; Log.d("Compass", "yaw0: " + (int) (resultingAngles[0]) + " pitch1: " + (int) (resultingAngles[1]) + " roll2: " + (int) (resultingAngles[2])); } } }

    Read the article

  • Animation Trouble with Java Swing Timer - Also, JFrame Will Not Exit_On_Close

    - by forgotton_semicolon
    So, I am using a Java Swing Timer because putting the animation code in a run() method of a Thread subclass caused an insane amount of flickering that is really a terrible experience for any video game player. Can anyone give me any tips on: Why there is no animation... Why the JFrame will not close when it is coded to Exit_On_Close 2 times My code is here: import java.awt.; import java.awt.event.; import javax.swing.*; import java.net.URL; //////////////////////////////////////////////////////////////// TFQ public class TFQ extends JFrame { DrawingsInSpace dis; //========================================================== constructor public TFQ() { dis = new DrawingsInSpace(); JPanel content = new JPanel(); content.setLayout(new FlowLayout()); this.setContentPane(dis); this.setDefaultCloseOperation(EXIT_ON_CLOSE); this.setTitle("Plasma_Orbs_Off_Orion"); this.setSize(500,500); this.pack(); //... Create timer which calls action listener every second.. // Use full package qualification for javax.swing.Timer // to avoid potential conflicts with java.util.Timer. javax.swing.Timer t = new javax.swing.Timer(500, new TimePhaseListener()); t.start(); } /////////////////////////////////////////////// inner class Listener thing class TimePhaseListener implements ActionListener, KeyListener { // counter int total; // loop control boolean Its_a_go = true; //position of our matrix int tf = -400; //sprite directions int Sprite_Direction; final int RIGHT = 1; final int LEFT = 2; //for obstacle Rectangle mega_obstacle = new Rectangle(200, 0, 20, HEIGHT); public void actionPerformed(ActionEvent e) { //... Whenever this is called, repaint the screen dis.repaint(); addKeyListener(this); while (Its_a_go) { try { dis.repaint(); if(Sprite_Direction == RIGHT) { dis.matrix.x += 2; } // end if i think if(Sprite_Direction == LEFT) { dis.matrix.x -= 2; } } catch(Exception ex) { System.out.println(ex); } } // end while i think } // end actionPerformed @Override public void keyPressed(KeyEvent arg0) { // TODO Auto-generated method stub } @Override public void keyReleased(KeyEvent arg0) { // TODO Auto-generated method stub } @Override public void keyTyped(KeyEvent event) { // TODO Auto-generated method stub if (event.getKeyChar()=='f'){ Sprite_Direction = RIGHT; System.out.println("matrix should be animating now "); System.out.println("current matrix position = " + dis.matrix.x); } if (event.getKeyChar()=='d') { Sprite_Direction = LEFT; System.out.println("matrix should be going in reverse"); System.out.println("current matrix position = " + dis.matrix.x); } } } //================================================================= main public static void main(String[] args) { JFrame SafetyPins = new TFQ(); SafetyPins.setVisible(true); SafetyPins.setSize(500,500); SafetyPins.setResizable(true); SafetyPins.setLocationRelativeTo(null); SafetyPins.setDefaultCloseOperation(EXIT_ON_CLOSE); } } class DrawingsInSpace extends JPanel { URL url1_plasma_orbs; URL url2_matrix; Image img1_plasma_orbs; Image img2_matrix; // for the plasma_orbs Rectangle bbb = new Rectangle(0,0, 0, 0); // for the matrix Rectangle matrix = new Rectangle(-400, 60, 430, 200); public DrawingsInSpace() { //load URLs try { url1_plasma_orbs = this.getClass().getResource("plasma_orbs.png"); url2_matrix = this.getClass().getResource("matrix.png"); } catch(Exception e) { System.out.println(e); } // attach the URLs to the images img1_plasma_orbs = Toolkit.getDefaultToolkit().getImage(url1_plasma_orbs); img2_matrix = Toolkit.getDefaultToolkit().getImage(url2_matrix); } public void paintComponent(Graphics g) { super.paintComponent(g); // draw the plasma_orbs g.drawImage(img1_plasma_orbs, bbb.x, bbb.y,this); //draw the matrix g.drawImage(img2_matrix, matrix.x, matrix.y, this); } } // end class enter code here

    Read the article

  • Reordering matrix elements to reflect column and row clustering in naiive python

    - by bgbg
    Hello, I'm looking for a way to perform clustering separately on matrix rows and than on its columns, reorder the data in the matrix to reflect the clustering and putting it all together. The clustering problem is easily solvable, so is the dendrogram creation (for example in this blog or in "Programming collective intelligence"). However, how to reorder the data remains unclear for me. Eventually, I'm looking for a way of creating graphs similar to the one below using naive Python (with any "standard" library such as numpy, matplotlib etc, but without using R or other external tools).

    Read the article

  • Efficient algorithm for finding largest eigenpair of small general complex matrix

    - by mklassen
    I am looking for an efficient algorithm to find the largest eigenpair of a small, general (non-square, non-sparse, non-symmetric), complex matrix, A, of size m x n. By small I mean m and n is typically between 4 and 64 and usually around 16, but with m not equal to n. This problem is straight forward to solve with the general LAPACK SVD algorithms, i.e. gesvd or gesdd. However, as I am solving millions of these problems and only require the largest eigenpair, I am looking for a more efficient algorithm. Additionally, in my application the eigenvectors will generally be similar for all cases. This lead me to investigate Arnoldi iteration based methods, but I have neither found a good library nor algorithm that applies to my small general complex matrix. Is there an appropriate algorithm and/or library?

    Read the article

  • Clustering [assessment] algorithm with distance matrix as an input

    - by Max
    Can anyone suggest some clustering algorithm which can work with distance matrix as an input? Or the algorithm which can assess the "goodness" of the clustering also based on the distance matrix? At this moment I'm using a modification of Kruskal's algorithm (http://en.wikipedia.org/wiki/Kruskal%27s_algorithm) to split data into two clusters. It has a problem though. When the data has no distinct clusters the algorithm will still create two clusters with one cluster containing one element and the other containing all the rest. In this case I would rather have one cluster containing all the elements and another one which is empty. Are there any algorithms which are capable of doing this type of clustering? Are there any algorithms which can estimate how well the clustering was done or even better how many clusters are there in the data? The algorithms should work only with distance(similarity) matrices as an input.

    Read the article

  • print matrix in dialog box

    - by Edan
    Hello, I'm having a little difficulty to print a matrix array on dialog box. The matrix is integer and as far as i understood i need to change it into string? anyway, here's the code: public void print_Matrix(int row, int column) { for (int i = 0; i <= row; i++) { for (int j = 0; j <= column; j++) { JOptionPane.showMessageDialog(null, matrix_Of_Life); } } what I need to do in order to print array into dialog box? thanks.

    Read the article

  • Static Typing and Writing a Simple Matrix Library

    - by duckworthd
    Aye it's been done a million times before, but damnit I want to do it again. I'm writing a simple Matrix Library for C++ with the intention of doing it right. I've come across something that's fairly obvious in mathematics, but not so obvious to a strongly typed system -- the fact that a 1x1 matrix is just a number. To avoid this, I started walking down the hairy path of matrices as a composition of vectors, but also stumbled upon the fact that two vectors multiplied together could either be a number or a dyad, depending on the orientation of the two. My question is, what is the right way to deal with this situation in a strongly typed language like C++ or Java?

    Read the article

  • Confusion Matrix with number of classified/misclassified instances on it (Python/Matplotlib)

    - by Pinkie
    I am plotting a confusion matrix with matplotlib with the following code: from numpy import * import matplotlib.pyplot as plt from pylab import * conf_arr = [[33,2,0,0,0,0,0,0,0,1,3], [3,31,0,0,0,0,0,0,0,0,0], [0,4,41,0,0,0,0,0,0,0,1], [0,1,0,30,0,6,0,0,0,0,1], [0,0,0,0,38,10,0,0,0,0,0], [0,0,0,3,1,39,0,0,0,0,4], [0,2,2,0,4,1,31,0,0,0,2], [0,1,0,0,0,0,0,36,0,2,0], [0,0,0,0,0,0,1,5,37,5,1], [3,0,0,0,0,0,0,0,0,39,0], [0,0,0,0,0,0,0,0,0,0,38] ] norm_conf = [] for i in conf_arr: a = 0 tmp_arr = [] a = sum(i,0) for j in i: tmp_arr.append(float(j)/float(a)) norm_conf.append(tmp_arr) plt.clf() fig = plt.figure() ax = fig.add_subplot(111) res = ax.imshow(array(norm_conf), cmap=cm.jet, interpolation='nearest') cb = fig.colorbar(res) savefig("confmat.png", format="png") But I want to the confusion matrix to show the numbers on it like this graphic (the right one): http://i48.tinypic.com/2e30kup.jpg How can I plot the conf_arr on the graphic?

    Read the article

  • Creating a Large Matrix in ff

    - by Ryan Rosario
    I am trying to create a huge matrix in ff, and I know that ff is good for this sort of thing. But, there is a major problem. The dimensions of the matrix exceed .Machine$max_integer! I am running on a 64 bit machine, using 64bit R and 64bit ff. Is there any way to get around this problem? It's been suggested that R is using the MAXINT value from stdint.h. Is there any way to fix this without changing that file and possibly breaking build? > ffMatrix <- ff(vmode="boolean", dim=c(1e10,1e10)) Error in if (length < 0 || length > .Machine$integer.max) stop("length must be between 1 and .Machine$integer.max") : missing value where TRUE/FALSE needed In addition: Warning message: In ff(vmode = "boolean", dim = c(1e+10, 1e+10)) : NAs introduced by coercion > 1e+10 > .Machine$integer.max [1] TRUE

    Read the article

  • print web on dot matrix receipt printer

    - by nightingale2k1
    Hi, I need to print a receipt from my web based apps using dot matrix printer epson tm-u220d (pos printer). I need to know, should I generate the receipt in html or in plain text ? I ever saw some commands for dot matrix printer to change the font size, line feed etc .. but I don't remember that commands. if I have to use plain text I need to use that commands. anyone knows where i can get the references ? Thanks

    Read the article

  • Projection matrix + world plane ~> Homography from image plane to world plane

    - by B3ret
    I think I have my wires crossed on this, it should be quite easy. I have a projection matrix from world coordinates to image coordinates (4D homogeneous to 3D homgeneous), and therefore I also have the inverse projection matrix from image coordinates to world "rays". I want to project points of the image back onto a plane within the world (which is given of course as 4D homogeneous vector). The needed homography should be uniquely identified, yet I can not figure out how to compute it. Of course I could also intersect the back-projected rays with the world plane, but this seems not a good way, knowing that there MUST be a homography doing this for me. Thanks in advance, Ben

    Read the article

  • Get positions for NAs only in the "middle" of a matrix column

    - by Abiel
    I want to obtain an index that refers to the positions of NA values in a matrix where the index is true if a given cell is NA and there is at least one non-NA value before and after it in the column. For example, given the following matrix [,1] [,2] [,3] [,4] [1,] NA 1 NA 1 [2,] 1 NA NA 2 [3,] NA 2 NA 3 the only value of the index that comes back TRUE should be [2,2]. Is there a compact expression for what I want to do? If I had to I could loop through columns and use something like min(which(!is.na(x[,i]))) to find the first non-NA value in each column, and then set all values before that to FALSE (and the same for all values after the max). This way I would not select leading and trailing NA values. But this seems a bit messy, so I'm wondering if there is a cleaner expression that does this without loops.

    Read the article

  • Tool to diagonalize large matrices

    - by Xodarap
    I want to compute a diffusion kernel, which involves taking exp(b*A) where A is a large matrix. In order to play with values of b, I'd like to diagonalize A (so that exp(A) runs quickly). My matrix is about 25k x 25k, but is very sparse - only about 60k values are non-zero. Matlab's "eigs" function runs of out memory, as does octave's "eig" and R's "eigen." Is there a tool to find the decomposition of large, sparse matrices? Dunno if this is relevant, but A is an adjacency matrix, so it's symmetric, and it is full rank.

    Read the article

  • extract data from an array without using loop in R

    - by Manolo
    I have a vector v with row positions: v<-c(10,3,100,50,...) with those positions I want to extract elements of a matrix, having a column fixed, for example lets suppose my column number is 2, so I am doing: data<-c() data<-c(matrix[[v]][[2]]) matrix has the data in the following format: [[34]] [1] "200_s_at" "4853" "1910" "3554" "2658" So for example, I want to extract from the row 342 the value 1910 only, column 2, and do the same with the next rows but I got an error when I want to do that, is it possible to do it directly? or should I have a loop that read one by one the positions in v and fill the data vector like: #algorithm for i<-1 to length(v) pos<-v[i] data[[i]]<-c(matriz[[pos]][[2]]) next i Thanks

    Read the article

  • Compute rolling window covariance matrix

    - by user1665355
    I am trying to compute a rolling window (shifting by 1 day) covariance matrix for a number of assets. Say my df looks like this: df <- data.frame(x = 0:4, y = 5:9,z=1:5,u=4:8) How would a possible for loop look like if I want to calculate a covariance matrix on a rolling basis by shifting the rolling window by 1 day? Or should I use some apply family function? What time series class would be preferrable if I want to create a time series object for the loop above? I simply can't get it... Best Regards

    Read the article

  • Generate (in R) a matrix of all possible outcomes for throwing n dice (ignoring order)

    - by Brani
    In cases where order does matter, it's rather easy to generate the matrix of all possible outcomes. One way for doing this is using expand.grid as shown here. What if it doesn't? If I'm right, the number of possible combinations is (S+N-1)!/S!(N-1)!, where S is the number of dice, each with N sides numbered 1 through N. (It is different from the well known combinations formula because it is possible for the same number to appear on more than one dice). For example, when throwing four six-sided dice, N=6 and S=4, so the number of possible combinations is (4+6-1)!/4!(6-1)! = 9!/4!x5! = 126. How can I generate a matrix of these 126 possible outcomes? Thank you.

    Read the article

  • Generate a matrix of all possible outcomes for throwing n dice (ignoring order)

    - by Brani
    In cases where order does matter, it's rather easy to generate the matrix of all possible outcomes. One way for doing this is using expand.grid as shown here. What if it doesn't? If I'm right, the number of possible combinations is (S+N-1)!/S!(N-1)!, where S is the number of dice, each with N sides numbered 1 through N. (It is different from the well known combinations formula because it is possible for the same number to appear on more than one dice). For example, when throwing four six-sided dice, N=6 and S=4, so the number of possible combinations is (4+6-1)!/4!(6-1)! = 9!/4!x5! = 126. How can I generate a matrix of these 126 possible outcomes? Thank you.

    Read the article

  • Calculating the null space of a matrix

    - by Ainsworth
    I'm attempting to solve a set of equations of the form Ax = 0. A is known 6x6 matrix and I've written the below code using SVD to get the vector x which works to a certain extent. The answer is approximately correct but not good enough to be useful to me, how can I improve the precision of the calculation? Lowering eps below 1.e-4 causes the function to fail. from numpy.linalg import * from numpy import * A = matrix([[0.624010149127497 ,0.020915658603923 ,0.838082638087629 ,62.0778180312547 ,-0.336 ,0], [0.669649399820597 ,0.344105317421833 ,0.0543868015800246 ,49.0194290212841 ,-0.267 ,0], [0.473153758252885 ,0.366893577716959 ,0.924972565581684 ,186.071352614705 ,-1 ,0], [0.0759305208803158 ,0.356365401030535 ,0.126682113674883 ,175.292109352674 ,0 ,-5.201], [0.91160934274653 ,0.32447818779582 ,0.741382053883291 ,0.11536775372698 ,0 ,-0.034], [0.480860406786873 ,0.903499596111067 ,0.542581424762866 ,32.782593418975 ,0 ,-1]]) def null(A, eps=1e-3): u,s,vh = svd(A,full_matrices=1,compute_uv=1) null_space = compress(s <= eps, vh, axis=0) return null_space.T NS = null(A) print "Null space equals ",NS,"\n" print dot(A,NS)

    Read the article

< Previous Page | 15 16 17 18 19 20 21 22 23 24 25 26  | Next Page >