Search Results

Search found 42 results on 2 pages for 'simplex'.

Page 1/2 | 1 2  | Next Page >

  • Simplex noise vs Perlin noise

    - by raRaRa
    I would like to know why Perlin noise is still so popular today after Simplex came out. Simplex noise was made by Ken Perlin himself and it was suppose to take over his old algorithm which was slow for higher dimensions and with better quality (no visible artifacts). Simplex noise came out in 2001 and over those 10 years I've only seen people talk of Perlin noise when it comes to generating heightmaps for terrains, creating procedural textures, et cetera. Could anyone help me out, is there some downside of Simplex noise? I heard rumors that Perlin noise is faster when it comes to 1D and 2D noise, but I don't know if it's true or not. Thanks!

    Read the article

  • Simplex Noise Help

    - by Alex Larsen
    Im Making A Minecraft Like Gae In XNA C# And I Need To Generate Land With Caves This Is The Code For Simplex I Have /// <summary> /// 1D simplex noise /// </summary> /// <param name="x"></param> /// <returns></returns> public static float Generate(float x) { int i0 = FastFloor(x); int i1 = i0 + 1; float x0 = x - i0; float x1 = x0 - 1.0f; float n0, n1; float t0 = 1.0f - x0 * x0; t0 *= t0; n0 = t0 * t0 * grad(perm[i0 & 0xff], x0); float t1 = 1.0f - x1 * x1; t1 *= t1; n1 = t1 * t1 * grad(perm[i1 & 0xff], x1); // The maximum value of this noise is 8*(3/4)^4 = 2.53125 // A factor of 0.395 scales to fit exactly within [-1,1] return 0.395f * (n0 + n1); } /// <summary> /// 2D simplex noise /// </summary> /// <param name="x"></param> /// <param name="y"></param> /// <returns></returns> public static float Generate(float x, float y) { const float F2 = 0.366025403f; // F2 = 0.5*(sqrt(3.0)-1.0) const float G2 = 0.211324865f; // G2 = (3.0-Math.sqrt(3.0))/6.0 float n0, n1, n2; // Noise contributions from the three corners // Skew the input space to determine which simplex cell we're in float s = (x + y) * F2; // Hairy factor for 2D float xs = x + s; float ys = y + s; int i = FastFloor(xs); int j = FastFloor(ys); float t = (float)(i + j) * G2; float X0 = i - t; // Unskew the cell origin back to (x,y) space float Y0 = j - t; float x0 = x - X0; // The x,y distances from the cell origin float y0 = y - Y0; // For the 2D case, the simplex shape is an equilateral triangle. // Determine which simplex we are in. int i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords if (x0 > y0) { i1 = 1; j1 = 0; } // lower triangle, XY order: (0,0)->(1,0)->(1,1) else { i1 = 0; j1 = 1; } // upper triangle, YX order: (0,0)->(0,1)->(1,1) // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where // c = (3-sqrt(3))/6 float x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords float y1 = y0 - j1 + G2; float x2 = x0 - 1.0f + 2.0f * G2; // Offsets for last corner in (x,y) unskewed coords float y2 = y0 - 1.0f + 2.0f * G2; // Wrap the integer indices at 256, to avoid indexing perm[] out of bounds int ii = i % 256; int jj = j % 256; // Calculate the contribution from the three corners float t0 = 0.5f - x0 * x0 - y0 * y0; if (t0 < 0.0f) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * grad(perm[ii + perm[jj]], x0, y0); } float t1 = 0.5f - x1 * x1 - y1 * y1; if (t1 < 0.0f) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * grad(perm[ii + i1 + perm[jj + j1]], x1, y1); } float t2 = 0.5f - x2 * x2 - y2 * y2; if (t2 < 0.0f) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * grad(perm[ii + 1 + perm[jj + 1]], x2, y2); } // Add contributions from each corner to get the final noise value. // The result is scaled to return values in the interval [-1,1]. return 40.0f * (n0 + n1 + n2); // TODO: The scale factor is preliminary! } public static float Generate(float x, float y, float z) { // Simple skewing factors for the 3D case const float F3 = 0.333333333f; const float G3 = 0.166666667f; float n0, n1, n2, n3; // Noise contributions from the four corners // Skew the input space to determine which simplex cell we're in float s = (x + y + z) * F3; // Very nice and simple skew factor for 3D float xs = x + s; float ys = y + s; float zs = z + s; int i = FastFloor(xs); int j = FastFloor(ys); int k = FastFloor(zs); float t = (float)(i + j + k) * G3; float X0 = i - t; // Unskew the cell origin back to (x,y,z) space float Y0 = j - t; float Z0 = k - t; float x0 = x - X0; // The x,y,z distances from the cell origin float y0 = y - Y0; float z0 = z - Z0; // For the 3D case, the simplex shape is a slightly irregular tetrahedron. // Determine which simplex we are in. int i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords int i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords /* This code would benefit from a backport from the GLSL version! */ if (x0 >= y0) { if (y0 >= z0) { i1 = 1; j1 = 0; k1 = 0; i2 = 1; j2 = 1; k2 = 0; } // X Y Z order else if (x0 >= z0) { i1 = 1; j1 = 0; k1 = 0; i2 = 1; j2 = 0; k2 = 1; } // X Z Y order else { i1 = 0; j1 = 0; k1 = 1; i2 = 1; j2 = 0; k2 = 1; } // Z X Y order } else { // x0<y0 if (y0 < z0) { i1 = 0; j1 = 0; k1 = 1; i2 = 0; j2 = 1; k2 = 1; } // Z Y X order else if (x0 < z0) { i1 = 0; j1 = 1; k1 = 0; i2 = 0; j2 = 1; k2 = 1; } // Y Z X order else { i1 = 0; j1 = 1; k1 = 0; i2 = 1; j2 = 1; k2 = 0; } // Y X Z order } // A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z), // a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and // a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where // c = 1/6. float x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords float y1 = y0 - j1 + G3; float z1 = z0 - k1 + G3; float x2 = x0 - i2 + 2.0f * G3; // Offsets for third corner in (x,y,z) coords float y2 = y0 - j2 + 2.0f * G3; float z2 = z0 - k2 + 2.0f * G3; float x3 = x0 - 1.0f + 3.0f * G3; // Offsets for last corner in (x,y,z) coords float y3 = y0 - 1.0f + 3.0f * G3; float z3 = z0 - 1.0f + 3.0f * G3; // Wrap the integer indices at 256, to avoid indexing perm[] out of bounds int ii = i % 256; int jj = j % 256; int kk = k % 256; // Calculate the contribution from the four corners float t0 = 0.6f - x0 * x0 - y0 * y0 - z0 * z0; if (t0 < 0.0f) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * grad(perm[ii + perm[jj + perm[kk]]], x0, y0, z0); } float t1 = 0.6f - x1 * x1 - y1 * y1 - z1 * z1; if (t1 < 0.0f) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * grad(perm[ii + i1 + perm[jj + j1 + perm[kk + k1]]], x1, y1, z1); } float t2 = 0.6f - x2 * x2 - y2 * y2 - z2 * z2; if (t2 < 0.0f) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * grad(perm[ii + i2 + perm[jj + j2 + perm[kk + k2]]], x2, y2, z2); } float t3 = 0.6f - x3 * x3 - y3 * y3 - z3 * z3; if (t3 < 0.0f) n3 = 0.0f; else { t3 *= t3; n3 = t3 * t3 * grad(perm[ii + 1 + perm[jj + 1 + perm[kk + 1]]], x3, y3, z3); } // Add contributions from each corner to get the final noise value. // The result is scaled to stay just inside [-1,1] return 32.0f * (n0 + n1 + n2 + n3); // TODO: The scale factor is preliminary! } private static byte[] perm = new byte[512] { 151,160,137,91,90,15, 131,13,201,95,96,53,194,233,7,225,140,36,103,30,69,142,8,99,37,240,21,10,23, 190, 6,148,247,120,234,75,0,26,197,62,94,252,219,203,117,35,11,32,57,177,33, 88,237,149,56,87,174,20,125,136,171,168, 68,175,74,165,71,134,139,48,27,166, 77,146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55,46,245,40,244, 102,143,54, 65,25,63,161, 1,216,80,73,209,76,132,187,208, 89,18,169,200,196, 135,130,116,188,159,86,164,100,109,198,173,186, 3,64,52,217,226,250,124,123, 5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,182,189,28,42, 223,183,170,213,119,248,152, 2,44,154,163, 70,221,153,101,155,167, 43,172,9, 129,22,39,253, 19,98,108,110,79,113,224,232,178,185, 112,104,218,246,97,228, 251,34,242,193,238,210,144,12,191,179,162,241, 81,51,145,235,249,14,239,107, 49,192,214, 31,181,199,106,157,184, 84,204,176,115,121,50,45,127, 4,150,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61,156,180, 151,160,137,91,90,15, 131,13,201,95,96,53,194,233,7,225,140,36,103,30,69,142,8,99,37,240,21,10,23, 190, 6,148,247,120,234,75,0,26,197,62,94,252,219,203,117,35,11,32,57,177,33, 88,237,149,56,87,174,20,125,136,171,168, 68,175,74,165,71,134,139,48,27,166, 77,146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55,46,245,40,244, 102,143,54, 65,25,63,161, 1,216,80,73,209,76,132,187,208, 89,18,169,200,196, 135,130,116,188,159,86,164,100,109,198,173,186, 3,64,52,217,226,250,124,123, 5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,182,189,28,42, 223,183,170,213,119,248,152, 2,44,154,163, 70,221,153,101,155,167, 43,172,9, 129,22,39,253, 19,98,108,110,79,113,224,232,178,185, 112,104,218,246,97,228, 251,34,242,193,238,210,144,12,191,179,162,241, 81,51,145,235,249,14,239,107, 49,192,214, 31,181,199,106,157,184, 84,204,176,115,121,50,45,127, 4,150,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61,156,180 }; private static int FastFloor(float x) { return (x > 0) ? ((int)x) : (((int)x) - 1); } private static float grad(int hash, float x) { int h = hash & 15; float grad = 1.0f + (h & 7); // Gradient value 1.0, 2.0, ..., 8.0 if ((h & 8) != 0) grad = -grad; // Set a random sign for the gradient return (grad * x); // Multiply the gradient with the distance } private static float grad(int hash, float x, float y) { int h = hash & 7; // Convert low 3 bits of hash code float u = h < 4 ? x : y; // into 8 simple gradient directions, float v = h < 4 ? y : x; // and compute the dot product with (x,y). return ((h & 1) != 0 ? -u : u) + ((h & 2) != 0 ? -2.0f * v : 2.0f * v); } private static float grad(int hash, float x, float y, float z) { int h = hash & 15; // Convert low 4 bits of hash code into 12 simple float u = h < 8 ? x : y; // gradient directions, and compute dot product. float v = h < 4 ? y : h == 12 || h == 14 ? x : z; // Fix repeats at h = 12 to 15 return ((h & 1) != 0 ? -u : u) + ((h & 2) != 0 ? -v : v); } private static float grad(int hash, float x, float y, float z, float t) { int h = hash & 31; // Convert low 5 bits of hash code into 32 simple float u = h < 24 ? x : y; // gradient directions, and compute dot product. float v = h < 16 ? y : z; float w = h < 8 ? z : t; return ((h & 1) != 0 ? -u : u) + ((h & 2) != 0 ? -v : v) + ((h & 4) != 0 ? -w : w); } This Is My World Generation Code Block[,] BlocksInMap = new Block[1024, 256]; public bool IsWorldGenerated = false; Random r = new Random(); private void RunThread() { for (int BH = 0; BH <= 256; BH++) { for (int BW = 0; BW <= 1024; BW++) { Block b = new Block(); if (BH >= 192) { } BlocksInMap[BW, BH] = b; } } IsWorldGenerated = true; } public void GenWorld() { new Thread(new ThreadStart(RunThread)).Start(); } And This Is A Example Of How I Set Blocks Block b = new Block(); b.BlockType = = Block.BlockTypes.Air; This Is A Example Of How I Set Models foreach (Block b in MyWorld) { switch(b.BlockType) { case Block.BlockTypes.Dirt: b.Model = DirtModel; break; ect. } } How Would I Use These To Generate To World (The Block Array) And If Possible Thread It More? btw It's 1024 Wide And 256 Tall

    Read the article

  • Why is my Simplex Noise appearing in four columns?

    - by Joe the Person
    I'm trying to make a Texture out of Simplex noise, but it keeps appearing like this regardless of how big or small scale is: The following code is used to produce the image's color date: private Color[,] GetSimplex() { Color[,] colors = new Color[800, 600]; float scale = colors.GetLength(0); for (int x = 0; x < 800; x++) { for (int y = 0; y < 600; y++) { byte noise = (byte)(Noise.Generate(x / scale, y / scale) * 255); colors[x, y] = new Color(noise, noise, noise); } } return colors; }

    Read the article

  • Using a permutation table for simplex noise without storing it

    - by J. C. Leitão
    Generating Simplex noise requires a permutation table for randomisation (e.g. see this question or this example). In some applications, we need to persist the state of the permutation table. This can be done by creating the table, e.g. using def permutation_table(seed): table_size = 2**10 # arbitrary for this question l = range(1, table_size + 1) random.seed(seed) # ensures the same shuffle for a given seed random.shuffle(l) return l + l # see shared link why l + l; is a detail and storing it. Can we avoid storing the full table by generating the required elements every time they are required? Specifically, currently I store the table and call it using table[i] (table is a list). Can I avoid storing it by having a function that computes the element i, e.g. get_table_element(seed, i). I'm aware that cryptography already solved this problem using block cyphers, however, I found it too complex to go deep and implement a block cypher. Does anyone knows a simple implementation of a block cypher to this problem?

    Read the article

  • Speeding up procedural texture generation

    - by FalconNL
    Recently I've begun working on a game that takes place in a procedurally generated solar system. After a bit of a learning curve (having neither worked with Scala, OpenGL 2 ES or Libgdx before), I have a basic tech demo going where you spin around a single procedurally textured planet: The problem I'm running into is the performance of the texture generation. A quick overview of what I'm doing: a planet is a cube that has been deformed to a sphere. To each side, a n x n (e.g. 256 x 256) texture is applied, which are bundled in one 8n x n texture that is sent to the fragment shader. The last two spaces are not used, they're only there to make sure the width is a power of 2. The texture is currently generated on the CPU, using the updated 2012 version of the simplex noise algorithm linked to in the paper 'Simplex noise demystified'. The scene I'm using to test the algorithm contains two spheres: the planet and the background. Both use a greyscale texture consisting of six octaves of 3D simplex noise, so for example if we choose 128x128 as the texture size there are 128 x 128 x 6 x 2 x 6 = about 1.2 million calls to the noise function. The closest you will get to the planet is about what's shown in the screenshot and since the game's target resolution is 1280x720 that means I'd prefer to use 512x512 textures. Combine that with the fact the actual textures will of course be more complicated than basic noise (There will be a day and night texture, blended in the fragment shader based on sunlight, and a specular mask. I need noise for continents, terrain color variation, clouds, city lights, etc.) and we're looking at something like 512 x 512 x 6 x 3 x 15 = 70 million noise calls for the planet alone. In the final game, there will be activities when traveling between planets, so a wait of 5 or 10 seconds, possibly 20, would be acceptable since I can calculate the texture in the background while traveling, though obviously the faster the better. Getting back to our test scene, performance on my PC isn't too terrible, though still too slow considering the final result is going to be about 60 times worse: 128x128 : 0.1s 256x256 : 0.4s 512x512 : 1.7s This is after I moved all performance-critical code to Java, since trying to do so in Scala was a lot worse. Running this on my phone (a Samsung Galaxy S3), however, produces a more problematic result: 128x128 : 2s 256x256 : 7s 512x512 : 29s Already far too long, and that's not even factoring in the fact that it'll be minutes instead of seconds in the final version. Clearly something needs to be done. Personally, I see a few potential avenues, though I'm not particularly keen on any of them yet: Don't precalculate the textures, but let the fragment shader calculate everything. Probably not feasible, because at one point I had the background as a fullscreen quad with a pixel shader and I got about 1 fps on my phone. Use the GPU to render the texture once, store it and use the stored texture from then on. Upside: might be faster than doing it on the CPU since the GPU is supposed to be faster at floating point calculations. Downside: effects that cannot (easily) be expressed as functions of simplex noise (e.g. gas planet vortices, moon craters, etc.) are a lot more difficult to code in GLSL than in Scala/Java. Calculate a large amount of noise textures and ship them with the application. I'd like to avoid this if at all possible. Lower the resolution. Buys me a 4x performance gain, which isn't really enough plus I lose a lot of quality. Find a faster noise algorithm. If anyone has one I'm all ears, but simplex is already supposed to be faster than perlin. Adopt a pixel art style, allowing for lower resolution textures and fewer noise octaves. While I originally envisioned the game in this style, I've come to prefer the realistic approach. I'm doing something wrong and the performance should already be one or two orders of magnitude better. If this is the case, please let me know. If anyone has any suggestions, tips, workarounds, or other comments regarding this problem I'd love to hear them.

    Read the article

  • Could someone explain in detail simplex /or perlin noise?

    - by Ryan Szemplinski
    I am really interested in perlin/simplex noise but I am having a difficult time understanding it. I am not very good at math but I am willing to learn because it interests me greatly. If someone is willing to dedicate there time into this I would be immensely appreciative of this. To be more concise, an explanation of functions and some calculation inside the functions would be nice to understand. Thanks in advance!

    Read the article

  • Sample uniformly at random from an n-dimensional unit simplex.

    - by dreeves
    Sampling uniformly at random from an n-dimensional unit simplex is the fancy way to say that you want n random numbers such that they are all non-negative, they sum to one, and every possible vector of n non-negative numbers that sum to one are equally likely. In the n=2 case you want to sample uniformly from the segment of the line x+y=1 (ie, y=1-x) that is in the positive quadrant. In the n=3 case you're sampling from the triangle-shaped part of the plane x+y+z=1 that is in the positive octant of R3: (Image from http://en.wikipedia.org/wiki/Simplex.) Note that picking n uniform random numbers and then normalizing them so they sum to one does not work. You end up with a bias towards less extreme numbers. Similarly, picking n-1 uniform random numbers and then taking the nth to be one minus the sum of them also introduces bias. Wikipedia gives two algorithms to do this correctly: http://en.wikipedia.org/wiki/Simplex#Random_sampling (Though the second one currently claims to only be correct in practice, not in theory. I'm hoping to clean that up or clarify it when I understand this better. I initially stuck in a "WARNING: such-and-such paper claims the following is wrong" on that Wikipedia page and someone else turned it into the "works only in practice" caveat.) Finally, the question: What do you consider the best implementation of simplex sampling in Mathematica (preferably with empirical confirmation that it's correct)? Related questions http://stackoverflow.com/questions/2171074/generating-a-probability-distribution http://stackoverflow.com/questions/3007975/java-random-percentages

    Read the article

  • FreeBSD 8.0 - Macbook: Trying to Connect to Wireless

    - by Koroviev
    What Happened A few days ago I installed FreeBSD 8from USB to my Macbook (Core Duo, 13"). The first thing I wanted to do was get my GUI back. I'm new to FreeBSD and it's my first time off of mac or windows, so I had some learning to do. I tried to a make clean install of xorg with ports but it returned many "No address record" errors. I realised I hadn't configured network settings and then the fun started. I ran ifconfig and it found 5 devices: msk0, ath0, fwe0, fwip0, lo0. * ath0 was identified as media: IEEE 802.11 Wireless Ethernet autoselect so it was clear which one I needed. From what I gathered, there are 3 files and two processes involved here: /boot/loader.conf /etc/wpa_supplicant.conf /etc/rc.conf /etc/rc.d/netif wpa_supplicant (which is a part of the former too) I'm certain it's a big simplification, so correct me if I'm wrong here. What I Tried I configured /boot/loader.conf with the few basic settings, and I'm most sure that this file is okay. The other 2 were more puzzling. I tried to make a network package in wpa_supplicant.conf. I found the ssid of the router, but the security wasn't so easy. The routers configuration on security is set to "Auto", with no explanation given. Other options are there, but Auto is selected. Another laptop uses WEP to connect (it's Vista, so I don't know how to get any more info than that), but I never configured it to do it. There's a string labled "wireless key" on the bottom of the router which I entered to set it up a new machine on the network (Windows and Macs, so it was simplified). I never had to choose a security type and only learned about them by installing FreeBSD. So perhaps WEP is what "Auto" means, but I can't find any other evidence. wpa_supplicant.conf seemed to never be correctly configured. I always got errors related to it and WPA_supplicant doesn't work. It gave me "Can't disable/enable WPA in the driver" errors and more once when I enabled -d -d. This was when I was trying some suspect configurations in rc.conf though. Usually it does nothing except hijack the shell and print "CTRL-SCAN-EVENT-RESULT" every 10 seconds. I learned how to clone the ath0 device to a wlandev interface (wlan0). ath0 is associated to it and their connection seems to go smoothly. But the wlan0's connection to the network is the problem. I couldn't create this with rc.conf, I do something wrong and get ifconfig: create: bad value errors whenever it's parsed. I did it via the shell instead. What Now? I scanned with wlan0 today: ifconfig wlan0 list scan It shows my router, even my neighbour's router. It was a relief to finally get some feedback. So wlan0 is UP and detects the router, but it is always status: no carrier. It can't associate with it and I can't figure out why. Running /etc/rc.d/netif start returns almost the same result as ifconfig would. It shows lo0 and wlan0, and sometimes ath0. I still not sure what lo0 is doing. So; how do I associate with it? We can assume it's WEP security based on how the other laptop is setup. I'll give every relevant output here. After boot, with a blank rc.conf this is what ifconfig returns: msk0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=11a<TXCSUM,VLAN_MTU,VLAN_HWTAGGING,TSO4> ether 00:17:f2:29:89:3b media: Ethernet autoselect ath0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 2290 ether 00:16:cb:bb:fe:65 media: IEEE 802.11 Wireless Ethernet autoselect (autoselect) status: no carrier fwe0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=8<VLAN_MTU> ether 02:17:f2:60:ad:7e ch 1 dma -1 fwip0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 lladdr 0.17.f2.ff.fe.60.ad.7e.a.2.ff.fe.0.0.0.0 lo0: flags=8049<UP,LOOPBACK,RUNNING,MULTICAST> metric 0 mtu 16384 options=3<RXCSUM,TXCSUM> inet6 fe80::1%lo0 prefixlen 64 scopeid 0x5 inet6 ::1 prefixlen 128 inet 127.0.0.1 netmask 0xff000000 I run: ifconfig wlan0 create wlandev ath0 It returns: wlan0: bpf attached wlan0: bpf attached wlan0: Ethernet address: xx:xx:xx:xx:xx:xx Ifconfig now returns: msk0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=11a<TXCSUM,VLAN_MTU,VLAN_HWTAGGING,TSO4> ether 00:17:f2:29:89:3b media: Ethernet autoselect ath0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 2290 ether 00:16:cb:bb:fe:65 media: IEEE 802.11 Wireless Ethernet autoselect (autoselect) status: no carrier fwe0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=8<VLAN_MTU> ether 02:17:f2:60:ad:7e ch 1 dma -1 fwip0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 lladdr 0.17.f2.ff.fe.60.ad.7e.a.2.ff.fe.0.0.0.0 lo0: flags=8049<UP,LOOPBACK,RUNNING,MULTICAST> metric 0 mtu 16384 options=3<RXCSUM,TXCSUM> inet6 fe80::1%lo0 prefixlen 64 scopeid 0x5 inet6 ::1 prefixlen 128 inet 127.0.0.1 netmask 0xff000000 wlan0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> metric 0 mtu 1500 ether 00:16:cb:bb:fe:65 media: IEEE 802.11 Wireless Ethernet autoselect (autoselect) status: no carrier ssid "" channel 1 (2412 Mhz 11b) regdomain 106 indoor ecm authmode OPEN privacy OFF txpower 20 bmiss 7 scanvalid 60 bgscan bgscanintvl 300 bgscanidle 250 roam:rssi 7 roam:rate 1 wme burst bintval 0 I run: ifconfig wlan0 up ifconfig wlan0 scan It finds my router and displays its details. I can feed it my routers details now, using: ifconfig wlan0 key value key value ... They show up in wlan0 when I run ifconfig, but it still doesn't associate. What details should I feed it, what exactly is needed? What, if anything, should I have in /etc/wpa_supplicant.conf (and if that psk is needed, is it most likely the string I mentioned above)? If I define the ssid in wpa_supplicant.conf, should I still feed it to wlan0? What process should I then use to associate it? 5 .How should I add these things to rc.conf so it will automatically do this at boot? A huge thank you in advance for any help you can give, I've spent hours crawling about the shell and I've learned quite a bit from it (I finally got the hang of vi too, from all that editing). But the sooner this is fixed, the better. *P.S. I was, and still am, wondering where the extra three devices come from (the wireless and wired were all I expected to find). lo0 is up at each boot and /etc/rc.d/netif, I have no idea what it is and can't find it in dmesg. Resources: /etc/loader.conf: Code: if_ath_load="YES" wlan_wep_load="YES" wlan_ccmp_load="YES" wlan_tkip_load="YES" /etc/wpa_supplicant.conf (I emptied it of everything unnecessary, because I was just causing errors) network={ ssid="BTVOYAGER2110-1C" } /etc/rc.conf has no network settings, I commented them out because of errors. There was my attempt to clone ath0 and feed it info, but I did if via the shell instead. I've included the output of dmesg as an attachment, in case it's useful. I'd include the boot text (which appears before login) but I don't know how to catch it into a text file. If it's needed and somebody tells me how, I will (actually, even if it's not needed, how can I view it to read?).

    Read the article

  • Can't connect to local IP address on OSX

    - by Alex Worden
    I'm trying to connect to a webserver that's running on my mac OSX 1.6. I'm able to connect to it locally using http://127.0.0.1:8888/myapp but when I attempt to connect to it using my machine's local IP address (http://192.168.1.15:8888/myapp IP shown below) from the same machine (or another on the network) I cannot connect. I can ping the LAN IP address. I've tried adding IP forwarding to my router for port 8888 but it didn't help. I've checked and the OSX firewall is disabled Can anyone suggest what else is blocking the connection? Here's what I get when I run ifconfig: ~ :ifconfig lo0: flags=8049<UP,LOOPBACK,RUNNING,MULTICAST> mtu 16384 inet6 ::1 prefixlen 128 inet6 fe80::1%lo0 prefixlen 64 scopeid 0x1 inet 127.0.0.1 netmask 0xff000000 gif0: flags=8010<POINTOPOINT,MULTICAST> mtu 1280 stf0: flags=0<> mtu 1280 en0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether 00:1f:5b:e8:16:4d media: autoselect status: inactive supported media: autoselect 10baseT/UTP <half-duplex> 10baseT/UTP <full-duplex> 10baseT/UTP <full-duplex,hw-loopback> 10baseT/UTP <full-duplex,flow-control> 100baseTX <half-duplex> 100baseTX <full-duplex> 100baseTX <full-duplex,hw-loopback> 100baseTX <full-duplex,flow-control> 1000baseT <full-duplex> 1000baseT <full-duplex,hw-loopback> 1000baseT <full-duplex,flow-control> none en1: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 inet6 fe80::21e:c2ff:febf:4809%en1 prefixlen 64 scopeid 0x5 inet 192.168.1.15 netmask 0xffffff00 broadcast 192.168.1.255 ether 00:1e:c2:bf:48:09 media: autoselect status: active supported media: autoselect fw0: flags=8802<BROADCAST,SIMPLEX,MULTICAST> mtu 4078 lladdr 00:1f:5b:ff:fe:2b:b3:3c media: autoselect <full-duplex> status: inactive supported media: autoselect <full-duplex> en5: flags=8822<BROADCAST,SMART,SIMPLEX,MULTICAST> mtu 1500 ether 00:1e:c2:8e:0f:45 media: autoselect status: inactive supported media: none autoselect 10baseT/UTP <half-duplex> en2: flags=8922<BROADCAST,SMART,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:1c:42:00:00:00 media: autoselect status: inactive supported media: autoselect en3: flags=8922<BROADCAST,SMART,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:1c:42:00:00:01 media: autoselect status: inactive supported media: autoselect

    Read the article

  • Draw multiple objects with textures

    - by Simplex
    I want to draw cubes using textures. void OperateWithMainMatrix(ESContext* esContext, GLfloat offsetX, GLfloat offsetY, GLfloat offsetZ) { UserData *userData = (UserData*) esContext->userData; ESMatrix modelview; ESMatrix perspective; //Manipulation with matrix ... glVertexAttribPointer(userData->positionLoc, 3, GL_FLOAT, GL_FALSE, 0, cubeFaces); //in cubeFaces coordinates verticles cube glVertexAttribPointer(userData->normalLoc, 3, GL_FLOAT, GL_FALSE, 0, cubeFaces); //for normals (use in fragment shaider for textures) glEnableVertexAttribArray(userData->positionLoc); glEnableVertexAttribArray(userData->normalLoc); // Load the MVP matrix glUniformMatrix4fv(userData->mvpLoc, 1, GL_FALSE, (GLfloat*)&userData->mvpMatrix.m[0][0]); //Bind base map glActiveTexture(GL_TEXTURE0); glBindTexture(GL_TEXTURE_CUBE_MAP, userData->baseMapTexId); //Set the base map sampler to texture unit to 0 glUniform1i(userData->baseMapLoc, 0); // Draw the cube glDrawArrays(GL_TRIANGLES, 0, 36); } (coordinates transformation is in OperateWithMainMatrix() ) Then Draw() function is called: void Draw(ESContext *esContext) { UserData *userData = esContext->userData; // Set the viewport glViewport(0, 0, esContext->width, esContext->height); // Clear the color buffer glClear(GL_COLOR_BUFFER_BIT); // Use the program object glUseProgram(userData->programObject); OperateWithMainMatrix(esContext, 0.0f, 0.0f, 0.0f); eglSwapBuffers(esContext->eglDisplay, esContext->eglSurface); } This work fine, but if I try to draw multiple cubes (next code for example): void Draw(ESContext *esContext) { ... // Use the program object glUseProgram(userData->programObject); OperateWithMainMatrix(esContext, 2.0f, 0.0f, 0.0f); OperateWithMainMatrix(esContext, 1.0f, 0.0f, 0.0f); OperateWithMainMatrix(esContext, 0.0f, 0.0f, 0.0f); OperateWithMainMatrix(esContext, -1.0f, 0.0f, 0.0f); OperateWithMainMatrix(esContext, -2.0f, 0.0f, 0.0f); eglSwapBuffers(esContext->eglDisplay, esContext->eglSurface); } A side faces overlapes frontal face. The side face of the right cube overlaps frontal face of the center cube. How can i remove this effect and display miltiple cubes without it?

    Read the article

  • CARP: two machines think they're the master, but only on one interface

    - by Conor McDermottroe
    I have two machines, each configured identically as a firewall/load balancer for a busy website. I have set them up with CARP and pfsync on both the internal and external interfaces. The internal interface is behaving as expected (primary listed as MASTER and secondary listed as BACKUP) On both machines, the network interfaces are as follows: em0 - External interface bge0 - Internal interface bge1 - Crossover connection between both machines carp0 - Shared external interface for CARP carp1 - Shared internal interface for CARP I've rewritten the IP addresses and MAC addresses below. The networks are as follows: 10.0.1.0/24 - External network 10.0.2.0/24 - Internal network 10.0.3.0/24 - Crossover network Here's the output from ifconfig on the primary: em0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=19b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM,TSO4> ether [SNIP] inet 10.0.1.10 netmask 0xffffff00 broadcast 10.0.1.255 media: Ethernet 100baseTX <full-duplex> status: active bge0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=9b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM> ether [SNIP] inet 10.0.2.10 netmask 0xffffff00 broadcast 10.0.2.255 media: Ethernet 1000baseT <full-duplex> status: active bge1: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=9b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM> ether [SNIP] inet 10.0.3.10 netmask 0xffffff00 broadcast 10.0.3.255 media: Ethernet 1000baseT <full-duplex> status: active lo0: flags=80c9<UP,LOOPBACK,RUNNING,NOARP,MULTICAST> metric 0 mtu 16384 options=3<RXCSUM,TXCSUM> inet6 fe80::1%lo0 prefixlen 64 scopeid 0x4 inet6 ::1 prefixlen 128 inet 127.0.0.1 netmask 0xff000000 pflog0: flags=141<UP,RUNNING,PROMISC> metric 0 mtu 33152 pfsync0: flags=0<> metric 0 mtu 1460 pfsync: syncdev: bge1 syncpeer: 10.0.3.11 maxupd: 128 carp0: flags=49<UP,LOOPBACK,RUNNING> metric 0 mtu 1500 inet 10.0.1.5 netmask 0xffffff00 carp: MASTER vhid 1 advbase 1 advskew 0 carp1: flags=49<UP,LOOPBACK,RUNNING> metric 0 mtu 1500 inet 10.0.2.5 netmask 0xffffff00 carp: MASTER vhid 2 advbase 1 advskew 0 And here's the /etc/rc.conf excerpt from the primary: defaultrouter="10.0.1.1" network_interfaces="em0 bge0 bge1 lo0 pfsync0" cloned_interfaces="carp0 carp1" ifconfig_em0="inet 10.0.1.10 netmask 255.255.255.0 media 100BaseTX mediaopt full-duplex" ifconfig_bge0="inet 10.0.2.10 netmask 255.255.255.0 media 1000BaseTX mediaopt full-duplex" ifconfig_bge1="inet 10.0.3.10 netmask 255.255.255.0 media 1000BaseTX mediaopt full-duplex" ifconfig_carp0="vhid 1 pass [SNIP] 10.0.1.5/24" ifconfig_carp1="vhid 2 pass [SNIP] 10.0.2.5/24" pfsync_enable="YES" pfsync_syncdev="bge1" pfsync_syncpeer="10.0.3.11" And here's the output on the secondary: em0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=19b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM,TSO4> ether [SNIP] inet 10.0.1.11 netmask 0xffffff00 broadcast 10.0.1.255 media: Ethernet 100baseTX <full-duplex> status: active bge0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=9b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM> ether [SNIP] inet 10.0.2.11 netmask 0xffffff00 broadcast 10.0.2.255 media: Ethernet 1000baseT <full-duplex> status: active bge1: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=9b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM> ether [SNIP] inet 10.0.3.11 netmask 0xffffff00 broadcast 10.0.3.255 media: Ethernet 1000baseT <full-duplex> status: active lo0: flags=80c9<UP,LOOPBACK,RUNNING,NOARP,MULTICAST> metric 0 mtu 16384 options=3<RXCSUM,TXCSUM> inet6 fe80::1%lo0 prefixlen 64 scopeid 0x4 inet6 ::1 prefixlen 128 inet 127.0.0.1 netmask 0xff000000 pflog0: flags=141<UP,RUNNING,PROMISC> metric 0 mtu 33152 pfsync0: flags=0<> metric 0 mtu 1460 pfsync: syncdev: bge1 syncpeer: 10.0.3.10 maxupd: 128 carp0: flags=49<UP,LOOPBACK,RUNNING> metric 0 mtu 1500 inet 10.0.1.5 netmask 0xffffff00 carp: MASTER vhid 1 advbase 1 advskew 20 carp1: flags=49<UP,LOOPBACK,RUNNING> metric 0 mtu 1500 inet 10.0.2.5 netmask 0xffffff00 carp: BACKUP vhid 2 advbase 1 advskew 20 And here's the /etc/rc.conf excerpt from the secondary: defaultrouter="10.0.1.1" network_interfaces="em0 bge0 bge1 lo0 pfsync0" cloned_interfaces="carp0 carp1" ifconfig_em0="inet 10.0.1.11 netmask 255.255.255.0 media 100BaseTX mediaopt full-duplex" ifconfig_bge0="inet 10.0.2.11 netmask 255.255.255.0 media 1000BaseTX mediaopt full-duplex" ifconfig_bge1="inet 10.0.3.11 netmask 255.255.255.0 media 1000BaseTX mediaopt full-duplex" ifconfig_carp0="vhid 1 pass [SNIP] advskew 20 10.0.1.5/24" ifconfig_carp1="vhid 2 pass [SNIP] advskew 20 10.0.2.5/24" pfsync_enable="YES" pfsync_syncdev="bge1" pfsync_syncpeer="10.0.3.10" What I don't understand is, the carp status on carp0 is MASTER on both machines when the status on carp1 is as it should be (MASTER on the primary and BACKUP on the secondary). What am I missing? Where should I be looking for clues?

    Read the article

  • ifconfig networking telnet

    - by jhon
    Hi guys, I'm newbie around networking, I have a question: what I want is to telnet a specific IP/server, let us say 192.168.128.1 then, I try $telnet 192.168.128.1 Trying... and that's all.. I never get connected one of my friends made some script that "fixes" it, AFTER running it I was able to connect to the server using $telnet 192.168.128.1 $ user: unfortunately I lost that script, so I'm here requesting your help. Reading my old notes, I remember that the script performed some modification to the entries listed by ifconfig -a, I also have the ifconfig's output (copy & paste) $ ifconfig -a adapter0: flags=5e080863,c0<UP,BROADCAST,NOTRAILERS,RUNNING,SIMPLEX,MULTICAST,GROUPRT,64BIT,CHECKSUM_OFFLOAD(ACTIVE),PSEG,LARGESEND,CHAIN> inet 192.168.128.150 netmask 0xffffff00 broadcast 192.168.128.255 tcp_sendspace 131072 tcp_recvspace 65536 rfc1323 0 adapter1: flags=5e080863,c0<UP,BROADCAST,NOTRAILERS,RUNNING,SIMPLEX,MULTICAST,GROUPRT,64BIT,CHECKSUM_OFFLOAD(ACTIVE),PSEG,LARGESEND,CHAIN> inet 192.168.251.150 netmask 0xffffff00 broadcast 192.168.251.255 tcp_sendspace 131072 tcp_recvspace 65536 rfc1323 0 adapter2: flags=5e080863,c0<UP,BROADCAST,NOTRAILERS,RUNNING,SIMPLEX,MULTICAST,GROUPRT,64BIT,CHECKSUM_OFFLOAD(ACTIVE),PSEG,LARGESEND,CHAIN> inet 192.168.250.150 netmask 0xffffff00 broadcast 192.168.250.255 tcp_sendspace 131072 tcp_recvspace 65536 rfc1323 0 lo0: flags=e08084b<UP,BROADCAST,LOOPBACK,RUNNING,SIMPLEX,MULTICAST,GROUPRT,64BIT> inet 127.0.0.1 netmask 0xff000000 broadcast 127.255.255.255 inet6 ::1/0 tcp_sendspace 131072 tcp_recvspace 131072 rfc1323 1 more than commands, I'm looking for some explanation why does "adding/changing" those entries enables me to connect to the server. I do not see the server ip (i.e 192.168.128.1) listed above. thanks

    Read the article

  • I Don't Understand Anything About Randomly Generated Worlds [closed]

    - by Alex Larsen
    What tools do I need to make a Minecraft-like generated world? I heard about Perlin noise and Simplex, but I don't understand anything about them. So far all I found on the internet was a Simplex version for C#, and all it has is functions, and this is what I get: Console.WriteLine(Noise.Generate(SomeNumber, SomeNumber, SumNumber)); Outputs random floats. I'm really lost. I don't understand the whole random generated worlds concept. Can someone help me? And if I use the noise thing I don't understand how to use it.

    Read the article

  • Can GJK be used with the same "direction finding method" every time?

    - by the_Seppi
    In my deliberations on GJK (after watching http://mollyrocket.com/849) I came up with the idea that it ins not neccessary to use different methods for getting the new direction in the doSimplex function. E.g. if the point A is closest to the origin, the video author uses the negative position vector AO as the direction in which the next point is searched. If an edge (with A as an endpoint) is closest, he creates a normal vector to this edge, lying in the plane the edge and AO form. If a face is the feature closest to the origin, he uses even another method (which I can't recite from memory right now) However, while thinking about the implementation of GJK in my current came, I noticed that the negative direction vector of the newest simplex point would always make a good direction vector. Of course, the next vertex found by the support function could form a simplex that less likely encases the origin, but I assume it would still work. Since I'm currently experiencing problems with my (yet unfinished) implementation, I wanted to ask whether this method of forming the direction vector is usable or not.

    Read the article

  • Bridged network on OS X only gets UDP broadcast traffic

    - by a paid nerd
    I've created a bridged network Mac OS X 10.8.5 using ifconfig and TUNTAP for OS X to bridge my wireless connection, en0, with a virtual interface, tap0, which I can use for guest VMs: $ sudo sysctl -w net.inet.ip.forwarding=1 $ sudo sysctl -w net.link.ether.inet.proxyall=1 $ sudo sysctl -w net.inet.ip.fw.enable=1 $ sudo ifconfig bridge0 create $ sudo ifconfig bridge0 addm en0 addm tap0 $ sudo ifconfig bridge0 up $ ifconfig en0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether 28:cf:xx:xx:xx:xx inet6 xxxx::xxxx:xxxx:xxxx:xxxx%en0 prefixlen 64 scopeid 0x4 inet 192.168.100.64 netmask 0xffffff00 broadcast 192.168.100.1 media: autoselect status: active bridge0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether ac:de:xx:xx:xx:xx Configuration: priority 0 hellotime 0 fwddelay 0 maxage 0 ipfilter disabled flags 0x2 member: en0 flags=3<LEARNING,DISCOVER> port 4 priority 0 path cost 0 member: tap0 flags=3<LEARNING,DISCOVER> port 8 priority 0 path cost 0 tap0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether ca:3d:xx:xx:xx:xx open (pid 88244) However, if I tcpdump -i tap0, I only see broadcast traffic. Shouldn't I see a mirror of everything on en0? (192.168.100.33, the host doing the broadcasting, is another unrelate, noisy server on my LAN.) (I asked a similar question here and will probably close it.)

    Read the article

  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

    Read the article

  • Mac OS X 10.6 assign mapped IP to Windows 7 VM in Parallels

    - by Alex
    I'm trying to assign a mapped IP address to a Windows 7 VM. I have setup running in Parallels 5 in wireless bridged networking mode. The problem I am having is that it looks like the VM is actually broadcasting the MAC address of the host machine and thus causing a clash of IP addresses on the network. This is my current setup: Macbook Pro :~ ifconfig -a lo0: flags=8049<UP,LOOPBACK,RUNNING,MULTICAST> mtu 16384 inet6 ::1 prefixlen 128 inet6 fe80::1%lo0 prefixlen 64 scopeid 0x1 inet 127.0.0.1 netmask 0xff000000 gif0: flags=8010<POINTOPOINT,MULTICAST> mtu 1280 stf0: flags=0<> mtu 1280 en0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether 00:26:b0:df:31:b4 media: autoselect status: inactive supported media: none autoselect 10baseT/UTP <half-duplex> 10baseT/UTP <full-duplex> 10baseT/UTP <full-duplex,flow-control> 10baseT/UTP <full-duplex,hw-loopback> 100baseTX <half-duplex> 100baseTX <full-duplex> 100baseTX <full-duplex,flow-control> 100baseTX <full-duplex,hw-loopback> 1000baseT <full-duplex> 1000baseT <full-duplex,flow-control> 1000baseT <full-duplex,hw-loopback> fw0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 4078 lladdr 00:26:b0:ff:fe:df:31:b4 media: autoselect <full-duplex> status: inactive supported media: autoselect <full-duplex> en1: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 inet6 fe80::226:bbff:fe0a:59a1%en1 prefixlen 64 scopeid 0x6 inet 192.168.1.97 netmask 0xffffff00 broadcast 192.168.1.255 ether 00:26:bb:0a:59:a1 media: autoselect status: active supported media: autoselect vnic0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> mtu 1500 inet 192.168.1.81 netmask 0xffffff00 broadcast 192.168.1.255 ether 00:1c:42:00:00:08 media: autoselect status: active supported media: autoselect vnic1: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> mtu 1500 inet 10.37.129.2 netmask 0xffffff00 broadcast 10.37.129.255 ether 00:1c:42:00:00:09 media: autoselect status: active supported media: autoselect Windows 7: :~ ipconfig -all Windows IP Configuration Host Name . . . . . . . . . . . . : Alex-PC Primary Dns Suffix . . . . . . . : Node Type . . . . . . . . . . . . : Hybrid IP Routing Enabled. . . . . . . . : No WINS Proxy Enabled. . . . . . . . : No Ethernet adapter Local Area Connection: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Parallels Ethernet Adapter Physical Address. . . . . . . . . : 00-1C-42-B8-E7-B4 DHCP Enabled. . . . . . . . . . . : Yes Autoconfiguration Enabled . . . . : Yes Tunnel adapter Teredo Tunneling Pseudo-Interface: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Microsoft Teredo Tunneling Adapter Physical Address. . . . . . . . . : 00-00-00-00-00-00-00-E0 DHCP Enabled. . . . . . . . . . . : No Autoconfiguration Enabled . . . . : Yes Tunnel adapter isatap.{ACAC7EBB-5E5F-4F53-AFD9-E6EAEEA0FEE2}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Microsoft ISATAP Adapter #3 Physical Address. . . . . . . . . : 00-00-00-00-00-00-00-E0 DHCP Enabled. . . . . . . . . . . : No Autoconfiguration Enabled . . . . : Yes Billion Bipac 7200 modem router: In DHCP server settings have the following two mapping entries. alex-macbook-win7 00:1c:42:00:00:08 192.168.1.98 alex-macbook 00:26:bb:0a:59:a1 192.168.1.97 The problem I have is that when the VM starts up it gets assigned the 192.168.1.97 address instead of the .98 address and thus networking on the host stops working as it says there is a clash. I have tried removing the mapping for "alex-macbook" which results in the guest machine being assigned a normal DHCP address and NOT the one that is in the mapping of the router.

    Read the article

  • OS X won't see Windows 7 in network (and vice versa)

    - by meds
    I've enabled SMB sharing in OS X Lion and have added folders to share, it says 'Windows Sharing: On' with a green circle next to it (from the sharing window) and that to access the volume I will need to to go to \\192.168.0.17. It also says that the OS X should be visible as 'macbook' in the network. Both my WIndows 7 and OS X are connected to the same network, yet when I try to go to \\192.168.0.17 or from the Mac try to go to my Windows system (smb://192.168.0.6) the two OSs don't see each other. Any ideas why? Attempting to ping the Mac from Windows results in this output in the command prompt: Pinging 192.168.0.17 with 32 bytes of data: Reply from 192.168.0.6: Destination host unreachable. Request timed out. Request timed out. Request timed out. Ping statistics for 192.168.0.17: Packets: Sent = 4, Received = 1, Lost = 3 (75% loss), ipconfig in Windows is: Wireless LAN adapter Wireless Network Connection: Connection-specific DNS Suffix . : Link-local IPv6 Address . . . . . : fe80::8918:efd1:b05c:890f%21 IPv4 Address. . . . . . . . . . . : 192.168.0.6 Subnet Mask . . . . . . . . . . . : 255.255.255.0 Default Gateway . . . . . . . . . : 192.168.0.1 Ethernet adapter Bluetooth Network Connection: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Ethernet adapter VMware Network Adapter VMnet1: Connection-specific DNS Suffix . : Link-local IPv6 Address . . . . . : fe80::98ab:63fc:3c07:d837%13 IPv4 Address. . . . . . . . . . . : 192.168.74.1 Subnet Mask . . . . . . . . . . . : 255.255.255.0 Default Gateway . . . . . . . . . : Ethernet adapter VMware Network Adapter VMnet8: Connection-specific DNS Suffix . : Link-local IPv6 Address . . . . . : fe80::80ff:c575:7b50:3a10%14 IPv4 Address. . . . . . . . . . . : 192.168.21.1 Subnet Mask . . . . . . . . . . . : 255.255.255.0 Default Gateway . . . . . . . . . : Tunnel adapter isatap.{2E97D0AE-9E18-4072-AC23-1979BA0DCB79}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Tunnel adapter isatap.{E260CE43-E9A7-4DE0-A88E-4EAFF68ACDDB}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Tunnel adapter isatap.{A5130812-59CE-4DDF-9C35-9433BCED9831}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Tunnel adapter Teredo Tunneling Pseudo-Interface: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Tunnel adapter isatap.{134BCAE7-CFFF-4A98-8DA0-3708806AABEB}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Tunnel adapter isatap.{8D9E3B8F-161C-4ACE-B211-3EDD694416B2}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : in OS X: lo0: flags=8049<UP,LOOPBACK,RUNNING,MULTICAST> mtu 16384 options=3<RXCSUM,TXCSUM> inet6 fe80::1%lo0 prefixlen 64 scopeid 0x1 inet 127.0.0.1 netmask 0xff000000 inet6 ::1 prefixlen 128 gif0: flags=8010<POINTOPOINT,MULTICAST> mtu 1280 stf0: flags=0<> mtu 1280 en0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 options=2b<RXCSUM,TXCSUM,VLAN_HWTAGGING,TSO4> ether c8:2a:14:01:24:c1 media: autoselect (none) status: inactive en1: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether e0:f8:47:0c:fe:04 inet6 fe80::e2f8:47ff:fe0c:fe04%en1 prefixlen 64 scopeid 0x5 inet 192.168.0.17 netmask 0xffffff00 broadcast 192.168.0.255 media: autoselect status: active p2p0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> mtu 2304 ether 02:f8:47:0c:fe:04 media: autoselect status: inactive fw0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 4078 lladdr 70:cd:60:ff:fe:d8:f1:32 media: autoselect <full-duplex> status: inactive

    Read the article

  • How do I create a wifi network bridge with qemu on OS X?

    - by a paid nerd
    I grabbed a small FreeBSD live CD and QEMU, and I'm trying to bridge my Mac OS X 10.8 wifi connection so that the guest OS is available on my LAN. However, the guest OS never gets a DHCP lease. This works perfectly with VirtualBox in their "bridged" network mode, so I know it can be done. I need to get it working with QEMU because VirtualBox doesn't support the architecture that I need for this project. Here's what I've done so far based on hours of googling: Installed TUNTAP for OS X Told OS X to supposedly forward all packets, even ARP: (NOTE: This doesn't appear to work.) $ sudo sysctl -w net.inet.ip.forwarding=1 $ sudo sysctl -w net.link.ether.inet.proxyall=1 $ sudo sysctl -w net.inet.ip.fw.enable=1 Created a bridge: $ sudo ifconfig bridge0 create $ sudo ifconfig bridge0 addm en0 addm tap0 $ sudo ifconfig bridge0 up $ ifconfig bridge0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500 ether ac:de:xx:xx:xx:xx Configuration: priority 0 hellotime 0 fwddelay 0 maxage 0 ipfilter disabled flags 0x2 member: en0 flags=3<LEARNING,DISCOVER> port 4 priority 0 path cost 0 member: tap0 flags=3<LEARNING,DISCOVER> port 8 priority 0 path cost 0 tap0: flags=8943<UP,BROADCAST,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether ca:3d:xx:xx:xx:xx open (pid 88244) Started tcpdump with -I in the hopes that it enables promiscuous mode on the wifi device: $ sudo tcpdump -In -i en0 Run QEMU using the bridged network instructions: $ qemu-system-x86_64 -cdrom mfsbsd-9.2-RELEASE-amd64.iso -m 1024 \ -boot d -net nic -net tap,ifname=tap0,script=no,downscript=no But the guest system never gets a DHCP lease: If I tcpdump -ni tap0, I see lots of traffic from the wireless network. But if I tcpdump -ni en0, I don't see any DHCP traffic from the QEMU guest OS. Any ideas? Update 1: I tried sudo defaults write "/Library/Preferences/SystemConfiguration/com.apple.Boot" "Kernel Flags" "net.inet.ip.scopedroute=0" and rebooting per this mailing list suggestion, but this didn't help. In fact, it made VirtualBox bridged mode stop working.

    Read the article

  • Under FreeBSD, can a VLAN interface have a smaller MTU than the primary interface?

    - by larsks
    I have a system with two physical interfaces, combined into a LACP aggregation group. That LACP channel has two VLANs, one untagged (the "native vlan") and one using VLAN tagging. This gives us: lagg0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=19b<RXCSUM,TXCSUM,VLAN_MTU,VLAN_HWTAGGING,VLAN_HWCSUM,TSO4> ether 00:25:90:1d:fe:8e inet 10.243.24.23 netmask 0xffffff00 broadcast 10.243.24.255 media: Ethernet autoselect status: active laggproto lacp laggport: em1 flags=1c<ACTIVE,COLLECTING,DISTRIBUTING> laggport: em0 flags=1c<ACTIVE,COLLECTING,DISTRIBUTING> vlan0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500 options=3<RXCSUM,TXCSUM> ether 00:25:90:1d:fe:8e inet 10.243.16.23 netmask 0xffffff80 broadcast 10.243.16.127 media: Ethernet autoselect status: active vlan: 610 parent interface: lagg0 Is it possible to set a 9K MTU on lagg0 while preserving the 1500 byte MTU on vlan0? Normally I would simply try this out, but this is actually on a vendor-supported platform and I am loathe to make changes "behind the back" of their administration interface. This system is roughly FreeBSD 7.3.

    Read the article

  • Query total page count via SNMP HP Laserjet

    - by Tim
    I was asked to get hold of the total pages counts for the 100+ printers we have at work. All of them are HP Laser or Business Jets of some description and the vast majority are connected via some form of HP JetDirect network card/switch. After many hours of typing in IP addresses and copying and pasting the relevant figure in to Excel I have now been asked to do this on a weekly basis. This led me to think there must be an easier way, as an IT professional I can surely work out some time saving method to solve this issue. Suffice it to say I do not feel very professional now after a day or so of trying to make SNMP work for me! From what I understand the first thing is to enable SNMP on the printer. Done. Next I would need something to query the SNMP bit. I decided to go open source and free and someone here recommended net-snmp as a decent tool (I would like to have just added the printers as nodes in SolarWinds but we are somewhat tight on licences apparently). Next I need the name of the MIB. For this I believe the HP-LASERJET-COMMON-MIB has the correct information in it. Downloaded this and added to net-snmp. Now I need the OID which I believe after much scouring is printed-media-simplex-count (we have no duplex printers, that we are interested in at least). Running the following command yields the following demoralising output: snmpget -v 2c -c public 10.168.5.1 HP-LASERJET-COMMON-MIB:.1.3.6.1.2.1.1.16.1.1.1 (the OID was derived from running: snmptranslate -IR -On printed-media-simplex-count Unlinked OID in HP-LASERJET-COMMON-MIB: hp ::= { enterprises 11 } Undefined identifier: enterprises near line 3 of C:/usr/share/snmp/mibs/HP-LASER JET-COMMON-MIB..txt .1.3.6.1.2.1.1.16.1.1.1 ) Unlinked OID in HP-LASERJET-COMMON-MIB: hp ::= { enterprises 11 } Undefined identifier: enterprises near line 3 of C:/usr/share/snmp/mibs/HP-LASER JET-COMMON-MIB..txt HP-LASERJET-COMMON-MIB:.1.3.6.1.2.1.1.16.1.1.1: Am I barking up the wrong tree completely with this? My aim was to script it all to output to a file for all the IP addresses of the printers and then plonk that in Excel for my lords and masters to digest at their leisure. I have a feeling I am using either the wrong MIB or the wrong OID from said MIB (or both). Does anyone have any pointers on this for me? Or should I give up and go back to navigationg each printers web page individually (hoping not).

    Read the article

  • Utility for scanning stacks of double-sided documents

    - by Peter Becich
    I have a simplex scanner with document feeder, and am looking for the best way to scan double-sided notes. It would be useful to be able to scan the same stack twice, once flipped, and have a utility automatically interleave the scanned images. Multi-page PDF export would also be nice. Is there a tool to do this? Otherwise, I'm considering writing it in Python, with the imagescanner module, if it can use the ADF -- http://pypi.python.org/pypi/imagescanner/0.9 Thanks

    Read the article

  • How to connect to a Virtualbox guest from the host when network cable unplugged

    - by Greg K
    I'd like to work offline (I'm flying to the US twice this month), to do this I need access to a linux development server. When I work from home I boot a VirtualBox VM and that acts as my dev server for the day (providing Apache, PHP & MySQL to run my server side code). However, I'd like to work with my VM when I'm not connected to a network. I have my Ubuntu VM guest set up with a bridge connection so it can serve HTTP and provide SSH access from inside my local network. I've tried to manually configure my network settings on both Mac OSX (the host) and Ubuntu (the guest) but I can't even ping my own NIC address (127.0.0.1 can, 192.168.21.x I can't) in OS X when I unplug the cable. Manual network settings: $ ifconfig en0 en0: flags=8963<UP,BROADCAST,SMART,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:xx:xx:xx:xx:xx inet 192.168.21.5 netmask 0xffffff00 broadcast 192.168.21.255 media: autoselect (100baseTX <full-duplex,flow-control>) status: active I can ping localhost fine, as well as my VM (.20) and SSH too. $ ping 192.168.21.5 PING 192.168.21.5 (192.168.21.5): 56 data bytes 64 bytes from 192.168.21.5: icmp_seq=0 ttl=64 time=0.085 ms 64 bytes from 192.168.21.5: icmp_seq=1 ttl=64 time=0.102 ms 64 bytes from 192.168.21.5: icmp_seq=2 ttl=64 time=0.100 ms 64 bytes from 192.168.21.5: icmp_seq=3 ttl=64 time=0.094 ms $ ping 192.168.21.20 PING 192.168.21.20 (192.168.21.20): 56 data bytes 64 bytes from 192.168.21.20: icmp_seq=0 ttl=64 time=0.910 ms 64 bytes from 192.168.21.20: icmp_seq=1 ttl=64 time=1.181 ms 64 bytes from 192.168.21.20: icmp_seq=2 ttl=64 time=1.159 ms 64 bytes from 192.168.21.20: icmp_seq=3 ttl=64 time=1.320 ms Network cable unplugged: $ ifconfig en0 en0: flags=8963<UP,BROADCAST,SMART,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:xx:xx:xx:xx:xx media: autoselect status: inactive $ ping 192.168.21.5 PING 192.168.21.5 (192.168.21.5): 56 data bytes ping: sendto: No route to host ping: sendto: No route to host Request timeout for icmp_seq 0 ping: sendto: No route to host Request timeout for icmp_seq 1 Does OS X disable the NIC when the network cable is unplugged? Any way to stop it doing this?

    Read the article

  • 10 Great Free Icon Packs To Theme Your Android Phone

    - by Chris Hoffman
    Android allows you to customize your home screen, adding widgets, arranging shortcuts and folders, choosing a background, and even replacing the included launcher entirely. You can install icon packs to theme your app icons, too. Third-party launchers use standard app icons by default, but they don’t have to. You can install icon packs that third-party launchers will use in place of standard app icons. How to Use Icon Packs To use icon packs, you’ll need to use a third-party launcher that supports them, such as Nova, Apex, ADW, Go Launcher, Holo Launcher, or Action Launcher Pro. Once you’re using a third-party launcher, you can install an icon pack and go into your launcher’s settings. You’ll find an option that allows you to choose between the icon packs you’ve installed. Many of these icon packs also include wallpapers, which you can set in the normal way. MIUI 5 Icons This icon pack offers over 1900 free icons that are similar to the icons used by the MIUi ROM developed by China’s Xiaomi Tech. The large list of icons is a big plus — this pack will give the majority of your app icons a very slick, consistent look. DCikonZ Theme DCikonZ is a free icon theme that includes a whopping 4000+ icons with a consistent look. This icon theme stands out not just because it’s huge, but also for offering for going in its own direction and avoiding the super-simple, flat look many icon packs use. Holo Icons Holo Icons replaces many app icons with simple, consistent-looking that match Google’s Holo style. If you’re a fan of Android’s Holo look, give it a try. It even tweaks many of the icons from Google’s own apps to make them look more consistent. Square Icon Pack Square Icon Pack turns your icons into simple squares. Even Google Chrome becomes an orb instead of a square. This makes every icon a consistent size and offers a unique look. The icons here almost look a bit like the small-size tiles available on Windows Phone and Windows 8.1. The free version doesn’t offer as many icons as the paid version, but it does offer icons for many popular apps. Rounded Want rounded icons instead? Try the Rounded icon theme, which offers simple rounded icons. The developer says they’re inspired by the consistently round icons used on Mozilla’s Firefox OS. Crumbled Icon Pack Crumbled Icon Pack applies an effect that makes icons look as if they’r crumbling. Rather than theming individual icons, Crumbled Icon Pack adds an effect to every app icon on your device. This means that all your app icons will be themed and consistent. Dainty Icon Pack Is your Android home screen too colorful? Dainty Icon Pack offers simple, gray-on-white icons for over 1200 apps. It’d be ideal over a simple background. The contrast may be a bit low here with the gray-on-white, but it’s otherwise very slick. Simplex Icons Simplex Icons offers more contrast, with black-on-gray icons. This icon pack could simplify busy home screens, allowing photographic wallpapers to come through. Min Icon Set Min attempts to go as minimal as possible, offering simple white icons for over 570 apps. It would be ideal over a simple wallpaper with app names hidden in your launcher, offering a calming, minimal home screen. For apps it doesn’t recognize, it will enclose part of the app’s icon in a white circle. Elegance Elegance goes in another direction entirely, offering icons that incorporate more details and gradients rather than going for minimalism. Its over 1200 icons offer another good option for people who aren’t into the minimal, flat look. Icon pack designers generally have to create and include their own icons to replace icons associated with specific apps, so you’ll probably find a few of your app icons aren’t replaced with most of these themes. Of course, a standard Android phone without an icon pack doesn’t have consistent icons, either. Even if all the icons in your app drawer aren’t themed, the few app icons you have on your home screen will be if you use widely used apps.     

    Read the article

  • Calculating adjacent quads on a quad sphere

    - by Caius Eugene
    I've been experimenting with generating a quad sphere. This sphere subdivides into a quadtree structure. Eventually I'm going to be applying some simplex noise to the vertices of each face to create a terrain like surface. To solve the issue of cracks I want to be able to apply a geomitmap technique of triangle fanning on the edges of each quad, but in order to know the subdivision level of the adjacent quads I need to identify which quads are adjacent to each other. Does anyone know any approaches to computing and storing these adjacent quads for quick lookup? Also It's important that I know which direction they are in so I can easily adjust the correct edge.

    Read the article

1 2  | Next Page >