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  • iPhone OS: Strategies for high density image work

    - by Jasconius
    I have a project that is coming around the bend this summer that is going to involve, potentially, an extremely high volume of image data for display. We are talking hundreds of 640x480-ish images in a given application session (scaled to a smaller resolution when displayed), and handfuls of very large (1280x1024 or higher) images at a time. I've already done some preliminary work and I've found that the typical 640x480ish image is just a shade under 1MB in memory when placed into a UIImageView and displayed... but the very large images can be a whopping 5+ MB's in some cases. This project is actually be targeted at the iPad, which, in my Instruments tests seems to cap out at about 80-100MB's of addressable physical memory. Details aside, I need to start thinking of how to move huge volumes of image data between virtual and physical memory while preserving the fluidity and responsiveness of the application, which will be high visibility. I'm probably on the higher ends of intermediate at Objective-C... so I am looking for some solid articles and advice on the following: 1) Responsible management of UIImage and UIImageView in the name of conserving physical RAM 2) Merits of using CGImage over UIImage, particularly for the huge images, and if there will be any performance gain 3) Anything dealing with memory paging particularly as it pertains to images I will epilogue by saying that the numbers I have above maybe off by about 10 or 15%. Images may or may not end up being bundled into the actual app itself as opposed to being loaded in from an external server.

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  • Estimate gaussian (mixture) density from a set of weighted samples

    - by Christian
    Assume I have a set of weighted samples, where each samples has a corresponding weight between 0 and 1. I'd like to estimate the parameters of a gaussian mixture distribution that is biased towards the samples with higher weight. In the usual non-weighted case gaussian mixture estimation is done via the EM algorithm. Does anyone know an implementation (any language is ok) that permits passing weights? If not, does anyone know how to modify the algorithm to account for the weights? If not, can some one give me a hint on how to incorporate the weights in the initial formula of the maximum-log-likelihood formulation of the problem? Thanks!

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  • Android Screen Density Compatibility on 1.5

    - by fordays
    Hi, I'm getting ready to release my first application the marketplace. It's being written for devices running Android 1.5 and above, however there aren't any specific folders for the three different screen densities (I think those came around in 1.6). Should I make these folders myself? Where should I put image resources for the different densities and what should I put in my Manifest??

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  • Article about code density as a measure of programming language power

    - by prosseek
    I remember reading an article saying something like "The number of bugs introduced doesn't vary much with different programming languages, but it depends pretty much on SLOC (source lines of code). So, using the programming language that can implement the same functions with smaller SLOC is preferable in terms of stability." The author wanted to stress the advantages of using Functional Programming, as normally one can program with a smaller number of LOC. I remember the author cited a research paper about the irrelevance of choice of programming language and the number of bugs. Is there anyone who knows the research paper or the article?

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  • How to obtain multiple lines in a single density plot, with a corrected scale?

    - by user1677055
    I have recently started working with microarray datasets and am trying to get my hands on R. I wish to make some plots out of my result data, but however I am stuck at the following. I have the following data (myData), cpg samp1 samp2 samp3 cpg1 0.43 0.32 0.21 cpg2 0.43 0.22 1.00 cpg3 0.11 0.99 0.78 cpg4 0.65 0.32 0.12 cpg5 0.11 0.43 0.89 And I wish to obtain a density plot for this, I did the following, plot (density(MyData$samp1), col="red") lines (density(MyData$samp2), col="green") lines (density(MyData$samp3), col="blue") But doing this does not give me correct plots, because not all sample curves fit within the plot limits. I did try looking for answers, but honestly i am still not able to work this out. Can you help me know how do i set my scale for the above? Or what additional should I do to the above code, so that all the curves are in range?? I have got many samples, so i need a something that could also automatically assign a different colour curve for each of my sample, after scaling it right. Thanks in advance..

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  • GNUPLOT: 2d histogram from set of points.

    - by Arman
    Hello, I have a pairs of the points with their weights: #x y w 0.111342 0.478917 0.232487 0.398107 1.79559 0.221714 0.200731 2.58651 0.0776068 0.0967412 1.49904 0.0645355 6.17638 8.63101 0.715604 0.306128 3.10917 0.0984595 0.340707 3.19344 0.10669 7.18627 8.59859 0.835751 8.56 9.63894 0.888065 5.14272 6.86074 0.749587 0.747202 3.812 0.196013 8.71891 10.1355 0.860232 0.346714 1.45895 0.237647 5.21932 8.84491 0.590094 9.42138 12.2082 0.771725 0.215627 2.42317 0.0889856 How to plot nice 2d histogram image with color bar? I found nice density map description but I don't wont to go via python. I there way to use only gnuplot scripting? Kind Regards Arman.

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  • How to generate a number in arbitrary range using random()={0..1} preserving uniformness and density?

    - by psihodelia
    Generate a random number in range [x..y] where x and y are any arbitrary floating point numbers. Use function random(), which returns a random floating point number in range [0..1] from P uniformly distributed numbers (call it "density"). Uniform distribution must be preserved and P must be scaled as well. I think, there is no easy solution for such problem. To simplify it a bit, I ask you how to generate a number in interval [-0.5 .. 0.5], then in [0 .. 2], then in [-2 .. 0], preserving uniformness and density? Thus, for [0 .. 2] it must generate a random number from P*2 uniformly distributed numbers. The obvious simple solution random() * (x - y) + y will generate not all possible numbers because of the lower density for all abs(x-y)>1.0 cases. Many possible values will be missed. Remember, that random() returns only a number from P possible numbers. Then, if you multiply such number by Q, it will give you only one of P possible values, scaled by Q, but you have to scale density P by Q as well.

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  • Load image in device independent and screen independent fashion into a layout view using 1.6 SDK

    - by Mark Wigzell
    I'm having trouble getting an asset image to scale up when I load it. The new call to BitmapDrawable(Resources, BitmapDrawable) is not available on 1.6 SDK. Is there a workaround to load the BitmapDrawable the old way and then somehow manipulate it? I have tried calling setTargetDensity() to no avail. My code (which doesn't scale properly) is: ImageView iv = (ImageView)view.findViewById(R.id.image); iv.setImageDrawable(new BitmapDrawable(view.getContext().getAssets().open(path)));

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  • Matlab - binary vector with high concentration of 1s (or 0s)

    - by JohnIdol
    What's the best way to generate a number X of random binary vectors of size N with concentration of 1s (or, simmetrically, of 0s) that spans from very low to very high? Using randint or unidrnd (as in this question) will generate binary vectors with uniform distributions, which is not what I need in this case. Any help appreciated!

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  • What is the peak theoretical WiFi G user density? [closed]

    - by Bigbio2002
    I've seen a few WiFi capacity planning questions, and this one is related, but hopefully different enough not to be closed. Also, this is related specifically to 802.11g, but a similar question could be made for N. In order to squeeze more WiFi users into a space, the transmit power on the APs need to be reduced and the APs squeezed closer together. My question is, how far can you practically take this before the network becomes unusable? There will come a point where the transmit power is so weak that nobody will actually be able to pick up a connection, or be constantly roaming to/from APs spaced a few feet apart as they walk around. There are also only 3 available channels to use as well, which is a factor to consider. After determining the peak AP density, then multiply by users-per-AP, which should be easier to find out. After factoring all of this in and running some back-of-the-envelope calculations, I'd like to be able to get a figure of "XX users per 10ft^2" or something. This can be considered the physical limit of WiFi, and will keep people from asking about getting 3,000 people in a ballroom conference on WiFi. Can anyone with WiFi experience chime in, or better yet, provide some calculations for a more accurate figure? Assumptions: Let's assume an ideal environment with no reflection (think of a big, square, open room, with the APs spaced out on a plane), APs are placed on the ceiling so humans won't absorb the waves, and the only interference are from the APs themselves and the devices. As for what devices specifically, that's irrelevant for the first point of the question (AP density, so only channel and transmit power should matter). User experience: Wikipedia states that Wireless G has about 22Mbps maximum effective throughput, or about 2.75MB/s. For the purpose of this question, anything below 100KB/s per user can be deemed to be a poor user experience. As for roaming, I'll assume the user is standing in the same place, so hopefully that will be a non-issue.

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  • Pseudorandom Number Generation with Specific Non-Uniform Distributions

    - by carnun
    Hello all, I'm writing a program that simulates various random walks (with differing distributions). At each timestep, I need randomly generated, two dimensional step distances and angles from the distribution of the random walk. I'm hoping someone can check my understanding of how to generate these random numbers. As I understand it I can use Inverse Transform Sampling as follows: If f(x) is the pdf of our random walk that has a non-uniform distribution, and y is a random number from a uniform distribution. Then if we let f(x) = y and solve to find x then we have a random number from the non-uniform distribution. Is this a feasible solution?

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  • Keyword Density - How Much is Too Much For SEO?

    A long time ago the easiest way to reach high rankings in many search engines at that time was to stuff pages with target keywords. Some tried to hide some part of the page by using background color also for text, while others simply put few paragraphs with apparently irrelevant keywords at the end of the page. Because word frequency was one of the most important factors to rank pages, it was pretty easy to reach top positions just by exaggerating with keywords.

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  • Python - calculate multinomial probability density functions on large dataset?

    - by Seafoid
    Hi, I originally intended to use MATLAB to tackle this problem but the inbuilt functions has limitations that do not suit my goal. The same limitation occurs in NumPy. I have two tab-delimited files. The first is a file showing amino acid residue, frequency and count for an in-house database of protein structures, i.e. A 0.25 1 S 0.25 1 T 0.25 1 P 0.25 1 The second file consists of quadruplets of amino acids and the number of times they occur, i.e. ASTP 1 Note, there are 8,000 such quadruplets. Based on the background frequency of occurence of each amino acid and the count of quadruplets, I aim to calculate the multinomial probability density function for each quadruplet and subsequently use it as the expected value in a maximum likelihood calculation. The multinomial distribution is as follows: f(x|n, p) = n!/(x1!*x2!*...*xk!)*((p1^x1)*(p2^x2)*...*(pk^xk)) where x is the number of each of k outcomes in n trials with fixed probabilities p. n is 4 four in all cases in my calculation. I have created three functions to calculate this distribution. # functions for multinomial distribution def expected_quadruplets(x, y): expected = x*y return expected # calculates the probabilities of occurence raised to the number of occurrences def prod_prob(p1, a, p2, b, p3, c, p4, d): prob_prod = (pow(p1, a))*(pow(p2, b))*(pow(p3, c))*(pow(p4, d)) return prob_prod # factorial() and multinomial_coefficient() work in tandem to calculate C, the multinomial coefficient def factorial(n): if n <= 1: return 1 return n*factorial(n-1) def multinomial_coefficient(a, b, c, d): n = 24.0 multi_coeff = (n/(factorial(a) * factorial(b) * factorial(c) * factorial(d))) return multi_coeff The problem is how best to structure the data in order to tackle the calculation most efficiently, in a manner that I can read (you guys write some cryptic code :-)) and that will not create an overflow or runtime error. To data my data is represented as nested lists. amino_acids = [['A', '0.25', '1'], ['S', '0.25', '1'], ['T', '0.25', '1'], ['P', '0.25', '1']] quadruplets = [['ASTP', '1']] I initially intended calling these functions within a nested for loop but this resulted in runtime errors or overfloe errors. I know that I can reset the recursion limit but I would rather do this more elegantly. I had the following: for i in quadruplets: quad = i[0].split(' ') for j in amino_acids: for k in quadruplets: for v in k: if j[0] == v: multinomial_coefficient(int(j[2]), int(j[2]), int(j[2]), int(j[2])) I haven'te really gotten to how to incorporate the other functions yet. I think that my current nested list arrangement is sub optimal. I wish to compare the each letter within the string 'ASTP' with the first component of each sub list in amino_acids. Where a match exists, I wish to pass the appropriate numeric values to the functions using indices. Is their a better way? Can I append the appropriate numbers for each amino acid and quadruplet to a temporary data structure within a loop, pass this to the functions and clear it for the next iteration? Thanks, S :-)

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  • Is it possible to plot a single density over a discrete variable?

    - by mattrepl
    The x-axis is time broken up into time intervals. There is an interval column in the data frame that specifies the time for each row. Plotting a histogram or line using geom_histogram and geom_freqpoly works great, but I'd like to use geom_density to get a filled area. Perhaps there is a better way to achieve this. Right now, if I use geom_density, curves are created for each discrete factor level instead of smoothing over all of them.

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  • Easiest way to convert json data into objects with methods attached?

    - by John Mee
    What's the quickest and easiest way to convert my json, containing the data of the objects, into actual objects with methods attached? By way of example, I get data for a fruitbowl with an array of fruit objects which in turn contain an array of seeds thus: {"fruitbowl": [{ "name": "apple", "color": "red", "seeds": [] },{ "name": "orange", "color": "orange", "seeds": [ {"size":"small","density":"hard"}, {"size":"small","density":"soft"} ]} } That's all nice and good but down on the client we do stuff with this fruit, like eat it and plant trees... var fruitbowl = [] function Fruit(name, color, seeds){ this.name = name this.color = color this.seeds = seeds this.eat = function(){ // munch munch } } function Seed(size, density){ this.size = size this.density = density this.plant = function(){ // grow grow } } My ajax's success routine currently is currently looping over the thing and constructing each object in turn and it doesn't handle the seeds yet, because before I go looping over seed constructors I'm thinking Is there not a better way? success: function(data){ fruitbowl.length = 0 $.each(data.fruitbowl, function(i, f){ fruitbowl.push(new Fruit(f.name, f.color, f.seeds)) }) I haven't explored looping over the objects as they are and attaching all the methods. Would that work?

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  • How can I get the correct DisplayMetrics from an AppWidget in Android?

    - by Gary
    I need to determine the screen density at runtime in an Android AppWidget. I've set up an HDPI emulator device (avd). If set up a regular executable project, and insert this code into the onCreate method: DisplayMetrics dm = getResources().getDisplayMetrics(); Log.d("MyTag", "screen density " + dm.densityDpi); This outputs "screen density 240" as expected. However, if I set up an AppWidget project, and insert this code into the onUpdate method: DisplayMetrics dm = context.getResources().getDisplayMetrics(); Log.d("MyTag", "screen density " + dm.densityDpi); This outputs "screen density 160". I noticed, hooking up the debugger, that the mDefaultDisplay member of the Resources object here is null in the AppWidget case. Similarly, if I get a resource at runtime using the Resources object obtained from context.getResources() in the AppWidget, it returns the wrong resource based on screen density. For instance, I have a 60x60px drawable for mdpi, and an 80x80 drawable for hdpi. If I get this Drawable object using context.getResources().getDrawable(...), it returns the 60x60 version. Is there any way to correctly deal with resources at runtime from the context of an AppWidget? Thanks!

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  • Pixels - A cry for some insight

    - by CarrotFile
    I'm pretty new to web developing and I'd love some clarification. Although reading more than one book on the topic, I cannot seem to wrap my head around the pixel concept. I encounter problems with this issue when trying to use CSS and pixel units for design that fits different screen sizes. To my understanding a pixel is the most basic unit used by a monitor in order to compose an image on the screen. So if me resolution is 800 by 600, everything on my screen is rendered using those 800*600 basic building blocks. If I were to enlarge my screen resolution, 3 things would accrue: A. The basic image building block(the pixel) would shrink in size B. The pixels would move close together C. Well, more pixels would now be available All these combined lead to a sharper(depending on the viewing distance) and more detail enabling image. Well so far so good. Here is were I start getting lost: To my knowledge a pixel is not a physical, real object. Monitors are not embedded with a few thousand pixels. I am drawn to this conclusion because anyone can change his screen's resolution, making a pixel on his screen bigger or smaller, and adding or subtracting the amount of total pixels on screen. Adding to that, I have herd that different monitors have different pixel densities. For example Apple's retina monitors. Taking all of the above as my knowledge base, These are my questions: If a pixel has no real world constant size, what does comparing different pixel densities matter? Each screen company can define it's own pixel concept and declare the higher density. What does a bigger pixel density mean? Say we take two screens with the same physical dimensions, but with a different pixel density, am I to assert that the main difference would be the larger density screen being able to display a higher max resolution? Or am I to assert that given the same resolution on both monitors, the higher density one would display a sharper, smaller image? If a pixel is not a fixed size within one monitor, is it a fixed size between the same resolution on two different monitors? For example, would two different monitors, set to the same resolution, be comprised of same size, same quantity pixels? I'd love some help (:

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  • How to generate a round-numbers graph in Excel?

    - by tcheregati
    folks! Now, I have an Excel file with measurements I made of some color patches (I work at a Press company), with a device called spectrophotometer. Here it is: https://docs.google.com/open?id=0B0i8fdSf2ihzRlFYNWd4anItenM Density and Hue are two characteristics of each color patch. The thing is: I'm looking at a non-linear increase between the 25 Color Density measurements I took, but I NEED to know exactly how the color's Hue changes as the color's Density increases. For that, I needed Excel to give me round numbers for the X axis (for example 0,70 to 1,50 in 0,05 increments). And for that, obviously, I needed Excel to calculate the probable Hue Values corresponding to those ghost/round/not-given values of Density (like a kind of advanced rule of three). So, can anyone help me on that? Thanks a lot!

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  • Resolution Independence in libGDX

    - by ashes999
    How do I make my libGDX game resolution/density independent? Is there a way to specify image sizes as "absolute" regardless of the underlying density? I'm making a very simple kids game; just a bunch of sprites displayed on-screen, and some text for menus (options menu primarily). What I want to know is: how do I make my sprites/fonts resolution independent? (I have wrapped them in my own classes to make things easier.) Since it's a simple kids game, I don't need to worry about the "playable area" of the game; I want to use as much of the screen space as possible. What I'm doing right now, which seems super incorrect, is to simply create images suitable for large resolutions, and then scale down (or rarely, up) to fit the screen size. This seems to work okay (in the desktop version), even with linear mapping on my textures, but the smaller resolutions look ugly. Also, this seems to fly in the face of Android's "device independent pixels" (DPs). Or maybe I'm missing something and libGDX already takes care of this somehow? What's the best way to tackle this? I found this link; is this a good way of solving the problem?: http://www.dandeliongamestudio.com/2011/09/12/android-fragmentation-density-independent-pixel-dip/ It mentions how to control the images, but it doesn't mention how to specify font/image sizes regardless of density.

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  • SQL Server - Rebuilding Indexes

    - by Renso
    Goal: Rebuild indexes in SQL server. This can be done one at a time or with the example script below to rebuild all index for a specified table or for all tables in a given database. Why? The data in indexes gets fragmented over time. That means that as the index grows, the newly added rows to the index are physically stored in other sections of the allocated database storage space. Kind of like when you load your Christmas shopping into the trunk of your car and it is full you continue to load some on the back seat, in the same way some storage buffer is created for your index but once that runs out the data is then stored in other storage space and your data in your index is no longer stored in contiguous physical pages. To access the index the database manager has to "string together" disparate fragments to create the full-index and create one contiguous set of pages for that index. Defragmentation fixes that. What does the fragmentation affect?Depending of course on how large the table is and how fragmented the data is, can cause SQL Server to perform unnecessary data reads, slowing down SQL Server’s performance.Which index to rebuild?As a rule consider that when reorganize a table's clustered index, all other non-clustered indexes on that same table will automatically be rebuilt. A table can only have one clustered index.How to rebuild all the index for one table:The DBCC DBREINDEX command will not automatically rebuild all of the indexes on a given table in a databaseHow to rebuild all indexes for all tables in a given database:USE [myDB]    -- enter your database name hereDECLARE @tableName varchar(255)DECLARE TableCursor CURSOR FORSELECT table_name FROM information_schema.tablesWHERE table_type = 'base table'OPEN TableCursorFETCH NEXT FROM TableCursor INTO @tableNameWHILE @@FETCH_STATUS = 0BEGINDBCC DBREINDEX(@tableName,' ',90)     --a fill factor of 90%FETCH NEXT FROM TableCursor INTO @tableNameENDCLOSE TableCursorDEALLOCATE TableCursorWhat does this script do?Reindexes all indexes in all tables of the given database. Each index is filled with a fill factor of 90%. While the command DBCC DBREINDEX runs and rebuilds the indexes, that the table becomes unavailable for use by your users temporarily until the rebuild has completed, so don't do this during production  hours as it will create a shared lock on the tables, although it will allow for read-only uncommitted data reads; i.e.e SELECT.What is the fill factor?Is the percentage of space on each index page for storing data when the index is created or rebuilt. It replaces the fill factor when the index was created, becoming the new default for the index and for any other nonclustered indexes rebuilt because a clustered index is rebuilt. When fillfactor is 0, DBCC DBREINDEX uses the fill factor value last specified for the index. This value is stored in the sys.indexes catalog view. If fillfactor is specified, table_name and index_name must be specified. If fillfactor is not specified, the default fill factor, 100, is used.How do I determine the level of fragmentation?Run the DBCC SHOWCONTIG command. However this requires you to specify the ID of both the table and index being. To make it a lot easier by only requiring you to specify the table name and/or index you can run this script:DECLARE@ID int,@IndexID int,@IndexName varchar(128)--Specify the table and index namesSELECT @IndexName = ‘index_name’    --name of the indexSET @ID = OBJECT_ID(‘table_name’)  -- name of the tableSELECT @IndexID = IndIDFROM sysindexesWHERE id = @ID AND name = @IndexName--Show the level of fragmentationDBCC SHOWCONTIG (@id, @IndexID)Here is an example:DBCC SHOWCONTIG scanning 'Tickets' table...Table: 'Tickets' (1829581556); index ID: 1, database ID: 13TABLE level scan performed.- Pages Scanned................................: 915- Extents Scanned..............................: 119- Extent Switches..............................: 281- Avg. Pages per Extent........................: 7.7- Scan Density [Best Count:Actual Count].......: 40.78% [115:282]- Logical Scan Fragmentation ..................: 16.28%- Extent Scan Fragmentation ...................: 99.16%- Avg. Bytes Free per Page.....................: 2457.0- Avg. Page Density (full).....................: 69.64%DBCC execution completed. If DBCC printed error messages, contact your system administrator.What's important here?The Scan Density; Ideally it should be 100%. As time goes by it drops as fragmentation occurs. When the level drops below 75%, you should consider re-indexing.Here are the results of the same table and clustered index after running the script:DBCC SHOWCONTIG scanning 'Tickets' table...Table: 'Tickets' (1829581556); index ID: 1, database ID: 13TABLE level scan performed.- Pages Scanned................................: 692- Extents Scanned..............................: 87- Extent Switches..............................: 86- Avg. Pages per Extent........................: 8.0- Scan Density [Best Count:Actual Count].......: 100.00% [87:87]- Logical Scan Fragmentation ..................: 0.00%- Extent Scan Fragmentation ...................: 22.99%- Avg. Bytes Free per Page.....................: 639.8- Avg. Page Density (full).....................: 92.10%DBCC execution completed. If DBCC printed error messages, contact your system administrator.What's different?The Scan Density has increased from 40.78% to 100%; no fragmentation on the clustered index. Note that since we rebuilt the clustered index, all other index were also rebuilt.

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  • How to include different resolution icons with Android App?

    - by Gerry
    The Android docs indicate that I should ship with different icons for different resolution phone screens. http://developer.android.com/guide/practices/screens_support.html#qualifiers res/drawable-ldpi/my_icon.png // icon image for low density res/drawable-mdpi/dpi/my_icon.png // icon for medium density res/drawable-hdpi/my_icon.png // icon image for high density This does not work when compiling with Eclipse for the Android. Does anyone has an example of a manifest file that works for multiple resolution icons? Thanks, Gerry

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