LZW Data Compression. Dr. Dobbs Journal. Screenshot%20from%202014-10-21%2014:56:40.png' alt='Matlab Save .Fig File Command Line' title='Matlab Save .Fig File Command Line' />File Exchange alternatives. There are many implementations of tab panels in the Matlab File Exchange. Matlabs official Desktop Blog had an article about one. Matlab Save .Fig File Command Line' title='Matlab Save .Fig File Command Line' />October, 1. Note I have an updated article on LZW posted here. Please check out the new article and tell me what you think. I hope it improves on this post and makes LZW easier to understand. Thanks to Jan Hakenberg for correction of a couple of errors In Figure 4, the values for new table entries 2. Thanks to David Littlewood for pointing out the missing line of pseudocde in Figure 6. Thanks to Joe Snyder for pointing out a line where a macro should replace a hard coded constant. Any programmer working on mini or microcomputers in this day and age should have at least some exposure to the concept of data compression. In MS DOS world, programs like ARC, by System Enhancement Associates, and PKZIP, by PKware are ubiquitous. ARC has also been ported to quite a few other machines, running UNIX, CPM, and so on. CPM users have long had SQ and USQ to squeeze and expand programs. Unix users have the COMPRESS and COMPACT utilities. Yet the data compression techniques used in these programs typically only show up in two places file transfers over phone lines, and archival storage. Data compression has an undeserved reputation for being difficult to master, hard to implement, and tough to maintain. In fact, the techniques used in the previously mentioned programs are relatively simple, and can be implemented with standard utilities taking only a few lines of code. Matplotlib is a Pythonbased plotting library with full support for 2D and limited support for 3D graphics, widely used in the Python scientific computing community. Webopedias list of Data File Formats and File Extensions makes it easy to look through thousands of extensions and file formats to find what you need. Saving+Figures+Figures+can+be+saved+in+many+formats.+The+common+ones+are%3A+.fig+preserves+all+information..jpg' alt='Matlab Save .Fig File Command Line' title='Matlab Save .Fig File Command Line' />This article discusses a good all purpose data compression technique Lempel Ziv Welch, or LZW compression. The routines shown here belong in any programmers toolbox. For example, a program that has a few dozen help screens could easily chop 5. K bytes off by compressing the screens. Or 5. 00. K bytes of software could be distributed to end users on a single 3. K byte floppy disk. Highly redundant database files can be compressed down to 1. Once the tools are available, the applications for compression will show up on a regular basis. LZW Fundamentals. The original Lempel Ziv approach to data compression was first published in in 1. Terry Welchs refinements to the 1. The algorithm is surprisingly simple. In a nutshell, LZW compression replaces strings of characters with single codes. It does not do any analysis of the incoming text. Instead, it just adds every new string of characters it sees to a table of strings. Compression occurs when a single code is output instead of a string of characters. The code that the LZW algorithm outputs can be of any arbitrary length, but it must have more bits in it than a single character. The first 2. 56 codes when using eight bit characters are by default assigned to the standard character set. The remaining codes are assigned to strings as the algorithm proceeds. The sample program runs as shown with 1. This means codes 0 2. Compression. The LZW compression algorithm in its simplest form is shown in Figure 1. A quick examination of the algorithm shows that LZW is always trying to output codes for strings that are already known. And each time a new code is output, a new string is added to the string table. Routine LZWCOMPRESSCODE STRING get input character. WHILE there are still input characters DO    CHARACTER get input character    IF STRINGCHARACTER is in the string table then        STRING STRINGcharacter    ELSE        output the code for STRING        add STRINGCHARACTER to the string table        STRING CHARACTER    END of IFEND of WHILEoutput the code for STRING The Compression Algorithm. Figure 1. A sample string used to demonstrate the algorithm is shown in Figure 2. The input string is a short list of English words separated by the character. Stepping through the start of the algorithm for this string, you can see that the first pass through the loop, a check is performed to see if the string W is in the table. Since it isnt, the code for is output, and the string W is added to the table. Since we have 2. 56 characters already defined for codes 0 2. After the third letter, E, has been read in, the second string code, WE is added to the table, and the code for letter W is output. This continues until in the second word, the characters and W are read in, matching string number 2. In this case, the code 2. The process continues until the string is exhausted and all of the codes have been output. Input String WEDWEWEEWEBWETCharacter Input. Code Output. New code value. New StringW2. 56WEW2. WEDE2. 58. EDD2. DWE2. WEE2. EWEE2. 60. 26. WEEW2. EWEB2. 57. WEBB2. BWET2. 60. WETEOFTThe Compression Process. Figure 2. The sample output for the string is shown in Figure 2 along with the resulting string table. As can be seen, the string table fills up rapidly, since a new string is added to the table each time a code is output. In this highly redundant input, 5 code substitutions were output, along with 7 characters. If we were using 9 bit codes for output, the 1. Of course, this example was carefully chosen to demonstrate code substitution. In real world examples, compression usually doesnt begin until a sizable table has been built, usually after at least one hundred or so bytes have been read in. Decompression. The companion algorithm for compression is the decompression algorithm. It needs to be able to take the stream of codes output from the compression algorithm, and use them to exactly recreate the input stream. One reason for the efficiency of the LZW algorithm is that it does not need to pass the string table to the decompression code. The table can be built exactly as it was during compression, using the input stream as data. This is possible because the compression algorithm always outputs the STRING and CHARACTER components of a code before it uses it in the output stream. Free Program The Smurfs 2 Games Pc here. This means that the compressed data is not burdened with carrying a large string translation table. Routine LZWDECOMPRESSCODE Read OLDCODEoutput OLDCODEWHILE there are still input characters DO    Read NEWCODE    STRING get translation of NEWCODE    output STRING    CHARACTER first character in STRING    add OLDCODE CHARACTER to the translation table    OLDCODE NEWCODEEND of WHILE The Decompression Algorithm. Figure 3. The algorithm is shown in Figure 3. Just like the compression algorithm, it adds a new string to the string table each time it reads in a new code. All it needs to do in addition to that is translate each incoming code into a string and send it to the output. Figure 4 shows the output of the algorithm given the input created by the compression earlier in the article. The important thing to note is that the string table ends up looking exactly like the table built up during compression. The output string is identical to the input string from the compression algorithm. Note that the first 2. Input Codes W E D 2. E 2. 60 2. 61 2. 57 B 2. TInputNEWCODEOLDCODESTRINGOutput. CHARACTERNew table entryWWW2. WEWEE2. 57 WEDEDD2. ED2. 56. DW2. 59 DE2. EE2. 60 WE2. 60. EWE2. E2. EE2. 62 WEE2. WEW2. 63 EWB2. BB2. WEB2. 60. BWE2. 65 BT2. TT2. 66 WETThe Decompression Process. Figure 4. The Catch. Unfortunately, the nice simple decompression algorithm shown in Figure 4 is just a little too simple. There is a single exception case in the LZW compression algorithm that causes some trouble to the decompression side. Figure toolbar components Undocumented Matlab. Toolbars are by now a staple of modern GUI design. An unobtrusive list of small icons enables easy access to multiple application actions without requiring large space for textual descriptions. Unfortunately, the built in documented support for the Matlab toolbars is limited to adding icon buttons via the uipushtool and uitoggletool functions, and new toolbars containing them via the uitoolbar function. In this post I will introduce several additional customizations that rely on undocumented features. This article will only describe figure toolbars. However, much of the discussion is also relevant to the desktop Command Window toolbars and interested users can adapt it accordingly. Accessing toolbar buttons undoredo. Lets start by adding undoredo buttons to the existing figure toolbar. I am unclear why such an elementary feature was not included in the default figure toolbar, but this is a fact that can easily be remedied. In another post I describe uiundo, Matlabs semi documented support for undoredo functionality, but for the present lets assume we already have this functionality set up. First, lets prepare our icons, which are basically a green filled triangle icon and its mirror image Load the Redo icon. Convert white pixels into a transparent background. Na. N. Convert into 3. D RGB space. cdata. Redo ind. 2rgbcdata,map. Undo cdata. Redo ,1. Now lets add these icons to the default figure toolbar Add the icon and its mirror image undo to the latest toolbar. Undo uipushtoolcdata,cdata. Undo, tooltip,undo, Clicked. Callback,uiundogcbf,exec. Undo. h. Redo uipushtoolcdata,cdata. Redo, tooltip,redo, Clicked. Callback,uiundogcbf,exec. Redo Undoredo buttons. In the preceding screenshot, since no figure toolbar was previously shown, uipushtool added the undo and redo buttons to a new toolbar. Had the figure toolbar been visible, then the buttons would have been added to its right end. Since undoredo buttons are normally requested near the left end of toolbars, we need to rearrange the toolbar buttons h. Bryan Adam Please Forgive Me Mp3 Free Download. Toolbar findallh. Fig,tag,Figure. Tool. Bar. h. Toolbar geth. Undo,Parent an alternative. Buttons findallh. Toolbar. seth. Toolbar,children,h. Buttons4 end 4,2,3,end 3 end. Undo,Separator,on Undoredo buttons in their expected positions. We would normally preserve h. Undo and h. Redo, and modify their Tooltip and VisibleEnable properties in run time, based on the availability and name of the latest undoredo actions Retrieve redoundo object. Obj getappdatah. Fig,uitoolsFigure. Tool. Manager. ifisemptyundo. Obj. undo. Obj uitools. Figure. Tool. Managerh. Fig. setappdatah. Fig,uitoolsFigure. Tool. Manager,undo. Obj. Customize the toolbar buttons. Undo. Action undo. Obj. Command. Manager. Undo. Actionseth. Undo, Tooltip, Enable,off. Str undo latest. Undo. Action. Name. Undo, Tooltip,tooltip. Str, Enable,on. We can easily adapt the method I have just shown to modifyupdate existing toolbar icons hidingdisabling them etc. Adding non button toolbar components undo dropdown. A more advanced customization is required if we wish to present the undoredo actions in a drop down combo box. Unfortunately, since Matlab only enables adding uipushtools and uitoggletools to toolbars, we need to use a Java component. The drawback of using such a component is that it is inaccessible via the toolbars Children property implementation of the drop down callback function is left as an exercise to the reader Add undo dropdown list to the toolbar. Toolbar getgeth. Toolbar,Java. Container,Component. Peer. if isemptyj. Toolbar. undo. Actions getundo. Obj. Command. Manager. Undo. Stack,Name. Combo javax. swing. JCombo. Boxundo. Actionsend 1 1. Combo, Action. Performed. Callback, my. Undo. Callback. Fcn. j. Toolbar1. addj. Combo,5 5th position, after printer icon. Toolbar1. repaint. Toolbar1. revalidate. Drop down combo box callback functionfunction my. Undo. Callback. Fcnh. Combo,h. Event. item. Index geth. Combo,Selected. Index 0topmost item. Name geth. Combo,Selected. Item. user processing needs to be placed hereend. Undo dropdown list. Note that the javax. JCombo. Box constructor accepts a cell array of strings undo. Actions in the snippet above. A user defined dropdownlist might be constructed as follows also see a related CSSM thread. Strings here, there, everywhere. Combo javax. swing. JCombo. Boxdropdown. Strings. setj. Combo, Action. Performed. Callback, my. Undo. Callback. Fcn. Toolbar1. add. Separator. Toolbar1. addj. Combo at end, following a separator mark. Toolbar1. repaint. Toolbar1. revalidate. A similar approach can be used to add checkboxes, radio buttons and other non button controls. In next weeks post I will describe how the toolbar can be customized using undocumented functionality to achieve a non default background, a floating toolbar palette effect and other interesting customizations. If you have any specific toolbar related request, Ill be happy to hear in the comments section below.