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E4A Version 4.5 is released.

The good news: :)These new features:

  • _Eigen_WriteMatrix_ToTextFile, with five predefined formats (default: csv) and optional user-defined precision.
  • bitmask versions of cellwise functions _Eigen_CwiseBinaryMasked, _Eigen_CwiseScalarMasked, and _Eigen_CwiseUnaryMasked, with new test script (#28).
  • a fifth cellwise logical operation "Flip," which replaces all non-zero values within scope with zero and all zero values within scope with unity
  • a major extension of _Eigen_LDA, now also supporting Bayesian linear and quadratic discriminant analysis
  •  Eigen includes for dlls upgraded to stable release version 3.3.5.

Additional details can be found in the Changelog, as usual.

The bad news: :( Due to compiler limitations (compilation time has mushroomed to take over fifty hours(!) per platform), the dll source has had to be completely re-organised and repartitioned, causing the final output to more or less double in size. I've unsuccessfully tried various alternative compilers and different settings, but those that download this latest version will have to live with this for now.

Furthermore, this will probably be the last release for this year, as my summer break is ending soon.:'( Nevertheless I'll do my best to keep this environment evolving when and where I can...

Edited by RTFC
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The Eigen C++ template library is a great environment for matrix computing; it is fast, reliable, extensive, and well-documented. It is also completely free, and does not rely on any external dependen

E4A version 4.4 has arrived. The name of the game this time is bitmask support (see _Eigen_ConditMask*, now fully functional), notably: a new family of CwiseLogicalOp functions with which t

E4A version 5,2 is available for download: the "2020 Hindsight" release. This is a maintenance upgrade, fixing many small issues (and the odd catastrophic bug ), filling some consistency gaps in

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E4A version 4.6 is released.

This is a minor update,:mellow: due to Eigen development over the past year seemingly being stagnant.

Various E4A Cwise functions have had Block/Diag variants added where missing, there's a new Show_Matrix function that writes matrix contents to console, and all external (open-source) template libraries have been updated to their latest stable release. The core library now contains 596 functions.

Edited by RTFC
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E4A Version 4.7 (the "Lockdown Release") is out. Get it now before stock runs out!:D

This is a major update, thanks to having to spend way too much time in pandemic lockdown. The library now features over six hundred Eigen functions, over sixteen hundred alias wrappers, and well over two and a half thousand dll functions. This update beefs up integer functions in particular, notably in the context of bitmasks. So for once, no abstruse advanced mathematics.

Some highlights:

  • compiler, platform toolkit, and Windows SDK upgraded (long overdue:>); as a result, the dlls are no longer suffering from elephantiasis
  • complete overhaul of CwiseLogicalOp functions, with new operators "nor" and "xcl" ("exclude"), and redundant operator "flip" removed (See the shiny truth tables below);  also a new flag (see _Eigen_SetLogicalBit0only) to control whether these ops affect all (32) bits or just bit 0. I've also created an example script to illustrate how, in combination with bitmask functions (see _Eigen_ConditMask and variants, which now all have _InPlace counterparts as well), these can be leveraged to approach computationally hard, but mathematically simple problems. Output matrix dimensions have also been standardised where possible between all Cwise*Op and ConditMask functions.
  • more vector support, including _Eigen_CreateCol/RowVector, _Eigen_IsVector, and _Eigen_CreateVector_FromAcell_Mask, which collects from an input matrix only those cell values that are masked in a separate bitmask matrix. In combination with _Eigen_FindAll (producing offset, row, and column of a targeted value) applied to the bitmask (so target value = 1), all relevant data satisfying a (simple or compound) bitmask condition can now be collected for further processing;
  • most MatrixSpecs_Single functions (in section: Matrix Reduction) can now be accessed more easily through their own dedicated function; for example, _Eigen_IsZero, _EigenIsOnes, and _Eigen_GetSum have already proven to be timesavers that also make the code more easily understandable; the same goes for new functions that specifically retrieve the minimum/maximum value or their row/col.
  • many matrix creation functions that use an existing matrix as input and result in a changed dimension now return that new size in macro @extended; likewise _Eigen_FindAll and _Eigen_Sort_Unique now return the number of results found in @extended.
  • many corrections and clarifications in the online/chm Help pages.

For full details, please consult the download page.

truthtables_30pct.png.d2fe7977bc4abeb2599519cf45a7e920.png

Edited by RTFC
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After almost six years, celebrating one thousand downloads of E4A today!

:guitar::cheer::cheer::cheer::guitar:

:cheer::dance::frantics::dance::cheer:

:guitar::cheer::cheer::cheer::guitar:

Edited by RTFC
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E4A version 4.8 is released, dedicated to @argumentum for digging into the @scriptlinenumber macro. As a result, all user-exposed E4A functions now return the main script's line number when an E4A error is triggered, when running uncompiled scripts. Other features:

  • matrix Reduction functions substantially expanded
  • new functions for reversing the order of all rows or all cols (content inside each row/col remains untouched)
  • sorting all rows or all cols based upon the content of a single col c.q. row

Again, the focus has been on strengthening basic matrix management and specs retrieval, rather than fancy maths. An application example is forthcoming soon published in my BitmaskSudokuSolver thread (v1.1)

Edited by RTFC
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E4A version 5,2 is available for download: the "2020 Hindsight" release.

This is a maintenance upgrade, fixing many small issues (and the odd catastrophic bug o:)), filling some consistency gaps in the function library, streamlining the environment functions, and updating Eigen's source to stable release 3.3.9. Full details can be found in the ChangeLog as per usual. Hope it helps!

EDIT: as every mission has at least one glitch,:doh: it's no surprise that the updated MatrixFileConverter.au3 script did not get copied to the bundle subdir before packing it into the setup. So since it's tiny, I'm providing it separately here:

 

EDIT2: as every mission apparently has at least two glitches,:blink: I Just discovered a potential issue in _Eigen_StartUp when calling _Eigen_DefineWorkspace repeatedly in x64-mode (luckily this is not a common scenario). See spoiler for a quick patch.

Spoiler

In _Eigen_StartUp: change this:

; in case of repeat calls
    If $releaseAll = True Then
        _Eigen_Cleanup()
        If @AutoItX64 Then _HighMem_ReleaseAll()
    EndIf
    If $EIGEN_DENSE_DLLHANDLE > 0 Then DllClose($EIGEN_DENSE_DLLHANDLE)

    If @AutoItX64 And $EIGEN_ALLOCATE_RAM_GB <> _Max(1, Number(IniRead($E4AIniFilename, "Operational Settings", "EIGEN_ALLOCATE_RAM_GB", $EIGEN_ALLOCATE_RAM_GB))) Then
        _HighMem_CleanUp()
        _HighMem_StartUp($EIGEN_ALLOCATE_RAM_GB, "GB")
    EndIf

into this:

; in case of repeat calls
    Local $newAlloc = ($EIGEN_ALLOCATE_RAM_GB <> _Max(1, Number(IniRead($E4AIniFilename, "Operational Settings", "EIGEN_ALLOCATE_RAM_GB", $EIGEN_ALLOCATE_RAM_GB))))
    If ($releaseAll Or $newAlloc) Then _Eigen_Cleanup()
    If $EIGEN_DENSE_DLLHANDLE > 0 Then DllClose($EIGEN_DENSE_DLLHANDLE)

    ; (re)start
    If (@AutoItX64 And $_HighMem_Active=False) Then _HighMem_StartUp($EIGEN_ALLOCATE_RAM_GB, "GB")

 

EDIT3: the aforementioned patches have now been incorporated into v5.2a (setup re-uploaded). Apologies for any inconvenience caused.

Edited by RTFC
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E4A Version 5.3 is finally out. :)

This is a long-overdue major upgrade, as the library now supports ZLib compression for real and integer matrices stored on file (complex matrices are still always stored as raw binary data). Reloading compressed matrix files is transparent (existing functions are used; the dll automatically redirects to the decompression versions of the function if the compressed-flag is set in the matrix file header (bit 8 in the variable type ID field). Saving matrices individually in compressed form is done through new functions _Eigen_SaveMatrix_Compressed and _Eigen_SaveMatrix_Transposed_Compressed, but alternatively, you can opt to always automatically compress when saving by setting new global flag EIGEN_ALWAYSCOMPRESS to True (stored in Eigen4AutoIt.ini) , through _Eigen_SetAlwaysCompressed. Under the hood, de/compression actually consists of two different algorithms, a fast one for x86 (for small-sized matrices, using a dynamically allocated work buffer, so it may fail if it runs out of memory when trying to de/compress a huge matrix) and a slower one in x64-mode that can handle matrices/files of any size (including > 4 GB). So if you start getting out-of-memory errors when using E4A compression on x86, it's high time to switch to x64-mode if you can. See new test scripts _EigenTest_29a/b_FileCompression.au3 for examples.

You can confirm the integrity of your data before compression vs. after decompression with new File I/O function _Eigen_GetMatrixHash_MD5, which returns the boost library's implementation of MD5 for any E4A matrix in memory. Note that the hash is computed over the matrix contents only; the matrix file header does not reside in memory and is thus excluded here (so computing the matrix file MD5 with a different utility would produce a different hash).

Other new goodies include Transformation functions _Eigen_ClampValue*, to replace all values within a defined range with a single constant, and _Eigen_Rescale*, to replace a given linear range of values with a newly-defined range. Furthermore, in the C(ell)wise sections, there is now support (in CwiseUnaryOp*) for two-way rad/deg conversion and (in CwiseScalarOp*) for new bit-wise functions (for integer matrices only!) shift-left/right ("shl", "shr") and rotate-left/right (the latter also for the LSB/LSW part of values), i.e., "rol", "ror", "rol8", "ror8", "rol16", "ror16". Relevant Cwise test scripts have been updated as well, switching to an integer work environment when demonstrating CwiseScalar operators.

Finally, the Eigen template library itself has been upgraded to latest stable release version 3.4.0.

For the complete list of additions, changes, and fixes, see the History /ChangeLog page in the Help as per usual. I should mention that the online version of the new Help will only be upgraded to v5.3 in the near future, hopefully within the coming week. However, the installer includes a .chm version of the same document in the main Eigen4AutoIt directory.

 

EDIT: and also as per usual, I managed to upload a version without the new rad/deg unary operators enabled, so please download again if you just did. Apologies for the oversight (I briefly moved development to another machine, and then the two versions diverged, and you know the rest...)

Edited by RTFC
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_WinAPI_DeleteObject($hHBitmap2) _GDIPlus_GraphicsDispose($hCanvas) _WinAPI_SelectObject($hDC_backbuffer, $hDC_obj) _WinAPI_DeleteDC($hDC_backbuffer) _WinAPI_DeleteObject($hHBitmap) _WinAPI_ReleaseDC($hGUI, $hDC) GUIDelete($hGUI) FMUSIC_StopSong($hMod) FSOUND_Close() MemoryDllClose($F_DLL) MemoryDllExit() DllClose($_MDKernel32Dll) EndFunc ;==>TheMatrix_v1 Func _Exit_About() $bExit = True EndFunc ;==>_Exit_About Func CalcFPS() ;display FPS $iShowFPS = $iFPS $iFPS = 0 EndFunc ;==>CalcFPS Func _WinAPI_BitmapCreateDIB($iWidth, $iHeight) Local $tBMI = DllStructCreate($tagBITMAPINFO) $tBMI.biSize = DllStructGetSize($tBMI) $tBMI.biWidth = $iWidth $tBMI.biHeight = -$iHeight $tBMI.biPlanes = 1 $tBMI.biBitCount = 32 $tBMI.biCompression = $BI_RGB Local $aResult = DllCall("gdi32.dll", "ptr", "CreateDIBSection", "hwnd", 0, "struct*", $tBMI, "uint", 0, "ptr*", 0, "ptr", 0, "uint", 0) Return $aResult[0] EndFunc ;Code below was generated by: 'File to Base64 String' Code Generator v1.20 Build 2018-02-02 Func _BG_Image($bSaveBinary = False, $sSavePath = @ScriptDir) Local $BG_Image $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '8QzL3xha61NNEJsJsYWI6WB+7iIlShDrroc1raqvHbsqKCODfY2wpFVUoxCB0BRkcms2sEJQ4bMWeFr38lq7FVGNGFFquCAWH36E4mIJslfxn1sPmfaXaucFqCIjE5hyygSiWgFoKUXmPMjk1jxWZjCkVDS0YXp48wCJBOmq2EdVF2Tp/3/bJgirC7TH2EwjPhqqWtVFQYMoW1sJIqXWAkVRKXOINbk3iZgZ8tIqUI2uLsgIDxfA5HC6IG2EZbggXqaMDNkD3VVftbomUBCyr1ykLAAiQSAyBZncGysilKEK9jpdESnSi3Mj2OvuwijY5kH8UMW/5zuxagRIa0MR9STRXV8IBNlJmRRRf6gy0VzNO7m7IEdmFtVKBG1U06Sqasxn9AhpDVGUKCTbRKFvGHwsKSubEl6c2D2+HpmjTkyEICMEYdPDUaI5DTK5NykfP9kEKX0OD9X10L0RRjyN+GgaEOfDdt6aIe/zk1kRFj330CO+ZpniXQEBQDlnHJt93Yi18GkGyOTepJ8mCLFCaLUXdV5RaZsSjn0ATAMFOI8a5DxT7oV9LHQcaxz919XwvKhhSIotU4h/5ji2WYJM7k3KPz9Hhqoc2QwxMV59bNUnC2OaHC6PUFbOP5+lJ8jf98GqcH20qn09nmiZYyYNjCog+HbElJi1oEE/Ztk2I2Ryc0GyLziEZFozoZohDbXuxACrvuAQKB9H8uOx/NSSlFkIO7wed0HUf8HzJAQRGJl/NtsRojCI0tvOPJmCTG7NJ+e8EqDZD87NUGN/vV67aizK3aH98RYocz7iECBPEDtlsfmVGXuF4XHTJ0MasbK9wa0f7Ze2lUjhU4ZNj/f7ff6ZTG6M/XmTAMjNEMpEPq3xetlf+dic3m7QWiHCLsgn2fFxDy9CLEJyFtQdzjN+B7sG1X4PUG5KPJYlZRNE9ThNr5+f5c9kcmOOzBkEsOmRyWVR9TGWxUh9Gfte60uZ7SuHC/JufrxbDWItc2aB' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= 'Xu5bb84/KpT2l9Iza4k6IPmleZ3bVE8rbDQ6zSVEKLZwA6e3Bs16N++EJkZsUFWwQKKkxSkjR7+K/vNRj9u6dp2Kp06IAZAmJAvn6T5ffqnf/sDeIzqhYLuEFzN5cmR0wsNoXgbn6MDYvSXLhA0JSk43cvRL6++UDx39UND6BtYEEQCRCjqweX/PCwFClw2CBcqljkoReECNhRGrLKAxivqxBhIaxvyjbedQ8p+njBz9kngkhYOnhLQeXHKh8ULJ7zTAhmdeU66jCoEEMBAQ0YEQLyasIAZv5Ts8YIIItww9iCbkRov0sBpnb/zRL1c9ug/v/Vd2HbNbdmk1Ia5GnN2KRX+y6Ehcr64udUajF1ddRcZYGSvVhPIABlxpdKbwsrTsrK+AguJxD4ipX2Sv1tHRf0Y2Hk8ZhaR//OdNSKU7Naae6h269WaDLPHepNSgfESZlVXJ2/NpCKJW6AxkMUgak4CCDHsdVXZ2/R79TP39X9XbrkwGIHy+11rtlqZPJ1UVqdFwVL5XV3hc9yUbIVItIpQykpSWNyKF2zSgQuJT1BNrOEzhp5E5PfvRT9Z/6m6w+3dG/VE/OFC3IcpBxy1ehaJtp0ZsXTm+tkhxe++OZJUW4tEkaKBW7zihL5dWjVky09DW+MuY/eRfDzo6P6L46S4sfPXnm7yXVvJMTfeZ6ZWV/WB8ZKSCBgMbVBMNJoPjTULhDcunYm87CKuK632BxZCxrijYTbzPLp0icvRTuo/xak1x8hQtu8n59JrwYLjc7+KCixdQMDC4BAamiJGVAQ+xBYuutXSClyHTKs3ZCNMZA+EpKC0yOiJOETn60TevvCYrK3HglAwdrZbYAIt1C8uTlFy+MVHUcHAoVlCo11RLzBGE6YAHedwm7lUpZzwo7F5FlEDI55CwJnOjdIrI0Y9cXq3dVpgJLE9GHDx8NeA1L/G/D8RDnyjcKuhKnpt5CxHBDDMdLG6sdFqwuYopigYqlla3D8JbCmjP' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= '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' $BG_Image &= 'AABJRU5ErkJggg==' Local $bString = _WinAPI_Base64Decode($BG_Image) If @error Then Return SetError(1, 0, 0) $bString = Binary($bString) If $bSaveBinary Then Local Const $hFile = FileOpen($sSavePath & "\Neo_Matrix_800x500_cut_32c.png", 18) If @error Then Return SetError(2, 0, $bString) FileWrite($hFile, $bString) FileClose($hFile) EndIf Return $bString EndFunc ;==>_BG_Image You need The Matrix Sound.au3 which is in the Zip archive (see below) to run the code properly!
       
      Download: The Matrix v1.31 (incl. sound), without sound The Matrix v1.30
       
      Can you decipher the code?
       
    • By RTFC
      The Short Version:
      This set of well-annotated example scripts shows how to solve sudoku puzzles with simple, powerful bitmask functions applied on a massive scale, demonstrating both common solving techniques and highly-optimised brute-force.
      All you need is:
      to like sudoku's basic logic primary school maths to download & install this bundle (v1.2; 25 July 2020) and this #include file (v5.1+) the CrossFilter GUI
    • By RTFC
      Eigen4AutoIt Features:
      free, fast matrix computing environment for Windows (runs under Wine on Linux and Mac) built upon the robust Eigen code base (open-source), with many enhancements simple, intuitive functions, with extensive online documentation supports integer, single, and double precision, in real and complex matrices Tutorials with scripts, plus Test scripts for each function section easily exchange data between native binary files (.mat) and ASCII, Excel, and Xbase files, or AutoIt arrays 32-bit (x86-mode) and 64-bit (x64-mode) support in x64-mode, matrices can be any size that fits into available virtual memory (>4GB), and can be shared between processes over one thousand alias wrappers for flexibility and ease-of-use  
      The Eigen4AutoIt thread is here:
      This computing environment allows you to do matrix I/O (memory & files), matrix arithmetic, transformation, reduction, and decomposition, solve systems of linear equations, and perform statistics. Most functions can act on integer, real, or complex matrices (or the latter's real/imaginary parts separately). Much of the actual complexity of using Eigen in its native C++ environment has been hidden for AutoIt users, through extensive bounds and error checks, an intuitive function-naming convention, a large help file, and detailed tutorials and test examples.
    • By AlecSadler
      Hello friends! I have been working on an encryption algorithm in autoit as a proof of concept for some time now. Basically the algorithm uses a progressive recursion to encode data inside a matrix using a key that changes according to the date-time of the system, which is extracted from a larger key array. Recently after a drive failure, I lost the source and had to start from scratch, now I can't quite get it working the way it was before, and I can't see what I'm doing wrong, if anyone who understands matrix math or encryption could help I would much appreciate it. The problem is that the values returned by the decryption (extraction) process are way too big.
       
      I have figured out the solution to my problem, it was a typo, please disregard this thread.
      I will post my project into example scripts when it's ready.
       
       
       
    • By Edano
      i searched the forum, but didn't find anything.
      has anyone an idea or ever done it with autoit ? simple image transforming, like sharpness, brightness, blurring etc. ?
      maybe, does gdiplus.dll feature that ?
      here is a tutorial on how to do it the hard (mathematical) way. http://lodev.org/cgtutor/filtering.html before i try that, i wanted to know if there is already an existing project or an idea or anyone has experiences.
      thx
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