Versione 2.1.1 (23,5 KB) da Jan
Get MD5 of files or arrays as fast C-Mex
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Aggiornato 7 mar 2019

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MD5 hash of files, strings and arrays (RFC 1321)
Hash = GetMD5(Data, Mode, Format)
Data: File name or array.
Mode: CHAR to declare the type of the 1st input.
'File': Data is a file name as CHAR.
'8Bit': If Data is a CHAR array, only the 8 bit ASCII part is used.
'Binary': The MD5 sum is obtained for the contents of Data.
This works for numerical, CHAR and LOGICAL arrays.
'Array': Include the class and dimensions of Data in the MD5
sum. This can be applied for (nested) structs, cells
and sparse arrays also.
Format: CHAR, format of the output: hex, HEX, double, uint8, base64

Hash: A 128 bit number is replied in the specified format.

This function is at least 2 times faster than the corresponding Java method.
For shorter arrays this C-Mex implementation is much faster, see the output
of the included unit test function.
The function DataHash can reply SHA hashes also, but it is remarkably
slower due to the overhead of calling Java. For nested structs this C-Mex
can be 100 times faster. See:
The C-function must be compiled before using: Call the M-function without
inputs. If you do not have a C-compiler, pre-compiled files can be

Cita come

Jan (2024). GetMD5 (, MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2018b
Compatibile con R13SP1 e release successive
Compatibilità della piattaforma
Windows macOS Linux

Ispirato da: MD5 in MATLAB

Ispirato: bimac/md5sum, JavaMD5, DataHash

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Versione Pubblicato Note della release

M-file accepts inputs now to care about users, who do not follow the install instructions.


String type is handled.

Compilation failed, when _LITTE_ENDIAN was undefined.
Improved speed, the class and size of arrays can be considered, cell and struct arrays accepted. Now arrays and files > 2.1GB are processed.
Fixed problem with compiling under MacOS X.

UINT32 has 4 bytes on 64-bit systems now. Thanks to Sebastiaan (34534)!