New syntax constructs allow analysis sequences to be explicitly split into parallel execution threads. Depending on the number of logical processors (cores) available in the PC, these can be processed simultaneously as parallel processes (Multithreading). Especially analyses with many channels, large amounts of data and complex calculations, which used to run for many hours, are thus significantly faster.   

While imc FAMOS enables users to perform comprehensive analyses and visualize them conveniently even without programming knowledge, it also offers numerous options for integrating modern programming languages and environments. In addition to the support of “R” for statistics, algorithms programmed in Python can now also be integrated.  

Functions are available for reading and writing Python variables as well as for executing Python functions, lines of code or entire programs. For this purpose, imc FAMOS now has an embedded runtime environment with interpreter. This enables users to benefit from the open source community around the popular programming tool and to integrate ready-made algorithms, for example from the field of AI/ML, into their imc FAMOS world.  

An improved FFT function now allows, among other things, a free choice of block sizes (mixed radix method). This allows frequency line spacing to be controlled specifically, so that smooth or round frequency resolutions can be achieved with decadic or 1, 2, 5 block sizes.  

Example: A sampling rate of 100 kHz and a block size of 20,000 samples results in a frequency line spacing of 5 Hz. 

In addition, the maximum block size was increased to 227.  

[FFT()], [Spec()], [iFF()]: Extension of the block size  

[FFT()], [Spec()]: New calculation modes 

Complex analyses can be structured and very efficiently simplified in imc FAMOS by applying functions or sequences to entire groups of channels or variables. These Group functions have been improved and extended in the new version. 

GrPart() : Creation of subgroups 

GrConcat() : Creates a group with variables as parameters. Any data types are supported, including groups.