Complete the functionality of an integrated CPU FLDO module and configure a standalone manual test of it

The folding algorithm has now been fully integrated into cheetah, and is able to take an input candidate list and inout data, fold the data given the parameters from the candidate list, and output the results into a data cube. The folded output is not yet as expected, but as all of the code is integrated and tests written, this is close to being done. Even though the folded output is not yet correct, the work done thus far delivers the full functionality of FLDO, in that it can populate a data cube which can be sent through the rest of the cheetah pipeline. In summary: the FLDO algorithm is fully implemented in cheetah all of the planned unit tests are written and pass the "product-level" test is fully written the "product-level" test generates a pulsar-like signal (which matches the FLDO input API in cheetah), which is passed to the FLDO module, along with a candidate list the pulsar-like signal is folded correctly within FLDO The FLDO module creates and outputs a folded candidate object which matches the FLDO output API in cheetah The only step that doesn't work is the final step of dedispersing and frequency scrunching (which is one step in this implementation), due to a bug that will be investigated in a separate bug ticket (AT4-1191). However, an output candidate is created while running FLDO, so it does successfully run end-to-end and produce output, which can be used as part of testing later stages in the pipeline or running an end-to-end cheetah pipeline. The current fully-integrated version of the code is in branch at4-1013_integarte_skald_ingest_accumulator_data_method_in_fldo, and as of this commit: https://gitlab.com/ska-telescope/pss/ska-pss-cheetah/-/commit/315b841c17db445af656a952fdc53ddd1d2cf2d7 the code builds and the new FLDO unit tests run.