few other cleanups

add automatic cacheing of various functions, and a cache_test() routine to test the runtimes with and without caching

attempt to fix (finally?) the joingingfile logic

the joiningfile is now made by whichever job gets to this task first, so the error where it wasn't fully made (when jobs were slowly run from the HPC queue) should not happen now unless it takes a long time to write that one short file. I guess we could put in a checkfile if required, but this should be *very* rare.

fix some bugs in restarting from snapshots: the start_at was calculated incorrectly (needed to take into account modulo and previous start_at)

all other files access the HPC API, not the slurm and condor objects directly

set up json functions to not convert ascii (should be faster and preserve UTF8)

Slurm restarts work, just take your old (unfinished) Slurm dir and set it with slurm_restart_dir=<whatever>

doesn't work for slurm yet, but small steps

also fixed a bug in keys_to_floats()

add CPU time to metadata output, and fix an issue with a tuple rather than a string from platform.something()

I've added a new grid_option, num_processes, which is the number of processes launched by Python's multiprocessing. num_cores is used to set this:

if > 0 use the number specified (as previously, so backwards compatibility is fine)
if == 0 use the number of logical cores
if == -1 use the number of physical cores

Try running it with a command like:

---
rm -rf /tmp/slurm ; nice python3.9 ./src/python/ensemble.py dists=Moe binaries=False r=100 verbosity=1 max_evolution_time=10 slurm_dir=/tmp/slurm slurm_partition=debug slurm_memory=100MB monte_carlo_kicks=0 save_ensemble_chunks=False num_cores=-1 slurm=1 slurm_njobs=2 num_cores=2
---

You will want to change num_cores and slurm_njobs to suit. Each Slurm job gets num_processes cores allocated to it.

Note: you should set your slurm directory to be empty. This isn't really required, but makes debugging a lot easier.

You also have to set the slurm_partition by hand - this is something you need to find out based on your cluster. In the above example I use "debug" because this is the default.

There are quite a few changes internally, particularly new functions to load, save and merge Population objects and their data (mostly) correctly, and updates to the dict merging functions that this required.

please report bugs because there will be many!

beware though: there are many debugging options still built in, and the gridcode should (but doesn't) have a unique filename

Fixing tests that failed. Added a function to filter dicts based on value instead of key. Added M&S data to grid options rather than custom options

remove deprecated resolution setting

add option "save_ensemble_chunks" to make sure the ensemble chunks are saved : I am chasing up a grid that completely froze (and gave segfaults) ...

also prevented the Moecache from being freed on grid exit: we can have nested grid objects, and in that case it is required to remain

attempted to harmoize the Moe and di Stefano (2017) variable names so they all use Moe2017 (or MOE2017)

added options to the Moe loader so we can change the JSON data and reload it after clearing the cache

the period distribution renormalization now gets the low and high limits from the loaded data

update_dicts() now copies the type of dict_1 for the new dict, rather than using OrderedDict (maybe merge_dicts should do this too?)