Refactor cleaning

- Fixed: some bugs left after the refactor @33acb021f1
RandomFactorialNetwork optimal parameter setting and some refactoring of HierarchialNet

- Added: autoset_parameters for RandomFactorialNetwork. Automatically sets the rc_scale corresponding to M. Should sort of work, in both Conjunctive or feature cases.
- Fix: cleaned up the rcscale setting pipeline
- Fix: Plot_neuron_activity now has a default neuron_index.
- Fix: HierarchicalRandomNetwork inherits from RandomFactorialNetwork, reducing some copy/paste of functions. Some functions may not work at all though, be careful.
Refactor of init_everything

- Modify: Defines init_everything in launchers, which could be used everywhere afterwards. Unless they do something more precise with one of the component.
PBS framework and launchers for HierarchicalRandomNetwork

- Added: Big work on the useability of SubmitPBS and overall flow of running simulations on PBS. Should now create specific .py files, to be placed in /nfs/data, which will generate PBS scripts directly. Keeps the parameters close to the simulations, easy to reproduce. The specific .py files are loaded as dynamic modules, which works nicely, and also allows to define functions (but could be more flexible…). Work on #12.
- Added: ExperimentLauncher can now receive parameters as arguments. They overwrite existing command line parameters.
- Added: Launchers_experimentalvolume now implements a launcher_do_generate_submit_pbs_from_param_files, which should be quite general enough. Use this to start a grid of parameters. Perhaps could be put somewhere else later.
- Added: SubmitPBS has 2 new entry-points, either to hide the parameter_generation method, or to get everything information from the loaded parameter module.
- Fix: SubmitPBS now enforces the dtype of parameters when generating the candidate parameters.
- Added: Launchers for HierarchicalRandomNetwork. PBS and normal. Work on #35