New parallelization mode & generic loss computation

Changes:

Renaming

• renamed launch_process_RunturbESN to parallelize_seeds in study.py
• renamed Callback to callback_seeds in study.py
• renamed start_thread_RunturbESN to thread_run_turbESN in study.py
• renamed nstudy to nsettings in util.py, core.py & study.py
• renamed istudy to isetting in util.py, core.py & study.py
• renamed CreateStudyConfigArray to create_study_config_list in util.py
• renamed SaveStudy, ReadStudy, ReadMSE, ReadESNOutput to snake case equivalents
• renamed ComputeWassersteinDistance to compute_wasserstein_distance in util.py
• renamed ComputeMSE to compute_mse in util.py
• renamed ComputeR2 to compute_r2 in util.py
• renamed RunturbESN to run_turbESN in util.py
• renamed setDevice to set_device in core.py
• renamed toTorch to to_torch in core.py
• renamed _MSE_DEFAULT to _LOSS_DEFAULT in _modes.py

New functionalities

• added functionality to parallelize grid & random search setting over subprocesses (before: only random seeds were distributed among processors)

  • added parallelize_settings & callback_setting methods in study.py
  • choose between parallelization in run_gs.py via the parameter use_parallel_setting
  • this speeds up studies, where the no. settings is larger than the no. random seeds

• changed computation of mse in run_turbESN to more generic way: user uses dict esn.loss_func to specify which loss functions should be computed, results are returned in loss_dict

  • added None init. for esn.loss_func
  • adapted save_study, read_study in util.py
  • adapted read in core.py
  • renamed read_mse to read_loss in util.py
  • adapted read_loss in util.py
  • adapted thread_run_turbESN, callback_settings, callback_seeds in study.py
  • adapted forward_validate_auto_ESN in util.py (not tested)

Misc.

• fixed minor issues in run_gs.py
• fixed bug in plot_esn_predictions method in util.py
• added default values to style_dict in plot_esn_predictions & plot_activation_arg_distribution in util.py
• fixed error in read method in core.py, where self.xrows was not adapted correctly
• • added member variable u_pre_val to ESN object in core.py
• added option to set u_pre_val via SetValidationData in core.py
• use self.u_pre_val (if not None) in run_turbESN to initialize reservoir state before validation phase (make it more comparable to test phase, which is also preceded by state from GT data)
• self.val_init_input is now taken from self.u_pre_val (if val_init_input is None and u_pre_val is not None)
• removed iseed argument in read_loss, read_study, read_esn_output in util.py
• adpated basic_tour.ipynb notebook to new turbESN