-__init__(l, t, N, system_cls, trials, ...[, ...])
|
+
__init__(l, t, N, system_cls, trials, ...[, ...])
|
Initialize the class. |
-create_job_configs([trials, seed])
|
+
create_job_configs([trials, seed])
|
Generates a job configurations by generating seeds for each trial of each base config. |
-evaluate(algo_cls[, algo_kwargs, ...])
|
+
evaluate(algo_cls[, algo_kwargs, ...])
|
Evaluates an algorithm class (NOT an instance) on a dynamical system over a set of experimental parameters. |
-execute_job(job_id[, trial, system_seed, ...])
|
+
execute_job(job_id[, trial, system_seed, ...])
|
For a given system latent dimension and embedding dimension, instantiates system and for a specific N, evaluates the algorithm on the system. |
-get_num_jobs(trials)
|
+
get_num_jobs(trials)
|
Calculates the total number of jobs based on the number of trials and the base configurations generated from sweep parameters. |
-plot(data[, latent_dim, embedding_dim, ...])
|
+
plot(data[, latent_dim, embedding_dim, ...])
|
- returns:
A plot of the data.
@@ -461,15 +461,15 @@ dynadojo.challenges.FixedComplexity
-base_configs
|
+ base_configs
|
Computes a base set of configurations for jobs by iterating over elements of sweep parameters. |
--
-__init__(l, t, N, system_cls, trials, test_examples, test_timesteps, e=None, max_control_cost_per_dim=1, control_horizons=0, system_kwargs=None)
+-
+__init__(l, t, N, system_cls, trials, test_examples, test_timesteps, e=None, max_control_cost_per_dim=1, control_horizons=0, system_kwargs=None)
Initialize the class.
- Parameters:
@@ -491,8 +491,8 @@ dynadojo.challenges.FixedComplexity |