Useful for grouping trials by the config they used. In use by upcoming #633 for generating graphs with variance error bars for repeated configs.

Also refactors a number of other things:

• Standardize on experiment_id instead of exp_id
  (but not the db schema for now)
• Standardize on tunable_config_id instead of config_id in the API since we also call it tunable_config for the object fetching property to distinguish from the config dict used internally.
  (but not the db schema for now)
• Rework the idea of TunableConfigTrialGroup as an object inaddition to an ID (further methods can be added later to move back and forth between types when doing interactive analysis).
• Rework the idea of a TunableConfig as an object for fetching tunable value assignments (similar justification - easier grouping in the future by fetching trial across experiments based on config - eventually could be used to house the experiment merge logic).
• Rename results APIs to results_df (similar for others that return pandas.DataFrame) to match the results_dict that return dict
• Refactor test fixtures to match other styles and for future use (moved to Remove TunableGroups from Storage classes and add TrialData tests #644).
• Expand tests

NOTE:

• We cut a new version with this commit since there are potentially breaking API changes (e.g., results -> to results_df and exp_id -> experiment_id).

Currently builds off of #644 and splits work out of #633