Experimental Data ================= Neural Data (optional) ---------------------- 1. Save the recorded neural data for the training and testing conditions in ‘./nusim_neural_data/neural_activity.pkl’ as a Python dict object .. code-block:: dict{ <'train'> : , <'test'> : } 2. ```` and ```` are Python dictionary objects that contain the neural data in the following format: ```` is the integer index of the corresponding condition as in the kinematics file. ```` is the numpy array that contains recorded firing rates with the following shape: ``[timepoints, num_neurons]``. num_neurons are the total number of recorded neurons. .. note:: If this step is omitted, various post-training *quantitative* analyses which require recorded neural data such as CCA, will not run. nuSim training will also not proceed (nusim_data_path can also be specified in the ``./configs/configs.txt`` file). Stimulus Data (optional) ------------------------ Provide any experimental stimulus data in ``./stimulus_data/stimulus_data.pkl`` as a Python dict object:: dict{ <'train'> : , <'test'> : } 1. ```` and ```` are Python dictionary objects that contain the experimental stimulus data in the following format: ```` is the integer index of the corresponding condition as in the kinematics file. ```` is the numpy array that contains recorded stimulus data with the following shape: ``[timepoints, num_features]``. num_features are the corresponding features in that stimulus. Initial Pose Data (optional) ---------------------------- Save the initial pose (containing the qpos and qvel) as numpy arrays in ``./inital_pose/`` as qpos.npy and qvel.npy with shape ``[nq, ]``. nq is the number of joints in the xml model. This step is optional. If omitted, the default initial pose for xml model will be used for CMA-ES and IK. (initial_pose_path can also be specified in the ``./configs/configs.txt`` file)