Data management

AsyncSession objects can store three kinds of data:

• scalar variables monitored in time at possibly irregular time intervals. Scalar values of these variables are logged, in a “data logger” manner. They are suited to the monitoring of quantities over time when a regular measurement rate is not required. We call them “logged variables”. Tasks can save values by calling the pymanip.asyncsession.AsyncSession.add_entry() method, and they can be later retrieved by calling the following methods pymanip.asyncsession.AsyncSession.logged_variables(), pymanip.asyncsession.AsyncSession.logged_variable(), pymanip.asyncsession.AsyncSession.logged_data(), pymanip.asyncsession.AsyncSession.logged_first_values(), pymanip.asyncsession.AsyncSession.logged_last_values(), pymanip.asyncsession.AsyncSession.logged_data_fromtimestamp(), or by using the sesn[varname] syntax shortcut which is equivalent to the logged_variable() method.

• scalar parameter defined once in the session. We call them “parameters”. A program can save parameters with the pymanip.asyncsession.AsyncSession.save_parameter() method, and they can be later retrieved by calling the pymanip.asyncsession.AsyncSession.parameter(), pymanip.asyncsession.AsyncSession.parameters(), pymanip.asyncsession.AsyncSession.has_parameter() methods.

• non-scalar variables monitored in time at possibly irregular time intervals. A non-scalar value is typically a numpy array from an acquisition card or a frame from a camera. We call them “datasets”. They can be saved with the pymanip.asyncsession.AsyncSession.add_dataset() method, and later be retrieved by the pymanip.asyncsession.AsyncSession.dataset(), pymanip.asyncsession.AsyncSession.datasets(), pymanip.asyncsession.AsyncSession.dataset_names(), pymanip.asyncsession.AsyncSession.dataset_last_data(), pymanip.asyncsession.AsyncSession.dataset_times() methods.