Quick Start

The quickest way to install cait is via the Python package index:

$ pip install cait

To get something working quickly, you can use simulated mock data, copy it to the work horse of cait – the DataHandler, which stores your analysis results – calculate pulse shape parameters, and have a look at the pulses and a first pulse height spectrum.

import cait as ai
import cait.versatile as vai

# Set up a DataHandler instance
dh = ai.DataHandler(nmbr_channels=2)
dh.set_filepath(path_h5="", fname="my_first_dh", appendix=False)
dh.init_empty()

# Fill it with Mock data and calculate pulse shape parameters
dh.include_event_iterator("events", vai.MockData(dt_us=dh.dt_us, n_events=1000).get_event_iterator())
dh.cmp("events")

# Have a look at the events
vai.Preview(dh.get_event_iterator("events").with_processing(vai.RemoveBaseline()))

# Have a look at pulse heights
vai.Histogram(dh["events/pulse_height", 0], xlabel="Pulse height (V)")

Once you accomplished this first step into the world of raw data analysis, start going through the tutorial notebooks, that demonstrate most of the functionality of cait.