Skip to main content
Donate to the Python Software Foundation or Purchase a PyCharm License to Benefit the PSF! Donate Now

Tools for neuroscience experiments

Project description


image image image image image


Additional tools for neuroscience experiments, including:

  • A framework for polling input devices on a separate process.
  • A framework for keyframe-based animation.

Everything should work on Windows/Mac/Linux.

See requirements.txt for dependencies.


Current release:

pip install toon

Development version:

pip install git+

For full install (including device and demo dependencies):

pip install toon[full]

See for a list of those dependencies, as well as device-specific subdivisions.

See the demos/ folder for usage examples (note: some require psychopy).



toon provides a framework for polling from input devices, including common peripherals like mice and keyboards, with the flexibility to handle less-common devices like eyetrackers, motion trackers, and custom devices (see toon/input/ for examples). The goal is to make it easier to use a wide variety of devices, including those with sampling rates >1kHz, with minimal performance impact on the main process.

We use the built-in multiprocessing module to control a separate process that hosts the device, and, in concert with numpy, to move data to the main process via shared memory. It seems that under typical conditions, we can expect single read() operations to take less than 500 microseconds (and more often < 100 us). See demos/ for an example of measuring user-side read performance.

Typical use looks like this:

from toon.input import MpDevice
from toon.input.mouse import Mouse
from timeit import default_timer

device = MpDevice(Mouse())

with device:
    t1 = default_timer() + 10
    while default_timer() < t1:
        data =
        # alternatively, unpack
        # clicks, pos, scroll =
        if data.pos is not None:
            # N-D array of data (0th dim is time)
            # time is 1D array of timestamps
            print(data.pos[-1].time) # most recent timestamp

Creating a custom device is relatively straightforward, though there are a few boxes to check.

from toon.input import BaseDevice, make_obs
from ctypes import c_double

# Obs is a class that manages observations
class MyDevice(BaseDevice):
    # optional: give a hint for the buffer size (we'll allocate 1s worth of this)
    sampling_frequency = 500

    # required: each data source gets its own Obs
    # can have multiple Obs per device
    # this can either be introduced at the class level, or during __init__
    # ctype can be a python type, numpy dtype, or ctype
    Pos = make_obs('Pos', shape=(3,), ctype=float)
    RotMat = make_obs('RotMat', (3, 3), c_double) # 2D data

    # optional. Do not start device communication here, wait until `enter`
    def __init__(self):

    ## Use `enter` and `exit`, rather than `__enter__` and `__exit__`
    # optional: configure the device, start communicating
    def enter(self):

    # optional: clean up resources, close device
    def exit(self, *args):

    # required
    def read(self):
        # See demos/ for examples of sharing a time source between the processes
        time = self.clock()
        # store new data with a timestamp
        pos = self.Pos(time, (1, 2, 3))
        rotmat = self.RotMat(time, [[1, 2, 3], [4, 5, 6], [7, 8, 9]])
        # can also be explicit, i.e. `self.Returns(pos=pos, rotmat=rotmat)`
        return pos, rotmat

This device can then be passed to a toon.input.MpDevice, which preallocates the shared memory and handles other details.

A few things to be aware of for data returned by MpDevice:

  • If a device only has a single Obs, MpDevice returns a single TsArray (a numpy array with a time attribute). Otherwise, MpDevice returns a named tuple of observations, where the names are alphabetically-sorted, lowercased versions of the pre-defined Obs.
  • If the data returned by a single read is scalar (e.g. a 1D force sensor), MpDevice will drop the 1st dimension.
  • If there's no data for a given observation, None is returned. The named tuple has a method for checking all members at once (data.any()).

Other notes:

  • The returned data is a view of the local copy of the data. toon.input.TsArrays and device Returns have a copy method, which may be useful if e.g. appending to a list for later concatenation.
  • Re: concatenation, there is a stack function available via from toon.input import stack, which is like numpy's vstack but keeps the time attribute intact. It also dispatches appropriately for either TsArrays or Returns.
  • If receiving batches of data when reading from the device, you can return a list of Returns (see tests/input/ for an example).
  • You can optionally use device.start()/device.stop() instead of a context manager.
  • You can check for remote errors at any point using device.check_error(), though this automatically happens after entering the context manager and when reading.
  • In addition to python types/dtypes/ctypes, Obs can use ctypes.Structures (see input tests or the cyberglove for examples).


This is still a work in progress, though I think it has some utility as-is. It's a port of the animation component in the Magnum framework, though lacking some of the features (e.g. Track extrapolation, proper handling of time scaling).


from time import sleep
from timeit import default_timer
import matplotlib.pyplot as plt
from toon.anim import Track, Player
# see toon/anim/ for all easings available
from toon.anim.easing import linear, elastic_in_out

class Circle(object):
    x = 0
    y = 0

circle = Circle()
# list of (time, value)
keyframes = [(0.2, -0.5), (0.5, 0), (3, 0.5)]
x_track = Track(keyframes, easing=linear)
# we can reuse keyframes
y_track = Track(keyframes, easing=elastic_in_out)

player = Player()

# directly modify an attribute
player.add(x_track, 'x', obj=circle)

def y_cb(val, obj):
    obj.y = val

# modify via callback
player.add(y_track, y_cb, obj=circle)

t0 = default_timer()
vals = []
while default_timer() < t0 + 3.2:
    vals.append([circle.x, circle.y])


Other notes:

  • Non-numeric attributes, like color strings, can also be modified in this framework (easing is ignored).
  • The Timeline class (in toon.anim) can be used to get the time between frames, or the time since some origin time, taken at timeline.start().
  • The Player can also be used as a mixin, in which case the obj argument can be omitted from player.add() (see the demos/ folder for examples).
  • Multiple objects can be modified simultaneously by feeding a list of objects into player.add().

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
toon-0.12.6-py2.py3-none-any.whl (37.4 kB) Copy SHA256 hash SHA256 Wheel py2.py3
toon-0.12.6.tar.gz (27.7 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page