Skip to main content

spike-recorder

Actions Status Documentation Status Code style: black

PyPI version Conda-Forge PyPI platforms

Gitter

This package implements a Python interface for the Backyard Brains Spike Recorder, a neural recording application. It is based off a fork of the original C++ code, found here. In addition, it contains two psychological experiment applications written in Python that control and record events via the SpikeRecorder.

Installation

You can install this library from PyPI with pip:

python -m pip install spike-recorder

Usage

To run the SpikeRecorder application simply invoke it on the command line

spike-recorder

If you want to launch the SpikeRecorder application alongside either of the experiments below then invoke them with the --spike-reord option.

Iowa Gambling Task

Iowa Task Screenshot

To launch the Iowa Gambling Task Experiment, run:

iowa

There are some available options and arguments:

usage: iowa [-h] [--spike-record] [--total-deck-pulls TOTAL_DECK_PULLS]

optional arguments:
  -h, --help            show this help message and exit
  --spike-record        Launch Backyard Brains Spike Recorder in background. Default is do not run.
  --total-deck-pulls TOTAL_DECK_PULLS
                        The total number of deck pulls in the experiment. Default is 100.


Libet Experiment

Libet Experiment Screenshot

To launch the Libet Task Experiment, simply run:

libet

If you wish to adjust the speed of the clock or the number of trials in either phase, see the available options:

usage: libet [-h] [--spike-record] [--num-trials-paradigm1 NUM_TRIALS_PARADIGM1] [--num-trials-paradigm2 NUM_TRIALS_PARADIGM2] [--clock-hz-paradigm1 CLOCK_HZ_PARADIGM1] [--clock-hz-paradigm2 CLOCK_HZ_PARADIGM2]

optional arguments:
  -h, --help            show this help message and exit
  --spike-record        Launch Backyard Brains Spike Recorder in background. 
                        Default is do not run.
  --num-trials-paradigm1 NUM_TRIALS_PARADIGM1
                        The number of trials to conduct for paradigm one. Default is 20.
  --num-trials-paradigm2 NUM_TRIALS_PARADIGM2
                        The number of trials to conduct for paradigm two, 
                        in which time of urge is asked. Default is 20.
  --clock-hz-paradigm1 CLOCK_HZ_PARADIGM1
                        The number of full rotations the clock makes per second in paradigm one. 
                        Default is 1 but can be set lower than 1.
  --clock-hz-paradigm2 CLOCK_HZ_PARADIGM2
                        The number of full rotations the clock makes per second in paradigm two. 
                        Default is 1 but can be set lower than 1.

Metadata

Release files for spike-recorder 0.3.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for spike-recorder 0.3.3
File Size Uploaded Provenance Actions
spike_recorder-0.3.3.tar.gz 6.9 kB Without provenance Details for spike_recorder-0.3.3.tar.gz

Built distributions (wheels)

Table of built distributions (wheels) for spike-recorder 0.3.3
File Actions
spike_recorder-0.3.3-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details for spike_recorder-0.3.3-cp39-cp39-win_amd64.whl
spike_recorder-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.9+ x86-64 Details for spike_recorder-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl
spike_recorder-0.3.3-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details for spike_recorder-0.3.3-cp38-cp38-win_amd64.whl
spike_recorder-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.9+ x86-64 Details for spike_recorder-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl
spike_recorder-0.3.3-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details for spike_recorder-0.3.3-cp37-cp37m-win_amd64.whl
spike_recorder-0.3.3-cp37-cp37m-macosx_10_9_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64 Details for spike_recorder-0.3.3-cp37-cp37m-macosx_10_9_x86_64.whl
spike_recorder-0.3.3-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details for spike_recorder-0.3.3-cp36-cp36m-win_amd64.whl
spike_recorder-0.3.3-cp36-cp36m-macosx_10_9_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64 Details for spike_recorder-0.3.3-cp36-cp36m-macosx_10_9_x86_64.whl

Total release size: 15.2 MB

Release files / spike_recorder-0.3.3.tar.gz

Download URL spike_recorder-0.3.3.tar.gz
Size 6.9 kB
Tags Source
SHA-256 checksum
How to use checksums
d019519c8b8b4f6f462b9bdc39580af95a7e62a011fac0df9939c9b4b074b1fd
BLAKE2b-256 checksum
How to use checksums
b59ba913c4ca0a72fbb4db57ef01c2e0a90ac155091b0996649a4f4a33c3a4c2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp39-cp39-win_amd64.whl

Download URL spike_recorder-0.3.3-cp39-cp39-win_amd64.whl
Size 1.9 MB
Tags CPython 3.9 Windows x86-64
SHA-256 checksum
How to use checksums
fd59769e4b0a78628a7b8ff7cfcae1f48e5887ae3e6d97f4cfcb254073b3b303
BLAKE2b-256 checksum
How to use checksums
cf678b7cd5ea099ae3f35a4bf20628ff662a400b1bb34bb1c6564a31534fe8f6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl

Download URL spike_recorder-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl
Size 1.9 MB
Tags CPython 3.9 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
e96f4fed29f1f79cfc3e4de7f7e8e33450e9e42a5938fe2428bf832242dcbca3
BLAKE2b-256 checksum
How to use checksums
b1f7bf6d467d5a13ab702a50b10da78becd2b6f1b02b66ce64e18d828269ac48
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp38-cp38-win_amd64.whl

Download URL spike_recorder-0.3.3-cp38-cp38-win_amd64.whl
Size 1.9 MB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
dfe36fd78e55e23663ebe518dda10142e3fcb955f50ec34b39d00500d9ee74ab
BLAKE2b-256 checksum
How to use checksums
46d22b8bdce33c74385d87934d777709a7ed17bd41cbf32319743966c998b516
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl

Download URL spike_recorder-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl
Size 1.9 MB
Tags CPython 3.8 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
dfbe2ea7c5aadce5910677f6266253f63f783cf05125e1206af94ab00ad7373b
BLAKE2b-256 checksum
How to use checksums
e4fb5c692223a1c6290217a8def92c8d7b19ed842de29a65eedade26fb80a6d2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp37-cp37m-win_amd64.whl

Download URL spike_recorder-0.3.3-cp37-cp37m-win_amd64.whl
Size 1.9 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
cdd1f6a4633f08138801afeca6d6451d294ed9b65faa906f070c1dd349eacbbc
BLAKE2b-256 checksum
How to use checksums
f0bafa129635e121db6ce53c9da907fba8ed0d2e4806c9badf280bb3fb8742f0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp37-cp37m-macosx_10_9_x86_64.whl

Download URL spike_recorder-0.3.3-cp37-cp37m-macosx_10_9_x86_64.whl
Size 1.9 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
a9aa153fe5e00737dfaeceba3847f74cd9ea4159054cc26c828d72341319eae8
BLAKE2b-256 checksum
How to use checksums
322401eca072d2594242f16abc4507871c6875c7a0173ddd387b6c94c958f5d1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp36-cp36m-win_amd64.whl

Download URL spike_recorder-0.3.3-cp36-cp36m-win_amd64.whl
Size 1.9 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
e6b43bf77079c697b42e4908b184faad6dfb26c0cb8cfc8f8211d63307274468
BLAKE2b-256 checksum
How to use checksums
b2c1f64122928faf8e1a12076982deb79ef3efe648cef1aca6ba47b10b625a28
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / spike_recorder-0.3.3-cp36-cp36m-macosx_10_9_x86_64.whl

Download URL spike_recorder-0.3.3-cp36-cp36m-macosx_10_9_x86_64.whl
Size 1.9 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
c95c0663e0efccce60413c2a8f6e48a1f03a49993268e38f22e566af72dba54b
BLAKE2b-256 checksum
How to use checksums
57f7d9f547afa0f60ddaa63aafa483743836e24c38c0a2b051af65a51254da17
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Security for spike-recorder 0.3.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page