Skip to main content

multipletau

PyPI Version Tests Status Coverage Status Docs Status

Multipe-tau correlation is computed on a logarithmic scale (less data points are computed) and is thus much faster than conventional correlation on a linear scale such as numpy.correlate.

Installation

Multipletau supports Python 2.7 and Python 3.3+ with a common codebase. The only requirement for multipletau is NumPy (for fast operations on arrays). Install multipletau from the Python package index:

pip install multipletau

Documentation

The documentation, including the reference and examples, is available on readthedocs.io.

Usage

import numpy as np
import multipletau
a = np.linspace(2,5,42)
v = np.linspace(1,6,42)
multipletau.correlate(a, v, m=2)
array([[   0.        ,  569.56097561],
       [   1.        ,  549.87804878],
       [   2.        ,  530.37477692],
       [   4.        ,  491.85812017],
       [   8.        ,  386.39500297]])

Citing

The multipletau package should be cited like this (replace “x.x.x” with the actual version of multipletau that you used and “DD Month YYYY” with a matching date).

Paul Müller (2012) Python multiple-tau algorithm (Version x.x.x) [Computer program]. Available at https://pypi.python.org/pypi/multipletau/ (Accessed DD Month YYYY)

You can find out what version you are using by typing (in a Python console):

>>> import multipletau
>>> multipletau.__version__
'0.3.0'

Release files for multipletau 0.3.0

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

Source distribution (sdist)

Source distribution for multipletau 0.3.0
File Size Uploaded
multipletau-0.3.0.tar.gz 94.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for multipletau 0.3.0
File Interpreter ABI Platform
multipletau-0.3.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 105.9 kB

Release files / multipletau-0.3.0.tar.gz

Download URL multipletau-0.3.0.tar.gz
Size 94.0 kB
Tags Source
SHA-256 checksum
How to use checksums
38843d2e6b7db2d711710669c9dc9413e0539368ca80c7077b6a123cd28dc307
BLAKE2b-256 checksum
How to use checksums
0a13cdd78ce44671fa79dcc72d94b55659e3d14f3510aa8cc6f74cd3d1b43b0e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.14

Release files / multipletau-0.3.0-py2.py3-none-any.whl

Download URL multipletau-0.3.0-py2.py3-none-any.whl
Size 11.9 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
eb38ffb2beff78b3bd3f8212e1ae5a84688b09efeebcd530ab7f5709938a50da
BLAKE2b-256 checksum
How to use checksums
96f87e540628ceba9da487962159bee56d173c86c3b1bbd62e0865b2e9269c1b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.14

Release history Release notifications | RSS feed

0.4.1

2 release files

0.4.0

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

This release

0.3.0 This release

2 release files

0.2.0

2 release files

0.1.9

2 release files

0.1.8

2 release files

0.1.7

1 release file

0.1.6

1 release file

0.1.5

1 release file

0.1.4

1 release file

0.1.3

1 release file

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