pyFCS

Purpose

Python module with C-level implementation of point-process correlations functions. These functions were primarily designed for computation of correlation functions for Fluorescence Correlation Spectroscopy (FCS)¹ and derivative methods.

Correlations can be computed easily

import numpy as np
import pyFCS as fcs

# Further importats and data processing
# should produce timesT and timesU as
# monotonicaly increasing non-gegative integer arrays

corrl = fcs.correlate(times, times, bins)

Advanced FCS

Beyond standard auto and cross-correlation of FCS data, pyFCS also implements calculation of correlation with weights for:

Fluorescence Lifetime Correlation Spectroscopy (FLCS)²
purified FCS (pFCS)³
filtered FCS (fFCS)⁴ (the combination of FLCS and pFCS)

All of these will have the same basic form:

import numpy as np
import pyFCS as fcs

# Code gets data for photons and nanotimes,
# Generates the appropriate filter functions
# And provides the times in times
# (in FLCS usually T/U arrays are the same)
# and weights

corrl = fcs.correlate(times, times, bins, weightsT=weights, weightsU=weights)

Implementation

Most of the code is implemented in C for maximal efficiency. The algorithms are all adapted from¹. If any issues are encountered that cannot be solved, especially segfaults/kernel crashes, please open an issue in github, providing the minimal code necessary to reproduce the crash.

Laurence et. al. (2006) Fast, flexible algorithm for calculating photon correlations. Optics Letters , 31 (6), 829–831 ↩ ↩²
Bohmer et. al. (2002) Time-resolved fluorescence correlation spectroscopy. Chem. Phys. Let. 353 (5-6) 439-445 ↩
Laurence et. al.(2007) Correlation Spectroscopy of Minor Fluorescent Species: Purification and Distribution Analysis. Biophysical Journal. 92, (6), 2184-2198 ↩
Felekyan et. al. (2012) Filtered FCS: Species Auto- and Cross-Correlation Functions Highlight Binding and Dynamics in Biomolecules. ChemPhysChem, 13 (4) 1036-1053 ↩

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BLAKE2b-256	`61cbbda85e8840f837ddd0847fcda5765bbae83e2016fe4a355f9214cba8a563`

Algorithm	Hash digest
SHA256	`643051f55349a12144bc86691975f9396971b44b1c2bd8fad9aaf5bf602c012c`
MD5	`495cb5630134d4523fc44323dd701184`
BLAKE2b-256	`491ccad7d94548dc2bb68fe0ffcf82ada2b282f719079f25c0a987ca5f141b69`

Algorithm	Hash digest
SHA256	`8cfeebf05fda2dcd86be36e138201b6f0e746084aea4dbe25223dce336b2083d`
MD5	`903cdd67b9dbafbec64a3622e33857ea`
BLAKE2b-256	`8b7dbe1068138cc9a2c61ada1c8460d2763c3eaf67b68866d34cb003e512b5ea`

Algorithm	Hash digest
SHA256	`0770adb1a22df5cc4814ad363aee78ecb315e4467d9a1c3547c0d91fa5cf9430`
MD5	`a87705ee6fab82d477096fd45c5a72ad`
BLAKE2b-256	`19f47462b1bf8e6ee7dbed80d736a782468537d3a5054b05b7ec5b38774f8990`

pyFCS 0.1.3

pyFCS

Purpose

Advanced FCS

Implementation

Key dates

1 maintainer

Credits

License expression

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Source Distribution

Built Distributions

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Algorithm	Hash digest
SHA256	`dee501179f13019d1ef15492a2ced5db9a060e4605b4e9d633e738b648dc174d`
MD5	`929766b24dacfbd7310263a92e033ac6`
BLAKE2b-256	`2c6df97fbae573f93feeb9ea75f7c4f828b6c722f74a614ebd47529c53c70082`

Algorithm	Hash digest
SHA256	`bdd60afa7defe80f3df58841be00174e4d62bdecc3d7a393856980034212c957`
MD5	`d4634d2401f26bcca7b2c7e034d029b3`
BLAKE2b-256	`37b01d952b7e0c483c4eae1a0cf814c1fd8e40b8a48ffa5ef6623b4e2b5e99cf`

Algorithm	Hash digest
SHA256	`5844ffffdbd45d1ef602ed50a2c2b5d23237a4f604ed260735eff3b9f3745507`
MD5	`44a6595fcb81fc48b6f93fdec48191dd`
BLAKE2b-256	`937e65fdbe59919ff87c27dd1f8b0f782d8a330050010b471f9bfe9e1b661e96`

Algorithm	Hash digest
SHA256	`dca7843d884e254bee52d7a06e782ad27aa7fe5cf572a08307920ab812327514`
MD5	`edf45ee659ef5a8332d569ff92c7bf74`
BLAKE2b-256	`76a93cb2b34ed79fa374fe0a9e3fc6452c6b8dc0f7730af9ea95682f34614e7a`

Algorithm	Hash digest
SHA256	`6873b333fb54d2d65013122f4e72bf88c8e62966b700098019181cd41b0e6d5d`
MD5	`78871c7d8143ee064689fd318f46bb87`
BLAKE2b-256	`a5dd243a6311bb0e174d8e7e9b0da4dbf9403b00780995584a186856db772008`

Algorithm	Hash digest
SHA256	`45160f0cf6a295dfb034f88e5efdb8ffd54329806b5649a1753d276f76f18989`
MD5	`a52763e46a31c754dbedb10e608849e2`
BLAKE2b-256	`7c82d2b6cd077dc27929b63d486e3e861e2596b0b2fab1bcaec248846c6c05fd`

Algorithm	Hash digest
SHA256	`3fc3ede789716a919d33ca4c736907507c44d98c281a13e05047a9e653b53d93`
MD5	`8d7385fefe519947b32d43c1471d8b47`
BLAKE2b-256	`189f6b7089d99e06e67f37b677982b1c735bc1b23a5900da6b9a42dee44d4885`

Algorithm	Hash digest
SHA256	`631dd4015ee988b93b2ddec2b5b6880cb6e7686b6cadb8585903bee54eb95447`
MD5	`0144571c135af749563e29a042412638`
BLAKE2b-256	`86119e50e8de7f32486a396e8d0b5d421ecab80d74a3975f8934a8284d57ac0b`

Algorithm	Hash digest
SHA256	`9fc9bec8a1363f848b33d80f6ba31c3406e5d70a6350cb7ef158b32c3419a328`
MD5	`8cdb2de1a16cf2aa11ff70b74e0e0865`
BLAKE2b-256	`cd2bee47fd3d69a91be49d79d564842af4016b734a57d1d7b7216ccda0ab623f`

Algorithm	Hash digest
SHA256	`97ad50a4bc4110e414f4735ac3da98b1e89261c40a83101afaf3c62fe8038fe6`
MD5	`0b68064fae3e61754ca6740ff0290eb7`
BLAKE2b-256	`3ff6425c2cef16dba4b3a3009c3ea2445e329a9955c8b0a442ed7259095e7178`