Skip to main content

Scientific tool for fitting correlation curves on a logarithmic plot.

Project description

PyCorrFit can be used for fitting any data on a semi-log plot. The program focusses on Fluorescence Correlation Spectroscopy (FCS) and comes with a couple of features that are crucial for FCS data analysis:

  • Averaging of curves

  • Background correction

  • Batch processing

  • Overlay tool to identify outliers

  • Fast simulation of model parameter behavior

  • Session management

  • User-defined model functions

  • High quality plot export using LaTeX (bitmap or vector graphics)

For a full list of features and supported file formats visit http://pycorrfit.craban.de. There are also precompiled binaries for various systems.

This package provides the Python module pycorrfit and its graphical user interface. The graphical user interface is written with wxPython. A HowTo for the installation of the latest version of PyCorrFit using pip can be found there:

https://github.com/paulmueller/PyCorrFit/wiki/Installation_pip

Further reading:

Project details


Download files

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

Source Distribution

pycorrfit-0.8.9.tar.gz (1.0 MB view details)

Uploaded Source

Built Distributions

pycorrfit-0.8.9-cp27-none-win_amd64.whl (790.8 kB view details)

Uploaded CPython 2.7 Windows x86-64

pycorrfit-0.8.9-cp27-none-win32.whl (789.3 kB view details)

Uploaded CPython 2.7 Windows x86

pycorrfit-0.8.9-cp27-none-macosx_10_9_intel.whl (812.5 kB view details)

Uploaded CPython 2.7 macOS 10.9+ intel

File details

Details for the file pycorrfit-0.8.9.tar.gz.

File metadata

  • Download URL: pycorrfit-0.8.9.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pycorrfit-0.8.9.tar.gz
Algorithm Hash digest
SHA256 9cc2c0377d137c7f908ca8a5730d0ea943a969f1cd0e4abee4d25720908e4994
MD5 ac2e5d29133ace048130a5991462d028
BLAKE2b-256 a7587854c418c057d85120daa66760593460d6bcbf76c3a57e9376232eaf75a2

See more details on using hashes here.

File details

Details for the file pycorrfit-0.8.9-cp27-none-win_amd64.whl.

File metadata

File hashes

Hashes for pycorrfit-0.8.9-cp27-none-win_amd64.whl
Algorithm Hash digest
SHA256 c36a34ead6252e91bcac94d6a349fc6dc772924217ae553cc7cc1f8c824465b9
MD5 72213c2070ebfc30874ac8c2b5821ece
BLAKE2b-256 b07de21a5c159bc4e1cc1f2caf238fe013abe826699f18930bcad54e9174fddd

See more details on using hashes here.

File details

Details for the file pycorrfit-0.8.9-cp27-none-win32.whl.

File metadata

File hashes

Hashes for pycorrfit-0.8.9-cp27-none-win32.whl
Algorithm Hash digest
SHA256 2b7c6ddcc29dfcb10ce64210585a73618813acf8ba9420f81e4d962ede819f37
MD5 8ae63723a2fd4769ffc7ba88c0d9b6f1
BLAKE2b-256 678c88ca26417e98bdd81c808e4b857b76587cba43bd4fc31867c128e0da7824

See more details on using hashes here.

File details

Details for the file pycorrfit-0.8.9-cp27-none-macosx_10_9_intel.whl.

File metadata

File hashes

Hashes for pycorrfit-0.8.9-cp27-none-macosx_10_9_intel.whl
Algorithm Hash digest
SHA256 237ff9b0d656a36bd18035c9bfdd23d04cdebe7d10a8055988e7dd2a446e07ab
MD5 2d322a5a2e0270d51d202b6026552e21
BLAKE2b-256 74eaaef8e55f379bb81f13853bc04ee01abf36deca28d28c47e3233bad880d93

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page