Stimfit

Stimfit

Electrophysiology signal analysis

Description

A patch-clamp session leaves you with a pile of traces in assorted formats. A general plotting tool either cannot open them or cannot measure a peak, and exporting to measure by hand is slow and error-prone.
Stimfit was built for exactly this data. It reads electrophysiology recordings directly and does event detection and fitting right on the trace - spontaneous events, presynaptic action potentials and postsynaptic currents are all measurable without exporting anything.

An embedded Python shell exposes NumPy and SciPy, so when the stock algorithms are not enough you write a few lines of script. Recent releases also add a dark trace display, a refreshed toolbar and better graph scaling.

Features



Many formats: reads CFS, Axon text, ASCII, HDF5, HEKA and Igor binary waves, with Biosig handling file I/O underneath.

Event detection: finds spontaneous events in a recording, filters by polarity and measures the ones you select.

Fitting and quantification: model testing and quantitative analysis of patch-clamp signals, with peak and decay parameters read straight off the plot.

Python scripting: an embedded Python shell, extensible with NumPy and SciPy.