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Tools for the analysis of electrophysiological data collected with the Axona or openephys recording systems.
ephysiopy requires python3.7 or greater. The easiest way to install is using pip:
python3 -m pip install ephysiopy
or,
pip3 install ephysiopy
Or similar.
For openephys-type analysis there are two main entry classes depending on whether you are doing OpenEphys- or Axona-based analysis. Both classes inherit from the same abstract base class (TrialInterface) and so share a high degree of overlap in what they can do. Because of the inheritance structure, the methods you call on each concrete class are the same
from ephysiopy.io.recording import OpenEphysBase
trial = OpenEphysBase("/path/to/top_level")
The "/path/to/top_level" bit here means that if your directory hierarchy looks like this:
::
├── 2020-03-20_12-40-15
├── Record Node 101
| └── settings.xml
experiment1
| └── recording1
| ├── structure.oebin
| ├── sync_messages.txt
| ├── continuous
| | └── Neuropix-PXI-107.0
| | └── continuous.dat
| └── events
├── Record Node 102
Then the "/path/to/top_level" is the folder "2020-03-20_12-40-15"
On insantiation of an OpenEphysBase object the directory structure containing the recording is traversed and various file locations are noted for later processing of the data in them.
The pos data is loaded by calling the load_pos_data() method:
npx.load_pos_data(ppm=300, jumpmax=100, cm=True)
Note ppm = pixels per metre, used to convert pixel coords to cms. jumpmax = maximum "jump" in cms for point to be considered "bad" and smoothed over
The same principles apply to the other classes that inherit from TrialInterface (AxonaTrial and OpenEphysNWB)
A mixin class called FigureMaker allows consistent plots, regardless of recording technique. All plotting functions there begin with "plot" e.g "_rate_map" and return an instance of a matplotlib axis. The plotting functions in turn call a corresponding "get" function e.g. "get_rate_map" that will return an instance of the BinnedData class containing the binned data, the histogram edges, the variable being binned (XY, SPEED etc) and the map type (RATE, SPK, POS).
FAQs
Analysis of electrophysiology data
We found that ephysiopy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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