Haussmeister: Handling 2-photon imaging datasets

Release:0.2.0
Date:Mar 10, 2017
Email:christsc@gmx.de
GitHub:https://github.com/neurodroid/haussmeister

Getting started

Define your recording as a pipeline2p.ThorExperiment:

from haussio import pipeline2p as p2p

experiment = p2p.ThorExperiment(
    "2016/2016-03/2016-03-21/DKL7-verm6f_002_016",  # Path to experiment (from root_path)
    "A",  # Channel
    "CE",  # Brain region
    "DKL7-verm6f_002_sync_016",  # ThorSync file name
    "vr/20160321_0029",  # Corresponding VR file
    mc_method="hmmc",  # Motion correction method
    root_path="/Volumes/fileserver/data/",  # Root path of your data
    seg_method="cnmf"  # Segmentation method
)

Preprocess your data (currently this involves motion correction only):

p2p.thor_preprocess(experiment)

Segment data and extract fluorescence signals:

p2p.thor_extract_roi(data)

Indices and tables