cell detection in calcium imaging recordings
BinaryFile replaces BinaryRWfile as a class and has a method for writing tiffs (ie, for cropping and generating new tifs after loading in a dataset). PyNwb has also been added to the list of dependencies needed for testing.
Fixes the following issues:
rastermap.mapping
for GUINOTE: right-click + drag now zooms the view; right-click once without dragging for cell flipping (CELL / NOT CELL)
Addresses the following bugs:
sparse_detection
mode to GUInp.bool
bin_frames
has also been patched to accommodate cases in which current batch has fewer frames than bin_size
.np.asanyarray
needs explicit input argumentsNew additions:
np.memmap
for file reading/writing (~20% speed up)Fixes several bugs:
Includes:
Fixes the following bugs:
ops[nonrigid]
set to false.suite2p can now handle numpy inputs to the main processing steps of the software! check out this notebook (thanks @chriski777!) with the exposed functions for registration, cell detection and ROI extraction.
fixing some bugs in v0.10.0
Also removing mkl-fft
dependency from library and replacing with pytorch fft's. Now suite2p can be installed from pip entirely
Fixes bugs in v0.9 with cellpose integration
Adds several new features, outlined here: https://docs.google.com/presentation/d/1UDikmED-dG3zwXz2uyavRNr5sGzjas7wPbP4IjDQ3HY/edit#slide=id.p1
pip install cellpose
in your suite2p environment and check out the ops['anatomical_only']
key.ops['norm_frames']
(set to True by default) to decrease noise in registrationops.npy
prohibitively largeops['classfile']
that allows user to specify classifier used in pipelineops['multiplane_parallel']
to run planes simultaneously on a server