Command-line tool and python library for visualising small 3D datasets
Simple matplotlib-based tool for viewing small amounts of 3D image data; helpful for debugging. Supports python 2.7 and 3.4+.
Adapted from this matplotlib recipe.
pip install smalldataviewer
Some file types require additional dependencies:
usage: smalldataviewer [-h] [-i INTERNAL_PATH] [-t TYPE] [-o ORDER] [-f OFFSET] [-s SHAPE] [-v] path positional arguments: path Path to HDF5, N5, zarr, npy, npz or JSON file containing a 3D dataset optional arguments: -h, --help show this help message and exit -i INTERNAL_PATH, --internal_path INTERNAL_PATH Internal path of dataset inside HDF5, N5, zarr or npz file. If JSON, assumes the outerobject is a dict, and internal_path is the key of the array -t TYPE, --type TYPE Dataset file type. Inferred from extension if not given. -o ORDER, --order ORDER Order of spatial axes for axis labelling purposes. Data is not transposed: dimension 0 will be scrolled through, dimension 1 will be on the up-down axis, dimension 2 will be on the left-right axis, anddimension 3, if it exists, will be used as the colour channels. Default "zyx". -f OFFSET, --offset OFFSET 3D offset of ROI from (0, 0, 0) in pixels, in the form "<scroll>,<vertical>,<horizontal>" -s SHAPE, --shape SHAPE 3D shape of ROI in pixels, in the form "<scroll>,<vertical>,<horizontal>" -v, --verbose Increase logging verbosity
smalldataviewer my_data.hdf5 -i /my_group/my_volume
Note: because of the circumstances under which python holds file descriptors open, and under which matplotlib blocks, the executable form reads the data into memory in its entirety. If your data are too big for this, look at small chunks with the oFfset and Shape options.
from smalldataviewer import DataViewer, dataviewer_from_file import numpy as np data = np.random.random((30, 100, 100)) viewer = DataViewer(data) viewer.show() # or matplotlib.pyplot.show() viewer2 = dataviewer_from_file(dataviewer, "my_data.npz", "volume") viewer2.show()
Note: dataviewer_from_file reads the requested data into memory. DataViewer does not, by default. However, you may need to, depending on the rest of your script.
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