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Read/Write streamline files

Overview

dipy can read and write many different file formats. In this example we give a short introduction on how to use it for loading or saving streamlines.

Read Frequently Asked Questions

import numpy as np
from dipy.data import get_data
from nibabel import trackvis
  1. Read/write trackvis streamline files with nibabel.
fname = get_data('fornix')
print(fname)

streams, hdr = trackvis.read(fname)
streamlines = [s[0] for s in streams]

Similarly you can use trackvis.write to save the streamlines.

  1. Read/writh streamlines with numpy.
streamlines_np = np.array(streamlines, dtype=np.object)
np.save('fornix.npy', streamlines_np)

streamlines2 = list(np.load('fornix.npy'))

3. We also work on our HDF5 based file format which can read/write massive datasets (as big as the size of you free disk space). With Dpy we can support

  • direct indexing from the disk
  • memory usage always low
  • extentions to include different arrays in the same file

Here is a simple example.

from dipy.io.dpy import Dpy
dpw = Dpy('fornix.dpy', 'w')

Write many streamlines at once.

dpw.write_tracks(streamlines2)

Write one track

dpw.write_track(streamlines2[0])

or one track each time.

for t in streamlines:
    dpw.write_track(t)

dpw.close()

Read streamlines directly from the disk using their indices

dpr = Dpy('fornix.dpy', 'r')
some_streamlines = dpr.read_tracksi([0, 10, 20, 30, 100])
dpr.close()


print(len(streamlines))
print(len(some_streamlines))

Example source code

You can download the full source code of this example. This same script is also included in the dipy source distribution under the doc/examples/ directory.