added 35-shell isbi2015 data

dmipy/data/saved_acquisition_schemes.py

@@ -1,9 +1,12 @@
 import numpy as np
 from os.path import join
+import os
 import pkg_resources
+import urllib2
 from ..core.acquisition_scheme import (
     acquisition_scheme_from_bvalues,
-    acquisition_scheme_from_gradient_strengths)
+    acquisition_scheme_from_gradient_strengths,
+    acquisition_scheme_from_schemefile)
 
 _GRADIENT_TABLES_PATH = pkg_resources.resource_filename(
     'dmipy', 'data/gradient_tables'
@@ -66,3 +69,22 @@ def duval_cat_spinal_cord_3d_acquisition_scheme():
     TE[:] = 0.0472
     return acquisition_scheme_from_gradient_strengths(
         G, bvecs, delta, Delta, TE, min_b_shell_distance=20e6)
+
+
+def isbi2015_white_matter_challenge_scheme():
+    "Returns 35-shell ISBI 2015 challenge DmipyAcquisitionScheme."
+    isbi_data_path = join(DATA_PATH, 'isbi2015_white_matter_challenge')
+    if not os.path.exists(isbi_data_path):
+        os.makedirs(isbi_data_path)
+
+    path_schemefile = (
+        "http://cmic.cs.ucl.ac.uk/wmmchallenge/ISBIdata/seenScheme.txt")
+    filename = 'isbi_schemefile.txt'
+
+    response = urllib2.urlopen(path_schemefile)
+    data = response.read()
+    file_ = open(join(isbi_data_path, filename), 'w')
+    file_.write(data)
+    file_.close()
+
+    return acquisition_scheme_from_schemefile(join(isbi_data_path, filename))

dmipy/data/saved_data.py

@@ -1,4 +1,6 @@
 from os.path import join
+import os
+import urllib2
 import pkg_resources
 import nibabel as nib
 import numpy as np
@@ -128,6 +130,55 @@ def __init__(self):
     return scheme, data
 
 
+def isbi2015_white_matter_challenge():
+    """
+    Downloads and returns the 35-shell multi-delta/Delta/G scheme and data for
+    the fornix and genu data that was used for the ISBI 2015 white matter
+    challenge [1]_.
+
+    Returns
+    -------
+    scheme: DmipyAcquisitionScheme instance,
+        acquisition scheme of the challenge data.
+    data_genu: array of size (3612, 6),
+        contains the DWIs for 6 genu voxels.
+    data_fornix: array of size (3612, 6),
+        contains the DWIs for 6 fornix voxels.
+
+    References
+    ----------
+    .. [1] Ferizi, Uran, et al. "Diffusion MRI microstructure models with in
+        vivo human brain Connectome data: results from a multi-group
+        comparison." NMR in Biomedicine 30.9 (2017)
+    """
+    isbi_data_path = join(DATA_PATH, 'isbi2015_white_matter_challenge')
+
+    if not os.path.exists(isbi_data_path):
+        os.makedirs(isbi_data_path)
+
+    path_genu = (
+        "http://cmic.cs.ucl.ac.uk/wmmchallenge/ISBIdata/seenSignal.txt")
+    path_fornix = (
+        "http://cmic.cs.ucl.ac.uk/wmmchallenge/ISBIdata/seenSignaX.txt")
+
+    filenames = ['genu.txt', 'fornix.txt']
+    paths = [path_genu, path_fornix]
+
+    for filename, path in zip(filenames, paths):
+        response = urllib2.urlopen(path)
+        data = response.read()
+        file_ = open(join(isbi_data_path, filename), 'w')
+        file_.write(data)
+        file_.close()
+
+    data_genu = np.loadtxt(join(isbi_data_path, 'genu.txt'), skiprows=1)
+    data_fornix = np.loadtxt(join(isbi_data_path, 'fornix.txt'), skiprows=1)
+    scheme = (
+        saved_acquisition_schemes.isbi2015_white_matter_challenge_scheme()
+    )
+    return scheme, data_genu, data_fornix
+
+
 def synthetic_camino_data_parallel():
     """The parallel data was generated using the Camino Monte-Carlo
     Diffusion Simulator. See http://camino.cs.ucl.ac.uk/.

dmipy/data/tests/test_saved_data.py

@@ -1,9 +1,11 @@
 from dmipy.data.saved_data import (
     duval_cat_spinal_cord_2d,
-    duval_cat_spinal_cord_3d
+    duval_cat_spinal_cord_3d,
+    isbi2015_white_matter_challenge
 )
 
 
 def test_loading_saved_duval_data_2dand3d():
     scheme, data = duval_cat_spinal_cord_2d()
     scheme, data = duval_cat_spinal_cord_3d()
+    scheme, data1, data2 = isbi2015_white_matter_challenge()