docker-python/tests/test_dipy.py at master · HpcDataLab/docker-python · GitHub

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import unittest

import os.path

import numpy as np

import numpy.testing as npt

import tempfile

from dipy.core.graph import Graph

from dipy.denoise.enhancement_kernel import EnhancementKernel

from dipy.tracking.fbcmeasures import FBCMeasures

from dipy.core.sphere import Sphere

from dipy.viz import window, actor

class TestDipy(unittest.TestCase):

def test_scene(self):

xyz = 10 * np.random.rand(100, 3)

colors = np.random.rand(100, 4)

radii = np.random.rand(100) + 0.5

sphere_actor = actor.sphere(centers=xyz, colors=colors, radii=radii)

scene = window.Scene()

scene.add(sphere_actor)

self.assertEqual((0, 0), scene.GetSize())

def test_graph(self):

g = Graph()

g.add_node('a', 5)

g.add_node('b', 6)

self.assertEqual(2, len(g.node))

# From: https://github.com/nipy/dipy/blob/51234a4437638535ff8f6e5819e14ccf7e1d1483/dipy/tracking/tests/test_fbc.py

def test_fbc(self):

"""Test the FBC measures on a set of fibers"""

# Generate two fibers of 10 points

streamlines = []

for i in range(2):

fiber = np.zeros((10, 3))

for j in range(10):

fiber[j, 0] = j

fiber[j, 1] = i*0.2

fiber[j, 2] = 0

streamlines.append(fiber)

# Create lookup table.

# A fixed set of orientations is used to guarantee deterministic results

D33 = 1.0

D44 = 0.04

t = 1

sphere = Sphere(xyz=np.array([[0.82819078, 0.51050355, 0.23127074],

[-0.10761926, -0.95554309, 0.27450957],

[0.4101745, -0.07154038, 0.90919682],

[-0.75573448, 0.64854889, 0.09082809],

[-0.56874549, 0.01377562, 0.8223982]]))

k = EnhancementKernel(D33, D44, t, orientations=sphere,

force_recompute=True)

# run FBC

fbc = FBCMeasures(streamlines, k, verbose=True)

# get FBC values

fbc_sl_orig, clrs_orig, rfbc_orig = \

fbc.get_points_rfbc_thresholded(0, emphasis=0.01)

# check mean RFBC against tested value

npt.assert_almost_equal(np.mean(rfbc_orig), 1.0500466494329224)

docker-python/tests/test_dipy.py at master · HpcDataLab/docker-python · GitHub

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