Mercurial > repos > greg > linear_fascile_evaluation
comparison linear_fascile_evaluation.py @ 1:84a2e30b5404 draft
Uploaded
author | greg |
---|---|
date | Tue, 28 Nov 2017 13:30:57 -0500 |
parents | cbfa8c336751 |
children | 0ddfcb3b5ce6 |
comparison
equal
deleted
inserted
replaced
0:cbfa8c336751 | 1:84a2e30b5404 |
---|---|
9 import matplotlib | 9 import matplotlib |
10 | 10 |
11 from dipy.viz.colormap import line_colors | 11 from dipy.viz.colormap import line_colors |
12 from dipy.viz import fvtk | 12 from dipy.viz import fvtk |
13 from mpl_toolkits.axes_grid1 import AxesGrid | 13 from mpl_toolkits.axes_grid1 import AxesGrid |
14 from dipy.data import read_stanford_labels, fetch_stanford_t1, read_stanford_t1 | |
14 | 15 |
15 parser = argparse.ArgumentParser() | 16 parser = argparse.ArgumentParser() |
16 parser.add_argument('--candidates', dest='candidates', help='Candidates selection') | 17 parser.add_argument('--candidates', dest='candidates', help='Candidates selection') |
17 parser.add_argument('--output_life_candidates', dest='output_life_candidates', help='Output life candidates') | 18 parser.add_argument('--output_life_candidates', dest='output_life_candidates', help='Output life candidates') |
18 parser.add_argument('--output_life_optimized', dest='output_life_optimized', help='Output life optimized streamlines') | 19 parser.add_argument('--output_life_optimized', dest='output_life_optimized', help='Output life optimized streamlines') |
20 parser.add_argument('--output_error_histograms', dest='output_error_histograms', help='Output error histograms') | 21 parser.add_argument('--output_error_histograms', dest='output_error_histograms', help='Output error histograms') |
21 parser.add_argument('--output_spatial_errors', dest='output_spatial_errors', help='Output spatial errors') | 22 parser.add_argument('--output_spatial_errors', dest='output_spatial_errors', help='Output spatial errors') |
22 | 23 |
23 args = parser.parse_args() | 24 args = parser.parse_args() |
24 | 25 |
25 if not op.exists(args.candidates): | 26 # We'll need to know where the corpus callosum is from these variables. |
26 from streamline_tools import * | 27 hardi_img, gtab, labels_img = read_stanford_labels() |
27 else: | 28 labels = labels_img.get_data() |
28 # We'll need to know where the corpus callosum is from these variables: | 29 cc_slice = labels == 2 |
29 from dipy.data import (read_stanford_labels, fetch_stanford_t1, read_stanford_t1) | 30 fetch_stanford_t1() |
30 hardi_img, gtab, labels_img = read_stanford_labels() | 31 t1 = read_stanford_t1() |
31 labels = labels_img.get_data() | 32 t1_data = t1.get_data() |
32 cc_slice = labels == 2 | 33 data = hardi_img.get_data() |
33 fetch_stanford_t1() | |
34 t1 = read_stanford_t1() | |
35 t1_data = t1.get_data() | |
36 data = hardi_img.get_data() | |
37 | 34 |
38 # Read the candidates from file in voxel space: | 35 # Read the candidates from file in voxel space: |
39 candidate_sl = [s[0] for s in nib.trackvis.read(args.candidates, points_space='voxel')[0]] | 36 candidate_sl = [s[0] for s in nib.trackvis.read(args.candidates, points_space='voxel')[0]] |
40 # Visualize the initial candidate group of streamlines | 37 # Visualize the initial candidate group of streamlines |
41 # in 3D, relative to the anatomical structure of this brain. | 38 # in 3D, relative to the anatomical structure of this brain. |