Merge pull request #233 from berkeley-stat159/find_activated

Find activated

code/utils/find_activated_voxel_functions.py → code/utils/functions/find_activated_voxel_functions.py

@@ -86,32 +86,18 @@ def find_activated_voxel(shape, p):
         The index of our activated voxels
         position1...4 correspond to the cond001...4 .txt in model_one
     """
-    loc1 = [i for i,j in enumerate(p[1,...]) if j < 0.05]
-    loc2 = [i for i,j in enumerate(p[2,...]) if j < 0.05]
-    loc3 = [i for i,j in enumerate(p[3,...]) if j < 0.05]
-    loc4 = [i for i,j in enumerate(p[4,...]) if j < 0.05]
+    # get the number of predictors(betas) first
+    n = p.shape[0]-1
+    loc={}
+    lst=[]
+    position=[]
+    for t in range(1,n+1):
+        loc["loc{0}".format(t)] = [i for i,j in enumerate(p[t,...]) if j < 0.05]
+        for i in loc["loc{0}".format(t)]:
+            position.append(get_index(shape,i))
+        position = np.asarray(position)
+        lst.append(position)
+        position=[]
 
-    position1 = []
-    for i in loc1:
-        position1.append(get_index(shape, i))
-
-    position2 = []
-    for i in loc2:
-        position2.append(get_index(shape, i))
-
-    position3 = []
-    for i in loc3:
-        position3.append(get_index(shape, i))
-
-    position4 = []
-    for i in loc4:
-        position4.append(get_index(shape, i))
-
-
-    position1 = np.asarray(position1)
-    position2 = np.asarray(position2)
-    position3 = np.asarray(position3)
-    position4 = np.asarray(position4)
-
-    return position1, position2, position3, position4
+    return lst
 

code/utils/scripts/find_activated_voxel_script.py

@@ -15,9 +15,9 @@
 beta, t, df,p=t_test(data,X_matrix_high_res)
 shape = data.shape[:3]
 
-position1,position2, position3,position4 = find_activated_voxel(shape, p)
+lst = find_activated_voxel(shape, p)
 location_of_txt="../txt_files/"
-np.savetxt(location_of_txt+'ds005_sub001_t1r1_position1.txt',position1,fmt='%i')
-np.savetxt(location_of_txt+'ds005_sub001_t1r1_position2.txt',position2,fmt='%i')
-np.savetxt(location_of_txt+'ds005_sub001_t1r1_position3.txt',position3,fmt='%i')
-np.savetxt(location_of_txt+'ds005_sub001_t1r1_position4.txt',position4,fmt='%i')
+
+for i in range(1,len(lst)+1):
+    np.savetxt(location_of_txt+'ds005_sub001_t1r1_position%s.txt'%(str(i)),lst[i-1].ravel())
+

code/utils/tests/test_find_activated_voxel.py

@@ -0,0 +1,33 @@
+import os
+import sys
+import numpy as np
+import nibabel as nib
+from nose.tools import assert_equal
+from numpy.testing import assert_almost_equal, assert_array_equal
+
+
+# Add path to functions to the system path.
+sys.path.append(os.path.join(os.path.dirname(__file__), "../functions/"))
+
+from find_activated_voxel_functions import *
+project_path=os.path.join(os.path.dirname(__file__), '../../../')
+
+
+def test_size():
+    shape = (2, 3, 2)
+    assert_equal(size(shape), 12)
+    assert_equal(size(shape, axis=0),2)
+
+def test_get_increment():
+    assert_equal(get_increment((2, 4)),[4, 1])
+    assert_equal(get_increment((2, 2, 2)),[4, 2, 1])
+
+def test_get_index():
+    shape = (2, 2, 2)
+    assert_equal(get_index(shape, 4),(1, 0, 0))
+    assert_equal(get_index(shape, 2),(0, 1, 0))
+
+
+def test_find_activated_voxel():
+    p = np.array([[ 0.39764537],[ 0.005514348],[ 0.04195935]])
+    assert_array_equal(find_activated_voxel((2, 3, 4),p)[0],[[0, 0, 0]])