More trying to reduce memory usage'

tests/__init__.py

@@ -285,21 +285,15 @@ def make_random_mask(filename, shape, xform, premask=None):
 
     mask = np.zeros(shape, dtype=np.uint8)
 
-    if premask is None:
-        numones = np.random.randint(1, np.prod(shape) / 100)
-        xc      = np.random.randint(0, shape[0], numones)
-        yc      = np.random.randint(0, shape[1], numones)
-        zc      = np.random.randint(0, shape[2], numones)
-        mask[xc, yc, zc] = 1
-    else:
-        xc, yc, zc = np.where(premask)
-        numones    = np.random.randint(1, len(xc))
-        idxs       = np.random.randint(1, len(xc), numones)
-        xc         = xc[idxs]
-        yc         = yc[idxs]
-        zc         = zc[idxs]
-
-        mask[xc, yc, zc] = 1
+    numones = np.random.randint(1, np.prod(shape) / 100)
+    xc      = np.random.randint(0, shape[0], numones)
+    yc      = np.random.randint(0, shape[1], numones)
+    zc      = np.random.randint(0, shape[2], numones)
+
+    mask[xc, yc, zc] = 1
+
+    if premask is not None:
+        mask[premask == 0] = 0
 
     img = fslimage.Image(mask, xform=xform)
     img.save(filename)

tests/test_atlases.py

@@ -20,7 +20,7 @@ import pytest
 import tests
 import fsl.utils.transform as transform
 import fsl.data.atlases    as atlases
-import fsl.data.image     as fslimage
+import fsl.data.image      as fslimage
 
 
 datadir = op.join(op.dirname(__file__), 'testdata')
@@ -222,7 +222,8 @@ def test_load_atlas():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical')
+    probatlas    = reg.loadAtlas('harvardoxford-cortical',
+                                 indexed=True, calcRange=False, loadData=False)
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 
@@ -236,7 +237,8 @@ def test_find():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical')
+    probatlas    = reg.loadAtlas('harvardoxford-cortical',
+                                 indexed=True, calcRange=False, loadData=False)
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 
@@ -268,7 +270,8 @@ def test_prepareMask():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical')
+    probatlas    = reg.loadAtlas('harvardoxford-cortical',
+                                 indexed=True, loadData=False, calcRange=False)
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 
@@ -276,13 +279,16 @@ def test_prepareMask():
 
         ashape        = list(atlas.shape[:3])
         m2shape       = [s * 1.5 for s in ashape]
-        goodmask1     = fslimage.Image(np.random.random(ashape),
-                                       xform=atlas.voxToWorldMat)
+
+        goodmask1     = fslimage.Image(
+            np.array(np.random.random(ashape), dtype=np.float32),
+            xform=atlas.voxToWorldMat)
+
         goodmask2, xf = goodmask1.resample(m2shape)
         goodmask2     = fslimage.Image(goodmask2, xform=xf)
 
         wrongdims     = fslimage.Image(
-            np.random.random(list(ashape) + [10]))
+            np.random.random(list(ashape) + [2]))
         wrongspace    = fslimage.Image(
             np.random.random((20, 20, 20)),
             xform=transform.concat(atlas.voxToWorldMat, np.diag([2, 2, 2, 1])))

tests/test_atlases_query.py

@@ -34,11 +34,12 @@ def _repeat(iterator, n):
             yield elem
 
 
-_atlases = cache.Cache(maxsize=1)
+_atlases = cache.Cache()
 def _get_atlas(atlasID, res, summary=False):
     atlas = _atlases.get((atlasID, res, summary), default=None)
     if atlas is None:
-        if summary or atlasID in ('talairach', 'striatum-structural', 'jhu-labels'):
+        if summary or atlasID in ('talairach', 'striatum-structural',
+                                  'jhu-labels'):
             kwargs = {}
         else:
             kwargs = {'loadData'  : False,
@@ -66,7 +67,7 @@ def _random_atlas(atype, res, summary=False):
 
 # Generate a mask which tells us which
 # voxels in the atlas are all zeros
-_zero_masks = {}
+_zero_masks = cache.Cache(maxsize=5)
 def _get_zero_mask(aimg):
 
     atlasID = aimg.desc.atlasID