Merge branch 'master' of github.com:gallantlab/pycortex

cortex/dataset/braindata.py

@@ -391,9 +391,11 @@ def __init__(self, dv):
             self.data = dv.data
 
     def __getitem__(self, masktype):
-        s, x = self.dv.subject, self.dv.xfmname
-        mask = db.get_mask(s, x, masktype)
-        return self.dv.copy(self.dv.volume[:,mask].squeeze())
+        try:
+            mask = db.get_mask(self.dv.subject, self.dv.xfmname, masktype)
+            return self.dv.copy(self.dv.volume[:,mask].squeeze())
+        except:
+            self.dv.copy(self.dv.volume[:, mask].squeeze())
 
 def _hash(array):
     '''A simple numpy hash function'''

cortex/dataset/view2D.py

@@ -158,3 +158,7 @@ def __repr__(self):
     def raw(self):
         r, g, b, a = self._to_raw(self.dim1.data, self.dim2.data)
         return VertexRGB(r, g, b, alpha=a, subject=self.dim1.subject)
+
+    @property
+    def vertices(self):
+        return self.raw.vertices

cortex/formats.pyx

@@ -12,7 +12,7 @@ from libc.stdlib cimport atoi, atof
 np.import_array()
 
 def read(str globname):
-    readers = OrderedDict([('gii', read_gii), ('npz', read_npz), ('vtk', read_vtk), ('off', read_off)])
+    readers = OrderedDict([('gii', read_gii), ('npz', read_npz), ('vtk', read_vtk), ('off', read_off), ('stl', read_stl)])
     for ext, func in readers.items():
         try:
             return func(globname+"."+ext)
@@ -63,13 +63,15 @@ def read_stl(str filename):
 
     idx = dict()
     polys = np.empty((npolys,3), dtype=np.uint32)
+    points = []
     for i, pts in enumerate(data['f1']):
         for j, pt in enumerate(pts):
             if tuple(pt) not in idx:
                 idx[tuple(pt)] = len(idx)
+                points.append(tuple(pt))
             polys[i, j] = idx[tuple(pt)]
 
-    return np.array(idx.keys()), polys
+    return np.array(points), polys
 
 @cython.boundscheck(False)
 def read_vtk(str filename):

cortex/mapper/__init__.py

@@ -101,7 +101,7 @@ def __call__(self, data):
                     right = right[..., self.idxmap[1]]
             return left, right
 
-        volume = data.volume
+        volume = np.ascontiguousarray(data.volume)
         volume.shape = len(volume), -1
         volume = volume.T
 

cortex/mapper/samplers.py

@@ -7,6 +7,10 @@ def collapse(j, data):
 
 def nearest(coords, shape, **kwargs):
     valid = ~(np.isnan(coords).all(1))
+    valid = np.logical_and(valid, np.logical_and(coords[:,0] > -.5, coords[:,0] < shape[2]+.5))
+    valid = np.logical_and(valid, np.logical_and(coords[:,1] > -.5, coords[:,1] < shape[1]+.5))
+    valid = np.logical_and(valid, np.logical_and(coords[:,2] > -.5, coords[:,2] < shape[0]+.5))
+
     rcoords = coords[valid].round().astype(int)
     j = np.ravel_multi_index(rcoords.T[::-1], shape, mode='clip')
     #return np.nonzero(valid)[0], j, (rcoords > 0).all(1) #np.ones((valid.sum(),))

cortex/quickflat.py

@@ -15,7 +15,8 @@ def make_figure(braindata, recache=False, pixelwise=True, thick=32, sampler='nea
                 with_dropout=False, with_curvature=False, extra_disp=None, 
                 linewidth=None, linecolor=None, roifill=None, shadow=None,
                 labelsize=None, labelcolor=None, cutout=None, cvmin=None,
-                cvmax=None, cvthr=None, fig=None, extra_hatch=None, **kwargs):
+                cvmax=None, cvthr=None, fig=None, extra_hatch=None,
+                colorbar_ticks=None, **kwargs):
     """Show a Volume or Vertex on a flatmap with matplotlib. Additional kwargs are passed on to
     matplotlib's imshow command.
 
@@ -134,7 +135,7 @@ def make_figure(braindata, recache=False, pixelwise=True, thick=32, sampler='nea
         iy,ix = ((0,-1),(0,-1))
 
     if with_curvature:
-        curv,ee = make(db.get_surfinfo(dataview.subject))
+        curv,ee = make(db.get_surfinfo(dataview.subject),recache=recache)
         if cutout: curv[co==0] = np.nan
         axcv = fig.add_axes((0,0,1,1))
         # Option to use thresholded curvature
@@ -188,9 +189,10 @@ def make_figure(braindata, recache=False, pixelwise=True, thick=32, sampler='nea
     ax.set_ylim(extents[2], extents[3])
 
 
-    if with_colorbar:
+    if with_colorbar and not isinstance(dataview, dataset.Volume2D):
         cbar = fig.add_axes((.4, .07, .2, .04))
-        fig.colorbar(cimg, cax=cbar, orientation='horizontal')
+        fig.colorbar(cimg, cax=cbar, orientation='horizontal',
+                     ticks=colorbar_ticks)
 
     if with_dropout is not False:
         if isinstance(with_dropout, dataset.Dataview):
@@ -262,7 +264,7 @@ def make_figure(braindata, recache=False, pixelwise=True, thick=32, sampler='nea
                               svgfile=svgfile)
             overlays.append(disp)
     for oo in overlays:
-        roitex = oo.get_texture(height, labels=with_labels)
+        roitex = oo.get_texture(height, labels=with_labels, size=labelsize)
         roitex.seek(0)
         oax = fig.add_axes((0,0,1,1))
         roi_im = plt.imread(roitex)
@@ -342,7 +344,8 @@ def make_png(fname, braindata, recache=False, pixelwise=True, sampler='nearest',
         fig.savefig(fname, transparent=True, dpi=dpi)
     else:
         fig.savefig(fname, facecolor=bgcolor, transparent=False, dpi=dpi)
-    plt.close()
+    fig.clf()
+    plt.close(fig)
 
 def make_svg(fname, braindata, recache=False, pixelwise=True, sampler='nearest', height=1024, thick=32, depth=0.5, **kwargs):
     dataview = dataset.normalize(braindata)
@@ -532,7 +535,7 @@ def _make_hatch_image(dropout_data, height, sampler):
     hatchpat = (hx+hy)%(2*hatchspace) < 2
     hatchpat = np.logical_or(hatchpat, hatchpat[:,::-1]).astype(float)
     hatchim = np.dstack([1-hatchpat]*3 + [hatchpat])
-    hatchim[:,:,3] *= (dmap>0.5).astype(float)
+    hatchim[:,:,3] *= np.clip(dmap, 0, 1).astype(float)
 
     return hatchim
 

cortex/webgl/view.py

@@ -527,7 +527,7 @@ def makeMovie(self, animation, filename="brainmovie%07d.png", offset=0,
             for i, sec in enumerate(np.arange(0, anim[-1][1]['idx']+1./fps, 1./fps)):
                 for start, end in anim:
                     if start['idx'] < sec <= end['idx']:
-                        idx = (sec - start['idx']) / (end['idx'] - start['idx'])
+                        idx = (sec - start['idx']) / float(end['idx'] - start['idx'])
                         if start['state'] == 'frame':
                             func = mixes['linear']
                         else:

cortex/xfm.py

@@ -74,7 +74,8 @@ def from_fsl(cls, xfm, func_nii, anat_nii):
         ----------
         xfm : array
             4x4 transformation matrix, loaded from an FSL .mat file, for a transform computed 
-            FROM the func_nii volume TO the anat_nii volume.
+            FROM the func_nii volume TO the anat_nii volume. Alternatively, a string file name
+            for the FSL .mat file.
         anat_nii : str or nibabel.Nifti1Image
             nibabel image object (or path to nibabel-readable image) for anatomical volume from 
             which cortical surface was created
@@ -99,6 +100,12 @@ def from_fsl(cls, xfm, func_nii, anat_nii):
         import numpy.linalg as npl
         inv = npl.inv
 
+        # Load transform from text file, if string is provided
+        if isinstance(xfm,(str,unicode)):
+            with open(xfm,'r') as fid:
+                L = fid.readlines()
+            xfm  = np.array([[np.float(s) for s in ll.split() if s] for ll in L])
+
         # Internally, pycortex computes the OPPOSITE transform: from anatomical volume to functional volume. 
         # Thus, assign anat to "infile" (starting point for transform)
         infile = anat_nii