ENH: added keyword to Dataset.from_file and propagated so saved datas…

…ets with old subject names can be loaded with new subject name

cortex/dataset/dataset.py

@@ -65,7 +65,7 @@ def __dir__(self):
         return list(self.__dict__.keys()) + list(self.views.keys())
 
     @classmethod
-    def from_file(cls, filename):
+    def from_file(cls, filename, subject=None):
         ds = cls()
         ds.h5 = h5py.File(filename, 'r')
 
@@ -76,14 +76,17 @@ def from_file(cls, filename):
             if name in ("data", "subjects", "views"):
                 continue
             try:
-                ds.views[name] = _from_hdf_data(ds.h5, name)
+                ds.views[name] = _from_hdf_data(ds.h5, name, subject=subject)
             except KeyError:
                 print('No metadata found for "%s", skipping...'%name)
 
         #load up the views generated by pycortex
         for name, node in ds.h5['views'].items():
             try:
-                ds.views[name] = Dataview.from_hdf(node)
+                ds.views[name] = Dataview.from_hdf(node, subject=subject)
+            except FileNotFoundError:
+                print("Could not load file; old subject name? Try using `subject` kwarg to specify a current pycortex subject")
+                raise
             except Exception:
                 import traceback
                 traceback.print_exc()

cortex/dataset/views.py

@@ -26,22 +26,24 @@ def normalize(data):
     else:
         raise TypeError("Invalid input for Dataview")
 
-def _from_hdf_data(h5, name, xfmname=None, **kwargs):
+def _from_hdf_data(h5, name, xfmname=None, subject=None, **kwargs):
     """Decodes a __hash named node from an HDF file into the 
     constituent Vertex or Volume object"""
     dnode = h5.get("/data/%s"%name)
     if dnode is None:
         dnode = h5.get(name)
 
     attrs = {k: u(v) for (k, v) in dnode.attrs.items()}
-    subj = attrs['subject']
+    if subject is None:
+        subject = attrs['subject']
     #support old style xfmname saving as attribute
     if xfmname is None and 'xfmname' in attrs:
         xfmname = attrs['xfmname']
     mask = None
     if 'mask' in attrs:
         if attrs['mask'].startswith("__"):
-            mask = h5['/subjects/%s/transforms/%s/masks/%s'%(attrs['subject'], xfmname, attrs['mask'])].value
+            mask = h5['/subjects/%s/transforms/%s/masks/%s' %
+                      (attrs['subject'], xfmname, attrs['mask'])].value
         else:
             mask = attrs['mask']
 
@@ -52,37 +54,37 @@ def _from_hdf_data(h5, name, xfmname=None, **kwargs):
             alpha = dnode[..., 3]
 
         if xfmname is None:
-            return VertexRGB(dnode[...,0], dnode[...,1], dnode[...,2], subj, 
+            return VertexRGB(dnode[...,0], dnode[...,1], dnode[...,2], subject, 
                              alpha=alpha, **kwargs)
 
-        return VolumeRGB(dnode[...,0], dnode[...,1], dnode[...,2], subj, xfmname, 
+        return VolumeRGB(dnode[...,0], dnode[...,1], dnode[...,2], subject, xfmname, 
                          alpha=alpha, mask=mask, **kwargs)
 
     if xfmname is None:
-        return Vertex(dnode, subj, **kwargs)
+        return Vertex(dnode, subject, **kwargs)
 
-    return Volume(dnode, subj, xfmname, mask=mask, **kwargs)
+    return Volume(dnode, subject, xfmname, mask=mask, **kwargs)
 
 
-def _from_hdf_view(h5, data, xfmname=None, vmin=None, vmax=None,  **kwargs):
+def _from_hdf_view(h5, data, xfmname=None, vmin=None, vmax=None,  subject=None, **kwargs):
 
     if isinstance(data, string_types):
-        return _from_hdf_data(h5, data, xfmname=xfmname, vmin=vmin, vmax=vmax, **kwargs)
+        return _from_hdf_data(h5, data, xfmname=xfmname, vmin=vmin, vmax=vmax, subject=subject, **kwargs)
 
     if len(data) == 2:
-        dim1 = _from_hdf_data(h5, data[0], xfmname=xfmname[0])
-        dim2 = _from_hdf_data(h5, data[1], xfmname=xfmname[1])
+        dim1 = _from_hdf_data(h5, data[0], xfmname=xfmname[0], subject=subject)
+        dim2 = _from_hdf_data(h5, data[1], xfmname=xfmname[1], subject=subject)
         cls = Vertex2D if isinstance(dim1, Vertex) else Volume2D
         return cls(dim1, dim2, vmin=vmin[0], vmin2=vmin[1], 
-                   vmax=vmax[0], vmax2=vmax[1], **kwargs)
+                   vmax=vmax[0], vmax2=vmax[1], subject=subject, **kwargs)
     elif len(data) == 4:
-        red, green, blue = [_from_hdf_data(h5, d, xfmname=xfmname) for d in data[:3]]
+        red, green, blue = [_from_hdf_data(h5, d, xfmname=xfmname, subject=subject) for d in data[:3]]
         alpha = None 
         if data[3] is not None:
-            alpha = _from_hdf_data(h5, data[3], xfmname=xfmname)
+            alpha = _from_hdf_data(h5, data[3], xfmname=xfmname, subject=subject)
 
         cls = VertexRGB if isinstance(red, Vertex) else VolumeRGB
-        return cls(red, green, blue, alpha=alpha, **kwargs)
+        return cls(red, green, blue, alpha=alpha, subject=subject, **kwargs)
     else:
         raise ValueError("Invalid Dataview specification")
 
@@ -140,7 +142,7 @@ def to_json(self, simple=False):
         return sdict
 
     @staticmethod
-    def from_hdf(node):
+    def from_hdf(node, subject=None):
         data = json.loads(u(node[0]))
         desc = node[1]
         try:
@@ -166,9 +168,9 @@ def from_hdf(node):
         if len(data) == 1:
             xfm = None if xfmname is None else xfmname[0]
             return _from_hdf_view(node.file, data[0], xfmname=xfm, cmap=cmap[0], description=desc, 
-                                  vmin=vmin[0], vmax=vmax[0], state=state, **attrs)
+                                  vmin=vmin[0], vmax=vmax[0], state=state, subject=subject, **attrs)
         else:
-            views = [_from_hdf_view(node.file, d, xfmname=x) for d, x in zip(data, xfname)]
+            views = [_from_hdf_view(node.file, d, xfmname=x, subject=subject) for d, x in zip(data, xfmname)]
             raise NotImplementedError
 
     def _write_hdf(self, h5, name="data", data=None, xfmname=None):