fixes #23

pyproject.toml

@@ -7,7 +7,7 @@ authors = ["François Laurent"]
 [tool.poetry.dependencies]
 python = "^3.8"
 julia = "^0.5.7"
-hdf5storage = "^0.1.18"
+hdf5storage = ">0.1.18"
 h5py = "^3.1.0"
 numpy = "^1.19.3"
 

src/taggingbackends/data/trxmat.py

@@ -79,9 +79,25 @@ class TrxMat:
                 records = records.split()
             if not lowlevel:
                 records, memoized_records = self._parse_record_names(records)
-            trx = hdf5storage.loadmat(self.path,
-                    variable_names=["trx/"+record for record in records])
+            file = h5py.File(self.path, 'r')
+            try:
+                trx = {}
+                for record in records:
+                    varname = 'trx/'+record
+                    refs = file[varname][0,:]
+                    # np arrays (and transpose) for backward compatibility
+                    trx[varname] = numpy.empty(refs.shape, dtype=object)
+                    if record == 'id':
+                        for i, ref in enumerate(refs):
+                            trx[varname][i] = numpy.array([file[ref][:].tobytes().decode('utf-16')])
+                    else:
+                        for i, ref in enumerate(refs):
+                            trx[varname][i] = numpy.transpose(file[ref][:])
+                    assert not numpy.isscalar(trx[varname])
+            finally:
+                file.close()
         elif lowlevel:
+            # TODO: replace hdf5storage or deprecate this use case
             trx = hdf5storage.loadmat(self.path)
         else:
             # explicit record names required for memoization
@@ -90,7 +106,7 @@ class TrxMat:
         for varname in trx:
             record = varname[4:]
             vardata = trx[varname]
-            assert len(vardata) == 1
+            if numpy.isscalar(vardata): # hdf5storage
                 vardata = vardata[0]
             try:
                 hook = getattr(self, record+"_hook")