def _load(self, fname, name, is_roi=False):
try:
extension = ""
parts = fname.split(".", 1)
if len(parts) > 1:
extension = parts[1]
self.debug("Loading: %s (%s)", fname, extension)
if extension == 'mat':
mat, _rows, _cols = load_matrix(fname)
extra = MatrixExtra(name, mat)
self.ivm.add_extra(name, extra)
elif extension == 'csv':
df = pd.read_csv(fname)
extra = DataFrameExtra(name, df)
self.ivm.add_extra(name, extra)
elif extension in ('nii', 'nii.gz'):
self.debug("Nifti data")
qpdata = load(fname)
# Remember this is from a temporary file so need to copy the actual data
qpdata = NumpyData(qpdata.raw(),
grid=qpdata.grid,
name=self._output_prefix + name,
roi=is_roi)
self._output_data_items.append(name)
self.ivm.add(qpdata)
except:
self.warn("Failed to load: %s", fname)
traceback.print_exc()
def _load_file(self, filename):
fvals, nrows, ncols = load_matrix(filename)
if ncols <= 0:
raise RuntimeError("No numeric data found in file")
elif ncols == 1:
self.value = [row[0] for row in fvals]
elif nrows == 1:
self.value = fvals[0]
else:
# Choose row or column you want
row, col = self._choose_row_col(fvals)
if row is not None:
self.value = fvals[row]
elif col is not None:
self.value = [v[col] for v in fvals]
def _load_file(self, filename):
fvals, _, ncols = load_matrix(filename)
if ncols <= 0:
raise RuntimeError("No numeric data found in file")
else:
self.setMatrix(fvals)
