WIP: Save SpatialImages into HDF5 files.

nibabel/hdfloadsave.py

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+# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
+#
+#   See COPYING file distributed along with the NiBabel package for the
+#   copyright and license terms.
+#
+### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
+
+import numpy as np
+import h5py
+
+from .nifti1 import Nifti1Image, Nifti1Header
+
+#from .spm2analyze import Spm2AnalyzeImage
+#from .nifti1 import Nifti1Image, Nifti1Pair, Nifti1Header, header_dtype as ni1_hdr_dtype
+#from .nifti2 import Nifti2Image, Nifti2Pair
+#from .minc1 import Minc1Image
+#from .minc2 import Minc2Image
+#from .freesurfer import MGHImage
+
+def nifti1img_to_hdf(fname, spatial_img, h5path='/img', append=True):
+    """
+    Saves a Nifti1Image into an HDF5 file.
+
+    fname: string
+    Output HDF5 file path
+
+    spatial_img: nibabel SpatialImage
+    Image to be saved
+
+    h5path: string
+    HDF5 group path where the image data will be saved.
+    Datasets will be created inside the given group path:
+    'data', 'extra', 'affine', the header information will
+    be set as attributes of the 'data' dataset.
+
+    append: bool
+    True if you don't want to erase the content of the file
+    if it already exists, False otherwise.
+
+    @note:
+    HDF5 open modes
+    >>> 'r' Readonly, file must exist
+    >>> 'r+' Read/write, file must exist
+    >>> 'w' Create file, truncate if exists
+    >>> 'w-' Create file, fail if exists
+    >>> 'a' Read/write if exists, create otherwise (default)
+    """
+    mode = 'w'
+    if append:
+        mode = 'a'
+
+    with h5py.File(fname, mode) as f:
+        h5img = f.create_group(h5path)
+        h5img['data']   = spatial_img.get_data()
+        h5img['extra']  = spatial_img.get_extra()
+        h5img['affine'] = spatial_img.get_affine()
+
+        hdr = spatial_img.get_header()
+        for k in hdr.keys():
+            h5img['data'].attrs[k] = hdr[k]
+
+
+def hdfgroup_to_nifti1image(fname, h5path):
+    """
+    Returns a nibabel Nifti1Image from an HDF5 group datasets
+
+    @param fname: string
+    HDF5 file path
+
+    @param h5path:
+    HDF5 group path in fname
+
+    @return: nibabel Nifti1Image
+    """
+    with h5py.File(fname, 'r') as f:
+        h5img  = f[h5path]
+        data   = h5img['data'][()]
+        extra  = h5img['extra'][()]
+        affine = h5img['affine'][()]
+
+        header = get_nifti1hdr_from_h5attrs(h5img['data'].attrs)
+
+    img = Nifti1Image(data, affine, header=header, extra=extra)
+
+    return img
+
+
+def get_nifti1hdr_from_h5attrs(h5attrs):
+    """
+    Transforms an H5py Attributes set to a dict.
+    Converts unicode string keys into standard strings
+    and each value into a numpy array.
+
+    @param h5attrs: H5py Attributes
+
+    @return: dict
+    """
+    hdr = Nifti1Header()
+    for k in h5attrs.keys():
+        hdr[str(k)] = np.array(h5attrs[k])
+
+    return hdr