[python-hdf5storage] 60/84: Added workaround for reading MAT files with variables larger than 2 GB when the variables to read aren't given explicitly.

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to annotated tag 0.1.10
in repository python-hdf5storage.

commit 95f9727788a5f013a1909b9dcad93cf00e1a9de5
Author: Freja Nordsiek <fnordsie at gmail.com>
Date:   Fri Aug 21 17:36:57 2015 -0400

    Added workaround for reading MAT files with variables larger than 2 GB when the variables to read aren't given explicitly.
---
 hdf5storage/__init__.py | 25 +++++++++++++++----------
 1 file changed, 15 insertions(+), 10 deletions(-)

diff --git a/hdf5storage/__init__.py b/hdf5storage/__init__.py
index e722943..f430b65 100644
--- a/hdf5storage/__init__.py
+++ b/hdf5storage/__init__.py
@@ -1360,16 +1360,21 @@ def loadmat(file_name, mdict=None, appendmat=True,
         # Read everything if we were instructed.
 
         if variable_names is None:
-            # Read everything from the root node.
-            data = read(path='/', filename=filename, options=options)
-
-            # If we didn't make a dict but instead got a structured
-            # ndarray, extract all the fields and make a dict from them.
-            if not isinstance(data, dict):
-                new_data = dict()
-                for field in data.dtype.names:
-                    new_data[field] = data[field][0]
-                data = new_data
+            data = dict()
+            with h5py.File(filename) as f:
+                for k in f:
+                    # Read if not group_for_references. Data that
+                    # produces errors when read is dicarded (the OSError
+                    # that would happen if this is not an HDF5 file
+                    # would already have happened when opening the
+                    # file).
+                    if f[k].name != options.group_for_references:
+                        try:
+                            data[k] = lowlevel.read_data(f, f, k,
+                                                         options)
+                        except:
+                            pass
+
         else:
             # Extract the desired fields into a dictionary one by one.
             data = dict()

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