Compare kind of dtype rather than dtype itself

caiman/tests/test_hdf5.py

@@ -0,0 +1,51 @@
+#!/usr/bin/env python
+
+import numpy as np
+import numpy.testing as npt
+import os
+from caiman.utils import utils
+from caiman.paths import get_tempdir
+
+
+def _recursively_assert_array_equal(a, b):
+    """Get around array_equal not ignoring nans for nested objects"""
+    if isinstance(a, dict):
+        if not isinstance(b, dict):
+            raise AssertionError('Values have different types')
+        if len(a) != len(b):
+            raise AssertionError('Dicts have different sizes')
+
+        for key in a:
+            if key not in b:
+                raise AssertionError(f'Dicts have different keys ({key} not found)')
+            _recursively_assert_array_equal(a[key], b[key])
+    else:
+        npt.assert_array_equal(a, b)
+
+
+def test_save_and_load_dict_to_hdf5():
+    filename = os.path.join(get_tempdir(), 'test_hdf5.hdf5')
+    dict_to_save = {
+        'int_scalar': 1,
+        'int_vector': np.array([1, 2], dtype=int),
+        'int_matrix': np.array([[1, 2], [3, 4]], dtype=int),
+        'float32': np.array([[1., 2.], [3., 4.]], dtype='float32'),
+        'float32_w_nans': np.array([[1., 2.], [3., np.nan]], dtype='float32'),
+        'float64_w_nans': np.array([[1., 2.], [3., np.nan]], dtype='float64'),
+        'dict': {
+            'nested_float': np.array([1.0, 2.0])
+        },
+        'string': 'foobar',
+        'bool': True,
+        'dxy': (1.0, 2.0)  # specific key that should be saved as a tuple
+    }
+    # test no validation error on save
+    utils.save_dict_to_hdf5(dict_to_save, filename)
+
+    # test that the same data gets loaded
+    loaded = utils.load_dict_from_hdf5(filename)
+    _recursively_assert_array_equal(dict_to_save, loaded)
+
+
+if __name__ == '__main__':
+    test_save_and_load_dict_to_hdf5()

caiman/utils/utils.py

@@ -516,7 +516,7 @@ def recursively_save_dict_contents_to_group(h5file:h5py.File, path:str, dic:dict
             except:
                 item = np.array(item).astype('|S32')
                 h5file[path + key] = item
-            if not np.array_equal(h5file[path + key][()], item, equal_nan=item.dtype == 'f'):  # just using True gives "ufunc 'isnan' not supported for the input types"
+            if not np.array_equal(h5file[path + key][()], item, equal_nan=item.dtype.kind == 'f'):  # just using True gives "ufunc 'isnan' not supported for the input types"
                 raise ValueError(f'Error while saving ndarray {key} of dtype {item.dtype}')
         # save dictionaries
         elif isinstance(item, dict):