Added two new methods, which are just wrappers to numpy.save and nump…

…y.load

The idea I had was that since pickling matplotlib figures is so tricky,
it would still be beneficial to be able to generate the figures without having to preprocess everything all over again. So once you have your data analyzed,
dump it into a numpy binary .npy file and load it up in a separate figure generation script.

Added some basic array roundtrip checks, for coverage purposes.

.gitignore

@@ -68,6 +68,4 @@ cover/keybd_open.png
 nanonispy.sublime-project
 nanonispy.sublime-workspace
 dev_test.py
-MANIFEST
-MANIFEST.in
 conda_build/

nanonispy/read.py

@@ -5,6 +5,7 @@
 
 
 class NanonisFile:
+
     """
     Base class for Nanonis data files (grid, scan, point spectroscopy).
 
@@ -23,6 +24,8 @@ class NanonisFile:
         Just the filename, no path.
     fname : str
         Full path of Nanonis file.
+    filetype : str
+        filetype corresponding to filename extension.
     byte_offset : int
         Size of header in bytes.
     header_raw : str
@@ -121,6 +124,7 @@ def start_byte(self):
         return byte_offset
 
 class Grid(NanonisFile):
+
     """
     Nanonis grid file class.
 
@@ -252,6 +256,7 @@ def _extract_topo(self):
 
 
 class Scan(NanonisFile):
+
     """
     Nanonis scan file class.
 
@@ -338,6 +343,7 @@ def _load_data(self):
 
 
 class Spec(NanonisFile):
+
     """
     Nanonis point spectroscopy file class.
 
@@ -397,13 +403,15 @@ def _load_data(self):
 
 
 class UnhandledFileError(Exception):
+
     """
     To be raised when unknown file extension is passed.
     """
     pass
 
 
 class FileHeaderNotFoundError(Exception):
+
     """
     To be raised when no header information could be determined.
     """
@@ -575,6 +583,63 @@ def _split_header_entry(entry, multiple=False):
         return val_str.strip('"')
 
 
+def save_array(file, arr, allow_pickle=True):
+    """
+    Wrapper to numpy.save method for arrays.
+
+    The idea would be to use this to save a processed array for later
+    use in a matplotlib figure generation scripts. See numpy.save
+    documentation for details.
+
+    Parameters
+    ----------
+    file : file or str
+        File or filename to which the data is saved.  If file is a file-
+        object, then the filename is unchanged.  If file is a string, a
+        ``.npy`` extension will be appended to the file name if it does
+        not already have one.
+    arr : array_like
+        Array data to be saved.
+    allow_pickle : bool, optional
+        Allow saving object arrays using Python pickles. Reasons for
+        disallowing pickles include security (loading pickled data can
+        execute arbitrary code) and portability (pickled objects may not
+        be loadable on different Python installations, for example if
+        the stored objects require libraries that are not available, and
+        not all pickled data is compatible between Python 2 and Python
+        3). Default: True
+    """
+    np.save(file, arr, allow_pickle=allow_pickle)
+
+
+def load_array(file, allow_pickle=True):
+    """
+    Wrapper to numpy.load method for binary files.
+
+    See numpy.load documentation for more details.
+
+    Parameters
+    ----------
+    file : file or str
+        The file to read. File-like objects must support the
+    ``seek()`` and ``read()`` methods. Pickled files require that the
+    file-like object support the ``readline()`` method as well.
+    allow_pickle : bool, optional
+        Allow loading pickled object arrays stored in npy files. Reasons
+        for disallowing pickles include security, as loading pickled
+        data can execute arbitrary code. If pickles are disallowed,
+        loading object arrays will fail. Default: True
+
+    Returns
+    -------
+    result : array, tuple, dict, etc.
+        Data stored in the file. For ``.npz`` files, the returned
+        instance of NpzFile class must be closed to avoid leaking file
+        descriptors.
+    """
+    return np.load(file)
+
+
 def _parse_scan_header_table(table_list):
     """
     Parse scan file header entries whose values are tab-separated
@@ -600,5 +665,3 @@ def _is_valid_file(fname, ext):
     """
     if fname[-3:] != ext:
         raise UnhandledFileError('{} is not a {} file'.format(fname, ext))
-
-

nanonispy/tests/test_read.py

@@ -293,5 +293,22 @@ def test_header_entries(self):
             b = ''.join(sorted(test_dict[key]))
             self.assertEqual(a, b)
 
+
+class TestUtilFunctions(unittest.TestCase):
+
+    def setUp(self):
+        self.temp_dir = tempfile.TemporaryDirectory()
+
+    def tearDown(self):
+        self.temp_dir.cleanup()
+
+    def test_arr_roundtrip(self):
+        fname = self.temp_dir.name + '/test_roundtrip.npy'
+        a = np.linspace(0, 1.00, dtype='>f4')
+        nap.read.save_array(fname, a)
+        b = nap.read.load_array(fname)
+
+        np.testing.assert_array_equal(a, b)
+
 if __name__ == '__main__':
     unittest.main()