Delete trailing spaces

Also make sure files end with a newline, for POSIX compliance.

MANIFEST.in

@@ -24,4 +24,4 @@ prune util
 prune */__pycache__
 
 global-exclude *.py[cod] *.egg *.egg-info
-global-exclude *~ *.bak *.swp _pyedflib.c
+global-exclude *~ *.bak *.swp _pyedflib.c

README.rst

@@ -18,9 +18,9 @@ pyEDFlib
 .. image:: https://img.shields.io/conda/vn/conda-forge/pyedflib.svg
    :target: https://anaconda.org/conda-forge/pyedflib
    :alt: Conda Version
-  
-.. image:: https://anaconda.org/conda-forge/pyedflib/badges/downloads.svg   
-   :target: https://anaconda.org/conda-forge/pyedflib 
+
+.. image:: https://anaconda.org/conda-forge/pyedflib/badges/downloads.svg
+   :target: https://anaconda.org/conda-forge/pyedflib
    :alt: Conda Downloads
 
 What is pyEDFlib
@@ -97,11 +97,11 @@ Additionally functionality as anonymizing, dropping or renaming channels can be
     # drop a channel from the file or anonymize edf
     highlevel.drop_channels('edf_file.edf', to_drop=['ch2', 'ch4'])
     highlevel.anonymize_edf('edf_file.edf', new_file='anonymized.edf'
-	                         to_remove=['patientname', 'birthdate'],
-	                         new_values=['anonymized', ''])
+                             to_remove=['patientname', 'birthdate'],
+                             new_values=['anonymized', ''])
     # check if the two files have the same content
     highlevel.compare_edf('edf_file.edf', 'anonymized.edf')
-    # change polarity of certain channels 
+    # change polarity of certain channels
     highlevel.change_polarity('file.edf', channels=[1,3])
     # rename channels within a file
     highlevel.rename_channels('file.edf', mapping={'C3-M1':'C3'})
@@ -112,12 +112,12 @@ License
 
 pyEDFlib is a free Open Source software released under the BSD 2-clause license.
 
-  
+
 Releases can be cited via Zenodo.
 
 .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5678481.svg
    :target: https://doi.org/10.5281/zenodo.5678481
-  
+
 .. _Cython: http://cython.org/
 .. _Anaconda: https://www.continuum.io
 .. _GitHub: https://github.com/holgern/pyedflib

demo/streamingEDFFile.py

@@ -25,15 +25,15 @@ def animate(frame):
         sigbufs[i] = f.readSignal(i)
         if n_min < len(sigbufs[i]):
             n_min = len(sigbufs[i])
-            
+
     duration = f.getFileDuration()
     f._close()
     del f
     dt = int(duration/5)
     fig = plt.figure()
-    ax1 = fig.add_subplot(1,1,1)    
+    ax1 = fig.add_subplot(1,1,1)
     n_plot = np.min((n_min, 2000))
-    sigbufs_plot = np.zeros((n, n_plot))    
+    sigbufs_plot = np.zeros((n, n_plot))
     offset = 0
     ani = animation.FuncAnimation(fig, animate, interval=200)
     plt.show()

dev-requirements.txt

@@ -4,4 +4,4 @@ numpy
 pytest
 dateparser
 tqdm
-tox
+tox

pyedflib/data/_readers.py

@@ -33,4 +33,4 @@ def test_generator():
 
 
 def get_generator_filename():
-    return os.path.join(os.path.dirname(__file__), 'test_generator.edf')
+    return os.path.join(os.path.dirname(__file__), 'test_generator.edf')

pyedflib/tests/test_edfreader.py

@@ -38,14 +38,14 @@ def tearDownClass(cls):
                 os.remove(os.path.join(data_dir, file))
             except Exception as e:
                 print(e)
-                
+
     def tearDown(self):
         # small hack to close handles in case of tests throwing an exception
         for obj in gc.get_objects():
             if isinstance(obj, (EdfWriter, EdfReader)):
                 obj.close()
                 del obj
-                
+
     def test_EdfReader(self):
         try:
             f = pyedflib.EdfReader(self.edf_data_file)
@@ -79,7 +79,7 @@ def test_EdfReader_BDF(self):
         np.testing.assert_equal(f.signals_in_file, 5)
         np.testing.assert_equal(f.datarecords_in_file, datarecords)
         np.testing.assert_equal(f.getFileDuration(), datarecords)
-        
+
         sample_frequencies = [1000, 800, 500, 975, 999]
 
         for i in np.arange(f.signals_in_file):
@@ -88,7 +88,7 @@ def test_EdfReader_BDF(self):
             np.testing.assert_equal(f.getNSamples()[i], int(sample_frequencies[i] * datarecords))
             np.testing.assert_almost_equal(f.getSignalHeader(i)["sample_frequency"], sample_frequencies[i])
             np.testing.assert_almost_equal(f.getSignalHeaders()[i]["sample_frequency"], sample_frequencies[i])
-            
+
         np.testing.assert_equal(f.handle, 0)
         f.close()
         np.testing.assert_equal(f.handle, -1)
@@ -107,7 +107,7 @@ def test_EdfReader_BDF_datarec_0_5(self):
         np.testing.assert_equal(f.datarecord_duration, datarecord_duration)
         np.testing.assert_equal(f.datarecords_in_file, datarecords / datarecord_duration)
         np.testing.assert_equal(f.getFileDuration(), datarecords)
-        
+
         sample_frequencies = [2000, 1600, 1000, 1950, 1998]
 
         for i in np.arange(f.signals_in_file):
@@ -134,7 +134,7 @@ def test_EdfReader_BDF_datarec_2(self):
         np.testing.assert_equal(f.datarecord_duration, datarecord_duration)
         np.testing.assert_equal(f.datarecords_in_file, datarecords / datarecord_duration)
         np.testing.assert_equal(f.getFileDuration(), datarecords)
-        
+
         sample_frequencies = [500, 400, 250, 487.5, 499.5]
 
         for i in np.arange(f.signals_in_file):
@@ -160,12 +160,12 @@ def test_indexerrors_thrown(self):
         for i in range(10):
             for func in funcs:
                 getattr(f, func)(i)
-            
+
         for i in [-1, 11]:
             for func in funcs:
                 with self.assertRaises(IndexError, msg=f"f.{func}({i})"):
                     getattr(f, func)(i)
-            
+
         f.close()
 
     def test_EdfReader_headerInfos(self):
@@ -294,7 +294,7 @@ def test_EdfReader_Close_file(self):
         # Don't close the file but try to reopen it and verify that it fails.
         with np.testing.assert_raises(OSError):
             ff = pyedflib.EdfReader(self.edf_data_file)
-        
+
         # Now close and verify it can be re-opened/read.
         f.close()
 
@@ -357,7 +357,7 @@ def test_read_incorrect_file(self):
                 f.setTechnician('tec1')
                 data = np.ones(100) * 0.1
                 f.writePhysicalSamples(data)
-    
+
             with open(self.bdf_accented_file, 'rb') as f:
                 content = bytearray(f.read())
                 content[181] = 58

pyedflib/tests/test_highlevel.py

@@ -38,7 +38,7 @@ def tearDownClass(cls):
                 os.remove(os.path.join(data_dir, file))
             except Exception as e:
                 print(e)
-                
+
     def tearDown(self):
         # small hack to close handles in case of tests throwing an exception
         for obj in gc.get_objects():
@@ -49,14 +49,14 @@ def tearDown(self):
     def test_dig2phys_calc(self):
         signals_phys, shead, _ = highlevel.read_edf(self.test_generator)
         signals_dig, _, _ = highlevel.read_edf(self.test_generator, digital=True)
-                
+
         dmin, dmax = shead[0]['digital_min'],  shead[0]['digital_max']
         pmin, pmax = shead[0]['physical_min'],  shead[0]['physical_max']
-        
+
         # convert to physical
-        signal_phys2 = highlevel.dig2phys(signals_dig, dmin, dmax, pmin, pmax)        
+        signal_phys2 = highlevel.dig2phys(signals_dig, dmin, dmax, pmin, pmax)
         np.testing.assert_allclose(signals_phys, signal_phys2)
-        
+
         # convert to digital
         signals_dig2 = highlevel.phys2dig(signals_phys, dmin, dmax, pmin, pmax)
         signals_dig2 = np.rint(signals_dig2)
@@ -66,7 +66,7 @@ def test_read_write_edf(self):
         startdate = datetime.now()
         t = startdate
         startdate = datetime(t.year,t.month,t.day,t.hour, t.minute,t.second)
-        
+
         header = highlevel.make_header(technician='tech', recording_additional='r_add',
                                                 patientname='name', patient_additional='p_add',
                                                 patientcode='42', equipment='eeg', admincode='120',
@@ -108,9 +108,9 @@ def test_read_write_edf(self):
             self.assertTrue(os.path.isfile(file))
             self.assertGreater(os.path.getsize(file), 0)
             self.assertTrue(success)
-            
+
             signals2, signal_headers2, header2 = highlevel.read_edf(file, digital=True)
-    
+
             self.assertEqual(len(signals2), 5)
             self.assertEqual(len(signals2), len(signal_headers2))
             np.testing.assert_array_equal(signals, signals2)
@@ -123,17 +123,17 @@ def test_read_write_edf(self):
             # EDF/BDF header writing does not correctly work yet
             if file_type in [-1, 1, 3]:
                 self.assertDictEqual(header, header2)
-        
+
     def test_read_write_with_annotations(self):
         signals, signal_headers, header = highlevel.read_edf(self.test_generator)
         expected = [[0.0, -1, 'Recording starts'], [600.0, -1, 'Recording ends']]
         self.assertEqual(header['annotations'], expected)
-        
+
         highlevel.write_edf(self.edfplus_data_file, signals, signal_headers, header)
         signals2, signal_header2s, header2 = highlevel.read_edf(self.edfplus_data_file)
         self.assertEqual(header['annotations'], header2['annotations'])
 
-        
+
     def test_quick_write(self):
         signals = np.random.randint(-2048, 2048, [3, 256*60])
         highlevel.write_edf_quick(self.edfplus_data_file, signals.astype(np.int32), sfreq=256, digital=True)
@@ -170,7 +170,7 @@ def test_read_write_decimal_sample_frequencies(self):
         highlevel.write_edf_quick(self.edfplus_data_file, signals.astype(np.int32), sfreq=8.5, digital=True)
         signals2, _, _ = highlevel.read_edf(self.edfplus_data_file, digital=True, verbose=True)
         np.testing.assert_allclose(signals, signals2)
-        
+
         # now with physical signals
         signals = np.random.rand(3, 256*60+8) # then rescale to 0-1
         signals = (signals - signals.min()) / (signals.max() - signals.min())
@@ -180,7 +180,7 @@ def test_read_write_decimal_sample_frequencies(self):
 
 
     def test_read_write_diff_sfreq(self):
-        
+
         signals = []
         sfreqs = [1, 64, 128, 200]
         sheaders = []
@@ -192,32 +192,32 @@ def test_read_write_diff_sfreq(self):
         signals2, sheaders2, _ = highlevel.read_edf(self.edfplus_data_file, digital=True)
         for s1, s2 in zip(signals, signals2):
             np.testing.assert_allclose(s1, s2)
-        
+
     def test_assertion_dmindmax(self):
-        
+
         # test digital and dmin wrong
         signals =[np.random.randint(-2048, 2048, 256*60).astype(np.int32)]
         sheaders = [highlevel.make_signal_header('ch1', sample_frequency=256)]
         sheaders[0]['digital_min'] = -128
         sheaders[0]['digital_max'] = 128
         with self.assertRaises(AssertionError):
             highlevel.write_edf(self.edfplus_data_file, signals, sheaders, digital=True)
-        
+
         # test pmin wrong
         signals = [np.random.randint(-2048, 2048, 256*60)]
         sheaders = [highlevel.make_signal_header('ch1', sample_frequency=256)]
         sheaders[0]['physical_min'] = -200
         sheaders[0]['physical_max'] = 200
         with self.assertRaises(AssertionError):
             highlevel.write_edf(self.edfplus_data_file, signals, sheaders, digital=False)
-            
+
 
     def test_read_write_accented(self):
         signals = np.random.rand(3, 256*60) # then rescale to 0-1
         signals = (signals - signals.min()) / (signals.max() - signals.min())
         highlevel.write_edf_quick(self.test_accented, signals, sfreq=256)
         signals2, _, _ = highlevel.read_edf(self.test_accented)
-        
+
         np.testing.assert_allclose(signals, signals2, atol=0.00002)
         # if os.name!='nt':
         self.assertTrue(os.path.isfile(self.test_accented), 'File does not exist')
@@ -233,7 +233,7 @@ def test_read_unicode(self):
 
 
     def test_read_header(self):
-        
+
         header = highlevel.read_edf_header(self.test_generator)
         self.assertEqual(len(header), 14)
         self.assertEqual(len(header['channels']), 11)
@@ -247,10 +247,10 @@ def test_read_header(self):
         self.assertEqual(header['patientcode'], 'abcxyz99')
         self.assertEqual(header['patientname'], 'Hans Muller')
         self.assertEqual(header['technician'], 'Mr. Spotty')
-        
-        
+
+
     def test_anonymize(self):
-        
+
         header = highlevel.make_header(technician='tech', recording_additional='radd',
                                                 patientname='name', patient_additional='padd',
                                                 patientcode='42', equipment='eeg', admincode='420',
@@ -261,9 +261,9 @@ def test_anonymize(self):
         signals = np.random.rand(3, 256*300)*200 #5 minutes of eeg
         signals = (signals - signals.min()) / (signals.max() - signals.min())
         highlevel.write_edf(self.personalized, signals, signal_headers, header)
-    
-        
-    
+
+
+
         highlevel.anonymize_edf(self.personalized, new_file=self.anonymized,
                                         to_remove=['patientname', 'birthdate',
                                                    'admincode', 'patientcode',
@@ -291,32 +291,32 @@ def test_anonymize(self):
         self.assertEqual(new_header['technician'], 'xxxx')
 
         with self.assertRaises(AssertionError):
-            highlevel.anonymize_edf(self.personalized, 
+            highlevel.anonymize_edf(self.personalized,
                                     new_file=self.anonymized,
                                     to_remove=['patientname', 'birthdate',
                                                'admincode', 'patientcode',
                                                'technician'],
                                     new_values=['x', '', 'xx', 'xxx'],
                                     verify=True)
-            
+
     def test_drop_channel(self):
         signal_headers = highlevel.make_signal_headers(['ch'+str(i) for i in range(5)])
         signals = np.random.rand(5, 256*300)*200 #5 minutes of eeg
         signals = (signals - signals.min()) / (signals.max() - signals.min())
         highlevel.write_edf(self.drop_from, signals, signal_headers)
-        
+
         dropped = highlevel.drop_channels(self.drop_from, to_keep=['ch1', 'ch2'], verbose=True)
-        
+
         signals2, signal_headers, header = highlevel.read_edf(dropped)
-        
+
         np.testing.assert_allclose(signals[1:3,:], signals2, atol=0.01)
-        
+
         highlevel.drop_channels(self.drop_from, self.drop_from[:-4]+'2.edf',
                                 to_drop=['ch0', 'ch1', 'ch2'])
         signals2, signal_headers, header = highlevel.read_edf(self.drop_from[:-4]+'2.edf')
 
         np.testing.assert_allclose(signals[3:,:], signals2, atol=0.01)
-        
+
         with self.assertRaises(AssertionError):
             highlevel.drop_channels(self.drop_from, to_keep=['ch1'], to_drop=['ch3'])
 

requirements-test.txt

@@ -8,4 +8,4 @@ cython
 numpy
 pytest
 dateparser
-tqdm
+tqdm

setup.cfg

@@ -2,4 +2,4 @@
 with-coverage = true
 with-doctest = true
 # Don't ignore files starting with '_'
-ignore-files = (?:^\.|^util)
+ignore-files = (?:^\.|^util)