loading improved

README.md

@@ -40,6 +40,11 @@ python setup install
 
 ###Changelog
 
+#### 0.36
+* bug fixing
+* data loading improved
+* better plotting
+
 #### 0.34
 * short-time statistics
 * documentation in sphinx ready on readthedocs

connectivipy/data.py

@@ -29,10 +29,12 @@ class Data(object):
           other information about the data
     '''
     def __init__(self, data, fs=1., chan_names=[], data_info=''):
-        self.__data = self._load_file(data, data_info)
         self.__fs = fs
+        self.__data = self._load_file(data, data_info)
         if self.__data.shape[0]==len(chan_names):
             self.__channames = chan_names
+        elif hasattr(self,'_Data__fs'):
+            pass
         else:
             self.__channames = ["x"+str(i) for i in range(self.__chans)]
         self.data_info = data_info
@@ -46,9 +48,7 @@ def _load_file(self, data_what, data_info):
         Args:
           *data_what* : str/numpy.array
               path to file with appropieate format or numpy data array
-          *dt_type* : str
-              file extension (mat,)
-          *dt_type* = '' : str
+          *data_info* = '' : str
               additional file with data settings if needed
         Returns:
           *data* : np.array
@@ -57,15 +57,18 @@ def _load_file(self, data_what, data_info):
         if dt_type == np.ndarray:
             data = data_what
         elif dt_type == str:
+            dt_type = data_what.split('.')[-1] # catch extension of file
             if dt_type == 'mat':
                 mat_dict = si.loadmat(data_what)
                 if data_info:
                     key = data_info
                 else:
-                    key = data.split('.')[0]
+                    key = data_what[:-4].split('/')[-1]
                 data = mat_dict[key]
-            if data_info=='sml':
-                data, sml = signalml_loader(data_what.split('.')[0])
+            if dt_type=='raw' and data_info=='sml':
+                data, sml = signalml_loader(data_what[:-4])
+                self.__fs = sml['samplingFrequency']
+                self.__channames = sml['channelNames']
                 self.smldict = sml # here SignalML data is stored
         else:
             return False

connectivipy/load/loaders.py

@@ -57,5 +57,4 @@ def give_xml_info(path):
         calibr_coef.append(float(calibr_gain.getElementsByTagName('rs:'+'calibrationParam')[j].childNodes[0].data))
     xml_data['channelNames'] = chann_names 
     xml_data['calibrationCoef'] = calibr_coef 
-
     return xml_data

doc/tutorial.rst

@@ -14,6 +14,29 @@ The easiest way is to use *GIT* and just execute:
     $ cd connectivipy
     $ python setup.py install
 
+Loading data
+########
+
+.. code-block:: python
+
+    import connectivipy as cp
+    
+    # for numpy.array simply put that array in the first argument
+    # fs means sampling frequency
+    # chan_names is a list with channel names (length of list must be
+    #            the same as first dimension of data)
+    # data_info - additional infromation about the data
+    dt = Data(numpy_array_data, fs=32., chan_names=['Fp1','O1'], data_info='sml')
+
+    # Matlab data we can read giving a path to a matlab file
+    # and in data_info we put variable name as a string
+    dd = Data('adata.mat' ,data_info='bdata')
+
+    # similarly for SignalML data, but in data_info you need to point out
+    # that you want to read 'sml' data from *.raw and *.xml files of the
+    # same name 
+    dt = Data('cdata.raw',data_info='sml')
+
 Data class example
 ########
 

tests/tests.py

@@ -43,7 +43,15 @@
 Ains[3, 4, 2] = 0.6
 
 class DataTest(unittest.TestCase):
-    "test data class"
+    "test Data class"
+    #def test_loading(self):
+        #dt = cp.Data('test_data/testsml.raw',data_info='sml')
+        #self.assertEquals(dt.fs,256)
+        #self.assertEquals(len(dt.channelnames),2)
+        #dd = cp.Data('test_data/m.mat' ,data_info='m')
+        #self.assertEquals(dd.data.shape[0],3)
+        #self.assertEquals(dd.data.shape[1],5)
+
     def test_resample(self):
         do = cp.Data(np.random.randn(3,100, 4), fs=10)
         do.resample(5)
@@ -65,7 +73,7 @@ def test_conn2(self):
 
 class MvarTest(unittest.TestCase):
     def test_fitting(self):
-        "test mvar fitting"
+        "test MVAR fitting"
         ys = mvar_gen(A,10**4)
         avm,vvm = vieiramorf(ys,2)
         ans,vns = nutallstrand(ys,2)
@@ -90,6 +98,8 @@ def test_orders(self):
         self.assertEqual(crmin, 2)
 
 class ConnTest(unittest.TestCase):
+    "test connectivity class Conn"
+
     def test_spectrum(self):
         ys = mvar_gen(A,10**4)
         avm,vvm = vieiramorf(ys,2)