expanded frames works for regular format

cx1111 · cx1111 · commit fd02efd54ad1 · 2017-05-31T13:34:03.000-04:00
diff --git a/wfdb/_signals.py b/wfdb/_signals.py
@@ -180,14 +180,16 @@ def dac(self, expanded):
         """
         # The digital nan values for each channel
         dnans = digi_nan(self.fmt)
-        
+
         if expanded:
             p_signal = []
             for ch in range(0, self.nsig):
-                chnanloc = self.e_d_signals == dnans
+                # nan locations for the channel
+                chnanlocs = self.e_d_signals[ch] == dnans[ch]
                 p_signal.append((self.e_d_signals[ch] - self.baseline[ch])/float(self.adcgain[ch]))
                 p_signal[ch][chnanlocs] = np.nan
         else:
+            # nan locations
             nanlocs = self.d_signals == dnans
             p_signal = (self.d_signals - self.baseline)/[float(g) for g in self.adcgain]
             p_signal[nanlocs] = np.nan
@@ -499,7 +501,7 @@ def rddat(filename, dirname, pbdir, fmt, nsig,
             # Transfer over samples
             for ch in range(nsig):
                 # Indices of the flat signal that belong to the channel
-                ch_indices = np.concatenate(([np.array(range(sampsperframe[ch])) + tsampsperframe*framenum for framenum in range(int(len(sigflat)/tsampsperframe))]))
+                ch_indices = np.concatenate(([np.array(range(sampsperframe[ch])) + sum([0]+sampsperframe[:ch]) + tsampsperframe*framenum for framenum in range(int(len(sigflat)/tsampsperframe))]))
                 sig.append(sigflat[ch_indices])
 
             # Skew the signal
@@ -519,6 +521,8 @@ def rddat(filename, dirname, pbdir, fmt, nsig,
         elif fmt == '160':
             sigbytes = sigbytes - 32768
 
+        #print('sigbytes:', sigbytes)
+
 
         # No extra samples/frame. Obtain original uniform numpy array
         if tsampsperframe==nsig:
@@ -532,9 +536,6 @@ def rddat(filename, dirname, pbdir, fmt, nsig,
 
         # Extra frames present to be smoothed. Obtain averaged uniform numpy array
         elif smoothframes:
-            
-            print('sigbytes:')
-            print(sigbytes)
 
             # Allocate memory for signal
             sig = np.empty([readlen, nsig], dtype='int')
@@ -549,8 +550,6 @@ def rddat(filename, dirname, pbdir, fmt, nsig,
                         sig[:, ch] += sigbytes[skew[ch]*tsampsperframe+sum(([0] + sampsperframe)[:ch + 1]) + frame::tsampsperframe]
             sig = (sig / sampsperframe)
 
-            print('sig after smoothing:')
-            print(sig)
 
         # Extra frames present without wanting smoothing. Return all expanded samples.
         else:
@@ -564,7 +563,9 @@ def rddat(filename, dirname, pbdir, fmt, nsig,
                 #     chansig[frame::sampsperframe[ch]] = sigbytes[skew[ch]*tsampsperframe+sum(([0] + sampsperframe)[:ch + 1]) + frame::tsampsperframe]
                 # sig.append(chansig)
 
-                ch_indices = np.concatenate([np.array(range(sampsperframe[ch])) + tsampsperframe*framenum for framenum in range(int(len(sigbytes)/tsampsperframe))])
+                # Get the sample indices of the channel samples to transfer over
+                ch_indices = np.concatenate([np.array(range(sampsperframe[ch])) + sum([0]+sampsperframe[:ch]) + tsampsperframe*framenum for framenum in range(int(len(sigbytes)/tsampsperframe))])
+
                 sig.append(sigbytes[ch_indices])
 
             # Skew the signal
diff --git a/wfdb/records.py b/wfdb/records.py
@@ -405,33 +405,39 @@ def wrsamp(self):
 
     # Arrange/edit object fields to reflect user channel and/or signal range input
     # Account for case when signals are expanded
-    def arrangefields(self, channels, expanded):
+    def arrangefields(self, channels, expanded=False):
 
         # Rearrange signal specification fields
         for field in _headers.sigfieldspecs:
             item = getattr(self, field)
             setattr(self, field, [item[c] for c in channels])
 
-        # Checksum and initvalue to be updated if present
-        # unless the whole signal length was input
-        if self.siglen != self.d_signals.shape[0]:
+        # Expanded signals - multiple samples per frame.
+        if expanded:
+            # clear checksum and initvalue for now
+            self.checksum = [None]*len(self.e_d_signals)
+            self.initvalue = [None]*len(self.e_d_signals)
+
+            self.nsig = len(channels)
+            self.siglen = min([len(sig) for sig in self.e_d_signals])
+
+
+        # MxN numpy array d_signals
+        else:
+            # Checksum and initvalue to be updated if present
+            # unless the whole signal length was input
+            if self.siglen != self.d_signals.shape[0]:
 
-            # If the signals are expanded, initvalue and checksum
-            # have no meaning, so just put None.
-            if expanded:
-                self.checksum = [None]*self.d_signals.shape[1]
-                self.initvalue = [None]*self.d_signals.shape[1]
-            else:
                 if self.checksum is not None:
                     self.checksum = self.calc_checksum()
                 if self.initvalue is not None:
                     ival = list(self.d_signals[0, :])
                     self.initvalue = [int(i) for i in ival]
 
-        # Update record specification parameters
-        # Important that these get updated after^^
-        self.nsig = len(channels)
-        self.siglen = self.d_signals.shape[0]
+            # Update record specification parameters
+            # Important that these get updated after^^
+            self.nsig = len(channels)
+            self.siglen = self.d_signals.shape[0]
 
 
 
