Produces EDF file from WFDB format

Introduces the conversion of WFDB files to EDF format. All data was written to the EDF file using struck.pack() so no outside packages were introduced. This implementation conserves the -h option which can now be used with help(wfdb.wfdb2edf) as well as the -o option which is now a parameter that the user must enter to specify their desired EDF file name. Further, the -v option was conserved and is no longer an option so all content will be printed to screen to help the user see what is going on and the specifications of their EDF file.

Author: Lucas-Mc

wfdb/__init__.py

@@ -1,5 +1,5 @@
 from wfdb.io.record import (Record, MultiRecord, rdheader, rdrecord, rdsamp,
-                            wrsamp, dl_database, edf2mit, wav2mit, wfdb2mat, sampfreq, signame)
+                            wrsamp, dl_database, edf2mit, wfdb2edf, wav2mit, wfdb2mat, sampfreq, signame)
 from wfdb.io.annotation import (Annotation, rdann, wrann, show_ann_labels,
                                 show_ann_classes, ann2rr)
 from wfdb.io.download import get_dbs, get_record_list, dl_files, set_db_index_url

wfdb/io/__init__.py

@@ -1,5 +1,5 @@
 from wfdb.io.record import (Record, MultiRecord, rdheader, rdrecord, rdsamp, wrsamp,
-                            dl_database, edf2mit, wav2mit, wfdb2mat, sampfreq, signame, SIGNAL_CLASSES)
+                            dl_database, edf2mit, wfdb2edf, wav2mit, wfdb2mat, sampfreq, signame, SIGNAL_CLASSES)
 from wfdb.io._signal import est_res, wr_dat_file
 from wfdb.io.annotation import (Annotation, rdann, wrann, show_ann_labels,
                                 show_ann_classes, ann2rr)

wfdb/io/_signal.py

@@ -432,7 +432,7 @@ def adc(self, expanded=False, inplace=False):
                 for ch in range(self.n_sig):
                     # NAN locations for the channel
                     ch_nanlocs = np.isnan(self.e_p_signal[ch])
-                    ch_d_signal = self.e_p_signal.copy()
+                    ch_d_signal = self.e_p_signal[ch].copy()
                     np.multiply(ch_d_signal, self.adc_gain[ch], ch_d_signal)
                     np.add(ch_d_signal, self.baseline[ch], ch_d_signal)
                     ch_d_signal = ch_d_signal.astype(intdtype, copy=False)
@@ -704,9 +704,14 @@ def convert_dtype(self, physical, return_res, smooth_frames):
                 if current_dtype != return_dtype:
                     self.p_signal = self.p_signal.astype(return_dtype, copy=False)
             else:
-                for ch in range(self.n_sig):
-                    if self.e_p_signal[ch].dtype != return_dtype:
-                        self.e_p_signal[ch] = self.e_p_signal[ch].astype(return_dtype, copy=False)
+                if self.e_p_signal is not None:
+                    for ch in range(self.n_sig):
+                        if self.e_p_signal[ch].dtype != return_dtype:
+                            self.e_p_signal[ch] = self.e_p_signal[ch].astype(return_dtype, copy=False)
+                else:
+                    for ch in range(self.n_sig):
+                        if self.p_signal[ch].dtype != return_dtype:
+                            self.p_signal[ch] = self.p_signal[ch].astype(return_dtype, copy=False)
         else:
             return_dtype = 'int'+str(return_res)
             if smooth_frames is True: