Refactor downsample_waveform_chan

Make downsample_waveform_chan return the downsampled list of times and
data instead of saving this information to the waveform channel data
dictionary. This makes the function comply with SRP.

sohstationviewer/model/handling_data.py

@@ -627,7 +627,8 @@ def trim_waveform_data(wf_channel_data: Dict, start_time: float,
 def downsample_waveform_chan(wf_channel_data: Dict,
                              trimmed_traces_list: List[Dict],
                              start_time: float, end_time: float,
-                             first_time: bool) -> None:
+                             first_time: bool
+                             ) -> Tuple[List[np.ndarray], List[np.ndarray]]:
     # Calculate the number of requested_points
     total_size = sum([tr['size'] for tr in trimmed_traces_list])
     requested_points = 0
@@ -639,8 +640,8 @@ def downsample_waveform_chan(wf_channel_data: Dict,
         wf_channel_data['fulldata'] = True
 
     # Downsample the data
-    wf_channel_data['times'] = []
-    wf_channel_data['data'] = []
+    downsampled_times_list = []
+    downsampled_data_list = []
     for trIdx, tr in enumerate(trimmed_traces_list):
         times = np.memmap(tr['times_f'],
                           dtype='int64', mode='r',
@@ -653,11 +654,10 @@ def downsample_waveform_chan(wf_channel_data: Dict,
         data = data[indexes]
         if requested_points != 0:
             times, data = downsample(times, data, requested_points)
-        wf_channel_data['times'].append(times)
-        wf_channel_data['data'].append(data)
+        downsampled_times_list.append(times)
+        downsampled_data_list.append(data)
 
-    wf_channel_data['times'] = np.hstack(wf_channel_data['times'])
-    wf_channel_data['data'] = np.hstack(wf_channel_data['data'])
+    return downsampled_times_list, downsampled_data_list
 
 
 def trim_downsample_WFChan(chan, startTm, endTm, firsttime):