docs: add set_setting example in quickstart and fix issue #366

README.md

@@ -159,6 +159,13 @@ To get a list with all the available feature names
 efel.get_feature_names()
 ```
 
+To change the spike detection threshold setting (default is -20 mV)
+
+```python
+efel.set_setting('Threshold', -30)
+```
+For a full list of available settings, please refer to the [Setting class](./efel/settings.py)
+
 The python function to extract features is get_feature_values(...).
 Below is a short example on how to use this function. The code and example
 trace are available
@@ -205,6 +212,9 @@ def main():
     # argument should be a list
     traces = [trace1]
 
+    # set the threshold for spike detection to -20 mV
+    efel.set_setting('Threshold', -20)
+
     # Now we pass 'traces' to the efel and ask it to calculate the feature
     # values
     traces_results = efel.get_feature_values(traces,

efel/api.py

@@ -182,7 +182,7 @@ def get_distance(
 
     if trace_check:
         trace_check_success = get_feature_values(
-            [trace], ['trace_check'])[0]  # type: ignore
+            [trace], ['trace_check'], None, True, True)[0]
 
         if trace_check_success["trace_check"] is None:
             return error_dist
@@ -401,14 +401,14 @@ def get_mean_feature_values(
         parallel_map=None,
         return_list=True,
         raise_warnings=raise_warnings)
-    for featureDict in featureDicts:  # type: ignore
+    for featureDict in featureDicts:
         for (key, values) in list(featureDict.items()):
             if values is None or len(values) == 0:
                 featureDict[key] = None
             else:
                 featureDict[key] = np.mean(values)
 
-    return featureDicts  # type: ignore
+    return featureDicts
 
 
 def register_feature(feature_function: Callable):

examples/basic/basic_example1.py

@@ -41,6 +41,9 @@ def main():
     # argument should be a list
     traces = [trace1]
 
+    # set the threshold for spike detection to -20 mV
+    efel.set_setting('Threshold', -20)
+
     # Now we pass 'traces' to the efel and ask it to calculate the feature
     # values
     traces_results = efel.get_feature_values(traces,