Fix tests

doc/sorting_extractor.rst

@@ -26,7 +26,7 @@ The contributed extractors are in the **spikeextractors/extractors** folder. You
             SortingExtractor.__init__(self)
 
             ## All file specific initialization code can go here.
-            # If your format stores the sampling frequency, you can overweite the self._sampling_frequency. This way,
+            # If your format stores the sampling frequency, you can overwrite the self._sampling_frequency. This way,
             # the base method self.get_sampling_frequency() will return the correct sampling frequency
 
             self._sampling_frequency = my_sampling_frequency

doc/spike_sorter.rst

@@ -49,17 +49,10 @@ Then, you can start creating a new class:
         'param2': 2,
         }
 
-    # (optional) rewrite the params as a list for the Spikely GUI to use
-    _extra_gui_params = [
-        {'name': 'param1', 'type': 'str', 'value': None, 'default': None,
-         'title': "My first param"},
-        {'name': 'param2', 'type': 'int', 'value': 2, 'default': 2,
-         'title': "My second param"},
-    ]
-
-    sorter_gui_params = copy.deepcopy(BaseSorter.sorter_gui_params)
-    for param in _extra_gui_params:
-        sorter_gui_params.append(param)
+    _params_description = {
+        'param1': 'Description for param1',
+        'param1': 'Description for param1',
+    }
 
     installation_mesg = """
         >>> pip install myspikesorter
@@ -79,12 +72,18 @@ Now you can start filling out the required methods:
     def get_sorter_version():
         return myspikesorter.__version__
 
+    @classmethod
+    def is_installed(cls):
+
+        # Fill code to check sorter installation. It returns a boolean
+        return HAVE_MSS
+
     def _setup_recording(self, recording, output_folder):
 
         # Fill code to set up the recording: convert to required file, parse config files, etc.
         # The files should be placed in the 'output_folder'
 
-    def _run(self,  recording, output_folder):
+    def _run(self, recording, output_folder):
 
         # Fill code to run your spike sorter based on the files created in the _setup_recording()
         # You can run CLI commands (e.g. klusta, spykingcircus, tridescous), pure Python code (e.g. Mountainsort4,

examples/modules/sorters/plot_3_sorting_by_group.py

@@ -22,9 +22,10 @@
 # (using the :code:`set_channel_property` method), or by using a probe file. In this example we will create a 16 channel
 # recording and split it in four channel groups (tetrodes).
 #
-# Let's create a toy example with 16 channels:
+# Let's create a toy example with 16 channels (the :code:`dumpable=True` dumps the extractors to a file, which is
+# required for parallel sorting):
 
-recording_tetrodes, sorting_true = se.example_datasets.toy_example(duration=10, num_channels=16)
+recording_tetrodes, sorting_true = se.example_datasets.toy_example(duration=10, num_channels=16, dumpable=True)
 
 ##############################################################################
 # Initially there is no group information ('location' is loaded automatically when creating toy data):

requirements.txt

@@ -1,5 +1,5 @@
 spikeextractors>=0.9.0
 spiketoolkit>=0.7.0
-spikesorters>=0.4.0
+spikesorters>=0.4.1
 spikecomparison>=0.3.0
 spikewidgets>=0.5.0