Merge IFR

.travis.yml

@@ -7,6 +7,10 @@ notifications:
 env:
   - TRAVIS_CI=1
 
+# set build size to avoid 137 out of memory error
+vm:
+  size: large
+
 # conda setup copied from the conda docs
 install:
   # We do this conditionally because it saves us some downloading if the

ramutils/cli/expconf.py

@@ -81,8 +81,17 @@ def validate_stim_settings(args):
         if args.experiment != "AmplitudeDetermination" and not args.experiment.startswith('PS'):
             if args.target_amplitudes is None:
                 raise RuntimeError("--target-amplitudes is required")
+            if not (args.min_amplitudes is None and args.max_amplitudes is None):
+                raise RuntimeError('--min-amplitudes and --max-amplitudes are only used with '
+                                   'AmplitudeDetermination and "PS" experiments. To specify '
+                                   'a config for ' + args.experiment + ', only specify '
+                                   '--target-amplitudes')
             valid = len(args.anodes) == len(args.target_amplitudes)
         else:
+            if not args.target_amplitudes is None:
+                raise RuntimeError('Cannot specify --target-amplitudes (which is only used in '
+                                   '"PS" and AtmplitudeDetermination experiments) with '
+                                   '--min-amplitudes or --max-amplitudes!')
             valid = len(args.anodes) == len(
                 args.min_amplitudes) == len(args.max_amplitudes)
 

ramutils/constants.py

@@ -12,7 +12,9 @@
         'CatFR1',
         'PAL1',
         'DBOY1',
-        'RepFR1'
+        'RepFR1',
+        'IFR1',
+        'ICatFR1'
     ],
     'ps': [
         'PS4_FR5',
@@ -38,6 +40,12 @@
         'CatFR6',
         'TICL_FR',
         'TICL_CatFR',
+        'IFR3',
+        'ICatFR3',
+        'IFR5',
+        'ICatFR5',
+        'IFR6',
+        'ICatFR6',
     ],
 
     # Experiments that allow multiple stim locations
@@ -48,6 +56,8 @@
         'PS4_CatFR5',
         'FR6',
         'CatFR6',
+        'IFR6',
+        'ICatFR6',
     ]
 }
 

ramutils/tasks/events.py

@@ -11,6 +11,9 @@
 from ramutils.tasks import task
 from ramutils.utils import extract_experiment_series
 
+from ..utils import insert_column
+import numpy as np
+
 __all__ = [
     'get_word_event_mask',
     'subset_events',
@@ -67,8 +70,36 @@ def build_training_data(subject, experiment, paths, sessions=None, **kwargs):
                                             pre=kwargs['pre_event_buf'],
                                             post=kwargs['post_event_buf'])
 
+        ifr_events = load_events(subject, 'IFR1', sessions=sessions,
+                                rootdir=paths.root)
+        cleaned_ifr_events = clean_events(ifr_events,
+                                         start_time=kwargs['baseline_removal_start_time'],
+                                         end_time=kwargs['retrieval_time'],
+                                         duration=kwargs['empty_epoch_duration'],
+                                         pre=kwargs['pre_event_buf'],
+                                         post=kwargs['post_event_buf'])
+        if 'iscorrect' not in cleaned_ifr_events.dtype.names:
+          iscorrect_index = fr_events.dtype.names.index('iscorrect')
+          cleaned_ifr_events = insert_column(cleaned_ifr_events, 'iscorrect', 
+                                               np.full(cleaned_ifr_events.shape, -999), int, iscorrect_index)
+
+        icatfr_events = load_events(subject, 'ICatFR1',
+                                   sessions=sessions,
+                                   rootdir=paths.root)
+        cleaned_icatfr_events = clean_events(icatfr_events,
+                                            start_time=kwargs['baseline_removal_start_time'],
+                                            end_time=kwargs['retrieval_time'],
+                                            duration=kwargs['empty_epoch_duration'],
+                                            pre=kwargs['pre_event_buf'],
+                                            post=kwargs['post_event_buf'])
+
+        if 'iscorrect' not in cleaned_icatfr_events.dtype.names:
+            iscorrect_index = catfr_events.dtype.names.index('iscorrect')
+            cleaned_icatfr_events = insert_column(cleaned_icatfr_events, 'iscorrect', 
+                                                  np.full(cleaned_icatfr_events.shape, -999), int, iscorrect_index)
+
         free_recall_events = concatenate_events_across_experiments(
-            [cleaned_fr_events, cleaned_catfr_events], cat=True)
+            [cleaned_fr_events, cleaned_catfr_events, cleaned_ifr_events, cleaned_icatfr_events], cat=True)
 
     elif "FR" in experiment and not kwargs['combine_events']:
         free_recall_events = load_events(subject, experiment, sessions=sessions,
@@ -140,13 +171,38 @@ def build_test_data(subject, experiment, paths, joint_report, sessions=None,
             pre=kwargs['pre_event_buf'], post=kwargs['post_event_buf'],
             return_stim_events=True)
 
+        # Immediate Free Recall variants
+        ifr_events = load_events(subject, 'IFR' + series_num,
+                                 sessions=sessions,
+                                 rootdir=paths.root)
+        cleaned_ifr_events, ifr_stim_params = clean_events(
+            ifr_events, start_time=kwargs['baseline_removal_start_time'],
+            end_time=kwargs['retrieval_time'],
+            duration=kwargs['empty_epoch_duration'],
+            pre=kwargs['pre_event_buf'], post=kwargs['post_event_buf'],
+            return_stim_events=True)
+
+        icatfr_events = load_events(subject, 'ICatFR' + series_num,
+                                    sessions=sessions,
+                                    rootdir=paths.root)
+        cleaned_icatfr_events, icatfr_stim_params = clean_events(
+            icatfr_events, start_time=kwargs['baseline_removal_start_time'],
+            end_time=kwargs['retrieval_time'],
+            duration=kwargs['empty_epoch_duration'],
+            pre=kwargs['pre_event_buf'], post=kwargs['post_event_buf'],
+            return_stim_events=True)
+
         all_events = concatenate_events_across_experiments([fr_events,
-                                                            catfr_events])
+                                                            catfr_events,
+                                                            ifr_events,
+                                                            icatfr_events])
         task_events = concatenate_events_across_experiments(
             [cleaned_fr_events, cleaned_catfr_events], cat=True)
 
         stim_params = concatenate_events_across_experiments([fr_stim_params,
-                                                             catfr_stim_params],
+                                                             catfr_stim_params,
+                                                             ifr_stim_params,
+                                                             icatfr_stim_params],
                                                             stim=True)
 
     elif not joint_report and 'FR' in experiment:

ramutils/tasks/summary.py

@@ -275,7 +275,7 @@ def summarize_stim_sessions(all_events, task_events, stim_params, pairs_data,
         # TODO: Add some sort of data quality check here potentially. Do the
         # observed stim items match what we expect from classifier output?
 
-        if experiment in ['FR3', 'FR5', 'catFR3', 'catFR5', 'FR6', 'catFR6']:
+        if experiment in ['FR3', 'FR5', 'catFR3', 'catFR5', 'FR6', 'catFR6', 'ICatFR5', 'FR5', 'ICatFR6', 'FR6']:
             stim_events = dataframe_to_recarray(stim_df, expected_dtypes)
             stim_session_summary = FRStimSessionSummary()
             stim_session_summary.populate(

ramutils/utils.py

@@ -390,3 +390,32 @@ def encode_file(fd):
     """
     fd.seek(0)
     return base64.b64encode(fd.read()).decode()
+
+
+def insert_column(recarr, column_name, data, dtype, position):
+    """
+    Insert a column into a recarray at a specific position.
+
+    Parameters:
+    - recarr: the original recarray
+    - column_name: the name of the new column to be added
+    - data: the data for the new column
+    - dtype: the data type for the new column
+    - position: the position to insert the new column at
+    Returns:
+    - new_arr: a new recarray with the inserted column
+    """
+
+    if position > len(recarr.dtype.names):
+        raise ValueError("Position is out of range.")
+
+    before = [(name, recarr.dtype.fields[name][0]) for name in recarr.dtype.names[:position]]
+    after = [(name, recarr.dtype.fields[name][0]) for name in recarr.dtype.names[position:]]
+    new_dtype = np.dtype(before + [(column_name, dtype)] + after)
+
+    new_arr = np.rec.array(np.zeros(recarr.shape, dtype=new_dtype))
+
+    for name in recarr.dtype.names:
+        new_arr[name] = recarr[name]
+    new_arr[column_name] = data
+    return new_arr