ENH: Calculate TA and store in run_info

Author: effigies

bids/analysis/analysis.py

@@ -388,13 +388,22 @@ def get_design_matrix(self, names=None, format='long', mode='both',
 
             if sampling_rate == 'TR':
                 trs = {var.run_info[0].tr for var in self.collection.variables.values()}
+                tas = {var.run_info[0].ta for var in self.collection.variables.values()}
                 if not trs:
                     raise ValueError("Repetition time unavailable; specify sampling_rate "
                                      "explicitly")
                 elif len(trs) > 1:
                     raise ValueError("Non-unique Repetition times found ({!r}); specify "
-                                     "sampling_rate explicitly")
-                sampling_rate = 1. / trs.pop()
+                                     "sampling_rate explicitly".format(trs))
+                TR = trs.pop()
+                if not tas:
+                    warnings.warn("Acquisition time unavailable; assuming TA = TR")
+                    tas = {TR}
+                elif len(tas) > 1:
+                    raise ValueError("Non-unique acquisition times found ({!r})".format(tas))
+
+                sampling_rate = 1. / TR
+                acquisition_time = tas.pop()
             elif sampling_rate == 'highest':
                 sampling_rate = None
             dense_df = coll.to_df(names, format='wide',

bids/variables/entities.py

@@ -36,23 +36,25 @@ class RunNode(Node):
         image_file (str): The full path to the corresponding nifti image.
         duration (float): Duration of the run, in seconds.
         repetition_time (float): TR for the run.
+        acquisition_time (float): TA for the run.
         task (str): The task name for this run.
     '''
 
-    def __init__(self, entities, image_file, duration, repetition_time):
+    def __init__(self, entities, image_file, duration, repetition_time, acquisition_time):
         self.image_file = image_file
         self.duration = duration
         self.repetition_time = repetition_time
+        self.acquisition_time = acquisition_time
         super(RunNode, self).__init__('run', entities)
 
     def get_info(self):
 
         return RunInfo(self.entities, self.duration, self.repetition_time,
-                       self.image_file)
+                       self.acquisition_time, self.image_file)
 
 
 # Stores key information for each Run.
-RunInfo = namedtuple('RunInfo', ['entities', 'duration', 'tr', 'image'])
+RunInfo = namedtuple('RunInfo', ['entities', 'duration', 'tr', 'ta', 'image'])
 
 
 class NodeIndex(Node):

bids/variables/io.py

@@ -82,6 +82,24 @@ def load_variables(layout, types=None, levels=None, skip_empty=True,
     return dataset
 
 
+def _get_timing_info(img_md):
+    if 'RepetitionTime' in img_md:
+        tr = img_md['RepetitionTime']
+        if 'DelayTime' in img_md:
+            ta = tr - img_md['DelayTime']
+        elif 'SliceTiming' in img_md:
+            slicetimes = sorted(img_md['SliceTiming'])
+            # a, b ... z
+            # z = final slice onset, b - a = slice duration
+            ta = slicetimes[-1] + slicetimes[1] - slicetimes[0]
+        else:
+            ta = tr
+    elif 'VolumeTiming' in img_md:
+        return NotImplemented
+
+    return tr, ta
+
+
 def _load_time_variables(layout, dataset=None, columns=None, scan_length=None,
                          drop_na=True, events=True, physio=True, stim=True,
                          regressors=True, skip_empty=True, **selectors):
@@ -141,8 +159,9 @@ def _load_time_variables(layout, dataset=None, columns=None, scan_length=None,
         if 'run' in entities:
             entities['run'] = int(entities['run'])
 
-        tr = layout.get_metadata(img_f, suffix='bold', domains=domains,
-                                 full_search=True)['RepetitionTime']
+        img_md = layout.get_metadata(img_f, suffix='bold', domains=domains,
+                                     full_search=True)
+        tr, ta = _get_timing_info(img_md)
 
         # Get duration of run: first try to get it directly from the image
         # header; if that fails, try to get NumberOfVolumes from the
@@ -162,7 +181,8 @@ def _load_time_variables(layout, dataset=None, columns=None, scan_length=None,
                 raise ValueError(msg)
 
         run = dataset.get_or_create_node('run', entities, image_file=img_f,
-                                         duration=duration, repetition_time=tr)
+                                         duration=duration, repetition_time=tr,
+                                         acquisition_time=ta)
         run_info = run.get_info()
 
         # Process event files