fixed sort_level issue (-->df.sort_index())

radd/__init__.py

@@ -5,7 +5,7 @@
 __all__ = [ os.path.basename(f)[:-3] for f in modules]
 
 _package_dir = os.path.dirname(os.path.realpath(__file__))
-__version__ = '0.5.4'
+__version__ = '0.5.5'
 
 def load_example_data(name='elife'):
     """ load example data from elife (2015) or jneuro (2018) publications

radd/dfhandler.py

@@ -88,7 +88,7 @@ def make_observed_groupDFs(self):
         data = self.data.copy()
         ssdmethod = self.ssd_method
         self.grpData = data.groupby(np.hstack(['idx', self.conds]).tolist())
-        datdf = self.grpData.apply(analyze.rangl_data, ssdmethod, self.quantiles).sortlevel(0)
+        datdf = self.grpData.apply(analyze.rangl_data, ssdmethod, self.quantiles).sort_index(0)
         # self.datdf = datdf
         groupvalues = datdf.reset_index()[self.groups].values
         nan_data = np.zeros((groupvalues.shape[0], len(odf_header)), dtype=np.int64)

radd/tools/analyze.py

@@ -75,11 +75,13 @@ def rangl_data(data, ssd_method='all', quantiles=np.linspace(.01,.99,15), fit_on
         goQuery = 'ttype=="go"'
         stopQuery = 'ttype=="stop"'
     gac = data.query(goQuery).acc.mean()
+
     grt = data.query('response==1 & acc==1').rt.values
     ert = data.query('response==1 & acc==0').rt.values
     gq = mq(grt[grt<5.], prob=quantiles)
     eq = mq(ert[ert<5.], prob=quantiles)
     data_vector = [gac, gq, eq]
+
     if 'ssd' in data.columns:
         stopdf = data.query(stopQuery)
         if 'probe' in stopdf.columns:
@@ -89,6 +91,7 @@ def rangl_data(data, ssd_method='all', quantiles=np.linspace(.01,.99,15), fit_on
         elif ssd_method=='central':
             sacc = np.array([stopdf.mean()['acc']])
         data_vector.insert(1, sacc)
+
     return np.hstack(data_vector)
 
 

setup.py

@@ -9,7 +9,7 @@
 
 setup(
     name='RADD',
-    version='0.5.4',
+    version='0.5.5',
     author='Kyle Dunovan, Timothy Verstynen, Jeremy Huang',
     author_email='dunovank@gmail.com',
     url='http://github.com/CoAxLab/radd',