BUG: Fix pandas 0.13 compat issues. Closes #35.

Author: twiecki

hddm/likelihoods.py

@@ -49,7 +49,7 @@ def generate_wfpt_stochastic_class(wiener_params=None, sampling_method='cdf', cd
 
     #create likelihood function
     def wfpt_like(x, v, sv, a, z, sz, t, st, p_outlier=0):
-        return hddm.wfpt.wiener_like(x['rt'], v, sv, a, z, sz, t, st, p_outlier=p_outlier, **wp)
+        return hddm.wfpt.wiener_like(x['rt'].values, v, sv, a, z, sz, t, st, p_outlier=p_outlier, **wp)
 
 
     #create random function
@@ -241,4 +241,3 @@ def theoretical_quantiles(self, quantiles=(.1, .3, .5, .7, .9)):
 
 #create default Wfpt class
 Wfpt = generate_wfpt_stochastic_class()
-

hddm/models/hlba_truncated.py

@@ -15,7 +15,7 @@
 def lba_like(value, t, A, b, s, v, p_outlier, w_outlier=.1):
     """LBA likelihood.
     """
-    return hddm.lba.lba_like(value['rt'], A, b, t, s, v, 0, normalize_v=True, p_outlier=p_outlier, w_outlier=w_outlier)
+    return hddm.lba.lba_like(value['rt'].values, A, b, t, s, v, 0, normalize_v=True, p_outlier=p_outlier, w_outlier=w_outlier)
 
 def pdf(self, x):#value, t, A, b, s, v, p_outlier, w_outlier=.1):
     """LBA likelihood.

hddm/tests/test_models.py

@@ -9,7 +9,6 @@
 import numpy as np
 import pandas as pd
 import nose
-pd.set_printoptions(precision=4)
 from nose import SkipTest
 
 import hddm
@@ -303,7 +302,7 @@ def test_group_only_depends(self):
         data['cov'] = 1.
         # Create one merged column
         data['condition2'] = 'merged'
-        data[data.condition == 'c1']['condition2'] = 'single'
+        data.ix[data.condition == 'c1', 'condition2'] = 'single'
         self.assertRaises(AssertionError, hddm.HDDMRegressor, data, 'v ~ cov', depends_on={'v_Intercept': 'condition2'}, group_only_regressors=True)
 
     def test_contrast_coding(self):

hddm/utils.py

@@ -32,7 +32,7 @@ def flip_errors(data):
 
     # Flip sign for lower boundary response
     idx = data['response'] == 0
-    data['rt'].ix[idx] = -data['rt'].ix[idx]
+    data.ix[idx, 'rt'] = -data.ix[idx, 'rt']
 
     return data