Remove odict and fix test (#259)

* input observed data as dictionary

* add tests for log_likelihood and observed_data

* remove odict and fix test

arviz/plots/plot_utils.py

@@ -1,6 +1,5 @@
 """Utilities for plotting."""
 from itertools import product
-from collections import OrderedDict as odict
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -204,7 +203,7 @@ def xarray_var_iter(data, var_names=None, combined=False, skip_dims=None, revers
         if var_name in data:
             new_dims = [dim for dim in data[var_name].dims if dim not in skip_dims]
             vals = [data[var_name][dim].values for dim in new_dims]
-            dims = [odict((k, v) for k, v in zip(new_dims, prod)) for prod in product(*vals)]
+            dims = [{k : v for k, v in zip(new_dims, prod)} for prod in product(*vals)]
             if reverse_selections:
                 dims = reversed(dims)
 

arviz/tests/test_plot_utils.py

@@ -26,14 +26,20 @@ def test_dataset_to_numpy_not_combined(sample_dataset):  # pylint: disable=inval
 
     # 2 vars x 2 chains
     assert len(var_names) == 4
-    assert (data == np.concatenate((mu, tau), axis=0)).all()
+    mu_tau = np.concatenate((mu, tau), axis=0)
+    tau_mu = np.concatenate((tau, mu), axis=0)
+    deqmt = data == mu_tau
+    deqtm = data == tau_mu
+    assert deqmt.all() or deqtm.all()
 
 
 def test_dataset_to_numpy_combined(sample_dataset):
     mu, tau, data = sample_dataset
     var_names, data = xarray_to_ndarray(data, combined=True)
 
     assert len(var_names) == 2
+    if var_names[0] == 'tau':
+        data = data[::-1]
     assert (data[0] == mu.reshape(1, 6)).all()
     assert (data[1] == tau.reshape(1, 6)).all()