Merge branch 'audit'

bet/sampling/adaptiveSampling.py

@@ -277,7 +277,7 @@ def generalized_chains(self, param_min, param_max, t_set, kern,
         # hypercube/space-filling curve to fully explore parameter space - not
         # necessarily random). Call these Samples_old.
         (samples_old, data_old) = super(sampler, self).random_samples(
-                initial_sample_type, param_min, param_max, psavefile,
+                initial_sample_type, param_min, param_max, savefile,
                 self.num_chains, criterion)
         self.num_samples = self.chain_length * self.num_chains
         comm.Barrier()
@@ -326,8 +326,10 @@ def generalized_chains(self, param_min, param_max, t_set, kern,
             mdat['step_ratios'] = all_step_ratios
             mdat['samples'] = samples
             mdat['data'] = data
-            super(sampler, self).save(mdat, psavefile)
-
+            if size > 1:
+                super(sampler, self).save(mdat, psavefile)
+            else:
+                super(sampler, self).save(mdat, savefile)
             MYsamples_old = samples_new
 
         # collect everything

setup.py

@@ -5,15 +5,18 @@
 '''
 The python script for building the BET package and subpackages.
 '''
-from distutils.core import setup
+try:
+  from setuptools import setup
+except ImportError:
+    from distutils.core import setup
 
 setup(name='bet',
       version='0.2.0',
       description='Butler, Estep, Tavener method',
       author='Steven Mattis',
       author_email='[email protected]',
-      liscense='GNU LGPL',
+      license='GNU LGPL',
       url='https://github.com/UT-CHG/BET',
       packages=['bet', 'bet.sampling', 'bet.calculateP', 'bet.postProcess'],
-      install_requires=['matplotlib', 'mpl_toolkits', 'pyDOE', 'scipy',
+      install_requires=['matplotlib', 'pyDOE', 'scipy',
           'numpy'])