0.3.1

* Updated README to rst and removed erroneous file

* removed extra file

* updated README to .rst, added badges for coveralls and appveyor

* updated badges

* removed target from badges

* and now on one line...

* more badge stuff

* updates rst

* removed extra file

* updated README to .rst, added badges for coveralls and appveyor

* updated badges

* removed target from badges

* and now on one line...

* more badge stuff

* rst code snippets

* few more readme fixes

* more readme stuff

* added numpy tests and more reasonable returns for empty responses

* 0.3.0 -> 0.3.1 in __init__ for dev branch

* bug fix with relabel having unexpected keyword

README.rst

@@ -24,19 +24,16 @@ dimod comes with a few samplers that are useful as reference implementations and
 Basic Usage
 -----------
 
-```python
 >>> import dimod
 >>> sampler = dimod.SimulatedAnnealingSampler()
 >>> Q = {(0, 0): 1, (1, 1): 1, (0, 1): -1}
 >>> response = sampler.sample_qubo(Q)
 >>> h = {0: 1, 1 : 1}
 >>> J = {(0, 1): -1}
 >>> spin_response = sampler.sample_ising(h, J)
-```
 
 The response object returned has many ways to access the information
 
-```python
 >>> list(response)  # your results might vary
 [{0: 0.0, 1: 0.0}, {0: 0.0, 1: 0.0}, {0: 0.0, 1: 0.0}, {0: 0.0, 1: 0.0}, {0: 0.0, 1: 0.0}, {0: 1.0, 1: 0.0}, {0: 1.0, 1: 0.0}, {0: 0.0, 1: 1.0}, {0: 0.0, 1: 1.0}, {0: 1.0, 1: 1.0}]
 >>> list(response.samples())
@@ -45,7 +42,7 @@ The response object returned has many ways to access the information
 [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0]
 >>> list(response.items())  # samples and energies
 [({0: 0.0, 1: 0.0}, 0.0), ({0: 0.0, 1: 0.0}, 0.0), ({0: 0.0, 1: 0.0}, 0.0), ({0: 0.0, 1: 0.0}, 0.0), ({0: 0.0, 1: 0.0}, 0.0), ({0: 1.0, 1: 0.0}, 1.0), ({0: 1.0, 1: 0.0}, 1.0), ({0: 0.0, 1: 1.0}, 1.0), ({0: 0.0, 1: 1.0}, 1.0), ({0: 1.0, 1: 1.0}, 1.0)]
-```
+
 
 See documentation for more examples.
 
@@ -54,15 +51,15 @@ Install
 
 Compatible with Python 2 and 3.
 
-`pip install dimod`
+>>> pip install dimod
 
 To install with optional components
 
-`pip install dimod[all]`
+>>> pip install dimod[all]
 
 To install from source:
 
-`python setup.py install`
+>>> python setup.py install
 
 License
 -------

dimod/__init__.py

@@ -2,7 +2,7 @@
 
 import sys
 
-__version__ = '0.3.0'
+__version__ = '0.3.1'
 __author__ = 'D-Wave Systems Inc.'
 __authoremail__ = 'acondello@dwavesys.com'
 __description__ = 'A shared API for binary quadratic model samplers.'

dimod/decorators.py

@@ -207,7 +207,7 @@ def _qubo_index_labels(f, *args, **kw):
         response = f(*newargs, **kw)
 
         # the returned response will need to be relabelled with inv_relabel
-        return response.relabel_samples(inv_relabel, copy=True)
+        return response.relabel_samples(inv_relabel)
 
     return _qubo_index_labels
 

dimod/responses/numpy_response.py

@@ -290,11 +290,23 @@ def add_samples_from_array(self, samples, energies, sample_data=None, sorted_by_
 
     def samples_array(self):
         """Returns the :obj:`numpy.ndarray` containing the samples."""
-        return self._samples
+        import numpy as np
+
+        samples = self._samples
+        if samples is None:
+            return np.empty((0, 0), dtype=int)
+        else:
+            return samples
 
     def energies_array(self):
         """Returns the :obj:`numpy.ndarray` containing the energies."""
-        return self._energies
+        import numpy as np
+
+        energies = self._energies
+        if energies is None:
+            return np.empty((0,), dtype=float)
+        else:
+            return energies
 
 
 class NumpySpinResponse(NumpyResponse):

dimod/responses/tests/test_numpy_response.py

@@ -78,6 +78,44 @@ def test_input_checking(self):
         with self.assertRaises(ValueError):
             response.add_samples_from_array(np.asarray([[0]]), np.asarray([0.0]), [{}, {}])
 
+    def test_sample_array_and_energy_array(self):
+
+        # first try loading them up by matrices
+        samples = np.asarray([[-1, -1, -1, -1],
+                              [1, 1, 1, 1],
+                              [-1, 1, -1, 1]])
+
+        h = {0: 1, 1: -1, 2: 1, 3: 1}
+        J = {(0, 2): -1, (2, 3): 1, (0, 2): .25}
+
+        energies = np.asarray([ising_energy(h, J, row) for row in samples])
+
+        response = self.response_factory()
+        response.add_samples_from_array(samples, energies)
+
+        r_samples = response.samples_array()
+        r_energies = response.energies_array()
+
+        # assert that samples are sorted by energy and that they agree
+        for idx, row in enumerate(r_samples):
+            self.assertEqual(ising_energy(h, J, row), r_energies[idx])
+
+        for idx in range(len(r_energies) - 1):
+            self.assertLessEqual(r_energies[idx], r_energies[idx + 1])
+        self.assertEqual(r_samples.ndim, 2)
+        self.assertEqual(r_energies.ndim, 1)
+
+        # test the empty case
+        response = self.response_factory()
+        r_samples = response.samples_array()
+        r_energies = response.energies_array()
+
+        self.assertIsInstance(r_energies, np.ndarray)
+        self.assertIsInstance(r_samples, np.ndarray)
+
+        self.assertEqual(r_samples.ndim, 2)
+        self.assertEqual(r_energies.ndim, 1)
+
 
 @unittest.skipUnless(_numpy, "numpy not installed")
 class TestSpinResponse(unittest.TestCase, ResponseGenericTests):