Merge pull request #65 from arcondello/numpy-2.0

Support NumPy 2.0

.circleci/config.yml

@@ -215,7 +215,9 @@ jobs:
     parameters:
       python-version:
         type: string
-      dimod-version:
+      dependency-versions:
+        type: string
+      only-binary:
         type: string
 
     docker:
@@ -230,9 +232,9 @@ jobs:
           command: |
             python -m venv env
             . env/bin/activate
-            pip install -r requirements.txt
+            pip install << parameters.dependency-versions >> --upgrade --only-binary << parameters.only-binary >>
             pip install dwave-samplers --no-index -f dist/ --no-deps --force-reinstall
-            pip install 'dimod<< parameters.dimod-version >>' --only-binary=dimod -U
+
       - run: &unix-run-tests
           name: run tests
           command: |
@@ -310,17 +312,16 @@ workflows:
       - test-codecov
       - test-doctest
       - test-dependencies:
-          name: test-dependencies-dimod<< matrix.dimod-version >>-py<< matrix.python-version >>
+          name: test-dependencies-python<< matrix.python-version >>-dependencies=<< matrix.dependency-versions >>
           requires:
             - build-and-test-linux
           matrix:
             parameters:
-              # test the lowest and highest of each minor for the dependencies
-              dimod-version: [==0.12.0, ~=0.12.0]
-              python-version: *python-versions
-            exclude:
-              - dimod-version: ==0.12.0  # Does not support Python 3.12
-                python-version: 3.12.0
+              dependency-versions: [dimod==0.12.13 oldest-supported-numpy networkx==3.0, dimod numpy networkx]
+              # Skip some of the intermediate Python versions for speed. 3.8 gets a special callout because
+              # Numpy 2 does not support it, so we build it differently
+              python-version: ["3.8", "3.9", "3.12"]
+              only-binary: ["numpy,dimod,networkx"]
       - test-linux-cpp11  
       - test-sdist:
           requires:

docs/requirements.txt

@@ -1,4 +1,3 @@
 pydata-sphinx-theme==0.14.3
 sphinx==7.3.7
 reno[sphinx]==3.3.0
-networkx==2.6.3

dwave/samplers/greedy/descent.pyx

@@ -25,7 +25,6 @@ cimport numpy as np
 
 cimport dwave.samplers.greedy.decl as decl
 
-
 def steepest_gradient_descent(num_samples,
                               linear_biases,
                               coupler_starts, coupler_ends, coupler_weights,

dwave/samplers/greedy/sampler.py

@@ -188,14 +188,16 @@ def sample(self, bqm: dimod.BinaryQuadraticModel,
             This example samples a simple two-variable Ising model.
 
             >>> import dimod
-            >>> bqm = dimod.BQM.from_ising({}, {'ab': 1})
+            >>> bqm = dimod.BQM.from_ising({'a': -1}, {'ab': 1})
             ...
             >>> from dwave.samplers import SteepestDescentSampler
             >>> sampler = SteepestDescentSampler()
             ...
-            >>> samples = sampler.sample(bqm)
-            >>> samples.first.energy
-            -1.0
+            >>> sampleset = sampler.sample(bqm)
+            >>> print(sampleset)      # doctest: +SKIP
+               a  b energy num_oc. num_st.
+            0 +1 -1   -2.0       1       0
+            ['SPIN', 1 rows, 1 samples, 2 variables]
 
             Run steepest descent one million times (takes ~150ms on an average
             laptop), converging to local minima, each time starting from a

dwave/samplers/planar/sampler.py

@@ -53,9 +53,11 @@ def sample(self,
             >>> bqm.add_interaction('b', 'c', +1.0)
             >>> bqm.add_interaction('c', 'a', +1.0)
             >>> pos = {'a': (0, 0), 'b': (1, 0), 'c': (0, 1)}
-            >>> sample = PlanarGraphSolver().sample(bqm, pos)
-            >>> sample.first
-            Sample(sample={'a': 1, 'b': -1, 'c': -1}, energy=-1.0, num_occurrences=1)
+            >>> sampleset = PlanarGraphSolver().sample(bqm, pos)
+            >>> print(sampleset)
+               a  b  c energy num_oc.
+            0 +1 -1 -1   -1.0       1
+            ['SPIN', 1 rows, 1 samples, 3 variables]
 
         """
 

dwave/samplers/sa/sampler.py

@@ -287,8 +287,7 @@ def sample(self, bqm: dimod.BinaryQuadraticModel,
             >>> # Reuse a seed
             >>> a1 = next((sampler.sample(bqm, seed=88)).samples())['a']
             >>> a2 = next((sampler.sample(bqm, seed=88)).samples())['a']
-            >>> a1 == a2
-            True
+            >>> assert a1 == a2
 
             .. [#] :math:`\\beta` represents the inverse temperature, :math:`1/(k_B T)`, of a
                `Boltzmann distribution <https://en.wikipedia.org/wiki/Boltzmann_distribution>`_

dwave/samplers/tabu/sampler.py

@@ -39,11 +39,11 @@ class TabuSampler(dimod.Sampler, dimod.Initialized):
         This example solves a two-variable Ising model.
 
         >>> from dwave.samplers import TabuSampler
-        >>> samples = TabuSampler().sample_ising({'a': -0.5, 'b': 1.0}, {'ab': -1})
-        >>> list(samples.data()) # doctest: +SKIP
-        [Sample(sample={'a': -1, 'b': -1}, energy=-1.5, num_occurrences=1)]
-        >>> samples.first.energy
-        -1.5
+        >>> sampleset = TabuSampler().sample_ising({'a': -0.5, 'b': 1.0}, {'ab': -1}, num_restarts=0)
+        >>> print(sampleset)
+           a  b energy num_oc. num_re.
+        0 -1 -1   -1.5       1       0
+        ['SPIN', 1 rows, 1 samples, 2 variables]
 
     """
 
@@ -156,14 +156,16 @@ def sample(self, bqm: dimod.BinaryQuadraticModel,
             This example samples a simple two-variable Ising model.
 
             >>> import dimod
-            >>> bqm = dimod.BQM.from_ising({}, {'ab': 1})
+            >>> bqm = dimod.BQM.from_ising({'a': -1}, {'ab': 1})
 
             >>> from dwave.samplers import TabuSampler
             >>> sampler = TabuSampler()
 
-            >>> samples = sampler.sample(bqm)
-            >>> samples.first.energy
-            -1.0
+            >>> sampleset = sampler.sample(bqm, num_restarts=0)
+            >>> print(sampleset)
+               a  b energy num_oc. num_re.
+            0 +1 -1   -2.0       1       0
+            ['SPIN', 1 rows, 1 samples, 2 variables]
         """
 
         if not bqm:

dwave/samplers/tree/samplers.py

@@ -49,8 +49,10 @@ class TreeDecompositionSolver(dimod.Sampler):
         Find the ground state.
 
         >>> sampleset = solver.sample_ising(h, J)
-        >>> sampleset.first.sample
-        {'a': -1, 'b': -1}
+        >>> print(sampleset)
+           a  b energy num_oc.
+        0 -1 -1   -1.1       1
+        ['SPIN', 1 rows, 1 samples, 2 variables]
 
         Take multiple reads to find states of increasing energy.
 

pyproject.toml

@@ -3,9 +3,9 @@ requires = [
     "setuptools>=46.4.0",       # PEP-420 support, PEP-517/518 support, setup.cfg attr: support
     "wheel>=0.30.0",            # limited python api support
     "cython~=3.0",
-    'dimod==0.12.13',           # Lowest that support Python 3.8 through 3.12
+    'dimod==0.12.16',           # Lowest that support Python 3.8 through 3.12 and NumPy 2.0
     'numpy==1.19.0;python_version<"3.9"',  # C API for numpy.random
-    'oldest-supported-numpy;python_version>="3.9"',
+    'numpy~=2.0;python_version>="3.9"',
 ]
 build-backend = "setuptools.build_meta"
 

releasenotes/notes/NumPy-2.0-2b5756ee0fcdac2f.yaml

@@ -0,0 +1,6 @@
+---
+features:
+  - Support, and build with, NumPy 2.0
+upgrade:
+  - Require ``dimod>=0.12.13``.
+  - Require ``NetworkX>=3.0``.

requirements.txt

@@ -1,7 +1,7 @@
-cython==3.0.4
-dimod==0.12.13
+cython==3.0.10
+dimod==0.12.16
 numpy==1.19.0;python_version<"3.9"  # C API for numpy.random
-oldest-supported-numpy;python_version>="3.9"
+numpy==2.0.0;python_version>="3.9"
 reno==3.3.0  # for changelog
 setuptools>=46.4.0  # to support setup.cfg getting __version__
-networkx==2.6.3
+networkx==3.2.1

setup.cfg

@@ -40,6 +40,6 @@ zip_safe = false
 include_package_data = true
 python_requires = >=3.8
 install_requires =
-    numpy>=1.19.0,<2.0.0
-    dimod>=0.12.0,<0.13.0
-    networkx>=2.4.0
+    numpy>=1.19.0,<3.0.0
+    dimod>=0.12.13,<0.13.0  # oldest dimod that supports Python 3.12
+    networkx>=3.0