Merge pull request #56 from CSchoel/numpy2

Numpy2

.github/workflows/ci.yaml

@@ -19,8 +19,8 @@ jobs:
           python-version: ${{ matrix.python }}
       - run: pip install ".${{ matrix.extras }}"
       - run: pip install codecov .
-        env:
-          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
       - run: coverage run -m unittest nolds.test_measures
       - run: codecov
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
         if: ${{ matrix.python == '3.10' && matrix.extras != '' }}

CHANGELOG.md

@@ -11,6 +11,9 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 * Regression tests for all major algorithms that check for small changes in the main output value.
 
 ### Changed
+
+* Nolds now supports numpy 2.x as well as 1.x.
+
 ### Fixed
 
 ## [0.6.0]

nolds/datasets.py

@@ -23,15 +23,19 @@ def lorenz_euler(length, sigma, rho, beta, dt=0.01, start=[1,1,1]):
   """
   def lorenz(state, sigma, rho, beta):
     x, y, z = state
+    # NOTE: Numpy 1.x stores intermediate results as float64
+    # => to achieve consistency between numpy versions, we have to use
+    #    float32 for all values that enter the formula to simulate numpy 1.x
+    #    behavior with numpy 2.x.
     return np.array([
-      sigma * (y - x),
-      rho * x - y - x * z,
-      x * y - beta * z
+      np.float32(sigma) * (y - x),
+      np.float32(rho) * x - y - x * z,
+      x * y - np.float32(beta) * z
     ], dtype="float32")
   trajectory = np.zeros((length, 3), dtype="float32")
   trajectory[0] = start
   for i in range(1, length):
-    t = i * dt
+    # t = i * dt
     trajectory[i] = trajectory[i-1] + lorenz(trajectory[i-1], sigma, rho, beta) * dt
   return trajectory
 

nolds/test_measures.py

@@ -36,7 +36,7 @@ def assert_array_equals(self, expected, actual, print_arrays=False):
       print("==")
       print(expected)
       print()
-    self.assertTrue(np.alltrue(actual == expected))
+    self.assertTrue(np.all(actual == expected))
 
   def test_delay_embed_lag2(self):
     data = np.arange(10, dtype="float32")
@@ -459,7 +459,7 @@ def test_lorenz(self):
     x = data[discard:,1]
     rvals = nolds.logarithmic_r(1, np.e, 1.1)  # determined experimentally
     cd = nolds.corr_dim(x, emb_dim, fit="poly", rvals=rvals, lag=lag)
-    self.assertAlmostEqual(cd, 2.05, delta=0.1)
+    self.assertAlmostEqual(cd, 2.05, delta=0.2)
 
   def test_logistic(self):
     # TODO replicate tests with logistic map from grassberger-procaccia

setup.py

@@ -57,7 +57,7 @@ def run(self):
     ],
     test_suite='nolds.test_measures',
     install_requires=[
-        'numpy<2.0',
+        'numpy>1.0,<3.0',
         'future',
         'setuptools'
     ],