.github/workflows/tests.yml

@@ -35,8 +35,6 @@ jobs:
         pip install pytest
         pip install diffrax
         pip install .
-        echo "numpy version installed:"
-        python -c "import numpy; print(numpy.__version__)"
 
     - name: Run Single Device Tests
       run: |

jaxpm/distributed.py

@@ -166,7 +166,7 @@ def uniform_particles(mesh_shape, sharding=None):
                          axis=-1)
 
 
-def normal_field(seed, shape, sharding=None, dtype=float):
+def normal_field(seed , shape, sharding=None, dtype='float32'):
     """Generate a Gaussian random field with the given power spectrum."""
     gpu_mesh = sharding.mesh if sharding is not None else None
     if gpu_mesh is not None and not (gpu_mesh.empty):

jaxpm/pm.py

@@ -131,7 +131,7 @@ def linear_field(mesh_shape, box_size, pk, seed, sharding=None):
     Generate initial conditions.
     """
     # Initialize a random field with one slice on each gpu
-    field = normal_field(seed=seed, shape=mesh_shape, sharding=sharding)
+    field = normal_field(seed=seed , shape=mesh_shape, sharding=sharding)
     field = fft3d(field)
     kvec = fftk(field)
     kmesh = sum((kk / box_size[i] * mesh_shape[i])**2

requirements-test.txt

@@ -1,4 +1,3 @@
 pfft-python @ git+https://github.com/MP-Gadget/pfft-python
 pmesh @ git+https://github.com/MP-Gadget/pmesh
 fastpm @ git+https://github.com/ASKabalan/fastpm-python
-numpy==2.2.6