Doc improvements

docs/api.rst

@@ -4,3 +4,5 @@
 
     mrinufft.operators
     mrinufft.trajectories
+    mrinufft.density
+    mrinufft.io

docs/misc/contributors.rst

@@ -2,3 +2,9 @@ Contributors
 ============
 
 Contributions to the project can be seen `here <https://github.com/mind-inria/mri-nufft/graphs/contributors>`_
+
+.. raw:: html
+
+  <a href="https://github.com/mind-inria/mri-nufft/graphs/contributors">
+     <img src="https://contrib.rocks/image?repo=mind-inria/mri-nufft" />
+  </a>

pyproject.toml

@@ -62,3 +62,6 @@ testpaths=["tests"]
 [tool.pylsp-mypy]
 enabled = false
 live_mode = false
+
+[tool.mypy]
+ignore_missing_imports = true

src/mrinufft/io/cfl.py

@@ -89,15 +89,16 @@ def traj2cfl(traj, shape, basename):
     """
     Export a trajectory defined in MRI-nufft to a BART compatible format.
 
+    The trajectory will be normalized to -(FOV-1)/2 +(FOV-1)/2,
+    and reshape to BART format.
+
     Parameters
     ----------
     traj: array_like
         trajectory array, shape (N_shot, N_points, 2 or 3)
     shape: tuple
         volume shape (FOV)
 
-    The trajectory will be normalized to -(FOV-1)/2 +(FOV-1)/2,
-    and reshape to BART format.
     """
     traj_ = traj * (np.array(shape) - 1)
     if traj.shape[-1] == 2:

src/mrinufft/io/nsp.py

@@ -1,4 +1,4 @@
-"""Read/Write trajectoru for Neurospin sequences."""
+"""Read/Write trajectory for Neurospin sequences."""
 
 import warnings
 import os

src/mrinufft/operators/interfaces/gpunufft.py

@@ -4,6 +4,7 @@
 import warnings
 from ..base import FourierOperatorBase
 from mrinufft._utils import proper_trajectory
+from mrinufft.density import get_density
 
 GPUNUFFT_AVAILABLE = True
 try:
@@ -300,13 +301,7 @@ def __init__(
         self.dtype = self.samples.dtype
         self.n_coils = n_coils
         self.smaps = smaps
-        if density is True:
-            self.density = self.pipe(self.samples, shape)
-        elif isinstance(density, np.ndarray):
-            self.density = density
-        else:
-            self.density = None
-        self.kwargs = kwargs
+        self.density = get_density(density)
         self.impl = RawGpuNUFFT(
             samples=self.samples,
             shape=self.shape,