Merge branch 'master' into fix_issue_211

docs/binder/environment.yml

@@ -7,4 +7,6 @@ dependencies:
   - jupyter>=1.0.0
   - pip:
       - mri-nufft[finufft]
-      - pynfft2
+      - joblib
+      - brainweb-dl
+      - torch

docs/sphinx_add_colab_link.py

@@ -73,7 +73,7 @@ def notebook_modifier(self, notebook_path, commands):
         idx = self.find_index_of_colab_link(notebook)
         code_lines = ["# Install libraries"]
         code_lines.append(commands)
-        code_lines.append("pip install brainweb-dl  # Required for data")
+        code_lines.append("!pip install brainweb-dl  # Required for data")
         dummy_notebook_content = {"cells": []}
         add_code_cell(
             dummy_notebook_content,

examples/GPU/example_cg.py

@@ -24,6 +24,12 @@
         - https://en.wikipedia.org/wiki/Momentum
 """
 
+# %%
+# .. colab-link::
+#    :needs_gpu: 1
+#
+#    !pip install mri-nufft[gpunufft] scikit-image
+
 # %%
 # Imports
 import numpy as np

examples/GPU/example_fastMRI_UNet.py

@@ -33,6 +33,11 @@
 .. warning::
     We train on a single image here. In practice, this should be done on a database like fastMRI [fastmri]_.
 """
+# %%
+# .. colab-link::
+#    :needs_gpu: 1
+#
+#    !pip install mri-nufft[gpunufft] scikit-image fastmri
 
 # %%
 # Imports

examples/GPU/example_learn_samples.py

@@ -19,6 +19,13 @@
 .. warning::
     This example only showcases the autodiff capabilities, the learned sampling pattern is not scanner compliant as the scanner gradients required to implement it violate the hardware constraints. In practice, a projection :math:`\Pi_\mathcal{Q}(\mathbf{K})` into the scanner constraints set :math:`\mathcal{Q}` is recommended (see [Proj]_). This is implemented in the proprietary SPARKLING package [Sparks]_. Users are encouraged to contact the authors if they want to use it.
 """
+
+# %%
+# .. colab-link::
+#    :needs_gpu: 1
+#
+#    !pip install mri-nufft[gpunufft] scikit-image
+
 import time
 import joblib
 

pyproject.toml

@@ -4,7 +4,7 @@ description = "MRI Non-Cartesian Fourier Operators with multiple computation bac
 authors = [{name="Pierre-antoine Comby", email="[email protected]"}]
 
 readme = "README.md"
-dependencies = ["numpy<2.0", "scipy", "matplotlib", "tqdm"]
+dependencies = ["numpy<=2.0.0", "scipy", "matplotlib", "tqdm"]
 requires-python = ">=3.8"
 
 dynamic = ["version"]
@@ -15,7 +15,7 @@ gpunufft = ["gpuNUFFT>=0.9.0", "cupy-cuda12x"]
 torchkbnufft = ["torchkbnufft", "cupy-cuda12x"]
 cufinufft = ["cufinufft<2.3", "cupy-cuda12x"]
 finufft = ["finufft"]
-pynfft = ["pynfft2>=1.4.3", "numpy>=2.0.0"]
+pynfft = ["pynfft2>=1.4.3; python_version < '3.12'", "numpy>=2.0.0; python_version < '3.12'"]
 pynufft = ["pynufft"]
 io = ["pymapvbvd"]
 smaps = ["scikit-image"]

src/mrinufft/io/cfl.py

@@ -71,8 +71,7 @@ def _writecfl(array, cfl_file, hdr_file=None):
 
     with open(hdr_file, "w") as h:
         h.write("# Dimensions\n")
-        for i in array.shape:
-            h.write("%d " % i)
+        h.write("".join(f"{i} " for i in array.shape))
         h.write("\n")
 
     size = np.prod(array.shape) * np.dtype(np.complex64).itemsize

src/mrinufft/operators/off_resonance.py

@@ -223,14 +223,15 @@ def __init__(
     ):
         if backend == "gpu" and not CUPY_AVAILABLE:
             raise RuntimeError("Cupy is required for gpu computations.")
-        if backend == "torch":
+        elif backend == "torch":
             self.xp = torch
-        if backend == "gpu":
+        elif backend == "gpu":
             self.xp = cp
         elif backend == "cpu":
             self.xp = np
         else:
             raise ValueError("Unsupported backend.")
+
         self._fourier_op = fourier_op
 
         self.n_coils = fourier_op.n_coils
@@ -311,7 +312,7 @@ def adj_op(self, coeffs, *args):
 
         """
         y = 0.0
-        coeffs_d = self.xp.array(coeffs)
+        coeffs_d = self.xp.asarray(coeffs)
         if self.C is not None:
             for idx in range(self.n_interpolators):
                 y += self.xp.conj(self.C[idx]) * self._fourier_op.adj_op(