Fix gridder (#279)

* Added

* Fix

* Remove bymistake add

* Fix

* Fixed lint

* Lint

* Added refbackend

* Fix NDFT

* feat: use finufft as ref backend.

* feat(tests): move ndft vs nufft tests to own file.

* Added a bunch of extra codes

* PEP fixes

* Update siemens.py

* Added fixes

* add [docs]

* Fixes and updates on the locatuions

* Fix display3D

* Fix style [doc]

---------

Co-authored-by: chaithyagr <[email protected]>
Co-authored-by: Pierre-antoine Comby <[email protected]>

Author: 3 people

src/mrinufft/trajectories/display3D.py

@@ -101,7 +101,7 @@ def get_gridded_trajectory(
             np.tile(np.linspace(1, 10, trajectory.shape[1]), (trajectory.shape[0],)),
             None,
             True,
-        )
+        ) / (gridded_ones + np.finfo(np.float32).eps)
     elif grid_type == "inversion":
         data = grid_op.raw_op.adj_op(
             np.repeat(
@@ -110,7 +110,7 @@ def get_gridded_trajectory(
             )[: samples.shape[0]],
             None,
             True,
-        )
+        ) / (gridded_ones + np.finfo(np.float32).eps)
     elif grid_type == "holes":
         data = np.abs(gridded_ones).squeeze() < threshold
         if elliptical_samp:
@@ -143,5 +143,5 @@ def get_gridded_trajectory(
             data = np.hstack([slews, np.zeros((slews.shape[0], 2, slews.shape[2]))])
         data = grid_op.raw_op.adj_op(
             np.linalg.norm(data, axis=-1).flatten(), None, True
-        )
+        ) / (gridded_ones + np.finfo(np.float32).eps)
     return np.squeeze(np.abs(data))

src/mrinufft/trajectories/inits/travelling_salesman.py

@@ -30,23 +30,22 @@ def _sort_by_coordinate(array: NDArray, coord: Coordinate) -> NDArray:
             f"Invalid `coord`='{coord}' for arrays with less than 3 dimensions."
         )
 
-    match coord.lower():
-        case "x":
-            coord = array[..., 0]
-        case "y":
-            coord = array[..., 1]
-        case "z":
-            coord = array[..., 2]
-        case "r":
-            coord = np.linalg.norm(array, axis=-1)
-        case "phi":
-            coord = np.sign(array[..., 1]) * np.arccos(
-                array[..., 0] / nl.norm(array[..., :2], axis=-1)
-            )
-        case "theta":
-            coord = np.arccos(array[..., 2] / nl.norm(array, axis=-1))
-        case _:
-            raise ValueError(f"Unknown coordinate `{coord}`")
+    if coord == "x":
+        coord = array[..., 0]
+    elif coord == "y":
+        coord = array[..., 1]
+    elif coord == "z":
+        coord = array[..., 2]
+    elif coord == "r":
+        coord = np.linalg.norm(array, axis=-1)
+    elif coord == "phi":
+        coord = np.sign(array[..., 1]) * np.arccos(
+            array[..., 0] / nl.norm(array[..., :2], axis=-1)
+        )
+    elif coord == "theta":
+        coord = np.arccos(array[..., 2] / nl.norm(array, axis=-1))
+    else:
+        raise ValueError(f"Unknown coordinate `{coord}`")
     order = np.argsort(coord)
     return array[order]