From 382ec92efa92f8d6c4e65d607853f5b13b7b6f1f Mon Sep 17 00:00:00 2001
From: Oscar Esteban <code@oscaresteban.es>
Date: Thu, 25 Aug 2022 14:17:41 +0200
Subject: [PATCH] FIX: Integration test with B0 (trivial) model

Drops the use of a real AFNI series of transforms. Instead, generate a
number of large-yet-plausible transformations for head motion.

Follow-up: #84.
Part-of: #40.
---
 test/test_integration.py | 49 ++++++++++++++++++++++++++++++++++------
 1 file changed, 42 insertions(+), 7 deletions(-)

diff --git a/test/test_integration.py b/test/test_integration.py
index b8d04e47..0cb1b3e1 100644
--- a/test/test_integration.py
+++ b/test/test_integration.py
@@ -36,18 +36,47 @@ def test_proximity_estimator_trivial_model(datadir, tmp_path):
     dwdata = DWI.from_filename(datadir / "dwi.h5")
     b0nii = nb.Nifti1Image(dwdata.bzero, dwdata.affine, None)
 
-    xfms = nt.linear.load(
-        datadir / "head-motion-parameters.aff12.1D",
-        fmt="afni",
+    # Generate a list of large-yet-plausible bulk-head motion.
+    xfms = nt.linear.LinearTransformsMapping(
+        [
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(x=0.03, z=0.005), (0.8, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(x=0.02, z=0.005), (0.8, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(x=0.02, z=0.02), (0.4, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(x=-0.02, z=0.02), (0.4, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(x=-0.02, z=0.002), (0.0, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(y=-0.02, z=0.002), (0.0, 0.2, 0.2)
+            ),
+            nb.affines.from_matvec(
+                nb.eulerangles.euler2mat(y=-0.01, z=0.002), (0.0, 0.4, 0.2)
+            ),
+        ],
+        reference=b0nii,
     )
-    xfms.reference = b0nii
 
-    # Generate a dataset with 10 b-zeros and motion
+    # Induce motion into dataset (i.e., apply the inverse transforms)
+    moved_nii = (~xfms).apply(b0nii, reference=b0nii)
+
+    # Uncomment to see the moved dataset
+    # moved_nii.to_filename(tmp_path / "test.nii.gz")
+    # xfms.apply(moved_nii).to_filename(tmp_path / "ground_truth.nii.gz")
+
+    # Wrap into dataset object
     dwi_motion = DWI(
-        dataobj=(~xfms).apply(b0nii, reference=b0nii).dataobj,
+        dataobj=moved_nii.dataobj,
         affine=b0nii.affine,
         bzero=dwdata.bzero,
-        gradients=dwdata.gradients[..., :10],
+        gradients=dwdata.gradients[..., : len(xfms)],
         brainmask=dwdata.brainmask,
     )
 
@@ -56,6 +85,12 @@ def test_proximity_estimator_trivial_model(datadir, tmp_path):
         dwdata=dwi_motion, n_iter=1, model="b0", align_kwargs=None, seed=None
     )
 
+    # Uncomment to see the realigned dataset
+    # nt.linear.LinearTransformsMapping(
+    #     em_affines,
+    #     reference=b0nii,
+    # ).apply(moved_nii).to_filename(tmp_path / "realigned.nii.gz")
+
     # For each moved b0 volume
     coords = xfms.reference.ndcoords.T
     for i, est in enumerate(em_affines):