Faster ptt

.pre-commit-config.yaml

@@ -0,0 +1,18 @@
+default_language_version:
+  python: python3
+
+repos:
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.14.10
+    hooks:
+      # Run the linter
+      - id: ruff
+        args: [ --fix, --config, pyproject.toml ]
+      # Run the formatter
+      - id: ruff-format
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.3.0
+    hooks:
+      - id: codespell
+        additional_dependencies:
+          - tomli

CLAUDE.md

@@ -49,9 +49,9 @@ cuslines/
     cu_propagate_seeds.py       # SeedBatchPropagator: chunked seed processing
     cu_direction_getters.py     # Direction getter ABC + Boot/Prob/PTT implementations
     cutils.py                   # REAL_DTYPE, REAL3_DTYPE, checkCudaErrors(), ModelType enum
-    _globals.py                 # AUTO-GENERATED from globals.h (never edit manually)
+    _globals.py                 # Global constants useful for all languages
   cuda_c/                       # CUDA kernel source
-    globals.h                   # Source-of-truth for constants (REAL_SIZE, thread config)
+    globals.h                   # CUDA specific global constants
     generate_streamlines_cuda.cu, boot.cu, ptt.cu, tracking_helpers.cu, utils.cu
     cudamacro.h, cuwsort.cuh, ptt.cuh, disc.h
   metal/                        # Metal backend (mirrors cuda_python/)
@@ -82,7 +82,6 @@ Each has `from_dipy_*()` class methods for initialization from DIPY models.
 
 ## Critical Conventions
 
-- **`_globals.py` is auto-generated** from `cuslines/cuda_c/globals.h` during `setup.py` build via `defines_to_python()`. Never edit it manually; change `globals.h` and rebuild.
 - **GPU arrays must be C-contiguous** — always use `np.ascontiguousarray()` and project scalar types (`REAL_DTYPE`, `REAL_SIZE` from `cutils.py` or `mutils.py`).
 - **All CUDA API calls must be wrapped** with `checkCudaErrors()`.
 - **Angle units**: CLI accepts degrees, internals convert to radians before the GPU layer.

cuslines/__init__.py

@@ -34,25 +34,37 @@ def _detect_backend():
 BACKEND = _detect_backend()
 
 if BACKEND == "metal":
+    from cuslines.metal import (
+        MetalBootDirectionGetter as BootDirectionGetter,
+    )
     from cuslines.metal import (
         MetalGPUTracker as GPUTracker,
+    )
+    from cuslines.metal import (
         MetalProbDirectionGetter as ProbDirectionGetter,
+    )
+    from cuslines.metal import (
         MetalPttDirectionGetter as PttDirectionGetter,
-        MetalBootDirectionGetter as BootDirectionGetter,
     )
 elif BACKEND == "cuda":
     from cuslines.cuda_python import (
+        BootDirectionGetter,
         GPUTracker,
         ProbDirectionGetter,
         PttDirectionGetter,
-        BootDirectionGetter,
     )
 elif BACKEND == "webgpu":
     from cuslines.webgpu import (
-        WebGPUTracker as GPUTracker,
+        WebGPUBootDirectionGetter as BootDirectionGetter,
+    )
+    from cuslines.webgpu import (
         WebGPUProbDirectionGetter as ProbDirectionGetter,
+    )
+    from cuslines.webgpu import (
         WebGPUPttDirectionGetter as PttDirectionGetter,
-        WebGPUBootDirectionGetter as BootDirectionGetter,
+    )
+    from cuslines.webgpu import (
+        WebGPUTracker as GPUTracker,
     )
 else:
     raise ImportError(

cuslines/boot_utils.py

@@ -8,45 +8,62 @@
 from dipy.reconst import shm
 
 
-def prepare_opdt(gtab, sphere, sh_order_max=6, full_basis=False,
-                 sh_lambda=0.006, min_signal=1):
+def prepare_opdt(
+    gtab, sphere, sh_order_max=6, full_basis=False, sh_lambda=0.006, min_signal=1
+):
     """Build bootstrap matrices for the OPDT model.
 
     Returns dict with keys: model_type, min_signal, H, R, delta_b,
     delta_q, sampling_matrix, b0s_mask.
     """
     sampling_matrix, _, _ = shm.real_sh_descoteaux(
-        sh_order_max, sphere.theta, sphere.phi,
-        full_basis=full_basis, legacy=True,
+        sh_order_max,
+        sphere.theta,
+        sphere.phi,
+        full_basis=full_basis,
+        legacy=True,
     )
     model = shm.OpdtModel(
-        gtab, sh_order_max=sh_order_max, smooth=sh_lambda,
+        gtab,
+        sh_order_max=sh_order_max,
+        smooth=sh_lambda,
         min_signal=min_signal,
     )
     delta_b, delta_q = model._fit_matrix
 
     H, R = _hat_and_lcr(gtab, model, sh_order_max)
 
     return dict(
-        model_type="OPDT", min_signal=min_signal,
-        H=H, R=R, delta_b=delta_b, delta_q=delta_q,
-        sampling_matrix=sampling_matrix, b0s_mask=gtab.b0s_mask,
+        model_type="OPDT",
+        min_signal=min_signal,
+        H=H,
+        R=R,
+        delta_b=delta_b,
+        delta_q=delta_q,
+        sampling_matrix=sampling_matrix,
+        b0s_mask=gtab.b0s_mask,
     )
 
 
-def prepare_csa(gtab, sphere, sh_order_max=6, full_basis=False,
-                sh_lambda=0.006, min_signal=1):
+def prepare_csa(
+    gtab, sphere, sh_order_max=6, full_basis=False, sh_lambda=0.006, min_signal=1
+):
     """Build bootstrap matrices for the CSA model.
 
     Returns dict with keys: model_type, min_signal, H, R, delta_b,
     delta_q, sampling_matrix, b0s_mask.
     """
     sampling_matrix, _, _ = shm.real_sh_descoteaux(
-        sh_order_max, sphere.theta, sphere.phi,
-        full_basis=full_basis, legacy=True,
+        sh_order_max,
+        sphere.theta,
+        sphere.phi,
+        full_basis=full_basis,
+        legacy=True,
     )
     model = shm.CsaOdfModel(
-        gtab, sh_order_max=sh_order_max, smooth=sh_lambda,
+        gtab,
+        sh_order_max=sh_order_max,
+        smooth=sh_lambda,
         min_signal=min_signal,
     )
     delta_b = model._fit_matrix
@@ -55,9 +72,14 @@ def prepare_csa(gtab, sphere, sh_order_max=6, full_basis=False,
     H, R = _hat_and_lcr(gtab, model, sh_order_max)
 
     return dict(
-        model_type="CSA", min_signal=min_signal,
-        H=H, R=R, delta_b=delta_b, delta_q=delta_q,
-        sampling_matrix=sampling_matrix, b0s_mask=gtab.b0s_mask,
+        model_type="CSA",
+        min_signal=min_signal,
+        H=H,
+        R=R,
+        delta_b=delta_b,
+        delta_q=delta_q,
+        sampling_matrix=sampling_matrix,
+        b0s_mask=gtab.b0s_mask,
     )