expose flow and hhd for benchmark

src/orisys/HHD.py

@@ -1628,7 +1628,7 @@ class PoissonSolver(object):
         Batched OpenCL Poisson solver for two 2D fields.
         Optimized: scatter H2D (~4x smaller transfer), fused multiply
         (reads g_fft once), async D2H (one sync instead of two).
-        When profile=True, records and optionally prints per-stage timings.
+        When profile=False, records and optionally prints per-stage timings.
         """
         if not OPENCL_AVAILABLE:
             if verbose:
@@ -1818,7 +1818,7 @@ class PoissonSolver(object):
     #     """
     #     OpenCL Poisson solver using pyvkfft FFT convolution.
     #     Replaces scipy.signal.fftconvolve(..., mode='same') for structured grids.
-    #     When profile=True, records and optionally prints per-stage timings.
+    #     When profile=False, records and optionally prints per-stage timings.
     #     """
     #     if not OPENCL_AVAILABLE:
     #         if verbose:

src/orisys/sensor.py

@@ -210,13 +210,13 @@ class Sensor:
         if self.img is None:
             raise Exception("Warning: Get image first")
         
-        self.__compute_flow()
+        self.compute_flow()
         if decompose:
-            self.__compute_hhd()
+            self.compute_hhd()
 
         return True
 
-    def __compute_flow(self):
+    def compute_flow(self):
         if self.img is None:
             raise Exception("Warning: Get image first")
         
@@ -226,7 +226,7 @@ class Sensor:
             flow = flow.download()
         self.flow = flow
     
-    def __compute_hhd(self):
+    def compute_hhd(self):
 
         flow = self.flow
         if flow is None: