PERF: optimize cylindrical pixelizer routine

yt/utilities/lib/pixelization_routines.pyx

@@ -546,6 +546,63 @@ def pixelize_off_axis_cartesian(
     if return_mask:
         return mask!=0
 
+@cython.cdivision(True)
+@cython.boundscheck(False)
+@cython.wraparound(False)
+def pixel_is_completely_contained_within_cylindrical_box(
+    np.float64_t box_rmin,
+    np.float64_t box_rmax,
+    np.float64_t box_thetamin,
+    np.float64_t box_thetamax,
+    np.float64_t img_x0,
+    np.float64_t img_y0,
+    np.float64_t img_dx,
+    np.float64_t img_dy,
+    int pixel_i,
+    int pixel_j,
+) -> bool:
+    cdef np.float64_t xp, yp
+    cdef np.float64_t prbounds[2]
+    cdef np.float64_t ptbounds[2]
+    cdef np.float64_t corners[4]
+
+    # now check that this pixel is entirely confined within
+    # the data domain
+    xp = img_x0 + pixel_i*img_dx
+    yp = img_y0 + pixel_j*img_dy
+    corners[0] = xp*xp + yp*yp
+    corners[1] = xp*xp + (yp+img_dy)**2
+    corners[2] = (xp+img_dx)**2 + yp*yp
+    corners[3] = (xp+img_dx)**2 + (yp+img_dy)**2
+    prbounds[0] = prbounds[1] = corners[3]
+    for i1 in range(3):
+        prbounds[0] = fmin(prbounds[0], corners[i1])
+        prbounds[1] = fmax(prbounds[1], corners[i1])
+    prbounds[0] = math.sqrt(prbounds[0])
+    if prbounds[0] < box_rmin:
+        return False
+
+    prbounds[1] = math.sqrt(prbounds[1])
+    if prbounds[1] > box_rmax:
+        return False
+
+    corners[0] = math.atan2(xp, yp)
+    corners[1] = math.atan2(xp, yp+img_dy)
+    corners[2] = math.atan2(xp+img_dx, yp)
+    corners[3] = math.atan2(xp+img_dx, yp+img_dy)
+    ptbounds[0] = ptbounds[1] = corners[3]
+    for i1 in range(3):
+        ptbounds[0] = fmin(ptbounds[0], corners[i1])
+        ptbounds[1] = fmax(ptbounds[1], corners[i1])
+
+    # shift to a [0, PI] interval
+    ptbounds[0] = ptbounds[0] % (2*np.pi)
+    if ptbounds[0] < box_thetamin:
+        return False
+
+    ptbounds[1] = ptbounds[1] % (2*np.pi)
+    return ptbounds[1] <= box_thetamax
+
 @cython.cdivision(True)
 @cython.boundscheck(False)
 @cython.wraparound(False)
@@ -561,11 +618,11 @@ def pixelize_cylinder(np.float64_t[:,:] buff,
 ):
 
     cdef np.float64_t x, y, dx, dy, r0, theta0
-    cdef np.float64_t rmin, rmax, tmin, tmax, x0, y0, x1, y1, xp, yp
+    cdef np.float64_t rmin, rmax, tmin, tmax, x0, y0, x1, y1
     cdef np.float64_t r_i, theta_i, dr_i, dtheta_i
     cdef np.float64_t r_inc, theta_inc
     cdef np.float64_t costheta, sintheta
-    cdef int i, i1, pi, pj
+    cdef int i, pi, pj
 
     cdef int imin, imax
     imin = np.asarray(radius).argmin()
@@ -585,8 +642,6 @@ def pixelize_cylinder(np.float64_t[:,:] buff,
     dx = (x1 - x0) / buff.shape[0]
     dy = (y1 - y0) / buff.shape[1]
     cdef np.float64_t rbounds[2]
-    cdef np.float64_t prbounds[2]
-    cdef np.float64_t ptbounds[2]
     cdef np.float64_t corners[8]
     # Find our min and max r
     corners[0] = x0*x0+y0*y0
@@ -637,40 +692,78 @@ def pixelize_cylinder(np.float64_t[:,:] buff,
                 if pi >= 0 and pi < buff.shape[0] and \
                    pj >= 0 and pj < buff.shape[1]:
                     # we got a pixel that intersects the grid cell
-                    # now check that this pixel doesn't go beyond the data domain
-                    xp = x0 + pi*dx
-                    yp = y0 + pj*dy
-                    corners[0] = xp*xp + yp*yp
-                    corners[1] = xp*xp + (yp+dy)**2
-                    corners[2] = (xp+dx)**2 + yp*yp
-                    corners[3] = (xp+dx)**2 + (yp+dy)**2
-                    prbounds[0] = prbounds[1] = corners[3]
-                    for i1 in range(3):
-                        prbounds[0] = fmin(prbounds[0], corners[i1])
-                        prbounds[1] = fmax(prbounds[1], corners[i1])
-                    prbounds[0] = math.sqrt(prbounds[0])
-                    prbounds[1] = math.sqrt(prbounds[1])
-
-                    corners[0] = math.atan2(xp, yp)
-                    corners[1] = math.atan2(xp, yp+dy)
-                    corners[2] = math.atan2(xp+dx, yp)
-                    corners[3] = math.atan2(xp+dx, yp+dy)
-                    ptbounds[0] = ptbounds[1] = corners[3]
-                    for i1 in range(3):
-                        ptbounds[0] = fmin(ptbounds[0], corners[i1])
-                        ptbounds[1] = fmax(ptbounds[1], corners[i1])
-
-                    # shift to a [0, PI] interval
-                    ptbounds[0] = ptbounds[0] % (2*np.pi)
-                    ptbounds[1] = ptbounds[1] % (2*np.pi)
-
-                    if prbounds[0] >= rmin and prbounds[1] <= rmax and \
-                       ptbounds[0] >= tmin and ptbounds[1] <= tmax:
-                        buff[pi, pj] = field[i]
-                        mask[pi, pj] = 1
+                    buff[pi, pj] = field[i]
+                    mask[pi, pj] = 1
+
                 r_i += r_inc
             theta_i += theta_inc
 
+    # now let's refine bounding box detection accuracy
+    # and clear pixels that intesect only partially with the bounding box
+    # We'll perform 4 loops, one for each axis/direction pair
+    cdef np.float64_t fillvalue = np.nan  # TODO: make sure this value makes sense
+    for pi in range(mask.shape[0]):
+        pj = 0
+        while pj < (mask.shape[1] - 1) and mask[pi, pj] == 0:
+            pj += 1
+        if mask[pi, pj] == 1 and not (
+            pixel_is_completely_contained_within_cylindrical_box(
+                box_rmin=rmin, box_rmax=rmax,
+                box_thetamin=tmin, box_thetamax=tmax,
+                img_x0=x0, img_y0=y0,
+                img_dx=dx, img_dy=dy,
+                pixel_i=pi, pixel_j=pj,
+            )
+        ):
+            buff[pi, pj] = fillvalue
+            mask[pi, pj] = 0
+
+        pj = mask.shape[1] - 1
+        while pj > 0 and mask[pi, pj] == 0:
+            pj -= 1
+        if mask[pi, pj] == 1 and not (
+            pixel_is_completely_contained_within_cylindrical_box(
+                box_rmin=rmin, box_rmax=rmax,
+                box_thetamin=tmin, box_thetamax=tmax,
+                img_x0=x0, img_y0=y0,
+                img_dx=dx, img_dy=dy,
+                pixel_i=pi, pixel_j=pj,
+            )
+        ):
+            buff[pi, pj] = fillvalue
+            mask[pi, pj] = 0
+
+    for pj in range(mask.shape[1]):
+        pi = 0
+        while pi < (mask.shape[0] - 1) and mask[pi, pj] == 0:
+            pi += 1
+        if mask[pi, pj] == 1 and not (
+            pixel_is_completely_contained_within_cylindrical_box(
+                box_rmin=rmin, box_rmax=rmax,
+                box_thetamin=tmin, box_thetamax=tmax,
+                img_x0=x0, img_y0=y0,
+                img_dx=dx, img_dy=dy,
+                pixel_i=pi, pixel_j=pj,
+            )
+        ):
+            buff[pi, pj] = fillvalue
+            mask[pi, pj] = 0
+
+        pi = mask.shape[0] - 1
+        while pi > 0 and mask[pi, pj] == 0:
+            pi -= 1
+        if mask[pi, pj] == 1 and not (
+            pixel_is_completely_contained_within_cylindrical_box(
+                box_rmin=rmin, box_rmax=rmax,
+                box_thetamin=tmin, box_thetamax=tmax,
+                img_x0=x0, img_y0=y0,
+                img_dx=dx, img_dy=dy,
+                pixel_i=pi, pixel_j=pj,
+            )
+        ):
+            buff[pi, pj] = fillvalue
+            mask[pi, pj] = 0
+
     if return_mask:
         return mask_arr.astype("bool")