cuckoo search, latin hypercube sampling

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index e957880..03e3014 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -10,7 +10,7 @@ from manual import lines as g_grid
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist
 import pcf
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist
 import pcf

-import pso
+import cs as Optimizer

 
 class GridFittingFailedError(Exception):
     pass
 
 class GridFittingFailedError(Exception):
     pass


@@ -52,7 +52,7 @@ def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
     for line in sum(lines, []):
         dr_l.line(line_from_angl_dist(line, size), width=1, fill=255)
 
     for line in sum(lines, []):
         dr_l.line(line_from_angl_dist(line, size), width=1, fill=255)
 

-    im_l = im_l.filter(MyGaussianBlur(radius=5))
+    im_l = im_l.filter(MyGaussianBlur(radius=3))

     #GaussianBlur is undocumented class, may not work in future versions of PIL
     im_l_s = im_l.tostring()
 
     #GaussianBlur is undocumented class, may not work in future versions of PIL
     im_l_s = im_l.tostring()
 


@@ -62,7 +62,7 @@ def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
     f_dist = partial(job_4, im_l=im_l_s, v1=v1, v2=v2, h1=h1, h2=h2,
                      dv=delta_v, dh=delta_h, size=size)
 
     f_dist = partial(job_4, im_l=im_l_s, v1=v1, v2=v2, h1=h1, h2=h2,
                      dv=delta_v, dh=delta_h, size=size)
 

-    x_v, y_v, x_h, y_h = pso.optimize(4, 30, f_dist, 32, 1028)
+    x_v, y_v, x_h, y_h = Optimizer.optimize(4, 30, f_dist, 128, 256)

 
     v1 = (v1[0] + x_v * delta_v, v1[1] + x_v)
     v2 = (v2[0] + y_v * delta_v, v2[1] + y_v)
 
     v1 = (v1[0] + x_v * delta_v, v1[1] + x_v)
     v2 = (v2[0] + y_v * delta_v, v2[1] + y_v)