better vector class

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index bc84ea8..23e4d04 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -3,6 +3,7 @@ import Image, ImageDraw, ImageFilter
 from manual import lines as g_grid, l2ad, intersection, line as g_line
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist
+import pcf
 
 class GridFittingFailedError(Exception):
     pass
@@ -15,7 +16,7 @@ class MyGaussianBlur(ImageFilter.Filter):
     def filter(self, image):
         return image.gaussian_blur(self.radius)
 
-class V():
+class V(object):
     def __init__(self, x, y):
         self.x = x
         self.y = y
@@ -29,16 +30,29 @@ class V():
     def __rmul__(self, other):
         return V(other * self.x, other * self.y)
 
-    def t(self):
-        return (self.x, self.y)
+    def __len__(self):
+        return 2;
 
+    def __getitem__(self, key):
+        if key == 0:
+            return self.x
+        elif key == 1:
+            return self.y
+        elif type(key) != int:
+            raise TypeError("V indices must be integers") 
+        else:
+            raise KeyError("V index ({}) out of range".format(key))
+
+    def __iter__(self):
+        yield self.x
+        yield self.y
+
+    @property
     def normal(self):
         return V(-self.y, self.x)
 
 def projection(point, line, vector):
-    n = vector.normal()
-    l2 = g_line(point.t(), (point + n).t())
-    return V(*intersection(l2, g_line(*line)))
+    return V(*intersection(g_line(point, point + vector.normal), g_line(*line)))
     
 def error_surface(lines, a, b, c, d, hough, size, v1):
     import matplotlib.pyplot as plt
@@ -49,12 +63,12 @@ def error_surface(lines, a, b, c, d, hough, size, v1):
     Y = []
     Z = []
     s = 0.001
-    k = 5
+    k = 200
     for i in range(-k, k):
         X.append(range(-k, k))
         Y.append(2*k*[i])
         
-    start = time.clock()
+    start = time.time()
     for x in range(0, 2*k):
         try:
             Z.append([distance(lines, get_grid(a + X[x][y] * s * v1, b + Y[x][y] * s * v1, 
@@ -62,7 +76,7 @@ def error_surface(lines, a, b, c, d, hough, size, v1):
                               size) for y in range(0, 2* k)])
         except Exception:
             Z.append(Z[-1])
-        o = ((time.clock() - start) * (2 * k - (x + 1))) / (60 * (x + 1))
+        o = ((time.time() - start) * (2 * k - (x + 1))) / (60 * (x + 1))
         print x + 1, "{0} h {1:2.2f} m".format(int(o) / 60, o % 60)
     s_file = open('surface' + str(k), 'w')
     pickle.dump((X, Y, Z), s_file)
@@ -131,8 +145,8 @@ def find(lines, size, l1, l2, bounds, hough, do_something):
     return grid, grid_lines
 
 def get_grid(a, b, c, d, hough, size):
-    l1 = hough.lines_from_list([a.t(), b.t()])
-    l2 = hough.lines_from_list([c.t(), d.t()])
+    l1 = hough.lines_from_list([a, b])
+    l2 = hough.lines_from_list([c, d])
     c = intersections_from_angl_dist([l1, l2], size, get_all=True)
     #TODO do something when a corner is outside the image
     corners = (c[0] + c[1])
@@ -154,7 +168,8 @@ def distance(lines, grid, size):
     for line in grid[0] + grid[1]:
         dr_g.line(line, width=1, fill=255)
     #im_g = im_g.filter(MyGaussianBlur(radius=3))
-    im_d, distance = combine(im_l, im_g)
+    #im_d, distance = combine(im_l, im_g)
+    distance = pcf.combine(im_l.tostring(), im_g.tostring())
     return distance
 
 def combine(bg, fg):