def __call__(self, **params_to_override):
p = ParamOverrides(self, params_to_override)
xsize, ysize = SheetCoordinateSystem(p.bounds, p.xdensity,
p.ydensity).shape
xsize, ysize = int(round(xsize)), int(round(ysize))
xdisparity = int(round(xsize * p.xdisparity))
ydisparity = int(round(xsize * p.ydisparity))
dotsize = int(round(xsize * p.dotsize))
bigxsize = 2 * xsize
bigysize = 2 * ysize
ndots = int(
round(p.dotdensity * (bigxsize + 2 * dotsize) *
(bigysize + 2 * dotsize) / min(dotsize, xsize) /
min(dotsize, ysize)))
halfdot = floor(dotsize / 2)
# Choose random colors and locations of square dots
random_seed = p.random_seed
np.random.seed(random_seed * 12 + random_seed * 99)
col = np.where(np.random.random((ndots)) >= 0.5, 1.0, -1.0)
np.random.seed(random_seed * 122 + random_seed * 799)
xpos = np.floor(np.random.random(
(ndots)) * (bigxsize + 2 * dotsize)) - halfdot
np.random.seed(random_seed * 1243 + random_seed * 9349)
ypos = np.floor(np.random.random(
(ndots)) * (bigysize + 2 * dotsize)) - halfdot
# Construct arrays of points specifying the boundaries of each
# dot, cropping them by the big image size (0,0) to (bigxsize,bigysize)
x1 = xpos.astype(numpy.int)
x1 = choose(less(x1, 0), (x1, 0))
y1 = ypos.astype(numpy.int)
y1 = choose(less(y1, 0), (y1, 0))
x2 = (xpos + (dotsize - 1)).astype(numpy.int)
x2 = choose(greater(x2, bigxsize), (x2, bigxsize))
y2 = (ypos + (dotsize - 1)).astype(numpy.int)
y2 = choose(greater(y2, bigysize), (y2, bigysize))
# Draw each dot in the big image, on a blank background
bigimage = zeros((bigysize, bigxsize))
for i in range(ndots):
bigimage[y1[i]:y2[i] + 1, x1[i]:x2[i] + 1] = col[i]
result = p.offset + p.scale * bigimage[
(ysize / 2) + ydisparity:(3 * ysize / 2) + ydisparity,
(xsize / 2) + xdisparity:(3 * xsize / 2) + xdisparity]
for of in p.output_fns:
of(result)
return result
def _set_image(self,image):
# Stores a SheetCoordinateSystem with an activity matrix
# representing the image
if not isinstance(image,numpy.ndarray):
image = array(image,Float)
rows,cols = image.shape
self.scs = SheetCoordinateSystem(xdensity=1.0,ydensity=1.0,
bounds=BoundingBox(points=((-cols/2.0,-rows/2.0),
( cols/2.0, rows/2.0))))
self.scs.activity=image
def __call__(self,**params_to_override):
p = ParamOverrides(self,params_to_override)
shape = SheetCoordinateSystem(p.bounds,p.xdensity,p.ydensity).shape
result = p.scale*ones(shape, Float)+p.offset
self._apply_mask(p,result)
for of in p.output_fns:
of(result)
return result
def __call__(self, **params_to_override):
p = ParamOverrides(self, params_to_override)
shape = SheetCoordinateSystem(p.bounds, p.xdensity, p.ydensity).shape
result = self._distrib(shape, p)
self._apply_mask(p, result)
for of in p.output_fns:
of(result)
return result
def _setup_xy(self,bounds,xdensity,ydensity,x,y,orientation):
"""
Produce pattern coordinate matrices from the bounds and
density (or rows and cols), and transforms them according to
x, y, and orientation.
"""
self.debug(lambda:"bounds=%s, xdensity=%s, ydensity=%s, x=%s, y=%s, orientation=%s"%(bounds,xdensity,ydensity,x,y,orientation))
# Generate vectors representing coordinates at which the pattern
# will be sampled.
# CB: note to myself - use slice_._scs if supplied?
x_points,y_points = SheetCoordinateSystem(bounds,xdensity,ydensity).sheetcoordinates_of_matrixidx()
# Generate matrices of x and y sheet coordinates at which to
# sample pattern, at the correct orientation
self.pattern_x, self.pattern_y = self._create_and_rotate_coordinate_arrays(x_points-x,y_points-y,orientation)
