def initialize():
# initialize the spline
c = np.array([0, 0])
R = 100.0
nbr_init = 30
phi = np.linspace(0, 2.0 * np.pi, nbr_init)
x_init = c[0] + R * np.cos(phi)
y_init = c[1] + R * np.sin(phi)
x_init[nbr_init - 1] = x_init[0]
y_init[nbr_init - 1] = y_init[0]
tck, _ = splprep([x_init, y_init], s=0, per=1)
spl = BSpline_periodic(tck[0],
np.transpose(tck[1]),
tck[2],
is_periodic=True)
# create an image
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
my_sgeom = circle(100, 0, 0)
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
tmp = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
x, y = tmp.arrf.sampling_vectors()
img = RectBivariateSpline(x, y, np.flipud(tmp.arr))
return spl, img
def create_image(R):
'''
Create a image in which the maximum pixels form a circle having a radius R
Parameters
----------
R : float
Radius of the circle
Returns
-------
img_xy : RectBivariate object
A narray whose values at non-integer coordinates are available thanks
to interpolation
imsh : ImShape object
A object which helps to display the contour and the image
'''
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
my_sgeom = circle(R, 0, 0)
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
img = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
x, y = img.arrf.sampling_vectors()
img_xy = interpolate.RectBivariateSpline(x, y, np.flipud(img.arr))
gcoll = GeomCollection()
gcoll.set_geom(0, my_sgeom)
imsh = ImShape(image=img, geom_coll=gcoll)
return img_xy, imsh
def create_circle_1():
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
R = 25
my_sgeom = circle(R, 0, 0)
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
img = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
img.plot()
plt.show()
def get_pts_from_sgeom_circle(R):
'''
Get a referenced points from Sgeom object in order to compute the distance
between the target and the final curve. In this case, it is from image of
circle
'''
sgeom = circle(R, 0, 0)
xy_arr = sgeom.get_xy()[0]
x_arr = xy_arr[:, 0]
y_arr = xy_arr[:, 1]
tck, _ = spline.build_spline(x_arr, y_arr, per=True, k=3)
knots = tck[0]
ctrl_pts = np.transpose(tck[1])
deg = tck[2]
spl = BSpline_periodic(knots, ctrl_pts, deg, is_periodic=True)
return spl(np.linspace(0, 1, 10000))
def create_2ob():
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
R = 25
my_sgeom_1 = circle(R, -100, 0)
my_sgeom_2 = SGeom(box(0, 0, 100, 50))
my_geom = MultiPolygon([my_sgeom_1.geom, my_sgeom_2.geom])
my_sgeom = SGeom(my_geom, label='circle_square')
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
img = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
gcoll = GeomCollection()
gcoll.set_geom(0, my_sgeom)
imsh = ImShape(image=img, geom_coll=gcoll)
imsh.plot()
plt.show()
def create_noisy_circle(R):
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
my_sgeom = circle(R, 0, 0)
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
img = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
mu, sigma = 0, 10
noise = np.random.normal(mu, sigma, img.arr.shape).astype(float)
noisy_img = img.arr + noise
x, y = img.arrf.sampling_vectors()
img_xy = interpolate.RectBivariateSpline(x, y, np.flipud(noisy_img))
gcoll = GeomCollection()
gcoll.set_geom(0, my_sgeom)
imsh = ImShape(image=img, geom_coll=gcoll)
imsh.plot()
plt.show()
def create_2ob():
'''
Create a image in which the maximum pixels form 2 objects
'''
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
R = 25
my_sgeom_1 = circle(R, -100, 0)
my_sgeom_2 = SGeom(box(0, 0, 100, 50))
my_geom = MultiPolygon([my_sgeom_1.geom, my_sgeom_2.geom])
my_sgeom = SGeom(my_geom, label='circle_square')
strat = lscad.MountainStrategy()
param_dict = {'hmax': 100., 'sigma': (0, 0)}
img = fk_img.img_from_sgeom(img_shape,
frame_bounds,
my_sgeom,
z_map_strategy=strat,
param_dict=param_dict)
x, y = img.arrf.sampling_vectors()
img_xy = interpolate.RectBivariateSpline(x, y, np.flipud(img.arr))
gcoll = GeomCollection()
gcoll.set_geom(0, my_sgeom)
imsh = ImShape(image=img, geom_coll=gcoll)
return img_xy, imsh