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_vague_local(R, threshold=50, per=np.pi / 3):
'''
Create a image in which the maximum pixels form a circular wave having a
radius R
Parameters
----------
R : float
Radius of the circle
threshold: float, optional
Every pixel of which the value is less than this threshold is set to 0
per: float, optional
Periodicity of the wave
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]
r_nb = 200
rough_dict = {'lwr': 10}
my_sgeom = rand_circle(R, 0, 0, r_nb, rough_dict, per)
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.arr[img.arr < threshold] = 0
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_fluctuation():
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
R = 25
r_nb = 150
rough_dict = {'lwr': 10}
r_per = np.pi / 3
my_sgeom = rand_circle(R, 0, 0, r_nb, rough_dict, r_per)
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_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_rect():
'''
Create a image in which the maximum pixels form a rectangular
'''
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
my_sgeom = SGeom(box(-100, -50, 100, 50))
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 plot_coll():
img_shape = (512, 512)
frame_bounds = [-256, 256, -256, 256]
R = 25
c = np.array([0, 0])
phi = np.linspace(0, 2 * np.pi, 1000)
x = c[0] + R * np.cos(phi)
y = c[1] + R * np.sin(phi)
dat = np.array([x, y]).T
my_sgeom = SGeom(Polygon(dat))
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_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