def __init__(self, width, height, rayleigh_scale=1.0):
np.random.seed(np.random.randint(1, 1000000 + 1))
self.width = width
self.height = height
self.rayleigh_scale = rayleigh_scale
self.x, self.y = np.meshgrid(range(self.width), range(self.height))
self.x = self.x.astype(np.float)
self.y = self.y.astype(np.float)
self.signal = np.zeros((height, width))
self.signal_gauss_bubbles = []
self.signal_ellipses = []
self.signal_polygons = []
self.signal_buildings = []
self.signal_faults = []
self.signal_band = []
amp = gauss_filt(
np.random.rayleigh(self.rayleigh_scale, (self.height, self.width)),
10)
self.amp1 = amp.copy()
self.amp2 = amp.copy()
self.slc1 = np.exp(1j * np.zeros((height, width)))
self.slc2 = np.zeros((height, width)).astype(np.complex)
self.noise1 = np.zeros((height, width)).astype(np.complex)
self.noise2 = np.zeros((height, width)).astype(np.complex)
self.ifg = np.zeros((height, width)).astype(np.complex)
self.noisy_ifg = np.zeros((height, width)).astype(np.complex)
self.add_random_dem_signal_flag = False
self.dem_scale = 1.0
def generate_band_mask(width, height, thickness=1):
screen = gauss_filt(np.random.normal(0, 500., (height, width)), 12.)
return (screen < thickness) & (screen > -thickness)