def init(self):
Image.init(self)
self.n_levels = int(np.log(np.max((self.pe.N_X, self.pe.N_Y)))/np.log(self.pe.base_levels))
self.sf_0 = .5 * (1 - 1/self.n_levels) / np.logspace(0, self.n_levels-1, self.n_levels, base=self.pe.base_levels, endpoint=False)
self.theta = np.linspace(-np.pi/2, np.pi/2, self.pe.n_theta+1)[1:]
self.oc = (self.pe.N_X * self.pe.N_Y * self.pe.n_theta * self.n_levels) #(1 - self.pe.base_levels**-2)**-1)
if self.pe.use_cache is True:
self.cache = {'band':{}, 'orientation':{}}
def init(self):
Image.init(self)
self.n_levels = int(
np.log(np.max(
(self.pe.N_X, self.pe.N_Y))) / np.log(self.pe.base_levels))
self.sf_0 = 1. / np.logspace(
1, self.n_levels, self.n_levels, base=self.pe.base_levels)
self.theta = np.linspace(-np.pi / 2, np.pi / 2,
self.pe.n_theta + 1)[1:]
self.oc = (self.pe.N_X * self.pe.N_Y * self.pe.n_theta * self.n_levels
) #(1 - self.pe.base_levels**-2)**-1)
