Commit 2bbd8133 by Martin Reinecke

### polishing

parent 0c5ab9e9
 ... ... @@ -24,6 +24,7 @@ def get_random_LOS(n_los): starts = list(np.random.uniform(0, 1, (n_los, 2)).T) ends = list(np.random.uniform(0, 1, (n_los, 2)).T) return starts, ends class GaussianEnergy2(ift.Operator): def __init__(self, mean=None, covariance=None): super(GaussianEnergy2, self).__init__() ... ... @@ -89,7 +90,6 @@ class FieldPicker(ift.Operator): if __name__ == '__main__': # FIXME description of the tutorial np.random.seed(42) #print(np.random.random()) position_space = ift.RGSpace([128, 128]) # Setting up an amplitude model ... ... @@ -101,12 +101,8 @@ if __name__ == '__main__': ht = ift.HarmonicTransformOperator(harmonic_space, position_space) power_space = A.target[0] power_distributor = ift.PowerDistributor(harmonic_space, power_space) position = ift.MultiField.from_dict( {'xi': ift.Field.from_random('normal', harmonic_space)}) dummy = ift.Field.from_random('normal', harmonic_space) # xi = ift.Variable(position)['xi'] # Amp = power_distributor(A) # correlated_field_h = Amp * xi correlated_field = lambda inp: ht(power_distributor(A(inp))*inp["xi"]) # alternatively to the block above one can do: # correlated_field,_ = ift.make_correlated_field(position_space, A) ... ... @@ -127,10 +123,7 @@ if __name__ == '__main__': # generate mock data domain = ift.MultiDomain.union((A.domain, ift.MultiDomain.make({'xi': harmonic_space}))) #print(np.random.random()) #print(A.domain) MOCK_POSITION = ift.from_random('normal', domain) #print(np.random.random()) data = signal_response(MOCK_POSITION) + N.draw_sample() # set up model likelihood ... ... @@ -144,9 +137,6 @@ if __name__ == '__main__': # build model Hamiltonian H = MyHamiltonian(likelihood, ic_sampling) #position = ift.from_random('normal', domain) #print (position.domain) #exit() H = EnergyAdapter(MOCK_POSITION, H) INITIAL_POSITION = ift.from_random('normal', H.position.domain) ... ...
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