Commit 94782c75 by Pumpe, Daniel (dpumpe)

### Merge branch 'master' of gitlab.mpcdf.mpg.de:ift/NIFTy

parents 58ca8d1a 846cc966
 ... ... @@ -117,13 +117,13 @@ if __name__ == "__main__": # Solving the problem analytically m0 = D0.inverse_times(j) sample_variance = Field(sh.domain, val=0. + 0j) sample_mean = Field(sh.domain, val=0. + 0j) sample_variance = Field(sh.domain, val=0.) sample_mean = Field(sh.domain, val=0.) # sampling the uncertainty map n_samples = 1 n_samples = 10 for i in range(n_samples): sample = sugar.generate_posterior_sample(m0, D0) sample = fft(sugar.generate_posterior_sample(0., D0)) sample_variance += sample**2 sample_mean += sample variance = sample_variance/n_samples - (sample_mean/n_samples) variance = (sample_variance - sample_mean**2)/n_samples
 ... ... @@ -24,7 +24,7 @@ from .field import Field __all__ = ['cos', 'sin', 'cosh', 'sinh', 'tan', 'tanh', 'arccos', 'arcsin', 'arccosh', 'arcsinh', 'arctan', 'arctanh', 'sqrt', 'exp', 'log', 'conjugate', 'clipped_exp', 'limited_exp'] 'conjugate', 'clipped_exp', 'limited_exp', 'limited_exp_deriv'] def _math_helper(x, function): ... ... @@ -101,15 +101,28 @@ def clipped_exp(x): def limited_exp(x): thr = 200 expthr = np.exp(thr) return _math_helper(x, lambda z: _limited_exp_helper(z, thr, expthr)) return _math_helper(x, _limited_exp_helper) def _limited_exp_helper(x): thr = 200. mask = x>thr if np.count_nonzero(mask) == 0: return np.exp(x) result = ((1.-thr) + x)*np.exp(thr) result[~mask] = np.exp(x[~mask]) return result def _limited_exp_helper(x, thr, expthr): mask = (x > thr) result = np.exp(x) result[mask] = ((1-thr) + x[mask])*expthr def limited_exp_deriv(x): return _math_helper(x, _limited_exp_deriv_helper) def _limited_exp_deriv_helper(x): thr = 200. mask = x>thr if np.count_nonzero(mask) == 0: return np.exp(x) result = np.empty_like(x) result[mask] = np.exp(thr) result[~mask] = np.exp(x[~mask]) return result ... ...
 ... ... @@ -330,7 +330,7 @@ class Field(Loggable, Versionable, object): Returns ------- out : Field The output object. It's domain is a PowerSpace and it contains The output object. Its domain is a PowerSpace and it contains the power spectrum of 'self's field. See Also ... ...
 ... ... @@ -28,7 +28,7 @@ class LineSearch(with_metaclass(abc.ABCMeta, type('NewBase', (Loggable, object), """Class for determining the optimal step size along some descent direction. Initialize the line search procedure which can be used by a specific line search method. Its finds the step size in a specific direction in the search method. It finds the step size in a specific direction in the minimization process. Attributes ... ...
 ... ... @@ -108,7 +108,7 @@ def generate_posterior_sample(mean, covariance): R = covariance.R N = covariance.N power = S.diagonal().power_analyze()**.5 power = sqrt(S.diagonal().power_analyze()) mock_signal = power.power_synthesize(real_signal=True) noise = N.diagonal(bare=True) ... ...
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