Commit 8cb12c47 by Theo Steininger

### Fixed a bug in EnsembleLikelihood

parent 7778ae29
 ... ... @@ -50,16 +50,17 @@ class EnsembleLikelihood(Likelihood): u_val = obs_val - obs_mean # compute quantities for OAS estimator mu = np.vdot(u_val, u_val)*weight/k mu = np.vdot(u_val, u_val)*weight/k/n self.logger.debug("mu: %f" % mu) alpha = (np.einsum(u_val, [0, 1], u_val, [2, 1])**2).sum() alpha /= k*2 # correct the volume factor: one factor comes from the internal scalar # product and one from the trace alpha *= weight**2 numerator = (1 - 2./n)*alpha + mu**2 denominator = (k + 1 - 2./n) * (alpha - (mu**2)/n) numerator = (1 - 2./n)*alpha + (mu*n)**2 denominator = (k + 1 - 2./n) * (alpha - ((mu*n)**2)/n) if denominator == 0: rho = 1 ... ... @@ -79,7 +80,7 @@ class EnsembleLikelihood(Likelihood): "DiagonalOperator.") A_bare_diagonal = data_covariance_operator.diagonal(bare=True) A_bare_diagonal.val += rho*mu/n A_bare_diagonal.val += rho*mu A = DiagonalOperator( domain=data_covariance_operator.domain, diagonal=A_bare_diagonal, ... ... @@ -94,9 +95,6 @@ class EnsembleLikelihood(Likelihood): np.einsum(u_val.conjugate(), [0, 1], a_u_val, [2, 1])*weight) middle = np.linalg.inv(middle) # result_array = np.zeros(k) # for i in xrange(k): # c = measured_data - obs_val[i] c = measured_data - obs_mean # assuming that A == A^dagger, this can be shortend ... ... @@ -117,14 +115,14 @@ class EnsembleLikelihood(Likelihood): second_summand_val = np.einsum(middle, [0, 1], u_a_c_val, [1]) second_summand_val = np.einsum(a_u_val, [0, 1], second_summand_val, [0]) second_summand_val *= -1 # second_summand_val *= -1 second_summand = first_summand.copy_empty() second_summand.val = second_summand_val result_1 = -c.vdot(first_summand) result_1 = c.vdot(first_summand) result_2 = -c.vdot(second_summand) result = result_1 + result_2 self.logger.info("Calculated (%s): %f + %f = %f" % result = -(result_1 + result_2) self.logger.info("Calculated (%s): -(%f + %f) = %f" % (self.observable_name, result_1, result_2, result)) # result_array[i] = result # total_result = result_array.mean() ... ...
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment