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MIT License Copyright (c) 2019 Daniel Jacobson and Stephen Whitelam Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ############################################################################## Calculates correction to the upper bound using blocked trajectory data. Uses the scaled cumulant generating function representation to get this correction as described in: Jacobson, D. & Whitelam, S. Direct evaluation of dynamical large-deviation rate functions using a variational ansatz. Phys. Rev. E 100, 052139 (2019). See --input command line argument. Data formatting is two columns. First column is the intensive observable minus the mean value, a - a_0. The second column is the intensive log likelihood ratio minus the mean, q - q_0. See also: Rohwer, C. M., Angeletti, F. & Touchette, H. Convergence of large-deviation estimators. Phys. Rev. E 92, 052104 (2015).
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