Recent Releases of symbolfit
symbolfit - v0.2.0
Updated PySR version and added parsing support for
pysr.TemplateExpressionSpec(see e.g. https://github.com/MilesCranmer/PySR/releases/tag/v1.4.0), so the new result syntax can be interfaced with downstream LMFIT for re-parameterization and re-optimization. Now, user can utilize this class method to impose desired structure on the final expressions, which can potentially help narrowing down the function search space when domain knowledge is present.- For example, one can constrain to search for dijet functions (new physics searches at the CERN LHC) of the form
f(x)^g(log(x)), wherefandgare functions being searched for. One can further constrain to allow only+and*operators, restrictingf(x)to be a polynomial ofxandg(log(x))to be a polynomial oflog(x). ``` from pysr import PySRRegressor, TemplateExpressionSpec
- For example, one can constrain to search for dijet functions (new physics searches at the CERN LHC) of the form
expressionspec = TemplateExpressionSpec( 'p[1] * f(x/13000) ^ g(log(x/13000))', expressions = ['f', 'g'], variablenames = ['x'], parameters = {'p': 1} )
pysrconfig = PySRRegressor( expressionspec = expressionspec, modelselection = 'accuracy', niterations = 200, maxsize = 40, binaryoperators = ['+', '*'], elementwiseloss='loss(y, ypred, weights) = (y - ypred)^2 * weights', ) ```
Full Changelog: https://github.com/hftsoi/symbolfit/compare/v0.1.5...v0.2.0
- Python
Published by hftsoi 11 months ago
symbolfit - v0.1.0
Full Changelog: https://github.com/hftsoi/symbolfit/compare/v0.0.2...v0.1.0
Main update: computation of function ensemble generated by sampling parameters to access uncertainty coverage of the whole fit, resulting in an additional output file per fit: candidates_sampling.pdf.
- Python
Published by hftsoi over 1 year ago