Ruggero Turra wiso
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wiso
/ newton optimization.py
Last active
June 6, 2017 18:19
— forked from rajarsheem/newton optimization.py
Newton's optimization method for multivariate function in tensorflow (updated to tf 1.1.0)
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| import numpy as np | |
| import tensorflow as tf | |
| # Newton's optimization method for multivariate function in tensorflow | |
| def cons(x): | |
| return tf.constant(x, dtype=tf.float32) | |
| def compute_hessian(fn, vars): | |
| mat = [] |
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| def loop_iterator(iterator): | |
| object = iterator.Next() | |
| while object: | |
| yield object | |
| object = iterator.Next() | |
| def iter_collection(rooAbsCollection): | |
| iterator = rooAbsCollection.createIterator() | |
| return loop_iterator(iterator) |
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wiso
/ covariance_to_correlation.py
Created
March 20, 2018 08:33
Compute correlation matrix from covariance matrix using numpy
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| import numpy as np | |
| def correlation_from_covariance(covariance): | |
| v = np.sqrt(np.diag(covariance)) | |
| outer_v = np.outer(v, v) | |
| correlation = covariance / outer_v | |
| correlation[covariance == 0] = 0 | |
| return correlation |
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wiso
/ ExampleISTAT.ipynb
Created
August 30, 2018 15:09
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wiso
/ tangent.ipynb
Created
March 7, 2019 14:46
Example using tangent and tensorflow to get covariance matrix from a statistical model (fit to Higgs gamma gamma production modes)
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| import ROOT | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.NumIntegration) | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Fitting) | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Minimization) | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.InputArguments) | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Eval) | |
| ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.DataHandling) | |
| ROOT.RooMsgService.instance().setGlobalKillBelow(ROOT.RooFit.ERROR) | |
| ROOT.RooMsgService.instance().setSilentMode(True) |