Mean of numpy array: 1.0066466535473984
Standard deviation of numpy array: 0.9973499677811349
Skipping `df.hist(column="x", bins=x.bins())` because matplotlib could not be imported or was not able to display the plot.
[#1] INFO:Fitting -- RooAbsPdf::fitTo(gauss_over_gauss_Int[x]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using CPU computation library compiled with -mavx512
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_gauss_over_gauss_Int[x]_) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
RooFitResult: minimized FCN value: 14152, estimated distance to minimum: 7.15007e-09
covariance matrix quality: Full, accurate covariance matrix
Status : MINIMIZE=0 HESSE=0
Floating Parameter FinalValue +/- Error
-------------------- --------------------------
mean -9.9158e-01 +/- 9.96e-03
sigma 9.9626e-01 +/- 7.04e-03
Counts and bin edges from RooDataHist.to_numpy:
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 2 0 4 5 4 12 21 29 57 91 133
176 263 336 442 497 612 698 753 827 783 777 732 623 522 442 326 260 210
149 82 65 29 20 9 5 3 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0]
[-10. -9.8 -9.6 -9.4 -9.2 -9. -8.8 -8.6 -8.4 -8.2 -8. -7.8
-7.6 -7.4 -7.2 -7. -6.8 -6.6 -6.4 -6.2 -6. -5.8 -5.6 -5.4
-5.2 -5. -4.8 -4.6 -4.4 -4.2 -4. -3.8 -3.6 -3.4 -3.2 -3.
-2.8 -2.6 -2.4 -2.2 -2. -1.8 -1.6 -1.4 -1.2 -1. -0.8 -0.6
-0.4 -0.2 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8
2. 2.2 2.4 2.6 2.8 3. 3.2 3.4 3.6 3.8 4. 4.2
4.4 4.6 4.8 5. 5.2 5.4 5.6 5.8 6. 6.2 6.4 6.6
6.8 7. 7.2 7.4 7.6 7.8 8. 8.2 8.4 8.6 8.8 9.
9.2 9.4 9.6 9.8 10. ]
Counts and bin edges from np.histogram:
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 2 0 4 5 4 12 21 29 57 91 133
176 263 336 442 497 612 698 753 827 783 777 732 623 522 442 326 260 210
149 82 65 29 20 9 5 3 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0]
[-10. -9.8 -9.6 -9.4 -9.2 -9. -8.8 -8.6 -8.4 -8.2 -8. -7.8
-7.6 -7.4 -7.2 -7. -6.8 -6.6 -6.4 -6.2 -6. -5.8 -5.6 -5.4
-5.2 -5. -4.8 -4.6 -4.4 -4.2 -4. -3.8 -3.6 -3.4 -3.2 -3.
-2.8 -2.6 -2.4 -2.2 -2. -1.8 -1.6 -1.4 -1.2 -1. -0.8 -0.6
-0.4 -0.2 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8
2. 2.2 2.4 2.6 2.8 3. 3.2 3.4 3.6 3.8 4. 4.2
4.4 4.6 4.8 5. 5.2 5.4 5.6 5.8 6. 6.2 6.4 6.6
6.8 7. 7.2 7.4 7.6 7.8 8. 8.2 8.4 8.6 8.8 9.
9.2 9.4 9.6 9.8 10. ]
RooDataHist imported with default binning and exported back to numpy:
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 2 0 4 5 4 12 21 29 57 91 133
176 263 336 442 497 612 698 753 827 783 777 732 623 522 442 326 260 210
149 82 65 29 20 9 5 3 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0]
[-10. -9.8 -9.6 -9.4 -9.2 -9. -8.8 -8.6 -8.4 -8.2 -8. -7.8
-7.6 -7.4 -7.2 -7. -6.8 -6.6 -6.4 -6.2 -6. -5.8 -5.6 -5.4
-5.2 -5. -4.8 -4.6 -4.4 -4.2 -4. -3.8 -3.6 -3.4 -3.2 -3.
-2.8 -2.6 -2.4 -2.2 -2. -1.8 -1.6 -1.4 -1.2 -1. -0.8 -0.6
-0.4 -0.2 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8
2. 2.2 2.4 2.6 2.8 3. 3.2 3.4 3.6 3.8 4. 4.2
4.4 4.6 4.8 5. 5.2 5.4 5.6 5.8 6. 6.2 6.4 6.6
6.8 7. 7.2 7.4 7.6 7.8 8. 8.2 8.4 8.6 8.8 9.
9.2 9.4 9.6 9.8 10. ]
RooDataHist imported with linspace binning and exported back to numpy:
[ 0 0 0 0 0 15 210 1350 3387 3437 1387 205 9 0
0 0 0 0 0 0]
[-10. -9. -8. -7. -6. -5. -4. -3. -2. -1. 0. 1. 2. 3.
4. 5. 6. 7. 8. 9. 10.]
RooDataHist imported with uniform binning and exported back to numpy:
[ 0 0 0 0 0 15 210 1350 3387 3437 1387 205 9 0
0 0 0 0 0 0]
[-10. -9. -8. -7. -6. -5. -4. -3. -2. -1. 0. 1. 2. 3.
4. 5. 6. 7. 8. 9. 10.]