NNPDF / nnusf

An open source machine learning framework that provides predictions for all-energy neutrino structure functions.
https://nnpdf.github.io/nnusf/
GNU General Public License v3.0
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Implementation of the commondata filters #2

Closed Radonirinaunimi closed 2 years ago

Radonirinaunimi commented 2 years ago

This PR implements the parsing of the HepData files into a format that we can easily use for the fit. Currently, the tables are saved directly as Pandas objects. The three categories of files (kinematics, data values, and uncertainties) have their own folders. The status (with some kinematic information) is summarized in the table below:

Datasets $[x{\text{min}},~x{\text{max}}]$ $Q^2_{\text{min}}$ Measured Obs. Done Checked Target
BEBCWA59 [0.028, 0.649] 0.160 $F_2, xF_3$ $N_e$
CCFR [0.015, 0.650] 1.260 $F_2, xF_3$ $F_e$
CHARM [0.015, 0.800] 0.180 $F_2, xF_3, \bar{Q} $ $CaCO_3$
NUTEV [0.015, 0.750] 0.190 $F_2, xF_3, d^2 \sigma/(dxdy)$ $F_e$
CHORUS [0.020, 0.650] 0.325 $F_2, xF_3, \sigma_L / \sigma_T, d^2 \sigma/(dxdy)$ $Pb$
CDHS $F_2, d^2 \sigma/(dxdy)$ $D$, $F_e$
CDHSW [0.015, 0.650] 0.190 $F_1, F_2, xF_3, d^2 \sigma/(dxdy)$ $F_e$
giacomomagni commented 2 years ago

Not yet implemented, to be done in later stage: