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Update DBs for HF jets and cleanup of bitwise selections #837

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merged 3 commits into from
Dec 1, 2023
Merged

Update DBs for HF jets and cleanup of bitwise selections #837

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2dae83a
Update DBs for D0 (jets)
qgp Dec 1, 2023
e8a0bf7
Clean up bitwise.py
qgp Dec 1, 2023
54510f7
Fix pylint issues
qgp Dec 1, 2023
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39 changes: 8 additions & 31 deletions machine_learning_hep/bitwise.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
#############################################################################
## © Copyright CERN 2018. All rights not expressly granted are reserved. ##
## © Copyright CERN 2023. All rights not expressly granted are reserved. ##
## Author: [email protected] ##
## This program is free software: you can redistribute it and/or modify it ##
## under the terms of the GNU General Public License as published by the ##
Expand All @@ -17,37 +17,14 @@
"""
from functools import reduce
import operator
import pandas as pd
#import numba

#@numba.njit
def selectbiton(array_cand_type, mask):
return [((abs(cand_type) & mask) == mask) for cand_type in array_cand_type]

#@numba.njit
def selectbitoff(array_cand_type, mask):
return [((abs(cand_type) & mask) == 0) for cand_type in array_cand_type]
import numpy as np

def tag_bit_df(dfin, namebitmap, activatedbit):
bitson = activatedbit[0]
bitsoff = activatedbit[1]
array_cand_type = dfin.loc[:, namebitmap].values.astype("int")
res_on = pd.Series([True]*len(array_cand_type))
res_off = pd.Series([True]*len(array_cand_type))
res = pd.Series(dtype = 'int')

if bitson:
mask = reduce(operator.or_, ((1 << bit) for bit in bitson), 0)
bitmapon = selectbiton(array_cand_type, mask)
res_on = pd.Series(bitmapon)
if bitsoff:
mask = reduce(operator.or_, ((1 << bit) for bit in bitsoff), 0)
bitmapoff = selectbitoff(array_cand_type, mask)
res_off = pd.Series(bitmapoff)
res = res_on & res_off
return res
mask_on = reduce(operator.or_, ((1 << bit) for bit in activatedbit[0]), 0)
mask_off = reduce(operator.or_, ((1 << bit) for bit in activatedbit[1]), 0)
ar = dfin[namebitmap].values.astype['int']
return np.logical_and(np.bitwise_and(ar, mask_on) == mask_on,
np.bitwise_and(ar, mask_off) == 0)

def filter_bit_df(dfin, namebitmap, activatedbit):
res = tag_bit_df(dfin, namebitmap, activatedbit)
df_sel = dfin[res.values]
return df_sel
return dfin[tag_bit_df(dfin, namebitmap, activatedbit)]
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