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readvmeoffline

we read asc data files from CAEN - created by gregory (or mc2). Create histograms, count zeroes etc...

Usage - brief version 2022

We try to update - with experiment 2021 12 03

./bin_readvme cut ~/09_DATA_ANALYSIS/20211203_54fe_nfs_ganil/Evaluation_1_fe40/run0055_211203_203227_1Fe40p3.asc 0 5 15

cuts channel 0 from 5sec to 15 sec

evacuttime

  • simple_read.eva_cut_time
    • calls general.readtable
    • calls general.select_channels
    • calls general.enhance_by_dtus...
    • call general.detect_zeroes for timewindow 4.2us

offers

Usage -brief version (OLD)

# convert asc to h5
read_vme_offline a2df run0022_20190719_070923.asc

# create spectra and table and ORG (text) file
read_vme_offline df2s run0014_20190718_165928.h5 --Emax 15200 -Ethres 5

# MASS CONVERT:
ls -1 *asc | xargs -n 1 -I III  read_vme_offline a2df III
ls -1 *h5 | xargs -n 1 -I III  read_vme_offline df2s  III  --Emax 15200 -Ethres 5

Installation

  • you can use ./pipall.py to get all python modules needed
  • since this is an exprerimental project, the recommended way to install is
    • pip3 install -e .
    • then you work on the code in local repo and run it globally in the same time
    • remove with pip3 uninstall project

Installation of ROOT

  • we start the manual with 6.22: https://root.cern/releases/release-62206/
  • the file root_v6.22.06.Linux-ubuntu20-x86_64-gcc9.3.tar.gz
  • create/unpack in in ~/root
  • run source ~/root/bin/thisroot/sh
  • go to ~/root/tutorials/pyroot and run python3 demo.py
  • something works, but there is a lot of problems

Connecting together

  • in the terminal, where source thisroot.sh was run try to call read_vme_offline
  • install

dependent module's details

rootnumpy

See http://scikit-hep.org/root_numpy/

  • create and FILL HISTOGRAMS from numpy array
  • an efficient interface between ROOT and NumPy
  • At the core of rootnumpy are powerful and flexible functions for converting ROOT TTrees into structured NumPy arrays
  • converting NumPy arrays back into ROOT TTrees
  • function for creating a random NumPy array by sampling a ROOT function or histogram:
from root_numpy import fill_hist
import numpy as np

# Fill a ROOT histogram from a NumPy array
hist = TH2D('name', 'title', 20, -3, 3, 20, -3, 3)
fill_hist(hist, np.random.randn(1000000, 2))
hist.Draw('LEGO2')

pylatex

library for creating and compiling LaTeX files or snippets

History

  • jm entered 2020 05 26
  • jm access 2021 02 19

Metadata

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