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import numpy as np
def neutrino_data():
    '''From arxiv:1405.7540 (table I)
    and asumming a Normal Hierarchy:
    Output:
    mnu1in: laightest neutrino mass
    Dms2: \Delta m^2_{12}
    Dma2: \Delta m^2_{13}
    ThetSol,ThetAtm,ThetRec: in radians
    '''

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#!/usr/bin/env bash
# Based on:  https://answers.launchpad.net/mg5amcnlo/+question/271396
# Also works with http://home.thep.lu.se/~torbjorn/pythia8/pythia8219.tgz which allows to install madevent
PYTHIA_VERSION=8219 #8212

echo "========= STEP 1: install MadGraph============"
wget https://launchpad.net/mg5amcnlo/2.0/2.6.x/+download/MG5_aMC_v2.6.2.tar.gz
tar zxf MG5_aMC_v2.6.2.tar.gz

echo "========= STEP 2: install hepmc with MadGraph============"

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#!/usr/bin/env bash                                                                                                                                                                  
SARAH_VERSION=4.13.0
wget http://www.hepforge.org/archive/sarah/SARAH-${SARAH_VERSION}.tar.gz
tar zxf SARAH-${SARAH_VERSION}.tar.gz
ln -s SARAH-${SARAH_VERSION} SARAH

wget http://www.hepforge.org/archive/spheno/SPheno-4.0.3.tar.gz
tar zxf SPheno-4.0.3.tar.gz
ln -s SPheno-4.0.3 SPHENO
sed -ri 's/(^F90\s*=\s*)ifort/\1gfortran/'  SPHENO/Makefile

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def hIndex(citations):
    """
    https://github.com/kamyu104/LeetCode/blob/master/Python/h-index.py
    :type citations: List[int]
    :rtype: int
    
    # Given an array of citations (each citation is a non-negative integer)
    # of a researcher, write a function to compute the researcher's h-index.
    #
    # According to the definition of h-index on Wikipedia: 

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import requests
import pandas as pd

r=requests.get('https://infogram.com/covid-2019-ins-colombia-1hnq41zg9ord63z')

head='"data":[[["ID de caso",'
tail=']]]'
js='{}{}{}'.format( head.split(':')[-1],
                    r.text.split(head)[-1].split(tail)[0],
                    tail

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