xs_plot.py

import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
import numpy as np
from math import *

def xs_plot(energy, values, titles=[]):

    n = len(energy) - 1
    
    for i in range(0, len(values)):
        values[i] = values[i][:n] + [values[i][n-1]]
        values[i] = np.array(values[i])  
        
    font = {'family' : 'normal',
            'weight' : 'bold',
            'size'   : 9}
    plt.rc('font', family='serif')
    fig = plt.figure(facecolor="white")
    ax = fig.add_subplot(111)
    ax.grid(which='both', linestyle="-", color="0.95")
    ax.set_axisbelow(True)

    for i in range(0, len(values)):
        if len(titles) > 1:
            ax.step(energy, values[i], lw=2, label=titles[i], color='C'+repr(i), where='pre', linewidth=1)
        else:
            ax.step(energy, values[i], lw=2, color='C'+repr(i), where='pre', linewidth=1)
    if (n>1):
        ax.legend(loc='lower left')
    xlabel = ax.set_xlabel('energy ($eV$)')
    ax.set_ylabel('cross section ($cm^{-1}$)')

    ax.loglog()
    
    min, max = ax.yaxis.get_data_interval()
    min = np.min( values )
    ticks = get_ticks( min, max )
    ax.set_yticks(ticks, minor=True)
    plt.yticks([])

    min, max = ax.xaxis.get_data_interval()
    ticks = get_ticks( min, max )
    ax.set_xticks(ticks, minor=True)
    plt.xticks([])

    fig.set_size_inches(2*4.36,2*2.23)
    plt.savefig('test.png',dpi=300, bbox_extra_artists=[xlabel], bbox_inches='tight')
    plt.show()
    
    
def get_ticks(mini,maxi):
    if mini == 0:
        mini = 1
    mini = 10**floor(log10(mini))
    maxi = 10**ceil(log10(maxi))
    a = [ np.linspace(mini,mini*10,10)[:-1] ]
    while a[-1][0]*10 < maxi:
        a.append(a[-1]*10)
    a = np.array(a)
    return np.append(a, a[-1][0]*10).flatten()