from __future__ import print_function import numpy as np import sys import os import datetime import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages from matplotlib.ticker import MultipleLocator from matplotlib.ticker import ScalarFormatter from matplotlib.ticker import NullFormatter import matplotlib.image as image import matplotlib.patches as patches import matplotlib.lines as lines import matplotlib.ticker as ticker from scipy.optimize import curve_fit def read_values (filename): xs = [] f = open(filename,'r') lines = f.readlines() f.close() for line in lines: p=line.split() xs.append(float(p[0])) xs = np.asarray(xs) return xs def make_figure (times_passive,times_Pe2ini,times_Pe2,times_Pe20ini,times_Pe20,times_Pe100ini,times_Pe100): # exponential distributions avg2 = np.mean(times_Pe2) avg20 = np.mean(times_Pe20) avg100 = np.mean(times_Pe100) xs = np.arange(0,6,0.1) ys2 = np.exp(-xs/avg2) / avg2 ys20 = np.exp(-xs/avg20) / avg20 ys100 = np.exp(-xs/avg100) / avg100 # setto alcune variabili comuni axisticslabelfontsize=9 axisticslabelfontsizeinset=7 axislabelfontsize=11 axislabelfontsizeinset=9 xfig,yfig=7.0,2.3 factor = xfig/yfig x1,y1 = 0.12,0.16 dx1,dy1=0.2,0.70 xgap = 0.06 x2,y2 = x1+dx1+xgap,y1 dx2,dy2 = dx1,dy1 x3,y3 = x2+dx2+xgap,y1 dx3,dy3 = dx1,dy1 xlim_left,xlim_right = 0,5.7 xtic_main,xtic_min = 2.5,0.5 ylim_low,ylim_up = 0,1.3 ytic_main,ytic_min = 0.5,0.1 bins = np.arange(0,11.5,0.2) with PdfPages('fig3.pdf') as pdf: fig = plt.figure(figsize=(xfig,yfig)) plt.rc('text', usetex=True) plt.rc('text.latex', preamble = ','.join('''\usepackage{txfonts} \usepackage{lmodern}'''.split())) ######################## panel A ######################################## panel = fig.add_axes([x1, y1, dx1, dy1]) panel.tick_params(axis='both',which='both',direction='in',bottom=True,top=True,left=True,right=True) for tick in panel.xaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) for tick in panel.yaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) panel.set_xlabel(r'$t_{\rm{target}} / \tau$',fontsize=axislabelfontsize) panel.set_ylabel(r'$P(t_{\rm{target}})$',fontsize=axislabelfontsize) panel.set_xlim(xlim_left,xlim_right) panel.set_ylim(ylim_low,ylim_up) panel.xaxis.set_major_locator(MultipleLocator(xtic_main)) panel.xaxis.set_minor_locator(MultipleLocator(xtic_min)) panel.yaxis.set_major_locator(MultipleLocator(ytic_main)) panel.yaxis.set_minor_locator(MultipleLocator(ytic_min)) panel.text(0.83,0.88,r'(a)',fontsize=axislabelfontsize,transform=panel.transAxes) t = panel.text(0.28,0.85,r'Pe = $2$',fontsize=axislabelfontsize+1,transform=panel.transAxes) t.set_bbox(dict(facecolor='white', alpha=0.8, edgecolor='none',pad=1.5)) #~ # plot avg line panel.plot(xs,ys2,'m-',linewidth=1.0) panel.hist(times_Pe2,bins=bins,density=True,color='b',alpha=0.5) panel.hist(times_passive,bins=bins,density=True,color='b',histtype='step',label=r'passive particle') panel.hist(times_Pe2ini,bins=bins,density=True,color='k',histtype='step',label=r'initial policy') ######################## panel B ######################################## panel = fig.add_axes([x2, y2, dx2, dy2]) panel.tick_params(axis='both',which='both',direction='in',bottom=True,top=True,left=True,right=True) for tick in panel.xaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) for tick in panel.yaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) panel.set_xlabel(r'$t_{\rm{target}} / \tau$',fontsize=axislabelfontsize) panel.set_xlim(xlim_left,xlim_right) panel.set_xlim(xlim_left,xlim_right) panel.set_ylim(ylim_low,ylim_up) panel.xaxis.set_major_locator(MultipleLocator(xtic_main)) panel.xaxis.set_minor_locator(MultipleLocator(xtic_min)) panel.yaxis.set_major_locator(MultipleLocator(ytic_main)) panel.yaxis.set_minor_locator(MultipleLocator(ytic_min)) panel.text(0.83,0.88,r'(b)',fontsize=axislabelfontsize,transform=panel.transAxes) t = panel.text(0.27,0.85,r'Pe = $20$',fontsize=axislabelfontsize+1,transform=panel.transAxes) t.set_bbox(dict(facecolor='white', alpha=0.8, edgecolor='none',pad=1.5)) #~ # plot avg line panel.hist(times_Pe20,bins=bins,density=True,color='r',alpha=0.8) panel.plot(xs,ys20,'m-',linewidth=1.0, label=r'$e^{(-t_{\rm target}/ \langle t_{\rm target} \rangle)} / \langle t_{\rm target} \rangle$') panel.hist(times_Pe20ini,bins=bins,density=True,color='k',histtype='step',label=r'initial policy') panel.hist(times_passive,bins=bins,density=True,color='b',histtype='step',label=r'passive particle') #~ panel.legend(loc='center', bbox_to_anchor=(0.5, 1.1),ncol=3,fontsize=8,handlelength=1.5,labelspacing=0.2) #specify order of items in legend handles, labels = panel.get_legend_handles_labels() order = [1,2,0] panel.legend([handles[idx] for idx in order],[labels[idx] for idx in order],loc='center', bbox_to_anchor=(0.5, 1.1),ncol=3,fontsize=8,handlelength=1.5,labelspacing=0.2) ######################## panel C ######################################## panel = fig.add_axes([x3, y3, dx3, dy3]) panel.tick_params(axis='both',which='both',direction='in',bottom=True,top=True,left=True,right=True) for tick in panel.xaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) for tick in panel.yaxis.get_major_ticks(): tick.label.set_fontsize(axisticslabelfontsize) panel.set_xlabel(r'$t_{\rm{target}} / \tau$',fontsize=axislabelfontsize) panel.set_xlim(xlim_left,xlim_right) panel.set_ylim(ylim_low,2.8) panel.xaxis.set_major_locator(MultipleLocator(xtic_main)) panel.xaxis.set_minor_locator(MultipleLocator(xtic_min)) panel.yaxis.set_major_locator(MultipleLocator(ytic_main)) panel.yaxis.set_minor_locator(MultipleLocator(ytic_min)) panel.text(0.83,0.88,r'(c)',fontsize=axislabelfontsize,transform=panel.transAxes) t = panel.text(0.25,0.85,r'Pe = $100$',fontsize=axislabelfontsize+1,transform=panel.transAxes) t.set_bbox(dict(facecolor='white', alpha=0.8, edgecolor='none',pad=1.5)) #~ # plot avg line panel.plot(xs,ys100,'m-',linewidth=1.0) panel.hist(times_Pe100,bins=bins,density=True,color='g',alpha=0.8) panel.hist(times_passive,bins=bins,density=True,color='b',histtype='step',label=r'passive particle') panel.hist(times_Pe100ini,bins=bins,density=True,color='k',histtype='step',label=r'initial policy') pdf.savefig(fig) return def main(): foldername = '../RESULTS/Target_Times_Distributions/TargetTimes_' # passive particle filename= foldername+'Passive.dat' times_passive = read_values (filename) # Pe=2 ini filename= foldername+'Pe2_ini.dat' times_Pe2ini = read_values (filename) # Pe=2 filename= foldername+'Pe2.dat' times_Pe2 = read_values (filename) # Pe=20 ini filename= foldername+'Pe20_ini.dat' times_Pe20ini = read_values (filename) # Pe=20 filename= foldername+'Pe20.dat' times_Pe20 = read_values (filename) # Pe=100 ini filename= foldername+'Pe100_ini.dat' times_Pe100ini = read_values (filename) # Pe=100 filename= foldername+'Pe100.dat' times_Pe100 = read_values (filename) # plots make_figure(times_passive,times_Pe2ini,times_Pe2,times_Pe20ini,times_Pe20,times_Pe100ini,times_Pe100) main()