我正在尝试使用一个基本针对波斯语设置的模板来构建我的博士论文。当所有内容都是波斯语时，这个模板非常棒。但有一个问题。我需要将我的Python代码添加到附录中。我在这里找到了一个链接tex.stackexchange.com这使得它与环境完全一样Jupyter并且很漂亮。
但是，当我将这种样式添加到我的文件时，输出 LaTeX 文件的某些部分会被破坏。
主要的 LaTeX 代码是：
\documentclass[oneside,phd,12pt]{AUTthesis}
\usepackage{graphicx,adjustbox}
\graphicspath{{figures/}} %Setting the graphicspath
\usepackage{amsthm,amssymb,amsmath}
\usepackage[center]{caption}
\usepackage{afterpage}
\usepackage{lscape}
\usepackage{xcolor}
\usepackage{color,soul}
\usepackage{multirow}
\usepackage{float}
\usepackage{pgfplots}
\usepackage{tikz}
\usetikzlibrary{plotmarks}
\usetikzlibrary{arrows.meta,patterns}
\pgfplotsset{compat=1.10}
\usepgfplotslibrary{fillbetween}
\usepgfplotslibrary{units}
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\definecolor{storeClusterComponent}{HTML}{FDAE61}
\definecolor{dbscan}{HTML}{ABDDA4}
\definecolor{constructCluster}{HTML}{2B83BA}
\usepackage{array}
\usepackage[skip=0pt]{caption}
\newcolumntype{P}[1]{>{\centering\arraybackslash}p{#1}}
\newcommand{\hlgreen}[1]{{\sethlcolor{green}\hl{#1}}}
%%%%%For colorful Jupyter style of Python code
\usepackage[utf8]{inputenc}
\usepackage[english]{babel}
\usepackage[T1]{fontenc}
\usepackage{xcolor}
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\usepackage{listings}
\lstset{
breaklines=true,
%
extendedchars=true,
literate=
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%%
%% Python definition (c) 1998 Michael Weber
%% Additional definitions (2013) Alexis Dimitriadis
%% modified by me (should not have empty lines)
%%
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{á}{{\'a}}1 {é}{{\'e}}1 {í}{{\'i}}1 {ó}{{\'o}}1 {ú}{{\'u}}1
{Á}{{\'A}}1 {É}{{\'E}}1 {Í}{{\'I}}1 {Ó}{{\'O}}1 {Ú}{{\'U}}1
{à}{{\`a}}1 {è}{{\`e}}1 {ì}{{\`i}}1 {ò}{{\`o}}1 {ù}{{\`u}}1
{À}{{\`A}}1 {È}{{\'E}}1 {Ì}{{\`I}}1 {Ò}{{\`O}}1 {Ù}{{\`U}}1
{ä}{{\"a}}1 {ë}{{\"e}}1 {ï}{{\"i}}1 {ö}{{\"o}}1 {ü}{{\"u}}1
{Ä}{{\"A}}1 {Ë}{{\"E}}1 {Ï}{{\"I}}1 {Ö}{{\"O}}1 {Ü}{{\"U}}1
{â}{{\^a}}1 {ê}{{\^e}}1 {î}{{\^i}}1 {ô}{{\^o}}1 {û}{{\^u}}1
{Â}{{\^A}}1 {Ê}{{\^E}}1 {Î}{{\^I}}1 {Ô}{{\^O}}1 {Û}{{\^U}}1
{œ}{{\oe}}1 {Œ}{{\OE}}1 {æ}{{\ae}}1 {Æ}{{\AE}}1 {ß}{{\ss}}1
{ç}{{\c c}}1 {Ç}{{\c C}}1 {ø}{{\o}}1 {å}{{\r a}}1 {Å}{{\r A}}1
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\input{commands}
\begin{document}
\baselineskip=.75cm
\linespread{1.75}
\input{fa_title}
\pagenumbering{alph}
%-----------------------------------------------------------------------------
\input{TOC-TOF-LOT}
\pagenumbering{arabic}
\pagestyle{style1}
%--------------------------------------------------------------------------appendix
\chapterfont{\vspace*{-2em}\centering\LARGE}%
\appendix
\renewcommand{\chaptermark}[1]{\markboth{#1}{}}
\include{appendix1}
\end{document}
附录为：
\chapter{کد شبیهسازی به زبان $Python$ در بستر $Jupyter$\ref{sec5}}\label{PythonCode}
\begin{lstlisting}[language=iPython]
"""
Initial definitions
"""
KSstrategies=['S','N']
CAstrategies=['R','O','D']
ALLstrategies=['SR','SO','SD','NR','NO','ND']
ALLstrategiesCodes={'SR':0,'SO':1,'SD':2,'NR':3,'NO':4,'ND':5}
Theta = 0.2
s = 0.3333
Lambda = 0.4
Etha = 1.15
l = {'Ent':0.08,'Inc':0.08} #[Ent,Inc]
k = {'Ent':Etha*l['Ent'],'Inc':Etha*l['Inc']} #[Ent,Inc]
n={'Ent':0.27,'Inc':0.12} #[Ent,Inc]
r={'Ent':0.2,'Inc':0.15} #[Ent,Inc]
v={'Ent':0.36,'Inc':0.225} #[Ent,Inc]
rho = {'Ent':1.2,'Inc':0.8} #[Ent,Inc]
omega = {'Ent':0.9,'Inc':1.1} #[Ent,Inc]
delta = {'Ent':1.4,'Inc':0.6} #[Ent,Inc]
phi = {'Ent':0.07,'Inc':0.085} #[Ent,Inc]
tau = {'Ent':0.06,'Inc':0.066} #[Ent,Inc]
c={}
c['Inc']={'R':0.09,'O':0.10,'D':0.20} #c[R,O,D]
c['Ent']={'R':0.11,'O':0.12,'D':0.14} #c[R,O,D]
costToQualityRatio = 2
ksnoise = 0.15
"""
Define functions
"""
import numpy as np
def optimumprofitIncLead(qEnt,qInc,Leader):
if Leader == 'Incumbent':
#The Incumbent is the leader in pricing
if qEnt>qInc:
priceInc = ((qEnt - qInc)*qInc)/(2*(2*qEnt - qInc))
profitInc = ((qEnt - qInc)*qInc)/(16*qEnt - 8*qInc)
priceEnt = ((qEnt - qInc)*(4*qEnt - qInc))/(4*(2*qEnt - qInc))
profitEnt = ((qEnt - qInc)*(-4*qEnt + qInc)**2)/(16*(-2*qEnt + qInc)**2)
elif qEnt==qInc:
priceInc = 'Whatever'
profitInc = 0
priceEnt = qEnt/2
profitEnt = qEnt/4
elif qEnt<qInc:
priceInc = ((qInc-qEnt)*qInc)/(2*qInc-qEnt)
profitInc = ((qEnt - qInc)*qInc)/(2*(qEnt - 2*qInc))
priceEnt = ((qInc-qEnt)*qEnt)/(2*(2*qInc-qEnt))
profitEnt = (qEnt*qInc*(-qEnt + qInc))/(4*(qEnt - 2*qInc)**2)
elif Leader == 'Entrant':
#The New Entrant is the leader in pricing
if qEnt>qInc:
priceInc = ((qInc-qEnt)*qInc)/(2*(qInc-2*qEnt))
profitInc = (qEnt*qInc*(qEnt-qInc))/(4*((2*qEnt-qInc)**2))
priceEnt = ((qInc-qEnt)*qEnt)/(qInc-2*qEnt)
profitEnt = ((qEnt - qInc)*qEnt)/(4*qEnt - 2*qInc)
elif qEnt==qInc:
priceInc = qInc/2
profitInc = qInc/4
priceEnt = 'Whatever'
profitEnt = 0
elif qEnt<qInc:
priceInc = ((qInc - qEnt)*(4*qInc - qEnt))/(4*(2*qInc - qEnt))
profitInc = ((qInc - qEnt)*(-4*qInc + qEnt)**2)/(16*(-2*qInc + qEnt)**2)
priceEnt = ((qInc - qEnt)*qEnt)/(2*(2*qInc - qEnt))
profitEnt = ((qInc - qEnt)*qEnt)/(16*qInc - 8*qEnt)
return priceEnt,profitEnt,priceInc,profitInc
def KSpayoff(strategyEnt,strategyInc):
global payoffEnt, payoffInc
if strategyEnt=='S' and strategyInc=='S':
payoffEnt=(1+Theta)*(r['Ent']+r['Inc']+Lambda*s+l['Ent'])-n['Ent']
payoffInc=(1+Theta)*(r['Ent']+r['Inc']+(1-Lambda)*s+l['Inc'])-n['Inc']
elif strategyEnt=='S' and strategyInc=='N':
payoffEnt=(1+Theta)*(r['Ent']-n['Ent'])
payoffInc=(1-Theta)*(r['Ent']+r['Inc']+v['Inc']+l['Inc'])
elif strategyEnt=='N' and strategyInc=='S':
payoffEnt=(1-Theta)*(r['Ent']+r['Inc']+v['Ent']+l['Ent'])
payoffInc=(1+Theta)*(r['Inc']-n['Inc'])
elif strategyEnt=='N' and strategyInc=='N':
payoffEnt=(1-Theta)*(r['Ent']+v['Ent'])
payoffInc=(1-Theta)*(r['Inc']+v['Inc'])
return payoffEnt,payoffInc
def CApayoff(CAstrategyEnt,CAstrategyInc,KSstrategyEnt,KSstrategyInc,qEnt,qInc,Leader):
global payoffEnt, payoffInc
receivedknowledge = {}
if KSstrategyEnt == 'N':
receivedknowledge['Inc'] = 0
else:
receivedknowledge['Inc'] = 1
if KSstrategyInc == 'N':
receivedknowledge['Ent'] = 0
else:
receivedknowledge['Ent'] = 1
if CAstrategyEnt=='R' and CAstrategyInc=='R':
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = rho['Ent']*profitEnt-c['Ent']['R']
payoffInc = rho['Inc']*profitInc-c['Inc']['R']
elif CAstrategyEnt=='R' and CAstrategyInc=='O':
qInc += receivedknowledge['Inc']*k['Inc']+c['Inc']['O']/costToQualityRatio-phi['Inc']
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = rho['Ent']*profitEnt-c['Ent']['R']
payoffInc = omega['Inc']*profitInc-c['Inc']['O']
elif CAstrategyEnt=='R' and CAstrategyInc=='D':
qInc += np.tanh(receivedknowledge['Inc']*k['Inc']+c['Inc']['D']/costToQualityRatio-tau['Inc'])
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = rho['Ent']*profitEnt-c['Ent']['R']
payoffInc = delta['Inc']*profitInc-c['Inc']['D']
elif CAstrategyEnt=='O' and CAstrategyInc=='R':
qEnt += receivedknowledge['Ent']*k['Ent']+c['Ent']['O']/costToQualityRatio-phi['Ent']
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = omega['Ent']*profitEnt-c['Ent']['O']
payoffInc = rho['Inc']*profitInc-c['Inc']['R']
elif CAstrategyEnt=='O' and CAstrategyInc=='O':
qEnt += receivedknowledge['Ent']*k['Ent']+c['Ent']['O']/costToQualityRatio-phi['Ent']
qInc += receivedknowledge['Inc']*k['Inc']+c['Inc']['O']/costToQualityRatio-phi['Inc']
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = omega['Ent']*profitEnt-c['Ent']['O']
payoffInc = omega['Inc']*profitInc-c['Inc']['O']
elif CAstrategyEnt=='O' and CAstrategyInc=='D':
qEnt += receivedknowledge['Ent']*k['Ent']+c['Ent']['O']/costToQualityRatio-phi['Ent']
qInc += np.tanh(receivedknowledge['Inc']*k['Inc']+c['Inc']['D']/costToQualityRatio-tau['Inc'])
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = omega['Ent']*profitEnt-c['Ent']['O']
payoffInc = delta['Inc']*profitInc-c['Inc']['D']
elif CAstrategyEnt=='D' and CAstrategyInc=='R':
qEnt += np.tanh(receivedknowledge['Ent']*k['Ent']+c['Ent']['D']/costToQualityRatio-tau['Ent'])
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = delta['Ent']*profitEnt-c['Ent']['D']
payoffInc = rho['Inc']*profitInc-c['Inc']['R']
elif CAstrategyEnt=='D' and CAstrategyInc=='O':
qEnt += np.tanh(receivedknowledge['Ent']*k['Ent']+c['Ent']['D']/costToQualityRatio-tau['Ent'])
qInc += receivedknowledge['Inc']*k['Inc']+c['Inc']['O']/costToQualityRatio-phi['Inc']
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = delta['Ent']*profitEnt-c['Ent']['D']
payoffInc = omega['Inc']*profitInc-c['Inc']['O']
elif CAstrategyEnt=='D' and CAstrategyInc=='D':
qEnt += np.tanh(receivedknowledge['Ent']*k['Ent']+c['Ent']['D']/costToQualityRatio-tau['Ent'])
qInc += np.tanh(receivedknowledge['Inc']*k['Inc']+c['Inc']['D']/costToQualityRatio-tau['Inc'])
priceEnt,profitEnt,priceInc,profitInc = optimumprofitIncLead(qEnt,qInc,Leader)
payoffEnt = delta['Ent']*profitEnt-c['Ent']['D']
payoffInc = delta['Inc']*profitInc-c['Inc']['D']
return payoffEnt,payoffInc,qEnt,qInc
\end{lstlisting}
输出中有三个问题（另请参见图像）：
- 在添加 Python 样式之前，文件中某些波斯语部分是正常的，但现在却以方块形式显示！
- 着色 Python 代码本身没问题，但所有单词都反向显示，如图所示。例如，单词
def显示为 ，fed这很奇怪。
- 数字以波斯语显示。这对于文档的其余部分来说没问题，但在这里我希望它们可以用英语显示。
如有任何建议，我将不胜感激。谢谢。