저는 기본적으로 페르시아어용으로 설정된 템플릿으로 박사 학위 논문을 작성하려고 합니다. 모든 것이 페르시아어일 때 템플릿은 훌륭합니다. 하지만 문제가 있습니다. 내 것을 추가해야 해요Python 부록에 코드를 . 여기에서 링크를 찾았어요tex.stackexchange.com환경과 똑같고 Jupyter아름답습니다.
하지만 이 스타일을 파일에 추가하면 출력 LaTeX 파일의 일부 부분이 중단됩니다.
주요 LaTeX 코드는 다음과 같습니다.
\documentclass[oneside,phd,12pt]{AUTthesis}
\usepackage{graphicx,adjustbox}
\graphicspath{{figures/}} %Setting the graphicspath
\usepackage{amsthm,amssymb,amsmath}
\usepackage[center]{caption}
\usepackage{afterpage}
\usepackage{lscape}
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\usepackage{tikz}
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\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
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\usepackage{listings}
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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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morestring=[s]{u'}{'},% unicode strings
morestring=[s]{u"}{"},%
morestring=[s]{u'''}{'''},%
morestring=[s]{u"""}{"""},%
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{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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%-----------------------------------------------------------------------------
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%--------------------------------------------------------------------------appendix
\chapterfont{\vspace*{-2em}\centering\LARGE}%
\appendix
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\end{document}
그리고 부록은 다음과 같습니다.
\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}
출력에는 세 가지 문제가 있습니다(이미지도 참조하세요).
- Python 스타일을 추가하기 전에는 괜찮았던 파일의 일부 페르시아어 부분이 이제 사각형으로 표시됩니다!!!
- 컬러링 파이썬 코드 자체는 괜찮지만, 이미지에서 볼 수 있듯이 모든 단어가 거꾸로 표시됩니다. 예를 들어 단어가 이상하게
def표시됩니다 .fed
- 숫자는 페르시아어로 표시됩니다. 문서의 나머지 부분에서는 괜찮지만 여기에서는 영어로 작성되었으면 좋겠습니다.
어떤 조언이라도 감사하겠습니다. 감사해요.