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FIT2004: Assessment

创建日期：2024-07-31 16:30:23

所属分类：计算机computer science

标签： FIT2004

Assessment

Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: THEend8_

FIT2004: Assessment

MARKING:You will be interviewed during your lab or at another time as arranged

by your demonstrator who will ask you a series of questions to assess your under-

standing of this exercise, and gauge how you implemented it. It is required that you

implement this exercise strictly using Python programming language. Practical

work is marked on the complexity of your program and also on your understand-

ing of the program. A perfect program with zero understanding implies you will get

zero marks! \Forgetting" is not an acceptable explanation for lack of understanding.

Demonstrators are not obliged to mark programs that do not run or that crash.

You will lose all marks for a given task if your algorithm does not produce correct

results for the task. Also, heavy penalties are applied if your complexity is worse

than the required complexity and you may lose all marks if the complexity is similar

to that of the naive algorithm. This is because our focus is on developing ecient

algorithms and data structures. Also, do not assume that each task carries equal

marks.

SUBMISSION REQUIREMENT: You will need to submit a zipped le contain-

ing your Python program (named cameradetector.py) as well as a PDF le brie

describing your solution and its space and time complexity. The PDF le must give

an outline of your solution (e.g., a high level idea of how did you solve it) and the

worst-case space and time complexity of your solution. Penalties will be applied if

you fail to submit the PDF le. The zipped le is to be submitted on Moodle before

the deadline.

Important: The assignments will be checked for plagiarism using an advanced pla-

giarism detector and the students will be interviewed by tutors to demonstrate the

understanding of their code. Last year, many students were detected by the plagia-

rism detector and almost all got zero mark for the assignment and, as a result, many

failed the unit. \Helping" others is NOT okay. Please do not share your solutions

with others. If someone asks you for help, ask them to visit us during consultation

hours for help.

1 Assessed Task: Red-light Camera Detector

Alice bursts into your room and is visibly upset. She waves a paper and screams, \I cannot

believe this. They sent me a ticket for violating the trac lights. I am sure the light was amber

when I crossed the intersection. This is unfair."

She then takes a long deep breath and rmly says, \Okay, I have decided that I will never

drive through an intersection with red-light cameras again. Never! Can you please help me to

write an app to detect the red-light cameras?".

By now, you know that you cannot say NO to Alice. So you respond: \Of course, Alice!

But give me some more information."

\Aaaww! You have always been such a good friend!" Alice happily says. \I also have a

small gift for you which I will give you later1. But let me give you details of what I need for

my camera detector app."

\Basically, I will provide you two text les named vertices.txt and edges.txt. The le

vertices.txt contains the IDs of the vertices/intersections that have red-light cameras. The

le edges.txt contains the information of edges corresponding to the road segments connecting

the intersections. Some of the edges (road segments) are toll roads. I want the application to

take as input a source vertex v and a value k; it must return me the k closest cameras from

the vertex v and the shortest paths to each of these cameras. I do not want to travel on a toll

road or drive through an intersection that has a red-light camera. Therefore, none of the paths

must contain a toll road or pass through a red-light camera. "

\hmmmm, okay I think I get it. But could you give me a more formal denition", you ask.

Alice: \Sure! A path from a vertex s to a vertex t is NOT safe if the source vertex s

contains a camera. Otherwise, the path is called a safe path if 1) none of the edges on the

path is a toll road; and 2) none of the vertices on the path (except the target vertex t) contains

a camera (the target vertex t may or may not have a camera). Safe distance from vertex s to

vertex t is the total length of the shortest safe path from s to t. Given an input vertex v, the

goal is to nd k-closest cameras considering only the safe paths.".

1.1 Input

The input les vertices.txt and edges.txt can be downloaded from Moodle2. The total

number of vertices are 6105 and you can assume that their IDs are in the range 0 to 6104.

Below are the rst 5 lines from vertices.txt denoting that the vertices 1; 5; 12; 16 and 20

have red-light cameras.

Below are some lines from edges.txt. The rst two values in each row correspond to the

vertices that the edge connects and the third value corresponds to the distance between the

vertices (i.e., the length of the edge). Some rows in edges.txt have four values where the

fourth value is TOLL denoting that this edge is a toll road. For example, the third line below

1Alice's reward is on page 5!

2This is a real data set corresponding to the road network in a German city Oldenburg.

shows that there is an edge between vertices with IDs 124 and 138. The length of this road

segment is 544:010193 and this is a toll road.

122 127 526.950012

123 125 228.396591

124 138 544.010193 TOLL

125 126 259.437286

1.2 Output

The program must ask the user to enter their location (vertex ID) and the value of k. It must

then display k-closest cameras considering only the safe paths. It must also display the safe

path to each of these cameras. Below is a sample output.

Enter your location: 1609

Enter k: 3

Camera 1 : 1595 Distance from your location: 89.02904600000001

Shortest path: 1609 --> 1600 --> 1593 --> 1595

Camera 2 : 1624 Distance from your location: 143.87629700000002

Shortest path: 1609 --> 1600 --> 1607 --> 1624

Camera 3 : 1648 Distance from your location: 170.821331

Shortest path: 1609 --> 1622 --> 1616 --> 1625 --> 1627 --> 1636 --> 1648

Note that there is a camera at vertex 1580 with distance 166:19017100000002 but it is not

returned in the above output because the shortest path to this camera passes through another

camera (at intersection 1595), i.e., the path is not a safe path. Below are the details of the

camera (and the shortest path to it) that must be ignored by your algorithm.

Camera : 1580 Distance from your location: 166.19017100000002

Shortest path: 1609 --> 1600 --> 1593 --> 1595 --> 1578 --> 1580

Below is another sample output.

Enter your location: 2011

Enter k: 2

Camera 1 : 1999 Distance from your location: 21.692297

Shortest path: 2011 --> 1999

Camera 2 : 1991 Distance from your location: 302.152092

Shortest path: 2011 --> 2016 --> 4563 --> 2003 --> 1985 --> 1976 --> 1991

There is a path to camera at intersection 4529 with distance 238:061092 but it is ignored

because the path contains a toll road. Below is a path to this camera which is invalid (i.e., not

safe) because it contains a toll road.

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25579 1ECE 273 M122 COMP4434 1ELEC ELEC5620M STAT0010 BFF2401 MXB361 MATH3811 CS330 CMT307 FIT1033 CptS 583 UP 431 MATH6005 AF5343 CS2435 ECOM30002 ES50061 CS 2506 ECMT6002 CODE 00099F MT4539 ESSAY ICM317 MATH1231 MFIT5010 BMA547 MATH334 CIVL2201 MATH39032 T-04 CIVE97119 EMESTER CAB302 CAB301 59PM STAT802 ISYS3412 RM3 COSC 2123 AcF 311 MATH2022 1FINAL 4CCS1PHC ICM 142 ENVS3023 Math 4023 I1 ACSE8 FIN B385F CS-275 STA 4109-01 A31021 EE140 MT1 EE124 ECO-6004B Inf2-IADS CS126 IS2184 UL18 MATH5092 ECOM009 COMP 6211 ELEC202 MKT3019 IAB230 FIT5046 584-S21 COMP3210 CO250 A29401 MATH 136 MGT6174 ECMT6007 DATA2001 MAT 443 MATH10222 PHDE0071 ELE00123M COSC1295 MAT00045H MATH32032 1004GRC MAS223 COMP10001 DATA3404 CIVL2110 STAT2008 FNCE10002 EEE6431 COM6515 COMP9120 NBS8185 ECTE942 ECON 405 MATH314301 STAT 2011 COMPSCI 350 COMP20007 CMPSC-132 ECON5002 STA 35 MTH6108 FIT5147 MTH6150 100C FINA 5260 DESC9115 ECON4998 NBS8257 GMM ECON 6070 BSA2 ECE599 STATS 102B STA120 INFS601 BFC3241 MATH20602 COMP532 MAS275 COMP5318 COMP4002 FIT5086 MAST20004 FIT3152 FIT5129 CIS2380 CS521 COMP 1005 EECMS CITS5501 ECE 462 ECON 6002 ENG 4051 CSC 648 CMT654 MECHENG 713 PHYS1002 AMME 2000 FP0060 DDES3200 MECHENG 743 BINF90002 FIT2081 ISYS90081 ELECTENG 722 BUS 360 ECOS3010 BUS2810 ETF2100 ENG2048 STAT5002 COMP2017 CEME 2003 MATS3004 COMP9319 PHYS1001 COMP5349 AMME2261 COMP-381 FIT3173 COSC2757 ENG4025 QBUS2820 COMP9414 MATH2021 EOSC118 MFIN6690 PMATH 321 CSE-141L MATH575A COMPSCI5002 COMP1511 management comp2123 FINS3616 COMP 3331 COMS30034 DTSC 71 AcF 702 AcF702 DTSC71 MAT021 ELE8083 ACFI213 EG-127J 127J FIT5163 FIT2001 ELE00113M CMT310 CS 245 ENGL 1101 MTH6115 EE497 CS 325 Math 124A MTH5130 MBA502 MGT 5380 ARCH 1261 F033800 20LLP109 ELE4009 FINANCIAL COMP3331 Computer ECE4179 20T3 COMP9311 COMP9311 UNSW MFIN6210 ACCT 5930 EE590 ENG2029 ECO100 SIT315 ACCT3610 COMP3600 STK2100 FIT2004 COMP30020 ACTL1101 Stat 101B BANA 200 COSC2473 ENGG1400 AI COMP90043 MMF 1914H PHYS 127 CS584 CIVL2010 ECMT2150 CS 333 CP1406 KIT308 Economics 701 ECON3740 ECE 5759 BFC3340 FINC2012 COMP4500 MATH3871 FIT3080 18-819C Economic ECO202Y5Y PHY100 FINC-780 Econ 100B EC602 IE582 EE450 COMP9517 WRDS 150B ECON 570 LECTURE 2 ECA5101 ECE 4420 ADAD9311 FIT3031 CS 544 MF 703 CS 6140 KIT501 ENGSCI 344 CSC171 IE 332 FINM8007 21S2 COSC 1114 FE545 E471 SIT102 CSC108 MAT301 IAE 101 COP3503 STAT2004 EC 303 CS1026 STAT1203 MATH3171 ISOM5160 IFN657 FIT2014 ACCT2102 DSCI550 STATS 330 ELEC421 COMP3670 QBUS6840 MEES:698B MAST30027 MIET1077 Economics IFT 6758 FIT5122 BUSN5101 CptS 111 HRMT5502 Math2018 PP 312 INFS3200 CZ3005 CSSE1001 SENG 2011 MKTG 553Q BUFN 640 COMP507 ETF5952 DATA 311 ECE4043 BANK3011 finance M3H623544 HW1 INFS 7410 AI6103 STAT3888 INFS3208 ACCT7103 ECOS3013 PSYCH 20B F79MA STAT3006 ENGG952 2X MGSC 7000 ECE4132 MSF 526 MATH 3033 CDS 511 EEEE4120 EEET2465 ECA5103 MATH2070 ELEC3104 BU51019 EEE8147 ENGR20003 COSC 1107 ETF3200 FNCE 435 MSFI 435 ISyE6420 GENG4405 HW ETC5523 IE 7315 MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A PHIL2617 PHYS3116 MIE250 BCPM0008 ECN 620 QBUS6830 ECSE-415 ECON5102 MGMT20005 MAT 653 ECO 480 COMP 5/600 CSSE 5600 ME 571 7CCMMS61 CS 550 COMP2865 MATH3075 STATS 506 QTM 220 ISYS2120 FIT5106 STAT 153 MKTG3112 ECON2102 ELE2018 COMP3031 MSIN0010 SCC461 MATH237 CS246 CSC3065 CSE 101 ICTWEB411 COMP9313 ECOS 2025 FN620 MATH11111 MATH 3018 KE1068 FINA 6112 C++ MISM 6202 MSIN0105 CSC8631 MECO6935 COMP4121 ACCT2011 DPBS1150 EEL 3701C F19PL OPM 661 CSE 310 CS918 BIOL30001 ACCT3563 BANK3600 MET CS622 MATH367 ACCT5907 Continuing COMP5048 COMP61021 CS3334 GSOE9210 CSCI-570 COMP 5322 HW 2 ALY-6020 IEOR 4706 DATA 200 EBUS504 CGE12412 COMP4108 7SSMM800 ECMM171P MATE50002 CS225 RS 6003 BH2274 ELEC3111 MAT6669 ECON-UA 227 PHIL 1012 7SSMM603 TB028A P6 ECS708 CSC 427 CS6476 CSE 250A A1A2 ITS61504 EECS 376 model HW6 UV0010 ECON 6074 MG4F7 CMP-7030Y INFO3008 BFIP013 ECON 5068 MATH6002 CS3483 PSTAT 131 C31FM CSOR W4246 AAEC 5307 DATA ELEC362 COMSM0047 ECN6006 MA20224 BST351 MATH 323 MATH323 AA2021 COMP3811 COMP2013 IB9X60 INVP001 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MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 IE5600 ECOS 3997 EDST2003 FIN 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