estimate the number of a given monster M a trainer will capture in a region R


Several small monster trainers have come to you for advice regarding expeditions they’re planning into various regions. You are writing a program to estimate how many monsters they can expect to capture in each region. • You’ve got a Small Monster Index that tells you the name, type, and relative commonality of all the small monsters in question. o (A monster’s absolute commonality is the same in each region. A monster’s relative commonality will change region by region as calculations are performed – we’ll show you how that works shortoy.) • You’ve also got an atlas that tells you about the relevant regions and which small monsters are present in them. • Each trainer tells you which regions they’re visiting, and how many monsters they intend to capture per region. • To estimate the number of a given monster M a trainer will capture in a region R: o Divide the relative population of M in R by R’s total relative population. o Multiply the result by the total number of captures the trainer intends per region. o Round this result to the nearest integer. .5 rounds up, so you can use round() and its friends. Note that this can result in a total slightly different than the trainer intended! Data Structures The structures you’ll use for the monsters, regions, itineraries and trainers are shown in the sidebar, and are also provided in fa20_cop3502_as1.h. You must use these structures. You’ll need to allocate, read, compute upon, output from, and subsequently free: • The monster index. o The names and elements of each monster in the monster index. • The region atlas. o The names and monster lists of each region. • A list of trainers. o The names and itineraries of each trainer. o The region list of each itinerary. typedef struct monster { int id; char *name; char *element; int population; } monster; typedef struct region { char *name; int nmonsters; int total_population; monster **monsters; } region; typedef struct itinerary { int nregions; region **regions; int captures; } itinerary; typedef struct trainer { char *name; itinerary *visits; } trainer; Example Input and Output We’ll provide more of these soon. Example Input 8 monsters StAugustine Grass 12 Zoysia Grass 8 WholeWheat Bread 6 MultiGrain Bread 10 Rye Bread 10 Cinnamon Spice 5 Pepper Spice 10 Pumpkin Spice 30 3 regions Rome 4 monsters StAugustine Zoysia WholeWheat Pepper Helve 5 monsters StAugustine WholeWheat MultiGrain Rye Cinnamon Aria 5 monsters Zoysia MultiGrain Cinnamon Pepper Pumpkin 3 Trainers Alice 5 captures 2 regions Rome Aria Bob 4 captures 3 regions Rome Helve Aria Carol 10 captures 1 region Aria Example Output Alice Rome 2 StAugustine 1 Zoysia 1 WholeWheat 1 Pepper Aria 1 Zoysia 1 MultiGrain 1 Pepper 2 Pumpkin Bob Rome 1 StAugustine 1 Zoysia 1 WholeWheat 1 Pepper Helve 1 StAugustine 1 WholeWheat 1 MultiGrain 1 Rye Aria 1 Zoysia 1 MultiGrain 1 Pepper 2 Pumpkin Carol Aria 1 Zoysia 2 MultiGrain 1 Cinnamon 2 Pepper 5 Pumpkin Mapping Example Here’s the table of how each individual trainer’s results are computed. It also shows how rounding issues can lead to trainers capturing more monsters than they intend! Rome Raw Divided Alice Round Bob Round Coefficient 1.00 36.00 5.00 4.00 StAugustine 12.00 0.33 1.67 2.00 1.33 1.00 Zoysia 8.00 0.22 1.11 1.00 0.89 1.00 WholeWheat 6.00 0.17 0.83 1.00 0.67 1.00 Pepper 10.00 0.28 1.39 1.00 1.11 1.00 Total 36.00 1.00 5.00 5.00 4.00 4.00 Helve Raw Divided Bob Round Coefficient 1.00 43.00 4.00 StAugustine 12.00 0.28 1.12 1.00 WholeWheat 6.00 0.14 0.56 1.00 MultiGrain 10.00 0.23 0.93 1.00 Rye 10.00 0.23 0.93 1.00 Cinnamon 5.00 0.12 0.47 0.00 Total 43.00 1.00 4.00 4.00 Aria Raw Divided Alice Round Bob Round Carol Round Coefficient 1.00 63.00 5.00 4.00 10.00 Zoysia 8.00 0.13 0.63 1.00 0.51 1.00 1.27 1.00 MultiGrain 10.00 0.16 0.79 1.00 0.63 1.00 1.59 2.00 Cinnamon 5.00 0.08 0.40 0.00 0.32 0.00 0.79 1.00 Pepper 10.00 0.16 0.79 1.00 0.63 1.00 1.59 2.00 Pumpkin 30.00 0.48 2.38 2.00 1.90 2.00 4.76 5.00 Total 63.00 1.00 5.00 5.00 4.00 5.00 10.00 11.00 Input and Output in General Read input from cop3502-as1-input.txt. Write output to cop3502-as1-output–.txt. For example, my output file will be named cop3502-as1-output-gerber-matthew.txt. There are blank lines in the sample inputs to make them more readable. They may or may not be present in the actual inputs; you should completely ignore blank lines. You’ll always get monsters, then regions, then trainers. Print order should generally be consistent with input: • Print the trainers in the order you got them. • Within the trainers, print the regions in the order you got the visits. • Within the regions, print the monster counts in the order they show up in the atlas for that region. • Print blank lines between each trainer. Specific Requirements • You need to free everything before closing the program. In fact: o You must #include “leak_detector_c.h” in your code, and o You must call atexit(report_mem_leak) as the first line of your main(). o (leak_detector_c.h and leak_detector_c.c will be provided. Keep them in your project directory while you’re working.) • I expect to see constructors and destructors for each of the structure types, with appropriate parameters. • You do not need to comment line by line, but comment every function and every “paragraph” of code. • You don’t have to hold to any particular indentation standard, but you must indent and you must do so consistently within your own code. • You may not use global variables.

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