===Orienteering Using A*===
Contributor: jacob verdesi jxv3386@rit.edu
Requirements: Python 3.7
              Pillow 6  (Used for image processing)
              plotly 4.2 ( Used for 3D render)
python3 lab1.py terrain.png mpp.txt red.txt winter redWinter.png
===Description===

This is a program that uses the A* algorithm to find the shortest path through a map

This map is given from a png file and colors correspond to the terrain type
Another file is given which is a txt file that stores the z values in an x and y format
Also a path file is given of points the A* algorithm traverses too this has an x and y value for each line
Next the season is given (spring,summer,fall, or winter) lowercase
The last program argument is a output image as a png file

Each pixel represents 7.55m in the y direction and 10.29m and 1m for z
There are 13 kinds of land that coorespond to colors:
Terrain type	        Color on map            Terrain Multiplyer
Open land	            #F89412 (248,148,18)    1.25
Rough meadow	        #FFC000 (255,192,0)     1.5
Easy movement forest	#FFFFFF (255,255,255)   2
Slow run forest	        #02D03C (2,208,60)      3
Walk forest	            #028828 (2,136,40)      4
Impassible vegetation	#054918 (5,73,24)       100
Lake/Swamp/Marsh	    #0000FF (0,0,255)       7
Paved road	            #473303 (71,51,3)       1
Footpath	            #000000 (0,0,0)         .95
Out of bounds	        #CD0065 (205,0,101)     200
MUD                                             7.5
ICE                                             8
LEAVES                                          6

The last 3 types of land are created based on the season (MUD,ICE,LEAVES)
Each Type of land has a different weight when traveling through it
This is accounted for in the g score by multiplying the distance to move 1 pixel with the terrain multiplyer
This score is added to the g score of the previous node to get this overall distance it took to get through here accounting terrain
By doing this we are able to keep the g and h scores balanced
To calculate h score we use Euclidean distance.
dx=abs(x1-x2)
dy=(y1-y2)
dz=(z1-z2)
return sqrt( sqrt(dx^2 + dy^2) + dz^2)
** I was thinking about using the Tobler's hiking function and the angle of z change but decided this output looked better
for calculating the f score we just add g+h

This diffrent seasons are calculated before the A* algorithm runs
First we read the terrain file , then the elevation file
We create a new map of points containing all of the data
After the map is created we search through the map for edges of water or trails,
based on the season.
For the winter and spring we use the edges to create a frontier for the BFS algorithm to travers
In the winter it looks for new Lake nodes while the spring looks for not water or mud or dz > 1
In the fall we just take these frontiers from the trails and look if the neigboring nodes have forests
When these nodes are found the map is updated with the new terrain and the image is also updated
Then it is sent to the a* algorithm

This program has a number of outputs
First it prints when its generating the map
Then it prints when it is running the paths
Onces it finds a point it prints the point until all the points are printed
Then it prints the time it took to find the points in seconds
Next it prints the Total disance the path is
Finally it prints what the output file is

**** I created additional renders in RenderMap that creates and elevation image, visitor map, and 3d render***
*** go in main and use the ConstuctRender function ***
The 3d render uses a downloaded package so if you dont want to use it , just delete the function
*tried to put the image over the surface of the 3d render but the library didnt allow custom colors :C