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Fixed long 88 characters line and object name issue and shortent learning source link

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miltonbhowmick 2023-08-12 21:22:34 +06:00
parent 89c60510dc
commit e2a380ed13
1 changed files with 14 additions and 5 deletions
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19
graphs/uniform_search_cost.py
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@ -1,10 +1,17 @@
##################### -- Learning Source -- ##################### ##################### -- Learning Source -- #####################
# 1. https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm#:~:text=Moreover%2C%20not%20inserting%20all%20nodes%20in%20a%20graph%20makes%20it%20possible%20to%20extend%20the%20algorithm%20to%20find%20the%20shortest%20path%20from # 1. https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
# 2. https://www.educative.io/answers/what-is-uniform-cost-search # 2. https://www.educative.io/answers/what-is-uniform-cost-search
# Uniform search cost is slighlty simillar to dijkstra. The main different between them is that UCS is having multiple goals. # In above 1 no. link, you will get about dijkstra algorithm.
# You may have to scroll down a little bit.
# And you will get a section titled as "Practical optimizations and infinite graphs"
# This section explains about Uniform Cost Search algorithm.
# Uniform search cost is slightly similar to dijkstra.
# The main different between them is that UCS is having multiple goals.
# Below code is fully based on 2D Grid environment
##################### --------------------- ##################### ##################### --------------------- #####################
# diagonal clockwise # diagonal clockwise
@ -269,9 +276,11 @@ def run() -> None:
>>> run() >>> run()
Increment Increment
Extended distance Extended distance
[[19, 17], [18, 18], [17, 19], [16, 19], [15, 19], [14, 19], [13, 18], [12, 17], [11, 16], [10, 15], [9, 14], [8, 13], [7, 13], [6, 12], [5, 11], [4, 10], [3, 9], [2, 8], [1, 8], [0, 7]] [[19, 17], [18, 18], [17, 19], [16, 19], [15, 19], [14, 19], [13, 18], [12, 17],
[11, 16], [10, 15],[9, 14], [8, 13], [7, 13], [6, 12], [5, 11], [4, 10], [3, 9],
[2, 8], [1, 8], [0, 7]]
""" """
object = UniformCostSearch( ucs_object = UniformCostSearch(
[ [
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
@ -295,7 +304,7 @@ def run() -> None:
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
], ],
) )
path_result = object.execute_algorithm( path_result = ucs_object.execute_algorithm(
[0, 7], [0, 7],
[19, 17], [19, 17],
[ [