reza1944
یک شنبه 20 تیر 1395, 01:33 صبح
با سیلام خدمت دوستان
ممنون میشم از دوستانی که بتونن این پروژه رو طبق فایل راهنماش کامپایل کنن
خیلی مهمه - یه فایل خروجی تولید میکنه
با تشکر از دوستان
usage:
The second argument is optional and changes the random number generator seed.
1) For simple undirected graphs:
./clusterer test 0
clusterer reads Datasets/test/test.txt
test.txt consists of the network edges in the format of "src dst"
2) For weighted undirected graphs:
./weclusterer test 0
./weintclusterer test 0
weintclusterer is optimized for integer edge weights.
weclusterer (weintclusterer) reads Datasets/test/test.txt
test.txt consists of network edges in the format of "src dst weight"
In case of conflicts, e.g. "2 5 2.5", "2 5 3.5" and "5 2 3", they consider "2 5 3.5", in which the weight is the maximum of the input weights.
Program automatically generates Datasets/test/test.smg for future use and it might take more time in the first run. In the future releases, this part should be more optimized.
if you have a .smg file, you don't need the .txt file anymore.
if you like to compile the program manually, here is what you need:
-DcompLimit=40 you can set a limit for the number of clusters
-DexactClustersCount using it in conjunction with -DcompLimit produces exactly compLimit clusters (Useful for when the number of clusters is known) (compLimit must be not higher than the number of vertices)
-DpageRankAlpha=0.7 to change the PageRank alpha value
-DTRIAL_DEFAULT=50 minimum number of random jumps starting from a vertex
-DTRIAL_DEFUALT_MULT=10 number of random jumps starting from a vertex = max{TRIAL_DEFUALT_MULT * node's degree, DTRIAL_DEFAULT}
-DHA creates .tree output file
-Dhier creates .tree output file: with hierarchy -> Datasets/football/hier_football.tree
-Dcreategraphml creates .graphml output file
-DWE for weighted graphs with float weights
-DWE -DintWeight for weighted graphs with integer weights
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ممنون میشم از دوستانی که بتونن این پروژه رو طبق فایل راهنماش کامپایل کنن
خیلی مهمه - یه فایل خروجی تولید میکنه
با تشکر از دوستان
usage:
The second argument is optional and changes the random number generator seed.
1) For simple undirected graphs:
./clusterer test 0
clusterer reads Datasets/test/test.txt
test.txt consists of the network edges in the format of "src dst"
2) For weighted undirected graphs:
./weclusterer test 0
./weintclusterer test 0
weintclusterer is optimized for integer edge weights.
weclusterer (weintclusterer) reads Datasets/test/test.txt
test.txt consists of network edges in the format of "src dst weight"
In case of conflicts, e.g. "2 5 2.5", "2 5 3.5" and "5 2 3", they consider "2 5 3.5", in which the weight is the maximum of the input weights.
Program automatically generates Datasets/test/test.smg for future use and it might take more time in the first run. In the future releases, this part should be more optimized.
if you have a .smg file, you don't need the .txt file anymore.
if you like to compile the program manually, here is what you need:
-DcompLimit=40 you can set a limit for the number of clusters
-DexactClustersCount using it in conjunction with -DcompLimit produces exactly compLimit clusters (Useful for when the number of clusters is known) (compLimit must be not higher than the number of vertices)
-DpageRankAlpha=0.7 to change the PageRank alpha value
-DTRIAL_DEFAULT=50 minimum number of random jumps starting from a vertex
-DTRIAL_DEFUALT_MULT=10 number of random jumps starting from a vertex = max{TRIAL_DEFUALT_MULT * node's degree, DTRIAL_DEFAULT}
-DHA creates .tree output file
-Dhier creates .tree output file: with hierarchy -> Datasets/football/hier_football.tree
-Dcreategraphml creates .graphml output file
-DWE for weighted graphs with float weights
-DWE -DintWeight for weighted graphs with integer weights
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