def testNRankInputMatrixThree(self):
mat1 = [[0, 0, 0, 0, 0, 0, 1.0 / 3, 0],
[1.0 / 2, 0, 1.0 / 2, 1.0 / 3, 0, 0, 0, 0],
[1.0 / 2, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1.0 / 2, 1.0 / 3, 0, 0, 1.0 / 3, 0],
[0, 0, 0, 1.0 / 3, 1.0 / 3, 0, 0, 1.0 / 2],
[0, 0, 0, 0, 1.0 / 3, 0, 0, 1.0 / 2],
[0, 0, 0, 0, 1.0 / 3, 1, 1.0 / 3, 0]]
mat2 = ['var1', 'var2', 'var3', 'var4', 'var5', 'var6', 'var7', 'var8']
mat3 = [1, 2, 1, 1, 2, 1, 1,
1] #so var2,var5 is twice as important as the other variables
#test to see if nRanking defaults to gRanking if alpha = 0
test = nRanking(mat1, mat2, 0,
mat3) #node and gain ranking are of equal importance
testCompare = gRanking(mat1, mat2)
for inclIntrinsic, exclIntrinsic in zip(test.rankArray,
testCompare.rankArray):
self.assertAlmostEqual(inclIntrinsic,
exclIntrinsic,
msg="Does not simplify to gRanking")
#test to see if important node is more important using this algorithm
test = nRanking(mat1, mat2, 0.5, mat3)
from numpy import array
highlighted = array((array(mat3) > 1), dtype=int)
for nrank, grank, high in zip(test.rankArray, testCompare.rankArray,
highlighted):
if (high == 1):
self.assertGreater(
nrank, grank,
"The more important node is not more important!")
def testNRankInputMatrixThree(self):
mat1 = [
[0, 0, 0, 0, 0, 0, 1.0 / 3, 0],
[1.0 / 2, 0, 1.0 / 2, 1.0 / 3, 0, 0, 0, 0],
[1.0 / 2, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1.0 / 2, 1.0 / 3, 0, 0, 1.0 / 3, 0],
[0, 0, 0, 1.0 / 3, 1.0 / 3, 0, 0, 1.0 / 2],
[0, 0, 0, 0, 1.0 / 3, 0, 0, 1.0 / 2],
[0, 0, 0, 0, 1.0 / 3, 1, 1.0 / 3, 0],
]
mat2 = ["var1", "var2", "var3", "var4", "var5", "var6", "var7", "var8"]
mat3 = [1, 2, 1, 1, 2, 1, 1, 1] # so var2,var5 is twice as important as the other variables
# test to see if nRanking defaults to gRanking if alpha = 0
test = nRanking(mat1, mat2, 0, mat3) # node and gain ranking are of equal importance
testCompare = gRanking(mat1, mat2)
for inclIntrinsic, exclIntrinsic in zip(test.rankArray, testCompare.rankArray):
self.assertAlmostEqual(inclIntrinsic, exclIntrinsic, msg="Does not simplify to gRanking")
# test to see if important node is more important using this algorithm
test = nRanking(mat1, mat2, 0.5, mat3)
from numpy import array
highlighted = array((array(mat3) > 1), dtype=int)
for nrank, grank, high in zip(test.rankArray, testCompare.rankArray, highlighted):
if high == 1:
self.assertGreater(nrank, grank, "The more important node is not more important!")
def testNRankTestPlantFeedReactorSeparatorRecycleOutput(self):
mat1 = [
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0],
[1.0 / 3, 0, 1.0 / 3, 0, 0, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[1.0 / 3, 0, 1.0 / 3, 0, 1, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[0, 1, 0, 1, 0, 0.5, 0, 0, 0, 0, 0, 0, 1, 0],
[1.0 / 3, 0, 1.0 / 3, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[0, 0, 0, 0, 0, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0],
]
mat2 = ["T1", "F1", "T2", "F2", "R1", "X1", "F3", "T3", "F4", "T4", "F6", "T6", "F5", "T5"]
mat3 = [
4,
1,
4,
1,
1,
1,
1,
4,
1,
4,
1,
4,
1,
4,
] # all the temperature variable are 4 times more important than the other ones (why? for safety reasons)
# test to see if nRanking defaults to gRanking if alpha = 0
test = nRanking(mat1, mat2, 0, mat3) # node and gain ranking are of equal importance
testCompare = gRanking(mat1, mat2)
for inclIntrinsic, exclIntrinsic in zip(test.rankArray, testCompare.rankArray):
self.assertAlmostEqual(inclIntrinsic, exclIntrinsic, msg="Does not simplify to gRanking")
# test to see if important node is more important using this algorithm
test = nRanking(mat1, mat2, 0.5, mat3)
from numpy import array
highlighted = array((array(mat3) > 1), dtype=int)
for nrank, grank, high in zip(test.rankArray, testCompare.rankArray, highlighted):
if high == 1:
self.assertGreater(nrank, grank, "The more important node is not more important!")
def testNRankTestPlantFeedReactorSeparatorRecycleOutput(self):
mat1 = [
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.5, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0,
0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0,
0],
[1.0 / 3, 0, 1.0 / 3, 0, 0, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[1.0 / 3, 0, 1.0 / 3, 0, 1, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[0, 1, 0, 1, 0, 0.5, 0, 0, 0, 0, 0, 0, 1, 0],
[1.0 / 3, 0, 1.0 / 3, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 1.0 / 3],
[0, 0, 0, 0, 0, 0, 1.0 / 3, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0]
]
mat2 = [
"T1", "F1", "T2", "F2", "R1", "X1", "F3", "T3", "F4", "T4", "F6",
"T6", "F5", "T5"
]
mat3 = [
4, 1, 4, 1, 1, 1, 1, 4, 1, 4, 1, 4, 1, 4
] #all the temperature variable are 4 times more important than the other ones (why? for safety reasons)
#test to see if nRanking defaults to gRanking if alpha = 0
test = nRanking(mat1, mat2, 0,
mat3) #node and gain ranking are of equal importance
testCompare = gRanking(mat1, mat2)
for inclIntrinsic, exclIntrinsic in zip(test.rankArray,
testCompare.rankArray):
self.assertAlmostEqual(inclIntrinsic,
exclIntrinsic,
msg="Does not simplify to gRanking")
#test to see if important node is more important using this algorithm
test = nRanking(mat1, mat2, 0.5, mat3)
from numpy import array
highlighted = array((array(mat3) > 1), dtype=int)
for nrank, grank, high in zip(test.rankArray, testCompare.rankArray,
highlighted):
if (high == 1):
self.assertGreater(
nrank, grank,
"The more important node is not more important!")
