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Implement Vogel's method. Some corrections and result forming is needed

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emil
2024-11-07 06:29:06 +03:00
parent d9a54bda30
commit a2ecef62f1
1 changed files with 129 additions and 29 deletions
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main.py
+129 -29
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@@ -35,7 +35,7 @@ def NorthwestCorner(
S = np.array([1, 2, 3, 4])
S = np.array([50, 60, 50, 50])
C = np.array([
[16, 16, 13, 22, 17],
@@ -51,43 +51,142 @@ def Vogel(
C: np.array,
D: np.array) -> Result:
C_length = len(C[0])
C_height = len(C)
#print(C_length)
#print(C_height)
RowD = np.array
ColD = np.array
print(C)
iteration = 0
while(len(C[0]) > 1 and len(C) > 1):
iteration += 1
C_map = dict()
for y in range(len(C)):
for x in range(len(C[0])):
C_map[x,y] = C[y][x]
C_length = len(C[0])
C_height = len(C)
print(f"C_length: {C_length}")
print(f"C_height: {C_height}")
RowD = np.array
ColD = np.array
RowD = np.resize(RowD, C_height)
ColD = np.resize(ColD, C_length)
#print(sorted(C[0]))
#print(sorted(C[0])[0])
#print(sorted(C[0])[1])
RowD = np.resize(RowD, C_height)
ColD = np.resize(ColD, C_length)
#print(sorted(C[0]))
#print(sorted(C[0])[0])
#print(sorted(C[0])[1])
#Finding differences
for y in range(C_height):
RowD[y] = abs(sorted(C[y])[0] - sorted(C[y])[1])
for x in range(C_length):
ColD[x] = abs(sorted(C.T[x])[0] - sorted(C.T[x])[1])
#Finding differences
for y in range(C_height):
RowD[y] = abs(sorted(C[y])[0] - sorted(C[y])[1])
for x in range(C_length):
ColD[x] = abs(sorted(C.T[x])[0] - sorted(C.T[x])[1])
print(f"S: {S}")
print(f"D: {D}")
print(f"RowD: {RowD}")
print(f"ColD: {ColD}")
#Maximum difference
maxD = max(np.concatenate((ColD, RowD)))
target_array = np.array([])
target_number = None
row_index_to_eleminate = None
column_index_to_eleminate = None
print(f"maxD: {maxD}")
'''if maxD in RowD:
target_array = C[np.where(RowD == maxD)[0]][0]
target_number = min(target_array)
row_index_to_eleminate = np.where(target_array == target_number)[0][0]
print(f"row {row_index_to_eleminate}")
C = np.delete(C, row_index_to_eleminate, 0)
S = np.delete(S, row_index_to_eleminate, 0)'''
if maxD in RowD:
print("in RowD")
y = np.where(RowD == maxD)[0][0]
target_array = C[np.where(RowD == maxD)[0]][0]
target_number = min(target_array)
print(f"target_number: {target_number}")
x = np.where(target_array == target_number)[0][0]
print(f"(x,y): {(x,y)}")
print(f"D[x]:{D[x]}, S[y]:{S[y]}")
if (D[x] >= S[y]): #TODO ?
print("D[x] > S[y]")
row_index_to_eleminate = y
print(f"row_index_to_eleminate {row_index_to_eleminate}")
selected_value = S[y]
D[x] -= selected_value
C = np.delete(C, row_index_to_eleminate, 0)
S = np.delete(S, row_index_to_eleminate, 0)
else:
print("D[x] <= S[y]")
column_index_to_eleminate = x
selected_value = D[x]
S[y] -= selected_value
C = np.delete(C, column_index_to_eleminate, 1)
D = np.delete(D, column_index_to_eleminate, 0)
if maxD in ColD:
print("in ColD")
x = np.where(ColD == maxD)[0][0]
target_array = C.T[np.where(ColD == maxD)[0]][0]
target_number = min(target_array)
print(f"target_number: {target_number}")
y = np.where(target_array == target_number)[0][0]
print(f"(x,y): {(x,y)}")
print(f"D[x]:{D[x]}, S[y]:{S[y]}")
if (D[x] >= S[y]): #TODO ?
print("D[x] > S[y]")
row_index_to_eleminate = y
selected_value = S[y]
D[x] -= selected_value
C = np.delete(C, row_index_to_eleminate, 0)
S = np.delete(S, row_index_to_eleminate, 0)
else:
print("D[x] <= S[y]")
column_index_to_eleminate = x
selected_value = D[x]
S[y] -= selected_value
C = np.delete(C, column_index_to_eleminate, 1)
D = np.delete(D, column_index_to_eleminate, 0)
print(f"target_array: {target_array}")
print(f"selected_value: {selected_value}")
print(C)
#print(target_array)
#print(maxD)
#print(RowD)
#print(ColD)
#Maximum difference
maxD = max(np.concatenate((ColD, RowD)))
#print(maxD)
# TODO Vogel's method
pass
Vogel(S,C,D)
#Vogel(S,C,D)
def Russell(
S: np.array,
@@ -156,7 +255,7 @@ def solve(
return 0
if __name__ == "__main__":
'''if __name__ == "__main__":
C = np.array([
[16, 16, 13, 22, 17],
[14, 14, 13, 19, 15],
@@ -173,3 +272,4 @@ if __name__ == "__main__":
])
print(Russell(S, C, D))
'''