def lup(A):
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
for k in range(0, n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
k_prime = i
if p == 0:
raise Exception('Error singular matrix')
pi[k], pi[k_prime] = pi[k_prime], pi[k]
LU[k], LU[k_prime] = LU[k_prime], LU[k]
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for j in range(k + 1, n):
LU[i][j] -= LU[i][k] * LU[k][j]
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lup(A):
"""
>>> lup([[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]])
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999, -0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994], [0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
# TODO Implement (psueodocode is in the book)
for i in range(n):
pi[i] = i
for k in range(n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
ki = i
if p == 0:
print "error"
temp = pi[k]
pi[k] = pi[ki]
pi[ki] = temp
for i in range(n):
temp1 = LU[k][i]
LU[k][i] = LU[ki][i]
LU[ki][i] = temp1
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for j in range(k + 1, n):
LU[i][j] -= (LU[i][k] * LU[k][j])
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lup(A):
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
result = "solved"
for k in range(n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
k1 = i
if p == 0:
result = "Error : Singular matrix"
temp = pi[k]
pi[k] = pi[k1]
pi[k1] = temp
for i in range(n):
temp = LU[k][i]
LU[k][i] = LU[k1][i]
LU[k1][i] = temp
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - LU[i][k] * LU[k][j]
return LU, pi, result
def lup(A):
"""
>>> A = [[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]]
>>> lup(A)
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999, -0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994], [0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
for k in range(0, n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
k1 = i
if p == 0:
raise Exception('SINGULAR MATRIX ERROR')
pi[k], pi[k1] = pi[k1], pi[k]
LU[k], LU[k1] = LU[k1], LU[k]
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - (LU[i][k] * LU[k][j])
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lu(A):
""" LUP method to find combined upper and lower method.
Parameters
----------
A: int
Matrix to operate the lup method on
Returns
-------
LU: upper triangular and lower triangular matrix which is the
solution of the given LU matrix
pi: The permutation for an identity matrix
>>> B = [[2,3],[3,1]]
>>> lu(B)
([[2, 3], [1, -2]], 'solved')
"""
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
for k in range(0, n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - LU[i][k] * LU[k][j]
printmat(LU)
return LU, 'solved'
def lup(A):
"""
>>> lup([[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]])
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999, -0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994], [0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
# TODO Implement (psueodocode is in the book)
for i in range(n):
pi[i] = i
for k in range(n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
ki = i
if p == 0:
print "error"
temp = pi[k]
pi[k] = pi[ki]
pi[ki] = temp
for i in range(n):
temp1 = LU[k][i]
LU[k][i] = LU[ki][i]
LU[ki][i] = temp1
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for j in range(k + 1, n):
LU[i][j] -= (LU[i][k] * LU[k][j])
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lup(A):
"""
>>> A = [[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]]
>>> lup(A)
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999, -0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994], [0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
for k in range(n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
q = i
if p == 0:
raise Exception("Error Singular Matrix")
temp = pi[k]
pi[k] = pi[q]
pi[q] = temp
temp = LU[k]
LU[k] = LU[q]
LU[q] = temp
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for j in range(k + 1, n):
LU[i][j] -= LU[i][k] * LU[k][j]
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lup(A):
"""
>>> A = [[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]]
>>> lup(A)
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999, -0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994], [0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
for k in range(0, n):
printmat(LU, perm=pi)
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
k1 = i
if p == 0:
raise Exception('SINGULAR MATRIX ERROR')
pi[k], pi[k1] = pi[k1], pi[k]
LU[k], LU[k1] = LU[k1], LU[k]
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - (LU[i][k] * LU[k][j])
printmat(LU, perm=pi)
return LU, pi, 'solved'
def lu(A):
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
for k in range(n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - (LU[i][k] * LU[k][j])
return LU, 'solved'
def lup(A):
""" LUP method to find combined upper and lower method.
Parameters
----------
A: int
Matrix to operate the lup method on
Returns
-------
LU: upper triangular and lower triangular
matrix which is the solution of the given LU matrix
pi: The permutation for an identity matrix
>>> A =[[2,0,2,.6],[3,3,4,-2],[5,5,4,2],[-1,-2,3.4,-1]]
>>> lup(A)
([[5.0, 5.0, 4.0, 2.0], [0.4, -2.0, 0.3999999999999999,\
-0.20000000000000007], [-0.2, 0.5, 4.0, -0.49999999999999994],\
[0.6, -0.0, 0.4, -3.0]], [2, 0, 3, 1], 'solved')
"""
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
pi = range(n)
temp = []
for i in range(0, n):
pi[i] = i
for k in range(0, n):
p = 0
for i in range(k, n):
if abs(LU[i][k]) > p:
p = abs(LU[i][k])
kp = i
if p == 0:
print"The matrix is singular"
return
printmat(LU, perm=pi)
temp = LU[k]
LU[k] = LU[kp]
LU[kp] = temp
temp = pi[k]
pi[k] = pi[kp]
pi[kp] = temp
printmat(LU, perm=pi)
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - LU[i][k] * LU[k][j]
return LU, pi, 'solved'
def check_lu():
A = LU_MATRIX
print "==========================="
print "Submitted by ", NAME
print "LU:"
print "Input:"
printmat(A)
print "Steps:"
LU, result = lu(A)
print "---------------------------"
print "Output:"
printmat(LU)
print 'result = ', result
print "---------------------------"
def check_lu():
A = LU_MATRIX
print "==========================="
print "Submitted by ", NAME
print "LU:"
print "Input:"
printmat(A)
print "Steps:"
LU, result = lu(A)
print "---------------------------"
print "Output:"
printmat(LU)
print 'result = ', result
print "---------------------------"
def lu(A):
n = len(A)
LU = [[float(A[i][j]) for j in range(n)] for i in range(n)]
for k in range(0, n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] -= LU[i][k] * LU[k][j]
printmat(LU)
return LU, 'solved'
def check_simplex():
A = SIMPLEX_MATRIX
print "==========================="
print "Submitted by ", NAME
print "SIMPLEX:"
print "Input:"
printmat(A)
print "Steps:"
SIMP, x, result = simplex(A)
print "---------------------------"
print "Output:"
printmat(SIMP)
print "result = ", result
print " z = ", x[0]
print " x = ", x[1:]
print "---------------------------"
def check_simplex():
A = SIMPLEX_MATRIX
print "==========================="
print "Submitted by ", NAME
print "SIMPLEX:"
print "Input:"
printmat(A)
print "Steps:"
SIMP, x, result = simplex(A)
print "---------------------------"
print "Output:"
printmat(SIMP)
print "result = ", result
print " z = ", x[0]
print " x = ", x[1:]
print "---------------------------"
def lu(A):
"""
>>> A = [[4, -5, 6], [8, -6, 7], [12, -7, 12]]
>>> lu(A)
([[4, -5, 6], [2, 4, -5], [3, 2, 4]], 'solved')
"""
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
for k in range(0, n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] = LU[i][k] / LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] = LU[i][j] - LU[i][k] * LU[k][j]
printmat(LU)
return LU, 'solved'
def lu(A):
"""
>>> lu([[4, -5, 6], [8, -6, 7], [12, -7, 12]])
([[4, -5, 6], [2, 4, -5], [3, 2, 4]], 'solved')
"""
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
# TODO Implement (psueodocode is in the book)
for k in range(n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] -= LU[i][k] * LU[k][j]
printmat(LU)
return LU, 'solved'
def check_lupsolve():
pi = LUPSOLVE_P
LU = LUPSOLVE_MATRIX
b = LUPSOLVE_B
print "==========================="
print "Submitted by ", NAME
print "LUP-SOLVE:"
print "---------------------------"
print "Input:"
printmat(LU, pi)
print "RHS:"
print b
print "---------------------------"
x = lupsolve(LU, pi, b)
print "x = [" + ', '.join(['%3.1f' % z for z in x]) + ']'
print "---------------------------"
def check_lup():
A = LUP_MATRIX
print "==========================="
print "Submitted by ", NAME
print "LUP:"
print "---------------------------"
print "Input:"
printmat(A)
print "---------------------------"
print "Steps:"
LUP, p, result = lup(A)
print "---------------------------"
print "Output:"
printmat(LUP, perm=p)
print "---------------------------"
print "result = ", result
print "---------------------------"
def lu(A):
"""
>>> lu([[4, -5, 6], [8, -6, 7], [12, -7, 12]])
([[4, -5, 6], [2, 4, -5], [3, 2, 4]], 'solved')
"""
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
# TODO Implement (psueodocode is in the book)
for k in range(n):
printmat(LU)
for i in range(k + 1, n):
LU[i][k] /= LU[k][k]
for i in range(k + 1, n):
for j in range(k + 1, n):
LU[i][j] -= LU[i][k] * LU[k][j]
printmat(LU)
return LU, 'solved'
def check_lupsolve():
pi = LUPSOLVE_P
LU = LUPSOLVE_MATRIX
b = LUPSOLVE_B
print "==========================="
print "Submitted by ", NAME
print "LUP-SOLVE:"
print "---------------------------"
print "Input:"
printmat(LU, pi)
print "RHS:"
print b
print "---------------------------"
x = lupsolve(LU, pi, b)
print "x = [" + ', '.join(['%3.1f' % z for z in x]) + ']'
print "---------------------------"
def check_lup():
A = LUP_MATRIX
print "==========================="
print "Submitted by ", NAME
print "LUP:"
print "---------------------------"
print "Input:"
printmat(A)
print "---------------------------"
print "Steps:"
LUP, p, result = lup(A)
print "---------------------------"
print "Output:"
printmat(LUP, perm=p)
print "---------------------------"
print "result = ", result
print "---------------------------"
def lu(A):
"""
>>> A = [[4, -5, 6], [8, -6, 7], [12, -7, 12]]
>>> lu(A)
([[4, -5, 6], [2, 4, -5], [3, 2, 4]], 'solved')
"""
n = len(A)
LU = [[A[i][j] for j in range(n)] for i in range(n)]
for i in range(0, n):
printmat(LU)
for j in range(i + 1, n):
LU[j][i] /= LU[i][i]
for k in range(i + 1, n):
for l in range(i + 1, n):
LU[k][l] = LU[k][l] - (LU[k][i] * LU[i][l])
printmat(LU)
return LU, 'solved'
def simplex(A):
# Assume that the input is already put into a table.
# Assume that the input is feasible already (no need to check)
m = len(A)
n = len(A[0])
x = [0] * (n - 1)
wiggle = [0] * m
while min(A[0][1:-1]) < 0:
# find entering variable
col = A[0].index(min(A[0][1:-1]))
min_wiggle = float('inf')
row = None
for i in range(1, m):
if A[i][col] > 0:
wiggle = A[i][-1] / float(A[i][col])
if wiggle < min_wiggle:
min_wiggle = wiggle
row = i
if row is None:
return A, x, 'unbounded'
printmat(A, pos=(row, col), row=row, col=col)
A = pivot(A, row, col)
printmat(A, pos=(row, col), row=row, col=col)
# Look for the basic variables and copy into x
for j in range(0, n - 1):
colvec = [A[i][j] for i in range(m)] # copy out the column
# Check if colvec is a column of the identity matrix.
if colvec.count(0.0) == m - 1 and colvec.count(1.0) == 1:
x[j] = A[colvec.index(1)][-1]
else:
x[j] = 0
return A, x, 'solved'
def simplex(A):
# Assume that the input is already put into a table.
# Assume that the input is feasible already (no need to check)
m = len(A)
n = len(A[0])
x = [0] * (n - 1)
wiggle = [0] * m
while min(A[0][1:-1]) < 0:
# find entering variable
col = A[0].index(min(A[0][1:-1]))
min_wiggle = float('inf')
row = None
for i in range(1, m):
if A[i][col] > 0:
wiggle = A[i][-1] / float(A[i][col])
if wiggle < min_wiggle:
min_wiggle = wiggle
row = i
if row is None:
return A, x, 'unbounded'
printmat(A, pos=(row, col), row=row, col=col)
A = pivot(A, row, col)
printmat(A, pos=(row, col), row=row, col=col)
# Look for the basic variables and copy into x
for j in range(0, n - 1):
colvec = [A[i][j] for i in range(m)] # copy out the column
# Check if colvec is a column of the identity matrix.
if colvec.count(0.0) == m - 1 and colvec.count(1.0) == 1:
x[j] = A[colvec.index(1)][-1]
else:
x[j] = 0
return A, x, 'solved'
