def gaussJordanPivot(a, tol=1.0e-9):
n = len(a)
seq = array(range(n))
# Set up scale factors
s = zeros((n), type=Float64)
for i in range(n):
s[i] = max(abs(a[i, :]))
for i in range(n):
# Row interchange, if needed
p = int(argmax(abs(a[i:n, i]) / s[i:n])) + i
if abs(a[p, i]) < tol: error.err('Matrix is singular')
if p != i:
swap.swapRows(s, i, p)
swap.swapRows(a, i, p)
swap.swapRows(seq, i, p)
# Elimination phase
temp = a[i, i]
a[i, i] = 1.0
a[i, 0:n] = a[i, 0:n] / temp
for k in range(n):
if k != i:
temp = a[k, i]
a[k, i] = 0.0
a[k, 0:n] = a[k, 0:n] - a[i, 0:n] * temp
# Rearrange columns in the right sequence
for i in range(n):
swap.swapCols(a, i, seq[i])
swap.swapRows(seq, i, seq[i])
return a
def gaussJordanPivot(a,tol=1.0e-9):
n = len(a)
seq = array(range(n))
# Set up scale factors
s = zeros((n),type=Float64)
for i in range(n):
s[i] = max(abs(a[i,:]))
for i in range(n):
# Row interchange, if needed
p = int(argmax(abs(a[i:n,i])/s[i:n])) + i
if abs(a[p,i]) < tol: error.err('Matrix is singular')
if p != i:
swap.swapRows(s,i,p)
swap.swapRows(a,i,p)
swap.swapRows(seq,i,p)
# Elimination phase
temp = a[i,i]
a[i,i] = 1.0
a[i,0:n] = a[i,0:n]/temp
for k in range(n):
if k != i:
temp = a[k,i]
a[k,i] = 0.0
a[k,0:n] = a[k,0:n] - a[i,0:n]*temp
# Rearrange columns in the right sequence
for i in range(n):
swap.swapCols(a,i,seq[i])
swap.swapRows(seq,i,seq[i])
return a
def sortJacobi(lam,x):
n = len(lam)
for i in range(n-1):
index = i
val = lam[i]
for j in range(i+1,n):
if lam[j] < val:
index = j
val = lam[j]
if index != i:
swap.swapRows(lam,i,index)
swap.swapCols(x,i,index)
def sortJacobi(lam, x):
n = len(lam)
for i in range(n - 1):
index = i
val = lam[i]
for j in range(i + 1, n):
if lam[j] < val:
index = j
val = lam[j]
if index != i:
swap.swapRows(lam, i, index)
swap.swapCols(x, i, index)
