# R, c, rx, cx = eigensolver.get_eigenpair(i)

Hello everyone,

1- How I can find the minimum eigenvalue ?
2- How I can determine the eigenvectors correspond to the minimum eigenvalue ?
3 -How I can plot the eigenvectors ?
Thank you for your time and consideration.
Cordially

Consider the following example:

``````from dolfin import *

# Set up some simple variational form for illustration:
mesh = UnitIntervalMesh(100)
V = FunctionSpace(mesh,"CG",1)
u = TrialFunction(V)
v = TestFunction(V)

# Must assemble form to a PETScMatrix:
A = PETScMatrix()
assemble(a,tensor=A)

# Create eigenvalue solver:
eigenSolver = SLEPcEigenSolver(A)

# Configure solver to get the smallest eigenvalues first:
eigenSolver.parameters["spectrum"]="smallest magnitude"

# Solve for the N smallest eigenvalues:
N = 5
eigenSolver.solve(N)

from matplotlib import pyplot as plt
for i in range(0,N):

# The smallest eigenpair is the first (0-th) one:
r, c, rx, cx = eigenSolver.get_eigenpair(i)

# Turn the eigenvector into a Function:
rx_func = Function(V)
rx_func.vector()[:] = rx

# Function can be plotted as usual:
plot(rx_func)

plt.autoscale()
plt.show()
``````
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