Return the eigenvector corresponding to the max eigenvalue of A
As the title says, I must compute the eigenvector v corresponding to the max eigenvalue. I'm not sure what commands do this. Any tips?
import numpy as np
import scipy.linalg as la
#x and y both 1D NumPy arrays of same length
def eigen_X(x,y):
xa = np.mean(x)
ya = np.mean(y)
x_bar = x - xa
y_bar = y - ya
X = np.column_stack(x_bar,y_bar)
A = X.transpose()@X
#The rest of the code goes here
python eigenvalue eigenvector
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
add a comment |
As the title says, I must compute the eigenvector v corresponding to the max eigenvalue. I'm not sure what commands do this. Any tips?
import numpy as np
import scipy.linalg as la
#x and y both 1D NumPy arrays of same length
def eigen_X(x,y):
xa = np.mean(x)
ya = np.mean(y)
x_bar = x - xa
y_bar = y - ya
X = np.column_stack(x_bar,y_bar)
A = X.transpose()@X
#The rest of the code goes here
python eigenvalue eigenvector
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
add a comment |
As the title says, I must compute the eigenvector v corresponding to the max eigenvalue. I'm not sure what commands do this. Any tips?
import numpy as np
import scipy.linalg as la
#x and y both 1D NumPy arrays of same length
def eigen_X(x,y):
xa = np.mean(x)
ya = np.mean(y)
x_bar = x - xa
y_bar = y - ya
X = np.column_stack(x_bar,y_bar)
A = X.transpose()@X
#The rest of the code goes here
python eigenvalue eigenvector
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
As the title says, I must compute the eigenvector v corresponding to the max eigenvalue. I'm not sure what commands do this. Any tips?
import numpy as np
import scipy.linalg as la
#x and y both 1D NumPy arrays of same length
def eigen_X(x,y):
xa = np.mean(x)
ya = np.mean(y)
x_bar = x - xa
y_bar = y - ya
X = np.column_stack(x_bar,y_bar)
A = X.transpose()@X
#The rest of the code goes here
python eigenvalue eigenvector
python eigenvalue eigenvector
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
edited Nov 14 '18 at 19:29
Chance Gordon
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
asked Nov 14 '18 at 19:06
Chance GordonChance Gordon
124
124
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
scipy.linalg.eig provides a function that calculates eigenvalues and eigenvectors of a 2D, square matrix. To get the (right?) eigenvector corresponding to the largest eigenvalue, use
w, vl, vr = la.eig(A)
largest_eigenvector = vr[:, np.argmax(w)]
Replace vr[:, np.argmax(w)] above with vl[np.argmax(w)] if you're looking for the corresponding left eigenvector.
answered Nov 14 '18 at 19:37
jwiljwil
1799
add a comment |
It's possible to do this with just numpy's "linalg" library. The eig() function can give you the eigenvalues and eigenvectors. I converted the eigenvalues from a numpy array into a list in order to use "index" here to find the position of the largest eigenvalue. Then I picked the corresponding column from the eigenvector array.
>>> from numpy import linalg as LA
>>> M = ((1,-3,3), (3,-5,3), (6,-6,4))
>>> vals, vects = LA.eig(M)
>>> maxcol = list(vals).index(max(vals))
>>> eigenvect = vects[:,maxcol]
>>> print eigenvect
[-0.40824829+0.j -0.40824829+0.j -0.81649658+0.j]
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53307152%2freturn-the-eigenvector-corresponding-to-the-max-eigenvalue-of-a%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
scipy.linalg.eig provides a function that calculates eigenvalues and eigenvectors of a 2D, square matrix. To get the (right?) eigenvector corresponding to the largest eigenvalue, use
w, vl, vr = la.eig(A)
largest_eigenvector = vr[:, np.argmax(w)]
Replace vr[:, np.argmax(w)] above with vl[np.argmax(w)] if you're looking for the corresponding left eigenvector.
answered Nov 14 '18 at 19:37
jwiljwil
1799
add a comment |
scipy.linalg.eig provides a function that calculates eigenvalues and eigenvectors of a 2D, square matrix. To get the (right?) eigenvector corresponding to the largest eigenvalue, use
w, vl, vr = la.eig(A)
largest_eigenvector = vr[:, np.argmax(w)]
Replace vr[:, np.argmax(w)] above with vl[np.argmax(w)] if you're looking for the corresponding left eigenvector.
answered Nov 14 '18 at 19:37
jwiljwil
1799
add a comment |
scipy.linalg.eig provides a function that calculates eigenvalues and eigenvectors of a 2D, square matrix. To get the (right?) eigenvector corresponding to the largest eigenvalue, use
w, vl, vr = la.eig(A)
largest_eigenvector = vr[:, np.argmax(w)]
Replace vr[:, np.argmax(w)] above with vl[np.argmax(w)] if you're looking for the corresponding left eigenvector.
answered Nov 14 '18 at 19:37
jwiljwil
1799
scipy.linalg.eig provides a function that calculates eigenvalues and eigenvectors of a 2D, square matrix. To get the (right?) eigenvector corresponding to the largest eigenvalue, use
w, vl, vr = la.eig(A)
largest_eigenvector = vr[:, np.argmax(w)]
Replace vr[:, np.argmax(w)] above with vl[np.argmax(w)] if you're looking for the corresponding left eigenvector.
answered Nov 14 '18 at 19:37
jwiljwil
1799
answered Nov 14 '18 at 19:37
jwiljwil
1799
answered Nov 14 '18 at 19:37
jwiljwil
1799
answered Nov 14 '18 at 19:37
jwiljwil
1799
1799
add a comment |
add a comment |
It's possible to do this with just numpy's "linalg" library. The eig() function can give you the eigenvalues and eigenvectors. I converted the eigenvalues from a numpy array into a list in order to use "index" here to find the position of the largest eigenvalue. Then I picked the corresponding column from the eigenvector array.
>>> from numpy import linalg as LA
>>> M = ((1,-3,3), (3,-5,3), (6,-6,4))
>>> vals, vects = LA.eig(M)
>>> maxcol = list(vals).index(max(vals))
>>> eigenvect = vects[:,maxcol]
>>> print eigenvect
[-0.40824829+0.j -0.40824829+0.j -0.81649658+0.j]
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
add a comment |
It's possible to do this with just numpy's "linalg" library. The eig() function can give you the eigenvalues and eigenvectors. I converted the eigenvalues from a numpy array into a list in order to use "index" here to find the position of the largest eigenvalue. Then I picked the corresponding column from the eigenvector array.
>>> from numpy import linalg as LA
>>> M = ((1,-3,3), (3,-5,3), (6,-6,4))
>>> vals, vects = LA.eig(M)
>>> maxcol = list(vals).index(max(vals))
>>> eigenvect = vects[:,maxcol]
>>> print eigenvect
[-0.40824829+0.j -0.40824829+0.j -0.81649658+0.j]
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
add a comment |
It's possible to do this with just numpy's "linalg" library. The eig() function can give you the eigenvalues and eigenvectors. I converted the eigenvalues from a numpy array into a list in order to use "index" here to find the position of the largest eigenvalue. Then I picked the corresponding column from the eigenvector array.
>>> from numpy import linalg as LA
>>> M = ((1,-3,3), (3,-5,3), (6,-6,4))
>>> vals, vects = LA.eig(M)
>>> maxcol = list(vals).index(max(vals))
>>> eigenvect = vects[:,maxcol]
>>> print eigenvect
[-0.40824829+0.j -0.40824829+0.j -0.81649658+0.j]
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
It's possible to do this with just numpy's "linalg" library. The eig() function can give you the eigenvalues and eigenvectors. I converted the eigenvalues from a numpy array into a list in order to use "index" here to find the position of the largest eigenvalue. Then I picked the corresponding column from the eigenvector array.
>>> from numpy import linalg as LA
>>> M = ((1,-3,3), (3,-5,3), (6,-6,4))
>>> vals, vects = LA.eig(M)
>>> maxcol = list(vals).index(max(vals))
>>> eigenvect = vects[:,maxcol]
>>> print eigenvect
[-0.40824829+0.j -0.40824829+0.j -0.81649658+0.j]
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
answered Nov 14 '18 at 19:44
Bill M.Bill M.
835112
835112
add a comment |
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53307152%2freturn-the-eigenvector-corresponding-to-the-max-eigenvalue-of-a%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
