import numpy as np

v = np.array([1,2])
A = np.array([[2,3],
              [5,2]])

t = A@v
print (t)

import numpy as np
v = np.array([1,2])
A = np.array([[2,3],
              [5,2],
              [1,1]])

t = A@v
print (t)

import numpy as np
v = np.array([1,2])
A = np.array([[1,2],
              [2,1]])

t = A@v
print (t)

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

v = np.array([1,0])
A = np.array([[2,0],
              [0,2]])

t = A@v
print (t)

# Plot v and t
vecs = np.array([t,v])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v, color=['blue'], scale=10)
plt.quiver(*origin, *t, color=['orange'], scale=10)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

v = np.array([1,0])
A = np.array([[0,-1],
              [1,0]])

t = A@v
print (t)

# Plot v and t
vecs = np.array([v,t])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t, color=['blue'], scale=10)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

v = np.array([1,0])
A = np.array([[2,1],
              [1,2]])

t = A@v
print (t)

# Plot v and t
vecs = np.array([v,t])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t, color=['blue'], scale=10)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

v = np.array([1,1])
A = np.array([[5,2],
              [3,1]])
b = np.array([-2,-6])

t = A@v + b
print (t)

# Plot v and t
vecs = np.array([v,t])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=15)
plt.quiver(*origin, *t, color=['blue'], scale=15)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

v = np.array([1,0])
A = np.array([[2,0],
              [0,2]])

t1 = A@v
print (t1)
t2 = 2*v
print (t2)

fig = plt.figure()
a=fig.add_subplot(1,1,1)
# Plot v and t1
vecs = np.array([t1,v])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t1, color=['blue'], scale=10)
plt.show()
a=fig.add_subplot(1,2,1)
# Plot v and t2
vecs = np.array([t2,v])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t2, color=['blue'], scale=10)
plt.show()

import numpy as np
A = np.array([[2,0],
              [0,3]])
eVals, eVecs = np.linalg.eig(A)
print(eVals)
print(eVecs)

vec1 = eVecs[:,0]
lam1 = eVals[0]

print('Matrix A:')
print(A)
print('-------')

print('lam1: ' + str(lam1))
print ('v1: ' + str(vec1))
print ('Av1: ' + str(A@vec1))
print ('lam1 x v1: ' + str(lam1*vec1))

print('-------')

vec2 = eVecs[:,1]
lam2 = eVals[1]

print('lam2: ' + str(lam2))
print ('v2: ' + str(vec2))
print ('Av2: ' + str(A@vec2))
print ('lam2 x v2: ' + str(lam2*vec2))

t1 = lam1*vec1
print (t1)
t2 = lam2*vec2
print (t2)

fig = plt.figure()
a=fig.add_subplot(1,1,1)
# Plot v and t1
vecs = np.array([t1,vec1])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t1, color=['blue'], scale=10)
plt.show()
a=fig.add_subplot(1,2,1)
# Plot v and t2
vecs = np.array([t2,vec2])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t2, color=['blue'], scale=10)
plt.show()

import numpy as np
A = np.array([[2,0],
              [0,2]])
eVals, eVecs = np.linalg.eig(A)
print(eVals)
print(eVecs)

vec1 = eVecs[:,0]
lam1 = eVals[0]

print('Matrix A:')
print(A)
print('-------')

print('lam1: ' + str(lam1))
print ('v1: ' + str(vec1))
print ('Av1: ' + str(A@vec1))
print ('lam1 x v1: ' + str(lam1*vec1))

print('-------')

vec2 = eVecs[:,1]
lam2 = eVals[1]

print('lam2: ' + str(lam2))
print ('v2: ' + str(vec2))
print ('Av2: ' + str(A@vec2))
print ('lam2 x v2: ' + str(lam2*vec2))


# Plot the resulting vectors
t1 = lam1*vec1
t2 = lam2*vec2

fig = plt.figure()
a=fig.add_subplot(1,1,1)
# Plot v and t1
vecs = np.array([t1,vec1])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t1, color=['blue'], scale=10)
plt.show()
a=fig.add_subplot(1,2,1)
# Plot v and t2
vecs = np.array([t2,vec2])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t2, color=['blue'], scale=10)
plt.show()

import numpy as np

A = np.array([[2,1],
              [1,2]])

eVals, eVecs = np.linalg.eig(A)
print(eVals)
print(eVecs)

vec1 = eVecs[:,0]
lam1 = eVals[0]

print('Matrix A:')
print(A)
print('-------')

print('lam1: ' + str(lam1))
print ('v1: ' + str(vec1))
print ('Av1: ' + str(A@vec1))
print ('lam1 x v1: ' + str(lam1*vec1))

print('-------')

vec2 = eVecs[:,1]
lam2 = eVals[1]

print('lam2: ' + str(lam2))
print ('v2: ' + str(vec2))
print ('Av2: ' + str(A@vec2))
print ('lam2 x v2: ' + str(lam2*vec2))


# Plot the results
t1 = lam1*vec1
t2 = lam2*vec2

fig = plt.figure()
a=fig.add_subplot(1,1,1)
# Plot v and t1
vecs = np.array([t1,vec1])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t1, color=['blue'], scale=10)
plt.show()
a=fig.add_subplot(1,2,1)
# Plot v and t2
vecs = np.array([t2,vec2])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t2, color=['blue'], scale=10)
plt.show()

import numpy as np

A = np.array([[3,2],
              [1,0]])

l, Q = np.linalg.eig(A)
print(Q)

L = np.diag(l)
print (L)

Qinv = np.linalg.inv(Q)
print(Qinv)

v = np.array([1,3])
t = A@v

print(t)

# Plot v and t
vecs = np.array([v,t])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t, color=['blue'], scale=10)
plt.show()

import math
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

t = (Q@(L@(Qinv)))@v

# Plot v and t
vecs = np.array([v,t])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=10)
plt.quiver(*origin, *t, color=['blue'], scale=10)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

t1 = Qinv@v
t2 = L@t1
t3 = Q@t2

# Plot the transformations
vecs = np.array([v,t1, t2, t3])
origin = [0], [0]
plt.axis('equal')
plt.grid()
plt.ticklabel_format(style='sci', axis='both', scilimits=(0,0))
plt.quiver(*origin, *v,  color=['orange'], scale=20)
plt.quiver(*origin, *t1, color=['blue'], scale=20)
plt.quiver(*origin, *t2, color=['red'], scale=20)
plt.quiver(*origin, *t3, color=['magenta'], scale=20)
plt.show()

import numpy as np
A = np.array([[1,2],
              [4,3]])
l, Q = np.linalg.eig(A)
L = np.diag(l)
print(L)

B = np.array([[3,-3,6],
              [2,-2,4],
              [1,-1,2]])
lb, Qb = np.linalg.eig(B)
Lb = np.diag(lb)
print(Lb)

import numpy as np
A = np.array([[1,2],
              [4,3]])

l, Q = np.linalg.eig(A)
L = np.diag(l)
print(Q)
Linv = np.linalg.inv(L)
Qinv = np.linalg.inv(Q)
print(Linv)
print(Qinv)

Ainv = (Q@(Linv@(Qinv)))
print(Ainv)

print(np.linalg.inv(A))