With the help of np.lagvander2d()
method, we can get the Pseudo-Vandermonde matrix from given array having degree which is passed as parameter by using np.lagvander2d()
method.
Syntax :
np.lagvander2d(x, y, deg)
Parameters:
x, y :[ array_like ] Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array
deg :[int] Degree of the resulting matrix.Return : Return the matrix having size i.e array.size + (degree + 1).
Example #1 :
In this example we can see that by using np.lagvander2d()
method, we are able to get the pseudo-vandermonde matrix using this method.
# import numpy import numpy as np import numpy.polynomial.laguerre as geek # using np.lagvander() method ans = geek.lagvander2d(( 1 , 3 , 5 , 7 ), ( 2 , 4 , 6 , 8 ), [ 2 , 2 ]) print (ans) |
Output :
[[ 1. -1. -1. 0. -0. -0. -0.5 0.5 0.5]
[ 1. -3. 1. -2. 6. -2. -0.5 1.5 -0.5]
[ 1. -5. 7. -4. 20. -28. 3.5 -17.5 24.5]
[ 1. -7. 17. -6. 42. -102. 11.5 -80.5 195.5]]
Example #2 :
# import numpy import numpy as np import numpy.polynomial.laguerre as geek ans = geek.lagvander2d(( 1 , 2 , 3 , 4 ), ( 5 , 6 , 7 , 8 ), [ 3 , 3 ]) print (ans) |
Output :
[[ 1. -4. 3.5 2.66666667 0. -0.
0. 0. -0.5 2. -1.75 -1.33333333
-0.66666667 2.66666667 -2.33333333 -1.77777778]
[ 1. -5. 7. 1. -1. 5.
-7. -1. -1. 5. -7. -1.
-0.33333333 1.66666667 -2.33333333 -0.33333333]
[ 1. -6. 11.5 -3.66666667 -2. 12.
-23. 7.33333333 -0.5 3. -5.75 1.83333333
1. -6. 11.5 -3.66666667]
[ 1. -7. 17. -12.33333333 -3. 21.
-51. 37. 1. -7. 17. -12.33333333
2.33333333 -16.33333333 39.66666667 -28.77777778]]