Need the python program for the following algorithm

Here is the explanation of the algorithm

Algorithm i: Vertex Component Analysis (VCA) INPUT p, R 1.r2. N] 15 10 log10 (p) 1: SNR th 2: if SNR SNRI then 4: X: UdR; (Ud obtained by SVD) 5: u:- mean(X); fu is a 1 x d vector 6: [Y] [x]: x] u); (projective projection 7: else 8: d p- 1; 9: [X] ,i Ud (IR] r); (Ud obtained by PCA) 10 c arg max. 1...N Illal J ll' 11 c [clcl Icl; {c is a 1 x N vector) 12 Y 13: end if 14: A 01; (eu 0, 1] and A is a p x p auxiliary matrix) 15: for i 1 to pdo 16 w randn 0, Ip); w is a zero-mean random Gaussian vector of covariance Ip) 17 f ((I-AA )w)/ (I (I AA )wll); (f is a vector orthonormal to the subspace spanned by Al 1:i 18 f Y 19 k arg maxi 1,...,N [v] find the projection ex treme. [A] [Y] 20 21 [indice] k; {stores the pixel index. 22: end for 23: if SNR th then 24 M d X] indice (M is a L x p estimated mixing matrix) 25: else 26 M Ud x]: indice +r; (M is a estimated mixing matrix) 27: end if Algorithm i: Vertex Component Analysis (VCA) INPUT p, R 1.r2. N] 15 10 log10 (p) 1: SNR th 2: if SNR SNRI then 4: X: UdR; (Ud obtained by SVD) 5: u:- mean(X); fu is a 1 x d vector 6: [Y] [x]: x] u); (projective projection 7: else 8: d p- 1; 9: [X] ,i Ud (IR] r); (Ud obtained by PCA) 10 c arg max. 1...N Illal J ll' 11 c [clcl Icl; {c is a 1 x N vector) 12 Y 13: end if 14: A 01; (eu 0, 1] and A is a p x p auxiliary matrix) 15: for i 1 to pdo 16 w randn 0, Ip); w is a zero-mean random Gaussian vector of covariance Ip) 17 f ((I-AA )w)/ (I (I AA )wll); (f is a vector orthonormal to the subspace spanned by Al 1:i 18 f Y 19 k arg maxi 1,...,N [v] find the projection ex treme. [A] [Y] 20 21 [indice] k; {stores the pixel index. 22: end for 23: if SNR th then 24 M d X] indice (M is a L x p estimated mixing matrix) 25: else 26 M Ud x]: indice +r; (M is a estimated mixing matrix) 27: end if