Octave 性能測定の例

(a)	行列と行列の積	*X = rand(2000,2000); Y = rand(2000,2000); Z = X Y**
(b)	LU 分解 (LU decomposition)	X = rand(2000,2000); [L, U, P] = lu(X)
(c)	正方行列の逆行列	X = rand(2000,2000); [Z, RCOND] = inv(X)
(d)	行列式 (determinant)	X = rand(2000,2000); [D, RCOND] = det(X)
(e)	Singular Value Decomposition (SVD), X = USV	X = rand(2000,2000); [U, S, V] = svd(X)
(f)	QR factorization	X = rand(2000,2000); [Q, R, P] = qr(X)
(g)	分散共分散行列	X = rand(2000,2000), Y = rand(2000,2000); Z = cov(X, Y)
(h)	分散共分散行列の固有値と固有ベクトル（主成分分析）	X = rand(2000,2000); [v, L] = eig( cov(X) )
(i)	2次元の畳み込み（コンボリューション）	X = rand(2000,2000); B = rand(21); Z = conv2(X, B, 'full')
(j)	2次元の高速フーリエ変換 (FFT)	X = rand(2000,2000); Z = fft2(X, 2000, 2000)
(k)	convex hull	x = rand(1000000,1); y = rand(1000000,1); H = convhull(x, y)

【実測値の例】

(a) 行列と行列の積: X = rand(2000,2000); Y = rand(2000,2000); Z = X * Y

(b) LU 分解 (LU decomposition): X = rand(2000,2000); [L, U, P] = lu(X)

(d) 行列式 (determinant): X = rand(2000,2000); [D, RCOND] = det(X)

(e) Singular Value Decomposition (SVD), X = U*S*V: X = rand(2000,2000); [U, S, V] = svd(X)

(f) QR factorization (QR decomposition ともいう): X = rand(2000,2000); [Q, R, P] = qr(X)

(g) 分散共分散行列: X = rand(2000,2000); Y = rand(2000,2000); Z = cov(X, Y)

(h) 分散共分散行列の固有値と固有ベクトル（主成分分析）: X = rand(2000,2000); [v, L] = eig( cov(X) )

(i) 2次元の畳み込み（コンボリューション）: X = rand(2000,2000); B = rand(21); Z = conv2(X, B, 'full')

(j) 2次元の高速フーリエ変換 (FFT): X = rand(2000,2000); Z = fft2(X, 2000, 2000)

(k) convex hull: x = rand(1000000,1); y = rand(1000000,1); H = convhull(x, y)

（オプション）関連ソフトウェアのインストール例（書きかけ）

sudo apt -y update
sudo apt -y install libopenblas-dev
sudo apt -y install libsuitesparse-dev
sudo apt -y install octave
sudo apt -y install octave-pkg-dev
sudo apt -y install octave-*
sudo apt -y install gmt
sudo apt -y install gmt-examples
sudo apt -y install gmt-tutorial-pdf
sudo apt -y install gmt-doc-pdf
sudo apt -y install gmt-coast-low
sudo apt -y install pfstools
sudo apt -y install libplplot11
sudo apt -y install qtoctave