np.meshgrid參考
官方文檔給出的解釋

Return coordinate matrices from coordinate vectors.
Make N-D coordinate arrays for vectorized evaluations of N-D scalar/vector fields over N-D grids, given one-dimensional coordinate arrays x1, x2,…, xn.

參數(shù)
indexing : {‘xy’, ‘ij’}, optional Cartesian (‘xy’, default) or matrix (‘ij’) indexing of output.
返回

X1, X2,..., XN : ndarray

For vectors x1, x2,…, xn with lengths Ni=len(xi) , return (N1, N2, N3,...Nn) shaped arrays if indexing=‘ij’ or (N2, N1, N3,...Nn) shaped arrays if indexing=‘xy’ with the elements of xi repeated to fill the matrix along the first dimension for x1, the second for x2 and so on.

• 關(guān)于indexing,默認(rèn)是xy形式的，即笛卡爾坐標(biāo)系的形式。
• 如果輸入向量 x1, x2,…, xn 的長(zhǎng)度Ni=len(xi)，那么在indexing = 'xy'時(shí)返回(N2, N1, N3,...Nn)形式的numpy數(shù)組，indexing = ‘ij’時(shí)返回 (N2, N1, N3,...Nn)形式的numpy數(shù)組
• 如果xi是np.array形式的數(shù)據(jù)，在進(jìn)行np.meshgrid會(huì)自動(dòng)地將xi先展平，再進(jìn)行操作
  下面x是維度為(2,3,4)地numpy數(shù)組，展平后是(24,)

x = np.linspace(1,15,24).reshape(2,3,4) y = np.linspace(11,15,6) z = np.linspace(21,25,5)xx,yy,zz = np.meshgrid(x,y,z)print(xx.shape) # (6,24,5)

• 對(duì)于numpy里面地矩陣(np.matrix)，則不會(huì)進(jìn)行展平。而且，需要注意變量的維度

m, n = (5, 3) x = np.linspace(0, 1, m) y = np.linspace(0, 1, n) x:array([ 0. , 0.25, 0.5 , 0.75, 1. ]) y:array([ 0. , 0.5, 1. ])

xx,yy = np.meshgrid(x,y)

x 是m 維向量，y是n維向量，np.meshgrid(x,y)后的結(jié)果是(n,m)
得到的xx,是x在縱軸方向上復(fù)制n次，yy是y在橫軸方向上復(fù)制m次

生成測(cè)試數(shù)據(jù)網(wǎng)格

grid_test = np.stack((xx.flat,yy.flat),axis=1) grid_predict= gmm.predict(grid_test)

得到grid_test

[[0. 0. ][0.25 0. ][0.5 0. ][0.75 0. ][1. 0. ][0. 0.5 ] ...]

總結(jié)

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