numPy基础知识

from numpy import *

a = numpy.arange(10) ** 2a

array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81])

b = numpy.arange(10) ** 3b

array([  0,   1,   8,  27,  64, 125, 216, 343, 512, 729])

c = a + bc

array([  0,   2,  12,  36,  80, 150, 252, 392, 576, 810])

m = array([arange(2),arange(3)])m

array([array([0, 1]), array([0, 1, 2])], dtype=object)

m.shape

(2,)

#切片a  = arange(9)a[3:7]

array([3, 4, 5, 6])

# 翻转a[::-1]

array([8, 7, 6, 5, 4, 3, 2, 1, 0])

# 0~7 步长为2 a[:7:2]

array([0, 2, 4, 6])

# 多维数组切片 b = arange(24).reshape(2,3,4)b #三维数组

array([[[ 0,  1,  2,  3],        [ 4,  5,  6,  7],        [ 8,  9, 10, 11]],       [[12, 13, 14, 15],        [16, 17, 18, 19],        [20, 21, 22, 23]]])

b.shape

(2, 3, 4)

b[0,0,1]

1

# 选取第二层数组b[1::]

array([[[12, 13, 14, 15],        [16, 17, 18, 19],        [20, 21, 22, 23]]])

# 选取第一层数组b[0, : , : ]

array([[ 0,  1,  2,  3],       [ 4,  5,  6,  7],       [ 8,  9, 10, 11]])

# 可以用一个省略号代替b[0, ...]

array([[ 0,  1,  2,  3],       [ 4,  5,  6,  7],       [ 8,  9, 10, 11]])

b[0,1]

array([4, 5, 6, 7])

b[0,1,::2]

array([4, 6])

# 选取第一层所有位于第二列的数据b[0,:,1]

array([1, 5, 9])

b[0,:,-1,]

array([ 3,  7, 11])

b[0,::-1,-1]

array([11,  7,  3])

b[0,::-1]

array([[ 8,  9, 10, 11],       [ 4,  5,  6,  7],       [ 0,  1,  2,  3]])

3 第一维和第二维颠倒b[::-1]

array([[[12, 13, 14, 15],        [16, 17, 18, 19],        [20, 21, 22, 23]],       [[ 0,  1,  2,  3],        [ 4,  5,  6,  7],        [ 8,  9, 10, 11]]])

b

array([[[ 0,  1,  2,  3],        [ 4,  5,  6,  7],        [ 8,  9, 10, 11]],       [[12, 13, 14, 15],        [16, 17, 18, 19],        [20, 21, 22, 23]]])

# 将数组平铺b.ravel()

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,       17, 18, 19, 20, 21, 22, 23])

b.flatten()

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,       17, 18, 19, 20, 21, 22, 23])

# 改变数组维度 别成二维数组b.shape=(6,4)b

array([[ 0,  1,  2,  3],       [ 4,  5,  6,  7],       [ 8,  9, 10, 11],       [12, 13, 14, 15],       [16, 17, 18, 19],       [20, 21, 22, 23]])

# 转换矩阵b.transpose()

array([[ 0,  4,  8, 12, 16, 20],       [ 1,  5,  9, 13, 17, 21],       [ 2,  6, 10, 14, 18, 22],       [ 3,  7, 11, 15, 19, 23]])

b.resize((2,12))b

array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11],       [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]])

# 数组组合

a = arange(9).reshape(3,3)a

array([[0, 1, 2],       [3, 4, 5],       [6, 7, 8]])

b = 2 * ab

array([[ 0,  2,  4],       [ 6,  8, 10],       [12, 14, 16]])

#水平组合hstack((a,b))

array([[ 0,  1,  2,  0,  2,  4],       [ 3,  4,  5,  6,  8, 10],       [ 6,  7,  8, 12, 14, 16]])

concatenate((a,b),axis=1)

array([[ 0,  1,  2,  0,  2,  4],       [ 3,  4,  5,  6,  8, 10],       [ 6,  7,  8, 12, 14, 16]])

#垂直组合vstack((a,b))

array([[ 0,  1,  2],       [ 3,  4,  5],       [ 6,  7,  8],       [ 0,  2,  4],       [ 6,  8, 10],       [12, 14, 16]])

concatenate((a,b),axis=0)

array([[ 0,  1,  2],       [ 3,  4,  5],       [ 6,  7,  8],       [ 0,  2,  4],       [ 6,  8, 10],       [12, 14, 16]])

#深度组合 将相同元祖作为参数传给dstack函数dstack((a,b))

array([[[ 0,  0],        [ 1,  2],        [ 2,  4]],       [[ 3,  6],        [ 4,  8],        [ 5, 10]],       [[ 6, 12],        [ 7, 14],        [ 8, 16]]])

# 列组合 oned = arange(2)oned

array([0, 1])

twiced_oned =2 *onedtwiced_oned

array([0, 2])

# 列组合对于一维数组 按照列的方向进行组合column_stack((oned,twiced_oned))

array([[0, 0],       [1, 2]])

# 列组合 对于二维数组 与hstack效果相同column_stack((a,b))

array([[ 0,  1,  2,  0,  2,  4],       [ 3,  4,  5,  6,  8, 10],       [ 6,  7,  8, 12, 14, 16]])

column_stack((a,b)) == hstack((a,b))

array([[ True,  True,  True,  True,  True,  True],       [ True,  True,  True,  True,  True,  True],       [ True,  True,  True,  True,  True,  True]], dtype=bool)

# 行组合row_stack((oned,twiced_oned))

array([[0, 1],       [0, 2]])

row_stack((a,b))

array([[ 0,  1,  2],       [ 3,  4,  5],       [ 6,  7,  8],       [ 0,  2,  4],       [ 6,  8, 10],       [12, 14, 16]])

row_stack((a,b)) == vstack((a,b))

array([[ True,  True,  True],       [ True,  True,  True],       [ True,  True,  True],       [ True,  True,  True],       [ True,  True,  True],       [ True,  True,  True]], dtype=bool)