一、numpy入門
阿新 • • 發佈：2018-04-19
常用函數 [1] counter bcb launch save unique port a + b 
Array
import numpy as np # create from python list list_1 = [1, 2, 3, 4] array_1 = np.array(list_1)#array([1, 2, 3, 4]) list_2 = [5, 6, 7, 8] array_2 = np.array([list_1, list_2])
結果：
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
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array_2.shape#(2, 4) array_2.size#8 array_2.dtype#dtype(‘int64‘) array_3 = np.array([[1.0,2,3],[4.0,5,6]]) array_3.dtype#dtype(‘float64‘) array_4 = np.arange(1, 10, 2)#array([1, 3, 5, 7, 9]) np.zeros(5)#array([ 0., 0., 0., 0., 0.])
np.zeros([2,3])
結果：
array([[ 0., 0., 0.],
[ 0., 0., 0.]])
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np.eye(5)
結果：
array([[ 1., 0., 0., 0., 0.], [ 0., 1., 0., 0., 0.], [ 0., 0., 1., 0., 0.], [ 0., 0., 0., 1., 0.], [ 0., 0., 0., 0., 1.]])View Code
np.eye(5).dtype#dtype(‘float64‘)
a = np.arange(1,10)#array([1, 2, 3, 4, 5, 6, 7, 8, 9]) a[1]#2 a[1:5]#array([2, 3, 4, 5])
b = np.array([[1,2,3],[4,5,6]]) b
結果：
array([[1, 2, 3],
[4, 5, 6]])
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b[1][0]#4 b[1,0]#4
c = np.array([[1,2,3],[4,5,6],[7,8,9]]) c
結果：
array([[1, 2, 3], [4, 5, 6], [View Code7, 8, 9]])
c[:2,1:]
結果：
array([[2, 3],
[5, 6]])
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數組與矩陣運算
快速創建數組
import numpy as np np.random.randn(10)
結果：
array([ 0.28906593, 1.4302902 , 1.10346334, 0.11146373, -0.47497452,
0.88859371, 0.18953089, -0.65780036, -2.06789973, -1.45679231])
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np.random.randint(10, size=20).reshape(4, 5)
結果：
array([[8, 5, 8, 4, 5], [4, 5, 2, 8, 3], [3, 6, 9, 7, 3], [3, 0, 4, 7, 0]])View Code
數組運算
a = np.random.randint(10, size=20).reshape(4, 5) b = np.random.randint(10, size=20).reshape(4, 5) a b
結果：
array([[3, 6, 5, 9, 3], [3, 3, 4, 6, 8], [3, 3, 2, 3, 4], [6, 0, 9, 7, 9]]) array([[1, 5, 6, 0, 6], [0, 2, 1, 7, 9], [7, 6, 1, 3, 8], [4, 4, 3, 1, 0]])View Code
a + b
結果：
array([[ 4, 11, 11, 9, 9], [ 3, 5, 5, 13, 17], [10, 9, 3, 6, 12], [10, 4, 12, 8, 9]])View Code
a-b
結果：
array([[ 2, 1, -1, 9, -3], [ 3, 1, 3, -1, -1], [-4, -3, 1, 0, -4], [ 2, -4, 6, 6, 9]])View Code
a * b
結果：
array([[ 3, 30, 30, 0, 18], [ 0, 6, 4, 42, 72], [21, 18, 2, 9, 32], [24, 0, 27, 7, 0]])View Code
a / b
結果：
RuntimeWarning: divide by zero encountered in true_divide """Entry point for launching an IPython kernel. array([[ 3. , 1.2 , 0.83333333, inf, 0.5 ], [ inf, 1.5 , 4. , 0.85714286, 0.88888889], [ 0.42857143, 0.5 , 2. , 1. , 0.5 ], [ 1.5 , 0. , 3. , 7. , inf]])View Code
np.mat([[1,2,3],[4,5,6]])
結果：
matrix([[1, 2, 3],
[4, 5, 6]])
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a
結果：
array([[3, 6, 5, 9, 3], [3, 3, 4, 6, 8], [3, 3, 2, 3, 4], [6, 0, 9, 7, 9]])View Code
np.mat(a)
結果：
matrix([[3, 6, 5, 9, 3], [3, 3, 4, 6, 8], [3, 3, 2, 3, 4], [6, 0, 9, 7, 9]])View Code
矩陣的運算
A = np.mat(a) B = np.mat(b) A B
結果：
matrix([[3, 6, 5, 9, 3], [3, 3, 4, 6, 8], [3, 3, 2, 3, 4], [6, 0, 9, 7, 9]]) matrix([[1, 5, 6, 0, 6], [0, 2, 1, 7, 9], [7, 6, 1, 3, 8], [4, 4, 3, 1, 0]])View Code
A + B A - B
結果：
matrix([[ 4, 11, 11, 9, 9], [ 3, 5, 5, 13, 17], [10, 9, 3, 6, 12], [10, 4, 12, 8, 9]]) matrix([[ 2, 1, -1, 9, -3], [ 3, 1, 3, -1, -1], [-4, -3, 1, 0, -4], [ 2, -4, 6, 6, 9]])View Code
A * B
結果： ValueError: shapes (4,5) and (4,5) not aligned: 5 (dim 1) != 4 (dim 0)
a = np.mat(np.random.randint(10, size=20).reshape(4, 5)) b = np.mat(np.random.randint(10, size=20).reshape(5, 4)) a b a * b
結果：
matrix([[4, 4, 3, 2, 7], [4, 7, 2, 4, 5], [8, 6, 6, 1, 0], [5, 9, 6, 2, 8]]) matrix([[5, 8, 9, 2], [8, 4, 3, 7], [4, 6, 7, 0], [5, 8, 5, 3], [0, 6, 9, 5]]) matrix([[ 74, 124, 142, 77], [104, 134, 136, 94], [117, 132, 137, 61], [131, 176, 196, 119]])View Code
Array常用函數
a = np.random.randint(10, size=20).reshape(4, 5) np.unique(a)#array([0, 1, 2, 3, 4, 5, 6, 8, 9]) a
結果：
array([[4, 1, 2, 5, 3], [9, 8, 1, 4, 0], [5, 4, 8, 0, 2], [8, 6, 2, 4, 3]])View Code
sum(a)#array([26, 19, 13, 13, 8]) sum(a[0])#15 sum(a[:,0])#26 a.max()#9 max(a[0])#5 max(a[:,0])#9
Array的input和output
使用pickle序列化numpy array
import pickle import numpy as np x = np.arange(10)#array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) f = open(‘x.pkl‘, ‘wb‘) pickle.dump(x, f)
f = open(‘x.pkl‘, ‘rb‘) pickle.load(f)#array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
np.save(‘one_array‘, x)
np.load(‘one_array.npy‘)#array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
y = np.arange(20)#array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19]) np.savez(‘two_array.npz‘, a=x, b=y)
c = np.load(‘two_array.npz‘) c[‘a‘]#array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) c[‘b‘]#array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19])
一、numpy入門