GuoXin Li's Blog

Numpy generate array

Numpy
字数统计: 444阅读时长: 2 min
2018/09/14 Share

Create array

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a = np.array([[1,2,3,4],[5,6,7,8]])
print(a)
'''array([[1, 2, 3, 4],
       [5, 6, 7, 8]])
'''
  • ndarray.ndim: show the dimensionality of array
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a.ndim
# 2
  • ndarray.shape: show the length of array in every direction
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a.shape
# (2,4)
  • ndarray.size: show the size of array(the value = the product of every item in shape)
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a.size
# 8
  • ndarray.dtype: assign the data type
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a.dtype
# dtype('int64')

  • ndarray.itemsize: calculate the size of every item in the memory. e.g. a float64 type of data occupies 8 bit in computer memory.

  • ndarray.data: show the address of this array in memory.

Create array with assigned data

  • int
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a = np.array([1,2,3,4],dtype = np.int)    #(int8,int16,int64......)
print(a)
#int 64 (defult )
  • float
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a = np.array([1,2,3,4],dtype = np.float)#(float32......)
print(a)
#float 64(defult)

Create the specific array

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a = np.array([1,2,3,4],[5,6,7,8])
print(a)
'''
[[1,2,3,4]
[5,6,7,8]]
'''

Create the zero array

  • all zero
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a = np.zeros((3,4)) #3 row 4 line
print(a)
'''
array([[0., 0., 0., 0.],
       [0., 0., 0., 0.],
       [0., 0., 0., 0.]])
'''
  • create array and assign data type
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a = np.ones((3,4),dtype = np.int)
'''
array([[1, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1]])
'''
  • create all empty array(every value is close to zero)
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a = np.empty((3,4))    #the value is close to zero, 3 row 4 line
'''
array([[0., 0., 0., 0.],
       [0., 0., 0., 0.],
       [0., 0., 0., 0.]])
'''

The “arange() “ function

arange() has three parameter, arange( , , * )

  • first
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np.arange(6)
# array([0,1,2,3,4,5])
  • second
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np.arange(0,6)    #the former is the initial value, the latter is the end value
# array([0,1,2,3,4,5,])
  • third
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np.arange(1,3,0.5)# the third parameter is the interval value.
#array([0. , 0.5, 1. , 1.5, 2. , 2.5])

The “linspace()“ function

linspace() can generate an well-proportion array in assigned interval range.

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np.linspace(0,10,20)
'''
array([ 0.        ,  0.52631579,  1.05263158,  1.57894737,  2.10526316,
        2.63157895,  3.15789474,  3.68421053,  4.21052632,  4.73684211,
        5.26315789,  5.78947368,  6.31578947,  6.84210526,  7.36842105,
        7.89473684,  8.42105263,  8.94736842,  9.47368421, 10.        ])

'''

rand() function generate array in range of [ 0,1 )

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np.random.rand(2,3,3)
'''
array([[[0.98995132, 0.51327869, 0.35285681],
        [0.64515764, 0.17032915, 0.17255685],
        [0.51559337, 0.98184312, 0.32625729]],

       [[0.5182059 , 0.09902392, 0.96491655],
        [0.18805998, 0.74772964, 0.91896079],
        [0.39425633, 0.84583609, 0.77468997]]])

'''
CATALOG
  1. 1. Create array
  2. 2. Create array with assigned data
  3. 3. Create the specific array
  4. 4. Create the zero array
  5. 5. The “arange() “ function
  6. 6. The “linspace()“ function
  7. 7. rand() function generate array in range of [ 0,1 )
Total : 89
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