Python | numpy

Numpy: Scientific computing with Python

• a powerful N-dimensional array object
• sophisticated (broadcasting) functions
• tools for integrating C/C++ and Fortran code
• useful linear algebra,Fourier transform,and random number capabilities

Structure^1

Useful funcions^2

• Array Creation: arange,array,copy,empty,empty_like,eye,fromfile,fromfunction,identity,linspace,logspace,mgrid,ogrid,ones,ones_like,r,zeros,zeros_like
• Conversions: ndarray.astype,atleast_1d,atleast_2d,atleast_3d,mat
• Manipulations: array_split,column_stack,concatenate,diagonal,dsplit,dstack,hsplit,hstack,ndarray.item,newaxis,ravel,repeat,reshape,resize,squeeze,swapaxes,take,transpose,vsplit,vstack
• Questions: all,any,nonzero,where
• Ordering: argmax,argmin,argsort,max,min,ptp,searchsorted,sort
• Operations: choose,compress,cumprod,cumsum,inner,ndarray.fill,imag,prod,put,putmask,real,sum
• Basic Statistics: cov,mean,std,var
• Basic Linear Algebra: cross,dot,outer,linalg.svd,vdot

Ordering

argmax^3

返回最大数的索引，参数axis默认0表示维度数。

• 二维

  import numpy as np
  a=np.array([[1,5,5,2],
              [9,6,2,8],
              [3,7,9,1]])
  print(np.argmax(a,axis=0)) #[1,2,2,1]
  print(np.argmax(a,axis=1)) #[1,0,2]

  axis=0意为，返回的是每一列的最大索引(a[0][j],a[1][j]…)即逐行比较。

• 三维

  import numpy as np
      a = np.array([
                    [
                        [ 1, 5, 5, 2],
                        [ 9,-6, 2, 8],
                        [-3, 7,-9, 1]
                    ],
                    [
                        [-1, 5,-5, 2],
                        [ 9, 6, 2, 8],
                        [ 3, 7, 9, 1]
                    ]
                  ])
      print(np.argmax(a, axis=0))
      #[[0 0 0 0]
      #[0 1 0 0]
      #[1 0 1 0]]
      print(np.argmax(a, axis=1))
      #[[1 2 0 1]
      # [1 2 2 1]]

  应当明确对应轴在数组中的表现。三维时，axis=0，逐片比较；axis=1，逐行比较。