numpy.append() programmā Python
The numpy.append() pievieno vērtības gar minēto asi masīva beigās Sintakse:
numpy.append(array, values, axis = None)
Parametri:
array : [array_like]Input array. values : [array_like]values to be added in the arr. Values should be shaped so that arr[...,obj,...] = values. If the axis is defined values can be of any shape as it will be flattened before use. axis : Axis along which we want to insert the values. By default, array is flattened.
Atgriešanās:
An copy of array with values being appended at the end as per the mentioned object along a given axis.
Kods 1: masīvu pievienošana
Python
# Python Program illustrating> # numpy.append()> > import> numpy as geek> > #Working on 1D> arr1> => geek.arange(> 5> )> print> (> '1D arr1 : '> , arr1)> print> (> 'Shape : '> , arr1.shape)> > > arr2> => geek.arange(> 8> ,> 12> )> print> (> '
1D arr2 : '> , arr2)> print> (> 'Shape : '> , arr2.shape)> > > # appending the arrays> arr3> => geek.append(arr1, arr2)> print> (> '
Appended arr3 : '> , arr3)> |
Izvade:
1D arr1 : [0 1 2 3 4] Shape : (5,) 1D arr2 : [ 8 9 10 11] Shape : (4,) Appended arr3 : [ 0 1 2 3 4 8 9 10 11]
The laika sarežģītība no numpy.append() funkcijas ir O(n), kur n ir pievienojamo elementu skaits. Tas nozīmē, ka laiks, kas nepieciešams elementu pievienošanai, palielinās lineāri līdz ar pievienojamo elementu skaitu.
The telpas sarežģītība no numpy.append() funkcijas ir arī O(n), kur n ir pievienojamo elementu skaits. Tas nozīmē, ka elementu pievienošanai nepieciešamās vietas apjoms lineāri palielinās līdz ar pievienojamo elementu skaitu.
Kods 2 : spēlēšanās ar asi
Python
# Python Program illustrating> # numpy.append()> > import> numpy as geek> > #Working on 1D> arr1> => geek.arange(> 8> ).reshape(> 2> ,> 4> )> print> (> '2D arr1 :
'> , arr1)> print> (> 'Shape : '> , arr1.shape)> > > arr2> => geek.arange(> 8> ,> 16> ).reshape(> 2> ,> 4> )> print> (> '
2D arr2 :
'> , arr2)> print> (> 'Shape : '> , arr2.shape)> > > # appending the arrays> arr3> => geek.append(arr1, arr2)> print> (> '
Appended arr3 by flattened : '> , arr3)> > # appending the arrays with axis = 0> arr3> => geek.append(arr1, arr2, axis> => 0> )> print> (> '
Appended arr3 with axis 0 :
'> , arr3)> > # appending the arrays with axis = 1> arr3> => geek.append(arr1, arr2, axis> => 1> )> print> (> '
Appended arr3 with axis 1 :
'> , arr3)> |
Izvade:
2D arr1 : [[0 1 2 3] [4 5 6 7]] Shape : (2, 4) 2D arr2 : [[ 8 9 10 11] [12 13 14 15]] Shape : (2, 4) Appended arr3 by flattened : [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] Appended arr3 with axis 0 : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Appended arr3 with axis 1 : [[ 0 1 2 3 8 9 10 11] [ 4 5 6 7 12 13 14 15]]
