NumPy - Insert an array of zeros after specified indices

up vote
5
down vote

favorite

My code is:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),np.zeros(3))

The output I want is:

[1,0,0,0,2,0,0,0,3,0,0,0,4,0,0,0,5]

The error I get is:

ValueError: shape mismatch: value array of shape (3,) could not be
broadcast to indexing result of shape (4,)

When I do:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),0)

The out is:

array([1., 0., 2., 0., 3., 0., 4., 0., 5.])

Why it doesn't work when I try to insert an array?

P.S. I I cannot use loops

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

add a comment |

up vote
5
down vote

favorite

My code is:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),np.zeros(3))

The output I want is:

[1,0,0,0,2,0,0,0,3,0,0,0,4,0,0,0,5]

The error I get is:

ValueError: shape mismatch: value array of shape (3,) could not be
broadcast to indexing result of shape (4,)

When I do:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),0)

The out is:

array([1., 0., 2., 0., 3., 0., 4., 0., 5.])

Why it doesn't work when I try to insert an array?

P.S. I I cannot use loops

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

add a comment |

up vote
5
down vote

favorite

My code is:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),np.zeros(3))

The output I want is:

[1,0,0,0,2,0,0,0,3,0,0,0,4,0,0,0,5]

The error I get is:

ValueError: shape mismatch: value array of shape (3,) could not be
broadcast to indexing result of shape (4,)

When I do:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),0)

The out is:

array([1., 0., 2., 0., 3., 0., 4., 0., 5.])

Why it doesn't work when I try to insert an array?

P.S. I I cannot use loops

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

My code is:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),np.zeros(3))

The output I want is:

[1,0,0,0,2,0,0,0,3,0,0,0,4,0,0,0,5]

The error I get is:

ValueError: shape mismatch: value array of shape (3,) could not be
broadcast to indexing result of shape (4,)

When I do:

x=np.linspace(1,5,5)

a=np.insert(x,np.arange(1,5,1),0)

The out is:

array([1., 0., 2., 0., 3., 0., 4., 0., 5.])

Why it doesn't work when I try to insert an array?

P.S. I I cannot use loops

python arrays numpy

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

edited Nov 8 at 13:50

jpp

80.2k184695

edited Nov 8 at 13:50

jpp

80.2k184695

edited Nov 8 at 13:50

jpp

80.2k184695

asked Nov 8 at 13:01

Danjmp

283

New contributor

asked Nov 8 at 13:01

Danjmp

283

asked Nov 8 at 13:01

Danjmp

283

New contributor

Danjmp is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

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2 Answers
2

active

oldest

votes

up vote
2
down vote

accepted

Another option:

np.hstack((x[:,None], np.zeros((5,3)))).flatten()[:-3]

gives:

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

That is, pretend x is a column vector and stack a 5x3 block of zeros to the right of it and then flatten.

answered Nov 8 at 13:19

xnx

15k43670

add a comment |

up vote
3
down vote

You can use np.repeat to feed repeated indices. For a 1d array, thhe obj argument for np.insert reference individual indices.

x = np.linspace(1, 5, 5)

a = np.insert(x, np.repeat(np.arange(1, 5, 1), 3), 0)

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

up vote
2
down vote

accepted

Another option:

np.hstack((x[:,None], np.zeros((5,3)))).flatten()[:-3]

gives:

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

That is, pretend x is a column vector and stack a 5x3 block of zeros to the right of it and then flatten.

answered Nov 8 at 13:19

xnx

15k43670

add a comment |

up vote
2
down vote

accepted

Another option:

np.hstack((x[:,None], np.zeros((5,3)))).flatten()[:-3]

gives:

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

That is, pretend x is a column vector and stack a 5x3 block of zeros to the right of it and then flatten.

answered Nov 8 at 13:19

xnx

15k43670

add a comment |

up vote
2
down vote

accepted

Another option:

np.hstack((x[:,None], np.zeros((5,3)))).flatten()[:-3]

gives:

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

That is, pretend x is a column vector and stack a 5x3 block of zeros to the right of it and then flatten.

answered Nov 8 at 13:19

xnx

15k43670

Another option:

np.hstack((x[:,None], np.zeros((5,3)))).flatten()[:-3]

gives:

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

That is, pretend x is a column vector and stack a 5x3 block of zeros to the right of it and then flatten.

answered Nov 8 at 13:19

xnx

15k43670

answered Nov 8 at 13:19

xnx

15k43670

answered Nov 8 at 13:19

xnx

15k43670

answered Nov 8 at 13:19

xnx

15k43670

add a comment |

up vote
3
down vote

You can use np.repeat to feed repeated indices. For a 1d array, thhe obj argument for np.insert reference individual indices.

x = np.linspace(1, 5, 5)

a = np.insert(x, np.repeat(np.arange(1, 5, 1), 3), 0)

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

add a comment |

up vote
3
down vote

You can use np.repeat to feed repeated indices. For a 1d array, thhe obj argument for np.insert reference individual indices.

x = np.linspace(1, 5, 5)

a = np.insert(x, np.repeat(np.arange(1, 5, 1), 3), 0)

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

add a comment |

up vote
3
down vote

You can use np.repeat to feed repeated indices. For a 1d array, thhe obj argument for np.insert reference individual indices.

x = np.linspace(1, 5, 5)

a = np.insert(x, np.repeat(np.arange(1, 5, 1), 3), 0)

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

You can use np.repeat to feed repeated indices. For a 1d array, thhe obj argument for np.insert reference individual indices.

x = np.linspace(1, 5, 5)

a = np.insert(x, np.repeat(np.arange(1, 5, 1), 3), 0)

array([ 1., 0., 0., 0., 2., 0., 0., 0., 3., 0., 0., 0., 4.,
 0., 0., 0., 5.])

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

edited Nov 8 at 14:25

answered Nov 8 at 13:16

jpp

80.2k184695

answered Nov 8 at 13:16

jpp

80.2k184695

answered Nov 8 at 13:16

jpp

80.2k184695

add a comment |

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