CODEWITHSUNDEEP
pythonnumpy
klapeyron
klapeyron

Reputation: 522

python numpy add 1 element to empty matrix

I have initialized matrix:

M = np.array(((),()))

M has the shape of (2,0) now. I wish to fill M by steps: firstly to add 1 number like

M[0] = np.append(M[0],55)

By this operation I want to get such a matrix

((55),())

How can I do this? I can make this with standard pythons arrays [] by "append" operation like

arr = [[],[]]
arr[0].append(55)

But after that, I need this array to be a numpy array and there is one extra type transform operation which I wish to avoid.

Upvotes: 0

Views: 847

Answers (2)

hpaulj
hpaulj

Reputation: 231335

I can start with a 2 element object dtype array:

In [351]: M = np.array((None,None))
In [352]: M.shape
Out[352]: (2,)
In [353]: M
Out[353]: array([None, None], dtype=object)
In [354]: M[0]=(5,)
In [355]: M[1]=()
In [356]: M
Out[356]: array([(5,), ()], dtype=object)
In [357]: print(M)
[(5,) ()]

Or more directly (from a list of tuples) (beware, sometimes this produces a error rather than object array).

In [362]: np.array([(55,),()])
Out[362]: array([(55,), ()], dtype=object)

But I don't see what it's good for. It would easier to construct a list of tuples:

In [359]: [(5,), ()]
Out[359]: [(5,), ()]

Do not try to use np.append like the list append. It is just a clumsy front end to np.concatenate.

M as you create it is:

In [360]: M = np.array(((),()))
In [361]: M
Out[361]: array([], shape=(2, 0), dtype=float64)

It can't hold any elements. And you can't change the shape of the slots as you can with a list. In numpy shape and dtype are significant.

You can specify object dtype:

In [367]: M = np.array([(),()], object)
In [368]: M
Out[368]: array([], shape=(2, 0), dtype=object)

but it's still impossible to reference and change one of those 0 elements.

Upvotes: 1

Jonathan R
Jonathan R

Reputation: 3928

The array you've written is no matrix because its axis has different dimensions. You could do it like this

  import numpy as np
  x = np.zeros((2,1))
  x[0][0] = 55

Then if you want to append to it you can do something like:

x = np.append(x, [[42], [0]], axis=1)

Note that in order to append to a martrix all the dimensions except for the concatenation axis must match exactly

Upvotes: 1

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