I want to create a dynamic array without size specification. In that array, I need to insert elements at any point I require. The remaining values in them can be either null or undefined till it gets a value assigned to it.
Ex:
a = np.array([])
np.insert(a, any index value, value)
So, if I use np.insert(a, 5, 1) I should get the result as:
array([null, null, null, null, null, 1])
In MATLAB/Octave you can create and extend a matrix with indexing:
>> a = []
a = [](0x0)
>> a(5) = 1
a =
0 0 0 0 1
That is if you index a slot beyond the current end, it expands the matrix, and fills it with 0s.
Javascript (in a Nodejs session) does something similar
> var a = [1,2];
undefined
> a
[ 1, 2 ]
> a[6] = 1
1
> a
[ 1, 2, , , , , 1 ]
> a[3]
undefined
Leaving the intermediate slots undefined.
A Python dictionary can grow simply by indexing
In [113]: a = {0:1, 1:2}
In [114]: a[5]=1
In [115]: a
Out[115]: {0: 1, 1: 2, 5: 1}
In [116]: a[3]
...
KeyError: 3
In [117]: a.get(3,None)
Dictionaries also implement a setdefault, and a defaultdict.
A Python list grows by append and extend
In [120]: a = [1,2]
In [121]: a.append(3)
In [122]: a
Out[122]: [1, 2, 3]
In [123]: a.extend([0,0,0,1])
In [124]: a
Out[124]: [1, 2, 3, 0, 0, 0, 1]
Lists also change size with del and sliced assignment, e.g. a[1:2] = [0,0,0,2].
A numpy array is fixed in size. To grow one, you have to make a new array by concatenation
In [125]: a = np.arange(3)
In [126]: a
Out[126]: array([0, 1, 2])
In [127]: a = np.concatenate((a, [0,0,1]))
In [128]: a
Out[128]: array([0, 1, 2, 0, 0, 1])
Array functions like append, stack, delete and insert use some form of concatenate or allocate-n-fill.
In restricted cases an array can be resized (but this method is not used very often):
In [161]: a.resize(10)
In [162]: a[-1]=10
In [163]: a
Out[163]: array([ 0, 1, 2, 0, 0, 1, 0, 0, 0, 10])
Check out this package.
from numpy_da import DynamicArray
data = DynamicArray(shape=2, index_expansion=True)
data[5] = 1
print(data) # [0, 0, 0, 0, 0, 1]
index_expansion option allows the array to grow if you index beyond the current largest index.
Noneand implement insert in required fashion. You can extend the array by doubling it if the user is accessing the index outside the limit of your data structure. refer this.insertI doubt it to be valid (in other words, I don't think insert will add nulls automatically). My advice is for you to make your own implementation storing a numpy array (and using its methods to obtain your required behavior).