## Issue

I am looking for some function that takes an input array of numbers and adds steps (range) between these numbers. I need to specify the length of the output’s array.

**Example:**

```
input_array = [1, 2, 5, 4]
output_array = do_something(input_array, output_length=10)
```

**Result:**

```
output_array => [1, 1.3, 1.6, 2, 3, 4, 5, 4.6, 4.3, 4]
len(output_array) => 10
```

Is there something like that, in Numpy for example?

I have a prototype of this function that uses dividing input array into pairs (`[0,2]`

, `[2,5]`

, `[5,8]`

) and filling "spaces" between with `np.linspace()`

but it don’t work well: https://onecompiler.com/python/3xwcy3y7d

```
def do_something(input_array, output_length):
import math
import numpy as np
output = []
in_between_steps = math.ceil(output_length/len(input_array))
prev_num = None
for num in input_array:
if prev_num is not None:
for in_num in np.linspace(start=prev_num, stop=num, num=in_between_steps, endpoint=False):
output.append(in_num)
prev_num = num
output.append(input_array[len(input_array)-1]) # manually add last item
return output
```

**How it works:**

```
input_array = [1, 2, 5, 4]
print(len(do_something(input_array, output_length=10))) # result: 10 OK
print(len(do_something(input_array, output_length=20))) # result: 16 NOT OK
print(len(do_something(input_array, output_length=200))) # result: 151 NOT OK
```

I have an array `[1, 2, 5, 4]`

and I need to "expand" a number of items in it but preserve the "shape":

## Solution

There is `numpy.interp`

which might be what you are looking for.

```
import numpy as np
points = np.arange(4)
values = np.array([1,2,5,4])
x = np.linspace(0, 3, num=10)
np.interp(x, points, values)
```

output:

```
array([1. , 1.33333333, 1.66666667, 2. , 3. ,
4. , 5. , 4.66666667, 4.33333333, 4. ])
```

Answered By – Kevin

Answer Checked By – Willingham (BugsFixing Volunteer)