fn main() {
let arr: [u8;8] = [97, 112, 112, 108, 101];
println!("Len is {}",arr.len());
println!("Elements are {:?}",arr);
}
error[E0308]: mismatched types
--> src/main.rs:2:23
|
2 | let arr: [u8;8] = [97, 112, 112, 108, 101];
| ------ ^^^^^^^^^^^^^^^^^^^^^^^^ expected an array with a fixed size of 8 elements, found one with 5 elements
| |
| expected due to this
Is there any way to pad the remaining elements with 0's? Something like:
let arr: [u8;8] = [97, 112, 112, 108, 101].something();
You can use numpy. pad , which pads default 0 to both ends of the array while in constant mode, specify the pad_width = (0, N) will pad N zeros to the right and nothing to the left: N = 4 np.
pad() function is used to pad the Numpy arrays. Sometimes there is a need to perform padding in Numpy arrays, then numPy. pad() function is used. The function returns the padded array of rank equal to the given array and the shape will increase according to pad_width.
You can use the zeros function to create a NumPy array with all zeros. You can use the NumPy arange function to create NumPy arrays as sequences of regularly spaced values. All of those methodologies enable you to create a new NumPy array. But often times, you'll have an existing array and you need to add new elements.
The array padding transformation sets a dimension in an array to a new size. The goal of this transformation is to reduce the number of memory system conflicts. The transformation is applied to a full function AST. The new size can be specified by the user or can be computed automatically.
In this article, we show how to pad an array with zeros or ones in Python using numpy. Say, you want to fill an array with all zeros or all ones. Numpy has built-in functions that allows us to do this in Python. We can create one-dimensional, two-dimensional, three-dimensional arrays, etc. padded with zeros or ones.
So, first, we must import numpy as np. We then create a variable named array1 and set it equal to np.zeros (4) What this line of code does is it creates a one-dimensional array with 4 zeros. We then output the contents of array1, which you can see is an array with 4 zeros. We then create an array called array2 padded with 4 ones.
So the np.zeros () function creates an array padded with zeros. And the np.ones () function creates an array padded with ones. So above we showed how to create a one-dimensional array padded with zeros or ones. Now we will show how to create a 2-dimensional array padded with zeros or ones.
Say, you want to fill an array with all zeros or all ones. Numpy has built-in functions that allows us to do this in Python. We can create one-dimensional, two-dimensional, three-dimensional arrays, etc. padded with zeros or ones.
In addition to the other answers, you can use const generics to write a dedicated method.
fn pad_zeroes<const A: usize, const B: usize>(arr: [u8; A]) -> [u8; B] {
assert!(B >= A); //just for a nicer error message, adding #[track_caller] to the function may also be desirable
let mut b = [0; B];
b[..A].copy_from_slice(&arr);
b
}
Playground
You can use concat_arrays macro for it:
use concat_arrays::concat_arrays;
fn main() {
let arr: [u8; 8] = concat_arrays!([97, 112, 112, 108, 101], [0; 3]);
println!("{:?}", arr);
}
I don't think it's possible to do without external dependencies.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With