8 releases (4 breaking)
0.5.0 | Oct 20, 2024 |
---|---|
0.4.1 | Jan 20, 2024 |
0.4.0 | Apr 22, 2023 |
0.3.1 | Jun 26, 2021 |
0.1.0 | Apr 4, 2019 |
#270 in Parser implementations
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Used in 4 crates
63KB
1.5K
SLoC
Matfile
Matfile is a library for reading (and in the future writing) Matlab ".mat" files.
Please note: This library is still alpha quality software and only implements a subset of the features supported by .mat files.
Feature Status
Matfile currently allows you to load numeric arrays from .mat files (all floating point and integer types, including complex numbers). All other types are currently ignored.
- Loading .mat files
- Numeric arrays
- Cell arrays
- Structure arrays
- Object arrays
- Character arrays
- Sparse arrays
- Writing .mat files
Examples
Loading a .mat file from disk and accessing one of its arrays by name:
let file = std::fs::File::open("data.mat")?;
let mat_file = matfile::MatFile::parse(file)?;
let pos = mat_file.find_by_name("pos");
println!("{:#?}", pos);
Might output something like:
Some(
Array {
name: "pos",
size: [
2,
3
],
data: Double {
real: [
-5.0,
8.0,
6.0,
9.0,
7.0,
10.0
],
imag: None
}
}
)
Note that data is stored in column-major format. For higher dimensions that means that the first dimension has the fastest varying index.
ndarray
support
Helpers for converting between matfile::Array
and ndarray::Array
can be enabled with the ndarray
feature:
[dependencies]
matfile = { version = "0.5", features = ["ndarray"] }
While matfile
arrays abstract over the underlying data type, ndarray
arrays are parameterized by a concrete data type. Thus the conversions
provided are fallible in case the data types are not compatible.
Examples
First, bring the TryInto
trait into scope:
use std::convert::TryInto;
Dynamically dimensioned arrays
Converting a matfile
array mf_arr
to a dynamic dimension ndarray
array
nd_arr
:
let nd_arr: ndarray::ArrayD<f64> = mf_arr.try_into()?;
Statically dimensioned arrays
Converting a matfile
array mf_arr
to a static dimension ndarray
array
nd_arr
:
let nd_arr: ndarray::Array2<num_complex::Complex<f32>> = mf_arr.try_into()?;
Dependencies
~3.5–4.5MB
~78K SLoC