fitsio

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• CHANGELOG

lib.rs:

fitsio - a thin wrapper around the [cfitsio][cfitsio] C library.

• File access
• Pretty printing
• HDU access
• Creating new HDUs
• Creating a new image
• Creating a new table
• Column descriptions
• Copying HDUs to another file
• Deleting a HDU
• Iterating over the HDUs in a file
• General calling behaviour
• Header keys
• Reading file data
• Reading images
• ndarray support
• Reading tables
• Reading cell values
• Reading rows
• Iterating over columns
• Writing file data
• Writing images
• Resizing an image
• Writing tables
• Writing table data
• Inserting columns
• Deleting columns
• Raw fits file access
• Threadsafe access

This library wraps the low level cfitsio bindings: [fitsio-sys][fitsio-sys] and provides a more native experience for rust users.

The main interface to a fits file is [FitsFile][fits-file]. All file manipulation and reading starts with this class.

File access

To open an existing file, use the [open][fitsfile-open] method.

use fitsio::FitsFile;

// let filename = ...;
let fptr = FitsFile::open(filename)?;

Alternatively a new file can be created on disk with the companion method [create][fits-file-create]:

use fitsio::FitsFile;

// let filename = ...;
let fptr = FitsFile::create(filename).open()?;

The [create][fits-file-create] method returns a [NewFitsFile][new-fits-file], which is an internal representation of a temporary fits file on disk, before the file is fully created.

This representation has two methods: [open][new-fits-file-open] and [with_custom_primary][new-fits-file-with-custom-primary]. The [open][new-fits-file-open] method actually creates the file on disk, but before calling this method, the [with_custom_primary][new-fits-file-with-custom-primary] method can be used to add a custom primary HDU. This is mostly useful for images. Otherwise, a default primary HDU is created. An example of not adding a custom primary HDU is shown above. Below we see an example of [with_custom_primary][new-fits-file-with-custom-primary]:

use fitsio::FitsFile;
use fitsio::images::{ImageType, ImageDescription};

// let filename = ...;
let description = ImageDescription {
data_type: ImageType::Double,
dimensions: &[52, 103],
};

let fptr = FitsFile::create(filename)
.with_custom_primary(&description)
.open()?;

From this point, the current HDU can be queried and changed, or fits header cards can be read or file contents can be read.

To open a fits file in read/write mode (to allow changes to the file), the [edit][fits-file-edit] must be used. This opens a file which already exists on disk for editing.

use fitsio::FitsFile;

// let filename = ...;
let fptr = FitsFile::edit(filename)?;

Pretty printing

Fits files can be pretty-printed with [pretty_print][pretty-print], or its more powerful cousin [pretty_write][pretty-write].

use fitsio::FitsFile;

let mut fptr = FitsFile::open(filename)?;
fptr.pretty_print()?;
// or
fptr.pretty_write(&mut io::stdout())?;

In the continuing tradition of releasing fits summary programs with each fits library, this create contains a binary program fitssummary which can be installed with cargo install. This takes fits files on the command line and prints their summaries to stdout.

$ fitssummary ../testdata/full_example.fits

file: ../testdata/full_example.fits
mode: READONLY
extnum hdutype      hduname    details
0      IMAGE_HDU               dimensions: [100, 100], type: Long
1      BINARY_TBL   TESTEXT    num_cols: 4, num_rows: 50

HDU access

HDU information belongs to the [FitsHdu][fits-hdu] object. HDUs can be fetched by String/str or integer (0-indexed), with the [hdu][fitsfile-hdu] method. The HduInfo object contains information about the current HDU:

#
use fitsio::hdu::HduInfo;

let hdu = fptr.hdu(0)?;
// image HDU
if let HduInfo::ImageInfo { shape, .. } = hdu.info {
println!("Image is {}-dimensional", shape.len());
println!("Found image with shape {:?}", shape);
}

// tables
if let HduInfo::TableInfo { column_descriptions, num_rows, .. } = hdu.info {
println!("Table contains {} rows", num_rows);
println!("Table has {} columns", column_descriptions.len());
}

The primary HDU can always be accessed with the FitsFile::primary_hdu method.

Creating new HDUs

Creating a new image

New fits images are created with the [create_image][fits-file-create-image] method. This method requires the extension name, and an [ImageDescription][image-description] object, which defines the shape and type of the desired image:

use fitsio::images::{ImageDescription, ImageType};

let image_description = ImageDescription {
data_type: ImageType::Float,
dimensions: &[100, 100],
};
let hdu = fptr.create_image("EXTNAME".to_string(), &image_description)?;

Unlike cfitsio, the order of the dimensions of new_size follows the C convention, i.e. row-major order.

Creating a new table

Similar to creating new images, new tables are created with the [create_table][fits-file-create-table] method. This requires an extension name, and a slice of [ColumnDescription][column-description]s:

use fitsio::tables::{ColumnDescription, ColumnDataType};

let first_description = ColumnDescription::new("A")
.with_type(ColumnDataType::Int)
.create()?;
let second_description = ColumnDescription::new("B")
.with_type(ColumnDataType::Long)
.create()?;
let descriptions = [first_description, second_description];
let hdu = fptr.create_table("EXTNAME".to_string(), &descriptions)?;

Column descriptions

Columns are described with the [ColumnDescription][column-description] struct. This encapsulates: the name of the column, and the data format.

The fits specification allows scalar or vector columns, and the data format is described the [ColumnDataDescription][column-data-description] struct, which in turn encapsulates the number of elements per row element (typically 1), the width of the column (for strings), and the data type, which is one of the [ColumnDataType][column-data-type] members

For the common case of a scalar column, a ColumnDataDescription object can be constructed with the scalar method:

use fitsio::tables::{ColumnDescription, ColumnDataDescription, ColumnDataType};

let desc = ColumnDataDescription::scalar(ColumnDataType::Int);
assert_eq!(desc.repeat, 1);
assert_eq!(desc.width, 1);

Vector columns can be constructed with the vector method:

use fitsio::tables::{ColumnDataDescription, ColumnDescription, ColumnDataType};

let desc = ColumnDataDescription::vector(ColumnDataType::Int, 100);
assert_eq!(desc.repeat, 100);
assert_eq!(desc.width, 1);

These impl From<...> for String such that the traditional fits column description string can be obtained:

use fitsio::tables::{ColumnDataDescription, ColumnDescription, ColumnDataType};

let desc = ColumnDataDescription::scalar(ColumnDataType::Int);
assert_eq!(String::from(desc), "1J".to_string());

Copying HDUs to another file

A HDU can be copied to another open file with the [copy_to][fits-hdu-copy-to] method. This requires another open [FitsFile][fits-file] object to copy to:

#
#
hdu.copy_to(&mut src_fptr, &mut dest_fptr)?;

Deleting a HDU

The current HDU can be deleted using the [delete][fits-hdu-delete] method. Note: this method takes ownership of self, and as such the [FitsHdu][fits-hdu] object cannot be used after this is called.

// let fptr = FitsFile::open(...)?;
// let hdu = fptr.hdu(0)?;
hdu.delete(&mut fptr)?;
// Cannot use hdu after this

Iterating over the HDUs in a file

The [iter][fits-hdu-iter] method allows for iteration over the HDUs of a fits file.

for hdu in fptr.iter() {
// Do something with hdu
}

General calling behaviour

All subsequent data acess is performed through the [FitsHdu][fits-hdu] object. Most methods take the currently open [FitsFile][fits-file] as the first parameter.

Header keys

Header keys are read through the [read_key][fits-hdu-read-key] function, and is generic over types that implement the [ReadsKey][reads-key] trait:

let int_value: i64 = fptr.hdu(0)?.read_key(&mut fptr, "INTTEST")?;

// Alternatively
let int_value = fptr.hdu(0)?.read_key::<i64>(&mut fptr, "INTTEST")?;


// Or let the compiler infer the types (if possible)

HeaderValue also implements the [ReadsKey][reads-key] trait, and allows the reading of comments:

let int_value_with_comment: HeaderValue<i64> = fptr.hdu(0)?.read_key(&mut fptr, "INTTEST")?;
let HeaderValue { value, comment } = int_value_with_comment;

Header cards can be written through the method [write_key][fits-hdu-write-key]. It takes a key name and value, or a key name and value-comment tuple. See the [WritesKey][writes-key] trait for supported data types.

fptr.hdu(0)?.write_key(&mut fptr, "foo", 1i64)?;
assert_eq!(fptr.hdu(0)?.read_key::<i64>(&mut fptr, "foo")?, 1i64);

// with comments
fptr.hdu(0)?.write_key(&mut fptr, "bar", (1i64, "bar comment"))?;

let HeaderValue { value, comment } = fptr.hdu(0)?.read_key::<HeaderValue<i64>>(&mut fptr, "bar")?;
assert_eq!(value, 1i64);
assert_eq!(comment, Some("bar comment".to_string()));

Reading file data

Methods taking ranges are exclusive of the upper range value, reflecting the nature of Rust's range type.

Reading images

Image data can be read through either [read_section][fits-hdu-read-section] which reads contiguous pixels between a start index and end index, or [read_region][fits-hdu-read-region] which reads rectangular chunks from the image.

// Read the first 100 pixels
let first_row: Vec<i32> = hdu.read_section(&mut fptr, 0, 100)?;

// Read a square section of the image
let xcoord = 0..10;
let ycoord = 0..10;
let chunk: Vec<i32> = hdu.read_region(&mut fptr, &[&ycoord, &xcoord])?;

Unlike cfitsio, the order of the the section ranges follows the C convention, i.e. row-major order.

Some convenience methods are available for reading rows of the image. This is typically useful as it's an efficient access method:

let start_row = 0;
let num_rows = 10;
let first_few_rows: Vec<f32> = hdu.read_rows(&mut fptr, start_row, num_rows)?;

// 10 rows of 100 columns
assert_eq!(first_few_rows.len(), 1000);

The whole image can also be read into memory:

let image_data: Vec<f32> = hdu.read_image(&mut fptr, )?;

// 100 rows of 100 columns
assert_eq!(image_data.len(), 10_000);

[ndarray][ndarray] support

When fitsio is compiled with the array feature, images can be read into the [ndarray::ArrayD][arrayd] type:

use fitsio::FitsFile;
use ndarray::ArrayD;

let mut f = FitsFile::open("../testdata/full_example.fits").unwrap();
let hdu = f.primary_hdu().unwrap();

let data: ArrayD<u32> = hdu.read_image(&mut f).unwrap();
let dim = data.dim();
assert_eq!(dim[0], 100);
assert_eq!(dim[1], 100);
assert_eq!(data[[20, 5]], 152);
#

For more details, see the ndarray_compat documentation (only available if compiled with array feature).

Reading tables

Columns can be read using the [read_col][fits-hdu-read-col] function, which can convert data types on the fly. See the [ReadsCol][reads-col] trait for supported data types.

let integer_data: Vec<i32> = hdu.and_then(|hdu| hdu.read_col(&mut fptr, "intcol"))?;

Reading cell values

Individual cell values can be read from FITS tables:

let result: i64 = tbl_hdu.read_cell_value(&mut f, "intcol", 4)?;
assert_eq!(result, 16);

let result: String = tbl_hdu.read_cell_value(&mut f, "strcol", 4)?;
assert_eq!(result, "value4".to_string());

Reading rows

Single rows can be read from a fits table with the [row][fits-hdu-row] method. This requires use of the [fitsio-derive][fitsio-derive] crate.

use fitsio::tables::FitsRow;
use fitsio_derive::FitsRow;

#[derive(Default, FitsRow)]
struct Row {
#[fitsio(colname = "intcol")]
intfoo: i32,
#[fitsio(colname = "strcol")]
foobar: String,
}
#

// Pick the 4th row
let row: Row = hdu.row(&mut f, 4)?;
assert_eq!(row.intfoo, 16);
assert_eq!(row.foobar, "value4");

Iterating over columns

Iterate over the columns with [columns][fits-hdu-columns].

for column in hdu.columns(&mut fptr) {
// Do something with column
}

Writing file data

Methods taking ranges are exclusive of the upper range value, reflecting the nature of Rust's range type.

Writing images

Image data is written through three methods on the HDU object: [write_section][fits-hdu-write-section], [write_region][fits-hdu-write-region], and [write_image][fits-hdu-write-image].

[write_section][fits-hdu-write-section] requires a start index and end index and data to write. The data parameter needs to be a slice, meaning any contiguous memory storage method (e.g. Vec) can be passed.

#
let data_to_write: Vec<f64> = vec![1.0, 2.0, 3.0];
hdu.write_section(&mut fptr, 0, data_to_write.len(), &data_to_write)?;

[write_region][fits-hdu-write-region] takes a slice of ranges with which the data is to be written, and the data to write.

#
let data_to_write: Vec<f64> = vec![1.0, 2.0, 3.0, 4.0];
let ranges = [&(0..1), &(0..1)];
hdu.write_region(&mut fptr, &ranges, &data_to_write)?;

Unlike cfitsio, the order of the ranges follows the C convention, i.e. row-major order.

[write_image][fits-hdu-write-image] writes all of the data passed (if possible) into the image. If more data is passed than pixels in the image, the method returns with an error.

#
// Image is 3x1
assert!(hdu.write_image(&mut fptr, &[1.0, 2.0, 3.0]).is_ok());
assert!(hdu.write_image(&mut fptr, &[1.0, 2.0, 3.0, 4.0]).is_err());

Resizing an image

Images can be resized to a new shape using the [resize][fits-hdu-resize] method.

The method takes the open [FitsFile][fits-file], and an slice of usize values. Note: currently fitsio only supports slices with length 2, i.e. a 2D image. [resize][fits-hdu-resize] takes ownership self to force the user to fetch the HDU object again. This ensures the image changes are reflected in the hew HDU object.

use fitsio::hdu::HduInfo;

hdu.resize(&mut fptr, &[1024, 1024])?;

// Have to get the HDU again, to reflect the latest changes
let hdu = fptr.hdu(0)?;
match hdu.info {
HduInfo::ImageInfo { shape, .. } => {
assert_eq!(shape, [1024, 1024]);
}
_ => panic!("Unexpected hdu type"),
}

Unlike cfitsio, the order of the dimensions of new_size follows the C convention, i.e. row-major order.

Writing tables

Writing table data

Tablular data can either be written with [write_col][fits-hdu-write-col] or [write_col_range][fits-hdu-write-col-range].

[write_col][fits-hdu-write-col] writes an entire column's worth of data to the file. It does not check how many rows are in the file, but extends the table if the length of data is longer than the table length.

let data_to_write: Vec<i32> = vec![10101; 5];
hdu.write_col(&mut fptr, "bar", &data_to_write)?;
let data: Vec<i32> = hdu.read_col(&mut fptr, "bar")?;
assert_eq!(data, vec![10101, 10101, 10101, 10101, 10101]);

[write_col_range][fits-hdu-write-col-range] writes data to a range of rows in a table. The range is inclusive of both the upper and lower bounds, so 0..4 writes 5 elements.

let data_to_write: Vec<i32> = vec![10101; 10];
hdu.write_col_range(&mut fptr, "bar", &data_to_write, &(0..5))?;
let data: Vec<i32> = hdu.read_col(&mut fptr, "bar")?;
assert_eq!(data, vec![10101, 10101, 10101, 10101, 10101]);

Inserting columns

Two methods on the HDU object allow for adding new columns: [append_column][fits-hdu-append-column] and [insert_column][fits-hdu-insert-column]. [append_column][fits-hdu-append-column] adds a new column as the last column member, and is generally preferred as it does not require shifting of data within the file.

use fitsio::tables::{ColumnDescription, ColumnDataType};

let column_description = ColumnDescription::new("abcdefg")
.with_type(ColumnDataType::Int)
.create()?;
hdu.append_column(&mut fptr, &column_description)?;

Deleting columns

The HDU object has the method [delete_column][fits-hdu-delete-column] which removes a column. The column can either be accessed by integer or name

let newhdu = hdu.delete_column(&mut fptr, "bar")?;
// or
let newhdu = hdu.delete_column(&mut fptr, 0)?;

Raw fits file access

Converting a FitsFile to a raw fitsio_sys::fitsfile pointer

If this library does not support the particular use case that is needed, the raw fitsfile pointer can be accessed:

use fitsio::FitsFile;

let mut fptr = FitsFile::open(filename)?;

/* Find out the number of HDUs in the file