astroimsim_data/
psf.rs

1use std::iter::Flatten;
2use std::path::PathBuf;
3use std::slice::Iter;
4use serde::{Deserialize, Serialize};
5use uvex_fitrs::{Fits, FitsData, FitsDataArray, Hdu, HeaderValue};
6use astroimsim_geometry::coordinate_system::{CoordinateSystem, Coordinates};
7use astroimsim_geometry::grid2d::GRID2D;
8use astroimsim_geometry::points::Point;
9use astroimsim_geometry::grid2d::InterpolationData;
10use ndarray::Array2;
11use ndarray_conv::{get_fft_processor, ConvExt, ConvFFTExt, ConvMode, PaddingMode};
12use std::time::{Duration, Instant};
13
14use convolutions_rs::convolutions::*;
15use ndarray::*;
16use convolutions_rs::Padding;
17use convolve2d::{convolve2d, DynamicMatrix, Matrix};
18
19#[derive(Debug,Clone,Serialize)]
20pub struct PSF {
21    pub path: PathBuf,
22    pub data: Vec<Vec<f64>>,
23    pub x_pixels: usize,
24    pub y_pixels: usize,
25    pub center: Point,
26    pub size: (f64,f64),
27}
28
29pub struct DataFile {
30    pub description: String,
31    pub path: PathBuf,
32    pub x_pixels: usize,
33    pub y_pixels: usize,
34}
35
36
37pub enum Load{
38    FromKey(String),
39    FromValue(f64)
40}
41
42
43pub enum FITSType{
44    thirtytwo,
45    sixtyfour,
46}
47
48impl PSF {
49    pub fn load_file(file: PathBuf, center:(Load, Load), size:(Load, Load), x_num:usize, y_num:usize) -> PSF {
50        println!("Loading {:?} into a DataFrame ",file);
51        let fits = Fits::open(file.clone()).expect("Failed to open FITS file");
52        let primary_hdu= fits.iter().next().expect("Couldn't find primary HDU");
53        let (mut data,shape) = match primary_hdu.read_data() {
54            FitsData::FloatingPoint32(FitsDataArray { shape, data }) => (data.iter().map(|x| *x as f64).collect(),shape),
55            FitsData::FloatingPoint64(FitsDataArray { shape, data }) => (data,shape),
56            _ => panic!("Could not unpack PSF data")
57        }; //TODO add support for f64 etc
58
59        let normalization:f64 = data.iter().sum();
60        let data:Vec<f64> = data.iter().map(|x|x/normalization).collect();
61        println!("PSF has been normalized to {:?}",data.iter().sum::<f64>());
62
63        assert_eq!(shape[0], x_num,"Diva down! Tried to load a file with data of the wrong x size"); //check that the data is the expected size
64        assert_eq!(shape[1], y_num,"Diva down! Tried to load a file with data of the wrong y size");
65        //TODO is this [x,y] or [y,x]
66
67        let center_x:f64 = PSF::load(center.0, &primary_hdu);
68        let center_y:f64 = PSF::load(center.1, &primary_hdu);
69        let size_x:f64 = PSF::load(size.0, &primary_hdu);
70        let size_y:f64 = PSF::load(size.1, &primary_hdu);
71        let data = data.chunks(x_num).map(|i| i.to_vec()).collect();
72      //  println!("{:?}",data);
73        PSF {
74            path: file,
75            data,
76            x_pixels: x_num,
77            y_pixels: y_num,
78            center: Point::new(center_x,center_y,Coordinates::ABSOLUTE),
79            size: (size_x,size_y),
80        }
81    }
82
83
84
85    pub fn write_file(&self, path:&str,center_keys:(&str,&str)){
86
87        let data:Vec<f64> = self.data.clone().iter().map(|x|x.to_owned()).flatten().collect();
88        let data= data.iter().map(|x| *x).collect();
89        println!("Trying to write to {path}, {:?}",data);
90        let mut primary_hdu = Hdu::new(&[64, 64], data);
91        println!("Done making hdu");
92        let (x,y) = self.center.to_absolute().values();
93        println!("x,y,{x} {y}");
94        primary_hdu.insert(center_keys.0,x.to_string().as_str() );
95        primary_hdu.insert(center_keys.1,y.to_string().as_str() );
96        println!("printed keys");
97        //primary_hdu.insert(size_keys.0, self.size.0);
98        //primary_hdu.insert(size_keys.1, self.size.1);
99        Fits::create(path, primary_hdu).expect("Failed to create");
100        println!("done??")
101
102
103    }
104
105    pub fn snap_to_grid(&self, grid: &GRID2D) -> usize{
106        let index = grid.snap(self.center.clone());
107        index
108    }
109
110
111    pub fn repack_data(flat_data: Vec<f64>) -> Vec<Vec<f64>>{
112        flat_data.chunks(64).map(|i| i.to_vec()).collect()
113    }
114
115    fn load(thingy:Load, header:&Hdu)-> f64{
116        match thingy{
117            Load::FromKey(Key) => {
118                match header.value(&Key).expect("failed to get key") {
119                    HeaderValue::RealFloatingNumber(value)=> *value,
120                    _ => panic!("could not unpack FITS header value")
121                }}
122            Load::FromValue(value) => value
123        }
124    }
125
126    pub fn convolve(&self, kernel:&Vec<Vec<f64>>) -> Vec<f64>{
127        let kernel:Vec<Vec<f64>> = kernel
128            .iter()
129            .rev()
130            .map(|v|v.iter().map(|x|*x).rev().collect()).collect();
131        let flat_data:Vec<f64> = self.data.iter().flatten().map(|x|*x).collect();
132        let flat_kernel:Vec<f64> = kernel.iter().flatten().map(|x|*x).collect();
133        let data = DynamicMatrix::new(self.x_pixels, self.y_pixels, flat_data).unwrap();
134        let kernel = DynamicMatrix::new(kernel[0].len(), kernel.len(), flat_kernel).unwrap();
135        let output = convolve2d(&data, &kernel);
136        output.get_data().to_vec()
137    }
138
139
140
141
142
143
144}
145
146
astroimsim_data/psf.rs

astroimsim_data/
psf.rs
