# 2. Getting started¶

The entire process can be summarized as follows:

1. Position all the input .fits files in the input/ folder.
2. Check the headers of these files to make sure they contain the required information.
3. Analyze all files with fitstats, and decide if some of them should be discarded.
4. Align and crop your standard and field frames if necessary with the align_crop script. <– TODO: replace the alignment with a new pymatch script.
5. Identify standard stars in your standard frames using the id_standard script.
6. Perform aperture photometry on standard stars with the aperphot_standard script.
7. Define and solve the transformation equations to the standard system using the fit_standard script.

After completing these steps, the final result is a calibrated PSF photometry analysis of the observed field.

## 2.1. Input parameters and folder structure¶

The required input parameters for all the scripts are stored in the params_input.dat file. This file is structured in blocks, with a general block containing parameters that are common to several tasks on top, and a block for each script following that.

The code expects standard and field observed frames to exist separately in corresponding folders within the photpy/input/ folder. The folder structure must look like this:

input/
│
├── standards/
│   ├── stand_001.fits
│   ├── stand_002.fits
│   ├── stand_003.fits
│   └── ...
│
├── field/
│   ├── field_100.fits
│   ├── field_101.fits
│   ├── field_102.fits
│   └── ...


The names of the .fits files are not important, as long as their headers contain all the required information. See the next section to learn of to check if your headers are correct.

The parameters Gain, Read noise, Filter, Exposure time are required information that must be present in the header of each .fits file to be processed.

The names of the keys that point to these values in each header are stored in the General observed data parameters section of the params_input.dat file:

• gain_key: Header key for the gain value.
• rdnoise_key: Header key for the noise value.
• filter_key: Header key for the filter’s name.
• exposure_key: Header key for the exposure time of the frame.

Additionally, this block also contains the required parameters:

• dmin: Minimum flux value accepted.
• dmax: Maximum flux value of a non-saturated star.

To display the header of a .fits, file you can use the following code:

from astropy.io import fits

hdulist = fits.open(image_file)
for k, v in zip(*[hdr.keys(), hdr.values()]):
print(k, v)


## 2.3. Extract data from your observed frames¶

fitstats parameters

• ellip_max: Maximum accepted ellipticity value.
• fwhm_min: Minimum accepted FWHM value.
• sky_method: BW
• thresh_level: Threshold detection level in units of the sky’s STDDEV, used by DAOStarFinder.
• fwhm_init: Initial estimate of the FWHM, used by DAOStarFinder.
• max_stars: Maximum number of bright unsaturated stars used to estimate the average FWHM of stars in the frame.
• do_plots_A: Flag to determine whether the output plot is produced. Accepted inputs are y/n.

The fitstats script is used to estimate the FWHM, sky mean, and sky standard deviation for your observed set of standard and field frames. Once executed, it will go through all the files defined as input (see Input parameters and folder structure section) and automatically process them.

The steps followed by the script are:

1. Estimate the sky’s mean and standard deviation values using the sigma_clipped_stats function.
2. Find candidate stars in the frame through the DAOStarFinder class. Only bright, unsaturated stars are selected.
3. Extract FWHM values for each of the stars selected in the above step, using IRAF’s psfmeasure task. Those stars with large ellipticities or suspiciously small FWHMs are rejected.
4. Remove outliers with large FWHM values.
5. Obtain mean and standard deviation FWHM values for each frame processed.
6. Save date to files and plot.

The script generates the following output files (where xxxxx is the name of the .fits file processed):

• xxxxx .coo: output data with x,y coordinates, FWHM, ellipticity, and relative magnitude values of the stars selected in the .fits file.
# x      y        FWHM   Ellip  Mag
2635.46  847.5    5.076  0.02   3.23
130.46   3820.8   4.788  0.04   1.91
3848.14  2100.48  5.224  0.04   2.24
3858.27  108.83   4.468  0.12   4.26
...

• xxxxx .png: output image showing the analysis performed on each .fits file processed.
• fitstats.dat: output file that contains the relevant data found after the analysis of either the single .fits file processed, or all the .fits files in the processed folder.
# image           filter  exposure    Sky_mean  Sky_STDDEV  FWHM_(N_stars)  FWHM_(mean)  FWHM_(std)
stk_2153.fits          U      20.0        1.96        3.48              46         4.73        0.70
stk_2085.fits          U     250.0       19.36        5.50              14         5.33        0.11
stk_2151.fits          U      20.0        1.96        3.48              49         4.31        0.62
....


Warning

The script uses the .coo files generated by the fitstats script, meaning that fitstats must be executed before this. All processed frames must have the same size.

align_crop parameters

• ref_align: none
• crop_save: y
• x_init_shift: 0.0
• y_init_shift: 0.0
• max_shift: -1.0
• tolerance: 0.05
• do_plots_B: y

This script performs an alignment and crop of all the frames located within a given folder. The alignment is done in the x,y axis exclusively; i.e., no rotation or scaling among the frames is expected.

The user can either select a reference frame to which all other frames will be aligned to, or let the script automatically select one. In this last case, the frame with the largest number of detected stars will be selected.

Cropped .fits files are saved to the same output/ folder where the .coo files exist, under the name xxxxx_crop.fits. A final image is also produced showing the aligned regions for all frames.