Empirical noise simulator
Simulates pure noise 2D images given a real ALMA cube or image in input.
A real sky image (same size as reference image) can also be added.
- Source Extractor version 2.25.0 (2018-02-08)
- Python 3.7
- Python non standard packages: pbd, astropy, numpy, scipy, matplotlib, math, cv2, skimage, re, argparse
$ python noisempire.py config_file.txt
If you want, you can specify some/all the parameters from command line (they will take precedence over those in the config file:
Example:
$ python noisempire.py config_file.txt --INPUT_IMAGE=input_image.fits --REAL_SKY_IMAGE=real_sky.fits --DEBUG=False
Examples of input images and real sky are provided for a test run.
$ python noisempire.py -h
or
$ python noisempire.py --help
The default configuration file is self-explanatory, and it is recommended to read it before using noisempire.
This is a complete list of all the outputs produced (some of them can be obtained ONLY using the DEBUG option)
Original image background - large scale
bck1_imagename.fits
Original image background - small scale
bck2_imagename.fits
Original image after all noise patterns are subtracted
Flat_noise_imagename.fits
High frequency Noise patterns isolated from the original image
HFN_imagename.fits
simulated PSF of the input image
PSF_sim_imagename.fits
rms map of the input image
rms1_imagename.fits
sources identified in the original image (step 1 - mostly point like)
srcs_only1_imagename.fits
sources identified in the original image (step 2 - point like and more extended components)
srcs_only2_imagename.fits
Elliptical (PSF-like patterns) isolated from the original image
Elliptical_Patterns_imagename.fits
Radial patterns isolated from the original image
Radial_Patterns_imagename.fits
simulated image sim_imagename.fits
original image subtracted of background on large scale and high frequency patterns
bck1_HF_sub_imagename.fits
original image subtracted of background on large scale
bck1_sub_imagename.fits
original cube flattened to a 2D image
FLAT_imagename.fits
original image subtracted of sources, background on large scale and high frequency patterns
nosrcs_bck1_HF_sub_imagename.fits
original image subtracted of sources, background on small and large scale, high frequency patterns and Radial and/or elliptical patterns (REP)
nosrcs_bck3_HF_REP_sub_imagename.fits
original image subtracted of sources, background on large scale and high frequency patterns
nosrcs_bck3_HF_sub_imagename.fits
original image subtracted of sources, background on large and small scales
nosrcs_bck3_sub_imagename.fits
original image subtracted of sources and high frequency patterns
nosrcs_HF_sub_imagename.fits
original image subtracted of sources only
nosrcs_patch_bck_imagename.fits
original image subtracted of sources and large scale background
nosrcs_patch_imagename.fits
original image subtracted of large scale background and sources set to 0.
nosrcs_imagename.fits
simulated background on large scale (if BCK1_TYPE Simulate)
sim_bck1_imagename.fits
simulated background on small scale (if BCK2_TYPE Simulate)
sim_bck2_imagename.fits
simulated image with noise at PSF scale, noise small scale subtracted (temporary file not to be considered)
sim_bck_sub_tmp2_imagename.fits
simulated image background on small scale (temporary file not to be considered)
sim_bck_tmp_imagename.fits
simulated flat image with noise at PSF scale
sim_Flat_PSFscale_noise_imagename.fits
simulated noise and background (no HF patterns yet)
sim_noise_and_bck_imagename.fits
simulated noise, background and HF patterns
sim_noise_bck_HFN_imagename.fits
xxxxx
sim_nosrcs_nobck_noHF_imagename.fits
simulated image with noise at PSF scale remodulated using the true rms of the original image
sim_PSFscale_noise_imagename.fits
simulated image with noise at pixels-scale only
sim_Pixscale_noise_imagename.fits
simulated flat image (temporary file not to be considered)
sim_tmp_Flat_PSFscale_noise_imagename.fits
V1.0.2 --> V1.0.3
- noisempire can now properly treat images with odd sizes (the high frequency patterns were not correctly computed before, in these cases).
- noisempire can now properly work on rectangular images (it couldn't before due to some little bugs)
- NaN and repeated pixels are masked in the original image, at the beginning of the process A "non problematic" image is computed (IMG_NP in the configuration file). The process ignores areas occupied by "problematic" pixels.
- Pixels below MIN_VAL are considered as problematic and masked pefore processing
- Pixels above MAX_VAL are considered as problematic and masked pefore processing
- The background at large and small scales is now simulated keeping into account possible underlying patterns at these same scales. These patterns are detected/measured computing the ACF at different scales, zooming out the original backgorund image.
- The image parameters (Pixel scale and Beam shape) can be read directly from the header or they can be provided by the user
- A prefix specified by the user is addedd to all the images created (parameter ALL_IMG_PREFIX)
- only selected images are saved, unless DEBUG option is active (list specified inside the configuration file)
- Parameter IMG_ELL_PATT replaced by IMG_ELL
- Parameter IMG_RAD_PATT replaced by IMG_RAD
- Execution time is measured and printed at the end of the process
- Some little bugs corrected
V1.0.1 --> V1.0.2 May 3 2024
- corrected bug (arising flattening cubes problem when extracting radial - elliptical patterns)
V1.0.0 --> V1.0.1 May 2 2024
- removed duplicated import (re)
- removed misleading comments