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Дата индексирования: Sun Apr 10 02:17:13 2016
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ALSVID is a package of utilities for command line and scripted processing of
FITS images. It was first released as Version 1.0 for Linux in 2010,
based on C code and the cfitsio library.

The most recent version written in Python is available from

http://www.astro.louisville.edu/software/alsvid

Starting with Version 2.0 in 2013, new python programs enhance the capabilities of the
original code and offer many opportunities for future development. These
programs will run on any operating system with Python, Numpy, Scipy, PyFITS, and
PyWCS installed.

With Version 3.0 released in 2014 the original C-programs are fully deprecated and not maintained.

Linux systems will usually have the Python core (Version 2.7) available.
As root user, use the distribution's installer "easy_install" to add the other
packages. For other operating systems, use the Python website, or install the
Enthought Canopy distribution of Python with Numpy and Scipy.

Packages in addition to the base Python that are recommended or required are

dateutil
matplotlib (recommended along with related packages for plotting)
numpy (and development code)
scipy
cython
scikit-image
pyfits
wcsfits
f2n


Alsvid works in conjunction with any camera software that produces FITS image
files. It does not require IRAF or IDL, and in many cases will replace those
environments with a system that is simple to implement with modern Linux, Windows,
or MacOS computing. Furthermore, Alsvid allows scripted operation and is
suitable for server-side web-based applications.

For a graphical user interface, consider AstroImageJ in addtion to Alsvid. AIJ
provides real-time photometry and includes the image processing code of ImageJ
as well, so it is suitable for a variety of astronomical image applications that
require user interaction. Alsvid also supports features of ds9.

Please see the documentation for details. Usage help for Alsvid routines
is given in response to a command line execution without arguments.



ALSVID Python Utilities for Processing FITS Images
==================================================

file_renumber.py Renumber files in a directory
fits_1d_to_dat.py Extract a 1-dimensional FITS array as data
fits_absolute_value.py Absolute value of an image
fits_background_remove.py Fit and subtract a background
fits_bias.py Subtract a bias frame
fits_bin.py Bin a stack of images one by one
fits_border.py Zero values outside borders
fits_clean_head.py Clear all but essential items from the header
fits_clip.py Clip an image at minimum and maximum values
fits_convert.py Convert an image from one type to another
fits_dark.py Subtract a dark frame from an image
fits_derivative.py Create a derivative stack from a temporal stack of FITS images
fits_divide.py Divide one FITS file by another
fits_edit_head.py Edit the FITS header
fits_fft.py Create a frequency stack from a temporal stack of FITS images
fits_fft_test.py Template to generate test stack for fits_fft.py
fits_find_stars.py Find stars in an image
fits_fix_col.py Repair a bad column
fits_flat.py Divide an image by a flat frame
fits_flip_lr.py Flip an image left-right
fits_flip_ud.py Fiip an image up-down
fits_from_png.py Convert a png file to a FITS file
fits_from_raster.py Built a FITS file from a stack of 1d raster data files
fits_from_raw_dslr.py Exctract R, B, and B fits images from a RAW Canon, Nikon, or Sony image
fits_from_text.py Create a FITS image from a text file
fits_from_tifs.py Generate FITS images from TIF files
fits_level.py Fit and remove a plane gradient
fits_list_exposure.py List all exposures for FITS files in a directory
fits_list_head.py List the FITS header
fits_list_head_to_csv.py Export the FITS header to a csv file
fits_mean.py Take the mean of several images
fits_median.py Take the median of several images
fits_mef_to_fits_images.py Extract individual FITS images from a Multi-Extension file
fits_multiply.py Multiply two FITS images of the same size
fits_nan_to_num.py Change "NAN" elements to numbers
fits_norm.py Normalize an image
fits_nstats.py Statistics on a stack of images
fits_phoenix_hires_to_dat.py Extract spectra from a PHOENIX model
fits_pixel_photometry.py Aperture photometry on an image
fits_pixel_to_wcs_photometry.py Aperture photometry outputing RA and Dec
fits_pix_to_ds9.py Convert an x,y list to ds9 regions
fits_pix_to_sky.py Convert an x,y list to a WCS ra,dec list
fits_radial_average.py Take an average assuming circular symmetry
fits_rd.py Create a random decrement autocorrelation stack from a temporal stack of FITS images
fits_remove_stars.py Use a pixel x,y list to remove stars from an image
fits_remove_stars_with_psf.py Remove stars and replace based on a model point spread function
fits_roll.py Rolls and wraps by dx and dy within the same image size
fits_rotate_90.py Rotate an image in 90 degree increments
fits_rotate.py Rotate an image an arbitrary angle
fits_scaled_dark.py Dark subtraction scaling exposure time
fits_scale.py Quadratically scale image data
fits_sky_to_aij.py Create AIJ x,y apertures from a sky ra,dec list
fits_sky_to_ds9.py Create ds9 x,y regions from a sky ra,dec list
fits_sky_to_pix.py Create plain x,y text from ra,dec
fits_stats.py Statistics on a single image
fits_subtract.py Subtract two FITS images of the same size
fits_sum_centered.py Center and sum an image stack
fits_sum_cols.py Sum selected columns (for spectra)
fits_sum.py Sum an image stack
fits_sum_region.py Sum over a region bounded by rows and columns
fits_sum_rows.py Sum selected rows (for spectra)
fits_to_float32.py Convert a FITS image to 32-bit float
fits_to_lin_png.py Create a linear 16-bit gray-scale png
fits_to_log_png.py Create a logarithmic 16-bit gray-scale png
fits_viewer.py Simple image viewer for a single FITS image


ALSVID Python Utilities for Date and Time
=========================================

jd.py Provide the Julian day now
lst.py Provide the local sidereal time now
utc.py Provide the universal time now


ALSVID Python Utilities for Spectroscopic Data
==============================================

spectrum_airtovac.py Convert spectral 2-column wavelength, flux file from air to vacuum wavelengths
spectrum_crosscorr.py Cross correlate target and template spectra to find the radial velocity of the target
spectrum_heliovel.py Return the barycentric velocity correction accounting for the topocentric motion of the observer
spectrum_rotbroad.py Broaden a stellar template spectrum with a model of vsini and linear limb darkening
spectrum_vactoair.py Convert spectral 2-column wavelength, flux file from vacuum to air wavelengths