Utilities for UAF Digital All-Sky Camera: reading and plotting
Project description
DASC all-sky camera utilitiess
Utilities for plotting, saving, analyzing the Poker Flat Research Range Digital All Sky Camera. (Other locations, too).
This program handles the corrupted FITS files due to the RAID array failure on 2013 data.
The raw data FITS are one image per file.
Install
pip install -e .
Usage
Many analysts may use the API directly, like:
import dascutils as du
data = du.load('tests/PKR_DASC_0558_20151007_082351.743.FITS')
This returns an xarray.Dataset, which is like a "smart" Numpy array.
The images are index by wavelength if it was specified in the data file, or 'unknown' otherwise.
The images are in a 3-D stack: (time, x, y).
data.time
is the time of each image.
also several metadata parameters are included like the location of the camera.
Download raw DASC files by time
Example download October 7, 2015 from 8:23 to 8:54 UTC to ~/data/
:
DownloadDASC 2015-10-07T08:23 2015-10-07T08:54 ~/data
-c
overwrite existing files-s
three-letter site acronym e.g.PKR
for poker flat etc.
Make movies from DASC raw data files
Plots all wavelengths in subplots, for example:
PlotDASC tests/ -a cal/PKR_DASC_20110112
additional options include:
-t
specifiy time limits e.g.-t 2014-01-02T02:30 2014-01-02T02:35
-w
choose only certain wavelength(s)
Spatial registration (plate scale)
The cal/
directory contains AZ
and EL
files corresponding to each pixel.
import dascutils as du
data = du.load('tests/PKR_DASC_0558_20151007_082351.743.FITS', azelfn='cal/PKR_DASC_20110112')
now data
includes data variables az
and el
, same shape as the image(s), along with camera position in lat
lon
alt_m
.
- Be sure you know if you're using magnetic north or geographic north, or you'll see a rotation by the declination.
- Note the date in the filename--perhaps the camera was moved since before or long after that date?
Map Projection
A common task in auroral and airglow analysis is to project the image to an imaginary alttiude, that is, as if all the brightness were coming from that altitude.
Typically that altitude is on the order of 100 km.
The dascutils.project_altitude()
function adds coordinates mapping_lat
mapping_lon
to the xarray.Dataset by:
import dascutils as du
import dascutils.projection as dp
data = du.load('myfile.FITS', azelfn='cal/PKR_DASC_20110112')
data = dp.project_altitude(data, 100.) # for 100 km
The dascutils.projection
is a separate import because it calls extra Python modules that aren't needed for basic data loading.
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