Tools to correct the pointing of Hinode/EIS
Tools to correct the pointing of Hinode/EIS.
This Python package implements the method described in the paper Pelouze et al. 2019, Sol Phys 294:59.
From the command line
This tool can be run from the command line by calling
usage: compute_eis_pointing [-h] [-s STEPS_FILE] [--io IO] [-c CORES] [--cache-aia-data] filename [filename ...] Determine the pointing of Hinode/EIS. positional arguments: filename The names of the level 0 EIS files, eg. 'eis_l0_20100815_192002'. optional arguments: -h, --help show this help message and exit -s STEPS_FILE, --steps-file STEPS_FILE Path to a yaml file containing the registration steps. --io IO Directory where output files are written, default: ./io. -c CORES, --cores CORES Maximum number of cores used for parallelisation, default: 4. --cache-aia-data Cache the AIA data to a file. This uses a lot of storage, but speeds things up when the same raster is aligned for the second time.
Examples (command line):
compute_eis_pointing -c16 eis_l0_20140810_042212 compute_eis_pointing --steps-file steps/shift_only.yml eis_l0_20140810_042212
As a Python module
The tool can also be used from within a Python script, using
compute(*filename, steps_file=None, io='io', cores=4, cache_aia_data=False) Perform all computation steps to determine the optimal EIS pointing. Parameters ========== filename : list The names of the level 0 EIS files, eg. 'eis_l0_20100815_192002'. steps_file : str or None (default: None) Path to a yaml file containing the registration steps. io : str (default: 'io') Directory where output files are written. cores : int (default: 4) Maximum number of cores used for parallelisation. cache_aia_data : bool (default: False) Cache the AIA data to a file. This uses a lot of storage, but speeds things up when the same raster is aligned for the second time.
import eis_pointing eis_pointing.compute('eis_l0_20140810_042212', cores=16) eis_pointing.compute('eis_l0_20140810_042212', steps_file='steps/shift_only.yml')
Install the latest release by running:
pip install eis_pointing.
Alternatively, the latest version can be installed from GitHub by cloning this
git clone https://github.com/gpelouze/eis_pointing, then
cd eis_pointing, and
pip install ..
Optional: install SolarSoft
Before computing the optimal pointing, this tool can download, prepare, and
export the EIS data by calling external IDL routines from SolarSoft. For
these features to be available, a functioning installation of SolarSoft
containing the EIS instrument is required. Install SolarSoft,
and set the environment variable
$SSW to your installation path (by default,
SolarSoft is assumed to be installed installed into
It is perfectly fine not to install or configure SolarSoft to run with this
tool. In this case, you will need to manually download the EIS level0 FITS,
prepare them into level1 FITS, and save a windata structure containing the
Fe XII 195.119 Å line to a
.sav file placed in
See pipeline for details on how to do this.
The registration steps used to find the optimal pointing can be customised in a
YAML file, and passed to
eis_pointing using the
--steps-file parameter (see
examples above). The file should have a top-level key named
contains a list of registration steps. Each step must specify at least a
type, chosen between
By default, EIS data are coaligned with synthetic AIA raster. To coalign with a
single AIA image, add the top-level key
single_aia_frame: True. In this case,
the reference AIA image chosen at the middle of the EIS raster.
See files in
steps/ for examples.
When no file is specified, the default behaviour is the same as using
All the steps required to determine the optimal pointing data from EIS level 0
files are defined in
driver.py. The appropriate functions are called by the
compute_eis_pointing when using the tool from the CLI, or by
eis_pointing.compute() when using it as a Python module.
Download data Download the required EIS level 0 FITS, and place them in the EIS data files and directory structure described in EIS Software Note #18 (eg.
Prepare data Generate EIS level 1 FITS from level 0, and save it to the EIS data files and directory structure (eg.
$HINODE_DATA/eis/level1/2014/08/10/eis_l1_20140810_042212.fits). Performed by
eis_pointing/prep.pro, which calls the SolarSoft routine
Export windata Save a
windatastructure containing the Fe XII 195.119 Å line, obtained using the SolarSoft function
eis_getwindata(see EIS Software Note #21). The structure is saved to
./io/windata/windata_20140810_042212.sav). Performed by
Alternative to steps 1-3 without SolarSoft If SolarSoft is not installed or
configured, you will need to separately generate a windata structure containing
the Fe XII 195.119 Å line, and save it to
wd = eis_getwindata('eis_l1_20140810_042212.fits', 195.119, /refill) save, wd, filename='./io/windata/windata_20140810_042212.sav'
Compute the EIS emission Generate an intensity map of the Fe XII 195.119 Å line by summing the spectra between 194.969 and 195.269 Å. Data are saved to
./io/eis_aia_emission/eis_aia_emission_20140810_042212.fits). Performed by
Determine the optimal pointing Determine the optimal pointing for EIS using the intensity map generated at the previous step, and AIA 193 data retrieved from Medoc as a reference. (The AIA FITS are downloaded to
./sdo/aia, or to
$SDO_DATA/aia/if the environment variable
$SDO_DATAis set set.) Results from the alignment (ie. new EIS coordinates) are saved to
<io>/pointing/eis_pointing_<date>.fits. Diagnostics plots, correlation cubes, as well as a YAML file containing the results from the coregistration are also saved to
<io>/pointing_verification/<date>/. Performed by
imagescontains functions to register images in translation, relatively to another image.
rasterscontains functions to register images in translation and rotation, relatively to a synthetic raster.
slitsfunctions to register slit positions (ie. vertical columns in an image) separately, relatively to a synthetic raster.
toolsfunctions shared among the previous submodules.
Functions shared by different components
AIARasterGeneratorthat builds synthetic rasters from AIA data. Also contains
cli: argument parsing and output display.
aia.py: functions to handle native EIS and AIA data, filenames, and data queries. This does not take care of transformed data such as
files: manage local filenames (ie. those in
io/); canonical EIS or AIA filenames are handled in
idl: run IDL or SSW code from Python, load and format data returned by IDL. Contains
num: tools that extend numpy or scipy.
plots: help generate plots at step 4.
sun: generic solar computations.
Reference / License
If you use this package for a publication, please acknowledge the following paper: Pelouze et al. 2019, Sol Phys 294:59.
This package is released under a MIT open source licence. See
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