Usage instructions

There are two main ways to use fcmaker. You can either execute the module as a script, i.e.:

python -m fcmaker

or you can import the module and execute it within a script, i.e.:

>>> import fcmaker
>>> fcmaker.make_fc( ... ) # or fcmaker.make_fc_local ( ... )

When running fcmaker as a script, any arguments you feed it is pretty much sent to the underlying functions make_fc() and make_fc_local(). For simplicity, this page only discusses how to run the entire module as a script, which ought to be slightly more friendly to users not (yet!) familiar with Python. Still, the hope is that after reading this page, the use of the functions make_fc() and make_fc_local() shouldn’t be too mysterious. Also, don’t forget the built-in help:

>>> import fcmaker
>>> help(fcmaker.make_fc)

Case 1: manual creation of a finding chart via p2

In its most basic mode, fcmaker connects to p2 and creates the finding chart for a given OB Id. To do so, simply type in a terminal:

python -m fcmaker

or from within a Python shell:

>>> run -m fcmaker

You will be prompted for your p2 username, password, and the ID of the observing block to process. fcmaker will create two folders fcm_data and fcm_plots at your current location, where it will store the background image and the finding charts. Once the finding charts have been generated, you can choose to attach the newly created finding chart to the OB on p2, or not.

Case 2a: semi-automatic creation of finding charts via p2 (incl. upload)

If you have a lot of finding charts to create, fcmaker allows for a semi-batch processing. First, create a text file p2_2_fcm.params.txt (the actual filename is flexible) with the following structure:

p2uid:                       # p2 username (will ask at prompt if left blank)
pswd:                        # p2 password (will ask at prompt if left blank)
obids:     [1234567,7654321] # List of Ob IDs to chart
bk_images: [SDSSr, None]     # SkyView survey, None for default, Gaia, or local FITS filename
bk_lams:   [None,None]       # Lambda of the chart (SkyView will override), None for default
data_loc:  fcm_data          # Relative path to the background images (local FITS file or SkyView images) 
plot_loc:  fcm_plots         # Relative path to store the finding charts 

Then, feed it to fcmaker with the -f flag:

python -m fcmaker -f p2_2_fcm.params.txt

In doing so, fcmaker will connect to p2 and process all the OBs listed. Note that for each finding chart, you will still need to manually specify whether you want to upload it to p2 (or not).

Case 2b: fully automatic creation of finding charts via p2 (no upload)

You can fully automate the creation of many finding charts if you include the --no-upload flag. In that case, fcmaker will never attempt to upload anything to p2, and only save them locally:

python -m fcmaker --no-upload -f p2_2_fcm.params.txt

Case 3: targets with proper motions

In case of large proper motions of the target, one can provide the expected year, (month, day, …!) of the observation to create an accurate finding chart, using the --obsdate flag. This also works for OBs that have Ephemeris files. For example:

python -m fcmaker -f --obsdate 2018
python -m fcmaker -f --obsdate 2018-05
python -m fcmaker -f --obsdate 2018-05-17 14:34:57 UTC

Finding charts for moving targets get automatically tagged with the symbol \(\leadsto\).

Case 4: creation of finding charts locally (without p2)

fcmaker can also create finding charts locally, without the need to have an OB present on p2 first (fcmaker will still require an internet connection, though!). To do so, one first needs to specify the basic OB parameters in a text file (in essence, a stripped-down version of a full OBX file). Here are templates for all supported instruments:

The file is then fed to fcmaker with the -f flag, together with the --local flag to indicate that it is a local run:

python -m fcmaker --local -f local_2_fcm.muse.txt
python -m fcmaker --local -f local_2_fcm.hawki.txt
python -m fcmaker --local -f local_2_fcm.xshooter.txt

fcmaker will create the associated finding chart, store it where specified, and exit.

The fcmaker flags

A series of flags allow to fine-tune the way fcmaker works. They are:

  • --help,-h : prints the basic help
  • --version : prints the fcmaker version
  • --montage : will use Montage, to force the finding charts to be rotated North (soon to be retired).
  • --systemtex : will use the system-wide LaTeX, rather than the matplotlib one. Finding charts will be prettier. [encouraged!]
  • --no-upload : tells fcmaker never to try to upload the finding chart(s) to p2.
  • --do-pdf : tells fcmaker to save a .pdf version of the finding chart (in addition to the jpg one).
  • --do-png : tells fcmaker to save a .png version of the finding chart (in addition to the jpg one).
  • --obsdate : allows to specify the observing date (and time), in case of large proper motions or moving target.
  • --do-parang: forces the drawing of the instrument field-of-view when a parallactic angle is set. This will be accurate, but very time-dependant!
  • --clear-SkyView-cache : does as it says. Note that the SkyView cache is not the same as the fcm_data folder in which fcmaker stores the downloaded FITS files.

For example, if you want to boost the aesthetic appeal of your finding charts with the exquisite Computer Modern Bright sans-serif font (why wouldn’t you?), try:

python -m fcmaker --systemtex

The background images

With the exception of MUSE NFM finding charts (see Mock Gaia images for MUSE NFM), fcmaker relies on astroquery.skyview to download background images for the finding charts (if no local FITS file is provided by the user). To display the full list of surveys available, type in a Python shell:

from astroquery.skyview import SkyView
SkyView.survey_dict['overlay_blue']

The default background survey images for the instruments supported by fcmaker are as follows:

  • MUSE WFM: DSS2 Red
  • HAWKI: 2MASS-J, 2MASS-H and 2MASS-K for filters J, H, K, and 2MASS-H for all other filters
  • XSHOOTER: DSS2 Red

Note

From an operational perspective, when using Skyview images, I would strongly recommend to only use DSS2 Red or SDSSr for optical instruments, and 2MASS-J, 2MASS-H or 2MASS-K for IR instruments.

Mock Gaia images for MUSE NFM

DSS2 Red background images are not well suited for MUSE NFM finding charts, given the small field-of-view of 7.5x7.5 square arcsec of this mode. To circumvent this issue, fcmaker creates pseudo sky images from the Gaia catalogue, via the fcmaker_plots.make_gaia_image() function. By default, the image is created with a pixel size of 25 mas (the pixel size of MUSE NFM). Each star is plotted as a 2D gaussian with a FWHM of 80 mas (typical to the image quality achieved in normal operations), and scaled in intensity as a function of its Gaia flux. Evidently, the position of each star takes into account their measured proper motions, to provide an accurate on-sky view at the time of the observation (requested by the user with the obsdate parameter). The resulting image is saved as a fully-fledged FITS file in the data_loc location.

See the Gallery (MUSE NFM) for an illustration of the benefit of these mock Gaia images.