Acknowledging brutus ==================== Only use lower case letters when mentioning brutus, and always include the release number, e.g.: brutus |release| brutus will be described in detail in **Vogt et al.**, in prep. If you find brutus useful for your research, please cite this reference accordingly. brutus uses several packages that **should also be acknowledged in their own right.** The following Tex-formatted acknowledgment is one way to do so:: This research has made use of \textsc{brutus}, a Python module to process data cubes from integral field spectrographs hosted at \url{http://fpavogt.github.io/brutus/}. \textsc{brutus} relies on \textsc{statsmodel} (Seabold & Perktold 2010), \textsc{ppxf} (Cappellari & Emsellem 2004), \textsc{fit_kinematic_pa} as described in Appendix C of Krajnovic et al. (2006), \textsc{matplotlib} (Hunter 2007), \textsc{astropy}, a community-developed core Python package for Astronomy (Astropy Collaboration et al., 2013), \textsc{photutils}, an affiliated package of \textsc{astropy} for photometry, \textsc{aplpy}, an open-source plotting package for Python hosted at \url{http://aplpy.github.com}, \textsc{montage}, funded by the National Science Foundation under Grant Number ACI-1440620 and previously funded by the National Aeronautics and Space Administration’s Earth Science Technology Office, Computation Technologies Project, under Cooperative Agreement Number NCC5-626 between NASA and the California Institute of Technology, and \textsc{mpfit}, a Python script that uses the Levenberg-Marquardt technique (Moré 1978) to solve least-squares problems, based on an original Fortran code part of the \textsc{minpack}-1 package. Finally, you also ought to cite the following works, depending on your use of brutus: 1) Cleveland(1979); the reference for the Locally Weighted Scatterplot Smoothing (LOWESS) algorithm used by brutus (via statsmodels) to fit the continuum. 2) The default SSP models shipped with brutus are:: Stellar population synthesis model predictions using the MILES stellar libraries (Sánchez-Blázquez et al. 2006, Falcón-Barroso et al. 2011) at FWHM=2.5 Å, based on the code presented in Vazdekis et al. (2010), using a Kroupa revised IMF with slope 1.3 (Kroupa 2001), Padova +00 (Girardi et al. 2000) isochrones, metallicities ranging from -2.32 to +0.22, and ages of 0.0631 to 17.7828 Gyr. 3) The reddening laws: Either the Cardelli, Clayton & Mathis (1989) law, the Calzetti et al. (2000) law or the theoretical model of a turbulent dust screen of **Fischera & Dopita (2005) [default]** for the extragalactic attenuation corrections, and the **Fitzpatrick (1999) law [default]** for the galactic extinction. If you use the extinction values :math:`A_V` and :math:`A_B` from the NASA Extragalactic Database (NED) to correct for the Galactic extinction [default], then to be thorough, you should mention that:: The Galactic extinction is derived using NED from the Schlafly & Finkbeiner (2011) recalibration of the Schlegel, Finkbeiner & Davis (1998) infrared-based dust map. The map is based on dust emission from COBE/DIRBE and IRAS/ISSA; the recalibration assumes a Fitzpatrick (1999) reddening law with Rv = 3.1 and different source spectrum than Schlegel, Finkbeiner & Davis (1998). and you also ought to acknowledge NED itself:: This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. References: - `Astropy Collaboration et al. (2013) `_ - `Cardelli, Clayton & Mathis (1989) `_ - `Calzetti et al. (2000) `_ - `Cappellari & Emsellem (2004) `_ - Cleveland (1979):: @article{doi:10.1080/01621459.1979.10481038, author = { William S. Cleveland }, title = {Robust Locally Weighted Regression and Smoothing Scatterplots}, journal = {Journal of the American Statistical Association}, volume = {74}, number = {368}, pages = {829-836}, year = {1979}, doi = {10.1080/01621459.1979.10481038}, } - `Falcón-Barroso et al. (2011) `_ - `Fischera & Dopita (2005) `_ - `Girardi et al. (2000) `_ - `Hunter (2007) `_ - `Krajnovic et al. (2006) `_ - `Kroupa 2001 `_ - Moré (1978):: @inbook{more1978, author={Mor{\'e}, Jorge J.}, editor={Watson, G. A.}, chapter={The Levenberg-Marquardt algorithm: Implementation and theory}, title={Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28--July 1, 1977}, year={1978}, publisher={Springer Berlin Heidelberg}, address={Berlin, Heidelberg }, pages={105--116}, isbn={978-3-540-35972-2}, doi={10.1007/BFb0067700}, url={http://dx.doi.org/10.1007/BFb0067700} } - `Sánchez-Blázquez et al. (2006) `_ - Seabold & Perktold (2010):: @inproceedings{seabold2010, title={Statsmodels: Econometric and statistical modeling with python}, author={Seabold, Skipper and Perktold, Josef}, booktitle={9th Python in Science Conference}, year={2010}, } - `Schlafly & Finkbeiner (2011) `_ - `Schlegel, Finkbeiner & Davis (1998) `_ - `Vazdekis et al. (2010) `_