latex-author-affiliation-generator

Tools for collecting author names and affiliations, setting the order and generating required LaTeX for various journal templates

Requires numpy, pandas. Compatible with MNRAS v3.0; AAS v6.3.1

Input author names and affiliations into the spreadsheet author-affiliation-example (including LaTeX-specific characters such as Ren\'{e} Artois for an accented e). You can make your own copy (File > Make a copy) in Google Sheets at this link.

Set the order of authors in the 'Order' column of this first sheet, you don't need to sort the list as the Python script will handle this. Any author with a blank 'Order' will be automatically ordered in the alphabetical section of the author list.

If using mnras.py:

In the Commands_Affiliations sheet, set the shorthand commands (I suggest three letter codes, but there's no restrictions) for each unique affiliation. Be careful not to define an already common/previously defined LaTeX command). If the spreadsheet is working properly it should have identified all the unique affiliations. Be sure to check the Google Sheet command is searching the full list of affiliations:

• The command in cell B2 by default is =UNIQUE(FILTER(FLATTEN(Authors_Affiliations!F5:H20),FLATTEN(Authors_Affiliations!F5:H20)<>"")). This means it is searching the range F5:H20 of the first sheet, flattenning it into a list, removing blanks (the FILTER command) and then finding the unique entries. You should only need to change the H20 in both parts of this command depending on the number of affiliation columns and number of authors.

Next, export BOTH sheets as .tsv files. Important .csv files WILL NOT WORK, the commas in affiliation addresses make this not viable (or maybe they do, but .tsv is safer and it's how the code is setup).

Place the .tsv files wherever you want, I'd suggest the same folder as the .py file you will use to generate the LaTeX.

The mnras.py file requires three arguments in the command line, relative paths to: the Author_Affiliations.tsv file; the Commands_Affiliations.tsv file; and the name of the file you with to create and write to.

Additionally, you can include author's ORCIDs by adding the --orcid argument. Make sure to upload the orcidlogo.pdf file to your LaTeX project and ensure the path in the pre-amble is correct (by default the path is figures/orcidlogo.pdf)

In the example, I ran the command python mnras.py -A "example/author-affiliation-example - Authors_Affiliations.tsv" -C "example/author-affiliation-example - Commands_Affiliations.tsv" -O example/example_mnras_output.txt --orcid to generate example_mnras_output.txt.

Finally, copy the relevant sections of example_mnras_output.txt into your LaTeX file. In the case of MNRAS, the first block of commands are placed with the other command definitions. The full author and affiliation command, wrapped in \author{}, is generated

If using aas.py:

In the Commands_Affiliations sheet, set the shorthand commands (I suggest three letter codes, but there's no restrictions) for each unique affiliation. Be careful not to define an already common/previously defined LaTeX command). If the spreadsheet is working properly it should have identified all the unique affiliations. Be sure to check the Google Sheet command is searching the full list of affiliations:

• The command in cell B2 by default is =UNIQUE(FILTER(FLATTEN(Authors_Affiliations!F5:H20),FLATTEN(Authors_Affiliations!F5:H20)<>"")). This means it is searching the range F5:H20 of the first sheet, flattenning it into a list, removing blanks (the FILTER command) and then finding the unique entries. You should only need to change the H20 in both parts of this command depending on the number of affiliation columns and number of authors.

Next, export BOTH sheets as .tsv files. Important .csv files WILL NOT WORK, the commas in affiliation addresses make this not viable (or maybe they do, but .tsv is safer and it's how the code is setup).

Place the .tsv file wherever you want, I'd suggest the same folder as the .py file you will use to generate the LaTeX.

The aas.py file requires three arguments in the command line, relative paths to: the Author_Affiliations.tsv file, the Commands_Affiliations.tsv file and the name of the file you with to create and write to.

In the example, I ran the command python aas.py -A "example/author-affiliation-example - Authors_Affiliations.tsv" -C "example/author-affiliation-example - Commands_Affiliations.tsv" -O example/example_aas_output.txt to generate example_aas_output.txt.

Finally, copy the relevant sections of example_output.txt into your LaTeX file. (The command definitions go before the begin document command in LaTeX)

Acknowledgments

Thank you to Matt Green for sharing the trick for making changes to affiliation numbers easy to deal with. Thank you to Ed Bryant for sharing the commands used to add ORCIDs to the author list for the MNRAS template.