A plain text (.txt)-based framework to efficiently describe methods and results in scientific communications.

Part of the software suite for data science: analyz, datavyz, finalyz

What this software enables is to:

• Perform automated export of quantitative results into manuscripts (no copy-paste of analysis results!)
• Benefit from the LaTeX support of figure, equations and corss-referencing in a simple markdown-like language: Org-Mode.
• provide bibliographic management and use different citation styles
• export to diverse formats/templates from the same manuscript file (see all Manuscript Templates)
• benefit from the Emacs editing capabilities when drafting your manuscript.

• Need a LaTeX distribution, e.g. MiKTeX on MsWin, TeXlive on Linux (apt-get install texlive-base). Some additional LaTeX packages will be need (e.g. float, wrapgfig, multirow, ...)

• finalyz source code

Clone the repository and install the module

git clone https://github.com/yzerlaut/finalyz
cd finalyz/
pip install . 

1. perform your quantitative analysis and store your results as your_study_file.npz (see the documentation notebook for an example of such analysis file)
2. draft your paper/presentation/report on a "txt" file (see the templates in the template folder
3. compile it with:

python -m finalyz you_paper.txt --study_file your_study_file.npz

(see the below section Manuscript Templates for a few shortcuts to specific journal formats, preprint templates, ...)

The different manuscript templates covered are:

This is the default finalyz command:

This is a format for short communications.

Use the report command directly. This is a shortcut for:

finalyz your_paper.txt --report --abstract_key '' --citation_style 'number_exponents' --references_key '' --insert_informations_at_the_end

Export a pdf-file with only your figures

Use:

finalyz your_paper.txt --figures_only # or just '-fo' as a shortcut

Generating submission files given specific journal guidelines:

Use:

finalyz your_paper.txt --journal JNeurosci

Note the automated manuscript analysis ! (word count per section, ...)

Use:

finalyz your_paper.txt --journal JPhysiol

other pre-defined templates: PloS journals, Springer journals, Physical Review journals, Cell journals, [...]

We show here how to use cross-referencing extracted from an analysis file to report the results of the study. In this demo case (generated in the documentation notebook, the study.npz file contains both study parameters and analysis results:

{'Nobs': 5,
 'Nsample': 100,
 'cc_coef_over_obs_max': 0.223,
 'cc_coef_over_obs_mean': 0.055,
 'cc_coef_over_obs_min': -0.122,
 'cc_coef_over_obs_std': 0.103,
 'cc_pval_over_obs_max': 0.856,
 'cc_pval_over_obs_min': 0.026,
 'mean_value': 1.605,
 'sem_value': 0.13,
 'study_duration': '2 months'}

we use the syntax (using python's dictionary replacement syntax):

The study was conducted over {study_duration}.
It contained {Nsample} of {Nobs} observations.
Signal was: {mean_value} $\pm$ {sem_value}.
Cross-correlation over observations was {cc_coef_over_obs_mean} $\pm$ {cc_coef_over_obs_mean} with minimum {cc_coef_over_obs_min} and maximum {cc_pval_over_obs_max}.
P-values of linear correlation spanned a range between pval={cc_pval_over_obs_min} and pval={cc_pval_over_obs_max}

are exported to:

The study was conducted over 2 months. It contained 100 of 5 observations. Signal was: 1.605 ± 0.13. Cross- correlation over observations was 0.055 ± 0.055 with minimum -0.122 and maximum 0.856. P-values of linear correlation spanned a range between pval=0.026 and pval=0.856.

References are included in the manuscript text with a plain text citation style:

A landwark study on visual cortex (Hubel and Wiesel, 1962), ...

The compiled citation will depend on the citation style used.

• For finalyz your_paper.txt --citation_style text # default settings, one gets:

A landwark study on visual cortex (Hubel and Wiesel, 1962)

• For finalyz your_paper.txt --citation_style number, one gets:

A landwark study on visual cortex [1]

• For finalyz your_paper.txt --citation_style exponent_number

A landwark study on visual cortex¹

All cited references should point to a bibtex entry in the References section, e.g.:

* References

@article{Hubel_and_Wiesel_1962,
  title={Receptive fields, binocular interaction and functional architecture in the cat's visual cortex},
  author={Hubel, David H and Wiesel, Torsten N},
  journal={The Journal of physiology},
  volume={160},
  number={1},
  pages={106--154},
  year={1962},
  publisher={Wiley Online Library}
}

Equations can be created using the LaTeX syntax:

\begin{equation}
\label{eq:eq1}
\left\{
\begin{split}
& \frac{\partial^2 d}{\partial t ^2} = -x^3 \\
& \sum_{x} 1/x^2 \rightarrow y
\end{split}
\right.
\end{equation}

references to equations are passed using the label of the equation as:

The model corresponding to Equation {eq:eq1} captures ...

By default it will export to:

The model corresponding to Eq. 1 captures ...

but you can set the equation_key explicitely, for example compiling:

finalyz your_paper.txt --equation_key 'Equation'

will produce:

The model corresponding to Equation 1 captures ...

Make a dedicated Figures section in the manuscript and fill it with your caption (main caption in bold) and subcaption in normal text, e.g.:

* Figures

*** Main caption for the single-column figure: description of the protocol.
#+options : {'label':'Fig1', 'extent':'singlecolumn', 'file':'docs/fig1.png', 'page_position':'b!'}
This figure has been produced in the documentation notebook using the datavyz software (a layer on top of matplotlib).

Figures can then be placed in the text with:

[[Figure {protocol-description} around here]]

and referenced by the plain text:

The protocol is described in Figure {protocol-description}, ...

By default it will export to:

The protocol is described in Fig. 1, ...

but you can set the figure_key explicitely, for example compiling:

finalyz your_paper.txt --figure_key Figure'

will produce:

Figure 1 describes the protocol, ...

The set of manuscript informations are:

• Title
• Short title
• Authors
• Short authors
• Affiliations
• Correspondance
• Keywords
• Conflict of interest
• Acknowledgements
• Funding

They can be set up either in the preamble, e.g. as:

#+Title: A template for scientific papers
#+Authors: First Author{1}, Second Author{1,2}*
#+Short title: Paper Template
#+Short authors: Author et al.
#+Affiliations: {1} My first affiliation, {2} Second author affiliation
#+Conflict of interest: The authors declare no conflict of interest

or in the information section as:

* Informations
*** Title
A template for scientific papers

*** Authors
First Author{1}, Second Author{1,2}*

*** Short title
Paper Template

*** Short authors
Author et al.

*** Affiliations
{1} My first affiliation, {2} Second author affiliation

*** Conflict of interest
The authors declare no conflict of interest