docs: update and improved navigation

Author: quantixed

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: TrackMateR
 Type: Package
 Title: Working with TrackMate outputs in R
-Version: 0.2.1
+Version: 0.3.0
 Authors@R:
     person(given = "Stephen J",
            family = "Royle",

README.Rmd

@@ -26,8 +26,6 @@ The standard output from a tracking session is in TrackMate XML format.
 
 The goal of this R package is to import all of the data associated with the final filtered tracks in TrackMate for further analysis and visualization in R.
 
-**This package is under development and should not be considered stable until its first release.**
-
 ## Installation
 
 Once you have installed [R](https://cran.rstudio.com) and [RStudio Desktop](https://www.rstudio.com/products/rstudio/download/), you can install TrackMateR using devtools

_pkgdown.yml

@@ -5,12 +5,81 @@ authors:
     href: https://quantixed.org
 
 template:
-  bootstrap: 5
-  bootswatch: flatly
+  params:
+    bootswatch: flatly
 
 repo:
   url:
     home: https://github.com/quantixed/TrackMateR/
     source: https://github.com/quantixed/TrackMateR/blob/master/
     issue: https://github.com/quantixed/TrackMateR/issues/
     user: https://github.com/quantixed/
+
+navbar:
+  left:
+    - icon: fa-home fa-lg
+      href: index.html
+    - text: Getting Started
+      href: articles/TrackMateR.html
+    - text: Guides
+      menu:
+      - text: Comparison of multiple datasets
+        href: articles/guides/comparison.html
+    - text: Reference
+      href: reference/index.html
+  right:
+    - icon: fa-github fa-lg
+      href: https://github.com/quantixed/TrackMateR
+
+reference:
+- title: Loading and correcting TrackMate data
+  desc: >
+    To start, TrackMate XML data needs to be read into R. It may need recalibrating
+    if the data were captured with incorrect parameters.
+  contents:
+  - readTrackMateXML
+  - correctTrackMateData
+- title: Automated reports
+  desc: >
+    TrackMateR can be used manually to have fine control over your analysis, however
+    if you just want to analyse your data with default parameters, these two functions will
+    process one dataset, or many
+  contents:
+  - reportDataset
+  - compareDatasets
+- title: Analysing track dynamics
+  desc: >
+    To analyse track dynamics, there are several functions to calculate them.
+    These functions are called (with set parameters) in the automated workflows
+    and all of them must be called to make a report.
+  contents:
+  - calculateAlpha
+  - calculateFD
+  - calculateJD
+  - calculateMSD
+  - calculateTrackDensity
+  - fittingJD
+- title: Generating reports and summaries
+  desc: >
+    Reports and summaries are collections of plots. They can be generated automatically
+    using the automated workflows, or they can be made manually after fine-tuning the analysis
+    of track dynamics.
+  contents:
+  - makeSummaryReport
+  - makeComparison
+- title: Plotting functions
+  desc: >
+    The autoimated workflows and the reports that can be generated with TrackMateR
+    use several different plotting functions.
+  contents:
+  - plot_tm_MSD
+  - plot_tm_NMSD
+  - plot_tm_allTracks
+  - plot_tm_alpha
+  - plot_tm_cumdistOverTime
+  - plot_tm_displacementHist
+  - plot_tm_displacementOverTime
+  - plot_tm_fd
+  - plot_tm_neighbours
+  - plot_tm_speed
+  - plot_tm_width

vignettes/comparison.Rmd

@@ -81,6 +81,18 @@ In the example above, the code will produce the following in a directory called
 
 That is, the individual reports are saved with a new name (regardless of the original XML filename), all datasets are combined (per condition) in `combined.pdf` and a comparison of a summary of all conditions is saved in the top level folder (`comparison.pdf`).
 
+As well as graphical outputs, `compareDatasets()` saves several csv files of data (to `Outputs/Data/`).
+In each condition folder, the data frames are collated and saved.
+This includes: TrackMate data, MSD, jump distance and fractal dimension data.
+There is also a csv file of the data frame used to plot the average msd for this condition.
+
+Above the condition folders, three csv files are saved.
+A collation of the msd summary data `allMSCurves.csv` for all conditions; summary data per dataset `allComparison.csv` which is the data frame used for making the comparison plots; and `allTraceData.csv` which is a data frame of properties per trace per dataset for all conditions.
+
+The idea with these files is that a user can load them back into R and process the data in new ways and go beyond TrackMateR.
+An advanced user can make their own data frames by running TrackMateR functions.
+A good place to start is to peruse the code for `compareDatasets()` and modify from there.
+
 ## Recalibrating TrackMate files
 
 It is possible to recalibrate TrackMate XML files _en masse_ by using a CSV file in the condition subfolder containing the XML files.