Interactive App

gui/TemporalMapperApp.m is a point-and-click alternative to the scripted pipeline in the Quickstart — load data, pick variables, set parameters, and view the resulting network without writing any code. It wraps exactly the same two-step pipeline (tknndigraph → filtergraph) and the same plotting functions (plottmgraph/plotgraphtcm) described elsewhere in these docs, so everything in Concepts about what the parameters mean still applies.

The same East Lansing weather dataset and parameters as the Quickstart, built through the app instead of the command line.

Launch it

addpath("tmapper_tools/")
addpath("gui/")
app = TemporalMapperApp;

Layout

The window is split into two parts: four Setup panels across the top, and the Network/recurrence plots filling the rest of the window.

Data

Load a data file (.csv/.txt, read with readtable) or a table/numeric matrix already sitting in your base workspace. Only numeric columns are offered as build variables. This panel also holds Build Network, Stop (cancels an in-progress build — see below), Reset (restores every parameter to its default, but leaves your loaded data and variable selection alone), Copy Code, and a live Status box with per-step timing once a build finishes.

Variables & Preprocessing

• Variables — the numeric columns to build the network from (⌘/Ctrl/Shift-click for multiple; Select All as a shortcut).
• z-score variables — on by default; see the Quickstart's note on why.
• start row / end row — restrict the build to a sub-range of the loaded data. end row = Inf means "the last row."
• downsample (N) — keep every Nth row. A moving-average lowpass is applied first so this doesn't alias high-frequency content into spurious low-frequency structure — see below.
• embed lag / embed order — optional delay embedding; order 1 (default) skips it.

Network Parameters

The four tknndigraph/filtergraph parameters explained in the Quickstart and Concepts: k, d (labeled "compression"), texclude, the two max dist cutoffs, and reciprocal.

Plot Options

Color/time axis variable, node size mode, label method, and whether to show the recurrence plot / a node-border scatter overlay. Changing any of these re-renders the existing network instead of rebuilding it — cheap, and safe to click through freely once a build has completed.

Missing data and downsampling

Two things the scripted pipeline leaves to you are handled automatically here:

Missing data is dropped, not ignored

Rows with a missing value in any selected variable are dropped automatically before building (the status area reports exactly how many), rather than being silently passed through the pipeline — an unremoved NaN here would poison the entire distance matrix without any visible error. Calling tknndigraph/plottmgraph directly on unclean data still raises an error, per the usual rmmissing-first convention.

Downsampling anti-aliases first

Setting downsample (N) > 1 applies a moving-average lowpass over a window of size N before striding, rather than naively picking every Nth raw row.

Stop cancels between, not mid-stage

Stop requests cancellation, but MATLAB callbacks run synchronously, so it only takes effect at the boundary between stages (distances → k-NN graph → simplify) — not mid-computation within one. For a very slow single stage (usually the distance/k-NN step on a large dataset), it may take a moment to actually stop.

Copy Code

Copy Code puts a complete, standalone script on the clipboard that reproduces the current build — including the data-loading line if you loaded a file — using the exact resolved parameters shown in the app. This is the bridge back to scripting: prototype interactively here, then paste the generated code into your own analysis once you have parameters you like.

What's next

• Concepts — what the network's nodes, edges, and loops mean.
• Quickstart — the same pipeline, scripted end to end.