LazyPlot

Version 2.0.2.6 (1,04 MB) von Claudius Simon Appel
LazyPlot is a toolbox for extensive plotting of data in 2D using any standard matlab fit model with minimal coding effort.
5.0
(1)
143 Downloads
Aktualisiert 1. Jun 2022
Lizenz auf GitHub anzeigen
LazyPlot can be used to both quickly display a figure containing any number of lines and data sets each.
It will also define the axes ranges of the figure, as well as title, x/y-label, the position labels of the legend. Also, by defining the vector "LPQS" before calling "LazyPlot", one can get a glance at the figure by sacrificing some features. Clear out the variable again to enter normal mode again.
For more information on how to use LazyPlot, open the "LPCodeComp.m"-file. The changelog can have some information about how this came to be. I'd advise reading through the v.1.5 notes, it contains a few useful information on how to operate LazyPlot.
LazyPlot can only plot if all matrices are of the same size. Use NaN to fill up missing data spots, or just call it a second time and plot into the same figure.
The multiple commented matrices in the LPCodeComp-script show other methods for calling LazyPlot.
The function LPFigurefun can be run separately as well, without having to call LazyPlot.
Credit for the LPTreePrompter goes to Guillaume, https://de.mathworks.com/matlabcentral/answers/512221-function-overwrites-output-with-a-different-number#answer_421822

Zitieren als

Claudius Simon Appel (2024). LazyPlot (https://github.com/Gewerd-Strauss/LazyPlot/releases/tag/v2.0.2.6), GitHub. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2020b
Kompatibel mit R2014b und späteren Versionen
Plattform-Kompatibilität
Windows macOS Linux

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Version Veröffentlicht Versionshinweise
2.0.2.6

See release notes for this release on GitHub: https://github.com/Gewerd-Strauss/LazyPlot/releases/tag/v2.0.2.6
2.0.2.5

See release notes for this release on GitHub: https://github.com/Gewerd-Strauss/LazyPlot/releases/tag/v2.0.2.5
2.0.2.4

v.2.0.2.4 [23.04.2022]
- added option to fix left bottom corner of graph to origin. Other corners not specifically supported. Please use the normal method of entering the axis range for doing so.
2.0.2.3

* couple of fixes
2.0.2.2

For detailed information on the update, open the "Changelog.txt"-file
2.0.2.1

Fixed small mistakes in several function documentations

2.0.2.0

For detailed update notes, look into the Changelog.txt-file
2.0.1.0

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.2.0.1.0.
2.0.0.0

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.2.0.0.0.
1.5.3.2

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.1.5.3.2.
1.5.3.1

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.1.5.3.1.
1.5.3.0

Restructured the whole toolbox to work via one structure which is passed to the different functions.

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.1.5.3.0.
1.5.2.1

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.1.5.2.1
1.5.2.0

Since the space in these patch-notes is restricted and too small, look into the "Changelog.txt"-file for the actual patch notes, under v.1.5.2.0

1.5.1.1

Removed a rather annoying bug in the creation of the LPmatx-matrix in QS-mode resulting in that creation not being possible. Fixed by implementing some of the code from the non-QS section.
1.5.1.0

Now displays the goodness of fit parameters in normal mode
1.5.0.1

Removed an overlooked disp()-line used for debugging.
1.5

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.