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=== Modify a plot ===
=== Modify a plot ===
Double click on a plot. A dialog opens that allows you to set the plotted variables, change the design of the plot and other things.
Double click on a plot. A dialog opens that allows you to set the plotted variables, change the design of the plot and other things.
== Tabs ==


=== Tab 'Values' ===
=== Tab 'Values' ===

Revision as of 17:44, 1 July 2020

Kast updated for: Version 1.5.3.15

Basics

Create a new plot

Goto 'Window' -> 'Plot' -> 'New..' A Plot widget will popup and now you can place it into the Dashboard

Remove a plot

Goto 'Window' -> 'Plot' -> 'Plot<i>' -> 'Remove' Here, <i> is the number of the plot.

Rename a plot

Goto 'Window' -> 'Plot' -> 'Plot<i>' -> 'Rename' Here, <i> is the number of the plot.

Modify a plot

Double click on a plot. A dialog opens that allows you to set the plotted variables, change the design of the plot and other things.

Tabs

Tab 'Values'

All Modules that are part of the sequencer are listed. Expand the modules and select the variables that you would like to plot:

  • 'x' refers to the bottom x axis
  • 'y' refers to the left y axis
  • 'z' refers to the right y axis

The functionality 'Slice/Filter' allows you to reduce the plotted data. The syntax is directly adapted from array slicing via numpy in python.

  • use '-1' to get the last point of a variation
  • use '-100:' to get the 100 points of a variaton
  • use '0' to get the data of first parameter of a variaton, and '1' to get the data of the second parameter of a variation
  • use '::2' to get every second data point
  • use '1::2' to get every second data point but starting from the second value.

If you make multi-dimensional parameter variations, you can tell SweepMe! where to split the lines by using the CheckBoxes underneath 'New line per value'. Select the module that performs the parameter variation for which you would like to split the plotted lines. Imaging you measure temperature dependent current-voltage characteristics. Typically, you would like to have each current-voltage characteristic as one line in the plot for each measured temperature. Hence, you have to check 'New line per value' for your Temperature module.

Tab 'Style'

There are different plot styles that you can use. The default setting is 'Lines' which displays markers and lines. Other plot styles are under development, but can be already tested. Let us know if you need further features and improvements. Just write to support@sweep-me.net

Color cycle

For each axis, a color cycle can be defined which is a png colormap file from which colors are extracted. In the folder "resources/colormaps" of the main porogram installation, a svg file template can be found to create own colormaps. These png colormap files should be saved in the public folder "Resource/colormaps" to keep them even if the SweepMe! version is changed. Colors are extracted along a horizontal central line along the image. If the file ends with an underscore and a number, a fixed number of colors is extracted. For example, 9 colors are extracted from the preinstalled colormap "SimpleColor_9.png" equidistantly. If no underscore + number is given at the end of the filename, as many colors are extracted as curves are in the plot. The alpha channel of each pixel is read out as well so that also transparency changes can be created.

You can use 'revert' to flip the colormap to start the color cycle other way around. The option 'start from last curve' uses the first color of the cycle always for the last added and then takes the second color for the second last addded curve and so. This way, you can make sure that your last added curves have always the same color. It can be helpful to use a colormap where the last added curve is always highlighted.

Tab 'Scales'

  • 'Scale' -> select whether scales are linear or logarithmic
  • 'Fixed axes limits' -> All plots are autoscaled. Select fixed boundaries for your data if you like.
  • 'Normalize to / Divide by' -> Enter a value and the data will be divided by this value or choose 'maximum', 'minimum', 'last', or 'first' to normalize your data.
  • 'Scaling mode' -> if you have visualize data at the left y axis ('y') and the right y axis ('z') you can define whether both axis use a global scaling, are individually scaled, or use a scale defined by either 'y' or 'z'
  • 'Design' -> in progress... :) You can already choose whether a grid should be shown. The legend also works but just shows an index that increments for each variaton.

Tab 'Design'

In this tab, you can find options to control the grid and the legend.