View
Measures
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At this stage it is
assumed that some measures have been computed on some time series.
Different operations can be used to visualize the computed measures on
the different time series, as shown below.
For any of the visualization operations the user is presented with the list of the time series names for which the measures are computed on and the list of measure names, where each measure name codes the measure name (first 10 characters) and its specified set of parameters (one parameter value for each name). A subset of time series names or measure names can be selected from the respective lists with standard use of the mouse: a click on a name and Shift^click on a another name further down in the list selects all names between the former and the latter; a click on a name and subsequent Ctrl^clicks on other names select these names including the first name; Ctrl^a selects the whole list. |
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Table of Measures |
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A table of selected measures and time series can be shown in a separate data window and can be further saved in a file. | |
Free Plot |
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Measures and time series can be selected to be shown in a so-called free plot of measures vs time series, provided that at least two time series are selected. This operation is useful to visualize the dependence of any measure on selected time series, as well as the difference of this dependence across different time series. | |
Plot of measure vs segment |
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This operation can be selected to plot a selection of measures computed on segments of time series, i.e. time series with names containing indices after the character 'S'. Then in one figure the graphs of the selected measures vs segment index are superimposed. Such a figure allows to track changes in the evolution of measure(s) along the recording epoch split in the time resolution of the duration of each segment. | |
Plot of measure vs resampled time series |
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This operation can be selected to plot a selection of measures computed on resampled time series of a time series, i.e. time series with names containing indices after the string code of the specified resampling type. Then in one figure the graphs of the selected measures vs resampled time series index are superimposed, with the zero index assigning the original time series. Such a figure visualizes the result of the resampling test for each time series, comparing the measure(s) value for the original time series at index 0 to the other values of the resampled time series at the other indices. | |
Plot of measure vs parameter |
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This operation can be selected to plot a measure as a function of a varying parameter (at least two values of the specified parameter should exist) for selected time series. Then in one figure the graphs of the selected measure for the selected time series vs the measure specific parameter are superimposed. This is the classical visualization for the dependence of a measure on its parameter, allowing for superimposing for different time series. This operation can be applied only to measures bearing at least one varying parameters. | |
Plot of measure vs 2 parameters |
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This operation can be selected to plot a measure as a function of two varying parameters (at least two values of the each specified parameter should exist) for one selected time series. Then the surface of the selected measure and time series vs the two measure specific parameters is displayed in a three dimensional (3D) plot. This 3D plot visualizes the dependence of the measure on its two parameters, so it can be applied only to measures bearing at least two varying parameters. | |
Plot of measure1 vs measure2 |
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This operation can be selected to make a scatter plot of two measures for en ensemble of selected time series. Then in a 2D plot the scatter of points, one for each time series, for the pair of the two selected measures will be shown. This visualization is particular useful to identify graphically cluster of time series with respect to the two selected measures. | |
3D scatter plot of measures |
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This operation can be selected to make a scatter plot of three measures for en ensemble of selected time series. Then in a 3D plot the scatter of points, one for each time series, for the triple of the three selected measures will be shown. This visualization is particular useful to identify graphically cluster of time series with respect to the three selected measures. | |
Exit |
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By pressing this button all figures generated by any of the above operations will be deleted, the window will be gone. | |
Help |
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This file will be shown |