Scatter plots, Regression lines and Curve fits are all referred to as 窶弭Y-plots窶. Such plots are produced using data from a pair of data nodes.
DynRisk allows you to produce any combination of the three XY-plot types in the same diagram.
Moreover, you can copy curves from one plot window and paste it into another using the 窶廚opy窶 and 窶弃aste窶 commands in the 窶廢dit窶 menu. If you do this, make sure that both plots have the same scale on both the X-axis and the Y-axis by using the 窶彜et scale窶 command.
Note also that you can add 窶徃ridlines窶 to the plots corresponding to certain key statistics for the data nodes. Specifically, you can have gridlines indicating the location of the following statistics:
窶｢ Base value
窶｢ Mean ﾂｱ st.dev.
窶｢ Fractiles
The fractiles are chosen according to the currently selected fractile set. You can change this using the 窶廡ractiles窶ｦ窶 command.
To display the gridlines, click anywhere in the plot window while pressing the 窶廚ommand窶 key on the keyboard. This will bring up a popup menu from which you could select the desired statistics. To hide the gridlines, just repeat the same procedure.
Scatter plot
A 窶彜catter plot窶 is a graph consisting of a 窶彡loud窶 of points reflecting the joint distribution of a pair of data nodes. Each point in the cloud represents corresponding values of the two data nodes from a single simulation. So if you make a 窶彜catter plot窶 from a simulation data file where each data node contains say 1000 values, then the plot will show a cloud of 1000 points. If the points are spread all over the diagram with no particular structure, this indicates that there is no dependence between the two variables. In particular the correlation between the two data nodes is neglectable. On the other hand if the points are clustered around a straight line, the correlation may be significant. If the points are clustered closely around some nonlinear curve, the correlation may be small. Still there appears to some sort of dependence between the two data nodes.
If the frontmost window is a main document window for a simulation data file, the 窶彜catter plot窶 button produces scatter plots for all selected pairs of data nodes. To select a pair of data nodes, select the first one whose values should appear along the X-axis in the 窶廡irst selection窶 mode, and the second one whose values should appear along the Y-axis in the 窶彜econd selection窶 mode.
If the frontmost window is an 窶弭Y-plot窶 window created by using the 窶彜catter plot窶 button, this button is disabled. In this case the window title is of the form:
<node1>(x) <node2>(y).scat
where <node1> is the name of the node whose values appear along the X-axis and <node2> is the name of the node whose values appear along the Y-axis.
If the frontmost window is an 窶弭Y-plot窶 window created by using either the 窶彝egression line窶 button or the 窶廚urve fit窶 button, the 窶彜catter plot窶 button is used to either hide or show a 窶彜catter plot窶 depending on the state of the window. If the plot already contains a scatter plot, you can use the 窶彜catter plot窶 button to hide this scatter. On the other hand, if the plot does not contain a scatter plot, then you can use the 窶彜catter plot窶 button to show it.
Regression line
A 窶彝egression line窶 is a graph that represents a best linear approximation to the relation between two data nodes. To see how well this line describes the 窶徨eal窶 relation between the data nodes, you can view the regression line in the same diagram as a scatter plot. If the points are clustered closely around the regression line, the linear approximation is good. You can also compare the regression line to a curve fit. If there is a strong linear relation between the data nodes, then the regression line and the curve fit will be similar. In such cases, you do not gain much by using a more flexible (and thus also more complex) functional relationship as offered by the curve fit.
If the frontmost window is a main document window for a simulation data file, the 窶彝egression line窶 button produces regression lines for all selected pairs of data nodes. To select a pair of data nodes, select the first one whose values should appear along the X-axis in the 窶廡irst selection窶 mode, and the second one whose values should appear along the Y-axis in the 窶彜econd selection窶 mode.
If the frontmost window is an 窶弭Y-plot窶 window created by using the 窶彝egression line窶 button, this button is disabled. In this case the window title is of the form:
<node1>(x) <node2>(y).reg
where <node1> is the name of the node whose values appear along the X-axis and <node2> is the name of the node whose values appear along the Y-axis.
If the frontmost window is an 窶弭Y-plot窶 window created by using either the 窶彜catter plot窶 button or the 窶廚urve fit窶 button, this 窶彝egression line窶 button is used to either hide or show a 窶彝egression line窶 depending on the state of the window. If the plot already contains a regression line, you can use the 窶彝egression line窶 button to hide this regression line. On the other hand, if the plot does not contain a regression line, then you can use the 窶彝egression line窶 button to show it.
Curve fit
A 窶廚urve fit窶 is a graph that attempts to describe the functional relation between two data nodes. To see how well this curve describes the 窶徨eal窶 relation between the data nodes, you can view the curve fit in the same diagram as a scatter plot. If the points are clustered closely around the curve fit, there is a strong functional relation between the two data nodes. You can also compare the curve fit to a regression line. If there is a strong linear relation between the data nodes, then the regression line and the curve fit will be similar. In such cases, you do not gain much by using a more flexible (and thus also more complex) functional relationship as offered by the curve fit.
DynRisk calculates the curve fit by modeling the relation between the two data nodes as a so-called Gaussian process. You can control how this is done by adjusting parameters such as 窶彝esolution窶, 窶彜moothness窶 and 窶彜ensitivity窶. To do this you select the node you want to adjust the parameter settings for and then use the 窶廚urve fit settings窶ｦ窶 command.
If the frontmost window is a main document window for a simulation data file, the 窶廚urve fit窶 button produces curve fits for all selected pairs of data nodes. To select a pair of data nodes, select the first one whose values should appear along the X-axis in the 窶廡irst selection窶 mode, and the second one whose values should appear along the Y-axis in the 窶彜econd selection窶 mode.
If the frontmost window is an 窶弭Y-plot窶 window created by using the 窶廚urve fit窶 button, this button is disabled. In this case the window title is of the form:
<node1>(x) <node2>(y).gf
where <node1> is the name of the node whose values appear along the X-axis and <node2> is the name of the node whose values appear along the Y-axis.
If the frontmost window is an 窶弭Y-plot窶 window created by using either the 窶彜catter plot窶 button or the 窶彝egression line窶 button, the 窶廚urve fit窶 button is used to either hide or show a 窶廚urve fit窶 depending on the state of the window. If the plot already contains a curve fit, you can use the 窶廚urve fit窶 button to hide this curve fit. On the other hand, if the plot does not contain a curve fit, then you can use the 窶廚urve fit窶 button to show it.
