In this video, we'll talk about slicing data for visualization
in SimBiology.
And for this, we'll use a model of the SGLT2 inhibitor that
contains 16 species and about 15 on custom parameters.
While all of them are important for the overall dynamics
of that system, you might only be
interested in a subset of them for visualization.
For instance, after a single simulation,
you might be interested in generating several plots
to gather time courses that belong together.
In this example, the plot from the top
shows this time course as related to the PK.
It displays the concentration of the inhibitor in the plasma
and in the GI tract.
The second plot shows us time courses related
to the PD part of that model.
It displays the glucose production and utilization.
The last plot shows us the AUC of the urinary glucose
excretion over a time period of 24 hours, which
might be a good biomarker to take decisions
based on simulations.
This type of slicing and visualization
is not only important for simulation data,
but also for experimental data.
For instance, you might want to slice your experimental data
depending on covariate values, like on these plots.
So let's go ahead and reproduce those plots together
in SimBiology.
We will start with the simulation data,
and for this I'll open a program I just preconfigured
focusing on simulation.
So I can now go ahead and click Run to run the simulation
and generate the default plot.
By default all states that have been logged in that program
will be displayed on a single plot.
So potentially I could go back to that program,
click on States to Log, and uncheck
any of the states I would like to hide in that plot,
Another option would be to go to the Property
Editor of that plot and uncheck the responses I
would like to hide.
A third option would be to select the responses
in that list, and I could perform multiple selection
by pressing Ctrl and click right to delete the responses.
The last option would be to start from a blank plot.
For this I'll click on New Plot, go
to the workspace of my program and our last run
and the results, and there select the states
I would like to visualize.
So I can perform multiple selection by pressing Ctrl
and drag and drop them on that plot to visualize the five time
courses I wanted to display.
So now I can go to the response list
and select time courses that belong together.
Click right and create a new set.
This will display them in a new subplot.
Can now go ahead and do the same for the AUC,
and now I have the configuration I wanted.
So I can change the name of those sets
to give them a meaningful name.
I can change, potentially, the color
of any of the time course.
I can also go to the Plot Settings
and give a title to this plot or change any other settings,
like the scale of the access or the grading, for instance.
Once I'm happy with those plots, I can go back to the plot,
click right to export this plot to a MATLAB figure that can now
be saved to any file format I need for documentation
or publication.
So please remark that by default,
the sets were sliced vertically and the responses by color.
But I can change this with any of the styles that
is here available.
So I could slice in a grid, horizontally,
vertically, by color, using line style or transparency.
So for instance, I could use line style for the responses.
This might be useful for publication in black and white.
It's important to understand that those plots are now
linked to my program.
So let me first revert back to color, go back to my program
and change any of the settings like the dosing
of the inhibitor, and I click here on overlay results
to see both front and keep the last results
of the last simulation.
Now, both plots-- plot one and plot two--
will be updated with the new results.
So as you can see, there is now the possibility
to slice by scenarios.
Those scenarios are my both runs.
Run with dosing run one and run without dosing, run two.
While on the table at the top I can choose the style
for slicing, at the bottom I can define the parameters
or properties of the style.
But of course, I can change the style of the slicing.
So here, the scenarios are displayed in different line
style, but I could also choose horizontal to get
two different columns--
the first one from run one with dosing,
and the second one for run two without dosing.
The same type of slicing can be used for a parameter scan.
For instance, if I run a parameter scan
with two parameters, those two parameters
will appear in the list of slicing properties.
In this example, I chose a vertical style
for the first parameter of the scanning,
and horizontal for the second parameter of this scan.
So now, I get the plot matrix with all parameter combinations
that were used for scanning.
This type of slicing is not only interesting for simulation
data, but also for experimental data.
I've here a data set that I will display in a data sheet first.
This data set contains a grouping variable,
it contains a time column, a dosing variable,
it contains one column for measurement,
and two covariates.
So now I'll go ahead and create a plot for this data.
So I click on New Plot to create a blank plot
and drag and drop this data set on this plot.
So by default, the scenarios will be the grouping variable,
and they will be used for slicing using color.
This is visible in the first table in the Property Editor.
But as you can see now, I have also
the other columns-- dosing columns and covariates--
as slicing properties available.
So for instance, I might not be interested in having
different groups in a different color.
So I remove the color style for scenarios,
and instead use this color for Apgar, my covariate.
I could also use a style for weight.
In this case, I chose grid to have different ridges
of rates in a different plot.
So since our covariates are continuous by nature,
SimBiology will bend them into ranges.
By default, the number of bends is set to four,
but I can change this number.
Here for weight, this will create, then, six subplots.
So now please go ahead and discover
the best way to visualize your data in SimBiology.