Splines | Simple Quadratic/Cubic curve implementations in Unity | Game Engine library

A chart needs to be plotted with smooth shape, so XYSplineRenderer is used. Also, the NumberAxis needs to be autoranged to the segment of data.

But in some cases when the spline is calculated, some spline values are out of the autorange segment and the curve is not plotted entirely.

Seems that the autorange is evaluated before the spline is calculated.

To mitigate it, I have adjusted the range of the vertical axis by increasing this range by a percentage of the range limits. But this leads to inaccurate curve fitting to charts, since depending of the data input the percentage could be up to 25%.

I am checking out the mgcv package in R and I would like to know how to update a model based on new data. For example, suppose I have the following data and I am interested in fitting a cubic regression spline.

I fitted a glm model and had to transform some variables with log1p. I now want to create a ggpredict plot with a backtransformed scale. I transformed the variables before using the glm function.

here's a sample of a few variables of my original data and my code:

So I have the following data. In this dataframe I have a username, date, and a list of packages. My goal is to transform that column packages into a format I can analyze.

wanna ask one question: I have two classes A and B, few data types can only be defined in class B, but A as a higher level class also need use these data types defined in class B. So, I defined a template function in class A, named define_spline(), I can using robot_1 (i.e., class B) class's pointer to passing the type, but what I want is the class A can have a member object of these types defined in B class (robot_1 struct sp{}). I try to write a template class for whole A, named A2, but I got error 'rp1 is not a type name', why this is ok in class A define_spline() function, but not work for class A2 ? and what's the correct way to do so?

I'm using graphviz to visualize an AST tree in a compiler project I'm doing but a big problem with this is that the trees can get quite large, with some nodes having a lot of children. What this causes to happen is some parent nodes will be hugely separated from their parents, because their children force them to.

It looks like this:

My question is, is it possible to make it so that all nodes with only one child stay directly above the node below it? So, the "decl f" node will be right above the "assignment" node, while that assignment node stays directly above the "additive" node.

I tried to do this with invisible edges and strong weights between, say in this case, the "decl f" and "additive" nodes, but that ends up offsetting the "assignment" node so it doesnt collide with the invisible edge.

The code is automatically generated, but I'll still put the output here. This output is for this graph:

I am a newbie in openmdao. Recently I am trying to implement a dummy wing optimization problem to learn openmdao. I have come up with a weird problem that I wanted to ask about. I am using a bspline to define twist and t/c distribution. The optimization setup is working when I use COBYLA, DifferentialEvolution or DOEdriver as the driver. But when I set SciPy SLSQP, the control points for these splines does not change during iterations. What could be the problem?

Below is the main section where I define the problem...

I created a series of 5 scipy cubic spline (interpolator type) objects as follows:

I can construct a spline of some 2-D data and query area integrals quite easily with scipy.interpolate.RectBivariateSpline. But there is not a function for easily/quickly calculating line integrals over such splines.