tophat | A small , pragmatic , and flexible async HTTP server | Reactive Programming library

I am trying to answer this question: Create a function cubefit(xdata, ydata) (arguments in that order) that returns a numpy array of the best fit* parameters [A, B, C, D] that fit the list xdata of x values to the list ydata of y values, to a cubic equation of the form y= Ax^3 + B x^2 + C x + D

*where the fit is determined using a non-linear least-squares regression test (the default fit method of scipy's curve_fit() function)

This is my attempt:

WINTER BASH 2020 season is coming to an end, and I thought it would be instructive to figure out the CSS and other markup for generating the excellent logo shown here:

In the image below, the numbers indicate the desired objects for animation

Animation script:

1. Hat generator. Should move unevenly up and down

2. The question mark should float in space with a simultaneous change in size. What does the collection of information about the disclosure of the conditions for obtaining "secret hats" symbolize.

3. The balloon should wiggle evenly.

4. The small blue hat should move along the path of the word WINTER

5. Moon wiggle. Should start after completing point 4 of the scenario

6. The big blue hat moves forward in search of new hats. Some time after the start of step 6, hats should begin to fall from above.

7. Animation of stars, should start after finding all the hats.

I managed to implement the first point of the scenario.

Hat animation starts after clicking on the canvas

I am trying to extract blood network from this face image: Face image

For such task, i am using the P&M anisotropic diffusion found in this question: Anisotropic diffusion 2d images. Then i am using tophat transform followed by blackhat transform, afterwards i use a simple threshold to set to 255 all pixel that has an intensity value of 100.

The problem is that, after i use the threshold and try to open the image, whatever way i try, the image is displayed as fully black:

In short, my goal is to extract the blood vessels using P&M anisotropic diffusion with structuring element of flat disk of 5x5, then apply tophat and blackhat, respectively and a simple threshold and actually be able to view the image afterwards.

Here's my code on how i am trying it:

Hi I'm stuck trying to solve this: class Classy, to represent how classy someone or something is. "Classy". If you add fancy-looking items, "classiness" increases!

Create a method, addItem() in Classy that takes a string as input, adds it to the "items" array and updates the classiness total.

Add another method, getClassiness() that returns the "classiness" value based on the items.

The following items have classiness points associated with them:

1. "tophat" = 2
2. "bowtie" = 4
3. "monocle" = 5

Everything else has 0 points.

The sum is not performing correctly. The first problem is when it falls in te default case, everything is 0, I've tried in the default with:

So basically I'm not a web developer and I really don't know how to talk about this issue correctly. So I'm building an arrow selector which has many selection fields and I have a div with pictures, the pictures changes within a user-selected field, so right here I have some bugs which appear when the user tries to select some options. For example, if I would select one field of arrow color, the image in the div changes, but in the wrong container( Every selected image appears in same container )

My Selector BUG GIF example:

The website with the selector which is functions well, you can see that every select option works good with the image.

My JQuery code:

I'm trying to make selection options and I need to change the class of selected item which is selected (On mouse over), so basically I'm not a web-developer so I really don't know how to achieve this, I was trying to research for this, but I didn't succeed.

So I need two things, once the user mouse over the selected opinion the class of li changes to dk_option_current and once the user clicks on the selection I can do some future stuff, I really don't know how to achieve this, I may be using Javascript, but that's just a lot of work to do my myself.

I have trawled through the internet for a solution to this and I still don't understand why I am getting the following error message:

"Error: Main method not found in class DrumKit, please define the main method as: public static void main(String[] args) or a JavaFX application class must extend javafx.application.Application"

Here is my code:

DrumKit.java

Let X, Y be 2 random variables, with probability density functions pdf1 and pdf2.

Z = X + Y

Then the probability density function of Z is given by the convolution of pdf1 and pdf2. Since we can't deal with continuous distributions, we descritize the continuous distributions and deal with them.

To find the convolution of uniform distribution and normal distribution, I came up with following code.

Let's say I have an array of shape (100000,1), representing samples of variable X of uniform distribution between 0 and 1. I want to approximate the density of probability of this variable, and I use Scikit-Learn KernelDensity to do that.

The problem is I only get a result which is not normalized. The integral of probability density does not sum to 1. How should I do to normalize automatically ? Am I doing something wrong ?