silhouette | Experimental Raytracer Written in C to Render STL Files | Graphics library

I have a stacked area chart built in d3.js and I want to update how the data is displayed on a button click-- showing absolute numbers, relative numbers, and displaying the data as a silhouette. I have worked out how to create these three formats with my data, but when I update the chart, it redraws it rather than updating the stacked areas. I'm not able to see what I'm doing wrong. I would greatly appreciate if someone could help!

My code is below, and can also be viewed in this Plunker: https://plnkr.co/edit/Y5zmRLnSJu0SALj3?open=lib%2Fscript.js

I’am trying to classify bivariate point patterns into groups using spatstat. The patterns are derived from the whole slide images of lymph nodes with cancer. I’ve trained a neural network to recognize cells of three types (cancer “LP”, immune cells “bcell” and all other cells). I do not wish to analyse all other cells but use them to construct a polygonal window in the shape of the lymph node. Thus, the patterns to be analysed are immune cells and cancer cells in polygonal windows. Each pattern can have several 10k cancer cells and up to 2mio immune cells. The patterns are of the type “Small World Model” as there is no possibility of points laying outside the window.

My classification should be based on the position of the cancer cells in relation to the immune cells. E.g. most cancer cells are laying on the “islands” of immune cells but in some cases cancer cells are (seemingly) uniformly dispersed and there are only a few immune cells. In addition, the patterns are not always uniform across the node. As I’m rather new to spatial statistics I developed a simple and crude method to classify the patterns. Here in short:

1. I calculated a kernel density of the immune cells with sigma=80 because this looked “nice” for me. Den<-density(split(cells)$"bcell",sigma=80,window= cells$window) (Should I have used e.g. sigma=bw.scott instead?)
2. Then I created a tessellation image by dividing density range in 3 parts (here again, I experimented with the breaks to get some “good looking results”).

Using the clustMixType package I'm trying to get the silhouette values of the following dataset using the example in page 13 here:

https://cran.r-project.org/web/packages/clustMixType/clustMixType.pdf

I have,

I am trying to replace some code which uses scipy.misc.imresize with skimage.transform.resize. However, I am struggling to understand some code which performs some math on the results:

I wanted to use a placeholder image. Unfortunately it's a mess in Inkscape.

The person who made it added a second layer (but Inkscape doesn't consider it a layer so I'm not entirely sure). The second layer adds a background-color. They did this because the nodes that make up the image of the cat are backwards! So when I set the fill it fills in the background behind the cat instead of the cat! So they basically added a second layer (or object?) to add color to the cat.

How do I inverse the nodes so that when I set the fill it fills in the background-color of the cat without the need for the second layer.

I basically want the cat to be black and the background to be transparent.

I have a sample dataset as following. all the features are categorical, and the label is binary of 0 and 1.

I applied decision trees for a classification problem. the question is how to print Dictionary named query_results containing accuracy, precision, recall and F1-score for each query in the evaluation set as {'query1':{'accuracy':value,'precision':value,...},'query2':{...}}

Expected Result:

I would like to implement functionality for being able to search a QPlainTextEdit for a query string, and display all matched lines in a table. Selecting a row in the table should move the cursor to the correct line in the document.

Below is a working example that finds all matches and displays them in a table. How can I get to the selected line number in the string that the plaintextedit holds? I could instead use the match.capturedEnd() and match.capturedStart() to show the matches, but line numbers are a more intuitive thing to think of, rather than the character index matches.

I am trying to see how some known labels explain, or are adjusted to the 2D representation from my data that I get from UMAP.

I tried to use silhouette function but the cluster information must be provided as a numeric vector and then these are the one that plot(sil) shows. Is there a way to use the cluster names or at least show these in the plot instead of the numbers? (similar question as here but instead of the sample labels I want to change the cluster labels)

For example: