eCAD | working based

I'm just trying to understand an example of WPF treeview.

My goal ist to populate a treeview with some items, stored in a List.

This is the example:

I have been able to generate the all permutation of length 4 from a string, the problem that I am facing now is that all the permutation have duplicates like {abcd) ,{adbc},{bcda}...which are all same as from Mathematical definition of set.

Is there a short version in java-8 where I can get the pure set?

My code that generated the all permutation:

Shall we use SVN or GIT? for the following use case

How shall we organize the system:

1: "master repo" containing all the projects and stand alone drivers as that the projects use, each project / driver being a different "branches"?

example:

I looked through the suggestions but could not find the likes of my error. I ran into this with vs141 and fixed it, I believe by changing the c++ ISO Standard in VS. I may have been too hasty in uninstalling VS2017 when I installed VS2019, so I can't go back to see what I did. It just works with vs140 which I do still have installed. This code will produce the vs142 error:

I am trying to use for loops (or the apply function as an alternative) to extract coordinates from a data.frame, search for the closest point within the E-OBS gridded dataset, extract the temperature-data for time x1-x2 and write it to another excel file.

While the code works to extract single data points, I seem unable to include this code within a loop and to add the results potentially next to the input-coordinates.

I have 2 C# datatables, the master(datatable1) that I want too update has many rows but the second contains only a few unique rows. Below is what I am trying to achieve.

I have searched to find a way to do this with loops and LINQ but none seem to update the ECAD column.

I tried this.

I have raster gridded data of Germany' historical daily temperature observation (15 years' historical daily mean temperature) in large RasterBrick object. Here is how my raster gridded data look like:

I have faced several challenges when I am dealing with very large RasterStack object in R. Here is the main story, I have downloaded gridded data from European Climate Assessment website(download site of gridded data and download link of gridded data that I am interested in). So my very first step was importing this data in R as RasterStack object. Then I intended to crop raster grid of only particular countries, so I used raster::crop to do that. My ultimate goal is to calculate the annual average temperature for each grid cell. Here is the grid coverage that I cropped from original raw RasterStack object where grid resolution is defined as 0.25-degree resolution:

Here is the R script that I took a shot:

I am wondering dplyr provide any useful utilities to conduct quick data aggregation on land surface temperature time series. However, I already extracted gridded data of Germany from E-OBS dataset (E-OBS grid data) and rendered this extracted raster grid in tabular data with excel format. Now, in newly exported data, data has shown with a respective geo-coordinate pair with 15 years temperature observation (1012 rows ,15x365/366 columns). Plase take a look the data on the fly: time series data.

Here is what I want to do, the data on the fly time series data, I want to do data aggregation by year because original observation was done by daily level observation. In particular, each geo-coordinate pair, I intend to calculate an average yearly temperature for each year and all operation goes to 15 years. More specifically, after the aggregation done, I want to put the result in new data.frame where original geo-coordinate pair come along, but add new column such as 1980_avg_temp, 1981_avg_temp,1982_avg_temp` and so on. So I want to reduce data dimension by column, introducing new aggregation column where the yearly average temperature will be added.

How can I get this done by using dplyr or data.table for excel data? Any easier way to make this data aggregation operation on attached data on the fly time series data? Any thought?