mersenne-twister | Mersenne Twister pseudorandom number generator | Generator Utils library

I am trying to update Rcpp from 1.0.6 to 1.0.7 or 1.0.8. The Rcpp update is essential for a primary R library that I intend to use.

I looked at the documentation and tried to install Rcpp using:

I'm following Jan Kirenz tutorial for classification using Tidymodels. Everything so far has gone well until I try to evaluate the model using the function fit_resamples(). I keep getting the error message Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow" .

The code he uses in that section is:

I'm following a tutorial from Julia Silge (link here) on using tidymodels and recipes. I can get most of the way through without a problem but when I come to calling the fit_resamples() function I get the error: Error: The first argument to [fit_resamples()] should be either a model or workflow.

I'm copying the code in the tutorial character for character, and everything runs fine up to and including printing out validation_splits. But as soon as I call fit_resamples() I get the error above (link to relevant part of tutorial). If useful, the output of rlang::last_error() is:

I want to use some of the parameters of the original deepnet package, so I set up a custom model. I read Caret's documentation (Custom Model), but it doesn't work.

Here is my code for setting up the customized model:

I got hold on an SUPER-FAST algorithm that generates an array of random bytes, uniformly. It's 6 times faster than c++ uniform distribution and mersenne-twister of std library.

The count of an array is divisible by 4, so it can be interpreted as array of integers. Casting each entry to an integer, produces values in the range [INT_MIN, INT_MAX]. But how can I transform these integer values to lie between my own [min, maximum]?

I want to avoid any if-else, to avoid branching.

Maybe I should apply some bitwise logic, to discard irrelevant bits in each number? (because all remaining, unmasked bits will be either 0 or 1 anyway). If I can extract the most significant bit in my maximum-value, I could mask any bits that are more significant than that one, in my integers.

For example, if I want my max to be 17, then it is 00010001 in binary form. Maybe my mask would then look as 00011111? I could then apply it to all numbers in my array.

But, this mask is wrong ...It actually allows values up to (1+2+4+8+16) :(

What can I do? Also, how to take care of the min?

Edit

I am generating millions of numbers every frame of my application, for neural networks. I managed to vectorize the code using AXV2 for float variants (using this post), but need to get integers working too.

i have been provided middleearth.h/cpp and was asked to make a makefile, doxyfile (which i did correctly) and a topological.cpp that works but has a small mistake in the output and i need help with that please.ill provide all three files and the text we use to test and the error.

I am attempting to use a for loop to rename the rows and columns of a matrix via the following code:

I know that I can set the RNGversion with e.g.

I'm working with a >1 GB data set and running into out of memory ("Cannot allocate...") errors in ggplot2 graphing. In trying to research where all my memory is going (with the help of sources like this and this and this, I've discovered that the following code with dummy data causes significant memory usage that appears to be unclaimed in the Windows Task Manager even after repeated calls to gc().