Precalc | repo contains some code which can graph equations

I have a struct with some other structs as member. Both external and internal structs are StandardLayout (it can be even assumed that internal are plain old data). Something like this:

I am trying to update a status filed in a SharePoint list. Did some googling, found most of the examples are using an ID column to locate the list item, but my list doesn't have such column, only a windows login and a status columns. I am wondering what the XML would be like?

This is what I come up with, but it doesn't work:

Note on duplicate message:

Similar themes, not exactly a duplicate. Esp. since the loop is still the fastest method. Thanks.

Goal:

Upscale an array from [small,small] to [big,big] by a factor quickly, don't use an image library. Very simple scaling, one small value will become several big values, after it is normalized for the several big values it becomes. In other words, this is "flux conserving" from an astronomical wording - a value of 16 from the small array spread into a big array's 4 values (factor of 2) would be 4 4's so the amount of the value has been retained.

Problem:

I've got some working codes to do the upscaling, but they don't work very fast compared to downscaling. Upscaling is actually easier than downscaling (which requires many sums, in this basic case) - upscaling just requires already-known data to be put in big chunks of a preallocated array.

For a working example, a [2,2] array of [16,24;8,16]:

16 , 24

8 , 16

Multiplied by a factor of 2 for a [4,4] array would have the values:

4 , 4 , 6 , 6

4 , 4 , 6 , 6

2 , 2 , 4 , 4

2 , 2 , 4 , 4

The fastest implementation is a for loop accelerated by numba's jit & prange. I'd like to better leverage Numpy's pre-compiled functions to get this job done. I'll also entertain Scipy stuff - but not its resizing functions.

It seems like a perfect problem for strong matrix manipulation functions, but I just haven't managed to make it happen quickly.

Additionally, the single-line numpy call is way funky, so don't be surprized. But it's what it took to get it to align correctly.

Code examples:

Check more optimized calls below Be warned, the case I have here makes a 20480x20480 float64 array that can take up a fair bit of memory - but can show off if a method is too memory intensive (as matrices can be).

Environment: Python 3, Windows, i5-4960K @ 4.5 GHz. Time to run for loop code is ~18.9 sec, time to run numpy code is ~52.5 sec on the shown examples.

% MAIN: To run these

trying to pass list items(PreCalc) into a simple function. trying to covert the list into a tuple version (calc) and then call the function.

Get the error message: TypeError: 'tuple' object is not callable

How can I pass my inputs() into the function?

I try to implement a multiple “if - else” statements in a JQuery code. It is about calculating an exam marks and divide the results into groups. There is obviously a mistake in the second function (the first one alone works just fine), but I could find it :( maybe I use wrong the “if - else” function.

Thank you for the help in advance.

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