xdata | Data validator for the zen of python | Validation library

However, I start to be curious why nm gives different marks on Cygwin than on Ubuntu?? and Why linker on Cgywin can handle two T definitions correctly?

You need to understand that the nm output does not give you the full picture.

nm is part of binutils, and uses libbfd. The way this works is that various object file formats are parsed into libbfd-internal representation, and then tools like nm print that internal representation in human-readable format.

Some things get "lost in translation". This is the reason you should ~never use e.g. objdump to look at ELF files (at least not at the symbol table of the ELF files).

As you correctly deduced, the reason multiple max() symbols are allowed on Linux is that the compiler emits them as a W (weakly defined) symbol.

The same is true for Windows, except Windows uses older COFF format, which doesn't have weak symbols. Instead, the symbol is emitted into a special .linkonce.$name section, and the linker knows that it can select any such section into the link, but should only do that once (i.e. it knows to discard all other duplicates of that section in any other object file).

So far, I've found adding the following code (from here) in a cell above the cell you have beginning with %matplotlib notebook works:

You need to include information about the sigma information of each Gaussian. When you say percentage coming from each population, I think you are asking about the total counts (integral) in each Gaussian. For a Gaussian in your form, the integral is:

The main problem is that you never redraw the canvas, so every change you communicate to matplotlib will not appear in the figure generated by the backend. You also have to update the properties of the rectangles representing the bars - you tried this with bar.set_color() in one of the versions which changes both facecolor and edgecolor, intended or otherwise.

I added more than you asked for to try and solve this, so I hope the extra steps are helpful or insightful. I also don't have xlsx since I don't have java, so I used openxlsx instead.

I can spot a few issues with your current code. For example, your reactive has an observeEvent in it, which observes the ws_var input, and is meant to update the worksheet names based on when a worksheet is selected. It might work better if you observed the xls_input instead.

What I provided may be a bit more robust. I added show/hide features using shinyjs, seeing as each step is dependent on the previous step. Meaning the following step will only show when the previous is selected. Additionally, not all columns in the tables are numeric. For output$calc, it will try and sum those characters which for me causes a problem. So I added an if statement which will look to see if the column is numeric or not (which uses dplyr)

Thanks to suggestions I've found the best fit and I think it can't be better.

The solution is:

You get the index of the closest point to x = -2.31 using numpy.searchsorted.

You have the arguments to np.trapz reversed. It should be

Check help time_specifiers. Your year it 2 digits %y not 4 digits %Y. The double quotes will make your date/time the first column. No need for extra double quotes in the format.

With the syntax set xdata time and set timefmt "..." you have only one format in the plot command. If you are using the syntax timecolumn() (check help timecolumn) you can use different input time formats in your plot command.

Note: the format %p as input format has been introduced in gnuplot 5.4.0 For older versions you have to use a workaround, see e.g. gnuplot: how to convert 12h time format into 24h time format?

Code: