Beojan Stanislaus
Beojan Stanislaus
Does rootpy have any RDataFrame support? For example, getting RDataFrame produced histograms as rootpy `Hist`s.
Currently, standout frames aren't automatically plain by default, so they get a frame number printed in the footline. Maybe they should be automatically plain.
I'm trying to use the text font for Greek letters in math. Following the font override code in Beamer, I have: ```latex \AtBeginDocument{% \DeclareMathSymbol{\Gamma}\mathalpha{pureletters}{"0394}% \DeclareMathSymbol{\Delta}\mathalpha{pureletters}{"0395}% \DeclareMathSymbol{\Theta}\mathalpha{pureletters}{"0398}% \DeclareMathSymbol{\Lambda}\mathalpha{pureletters}{"039B}% \DeclareMathSymbol{\Xi}\mathalpha{pureletters}{"039E}% \DeclareMathSymbol{\Pi}\mathalpha{pureletters}{"03A0}% \DeclareMathSymbol{\Sigma}\mathalpha{pureletters}{"03A3}%...
The unumpy vectorized functions are *extremely* slow. This seems to be because the uncertainty propagation seems to be repeated for every element rather than simply being done once.
# Description Resolves #1265 This PR uses SciPy's TOMS748 implementation to autoscan for the upper limit. @alexander-held's suggestions about memoizing the objective function and determining the best brackets for each...
The numexpr-3.0 branch hasn't been updated in a year. Is it still going to be released, or is it abandoned?
Numexpr would benefit from a flake8 plugin that checks code in `ne.evaluate` calls, and silences warnings about unused variables that are in fact used in numexpr code.
The online documentation at https://xtl.readthedocs.io/en/latest/ contains only installation instructions and the changelog. API documentation is missing.
## Description As stated [here](https://github.com/wspr/unicode-math/issues/189#issuecomment-460231546), there is no way to request an additional font to be used as fallback if glyphs are missing in the main math font. The best...
Is there a way to limit parameters to integers only? I'm currently rounding the parameter in the objective function, but this leads to the same value being evaluated multiple times.