For aliasing, in C, there's the restrict keyword, although it isn't used that often. If you take a look at BLIS or even BLAS, restrict isn't used. C++ doesn't have restrict, but that hasn't stopped the development of great numerical linear algebra libraries like Eigen or Armadillo.
C++ has had std::complex for... forever. And C99 has support for complex numbers.
Range types are handy, but not having them typically isn't a show stopper when designing libraries of numerical kernels. They are more useful for high-level prototyping, a la MATLAB. Nevertheless, it's not that hard to emulate the behavior using a well-designed API in C, or operator overloading in C++.
The only parallelism that Fortran has that C or C++ lack is co-array Fortran. I haven't used it myself, so can't speak to how useful it is. Both C and C++ have many options for parallelism: pthreads, OpenMP, MPI, C++'s parallel stuff, and tons of other libraries.
I'm not sure what "robust structured/procedural programming" is. I think Fortran is at a clear disadvantage compared to C and C++, here. The amount of boilerplate needed to define a function in Fortran is pretty painful. Fortran's control flow is a subset of C and C++'s, so any style of structured or procedural programming you would do in Fortran can obviously be done in C and C++.
And of course, numpy (and similar) call out to Fortran, but they call out to loads of C and C++, too!
This isn't to say Fortran is a bad language. I work with people who use it and prefer it. But the reasons you pointed out simply aren't valid. A good reason to use Fortran: you work in a group where Fortran is the language that's used and you want to be able to contribute to what's going on!
For aliasing, in C, there's the restrict keyword, although it isn't used that often. If you take a look at BLIS or even BLAS, restrict isn't used. C++ doesn't have restrict, but that hasn't stopped the development of great numerical linear algebra libraries like Eigen or Armadillo.
C++ has had std::complex for... forever. And C99 has support for complex numbers.
Range types are handy, but not having them typically isn't a show stopper when designing libraries of numerical kernels. They are more useful for high-level prototyping, a la MATLAB. Nevertheless, it's not that hard to emulate the behavior using a well-designed API in C, or operator overloading in C++.
The only parallelism that Fortran has that C or C++ lack is co-array Fortran. I haven't used it myself, so can't speak to how useful it is. Both C and C++ have many options for parallelism: pthreads, OpenMP, MPI, C++'s parallel stuff, and tons of other libraries.
I'm not sure what "robust structured/procedural programming" is. I think Fortran is at a clear disadvantage compared to C and C++, here. The amount of boilerplate needed to define a function in Fortran is pretty painful. Fortran's control flow is a subset of C and C++'s, so any style of structured or procedural programming you would do in Fortran can obviously be done in C and C++.
And of course, numpy (and similar) call out to Fortran, but they call out to loads of C and C++, too!
This isn't to say Fortran is a bad language. I work with people who use it and prefer it. But the reasons you pointed out simply aren't valid. A good reason to use Fortran: you work in a group where Fortran is the language that's used and you want to be able to contribute to what's going on!