Don't use the Jacobian for prediction

[leouieda]

All gridders create a Jacobian matrix to make predictions (using a dot product with the estimated parameters). This is very inefficient with regards to memory. Generating largeish grids requires a huge amount of RAM.

Replace these with a for loop summation. Accelerate them with numba to achieve the same performance. The pure Python version is slower than the dot product but at least it won't blow up memory.

Reminders

• Run make format and make check to make sure the code follows the style guide.
• Add tests for new features or tests that would have caught the bug that you're fixing.
• Add new public functions/methods/classes to doc/api/index.rst.
• Write detailed docstrings for all functions/methods.
• If adding new functionality, add an example to the docstring, gallery, and/or tutorials.