lbvp.m and lbvp.py This code solves and then plots the solution of the linear BVP:
y'' + p(x)y' + q(x)y = f(x), for xL < x < xR,
where a0*y(xL) + b0*y'(xL) = c0 and a1*y(xR) + b1*y'(xR) = c1
Front Matter to the 3rd edition
Availability: the book is in production (i.e., Springer has it); it should be available in October
Answers to selected exercises
Contact Information Mark H. Holmes Department of Mathematical Sciences Rensselaer Polytechnic Institute, Troy, NY 12180 USA holmes (@rpi.edu) HomePageSpringer web page
Reviews of first edition
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Figures in Text
The following zip files contain codes for generating most of the figures in the text. Note that the Python files are direct conversions of the MATLAB files. I checked several of the Python codes and they all worked as expected. If you find any that don't work please let me know.
For the record, the conversion was done using ChatGPT. More importantly, if you are not a fan of MATLAB or Python, it is probably possible to convert the original MATLAB codes into almost any programming language with similar capabilities, such as Mathematica. In ChatGPT, I entered the command shown here, then dragged in a folder containing the MATLAB files for a particular chapter and pressed the Return key.
Extras
The following are MATLAB and Python files that I wrote to solve BVPs problems. A short explanation at the end of the file is provided on how to use the code.
nbvp.m and nbvp.py This code solves and then plots the solution of the nonlinear BVP:
y'' = f(x, y, y'), for xL < x < xR,
where y(xL) = yL and y(xR) = yR
sbvp.m and sbvp.py This code solves and then plots the solution of the nonlinear BVP:
ep*y'' = f(x, y, y', ep), for xL < x < xR,
where y(xL) = yL and y(xR) = yR