The explanatory text "Note that the matrix first element-wise multiplied by 3." is very unclear.
Also, looking at it from a Python novice, it is not clear we were supposed to know that the .prod() operator can act on something that is not purely a named variable, but can work on an already manipulated quantity within parentheses.
Also, and this is not your fault but of Python's, but it is not clear (or merits some explanation) why some operators take the form "operator(x)" while others behave like "x.operator" or even "x.operator()" with no argument.
I've simplified question 9 to just `m.prod()` from the previous solution of `(m * 3).prod()` for now.
Re: Methods vs. functions — I completely agree! I actually originally implemented Math to Code using Tensorflow.js (which was simpler than using a Python interpreter) where the syntax was:
m.pow(2).sum().sqrt()
Vs. np.sqrt((m ** 2).sum())
I decided to go with NumPy + Python because I felt it would be more immediately applicable vs. just learning the Tensorflow.js syntax. Also Python allows operator overloading so you can just do `2 * m` vs. `m.mul(2)`.PyTorch has a similarly clean syntax to Tensorflow.js and includes operator overloading, but there doesn't seem to be a PyTorch shim for Skulpt, but that would be a fun project.
Also, my difficulty with numpy isn't applying functions to arrays, it's seeing __repr__ of a multi-dimensional arrays and grokking what it's showing me.
Site worked well on both my iphone and pc btw.
I'd like to more clearly show the answers / I originally didn't show what the test inputs (e.g. if square root is tested with 25, 9, and 4) so you couldn't just return 5 if 25, 3 if 9, etc... but I could display some of the test inputs and not all of them.
It definitely would be great to show the intermediate results of the calculations and for things like matrix multiplication `a.dot(b)` isn't very complicated, but it doesn't give you intuition on what's happening under the hood.
Thanks for the iPhone feedback — I tried my best to make sure it worked well on mobile. The few examples I could find of interactive Python tutorials usually involved spinning up a VM with multi-second lag for each question and textareas which were not at all mobile-optimized so I wanted to try and do something better :-).