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Nov 8, 2019 at 19:45 comment added ali Perfect. It's all clear now. I had missed the capital F function.
Nov 8, 2019 at 17:44 history edited Simon F CC BY-SA 4.0
Further remarks
Nov 8, 2019 at 17:22 comment added Simon F But you are building a surface in 3D. I'll add another note
Nov 8, 2019 at 14:24 comment added ali "but for a surface, if a given first (partial) derivative is non-zero then it also is locally tangential...". I am not making a fuss :) but your argument already assumes partial derivative to be a vector(otherwise it won't be tangential) whereas I think it is scalar.
Nov 8, 2019 at 11:05 history edited Simon F CC BY-SA 4.0
Added some more explanatory notes
Nov 8, 2019 at 10:56 comment added Simon F "I thought derivative is the rate of change of "function value" with respect to one of its arguments" That is indeed correct. But for a surface, if a given first (partial) derivative is non-zero (which is guaranteed in your case because of the way you construct the surface), then it also is locally tangential to the surface. Further, we know your two partial derivates aren't parallel, so the cross product will construct a valid normal. (FWIW For some arrangements of control points, in more general use cases, you can get so-called 'degenerate' surfaces, but you're safe here)
Nov 7, 2019 at 22:43 comment added ali Thanks for the update. My math is not very good. I thought derivative is the rate of change of "function value" with respect to one of its arguments(unless it is a vector-valued function and you are assuming that the point S(x,y,z) is the function value); the gradient is a vector but not the partial derivatives, is that correct?
Nov 7, 2019 at 22:15 vote accept ali
Nov 7, 2019 at 11:03 history edited Simon F CC BY-SA 4.0
Responded to comment
Nov 6, 2019 at 23:41 comment added ali Thanks Simon. You mentioned that both partial derivatives are vectors(in i,j directions). could you write each vector components plz.
Nov 6, 2019 at 14:59 history answered Simon F CC BY-SA 4.0