Directional derivative question

In summary, the conversation discusses the concepts of level curves and directional derivatives. The speaker is initially confused about the meaning of level curve and the concept of gradient in a direction. However, through further explanation, they come to understand that the level curve is the contour lines on a 2D map and the gradient in a direction represents the rate of change along a line. The speaker also mentions that they initially did not properly understand these concepts, but after further explanation, they are now able to grasp the concepts and complete their work.
  • #1
question dude
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0
attachment.php?attachmentid=262056&d=1389451604.jpg



I've done the first part, but I'm stuck on the second paragraph of the question. Maybe I'm being stupid, I don't even understand exactly what is meant by, 'the level curve'.

I also don't quite understand the whole concept of directional derivative. When it says, 'the gradient in the direction making an angle A with the x-axis, how should I think of this? what does the gradient mean in this context?

because when its just a simple curve/line on an xy axis, I know what the 'gradient' means, it is literally how much 'y' changes per unit x along that curve/line. But when I'm told about a 'gradient in a direction', I'm confused.
 
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  • #2
hey, question dude! :smile:
question dude said:
… what is meant by, 'the level curve'.

think of the 3D graph, z = f(x,y)

you can make a 2D contour map showing the lines of equal height

those contours are the level curves :wink:
I also don't quite understand the whole concept of directional derivative. When it says, 'the gradient in the direction making an angle A with the x-axis, how should I think of this? what does the gradient mean in this context?

the directional derivative in the direction (cosθ,sinθ) is df(kcosθ,ksinθ)/dk

it's the rate at which f increases if you go along the line y/x = tanθ :smile:
 
  • #3
question dude said:
attachment.php?attachmentid=262056&d=1389451604.jpg



I've done the first part, but I'm stuck on the second paragraph of the question. Maybe I'm being stupid, I don't even understand exactly what is meant by, 'the level curve'.

I also don't quite understand the whole concept of directional derivative. When it says, 'the gradient in the direction making an angle A with the x-axis, how should I think of this? what does the gradient mean in this context?

because when its just a simple curve/line on an xy axis, I know what the 'gradient' means, it is literally how much 'y' changes per unit x along that curve/line. But when I'm told about a 'gradient in a direction', I'm confused.

You are supposed to show your work, confused or not (those are PF rules). I don't see how you can have done the first part (which involves directional derivatives) but then claim you do not understand directional derivatives. I would need to see your work in order to grasp what is going on.
 
  • #4
tiny-tim said:
hey, question dude! :smile:


think of the 3D graph, z = f(x,y)

you can make a 2D contour map showing the lines of equal height

those contours are the level curves :wink:


the directional derivative in the direction (cosθ,sinθ) is df(kcosθ,ksinθ)/dk

it's the rate at which f increases if you go along the line y/x = tanθ :smile:

Thanks a lot! I understand what's going on now. Before I was just plugging in the numbers without knowing the concepts properly.
 
  • #5
Ray Vickson said:
You are supposed to show your work, confused or not (those are PF rules). I don't see how you can have done the first part (which involves directional derivatives) but then claim you do not understand directional derivatives. I would need to see your work in order to grasp what is going on.

Sorry about that, what I meant to get across, was that I understood the method in a sort of algorithmic way, but didn't understood the reason behind steps due to not understanding some basic stuff like 'level curve'. Anyway its sorted now.
 

Related to Directional derivative question

1. What is a directional derivative?

A directional derivative is a measure of how a function changes in the direction of a given vector at a given point. It represents the instantaneous rate of change of the function in that direction.

2. How is a directional derivative calculated?

The directional derivative is calculated using the dot product of the gradient vector of the function and the unit vector in the direction of interest. This can be represented mathematically as Df(x,y) = ∇f(x,y) · u, where ∇f(x,y) is the gradient vector and u is the unit vector in the desired direction.

3. What is the difference between a partial derivative and a directional derivative?

A partial derivative represents the rate of change of a function with respect to one of its variables, while a directional derivative represents the rate of change of a function in a specific direction at a given point. In other words, the partial derivative considers all possible directions, while the directional derivative only considers one specific direction.

4. What is the significance of the directional derivative in real life?

The directional derivative is useful in many applications, such as physics, engineering, and economics. It can be used to determine the steepest slope of a terrain, the direction of maximum wind force, or the most profitable direction for a business to expand in.

5. How is the directional derivative related to the gradient?

The gradient is a vector that contains the partial derivatives of a function with respect to each of its variables. The directional derivative is the dot product of the gradient and a unit vector in the desired direction. Therefore, the directional derivative is a scalar multiple of the gradient and represents the magnitude of change in that direction.

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