Jacobian directional derivative

In summary: But I think the equations are the same. Check that the signs are the same as in your equations.The ECEF to LL transformation is not the same as the Jacobian matrix, but the Jacobian matrix will be related to that. The Jacobian matrix is used in the calculation of the transformation matrix, but that is a different concept from the Jacobian matrix. I think it is not the same. I'm not sure. But the transformation matrix is not just the Jacobian matrix.Last edited by a moderator: May 8, 2017In summary, the conversation discusses the use of spherical coordinates and the directional derivative in the context of a sphere.
  • #1
rabbed
243
3
Hi

For a sphere:

x = r*cos(a)*sin(o)
y = r*sin(a)
z = -r*cos(a)*cos(o)

where r is radius, a is latitude and o is longitude, the directional derivative (dx,dy,dz) is the jacobian multiplied by a unit vector (vx,vy,vz), right? So i get:

dx = cos(a)*sin(o)*vx - r*sin(a)*sin(o)*vy + r*cos(a)*cos(o)*vz
dy = sin(a)*vx + r*cos(a)*vy
dz = -cos(a)*cos(o)*vx + r*sin(a)*cos(o)*vy + r*cos(a)*sin(o)*vz

Is this correct?

When I visualize this with a computer program I assume x to the right, y upwards and z into the screen.
I use (vx,vy,vz) := (0, cos(v), sin(v)) for an increasing angle variable v to get a unit length vector where vx = 0 because as I understand (vx,vy,vz) should be a vector in (r,a,o) space and r is not changing.

Then (dx,dy,dz) is pointing out from some point p on the sphere and rotate in a plane (seemingly) tangent to the sphere. When p is close to the poles, the length of (dx,dy,dz) seems to change as v goes from 0 to 2*pi, otherwise it looks like the length is more constant during a revolution around p.

Can someone expain if this is correct behaviour?
 
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  • #3
Does it really matter? The math is still the same, just with different expressions.
The aim of my question is to get intuition about jacobians and directional derivatives.
 
  • #4
I was thinking that the signs would be wrong and hence the directions so to me I'd want it to be correct.

My vector analysis is a bit rusty. I've been trying to figure out how to best answer your question but no luck yet. However, a math mentor should see this and comment shortly.
 
  • #5
Okay,
thanks jedishrfu
 
  • #7
I'm wondering how to picture it.

First, what space is the unit vector (vx,vy,vz) in? Since the number of columns in the jacobian and hence the number of dimensions in the unit vector comes from (r,a,o) space, I'm assuming it's a vector in that space.

Second, how does my choice of (vx,vy,vz) change (dx,dy,dz)? If (vx,vy,vz) is a vector in (r,a,o) space, does it make sense to think of it as (r,a,o) space or should I think of it as a new space with the same number of dimensions?
Does (dx,dy,dz) have the same direction as (vx,vy,vz)?
 
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  • #8
I'm puzzled by the original question. Normally a directional derivative is taken of some real-valued function on some space. I am not seeing a real-valued function anywhere.
 
  • #9
rabbed said:
I'm wondering how to picture it.

First, what space is the unit vector (vx,vy,vz) in? Since the number of columns in the jacobian and hence the number of dimensions in the unit vector comes from (r,a,o) space, I'm assuming it's a vector in that space.
I'll take a stab at it. This is much easier to keep track of if you stay with right hand systems and stick to some standard direction conventions. But I'll try to use your definitions. (vx,vy,vz) is in the "locally-level" coordinate system. It's called that because the XYll plane is tangent to the surface of the Earth at that latitude & longitude. (0,0,0)ll is the point on the surface of the Earth at that latitude & longitude. Yll points toward the North Pole (increasing latitude) and Xll points East (increasing longitude), and Zll points up from the center of the Earth. (This is a right-hand system, so I haven't checked the signs in your equations).

Then the (x,y,z) if your equations are in what is called the "Earth Centered, Earth Fixed" coordinate system. (0,0,0)ecef is at the center of the Earth. Yecef points to the North Pole. Xecef points to the intersection of the Equator and the Prime Meridian. Zecef points to a location in the Atlantic Ocean (I think).

I'm not sure if I got the details right, but I hope this gives you the idea.
 
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  • #10
FactChecker - Can I express it like this?
(vx,vy,vz) are coordinates in a cartesian coordinate system C placed inside the destination space.
C is placed at the point that we want to derivate on the surface and is rotated so that it's x-axis vector aims in the destination space direction where the first coordinate of the source space increases from that point, and similar for the other axes?
Was is possible to understand that?

zinq - I think both dx, dy and dz are directional derivatives, if I've understood correctly.
 
  • #11
rabbed said:
Hi

For a sphere:

x = r*cos(a)*sin(o)
y = r*sin(a)
z = -r*cos(a)*cos(o)

where r is radius, a is latitude and o is longitude, the directional derivative (dx,dy,dz) is the jacobian multiplied by a unit vector (vx,vy,vz), right? So i get:

dx = cos(a)*sin(o)*vx - r*sin(a)*sin(o)*vy + r*cos(a)*cos(o)*vz
dy = sin(a)*vx + r*cos(a)*vy
dz = -cos(a)*cos(o)*vx + r*sin(a)*cos(o)*vy + r*cos(a)*sin(o)*vz

Is this correct?
This looks wrong to me. Since (x,y,z) is scaled by multiplier r, my immediate reaction is that (dx,dy,dz) should also be scaled by the multiplier r. Your equations don't have that. Your first term in each equation needs 'r*'. There may be other problems. You should check those calculations.

See the last section of http://www.moog-crossbow.com/Literature/Application_Notes_Papers/Datum_Transformations_of_Inertial_Reference_Frames.pdf . That is going from ECEF to the LL system, so you need to take the inverse of the transformation matrix.
 
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  • #12
FactChecker said:
This looks wrong to me. Since (x,y,z) is scaled by multiplier r, my immediate reaction is that (dx,dy,dz) should also be scaled by the multiplier r. Your equations don't have that. Your first term in each equation needs 'r*'. There may be other problems. You should check those calculations.

For the first row of the jacobian:
In the first column i derivate r*cos(a)*sin(o) wrt r which gets me cos(a)*sin(o)
In the second column i derivate r*cos(a)*sin(o) wrt a which gets me -r*sin(a)*sin(o)
In the third column i derivate r*cos(a)*sin(o) wrt o which gets me r*cos(a)*cos(o)

Is that wrong?
 
  • #13
rabbed said:
For the first row of the jacobian:
In the first column i derivate r*cos(a)*sin(o) wrt r which gets me cos(a)*sin(o)
In the second column i derivate r*cos(a)*sin(o) wrt a which gets me -r*sin(a)*sin(o)
In the third column i derivate r*cos(a)*sin(o) wrt o which gets me r*cos(a)*cos(o)

Is that wrong?
Oh. Sorry. You are doing something different from what I was thinking. Then I think you should be using (dr, da, do) instead of (vx, vy, vz).
 
  • #14
Okay

Yeah, maybe it got confusing with (dx, dy, dz), but it does have with delta to do.
But just to be clear, with (dr, da, do) you still mean a unit vector, right?
 
  • #15
rabbed said:
Okay

Yeah, maybe it got confusing with (dx, dy, dz), but it does have with delta to do.
But just to be clear, with (dr, da, do) you still mean a unit vector, right?
It's a good idea to use a unit vector to visualize it, but that is not necessary. It should convert any velocity vector in the (r,a,o) coordinate system to the (x,y,z) coordinate system.
 
  • #16
FactChecker said:
It's a good idea to use a unit vector to visualize it, but that is not necessary. It should convert any velocity vector in the (r,a,o) coordinate system to the (x,y,z) coordinate system.
Okay

But for the directional derivative to get the correct amount of slope in the direction of (vx,vy,vz) it would need to have a length of one?
Did you agree with my description above, about a coordinate system C placed inside the destination space?
In that case, my next question is how to get the direction of maximum slope in the point
 

1. What is a Jacobian directional derivative?

A Jacobian directional derivative is a mathematical tool used to calculate the rate of change of a multivariable function in a specific direction. It measures how much the function changes as you move along a particular direction in the input space.

2. How is a Jacobian directional derivative calculated?

A Jacobian directional derivative is calculated using the Jacobian matrix, which is a matrix of partial derivatives. The directional derivative is then calculated by taking the dot product of the Jacobian matrix and the direction vector.

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

The main difference is that a Jacobian directional derivative is used for multivariable functions, while a regular directional derivative is used for single-variable functions. The Jacobian directional derivative also takes into account the direction of change in the input space, while a regular directional derivative only considers the change in output along a specific direction.

4. When is a Jacobian directional derivative useful?

A Jacobian directional derivative is useful in many areas of mathematics, physics, and engineering. It is commonly used in optimization problems to find the direction of steepest ascent or descent of a multivariable function. It is also used in the study of fluid mechanics, electromagnetics, and other fields where vector calculus is applied.

5. Are there any limitations or assumptions to using a Jacobian directional derivative?

One limitation is that the function must be differentiable at the point of interest. Additionally, the direction vector must be a unit vector. Assumptions include the use of Cartesian coordinates and the existence of partial derivatives for all input variables.

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