I am going to rotate from one frame to another one with rotation matrix. goal of program is to make my Gyro parallel to earth, it means output vector should has first two numbers zero and third one -9.81.
Codes:
vs1 = 1;
vs2 = -0.003;
vs3 = -9.808;
vst = [vs1 vs2 vs3]';
alpha = (acosd(vs1/sqrt(vs1^2+vs2^2)));
gama = (acosd(vs2/sqrt(vs1^2+vs2^2)));
beta = (acosd(vs3/sqrt(vs1^2+vs2^2+vs3^2)));
R1 = [(cosd(gama)*cosd(beta)*cosd(alpha))-(sind(gama)*sind(alpha)) (cosd(gama)*cosd(beta)*sind(al)+sind(gama)*cosd(al)) (-cosd(gama)*sind(beta));((-sind(gama)*cosd(beta)*cosd(alpha))-cosd(gama)*sind(alpha)) ((-sind(gama)*cosd(beta)*sind(alpha))+(cosd(gama)*cosd(alpha))) sind(gama)*sind(beta);sind(beta)*cosd(alpha) sind(beta)*sind(alpha) cosd(beta)];
disp (R1*vst)
result for vs1,vs2 and vs3 is : -0.00599, 0.0000359 and 9.858845622079866. first, I can not understand why program give me positive Z and why it does not make first two numbers zero?
thanks in advance
You have a bug in your code. There are two places where I think the variable "al" should actually be "alpha" if I'm following your code correctly.
But your code also generates alpha = 90 and gama = 180 for those inputs. All you're going to do is flip the axes to within machine precision with those inputs, so it's not going to achieve the results you're looking for.
1) Are you sure the input vector is correct? Why would gravity have a value near X=1 if you're nearly vertical (Z = -9.808)?
Related
I'm a bit confused about the angle() function in Matlab, in particular when applied to an array of real numbers.
The angle() function should give me the phase of a complex number. Example: y = a + bi, ==> phase = arctan(b/a). Indeed, the following works:
for t=1:1000
comp(t) = exp(1i*(t/10));
end
phase_good_comp1 = unwrap(angle(comp)); %this gives me the right answer
b = imag(comp);
a = real(comp);
phase_good_comp2 = atan(b./a); %this gives me the right answer too, but
wrapped (not sure if there is a way to unwrap this, but unwrap() does not
work)
figure(1)
plot(phase_good_comp1)
hold on
plot(phase_good_comp2,'--r')
legend('good phase1', 'good phase2')
title('complex number')
Here's the plot for the complex numbers --
Note that I can use either the angle() function, or the explicit definition of phase, as I have shown above. Both yield good results (I can't unwrap the latter, but that's not my issue).
Now if I apply the same logic to an array of real numbers, I should get a constant phase everywhere, since no imaginary part exists, so arctan(b/a) = arctan(0) = 0. This works if I use the explicit definition of phase, but I get a weird result if I use angle():
for t=1:1000
ree(t) = cos((t/10));
end
phase_bad_re = unwrap(angle(ree)); %this gives me an unreasonable (?) answer
b = imag(ree);
a = real(ree);
phase_good_re = atan(b./a); %this gives me the right answer
figure(1)
plot(phase_bad_re)
hold on
plot(phase_good_re,'--r')
legend('bad phase', 'good phase')
title('real number')
Here's the plot for the real numbers --
Why the oscillation when I use angle()???
The Matlab documentation tells you how to compute this:
The angle function can be expressed as angle(z) = imag(log(z)) = atan2(imag(z),real(z)).
https://www.mathworks.com/help/matlab/ref/angle.html
Note that they define it with atan2 instead of atan.
Now your data is in the range of cosine, which includes both positive and negative numbers. The angle on the positive numbers should be 0 and the angle on the negative numbers should be an odd-integer multiple of pi in general. Using the specific definition that they've chosen to get a unique answer, it is pi. That's what you got. (Actually, for the positive numbers, any even-integer multiple of pi will do, but 0 is the "natural" choice and the one that you get from atan2.)
If you're not clear why the negative numbers don't have angle = 0, plot it out in the complex plane and keep in mind that the radial part of the complex number is positive by definition. That is z = r * exp(i*theta) for positive r and theta given by this angle you're computing.
Since sign of cosine function is periodically changed, angle() is also oscillated.
Please, try this.
a=angle(1);
b=angle(-1);
Phase of 1+i*0 is 0, while phase of -1+i*0 is 3.14.
But, in case of atan, b/a is always 0, so that the result of atan() is all 0.
Given the data of the curve and the size of the image, how to calculate the length of the curve ?
curve = [9.93,4;9.87,4.10;9.80,4.20;9.74,4.30;9.68,4.40;9.63,4.50;9.59,4.60;9.55,4.70;9.53,4.80;9.51,4.90;9.50,5;9.50,5.10;9.51,5.20;9.48,5.30;9.55,5.40;9.45,5.47;9.55,5.52;9.45,5.59;9.55,5.65;9.45,5.72;9.55,5.77;9.45,5.84;9.55,5.90];
backgroud = ones(20,20);
imshow(backgroud)
hold on, plot(curve(2,:),curve(1,:),'r');
To expand on the comment, you can simply sum the lengths of the line segments that make up the curve. This could be accomplished using the following code.
curve = [9.93,4;9.87,4.10;9.80,4.20;9.74,4.30;9.68,4.40;9.63,4.50;9.59,4.60;9.55,4.70;9.53,4.80;9.51,4.90;9.50,5;9.50,5.10;9.51,5.20;9.48,5.30;9.55,5.40;9.45,5.47;9.55,5.52;9.45,5.59;9.55,5.65;9.45,5.72;9.55,5.77;9.45,5.84;9.55,5.90];
len = sum(sqrt(sum(diff(curve).^2,2)))
result
len =
2.4757
Edit: As beaker pointed out, the indices are backwards in your answer. Take a look at the values of curve_x1, curve_x2, etc... and you will see that they are just a single value. If you reverse the indices we get the same result. Also, as a sanity check take a look at the plot of the curve, it spans about 2 units in the first dimension and about 0.4 units in the second dimension so a number near 2.5 seems reasonable, a number like around 8 is much too large.
curve_x1 = num2cell(curve(1:end-1,1));
curve_y1 = num2cell(curve(1:end-1,2));
curve_x2 = num2cell(curve(2:end,1));
curve_y2 = num2cell(curve(2:end,2));
instance_length = cellfun(#(x1,y1,x2,y2) sqrt((x2-x1)^2+(y2-y1)^2), curve_x1,curve_y1,curve_x2,curve_y2);
distance = sum(instance_length)
I do not know what this error means or how to fix it. I am trying to perform an image rotation in a separate space of coordinates. When defining the reference space of the matrix to be at zero, I am getting the error that integers can only be comibined with integers of the same class or scalar doubles. the line is
WZcentered = WZ - [x0;yo]*ones(1,Ncols);
WZ is classified as a 400x299x3 unit 8, in the workspace. It is an image. x0 and y0 are set to 0 when the function is called. How can I fix this issue/what exactly is happening here?
Also, when I do the same thing yet make WZ to be equal to double(WZ) I get the error that 'matrix dimensions must agree.' I am not sure what the double function does however. Here is the whole code.
function [out_flag, WZout, x_final, y_final] = adopted_moveWZ(WZ, x0, y0);
%Initial Test of plot
[Nrows,Ncols]=size(WZ);
if Nrows ~= 2
if Ncols ==2
WZ=transpose(WZ); %take transpose
[Nrows,Ncols]=size(WZ); %reset the number of rows and columns
else
fprintf('ERROR: Input file should have 2-vectors for the input points.\n');
end
end
plot(WZ(1,:),WZ(2,:),'.')
title('These are the original points in the image');
pause(2.0)
%WZorig = WZ;
%centering
WZcentered = WZ - ([x0;y0] * ones(1,Ncols));
FigScale=400;
axis([-FigScale 2*FigScale -FigScale 2*FigScale])
disp('Hit any key to start the animation');
pause;
SceneCenter = zeros(Nrows,Ncols);
WZnew = WZcentered;
for ii=0:20
%rotate
R = [cos(pi/ii) -sin(pi/ii) 0; sin(pi/ii) cos(pi/ii) 0; 0 0 1];
WZnew = R * WZnew;
plot(WZnew(1,:),WZnew(2,:),'.')
%place WZnew at a different place in the scene
SceneCenter = (ii*[30;40])*ones(1,Ncols);
plot(SceneCenter(1,:) + WZnew(1,:), SceneCenter(2,:) + WZnew(2,:),'.')
axis([-FigScale 2*FigScale -FigScale 2*FigScale])
pause(1.0);
end
%Set final values for output at end of program
x_final = SceneCenter(1,1);
y_final = SceneCenter(2,1);
PPout = PPnew + SceneCenter;
This happens due to WZ and ([x0;y0] * ones(1,Ncols)) being of different data types. You might think MATLAB is loosely typed, and hence should do the right thing when you have a floating point type operated with an integer type, but this rule breaks every once in a while. A simpler example to demonstrate this is here:
X = uint8(magic(5))
Y = zeros(5)
X - Y
This breaks with the same error that you are reporting. One way to fix this is to force cast one of the operands to the other, typically up-casted to make sure the math works. When you do this, both the numbers you are working on are floating point (double precision), and so they are represented in the same byte formatting sequence in memory. This way, the '-' sign is valid, in the same way that you can say 3 apples + 4 apples = 7 apples, but 3 oranges (uint8) + 4 apples (double) = ?. The double(X) makes it clear that you really mean to use double precision arithmetic, and hence fixes the error. This is how it looks now:
double(X) - Y
After having identified this, the new error is 'matrix dimensions do not match'. This means exactly what it says. WZ is a 400x299x3 matrix, and the right hand side matrix is 2xnCols. Now can you subtract a 2D matrix from a 3D matrix of different sizes meaningfully?
Depending on what your code is really intending to do, you can pad the RHS matrix, or find out other ways to make the sizes equal.
All of this is why MATLAB includes routines to do image rotation, namely http://www.mathworks.com/help/images/ref/imrotate.html . This is part of the Image Processing Toolbox, though.
i am trying to calculate the inverse fourier transform of the vector XRECW. for some reason i get a vector of NANs.
please help!!
t = -2:1/100:2;
x = ((2/5)*sin(5*pi*t))./((1/25)-t.^2);
w = -20*pi:0.01*pi:20*pi;
Hw = (exp(j*pi.*(w./(10*pi)))./(sinc(w./(10*pi)))).*(heaviside(w+5*pi)-heaviside(w-5*pi));%low pass filter
xzohw = 0;
for q=1:20:400
xzohw = xzohw + x(q).*(2./w).*sin(0.1.*w).*exp(-j.*w*0.2*((q-1)/20)+0.5);%calculating fourier transform of xzoh
end
xzohw = abs(xzohw);
xrecw = abs(xzohw.*Hw);%filtering the fourier transform high frequencies
xrect=0;
for q=1:401
xrect(q) = (1/(2*pi)).*trapz(xrecw.*exp(j*w*t(q))); %inverse fourier transform
end
xrect = abs(xrect);
plot(t,xrect)
Here's a direct answer to your question of "why" there is a nan. If you run your code, the Nan comes from dividing by zero in line 7 for computing xzohw. Notice that w contains zero:
>> find(w==0)
ans =
2001
and you can see in line 7 that you divide by the elements of w with the (2./w) factor.
A quick fix (although it is not a guarantee that your code will do what you want) is to avoid including 0 in w by using a step which avoids zero. Since pi is certainly not divisible by 100, you can try taking steps in .01 increments:
w = -20*pi:0.01:20*pi;
Using this, your code produces a plot which might resemble what you're looking for. In order to do better, we might need more details on exactly what you're trying to do, or what these variables represent.
Hope this helps!
I have an physical instrument of measurement (force platform with load cells) which gives me three values, A, B and C. It happens, though, that these values - that should be orthogonal - actually are somewhat coupled, due to physical characteristics of the measuring device, which causes cross-talk between applied and returned values of force and torque.
Then, it is recommended that a calibration matrix be used to transform the measured values into a better estimate of the actual values, like this:
The problem is that it is necessary to perform a SET of measurements, so that different measured(Fz, Mx, My) and actual(Fz, Mx, My) are least-squared to get some C matrix that works best for the system as a whole.
I can solve Ax = B problems with scipy.linalg.lststq, or even scipy.linalg.solve (giving an exact solution) for ONE measurement, but how should I proceed to consider a set of different measurements, each one with its own equation giving a potentially different 3x3 matrix?
Any help is much appreciated, thanks for reading.
I posted a similar question containing just the mathematical part of this at math.stackexchange.com, and this answer solved the problem:
math.stackexchange.com/a/232124/27435
In case anyone have a similar problem in the future, here is the almost literal Scipy implementation of that answer (first lines are initialization boilerplate code):
import numpy
import scipy.linalg
### Origin of the coordinate system: upper left corner!
"""
1----------2
| |
| |
4----------3
"""
platform_width = 600
platform_height = 400
# positions of each load cell (one per corner)
loadcell_positions = numpy.array([[0, 0],
[platform_width, 0],
[platform_width, platform_height],
[0, platform_height]])
platform_origin = numpy.array([platform_width, platform_height]) * 0.5
# applying a known force at known positions and taking the measurements
measurements_per_axis = 5
total_load = 50
results = []
for x in numpy.linspace(0, platform_width, measurements_per_axis):
for y in numpy.linspace(0, platform_height, measurements_per_axis):
position = numpy.array([x,y])
for loadpos in loadcell_positions:
moments = platform_origin-loadpos * total_load
load = numpy.array([total_load])
result = numpy.hstack([load, moments])
results.append(result)
results = numpy.array(results)
noise = numpy.random.rand(*results.shape) - 0.5
measurements = results + noise
# now expand ("stuff") the 3x3 matrix to get a linearly independent 3x3 matrix
expands = []
for n in xrange(measurements.shape[0]):
k = results[n,:]
m = measurements[n,:]
expand = numpy.zeros((3,9))
expand[0,0:3] = m
expand[1,3:6] = m
expand[2,6:9] = m
expands.append(expand)
expands = numpy.vstack(expands)
# perform the actual regression
C = scipy.linalg.lstsq(expands, measurements.reshape((-1,1)))
C = numpy.array(C[0]).reshape((3,3))
# the result with pure noise (not actual coupling) should be
# very close to a 3x3 identity matrix (and is!)
print C
Hope this helps someone!