Surface Plot or Mesh Plot

I am quite naive to MATLAB, so i beg your apology for asking simple questions. Here is the code:

A=50;
tau=1;
P_f=0.02;
for i=1:100
  v0(i)=i;
  v(i)=v0(i).*5/18;
  Kf=tan(atan((v(i).*tau)/sqrt((4*A^2)-((v(i)^2)*(tau^2))))-((pi*P_f)/2));
  M=(2*A*Kf)/(v(i).*sqrt(1+Kf^2));
  Phf(i)=(2/pi)*(atan((v(i).*tau)/sqrt((4*A^2)-(((v(i))^2)*tau^2)))-atan((v(i).*M)/sqrt((4*A^2)-(((v(i))^2)*M^2))));
end
plot (v0,Phf)

Now, how to make a Surface Plot or Mesh Plot of this ?

[Azzi Abdelmalek]

You need three variables. What are they?

[Adnan]

I just have two variables here ~ v0 and Phf. How to define this third matrix or vector

[Star Strider]

Which other one do you want to plot: Kf, M, or something else?

[Adnan]

Can you just help me to adjust the scale of this plot (as per the above code). The plot comes around 0.02, but i can't figure out the exact values on the y axis with respect to the x axis. I need something where i can clearly see the rising or the declining points

[Star Strider]

When I calculated your data, the range (max(Phf)-min(Phf)) = 69.3889e-018. The variations in Phf are on the order of machine precision.

Do this calculation (dPhf/dv0) and plot to illustrate that:

dPhfdv0 = diff([Phf])./diff([v0]);
plot(dPhfdv0)

[Adnan]

Thanks Star Strider. I m calculating probability and it can't be negative. Is there any method to avoid negative probabilities in this plot, plot(dPhfdv0)

Answer 1

[Star Strider]

Probabilities are by definition always positive.

I used dPhfdV0 to illustrate the fact that your Phf array has very little variation. If you want to calculate the statistics, I would calculate those on Phf itself. Calculating the mean and standard deviation are easy enough:

Phfmn = mean(Phf)
Phfsd = std(Phf)

If you want the values that will define the range that Phf will be found within with 95% probability, you can calculate them as:

PhfRng95 = [Phfmn-1.96*Phfsd  Phfmn+1.96*Phfsd]

You have to use format long e to see the details of PhfRng95. The value of 1.96 is the inverse normal distribution for the probabilities of 0.025 and 0.975, encompassing a total probability of 0.95.