hello
with the supplied csv file there is no error poping up , at least on my R2020b
also there is no figure 2 showing up, so I ended up ploting myself the TT(k)/(msd(k,1)) array , which, for the csv file provided, is above 5 ; the if statement (ballistic) is never met
if (1.5 >= TT(k)/(msd(k,1))) && (TT(k)/(msd(k,1)) >= 0.75) %ballistic
- is that your issue ?
clc
clearvars
% LET = ['ABCDE']; %# letters represent # of beetles; ie ABC means there are 3 beetles
LET = ['A']; %# letters represent # of beetles; ie ABC means there are 3 beetles
for e = 1:2
%%%% 0 frequency
if e == 1, freq = 0;
% figure(e*10+1); clf; hold on;
% figure(e*10+2); clf; hold on;
figure(e*10+3); clf; hold on;
for j = 1:1%5
clear data
data = csvread(['Control4' LET(j) '.csv']); %yes
nData = size(data,1); %# number of data points
numberOfDeltaT = floor(nData); %# for MSD, dt should be up to 1/4 of number of data points
msd = zeros(numberOfDeltaT,3); %# We'll store [mean, std, n]
%# calculate msd for all deltaT's
for dt = 1:numberOfDeltaT
deltaCoords = data(1+dt:end,1:2) - data(1:end-dt,1:2);
squaredDisplacement = sum(deltaCoords.^2,2); %# dx^2+dy^2+dz^2
msd(dt,1) = mean(squaredDisplacement); %# average
msd(dt,2) = std(squaredDisplacement); %# std
msd(dt,3) = length(squaredDisplacement); %# n
end
% figure(e*10+1);
% plot(data(:,1), data(:,2)); axis equal;
%
% figure(e*10+2);
TT = (1:numberOfDeltaT);
% h = errorbar(TT, msd(:,1), msd(:,2), 'o', 'markersize', 12);
% h = plot(TT, msd(:,1), 'o', 'markersize', 12);
% h.LineWidth = 2;
% set(gca, 'xscale', 'log', 'yscale', 'log');
% plot(xlim, ylim, '--k', 'markersize', 4) %GOAL: place a line in the middle so we know where slope = 1 as a reference
% xlabel('i\deltat(s)');
% ylabel('\langle\Deltax_{i}^{2}\rangle/\langle\Deltax_{1}^{2}\rangle');
% title('Normalized Mean Square Displacements vs. Time Difference for Control 4')
figure(e*10+3);
behaviors= 2; % 2 behaviors
beetles=5; %ideally will use LET so the loop worked regardless of if 4 or 5 beetles and not a manual input
count= zeros(1,beetles*behaviors); % creates 2 empty 'bins' or storage areas for ballistic or diffusive
yValues=nData*beetles;
% Count outcomes of behavior of beetles
behaviorSum=zeros(1,beetles*behaviors);
for k= 1:nData
for i=1:beetles
my_test_data(k) = TT(k)/(msd(k,1));
if (1.5 >= TT(k)/(msd(k,1))) && (TT(k)/(msd(k,1)) >= 0.75) %ballistic
behaviorSum(2*i-1)=behaviorSum(2*i-1)+1; %incrementing ballistic bin
else
behaviorSum(2*i)=behaviorSum(2*i)+1; %incrementing diffusive bin
end
% increment appropriate bin
end
%this is storing a value in one of the bins created
end
for n=1:beetles*behaviors
count(n)=behaviorSum(n)/nData;
end
end
% Show bar graph of outcome
bar(1:beetles*behaviors, count) %this is creating the histogram with 1:behaviors as number of bars and count as y values for bars
title(sprintf('Characteristic time \deltat_{c} vs. Probability', yValues), 'Fontsize',14)
xlabel('Characteristic time \deltat_{c}', 'Fontsize',14)
ylabel('Probability', 'Fontsize',14)
shg %show graph window
else
fprintf('Thanks for helping!');
end
end
figure
semilogy(my_test_data)
