Ben Matlab experiments

Experiments and noise characterization

BenMatLabExperiments/BenMatLabExperiments/Experiment_05.01.21/session050121.m

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+df = readtable("decodeddata2.csv")
+pier_data = readtable('autoss_c905_75dd_f5ff.csv')
+%decodeddata2.csv is the session from 5-1-21
+%% 
+% Scripps Pier
+% 
+% Operated by the Scripps Institution of Oceanography (SIO). The instrument 
+% package is mounted at a nominal depth of 5 meters MLLW. Historical data has 
+% been collected continuously since April 4, 2005.
+% 
+% https://sccoos.org/data/autoss/
+
+% %convert raw values into SI units
+df.Ax = df.Ax .* 9.81; %Accelerometer multiply by 0.019141 to get m/s^2 or divide by 512 to
+%get answer in Gs
+df.Ay = df.Ay .* 9.81;
+df.Az = df.Az .* 9.81;
+% %Mag is already in micro-Teslas
+% df.Gx = df.Gx ./8.2; %Gyroscope divide by 8.2 to get degrees/second
+% df.Gy = df.Gy ./8.2;
+% df.Gz = df.Gz ./8.2;
+%%
+figure(1)
+clf
+%accelerometer plots
+subplot(331)
+plot(df.time,df.Ax)
+title('x-axis')
+ylabel('m/s^2')
+xlabel('time [s]')
+subplot(332)
+plot(df.time,df.Ay)
+title('y-axis')
+ylabel('m/s^2')
+xlabel('time [s]')
+subplot(333)
+plot(df.time,df.Az)
+title('z-axis')
+ylabel('m/s^2')
+xlabel('time [s]')
+%Mag plots
+subplot(334)
+plot(df.time,df.Mx)
+ylabel('micro-Teslas')
+xlabel('time [s]')
+title('x-Mag')
+subplot(335)
+plot(df.time,df.My)
+ylabel('micro-Teslas')
+xlabel('time [s]')
+title('y-Mag')
+subplot(336)
+plot(df.time,df.Mz)
+ylabel('micro-Teslas')
+xlabel('time [s]')
+title('z-Mag')
+%Gyroscope plots
+subplot(337)
+plot(df.time,df.Gx)
+ylabel('degrees/second')
+xlabel('time [s]')
+title('x-Gyro')
+subplot(338)
+plot(df.time,df.Gy)
+ylabel('degrees/second')
+xlabel('time [s]')
+title('y-Gyro')
+subplot(339)
+plot(df.time,df.Gz)
+ylabel('degrees/second')
+xlabel('time [s]')
+title('z-Gyro')
+%%
+temp = pier_data.temperature_celsius_(2702:2708);
+time = linspace(0,length(df.time),length(temp));
+% DateString = '2021-04-24T08:10:18Z'
+% formatIn = 'yr-mo-dyThr:min:secZ';
+% datevec(DateString,formatIn)
+%%
+figure(2)
+clf
+subplot(211)
+plot(df.time,df.temp)
+title('temperature vs. time')
+xlabel('time [s]')
+ylabel('temperature [^oC]')
+subplot(212)
+histogram(df.temp)
+
+% ldg = legend('Smartfin','Scripps Pier','Location',"best")
+% ldg.FontSize = 20
+
+% subplot(211)
+% plot(df.time,df.temp)
+% title('temperature vs. time')
+% xlabel('time [s]')
+% ylabel('temperature [^oC]')
+% subplot(212)
+% histogram(df.temp)
+%%
+figure(3)
+clf
+idx = find(df.wet > 0);
+scatter(df.time,df.wet)
+title('in water?')
+%%
+names = df.Properties.VariableNames(6:14);
+data = df(:,6:14);
+data_to_calc = table2array(data);
+stds = zeros(1,9);
+var = zeros(1,9);
+for i=1:9    
+    stds(i) = std(data_to_calc(:,i));
+    var(i) = (std(data_to_calc(:,i)))^2;
+end
+results = [stds ; var];
+results = array2table(results,"RowNames",{'std. dev.','variance'});
+results.Properties.VariableNames(:) = names;
+results