add SCRIPT_allan_txtparallel.m (Without building bagconvert)

ReadMe.md

@@ -38,6 +38,8 @@ Accelerometer "random walk" | `accelerometer_random_walk` | <img src="https://la
     * Tango Yellowstone Tablet
     * ASL-ETH VI-Sensor
 
+Tip: Can also use `SCRIPT_allan_txtparallel.m` with `imu.txt` to generate an allan deviation (Without Ros)
+
 ### Example Plot - XSENS MTI-G-700
 ![allan chart acceleration](data/results_20170908T182715_accel.png)
 

matlab/SCRIPT_allan_txtparallel.m

@@ -0,0 +1,106 @@
+%% Initalization
+close all
+clear all
+
+% Read in our toolboxes
+addpath('functions/allan_v3')
+
+% Our bag information
+mat_path = 'imu.txt';
+
+% IMU information (todo: move this to the yaml file)
+update_rate = 200;
+
+
+%% Data processing
+% Load the txt file (Ts, ax, ay, az, wx, wy, yz)
+% Ts(s) acc(m/s^2) w(rad/s)
+fprintf('opening the txt file.\n')
+data_imu = dlmread(mat_path);
+
+% Load our time series information
+fprintf('loading timeseries.\n')
+ts_imua = timeseries(data_imu(:,2:4),data_imu(:,1));
+ts_imuw = timeseries(data_imu(:,5:7),data_imu(:,1));
+
+
+%% Process the timeseries data
+
+% Find the frequency of the imu unit
+% delta = mean(diff(ts_imua.Time(1:10)));
+% update_rate = 1/delta;
+delta = 1/update_rate;
+fprintf('imu frequency of %.2f.\n',update_rate);
+fprintf('sample period of %.5f.\n',delta);
+
+% Calculate our tau range (max is half of the total measurements)
+taumax = floor((length(ts_imua.Time)-1)/2);
+tau = delta*logspace(log10(delta),log10(taumax),2000);
+%tau = delta*linspace(1,taumax,1000);
+
+
+%% Calculate the acceleration allan deviation of the time series data!
+
+data1.rate = update_rate;
+data1.freq = ts_imua.data(:,1)';
+data2.rate = update_rate;
+data2.freq = ts_imua.data(:,2)';
+data3.rate = update_rate;
+data3.freq = ts_imua.data(:,3)';
+data4.rate = update_rate;
+data4.freq = ts_imuw.data(:,1)';
+data5.rate = update_rate;
+data5.freq = ts_imuw.data(:,2)';
+data6.rate = update_rate;
+data6.freq = ts_imuw.data(:,3)';
+
+fprintf('calculating allan deviation.\n');
+tic;
+cluster = parcluster();
+j1 = batch(cluster,@allan,1,{data1,tau});
+j2 = batch(cluster,@allan,1,{data2,tau});
+j3 = batch(cluster,@allan,1,{data3,tau});
+j4 = batch(cluster,@allan,1,{data4,tau});
+j5 = batch(cluster,@allan,1,{data5,tau});
+j6 = batch(cluster,@allan,1,{data6,tau});
+
+% Wait for the jobs to finish
+wait(j1)
+wait(j2)
+wait(j3)
+wait(j4)
+wait(j5)
+wait(j6)
+
+% Get results into a cell array
+r1 = fetchOutputs(j1);
+r2 = fetchOutputs(j2);
+r3 = fetchOutputs(j3);
+r4 = fetchOutputs(j4);
+r5 = fetchOutputs(j5);
+r6 = fetchOutputs(j6);
+results_ax = r1{1};
+results_ay = r2{1};
+results_az = r3{1};
+results_wx = r4{1};
+results_wy = r5{1};
+results_wz = r6{1};
+
+% Finally cleanup
+delete(j1)
+delete(j2)
+delete(j3)
+delete(j4)
+delete(j5)
+delete(j6)
+toc
+
+%% Save workspace
+filename = ['results_',datestr(now,30),'.mat'];
+fprintf('saving to: %s\n',filename);
+save(['../data/',filename],'update_rate','ts_imua','ts_imuw','tau','taumax','results_ax','results_ay','results_az','results_wx','results_wy','results_wz')
+fprintf('done saving!\n');
+
+
+
+