added geoplot function

README.md

@@ -1,68 +1,42 @@
 !!! Important !!!
-See Example: start the App in Matlab the correct folder (see picture), otherwise it will throw an error
-![double click app.mlapp in this folder! make sure ](tutorial/image.png)!
-
-Updated app is out. Check out app2 (everything except laps, grayed out buttons and presets works, presets might work in old app)
+See Example: start the App in Matlab the correct folder (see picture), otherwise it will give out an error
+![double click app.mlapp in this folder! make sure ](tutorial/image.png)
 
 KNOWN ERRORS / NOT WORKING / UNKNOWN
-- FT25-Presets -> instead use Load(fast) and Plot Subplot
-- new implementation of date selection might mess with lap selection
-- unknown status of Presets for FT23 and FT24 after the last few updates, might not work
+- should the imported data contain more than one day, preconfigured presets will might not work
+- geoplot was not tested throughly, might not work with subplotting, so close the figures before you plot either of them
 
 FYI:
-- code is starting to get really clunky, going to rewrite the handling of loaded data some time in the future
 - search is case sensitive
 - you need to delete your search if you misspelled something
 - if something doesnt work try reset subplot and then press plot subplot again
 
+Short tutorial:
+Part 1 - General Tab:
 ![Tutorial for new app2](<tutorial/app2 tutorial.png>)
+Part 2 - Preset Tab:
+![Tutorial for new app2 - presets](<tutorial/app2 tutorial - presets.png>)
+Part 3 - Geoplot:
+- need to manually load latitude and longitude
+- third value can be inserted as linecolor by choosing a dataset in the dropdown next to custom geoplot
+- can also apply timestamps like the subplots
+![Tutorial for new app2 - Geoplot](<tutorial/geoplot.png>)
 
+Quick notes:
+There are two options to plot data
+- 1. Tab: General
+    - Allows to make custom plots based on the data you have choosen
+    - Allows to apply external functions saved in the folder "functions" to be applied to loaded dataset
+        - Note: check "example.m" in the functions folder to learn how to make a custom function (there are some rules)
+    - Timestamped data can only be created from app.data / Loaded Datasets
+        - To timestamp the data you created with custom functions you need to append it first
+- 2. Tab: Presets
+    - this tab allows you to plot and save preconfigured seasonal presets
+    - presets exist for the seasons 23,24,25
+    - check the Dropdown Box to see which plots are available
 
-Quick tutorial:
-1. Browse the .mat file you want to open. (put it into /data folder)
-2. Choose either Load (fast) or Load (Presets)
-    - Load(fast):
-        - will load ONLY the name of all saved data in your .mat file
-        - select data you want to plot in custom subplots -> select data (left side) 
-        - all features will work for this option
-        - for customizing look under the next chapter
-
-    - Load (Presets)
-        - will load a pre configured set of data in your .mat file (takes a bit of time)
-        - choose a preset and a season, then press "Plot Presets"
-            -> will plot pre configured graphs
-        - all features in "Custom Subplots" do NOT work with this
-        - the idea is that only sortdata.m and the plot_settings need to be configured each season
-        - for customizing look under the next chapter (only features within Set Timestamps panel work)
-
-Features:
-1. Set Timestamps:
-    - works for both
-    - entire stint (all data recorded) is the default option that will be plotted
-    - otherwise you can select either the detected laps (will plot, but laps might be inaccurately recorded) or custom timestamps (remember to tick the Use box)
-2. Reset Panel and To Workspace Buttons:
-    - work only for Presets
-    - should something not work try pressing reset and plot preset again
-    - to workspace throws the entire preset dataset into the matlab workspace (for further manipulation)
-        - currently limited in capabilites
-3. Custom Subplots:
-    - only works for the selected data (if you press load preset you can also use the displayed data, but somethings like cell voltages might not be avaible)
-    - columns and rows to set the number of plots you want in one figure
-    - press Plot Subplot to plot 
-    - how it works:
-![selected subplot is 1](tutorial/1.png)
-![this time a lap, and a different dataset was selected](tutorial/2.png)
-![only if you want a second -yaxis select the option "plot with 2nd yAxis](tutorial/3.png)
-    - press reset subplot to delete the selected graph
-
-
-Presets:
-Adapting a preset:
-- sortdata creates an struct pltData with all necessary data for plot_settings
-    - easiest case: the data from the vectorlogger has the same fieldnames as last season -> probably no changes necessary, unless you want to plot different things
-    - vectorlogger fieldnames changed: adapt the fieldname to the updated name
-    - otherwise: add missing data with pltData.XXX =
-- plot_settings: uses the data given from pltData to plot, adapt as you see fit
-    - plotData currently hands over all data that use the following strings:
-        - "ABX*","Shunt*","AMS_Status*","INV*","XSens*
-        - which can make problems (e.g. FT23 and FT25 use XSens, FT24 uses VN200)
+4 seperate datasets:
+app.data - main dataset for custom plots
+app.data_created - dataset created by custom functions/filter, can be appended to app.data via synchronize()
+app.data_tr = app.data(tr,:) - main dataset cut down with timestamp (timerange tr)
+app.pltData  - main dataset for preset dataset

season/FT25/sortdata.m

@@ -1,44 +1,45 @@
-function [pltData] = sortdata(data,start,stop)
+function [pltData, stats] = sortdata(data)
     date = dateshift(data.Time(1),'start','day');
     time_hms = data.Time-date;
     time_s = seconds(time_hms);
     time_s = time_s - time_s(1);    % set beginning of session to 0
 
     % x-Axis:
-    pltData.Time = data.Time(start:stop);
-    pltData.time_s = time_s(start:stop)-time_s(start);
-    pltData.time_hms = time_hms(start:stop);
+    pltData.time_s = time_s;
+    pltData.time_hms = time_hms;
+
 
     % distance calculation
-    speed_mps = movmean(data.ABX_Driver_ABX_Speed(start:stop),50); % TODO: test different speed filters for distance calculation
+    speed_mps = movmean(data.FTCU_Driver_FTCU_Speed,50); % TODO: test different speed filters for distance calculation
     pltData.distance(1) = 0;
     for i = 2:length(speed_mps)
-        pltData.distance(i) = speed_mps(i)*(pltData.time_s(i)-pltData.time_s(i-1)) + pltData.distance(i-1);
+        pltData.distance(i) = speed_mps(i)*(time_s(i)-time_s(i-1)) + pltData.distance(i-1);
     end
+    pltData.distance = pltData.distance.';
     pltData.xAxis = pltData.time_s;     % set time as default x-Axis for plotting
 
     %% Misc
-    pltData.app_percent = data.ABX_Driver_ABX_APPS_percent(start:stop);
-    pltData.speed_kph = 3.6*movmean(data.ABX_Driver_ABX_Speed(start:stop),50);  % same filter as for distance calculation ???
-    pltData.steering_deg = data.ABX_Driver_ABX_Steering_Angle(start:stop);
+    pltData.app_percent = data.FTCU_Driver_FTCU_APPS_Percent;
+    pltData.speed_kph = 3.6*movmean(data.FTCU_Driver_FTCU_Speed,50);  % same filter as for distance calculation ???
+    pltData.steering_deg = data.FTCU_Driver_FTCU_Steering_Angle;
 
     %% AMS:
-    pltData.ams_soc = data.AMS_Status_SOC(start:stop);
-    pltData.ams_tmax = data.AMS_Status_Max_cell_temp(start:stop);
-    pltData.ams_utot = data.Shunt_Voltage1_Shunt_Voltage1(start:stop);
-    pltData.ams_itot = data.Shunt_Current_Shunt_Current(start:stop);
+    pltData.ams_soc = data.AMS_Status_SOC;
+    pltData.ams_tmax = data.AMS_Status_Max_cell_temp;
+    pltData.ams_utot = data.Shunt_Voltage1_Shunt_Voltage1;
+    pltData.ams_itot = data.Shunt_Current_Shunt_Current;
     % calculations:
     pltData.ams_ptot = pltData.ams_utot.*pltData.ams_itot/1000;
 
     %% Brakes
     % brake pressure
-    pltData.brakePFront_bar = data.ABX_Driver_ABX_BrakeP_F(start:stop);
-    pltData.brakePRear_bar = data.ABX_Driver_ABX_BrakeP_R(start:stop);
+    pltData.brakePFront_bar = data.FTCU_Driver_FTCU_Brake_Pressure_F;
+    pltData.brakePRear_bar = data.FTCU_Driver_FTCU_Brake_Pressure_R;
     % brake disc temperatures
-    pltData.brakeTFrontLeft_degC = data.ABX_BrakeT_ABX_BrakeT_FL(start:stop);
-    pltData.brakeTFrontRight_degC = data.ABX_BrakeT_ABX_BrakeT_FR(start:stop);
-    pltData.brakeTRearLeft_degC = data.ABX_BrakeT_ABX_BrakeT_RL(start:stop);
-    pltData.brakeTRearRight_degC = data.ABX_BrakeT_ABX_BrakeT_RR(start:stop);
+    pltData.brakeTFrontLeft_degC = data.Sensornode_F_10Hz_BDTS_FL;
+    pltData.brakeTFrontRight_degC = data.Sensornode_F_10Hz_BDTS_FR;
+    pltData.brakeTRearLeft_degC = data.Sensornode_R_10Hz_BDTS_RL;
+    pltData.brakeTRearRight_degC = data.Sensornode_R_10Hz_BDTS_RR;
     % calculate brake bias [%]
     minBrakeP = 5;  % minimum brake pressure to avoid artifacts due to sensor noise near 0 bar
     brakePFront = pltData.brakePFront_bar;
@@ -51,10 +52,10 @@ function [pltData] = sortdata(data,start,stop)
 
     %% Dampers
     % damper positions
-    pltData.damper_FL_mm = data.ABX_Dampers_ABX_Damper_FL(start:stop); %Heave_F
-    pltData.damper_FR_mm = data.ABX_Dampers_ABX_Damper_FR(start:stop); %Roll_F
-    pltData.damper_RL_mm = data.ABX_Dampers_ABX_Damper_RL(start:stop); %Heave_R
-    pltData.damper_RR_mm = data.ABX_Dampers_ABX_Damper_RR(start:stop); %Roll_R
+    pltData.damper_FL_mm = data.Sensornode_F_100Hz_2_DS_FL; %Heave_F
+    pltData.damper_FR_mm = data.Sensornode_F_100Hz_2_DS_FR; %Roll_F
+    pltData.damper_RL_mm = data.Sensornode_R_100Hz_DS_RL; %Heave_R
+    pltData.damper_RR_mm = data.Sensornode_R_100Hz_DS_RR; %Roll_R
     % calculate damper velocities
     pltData.velocity_FL_mmps(1) = 0;
     pltData.velocity_FR_mmps(1) = 0;
@@ -68,36 +69,36 @@ function [pltData] = sortdata(data,start,stop)
         pltData.velocity_RR_mmps(i) = pltData.damper_RR_mm(i)-pltData.damper_RR_mm(i-1)/timestep;
     end
     % filter damper velocities ??? bessere Berechnung über mittelwert aus mehreren werten? Vorfilterung?
-    pltData.velocity_FL_mmps = movmean(pltData.velocity_FL_mmps,100);
-    pltData.velocity_FR_mmps = movmean(pltData.velocity_FR_mmps,100);
-    pltData.velocity_RL_mmps = movmean(pltData.velocity_RL_mmps,100);
-    pltData.velocity_RR_mmps = movmean(pltData.velocity_RR_mmps,100);
+    pltData.velocity_FL_mmps = movmean(pltData.velocity_FL_mmps,100).';
+    pltData.velocity_FR_mmps = movmean(pltData.velocity_FR_mmps,100).';
+    pltData.velocity_RL_mmps = movmean(pltData.velocity_RL_mmps,100).';
+    pltData.velocity_RR_mmps = movmean(pltData.velocity_RR_mmps,100).';
 
-    %% IMU
+    %% IMU - VN200, no need to implement didnt work well anyway
     % Acceleration
-    pltData.acc_long_g = movmean(data.XSens_Acceleration_XSens_accX(start:stop),100)/9.81;
-    pltData.acc_lat_g = movmean(data.XSens_Acceleration_XSens_accY(start:stop),100)/9.81;
+    pltData.acc_long_g = movmean(data.XSens_Acceleration_XSens_accX,100)/9.81;
+    pltData.acc_lat_g = movmean(data.XSens_Acceleration_XSens_accY,100)/9.81;
     % Rate of turn
-    pltData.rot_roll_degps = movmean(data.XSens_RateOfTurn_XSens_gyrX(start:stop),100);
-    pltData.rot_pitch_degps = movmean(data.XSens_RateOfTurn_XSens_gyrY(start:stop),100);
-    pltData.rot_yaw_degps = movmean(data.XSens_RateOfTurn_XSens_gyrZ(start:stop),100);
+    pltData.rot_roll_degps = movmean(data.XSens_rateofturn_XSens_gyrX,100);
+    pltData.rot_pitch_degps = movmean(data.XSens_rateofturn_XSens_gyrY,100);
+    pltData.rot_yaw_degps = movmean(data.XSens_rateofturn_XSens_gyrZ,100);
 
     %% Inverters
     % inverter temperatures
-    pltData.invL_temp = data.INV_L_TxPDO_1_T_Inv_L(start:stop);
-    pltData.invR_temp = data.INV_R_TxPDO_1_T_Inv_R(start:stop);
+    pltData.invL_temp = data.INV_1_TxPDO_1_T_Inv_1; % not sure if 1 is left and 2 is right
+    pltData.invR_temp = data.INV_2_TxPDO_1_T_Inv_2;
     % motor temperatures
-    pltData.motL_temp = data.INV_L_TxPDO_1_T_Mot_L(start:stop);
-    pltData.motR_temp = data.INV_R_TxPDO_1_T_Mot_R(start:stop);
+    pltData.motL_temp = data.INV_1_TxPDO_1_T_Mot_1; % not sure if 1 is left and 2 is right
+    pltData.motR_temp = data.INV_2_TxPDO_1_T_Mot_2;
     % motor velocities
-    pltData.motL_vel_rpm = 60*data.INV_L_TxPDO_4_Velocity_L(start:stop);
-    pltData.motR_vel_rpm = 60*data.INV_R_TxPDO_4_Velocity_R(start:stop);
+    pltData.motL_vel_rpm = 60*data.INV_1_TxPDO_4_Velocity_1; % not sure if 1 is left and 2 is right
+    pltData.motR_vel_rpm = 60*data.INV_2_TxPDO_4_Velocity_2;
     % inverter torque demand
-    pltData.invL_torqueDemand = data.INV_L_TxPDO_3_DemandedTorque_L(start:stop)/10; % /10 to match autobox torque
-    pltData.invR_torqueDemand = data.INV_R_TxPDO_3_DemandedTorque_R(start:stop)/10;
+    pltData.invL_torqueDemand = data.INV_1_TxPDO_3_DemandedTorque_1/10; % /10 to match autobox torque % not sure if 1 is left and 2 is right
+    pltData.invR_torqueDemand = data.INV_2_TxPDO_3_DemandedTorque_2/10;
     % inverter actual torque
-    pltData.invL_torqueActual = data.INV_L_TxPDO_3_ActualTorque_L(start:stop)/10;
-    pltData.invR_torqueActual = data.INV_R_TxPDO_3_ActualTorque_R(start:stop)/10;
+    pltData.invL_torqueActual = data.INV_1_TxPDO_3_DemandedTorque_1/10; % not sure if 1 is left and 2 is right
+    pltData.invR_torqueActual = data.INV_2_TxPDO_3_DemandedTorque_2/10;
 
     %% Wheelspeed
 
@@ -109,15 +110,18 @@ function [pltData] = sortdata(data,start,stop)
     power_regen_kw(power_regen_kw > 0) = 0;
     power_used_kw = pltData.ams_ptot;
     power_used_kw(power_used_kw < 0) = 0;
-    pltData.energy_kwh = trapz(pltData.time_s, pltData.ams_ptot)/3600;
-    pltData.energy_regen_kwh = trapz(pltData.time_s, power_regen_kw)/3600;
-    pltData.energy_used_kwh = trapz(pltData.time_s, power_used_kw)/3600;
-    pltData.distanceTotal_km = trapz(pltData.time_s, pltData.speed_kph./3.6)/1000; % 1/3.6 for km/h to m/s and /1000 for km output
-    pltData.peakPower_kw = max(pltData.ams_ptot);
-    pltData.peakPowerMean_kw = max(movmean(pltData.ams_ptot,500));
+    stats.energy_kwh = trapz(time_s, pltData.ams_ptot)/3600;
+    stats.energy_regen_kwh = trapz(time_s, power_regen_kw)/3600;
+    stats.energy_used_kwh = trapz(time_s, power_used_kw)/3600;
+    stats.distanceTotal_km = trapz(time_s, pltData.speed_kph./3.6)/1000; % 1/3.6 for km/h to m/s and /1000 for km output
+    stats.peakPower_kw = max(pltData.ams_ptot);
+    stats.peakPowerMean_kw = max(movmean(pltData.ams_ptot,500));
 
-    pltData.maxSpeed_kph = max(pltData.speed_kph);
-    pltData.startTime = time_hms(start);
-    pltData.stopTime = time_hms(stop);
+    stats.maxSpeed_kph = max(pltData.speed_kph);
+    % pltData.startTime = time_hms(1);
+    % pltData.stopTime = time_hms(end);
+
+    %% struct2timetable
+    pltData = table2timetable(struct2table(pltData), "RowTimes", data.Time); 
 end