Class constructor says "not enough input arguments"

I am trying to implement a particle filter and run it on saved data. One function "pf2_1" loops through the data and uses a particle filter constructed in the class "Model". It is in a separate class for organization purposes.

When I try and construct Model, I get the following error:

Not enough input arguments.
Error in pf2_1 (line 52)
      model = Model(sensorPositions, gsd_, np_, psf_, rsm_);

I added underscores after those inputs for fear I was having a name conflict. No matter what I try I cannot get past the construction. Below are my files:

pf2_1:

% D is [secs, mins, raw data... raw data, state est 1... state est n]
%function [avgDist, avgAng, stddevDist, stddevAng, D] = doPF(dataFile, aggFname, directory, params)
function [avgDistMean, avgAngMean, stddevDistMean, stddevAngMean, avgDistMax, avgAngMax, stddevDistMax, stddevAngMax, D] = pf2_1(simFile, makePlot, gsd_, wbd, psf_, np_, sem, rsm_)

      %clear all 
      %close all
      %fclose('all');
      delete(instrfindall) % For open serial ports

      % Output file
      outputname = '';

      % Declare # of receivers
      NUM_RECEIVERS = 6;

      sensorPositions = zeros(2, NUM_RECEIVERS);

      % Plot or no plot?
      PLOT = makePlot;
      myPlot = [];

      % Live or simulated?
      LIVE = false;

      if (LIVE) 
          %   Specify beacon locations

          %   initialize beacons (do all this in beacon-handling class?)

          %   collect garbage

          %   ENSURE ALL OF THEM ARE TALKING TO YOU

          %   They are talking? Good, start up everything else

          %   Create file to log to (inside file handling class!!)

      else
          sim_file = simFile;

          data = csvread(sim_file);

          %disp(size(sensorPositions(1,:)));
          %disp(size(data(1,2:2+NUM_RECEIVERS)));

          sensorPositions(1,:) = data(1,3:2+NUM_RECEIVERS);
          sensorPositions(2,:) = data(2,3:2+NUM_RECEIVERS);

          %disp(sensorPositions);

          % Create model (includes particle filter, mapping RSSI-m, etc...
          %                            ====================== ERROR OCCURS HERE ======================
          model = Model(sensorPositions, gsd_, np_, psf_, rsm_);
          %model = Model();
          %model.begin(sensorPositions, gsd_, np_, psf_, rsm_);

          % Create plot class
          if (PLOT)
              myPlot = PlotClass();
              myPlot.begin(max(sensorPositions(1,:)), max(sensorPositions(2,:)), ...
                  sensorPositions, model.bound, ... 
                  LIVE); % Not live if in this branch, leave for ease of reuse

          end

          disp('starting loop');

          distMeanList = []; % Can predetermine size for improved speed
          angleMeanList = [];
          distMaxList = [];
          angleMaxList = [];
          D = [];

          % Loop over data
          for s=3:length(data)
              [statePred, covPred] = predict(model.pf, model.noise);
              %disp('exited predict');

              secs = data(s, 1);
              mins = data(s, 2);
              raws = data(s, 3:2+NUM_RECEIVERS);
              x_truth = data(s, 3+NUM_RECEIVERS);
              y_truth = data(s, 4+NUM_RECEIVERS);

              %mapped = model.RSSI_TO_M_COEFF * exp(model.RSSI_TO_M_EXP * data(s, 3:2+NUM_RECEIVERS));
              mapped = model.RSSI_TO_M_COEFF * exp(model.RSSI_TO_M_EXP * raws);

              %[stateCorrected, covCorrected] = correct(model.pf, data(s, 3:2+NUM_RECEIVERS), sensorPositions);
              [stateCorrected, covCorrected] = correct(model.pf, mapped, sensorPositions);
              %disp('exited correct');

              %disp(stateCorrected);

              % Get dist from truth
              diff = sqrt((stateCorrected(1)-y_truth)^2 + (stateCorrected(2)-y_truth)^2);

              %disp(data(s, 3+NUM_RECEIVERS:4+NUM_RECEIVERS));
              %disp(stateCorrected);

              angle = atan2(x_truth-stateCorrected(1), y_truth-stateCorrected(2));

              D = [D, [stateCorrected, covCorrected]];
              distMeanList = [distMeanList, diff];
              angleMeanList = [angleMeanList, angle];

              notNeeded, idx = max(model.pf.Weights);
              diffMax = sqrt((model.pf.Particles(idx,2)-y_truth)^2 + (model.pf.Particles(idx,1)-y_truth)^2);
              angleMax = atan2(x_truth-model.pf.Particles(idx,1), y_truth-model.pf.Particles(idx,2));

              distMaxList = [distMaxList, diffMax];
              angleMaxList = [angleMaxList, angleMax];

              %disp(diff);
              %disp(angle);
              %disp(sprintf('%f, %f', diff, angle));

              %rawString = sprintf('%d, ', raws);

              % secs, mins, raw data, x truth, y truth, x meas, y meas, diff, angle
              %toPrint = sprintf('%f,%f,%s,%d,%d,%d,%d,%f,%f', secs, mins, rawString, x_truth, y_truth, stateCorrected(1), stateCorrected(2), diff, angle);

              %disp(toPrint);

              %fprintf(fid, '%s', toPrint);
              %fprintf(fid, '\n');

              if (PLOT)
                  %myPlot.updatePlotSim(model.pf, data(s,1), stateCorrected, data(s, 2+NUM_RECEIVERS:3+NUM_RECEIVERS));
                  myPlot.updatePlotSim(model.pf, data(s,1), mapped, sensorPositions, stateCorrected, [x_truth, y_truth]);
                  disp('updated plot');
              end

          end

          avgDistMean = mean(distMeanList);
          avgAngMean = mean(angleMeanList);
          stddevDistMean = std2(distMeanList); 
          stddevAngMean = std2(angleMeanList);
          avgDistMax = mean(distMaxList);
          avgAngMax = mean(angleMaxList);
          stddevDistMax = std2(distMaxList); 
          stddevAngMax = std2(angleMaxList);

      end

end

Model:

classdef Model < handle
% Holds all the tuable parameters of the particle filter

      properties(SetAccess = public)
          % The particle filter
          %pf = robotics.ParticleFilter % Is this allowed here?
          pf

          % # of particles in the filter
          NUM_PARTICLES = 1000

          % Boundaries of the system, square with edge 2*bound
          bound = 10

          % sensor positions (x, y)
          sensorPositions

          % Noise parameter 
          noise = 0.1

          % State estimation method
          sem = 'mean' % or 'maxweight'

          % Resampling mehtod 'multinomial' or 'systematic'
          rsm = 'systematic'

          % Gaussian stddev in mlf
          gsd

          % RSSI to m conversion coeffs
          RSSI_TO_M_COEFF = 0.00482998
          RSSI_TO_M_EXP = -0.104954

      end

      properties(SetAccess = private)

      end

      methods

%         function obj = Model(sensorPositions, gsd, numParticles, psf, rsm)
        %function obj = Model()
%             %pf = robotics.ParticleFilter; % Do stuff like this in the
%             %properties
%             obj.pf = robotics.ParticleFilter;
%             
%             obj.gsd = gsd;
%             obj.NUM_PARTICLES = numParticles;
%             obj.noise = psf;
%             %obj.sem = sem;
%             obj.rsm = rsm;
%             
%             stateBounds = [
%                 -obj.bound, obj.bound;
%                 -obj.bound, obj.bound];
%             initialize(obj.pf, obj.NUM_PARTICLES, stateBounds);
%             
%             obj.pf.StateEstimationMethod = 'mean'; % is this allowed in the properties?
%             obj.pf.ResamplingMethod = obj.rsm; 
%             
%             obj.pf.StateTransitionFcn = @stf1_1;
%             obj.pf.MeasurementLikelihoodFcn = @mlf1_1;
%             
%             obj.sensorPositions = sensorPositions;

              % Do nothing?

          %end

          %function begin(obj, array)
          %function begin(obj, sensorPosition, gsd, numParticles, psf, rsm)
          function obj = Model(sensorPosition_, gsd_, numParticles_, psf_, rsm_)

               %[sensorPosition, gsd, numParticles, psf, rsm] = array;
  %             sensorPosition = array(0);
  %             gsd = array(1);
  %             numParticles = array(2);
  %             psf = array(3);
  %             rsm = array(4); 

              obj.pf = robotics.ParticleFilter;

              obj.gsd = gsd_;
              obj.NUM_PARTICLES = numParticles_;
              obj.noise = psf_;
              %obj.sem = sem;
              obj.rsm = rsm_;

              stateBounds = [
                  -obj.bound, obj.bound;
                  -obj.bound, obj.bound];
              initialize(obj.pf, obj.NUM_PARTICLES, stateBounds);

              obj.pf.StateEstimationMethod = 'mean'; % is this allowed in the properties?
              obj.pf.ResamplingMethod = obj.rsm; 

              obj.pf.StateTransitionFcn = @stf1_1;
              obj.pf.MeasurementLikelihoodFcn = @mlf1_1;

              obj.sensorPositions = sensorPosition_;
          end

          function [stateCorrected, covCorrected] = correct(pf, measurement, sensorPositions)
              [stateCorrected, covCorrected] = correct(pf, measurement, sensorPositions, obj.gsd);

          end

          function [statePred, covPred] = predict(pf, NOISE)
              [statePred, covPred] = predict(pf, NOISE);

          end

      end

end

As you can see I have also tried an initialization function for Model (begin) instead of doing everything in the constructor and received the same error. I also tried passing the variables in an array instead of one at a time and received the same "Not enough inputs" error.

If you see any other ways I can improve my organization, efficiency, etc your suggestions are appreciated.

[Adam]

How are you calling your pf2_1 function? The error is here, not anything to do with your class so changing the constructor, using an initialisation function, etc, etc will make no difference at all.

It appears that at least one of gsd_, np_, psf_, rsm_ does not exist in the workspace when you make the call to construct your class, which is why you get the error. The error is not pointing inside your constructor which it would do if the error was one of not having passed in enough input arguments to it.

[Thomas]

You are right, I had an extra argument in that file. Thank you!! Why did matlab not produce an error at the pf2_1 function or call?

[Adam]

You only get an error when you try to use one of the input arguments. If you never use it Matlab doesn't care if you pass it in or not. This is how you can have optional arguments to a function.

So if you don't use an input argument until line 200 you won't get the error until then if it doesn't exist.

This is one of the reasons I use

doc validateattributes

in most of my public functions for every input argument, together with narginchk and if exist(...) and ~isempty(...) type checks on all my input arguments so that I will get these errors at the top of a function rather than further down where their cause may be less obvious

[Thomas]

I will start doing that too. Thanks again!

Answer 1

[Thomas]

Adam identified the problem in his comment.