process_constraints.py

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import math
import sys
import matplotlib.pyplot as plt
import random
 
'''
Purpose: This is a simple graphing tool to find the relationship between number of nodes
                 and number of constraints over time.
 
To use: add the following code to publishGraph and disable the optimizer printouts
 
  std::map<karto::Name, std::vector<karto::Vertex<karto::LocalizedRangeScan>*> > vertices = mapper_->GetGraph()->GetVertices();
  std::vector<karto::Vertex<karto::LocalizedRangeScan>*>::const_iterator it;
  std::map<int, int> vertex_ctr;
  for (it = vertices[mapper_->GetMapperSensorManager()->GetSensorNames()[0]].begin(); it != vertices[mapper_->GetMapperSensorManager()->GetSensorNames()[0]].end(); ++it)
  {
    int num = (*it)->GetEdges().size();
    if (vertex_ctr.find(num) == vertex_ctr.end())
    {
      vertex_ctr[num] = 1;
    }
    vertex_ctr[num]++;
  }
 
  std::cout << "UpdateMap: Vertex count: " << std::endl;
  std::map<int, int>::const_iterator it2;
  for (it2 = vertex_ctr.begin(); it2 != vertex_ctr.end(); ++it2)
  {
    std::cout << it2->first << " constraints are in " << it2->second << " vertexes" << std::endl;
  }
  std::cout << std::endl;
'''
 
def readFileToList(filename):
        with open(filename) as fp:
                line = fp.readline()
                lines = []
                lines.append(line)
                while line:
                        line = fp.readline()
                        lines.append(line)
        return lines
 
def getSingleSets(lines):
        measurements = []
        measurement = []
        for line in lines:
                if line == "\n":
                        continue
                if "UpdateMap: Vertex count:" in line:
                        measurements.append(measurement)
                        measurement = []
                measurement.append(line)
        return measurements[1:]
 
def processForData(measurements):
        measurements_out = []
        measurement_out = []
        for measurement in measurements:
                for m in measurement:
                        txt = m.split(" ")
                        nums = [r for r in txt if r.isdigit()]
                        if not nums:
                                continue
                        measurement_out.append(nums)
                measurements_out.append(measurement_out)
                measurement_out = []
        return measurements_out
 
def plotData(data):
        #plot lines
 
        # give us the number of lines to create and unque items
        max_size = 0
        keys = []
        for d in data:
                for m in d:
                        if m[0] not in keys:
                                keys.append(m[0])
 
        data_len = len(data)
 
        dat = {}
        for k in keys:
                dat[k] = []
 
        for d in data:
                local_keys = []
                for pt in d:
                        local_keys.append(pt[0])
                        dat[pt[0]].append(int(pt[1]))
                for k in keys:
                        if k not in local_keys:
                                dat[k].append(0)
 
        total_nodes = []
        for d in data:
                summ = 0
                for pt in d:
                        summ = summ + int(pt[1])
                total_nodes.append(summ)
 
        for k in keys:
                plt.plot( [10*i for i in range(0, len(dat[k]))], dat[k], marker='o', color=[random.random(),random.random(),random.random()], linewidth=2, label=k+' Constraints')
        
        plt.plot( [10*i for i in range(0, len(dat[k]))], total_nodes, marker='o', color=[random.random(),random.random(),random.random()], linewidth=2, label='Total Num. Nodes')
        plt.legend()
        plt.xlabel("time (s)")
        plt.ylabel("Node count")
        #plt.yscale("log")
        plt.show()
 
if __name__ == "__main__":
        filename = sys.argv[1]
        print ("reading file: " + filename)
        listOfContents = readFileToList(filename)
        listOfListOfMeasurements = getSingleSets(listOfContents)
        data = processForData(listOfListOfMeasurements)
        plotData(data)