parser/statistics.py at master · simpaddock/parser · GitHub

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from collections import OrderedDict
from classes.sessionresult import SessionResult
from typing import List
import matplotlib.pyplot as plt
import numpy as np
from hashlib import sha256
import random
from os.path import join

def getHotLaps(results: List[SessionResult]):
  tracks = OrderedDict()
  for result in results:
    if result.getHash() not in tracks:
      tracks[result.getHash()] = OrderedDict()
    for driver in result.Drivers:
      hotlapTime = driver.BestLapTime
      if driver.getHash() in tracks[result.getHash()]:
        existingHotLap =  tracks[result.getHash()][driver.getHash()]["BestLapTime"]
        if existingHotLap > hotlapTime and hotlapTime > 0.0:
          tracks[result.getHash()][driver.getHash()]["BestLapTime"] = hotlapTime
          tracks[result.getHash()][driver.getHash()]["ResultFile"] = result.getPageFilename()
        tracks[result.getHash()][driver.getHash()]["LapCount"] = tracks[result.getHash()][driver.getHash()]["LapCount"] + driver.getTimedLaps()
        tracks[result.getHash()][driver.getHash()]["AllLapCount"] = tracks[result.getHash()][driver.getHash()]["AllLapCount"] + len(driver.Laps)
      else:
        if driver.BestLapTime != 0.0:
          tracks[result.getHash()][driver.getHash()] = {
            "Name": driver.Name,
            "Vehicle": driver.VehName,
            "CarType": driver.CarType,
            "BestLapTime": driver.BestLapTime,
            "LapCount": driver.getTimedLaps(),
            "AllLapCount": len(driver.Laps),
            "Track": result.TrackEvent,
            "ResultFile": result.getPageFilename()
          }
  return tracks

def calculateGaps(result: SessionResult):
  gaps= OrderedDict()
  for lapCount in range(0, result.MostLapsCompleted ):
    leadingTime = 0.0
    for driver in result.Drivers:
      if  driver.Name not in gaps:
        gaps[driver.Name] = []
      # get the currently leading car
      if lapCount < len(driver.Laps):
        if  driver.Laps[lapCount].Position == 1:
          leadingTime = driver.Laps[lapCount].Et


    for driver in result.Drivers:
      if lapCount < len(driver.Laps):
        ownTime =  driver.Laps[lapCount].Et
        delta = ownTime - leadingTime
        # negative delta?
        gaps[driver.Name].append(delta)

  return gaps

def plotGaps(result: SessionResult, targetDirectory):

  plt.clf()
  plt.cla()
  plt.close()
  gaps = calculateGaps(result)
  for driver in gaps:
    y = gaps[driver]
    x = []
    for i in range(0, len(y) ):
      x.append(i)
    plt.plot(x,y,label=driver,color=(np.random.uniform(0, 1), np.random.uniform(0, 1), np.random.uniform(0, 1)))

  plt.xlim(left=0,right=result.MostLapsCompleted -1)
  plt.xticks(np.arange(0, result.MostLapsCompleted , 1.0))
  plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
  plt.savefig(join(targetDirectory,"{0}{1}{2}_gaps.png".format(result.getHash(),result.DateTime,result.Session)), bbox_inches='tight')


def getPositions(result: SessionResult):
  results = OrderedDict()
  for driver in result.Drivers:
    results[driver.Name] = [driver.ClassGridPos]
    for lap in driver.Laps:
      results[driver.Name].append(lap.Position)
  return results

def plotPositionGraph(result: SessionResult, targetDirectory):

  plt.clf()
  plt.cla()
  plt.close()
  results = getPositions(result)
  yticks = []
  sortedDrivers = sorted(result.Drivers, key=lambda x: x.ClassGridPos, reverse=False)
  for driver in sortedDrivers:
    yticks.append(driver.Name)
  for name in results:
    x = []
    y = results[name]
    for i in range(0, len(y) ):
      x.append(i)

    plt.plot(x,y,label=name)
  plt.xlim(left=1,right=result.MostLapsCompleted)
  plt.ylim(bottom=len(result.Drivers), top=0)
  plt.yticks(np.arange(1,len(result.Drivers)  +1),yticks)
  plt.xticks(np.arange(0, result.MostLapsCompleted +1, 1.0))
  plt.savefig(join(targetDirectory,"{0}{1}{2}_positions.png".format(result.getHash(),result.DateTime,result.Session)), bbox_inches='tight')

def plotStandardDeviation(result:SessionResult, targetDirectory):
  x = []
  y = []
  for driver in result.Drivers:
    x.append(driver.Name)
    y.append(driver.getStandardDeviation())


  plt.clf()
  plt.cla()
  plt.close()

  objects = x
  y_pos = np.arange(len(x))
  performance = [10,8,6,4,2,1]

  plt.bar(y_pos, y, align='center', alpha=0.5)
  plt.xticks(y_pos, x)
  plt.ylabel('Deviation in seconds')
  plt.xticks(rotation=90)
  plt.savefig(join(targetDirectory,"{0}{1}{2}_deviations.png".format(result.getHash(),result.DateTime,result.Session)), bbox_inches='tight')