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Mason-PhillipsMason-Phillips
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KC Night 1 picklist
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5 files changed

+292
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‎2020Analyzer.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -298,7 +298,7 @@ def MatchReport(MatchList, cycleDf, mainDf, TeamNumber):
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teams.extend(match['allies'])
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teams.extend(match['opponents'])
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LastScouted = max(mainDf['matchNo'])
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if match['match'] > LastScouted:
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if match['match'] == 53:
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FileName = 'Match ' + str(match['match']) + ' Pre-match Report.html'
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with open(FileName, 'w') as File:
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File.write('<html>')
@@ -731,7 +731,7 @@ def getPrematchReportDf(mainDf, cycleDf, pitDf):
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botheight = pitDf['Tall or Short bot?']
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teamList = mainDf['teamNo']
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pitTeamList = pitDf['Team number of team you are scouting']
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pitTeamList = pitDf['Team number of the team you are scouting(not 1939 unless you are scouting us)']
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#bottype = pd.pivot_table(pitDf, columns = ['Tall or Short bot?'], index = ['Team number of team you are scouting'])
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heightdict = {'teamNo' : pitTeamList, 'bot height' : botheight}

‎GKC Picklist Graphs.png‎

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‎__pycache__/tbaUtils.cpython-37.pyc‎

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‎graphFunctions2020.py‎

Lines changed: 290 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,290 @@
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# -*- coding: utf-8 -*-
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"""
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Created on Wed Sep 18 14:33:57 2019
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@author: Mason
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"""
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import pandas as pd
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import numpy as np
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import seaborn as sb
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from tkinter import filedialog
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from pprint import pprint
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import matplotlib.pyplot as plt
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import matplotlib.gridspec as gridspec
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import matplotlib.ticker as ticker
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pd.set_option('display.max_columns', 200)
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def combineColumn(scoutData):
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'''
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This combines columns and creates columns from adding other columns. Specifics:
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Total/low/high/outer/inner goal makes/misses/attempts across game phase(overall)
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Percent of shots are makes, percent of makes in low/high/outer goals, accuracy
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in low and high goal, autonomous score, teleop score.
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'''
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scoutData['totalAttempts']=scoutData['lowGoalMissesAuto']+scoutData['highGoalMissesAuto']
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scoutData['totalAttempts']+=scoutData['lowGoalMakesAuto']+scoutData['outerGoalMakesAuto']
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scoutData['totalAttempts']+=scoutData['innerGoalMakesAuto']+scoutData['lowGoalMissesTele']
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scoutData['totalAttempts']+=scoutData['lowGoalMakesTele']+scoutData['outerGoalMakesTele']
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scoutData['totalAttempts']+=scoutData['innerGoalMakesTele']
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scoutData['lowGoalAttemptsAuto']=scoutData['lowGoalMissesAuto']+scoutData['lowGoalMakesAuto']
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scoutData['lowGoalAttemptsTele']=scoutData['lowGoalMissesTele']+scoutData['lowGoalMakesTele']
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scoutData['lowGoalAttempts']=scoutData['lowGoalAttemptsAuto']+scoutData['lowGoalAttemptsTele']
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scoutData['lowGoalMakes']=scoutData['lowGoalMakesAuto']+scoutData['lowGoalMakesTele']
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scoutData['highGoalMakesAuto'] = (scoutData['outerGoalMakesAuto']+scoutData['innerGoalMakesAuto'])
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scoutData['highGoalAttemptsAuto']=(scoutData['outerGoalMakesAuto']+scoutData['innerGoalMakesAuto'])+scoutData['highGoalMissesAuto']
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scoutData['highGoalAttemptsTele']=(scoutData['outerGoalMakesTele']+scoutData['innerGoalMakesTele'])+scoutData['highGoalMissesTele']
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scoutData['highGoalMakesTele']=scoutData['outerGoalMakesTele']+scoutData['innerGoalMakesTele']
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scoutData['highGoalAttempts']=scoutData['highGoalAttemptsAuto']+scoutData['highGoalAttemptsTele']
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scoutData['highGoalMakes']=scoutData['outerGoalMakesTele']+scoutData['outerGoalMakesAuto']+scoutData['innerGoalMakesTele']+scoutData['innerGoalMakesAuto']
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scoutData['outerGoalMakes']=scoutData['outerGoalMakesTele']+scoutData['outerGoalMakesAuto']
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scoutData['innerGoalMakes']=scoutData['innerGoalMakesAuto']+scoutData['innerGoalMakesTele']
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scoutData['totalMakes']=scoutData['innerGoalMakes']+scoutData['outerGoalMakes']+scoutData['lowGoalMakes']
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scoutData['autoMakes']=scoutData['innerGoalMakesAuto']+scoutData['outerGoalMakesAuto']+scoutData['lowGoalMakesAuto']
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scoutData['totalAccuracy']=(scoutData['totalMakes']/scoutData['totalAttempts'])*100
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scoutData['lowGoalMakesAccuracy']=(scoutData['lowGoalMakes']/scoutData['lowGoalAttempts'])*100
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scoutData['lowGoalMakesAccuracyAuto']=(scoutData['lowGoalMakesAuto']/scoutData['lowGoalAttemptsAuto'])*100
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scoutData['lowGoalMakesAccuracyTele']=(scoutData['lowGoalMakesTele']/scoutData['lowGoalAttemptsTele'])*100
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scoutData['highGoalMakesAccuracy']=(scoutData['highGoalMakes']/scoutData['highGoalAttempts'])*100
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scoutData['highGoalMakesAccuracyAuto']=((scoutData['outerGoalMakesAuto']+scoutData['innerGoalMakesAuto'])/scoutData['highGoalAttemptsAuto'])*100
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scoutData['highGoalMakesAccuracyTele']=((scoutData['outerGoalMakesTele']+scoutData['innerGoalMakesTele'])/scoutData['highGoalAttemptsTele'])*100
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scoutData['percentOfLowGoal']=(scoutData['lowGoalMakes']/scoutData['totalMakes'])*100
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scoutData['percentOfOuterGoal']=(scoutData['outerGoalMakes']/scoutData['totalMakes'])*100
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scoutData['percentOfInnerGoal']=(scoutData['innerGoalMakes']/scoutData['totalMakes'])*100
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scoutData['teleopScore']=scoutData['lowGoalMakesTele']+2*scoutData['outerGoalMakesTele']
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scoutData['teleopScore']+=3*scoutData['innerGoalMakesTele']
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scoutData['autoScore']=2*scoutData['lowGoalMakesAuto']+4*scoutData['outerGoalMakesAuto']
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scoutData['autoScore']+=6*scoutData['innerGoalMakesAuto']
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scoutData=scoutData.fillna(0)
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# print(scoutData.head())
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return scoutData
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def getPicklistHeatmap(mainDf, df, ax, graphVar):
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df['highGoalMakes'] = df['innerGoalMakes'] + df['outerGoalMakes']
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pprint(df)
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''' FIX ME VICTORIA
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THE APPEND DOESN'T WORK'''
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mainteams = mainDf['teamNo'].drop_duplicates().to_numpy()
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teams = df['teamNo'].drop_duplicates().to_numpy()
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for team in mainteams:
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if team not in teams:
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#df.append([0, 0, team, 0, 'A', 0, 0, 0, 0, 0, 0])
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newdfentry = pd.DataFrame({'id': [df['id'].max()],'matchNo':[0], 'teamNo':[team], 'cycle':[0], 'shooterPosition':['A'], 'lowGoalMisses':[0],
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'highGoalMisses':[0], 'lowGoalMakes':[0], 'outerGoalMakes':[0], 'innerGoalMakes':[0],
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'gamePhase':[0], 'highGoalMakes':[0]})
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print('\n', newdfentry, '\n')
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df = pd.concat([df, newdfentry], ignore_index=True)
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print(team)
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print()
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print(df.tail())
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print(df['teamNo'].drop_duplicates())
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df = df.sort_values('teamNo', ascending=True)
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highGoalMakesbyMatchDf = getHeatMapPivot(df.loc[:,['matchNo','teamNo','cycle','shooterPosition', graphVar]])
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cookedDf = pd.pivot_table(highGoalMakesbyMatchDf.reset_index().drop(['matchNo'], axis=1), index='teamNo')
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print(cookedDf.stack(1).unstack(level=0))
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yLabels=['A']
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for position in df['shooterPosition'].sort_values().values:
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# print(position)
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passer = False
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for label in yLabels:
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if label == position:
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passer = True
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if passer == False:
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yLabels.append(position)
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teamList = df['teamNo'].drop_duplicates().to_numpy()
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ax.set_title(graphVar)
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sb.heatmap(cookedDf.stack(1).unstack(level=0).to_numpy(), cmap="YlGn", ax=ax, annot=True, vmin=0, vmax=55, yticklabels=yLabels, xticklabels=teamList )
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def getPicklistBoxplotData(df, graphVar, title, ax):
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df = df.sort_values('teamNo', ascending=True)
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df = combineColumn(df)
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teamList = df['teamNo'].drop_duplicates()
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df.set_index('teamNo', inplace = True)
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data = []
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dataArr = []
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k=0
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for team in teamList:
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data.append(df.loc[[team], [graphVar]].get_values())
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for i in data:
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dataArr.append([])
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for j in i:
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dataArr[k].append(j[0])
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k+=1
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ax.set_title(title, fontsize=14)
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ax.set_xticklabels(teamList.get_values())
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ax.boxplot(dataArr)
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def getClimbHeatMap(mainData, ax):
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mainData['climbCounter'] = 1
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climbData = mainData.set_index('teamNo').loc[:, ['climbLevel', 'climbCounter']]
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climbData = pd.pivot_table(climbData.reset_index(), index=['teamNo', 'climbLevel'], aggfunc=sum)
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climbSums = pd.pivot_table(climbData.reset_index(), index='teamNo', columns= 'climbLevel', aggfunc=sum, margins=True)
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climbSums.fillna(0, inplace=True)
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climbSums.drop('All', inplace=True)
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xLabels = climbSums.index.to_series().values
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climbSums = climbSums.stack(1).unstack(level=0)
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climbSums.drop('No Climb', inplace=True)
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yLabels = climbSums.index.to_series().values
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sb.heatmap(climbSums.to_numpy(), cmap="YlGn", ax=ax, annot=True, yticklabels=yLabels, xticklabels = xLabels)
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def getTeamList(df):
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teamList = df['teamNo'].drop_duplicates()
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return(teamList)
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def initPicklistGraph(teamList):
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fig = plt.figure(tight_layout=True, figsize=(len(teamList), 10))
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gs = gridspec.GridSpec(5, 1)
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return fig, gs
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def initMatchReportGraph():
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fig = plt.figure(tight_layout=True, figsize=(14, 7))
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gs = gridspec.GridSpec(2, 4)
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return fig, gs
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def picklistGraphs(df, cycleDf):
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fig, gs = initPicklistGraph(getTeamList(df))
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ax1 = fig.add_subplot(gs[0, 0])
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ax2 = fig.add_subplot(gs[1, 0])
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ax3 = fig.add_subplot(gs[2, 0])
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ax4 = fig.add_subplot(gs[3, 0])
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ax5 = fig.add_subplot(gs[4, 0])
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getPicklistBoxplotData(df, 'totalMakes', 'Total Shots Made', ax1)
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getPicklistBoxplotData(df, 'highGoalMakes', 'Total High Shots Made', ax2)
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getPicklistBoxplotData(df, 'autoMakes', 'Total Auto Shots Made', ax3)
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getPicklistHeatmap(df, cycleDf, ax4, 'highGoalMakes')
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getClimbHeatMap(df, ax5)
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plt.savefig(input('Event name: ') + ' Picklist Graphs')
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plt.show()
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def getPrematchScatterPlot(df, team, graphVar, ax):
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ax.scatter(df.loc[[team], ["matchNo"]], df.loc[[team], [graphVar]], color="red")
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ax.set_ylim(top=55, bottom=0)
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ax.xaxis.set_major_locator(ticker.MaxNLocator(integer=True))
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if graphVar == 'autoMakes':
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ax.set_ylim(top=15, bottom=0)
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ax.set_title(graphVar)
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ax.set_xlabel('Matches')
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ax.set_ylabel(graphVar)
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def getHeatMapPivot(df):
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firstmove = pd.pivot_table(df, index=['matchNo','teamNo','cycle'], columns='shooterPosition',aggfunc=np.sum).fillna(0)
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print(firstmove)
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secondmove = firstmove.groupby(axis=0,level=['matchNo','teamNo'])
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thirdmove = secondmove.sum()
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# print(thirdmove)
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fourthmove = thirdmove.swaplevel(i='matchNo',j='teamNo').sort_index()
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# print(fourthmove)
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return fourthmove
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def getHeatMap(df, mainDf, team, graphVar, ax):
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maxShot =55
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df['highGoalMakes'] = df['innerGoalMakes'] + df['outerGoalMakes']
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df['lowGoalAttempts'] = df['lowGoalMisses'] + df['lowGoalMakes']
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df['highGoalAttempts'] = df['highGoalMisses'] + df['innerGoalMakes'] + df['outerGoalMakes']
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highGoalMakesbyMatchDf = getHeatMapPivot(df.loc[:,['matchNo','teamNo','cycle','shooterPosition', graphVar]])
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yLabels=['A']
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matchNum = []
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for position in df['shooterPosition'].sort_values().values:
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passer = False
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for label in yLabels:
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if label == position:
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passer = True
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if passer == False:
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yLabels.append(position)
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for match in mainDf.set_index('teamNo').loc[[team], ["matchNo"]].values:
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matchNum.append(str(match[0]))
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print(matchNum)
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print(yLabels)
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ax.set_title(graphVar)
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ax.set_xlabel('Matches')
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ax.set_ylabel('Position')
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try: sb.heatmap(highGoalMakesbyMatchDf.loc[[team], :].unstack().stack(1).to_numpy(), cmap="YlGn", ax=ax, annot=True, yticklabels=yLabels, xticklabels=matchNum, vmin=0, vmax=maxShot)
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except:print('data not available')
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def prematchGraphs(maindf, cycledf, team):
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df = combineColumn(maindf)
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df.set_index("teamNo", inplace = True)
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fig, gs = initMatchReportGraph()
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ax1 = fig.add_subplot(gs[0, 0])
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ax2 = fig.add_subplot(gs[0, 1])
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ax3 = fig.add_subplot(gs[0, 2])
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ax4 = fig.add_subplot(gs[0, 3])
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ax5 = fig.add_subplot(gs[1, 1])
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ax6 = fig.add_subplot(gs[1, 2])
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ax7 = fig.add_subplot(gs[1, 3])
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getPrematchScatterPlot(df, team, 'autoMakes', ax1)
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getPrematchScatterPlot(df, team, 'totalMakes', ax2)
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getHeatMap(cycledf, maindf, team, 'highGoalAttempts', ax3)
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getHeatMap(cycledf, maindf, team, 'lowGoalAttempts', ax4)
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getHeatMap(cycledf, maindf, team, 'innerGoalMakes', ax5)
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getHeatMap(cycledf, maindf, team, 'outerGoalMakes', ax6)
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getHeatMap(cycledf, maindf, team, 'lowGoalMakes', ax7)
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ax3.title.set_position([.5, 1.2])
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ax4.title.set_position([.5, 1.2])
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ax5.title.set_position([.5, 1.2])
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ax6.title.set_position([.5, 1.2])
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ax7.title.set_position([.5, 1.2])
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plt.savefig(str(team) + ' Prematch Graphs')
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plt.show()
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maindf = pd.read_csv(filedialog.askopenfilename(title = 'select unfiltered main data file'), sep = '|')
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cycledf = pd.read_csv(filedialog.askopenfilename(title = 'select unfiltered cycle data file'), sep = '|')
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picklistGraphs(maindf, cycledf)
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#prematchGraphs(maindf, cycledf, 1939)
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#getPicklistHeatmapPivot(cycledf, 'outerGoalMakes')

‎prematch scouting report2020-02-29-19-11-23.xlsx‎

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