mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-12-28 10:39:09 +00:00
removed gui (last commit tagged "gui"),
removed print statement in pit module Former-commit-id: 4978aee142eaf9431913b44eabfc0dfb79c7b600
This commit is contained in:
Arthur Lu
parent
9c152fb109
commit
524a0a211d
129
src/gui/data.py
129
src/gui/data.py
@ -1,129 +0,0 @@
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import requests
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import pymongo
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import pandas as pd
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import time
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def pull_new_tba_matches(apikey, competition, cutoff):
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api_key= apikey
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x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth_Key":api_key})
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out = []
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for i in x.json():
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if i["actual_time"] != None and i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm":
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out.append({"match" : i['match_number'], "blue" : list(map(lambda x: int(x[3:]), i['alliances']['blue']['team_keys'])), "red" : list(map(lambda x: int(x[3:]), i['alliances']['red']['team_keys'])), "winner": i["winning_alliance"]})
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return out
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def get_team_match_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.matchdata
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out = {}
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for i in mdata.find({"competition" : competition, "team_scouted": team_num}):
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out[i['match']] = i['data']
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return pd.DataFrame(out)
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def get_team_pit_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.pitdata
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out = {}
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return mdata.find_one({"competition" : competition, "team_scouted": team_num})["data"]
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def get_team_metrics_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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mdata = db.team_metrics
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return mdata.find_one({"competition" : competition, "team": team_num})
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def get_match_data_formatted(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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out = {}
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for i in x:
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try:
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out[int(i)] = unkeyify_2l(get_team_match_data(apikey, competition, int(i)).transpose().to_dict())
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except:
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pass
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return out
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def get_metrics_data_formatted(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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out = {}
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for i in x:
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try:
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out[int(i)] = d.get_team_metrics_data(apikey, competition, int(i))
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except:
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pass
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return out
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def get_pit_data_formatted(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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out = {}
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for i in x:
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try:
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out[int(i)] = get_team_pit_data(apikey, competition, int(i))
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except:
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pass
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return out
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def get_pit_variable_data(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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mdata = db.team_pit
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out = {}
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return mdata.find()
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def get_pit_variable_formatted(apikey, competition):
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temp = get_pit_variable_data(apikey, competition)
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out = {}
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for i in temp:
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out[i["variable"]] = i["data"]
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return out
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def push_team_tests_data(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
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client = pymongo.MongoClient(apikey)
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db = client[dbname]
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mdata = db[colname]
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mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "data" : data}, True)
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def push_team_metrics_data(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_metrics"):
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client = pymongo.MongoClient(apikey)
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db = client[dbname]
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mdata = db[colname]
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mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "metrics" : data}, True)
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def push_team_pit_data(apikey, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
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client = pymongo.MongoClient(apikey)
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db = client[dbname]
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mdata = db[colname]
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mdata.replace_one({"competition" : competition, "variable": variable}, {"competition" : competition, "variable" : variable, "data" : data}, True)
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def get_analysis_flags(apikey, flag):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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mdata = db.flags
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return mdata.find_one({flag:{"$exists":True}})
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def set_analysis_flags(apikey, flag, data):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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mdata = db.flags
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return mdata.replace_one({flag:{"$exists":True}}, data, True)
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def unkeyify_2l(layered_dict):
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out = {}
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for i in layered_dict.keys():
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add = []
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sortkey = []
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for j in layered_dict[i].keys():
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add.append([j,layered_dict[i][j]])
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add.sort(key = lambda x: x[0])
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out[i] = list(map(lambda x: x[1], add))
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return out
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@ -1,151 +0,0 @@
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<Launch>:
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orientation: "vertical"
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NavigationLayout:
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ScreenManager:
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id: screen_manager
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HomeScreen:
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name: "Home"
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BoxLayout:
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orientation: "vertical"
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MDToolbar:
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title: screen_manager.current
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elevation: 10
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left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
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GridLayout:
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cols: 1
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padding: 15, 15
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spacing: 20, 20
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MDTextFieldRect:
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hint_text: "Console Log"
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# size_hint: .8, None
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# align: 'center'
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# Widget:
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SettingsScreen:
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name: "Settings"
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BoxLayout:
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orientation: 'vertical'
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MDToolbar:
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title: screen_manager.current
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elevation: 10
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left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
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Widget:
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InfoScreen:
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name: "Info"
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BoxLayout:
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orientation: 'vertical'
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MDToolbar:
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title: screen_manager.current
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elevation: 10
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left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
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# GridLayout:
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# cols: 2
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# padding: 15, 15
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# spacing: 20, 20
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BoxLayout:
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orientation: "horizontal"
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MDLabel:
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text: "DB Key:"
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halign: 'center'
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MDTextField:
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hint_text: "placeholder"
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pos_hint: {"center_y": .5}
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BoxLayout:
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orientation: "horizontal"
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MDLabel:
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text: "TBA Key:"
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halign: 'center'
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MDTextField:
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hint_text: "placeholder"
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pos_hint: {"center_y": .5}
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BoxLayout:
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orientation: "horizontal"
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MDLabel:
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text: "CPU Use:"
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halign: 'center'
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MDLabel:
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text: "placeholder"
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halign: 'center'
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BoxLayout:
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orientation: "horizontal"
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MDLabel:
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text: "Network:"
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halign: 'center'
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MDLabel:
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text: "placeholder"
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halign: 'center'
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Widget:
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BoxLayout:
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orientation: "horizontal"
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MDLabel:
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text: "Progress"
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halign: 'center'
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MDProgressBar:
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id: progress
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value: 50
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StatsScreen:
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name: "Stats"
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MDCheckbox:
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size_hint: None, None
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size: "48dp", "48dp"
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pos_hint: {'center_x': .5, 'center_y': .5}
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on_active: Screen.test()
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#Navigation Drawer -------------------------
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MDNavigationDrawer:
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id: nav_drawer
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BoxLayout:
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orientation: "vertical"
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padding: "8dp"
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spacing: "8dp"
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MDLabel:
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text: "Titan Scouting"
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font_style: "Button"
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size_hint_y: None
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height: self.texture_size[1]
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MDLabel:
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text: "Data Analysis"
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font_style: "Caption"
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size_hint_y: None
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height: self.texture_size[1]
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ScrollView:
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MDList:
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OneLineAvatarListItem:
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text: "Home"
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on_press:
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# nav_drawer.set_state("close")
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# screen_manager.transition.direction = "left"
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screen_manager.current = "Home"
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IconLeftWidget:
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icon: "home"
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OneLineAvatarListItem:
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text: "Settings"
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on_press:
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# nav_drawer.set_state("close")
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# screen_manager.transition.direction = "right"
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# screen_manager.fade
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screen_manager.current = "Settings"
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IconLeftWidget:
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icon: "cog"
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OneLineAvatarListItem:
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text: "Info"
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on_press:
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# nav_drawer.set_state("close")
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# screen_manager.transition.direction = "right"
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# screen_manager.fade
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screen_manager.current = "Info"
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IconLeftWidget:
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icon: "cog"
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OneLineAvatarListItem:
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text: "Stats"
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on_press:
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# nav_drawer.set_state("close")
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# screen_manager.transition.direction = "right"
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# screen_manager.fade
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screen_manager.current = "Stats"
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IconLeftWidget:
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icon: "cog"
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@ -1,58 +0,0 @@
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from kivy.lang import Builder
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from kivymd.uix.screen import Screen
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from kivymd.uix.list import OneLineListItem, MDList, TwoLineListItem, ThreeLineListItem
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from kivymd.uix.list import OneLineIconListItem, IconLeftWidget
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from kivy.uix.scrollview import ScrollView
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from kivy.uix.boxlayout import BoxLayout
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from kivy.uix.screenmanager import ScreenManager, Screen
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from kivy.uix.dropdown import DropDown
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from kivy.uix.button import Button
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from kivy.base import runTouchApp
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from kivymd.uix.menu import MDDropdownMenu, MDMenuItem
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from kivymd.app import MDApp
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# import superscript as ss
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# from tra_analysis import analysis as an
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import data as d
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from collections import defaultdict
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import json
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import math
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import numpy as np
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import os
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from os import system, name
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from pathlib import Path
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from multiprocessing import Pool
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import matplotlib.pyplot as plt
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from concurrent.futures import ThreadPoolExecutor
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import time
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import warnings
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# global exec_threads
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# Screens
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class HomeScreen(Screen):
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pass
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class SettingsScreen(Screen):
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pass
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class InfoScreen(Screen):
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pass
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class StatsScreen(Screen):
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pass
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class MyApp(MDApp):
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def build(self):
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self.theme_cls.primary_palette = "Red"
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return Builder.load_file("design.kv")
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def test():
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print("test")
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if __name__ == "__main__":
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MyApp().run()
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@ -1,627 +0,0 @@
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# Titan Robotics Team 2022: Superscript Script
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# Written by Arthur Lu, Jacob Levine, and Dev Singh
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# Notes:
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# setup:
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__version__ = "0.8.6"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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0.8.6:
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- added proper main function
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0.8.5:
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- added more gradeful KeyboardInterrupt exiting
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- redirected stderr to errorlog.txt
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0.8.4:
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- added better error message for missing config.json
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- added automatic config.json creation
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- added splash text with version and system info
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0.8.3:
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- updated matchloop with new regression format (requires tra_analysis 3.x)
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0.8.2:
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- readded while true to main function
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- added more thread config options
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0.8.1:
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- optimized matchloop further by bypassing GIL
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0.8.0:
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- added multithreading to matchloop
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- tweaked user log
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0.7.0:
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- finished implementing main function
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0.6.2:
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- integrated get_team_rankings.py as get_team_metrics() function
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- integrated visualize_pit.py as graph_pit_histogram() function
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0.6.1:
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- bug fixes with analysis.Metric() calls
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- modified metric functions to use config.json defined default values
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0.6.0:
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- removed main function
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- changed load_config function
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- added save_config function
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- added load_match function
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- renamed simpleloop to matchloop
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- moved simplestats function inside matchloop
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- renamed load_metrics to load_metric
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- renamed metricsloop to metricloop
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- split push to database functions amon push_match, push_metric, push_pit
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- moved
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0.5.2:
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- made changes due to refactoring of analysis
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0.5.1:
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- text fixes
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- removed matplotlib requirement
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0.5.0:
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- improved user interface
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0.4.2:
|
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- removed unessasary code
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0.4.1:
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- fixed bug where X range for regression was determined before sanitization
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- better sanitized data
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0.4.0:
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- fixed spelling issue in __changelog__
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- addressed nan bug in regression
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- fixed errors on line 335 with metrics calling incorrect key "glicko2"
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- fixed errors in metrics computing
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0.3.0:
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- added analysis to pit data
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0.2.1:
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- minor stability patches
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- implemented db syncing for timestamps
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- fixed bugs
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0.2.0:
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- finalized testing and small fixes
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0.1.4:
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- finished metrics implement, trueskill is bugged
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0.1.3:
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- working
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0.1.2:
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- started implement of metrics
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0.1.1:
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- cleaned up imports
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0.1.0:
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- tested working, can push to database
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0.0.9:
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- tested working
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- prints out stats for the time being, will push to database later
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0.0.8:
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- added data import
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- removed tba import
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- finished main method
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0.0.7:
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- added load_config
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- optimized simpleloop for readibility
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- added __all__ entries
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- added simplestats engine
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- pending testing
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0.0.6:
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- fixes
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0.0.5:
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- imported pickle
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- created custom database object
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0.0.4:
|
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- fixed simpleloop to actually return a vector
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0.0.3:
|
||||
- added metricsloop which is unfinished
|
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0.0.2:
|
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- added simpleloop which is untested until data is provided
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0.0.1:
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- created script
|
||||
- added analysis, numba, numpy imports
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"""
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|
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__author__ = (
|
||||
"Arthur Lu <learthurgo@gmail.com>",
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"Jacob Levine <jlevine@imsa.edu>",
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)
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|
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__all__ = [
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"load_config",
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"save_config",
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"get_previous_time",
|
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"load_match",
|
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"matchloop",
|
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"load_metric",
|
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"metricloop",
|
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"load_pit",
|
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"pitloop",
|
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"push_match",
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"push_metric",
|
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"push_pit",
|
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]
|
||||
|
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# imports:
|
||||
|
||||
from tra_analysis import analysis as an
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import data as d
|
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from collections import defaultdict
|
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import json
|
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import math
|
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import numpy as np
|
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import os
|
||||
from os import system, name
|
||||
from pathlib import Path
|
||||
from multiprocessing import Pool
|
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import platform
|
||||
import sys
|
||||
import time
|
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import warnings
|
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|
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global exec_threads
|
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|
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def main():
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|
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global exec_threads
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|
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sys.stderr = open("errorlog.txt", "w")
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||||
|
||||
warnings.filterwarnings("ignore")
|
||||
|
||||
splash()
|
||||
|
||||
while (True):
|
||||
|
||||
try:
|
||||
|
||||
current_time = time.time()
|
||||
print("[OK] time: " + str(current_time))
|
||||
|
||||
config = load_config("config.json")
|
||||
competition = config["competition"]
|
||||
match_tests = config["statistics"]["match"]
|
||||
pit_tests = config["statistics"]["pit"]
|
||||
metrics_tests = config["statistics"]["metric"]
|
||||
print("[OK] configs loaded")
|
||||
|
||||
print("[OK] starting threads")
|
||||
cfg_max_threads = config["max-threads"]
|
||||
sys_max_threads = os.cpu_count()
|
||||
if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
|
||||
alloc_processes = sys_max_threads + cfg_max_threads
|
||||
elif cfg_max_threads > 0 and cfg_max_threads < 1:
|
||||
alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
|
||||
elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
|
||||
alloc_processes = cfg_max_threads
|
||||
elif cfg_max_threads == 0:
|
||||
alloc_processes = sys_max_threads
|
||||
else:
|
||||
print("[ERROR] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
|
||||
exit()
|
||||
exec_threads = Pool(processes = alloc_processes)
|
||||
print("[OK] " + str(alloc_processes) + " threads started")
|
||||
|
||||
apikey = config["key"]["database"]
|
||||
tbakey = config["key"]["tba"]
|
||||
print("[OK] loaded keys")
|
||||
|
||||
previous_time = get_previous_time(apikey)
|
||||
print("[OK] analysis backtimed to: " + str(previous_time))
|
||||
|
||||
print("[OK] loading data")
|
||||
start = time.time()
|
||||
match_data = load_match(apikey, competition)
|
||||
pit_data = load_pit(apikey, competition)
|
||||
print("[OK] loaded data in " + str(time.time() - start) + " seconds")
|
||||
|
||||
print("[OK] running match stats")
|
||||
start = time.time()
|
||||
matchloop(apikey, competition, match_data, match_tests)
|
||||
print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
|
||||
|
||||
print("[OK] running team metrics")
|
||||
start = time.time()
|
||||
metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
|
||||
print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
|
||||
|
||||
print("[OK] running pit analysis")
|
||||
start = time.time()
|
||||
pitloop(apikey, competition, pit_data, pit_tests)
|
||||
print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
|
||||
|
||||
set_current_time(apikey, current_time)
|
||||
print("[OK] finished all tests, looping")
|
||||
|
||||
print_hrule()
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n[OK] caught KeyboardInterrupt, killing processes")
|
||||
exec_threads.terminate()
|
||||
print("[OK] processes killed, exiting")
|
||||
exit()
|
||||
|
||||
else:
|
||||
pass
|
||||
|
||||
#clear()
|
||||
|
||||
def clear():
|
||||
|
||||
# for windows
|
||||
if name == 'nt':
|
||||
_ = system('cls')
|
||||
|
||||
# for mac and linux(here, os.name is 'posix')
|
||||
else:
|
||||
_ = system('clear')
|
||||
|
||||
def print_hrule():
|
||||
|
||||
print("#"+38*"-"+"#")
|
||||
|
||||
def print_box(s):
|
||||
|
||||
temp = "|"
|
||||
temp += s
|
||||
temp += (40-len(s)-2)*" "
|
||||
temp += "|"
|
||||
print(temp)
|
||||
|
||||
def splash():
|
||||
|
||||
print_hrule()
|
||||
print_box(" superscript version: " + __version__)
|
||||
print_box(" os: " + platform.system())
|
||||
print_box(" python: " + platform.python_version())
|
||||
print_hrule()
|
||||
|
||||
def load_config(file):
|
||||
|
||||
config_vector = {}
|
||||
|
||||
try:
|
||||
f = open(file)
|
||||
except:
|
||||
print("[ERROR] could not locate config.json, generating blank config.json and exiting")
|
||||
f = open(file, "w")
|
||||
f.write(sample_json)
|
||||
exit()
|
||||
|
||||
config_vector = json.load(f)
|
||||
|
||||
return config_vector
|
||||
|
||||
def save_config(file, config_vector):
|
||||
|
||||
with open(file) as f:
|
||||
json.dump(config_vector, f)
|
||||
|
||||
def get_previous_time(apikey):
|
||||
|
||||
previous_time = d.get_analysis_flags(apikey, "latest_update")
|
||||
|
||||
if previous_time == None:
|
||||
|
||||
d.set_analysis_flags(apikey, "latest_update", 0)
|
||||
previous_time = 0
|
||||
|
||||
else:
|
||||
|
||||
previous_time = previous_time["latest_update"]
|
||||
|
||||
return previous_time
|
||||
|
||||
def set_current_time(apikey, current_time):
|
||||
|
||||
d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
|
||||
|
||||
def load_match(apikey, competition):
|
||||
|
||||
return d.get_match_data_formatted(apikey, competition)
|
||||
|
||||
def simplestats(data_test):
|
||||
|
||||
data = np.array(data_test[0])
|
||||
data = data[np.isfinite(data)]
|
||||
ranges = list(range(len(data)))
|
||||
|
||||
test = data_test[1]
|
||||
|
||||
if test == "basic_stats":
|
||||
return an.basic_stats(data)
|
||||
|
||||
if test == "historical_analysis":
|
||||
return an.histo_analysis([ranges, data])
|
||||
|
||||
if test == "regression_linear":
|
||||
return an.regression(ranges, data, ['lin'])
|
||||
|
||||
if test == "regression_logarithmic":
|
||||
return an.regression(ranges, data, ['log'])
|
||||
|
||||
if test == "regression_exponential":
|
||||
return an.regression(ranges, data, ['exp'])
|
||||
|
||||
if test == "regression_polynomial":
|
||||
return an.regression(ranges, data, ['ply'])
|
||||
|
||||
if test == "regression_sigmoidal":
|
||||
return an.regression(ranges, data, ['sig'])
|
||||
|
||||
def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][Variable][Match]
|
||||
|
||||
global exec_threads
|
||||
|
||||
short_mapping = {"regression_linear": "lin", "regression_logarithmic": "log", "regression_exponential": "exp", "regression_polynomial": "ply", "regression_sigmoidal": "sig"}
|
||||
|
||||
class AutoVivification(dict):
|
||||
def __getitem__(self, item):
|
||||
try:
|
||||
return dict.__getitem__(self, item)
|
||||
except KeyError:
|
||||
value = self[item] = type(self)()
|
||||
return value
|
||||
|
||||
return_vector = {}
|
||||
|
||||
team_filtered = []
|
||||
variable_filtered = []
|
||||
variable_data = []
|
||||
test_filtered = []
|
||||
result_filtered = []
|
||||
return_vector = AutoVivification()
|
||||
|
||||
for team in data:
|
||||
|
||||
for variable in data[team]:
|
||||
|
||||
if variable in tests:
|
||||
|
||||
for test in tests[variable]:
|
||||
|
||||
team_filtered.append(team)
|
||||
variable_filtered.append(variable)
|
||||
variable_data.append((data[team][variable], test))
|
||||
test_filtered.append(test)
|
||||
|
||||
result_filtered = exec_threads.map(simplestats, variable_data)
|
||||
i = 0
|
||||
|
||||
result_filtered = list(result_filtered)
|
||||
|
||||
for result in result_filtered:
|
||||
|
||||
filtered = test_filtered[i]
|
||||
|
||||
try:
|
||||
short = short_mapping[filtered]
|
||||
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result[short]
|
||||
except KeyError: # not in mapping
|
||||
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result
|
||||
i += 1
|
||||
|
||||
push_match(apikey, competition, return_vector)
|
||||
|
||||
def load_metric(apikey, competition, match, group_name, metrics):
|
||||
|
||||
group = {}
|
||||
|
||||
for team in match[group_name]:
|
||||
|
||||
db_data = d.get_team_metrics_data(apikey, competition, team)
|
||||
|
||||
if d.get_team_metrics_data(apikey, competition, team) == None:
|
||||
|
||||
elo = {"score": metrics["elo"]["score"]}
|
||||
gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
|
||||
ts = {"mu": metrics["ts"]["mu"], "sigma": metrics["ts"]["sigma"]}
|
||||
|
||||
group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
|
||||
|
||||
else:
|
||||
|
||||
metrics = db_data["metrics"]
|
||||
|
||||
elo = metrics["elo"]
|
||||
gl2 = metrics["gl2"]
|
||||
ts = metrics["ts"]
|
||||
|
||||
group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
|
||||
|
||||
return group
|
||||
|
||||
def metricloop(tbakey, apikey, competition, timestamp, metrics): # listener based metrics update
|
||||
|
||||
elo_N = metrics["elo"]["N"]
|
||||
elo_K = metrics["elo"]["K"]
|
||||
|
||||
matches = d.pull_new_tba_matches(tbakey, competition, timestamp)
|
||||
|
||||
red = {}
|
||||
blu = {}
|
||||
|
||||
for match in matches:
|
||||
|
||||
red = load_metric(apikey, competition, match, "red", metrics)
|
||||
blu = load_metric(apikey, competition, match, "blue", metrics)
|
||||
|
||||
elo_red_total = 0
|
||||
elo_blu_total = 0
|
||||
|
||||
gl2_red_score_total = 0
|
||||
gl2_blu_score_total = 0
|
||||
|
||||
gl2_red_rd_total = 0
|
||||
gl2_blu_rd_total = 0
|
||||
|
||||
gl2_red_vol_total = 0
|
||||
gl2_blu_vol_total = 0
|
||||
|
||||
for team in red:
|
||||
|
||||
elo_red_total += red[team]["elo"]["score"]
|
||||
|
||||
gl2_red_score_total += red[team]["gl2"]["score"]
|
||||
gl2_red_rd_total += red[team]["gl2"]["rd"]
|
||||
gl2_red_vol_total += red[team]["gl2"]["vol"]
|
||||
|
||||
for team in blu:
|
||||
|
||||
elo_blu_total += blu[team]["elo"]["score"]
|
||||
|
||||
gl2_blu_score_total += blu[team]["gl2"]["score"]
|
||||
gl2_blu_rd_total += blu[team]["gl2"]["rd"]
|
||||
gl2_blu_vol_total += blu[team]["gl2"]["vol"]
|
||||
|
||||
red_elo = {"score": elo_red_total / len(red)}
|
||||
blu_elo = {"score": elo_blu_total / len(blu)}
|
||||
|
||||
red_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)}
|
||||
blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)}
|
||||
|
||||
|
||||
if match["winner"] == "red":
|
||||
|
||||
observations = {"red": 1, "blu": 0}
|
||||
|
||||
elif match["winner"] == "blue":
|
||||
|
||||
observations = {"red": 0, "blu": 1}
|
||||
|
||||
else:
|
||||
|
||||
observations = {"red": 0.5, "blu": 0.5}
|
||||
|
||||
red_elo_delta = an.Metric().elo(red_elo["score"], blu_elo["score"], observations["red"], elo_N, elo_K) - red_elo["score"]
|
||||
blu_elo_delta = an.Metric().elo(blu_elo["score"], red_elo["score"], observations["blu"], elo_N, elo_K) - blu_elo["score"]
|
||||
|
||||
new_red_gl2_score, new_red_gl2_rd, new_red_gl2_vol = an.Metric().glicko2(red_gl2["score"], red_gl2["rd"], red_gl2["vol"], [blu_gl2["score"]], [blu_gl2["rd"]], [observations["red"], observations["blu"]])
|
||||
new_blu_gl2_score, new_blu_gl2_rd, new_blu_gl2_vol = an.Metric().glicko2(blu_gl2["score"], blu_gl2["rd"], blu_gl2["vol"], [red_gl2["score"]], [red_gl2["rd"]], [observations["blu"], observations["red"]])
|
||||
|
||||
red_gl2_delta = {"score": new_red_gl2_score - red_gl2["score"], "rd": new_red_gl2_rd - red_gl2["rd"], "vol": new_red_gl2_vol - red_gl2["vol"]}
|
||||
blu_gl2_delta = {"score": new_blu_gl2_score - blu_gl2["score"], "rd": new_blu_gl2_rd - blu_gl2["rd"], "vol": new_blu_gl2_vol - blu_gl2["vol"]}
|
||||
|
||||
for team in red:
|
||||
|
||||
red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
|
||||
|
||||
red[team]["gl2"]["score"] = red[team]["gl2"]["score"] + red_gl2_delta["score"]
|
||||
red[team]["gl2"]["rd"] = red[team]["gl2"]["rd"] + red_gl2_delta["rd"]
|
||||
red[team]["gl2"]["vol"] = red[team]["gl2"]["vol"] + red_gl2_delta["vol"]
|
||||
|
||||
for team in blu:
|
||||
|
||||
blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
|
||||
|
||||
blu[team]["gl2"]["score"] = blu[team]["gl2"]["score"] + blu_gl2_delta["score"]
|
||||
blu[team]["gl2"]["rd"] = blu[team]["gl2"]["rd"] + blu_gl2_delta["rd"]
|
||||
blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
|
||||
|
||||
temp_vector = {}
|
||||
temp_vector.update(red)
|
||||
temp_vector.update(blu)
|
||||
|
||||
push_metric(apikey, competition, temp_vector)
|
||||
|
||||
def load_pit(apikey, competition):
|
||||
|
||||
return d.get_pit_data_formatted(apikey, competition)
|
||||
|
||||
def pitloop(apikey, competition, pit, tests):
|
||||
|
||||
return_vector = {}
|
||||
for team in pit:
|
||||
for variable in pit[team]:
|
||||
if variable in tests:
|
||||
if not variable in return_vector:
|
||||
return_vector[variable] = []
|
||||
return_vector[variable].append(pit[team][variable])
|
||||
|
||||
push_pit(apikey, competition, return_vector)
|
||||
|
||||
def push_match(apikey, competition, results):
|
||||
|
||||
for team in results:
|
||||
|
||||
d.push_team_tests_data(apikey, competition, team, results[team])
|
||||
|
||||
def push_metric(apikey, competition, metric):
|
||||
|
||||
for team in metric:
|
||||
|
||||
d.push_team_metrics_data(apikey, competition, team, metric[team])
|
||||
|
||||
def push_pit(apikey, competition, pit):
|
||||
|
||||
for variable in pit:
|
||||
|
||||
d.push_team_pit_data(apikey, competition, variable, pit[variable])
|
||||
|
||||
def get_team_metrics(apikey, tbakey, competition):
|
||||
|
||||
metrics = d.get_metrics_data_formatted(apikey, competition)
|
||||
|
||||
elo = {}
|
||||
gl2 = {}
|
||||
|
||||
for team in metrics:
|
||||
|
||||
elo[team] = metrics[team]["metrics"]["elo"]["score"]
|
||||
gl2[team] = metrics[team]["metrics"]["gl2"]["score"]
|
||||
|
||||
elo = {k: v for k, v in sorted(elo.items(), key=lambda item: item[1])}
|
||||
gl2 = {k: v for k, v in sorted(gl2.items(), key=lambda item: item[1])}
|
||||
|
||||
elo_ranked = []
|
||||
|
||||
for team in elo:
|
||||
|
||||
elo_ranked.append({"team": str(team), "elo": str(elo[team])})
|
||||
|
||||
gl2_ranked = []
|
||||
|
||||
for team in gl2:
|
||||
|
||||
gl2_ranked.append({"team": str(team), "gl2": str(gl2[team])})
|
||||
|
||||
return {"elo-ranks": elo_ranked, "glicko2-ranks": gl2_ranked}
|
||||
|
||||
sample_json = """{
|
||||
"max-threads": 0.5,
|
||||
"team": "",
|
||||
"competition": "2020ilch",
|
||||
"key":{
|
||||
"database":"",
|
||||
"tba":""
|
||||
},
|
||||
"statistics":{
|
||||
"match":{
|
||||
"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
|
||||
"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
|
||||
|
||||
},
|
||||
"metric":{
|
||||
"elo":{
|
||||
"score":1500,
|
||||
"N":400,
|
||||
"K":24
|
||||
},
|
||||
"gl2":{
|
||||
"score":1500,
|
||||
"rd":250,
|
||||
"vol":0.06
|
||||
},
|
||||
"ts":{
|
||||
"mu":25,
|
||||
"sigma":8.33
|
||||
}
|
||||
},
|
||||
"pit":{
|
||||
"wheel-mechanism":true,
|
||||
"low-balls":true,
|
||||
"high-balls":true,
|
||||
"wheel-success":true,
|
||||
"strategic-focus":true,
|
||||
"climb-mechanism":true,
|
||||
"attitude":true
|
||||
}
|
||||
}
|
||||
}"""
|
||||
|
||||
if __name__ == "__main__":
|
||||
if sys.platform.startswith('win'):
|
||||
multiprocessing.freeze_support()
|
||||
main()
|
||||
@ -299,7 +299,6 @@ class Pit (Module):
|
||||
|
||||
def _process_data(self, exec_threads):
|
||||
tests = self.config["tests"]
|
||||
print(tests)
|
||||
return_vector = {}
|
||||
for team in self.data:
|
||||
for variable in self.data[team]:
|
||||
Loading…
Reference in New Issue
Block a user