Merge branch 'competition'

This commit is contained in:
Dev Singh 2023-03-17 10:11:56 -05:00
commit df37947b21
20 changed files with 1545 additions and 409 deletions

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@ -4,4 +4,4 @@ RUN apt-get -y update
RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends tzdata
RUN apt-get install -y python3 python3-dev git python3-pip python3-kivy python-is-python3 libgl1-mesa-dev build-essential
RUN ln -s $(which pip3) /usr/bin/pip
RUN pip install pymongo pandas numpy scipy scikit-learn matplotlib pylint kivy
RUN pip install pymongo pandas numpy scipy scikit-learn matplotlib pylint kivy

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@ -8,16 +8,10 @@
"python.pythonPath": "/usr/local/bin/python",
"python.linting.enabled": true,
"python.linting.pylintEnabled": true,
"python.formatting.autopep8Path": "/usr/local/py-utils/bin/autopep8",
"python.formatting.blackPath": "/usr/local/py-utils/bin/black",
"python.formatting.yapfPath": "/usr/local/py-utils/bin/yapf",
"python.linting.banditPath": "/usr/local/py-utils/bin/bandit",
"python.linting.flake8Path": "/usr/local/py-utils/bin/flake8",
"python.linting.mypyPath": "/usr/local/py-utils/bin/mypy",
"python.linting.pycodestylePath": "/usr/local/py-utils/bin/pycodestyle",
"python.linting.pydocstylePath": "/usr/local/py-utils/bin/pydocstyle",
"python.linting.pylintPath": "/usr/local/py-utils/bin/pylint",
"python.testing.pytestPath": "/usr/local/py-utils/bin/pytest"
"python.linting.pylintPath": "/usr/local/bin/pylint",
"python.testing.pytestPath": "/usr/local/bin/pytest",
"editor.tabSize": 4,
"editor.insertSpaces": false
},
"extensions": [
"mhutchie.git-graph",
@ -25,4 +19,4 @@
"waderyan.gitblame"
],
"postCreateCommand": "/usr/bin/pip3 install -r ${containerWorkspaceFolder}/src/requirements.txt && /usr/bin/pip3 install --no-cache-dir pylint && /usr/bin/pip3 install pytest"
}
}

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@ -0,0 +1,16 @@
cerberus
dnspython
numpy
pandas
pyinstaller
pylint
pymongo
pyparsing
pytest
python-daemon
pyzmq
requests
scikit-learn
scipy
six
tra-analysis

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@ -1,38 +0,0 @@
---
name: Bug report
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
Steps to reproduce the behavior:
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
**Expected behavior**
A clear and concise description of what you expected to happen.
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Desktop (please complete the following information):**
- OS: [e.g. iOS]
- Browser [e.g. chrome, safari]
- Version [e.g. 22]
**Smartphone (please complete the following information):**
- Device: [e.g. iPhone6]
- OS: [e.g. iOS8.1]
- Browser [e.g. stock browser, safari]
- Version [e.g. 22]
**Additional context**
Add any other context about the problem here.

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@ -1,20 +0,0 @@
---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: ''
assignees: ''
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context or screenshots about the feature request here.

12
.gitignore vendored
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@ -11,4 +11,14 @@
**/errorlog.txt
/dist/superscript.*
/dist/superscript
/dist/superscript
**/*.pid
**/profile.*
**/*.log
**/errorlog.txt
/dist/*
slurm-tra-superscript.out
config*.json

251
competition/config.py Normal file
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@ -0,0 +1,251 @@
import json
from exceptions import ConfigurationError
from cerberus import Validator
from data import set_database_config, get_database_config
class Configuration:
path = None
config = {}
_sample_config = {
"persistent":{
"key":{
"database":"",
"tba":"",
"tra":{
"CLIENT_ID":"",
"CLIENT_SECRET":"",
"url": ""
}
},
"config-preference":"local",
"synchronize-config":False
},
"variable":{
"event-delay":False,
"loop-delay":0,
"competition": "2020ilch",
"modules":{
"match":{
"tests":{
"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":{
"tests":{
"elo":{
"score":1500,
"N":400,
"K":24
},
"gl2":{
"score":1500,
"rd":250,
"vol":0.06
},
"ts":{
"mu":25,
"sigma":8.33
}
}
},
"pit":{
"tests":{
"wheel-mechanism":True,
"low-balls":True,
"high-balls":True,
"wheel-success":True,
"strategic-focus":True,
"climb-mechanism":True,
"attitude":True
}
}
}
}
}
_validation_schema = {
"persistent": {
"type": "dict",
"required": True,
"require_all": True,
"schema": {
"key": {
"type": "dict",
"require_all":True,
"schema": {
"database": {"type":"string"},
"tba": {"type": "string"},
"tra": {
"type": "dict",
"require_all": True,
"schema": {
"CLIENT_ID": {"type": "string"},
"CLIENT_SECRET": {"type": "string"},
"url": {"type": "string"}
}
}
}
},
"config-preference": {"type": "string", "required": True},
"synchronize-config": {"type": "boolean", "required": True}
}
}
}
def __init__(self, path):
self.path = path
self.load_config()
self.validate_config()
def load_config(self):
try:
f = open(self.path, "r")
self.config.update(json.load(f))
f.close()
except:
self.config = self._sample_config
self.save_config()
f.close()
raise ConfigurationError("could not find config file at <" + self.path + ">, created new sample config file at that path")
def save_config(self):
f = open(self.path, "w+")
json.dump(self.config, f, ensure_ascii=False, indent=4)
f.close()
def validate_config(self):
v = Validator(self._validation_schema, allow_unknown = True)
isValidated = v.validate(self.config)
if not isValidated:
raise ConfigurationError("config validation error: " + v.errors)
def __getattr__(self, name): # simple linear lookup method for common multikey-value paths, TYPE UNSAFE
if name == "persistent":
return self.config["persistent"]
elif name == "key":
return self.config["persistent"]["key"]
elif name == "database":
# soon to be deprecated
return self.config["persistent"]["key"]["database"]
elif name == "tba":
return self.config["persistent"]["key"]["tba"]
elif name == "tra":
return self.config["persistent"]["key"]["tra"]
elif name == "priority":
return self.config["persistent"]["config-preference"]
elif name == "sync":
return self.config["persistent"]["synchronize-config"]
elif name == "variable":
return self.config["variable"]
elif name == "event_delay":
return self.config["variable"]["event-delay"]
elif name == "loop_delay":
return self.config["variable"]["loop-delay"]
elif name == "competition":
return self.config["variable"]["competition"]
elif name == "modules":
return self.config["variable"]["modules"]
else:
return None
def __getitem__(self, key):
return self.config[key]
def resolve_config_conflicts(self, logger, client): # needs improvement with new localization scheme
sync = self.sync
priority = self.priority
if sync:
if priority == "local" or priority == "client":
logger.info("config-preference set to local/client, loading local config information")
remote_config = get_database_config(client)
if remote_config != self.config["variable"]:
set_database_config(client, self.config["variable"])
logger.info("database config was different and was updated")
# no change to config
elif priority == "remote" or priority == "database":
logger.info("config-preference set to remote/database, loading remote config information")
remote_config = get_database_config(client)
if remote_config != self.config["variable"]:
self.config["variable"] = remote_config
self.save_config()
# change variable to match remote
logger.info("local config was different and was updated")
else:
raise ConfigurationError("persistent/config-preference field must be \"local\"/\"client\" or \"remote\"/\"database\"")
else:
if priority == "local" or priority == "client":
logger.info("config-preference set to local/client, loading local config information")
# no change to config
elif priority == "remote" or priority == "database":
logger.info("config-preference set to remote/database, loading database config information")
self.config["variable"] = get_database_config(client)
# change variable to match remote without updating local version
else:
raise ConfigurationError("persistent/config-preference field must be \"local\"/\"client\" or \"remote\"/\"database\"")

218
competition/data.py Normal file
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@ -0,0 +1,218 @@
from calendar import c
import requests
import pull
import pandas as pd
import json
def pull_new_tba_matches(apikey, competition, last_match):
api_key= apikey
x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth-Key":api_key})
json = x.json()
out = []
for i in json:
if i["actual_time"] != None and i["comp_level"] == "qm" and i["match_number"] > last_match :
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"]})
out.sort(key=lambda x: x['match'])
return out
def pull_new_tba_matches_manual(apikey, competition, cutoff):
filename = competition+"-wins.json"
with open(filename, 'r') as f:
data = json.load(f)
return data
def get_team_match_data(client, competition, team_num):
db = client.data_scouting
mdata = db.matchdata
out = {}
for i in mdata.find({"competition" : competition, "team_scouted": str(team_num)}):
out[i['match']] = i['data']
return pd.DataFrame(out)
def clear_metrics(client, competition):
db = client.data_processing
data = db.team_metrics
data.delete_many({competition: competition})
return True
def get_team_pit_data(client, competition, team_num):
db = client.data_scouting
mdata = db.pitdata
out = {}
return mdata.find_one({"competition" : competition, "team_scouted": str(team_num)})["data"]
def get_team_metrics_data(client, competition, team_num):
db = client.data_processing
mdata = db.team_metrics
temp = mdata.find_one({"team": team_num})
if temp != None:
if competition in temp['metrics'].keys():
temp = temp['metrics'][competition]
else :
temp = None
else:
temp = None
return temp
def get_match_data_formatted(client, competition):
teams_at_comp = pull.get_teams_at_competition(competition)
out = {}
for team in teams_at_comp:
try:
out[int(team)] = unkeyify_2l(get_team_match_data(client, competition, team).transpose().to_dict())
except:
pass
return out
def get_metrics_data_formatted(client, competition):
teams_at_comp = pull.get_teams_at_competition(competition)
out = {}
for team in teams_at_comp:
try:
out[int(team)] = get_team_metrics_data(client, competition, int(team))
except:
pass
return out
def get_pit_data_formatted(client, competition):
x=requests.get("https://scouting.titanrobotics2022.com/api/fetchAllTeamNicknamesAtCompetition?competition="+competition)
x = x.json()
x = x['data']
x = x.keys()
out = {}
for i in x:
try:
out[int(i)] = get_team_pit_data(client, competition, int(i))
except:
pass
return out
def get_pit_variable_data(client, competition):
db = client.data_processing
mdata = db.team_pit
out = {}
return mdata.find()
def get_pit_variable_formatted(client, competition):
temp = get_pit_variable_data(client, competition)
out = {}
for i in temp:
out[i["variable"]] = i["data"]
return out
def push_team_tests_data(client, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "data" : data}, True)
def push_team_metrics_data(client, competition, team_num, data, dbname = "data_processing", colname = "team_metrics"):
db = client[dbname]
mdata = db[colname]
mdata.update_one({"team": team_num}, {"$set": {"metrics.{}".format(competition): data}}, upsert=True)
def push_team_pit_data(client, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "variable": variable}, {"competition" : competition, "variable" : variable, "data" : data}, True)
def get_analysis_flags(client, flag):
db = client.data_processing
mdata = db.flags
return mdata.find_one({"_id": "2022"})
def set_analysis_flags(client, flag, data):
db = client.data_processing
mdata = db.flags
return mdata.update_one({"_id": "2022"}, {"$set": data})
def unkeyify_2l(layered_dict):
out = {}
for i in layered_dict.keys():
add = []
sortkey = []
for j in layered_dict[i].keys():
add.append([j,layered_dict[i][j]])
add.sort(key = lambda x: x[0])
out[i] = list(map(lambda x: x[1], add))
return out
def get_previous_time(client):
previous_time = get_analysis_flags(client, "latest_update")
if previous_time == None:
set_analysis_flags(client, "latest_update", 0)
previous_time = 0
else:
previous_time = previous_time["latest_update"]
return previous_time
def set_current_time(client, current_time):
set_analysis_flags(client, "latest_update", {"latest_update":current_time})
def get_database_config(client):
remote_config = get_analysis_flags(client, "config")
return remote_config["config"] if remote_config != None else None
def set_database_config(client, config):
set_analysis_flags(client, "config", {"config": config})
def load_match(client, competition):
return get_match_data_formatted(client, competition)
def load_metric(client, competition, match, group_name, metrics):
group = {}
for team in match[group_name]:
db_data = get_team_metrics_data(client, competition, team)
if db_data == None:
gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
group[team] = {"gl2": gl2}
else:
metrics = db_data
gl2 = metrics["gl2"]
group[team] = {"gl2": gl2}
return group
def load_pit(client, competition):
return get_pit_data_formatted(client, competition)
def push_match(client, competition, results):
for team in results:
push_team_tests_data(client, competition, team, results[team])
def push_metric(client, competition, metric):
for team in metric:
push_team_metrics_data(client, competition, team, metric[team])
def push_pit(client, competition, pit):
for variable in pit:
push_team_pit_data(client, competition, variable, pit[variable])
def check_new_database_matches(client, competition):
return True

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competition/dep.py Normal file
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# contains deprecated functions, not to be used unless nessasary!
import json
sample_json = """
{
"persistent":{
"key":{
"database":"",
"tba":"",
"tra":{
"CLIENT_ID":"",
"CLIENT_SECRET":"",
"url": ""
}
},
"config-preference":"local",
"synchronize-config":false
},
"variable":{
"max-threads":0.5,
"team":"",
"event-delay":false,
"loop-delay":0,
"reportable":true,
"teams":[
],
"modules":{
"match":{
"tests":{
"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":{
"tests":{
"gl2":{
"score":1500,
"rd":250,
"vol":0.06
},
}
},
"pit":{
"tests":{
"wheel-mechanism":true,
"low-balls":true,
"high-balls":true,
"wheel-success":true,
"strategic-focus":true,
"climb-mechanism":true,
"attitude":true
}
}
}
}
}
"""
def load_config(path, config_vector):
try:
f = open(path, "r")
config_vector.update(json.load(f))
f.close()
return 0
except:
f = open(path, "w")
f.write(sample_json)
f.close()
return 1

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class APIError(Exception):
def __init__(self, str):
super().__init__(str)
class ConfigurationError (Exception):
def __init__(self, str):
super().__init__(str)

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competition/interface.py Normal file
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from logging import Logger as L
import datetime
import platform
import json
class Logger(L):
file = None
levels = {
0: "",
10:"[DEBUG] ",
20:"[INFO] ",
30:"[WARNING] ",
40:"[ERROR] ",
50:"[CRITICAL]",
}
targets = []
def __init__(self, verbose, profile, debug, file = None):
super().__init__("tra_logger")
self.file = file
if file != None:
self.targets.append(self._send_file)
if profile:
self.targets.append(self._send_null)
elif verbose:
self.targets.append(self._send_scli)
elif debug:
self.targets.append(self._send_scli)
else:
self.targets.append(self._send_null)
def _send_null(self, msg):
pass
def _send_scli(self, msg):
print(msg)
def _send_file(self, msg):
f = open(self.file, 'a')
f.write(msg + "\n")
f.close()
def get_time_formatted(self):
return datetime.datetime.now().strftime("%Y/%m/%d %H:%M:%S %Z")
def log(self, level, msg):
for t in self.targets:
t(self.get_time_formatted() + "| " + self.levels[level] + ": " + msg)
def debug(self, msg):
self.log(10, msg)
def info(self, msg):
self.log(20, msg)
def warning(self, msg):
self.log(30, msg)
def error(self, msg):
self.log(40, msg)
def critical(self, msg):
self.log(50, msg)
def splash(self, version):
def hrule():
self.log(0, "#"+38*"-"+"#")
def box(s):
temp = "|"
temp += s
temp += (40-len(s)-2)*" "
temp += "|"
self.log(0, temp)
hrule()
box(" superscript version: " + version)
box(" os: " + platform.system())
box(" python: " + platform.python_version())
hrule()
def save_module_to_file(self, module, data, results):
f = open(module + ".log", "w")
json.dump({"data": data, "results":results}, f, ensure_ascii=False, indent=4)
f.close()

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competition/module.py Normal file
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import abc
import data as d
import signal
import numpy as np
from tra_analysis import Analysis as an
from tqdm import tqdm
class Module(metaclass = abc.ABCMeta):
@classmethod
def __subclasshook__(cls, subclass):
return (hasattr(subclass, '__init__') and
callable(subclass.__init__) and
hasattr(subclass, 'validate_config') and
callable(subclass.validate_config) and
hasattr(subclass, 'run') and
callable(subclass.run)
)
@abc.abstractmethod
def __init__(self, config, apikey, tbakey, timestamp, competition, *args, **kwargs):
raise NotImplementedError
@abc.abstractmethod
def validate_config(self, *args, **kwargs):
raise NotImplementedError
@abc.abstractmethod
def run(self, *args, **kwargs):
raise NotImplementedError
class Match (Module):
config = None
apikey = None
tbakey = None
timestamp = None
competition = None
data = None
results = None
def __init__(self, config, apikey, tbakey, timestamp, competition):
self.config = config
self.apikey = apikey
self.tbakey = tbakey
self.timestamp = timestamp
self.competition = competition
def validate_config(self):
return True, ""
def run(self):
self._load_data()
self._process_data()
self._push_results()
def _load_data(self):
self.data = d.load_match(self.apikey, self.competition)
def _simplestats(self, data_test):
signal.signal(signal.SIGINT, signal.SIG_IGN)
data = np.array(data_test[3])
data = data[np.isfinite(data)]
ranges = list(range(len(data)))
test = data_test[2]
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 _process_data(self):
tests = self.config["tests"]
data = self.data
input_vector = []
for team in data:
for variable in data[team]:
if variable in tests:
for test in tests[variable]:
input_vector.append((team, variable, test, data[team][variable]))
self.data = input_vector
self.results = []
for test_var_data in self.data:
self.results.append(self._simplestats(test_var_data))
def _push_results(self):
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
result_filtered = self.results
input_vector = self.data
return_vector = AutoVivification()
i = 0
for result in result_filtered:
filtered = input_vector[i][2]
try:
short = short_mapping[filtered]
return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result[short]
except KeyError: # not in mapping
return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result
i += 1
self.results = return_vector
d.push_match(self.apikey, self.competition, self.results)
class Metric (Module):
config = None
apikey = None
tbakey = None
timestamp = None
competition = None
data = None
results = None
def __init__(self, config, apikey, tbakey, timestamp, competition):
self.config = config
self.apikey = apikey
self.tbakey = tbakey
self.timestamp = timestamp
self.competition = competition
def validate_config(self):
return True, ""
def run(self):
self._load_data()
self._process_data()
self._push_results()
def _load_data(self):
self.last_match = d.get_analysis_flags(self.apikey, 'metrics_last_match')['metrics_last_match']
print("Previous last match", self.last_match)
self.data = d.pull_new_tba_matches(self.tbakey, self.competition, self.last_match)
def _process_data(self):
self.results = {}
self.match = self.last_match
matches = self.data
red = {}
blu = {}
for match in tqdm(matches, desc="Metrics"): # grab matches and loop through each one
self.match = max(self.match, int(match['match']))
red = d.load_metric(self.apikey, self.competition, match, "red", self.config["tests"]) # get the current ratings for red
blu = d.load_metric(self.apikey, self.competition, match, "blue", self.config["tests"]) # get the current ratings for blue
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: # for each team in red, add up gl2 score components
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: # for each team in blue, add up gl2 score components
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_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)} # average the scores by dividing by 3
blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)} # average the scores by dividing by 3
if match["winner"] == "red": # if red won, set observations to {"red": 1, "blu": 0}
observations = {"red": 1, "blu": 0}
elif match["winner"] == "blue": # if blue won, set observations to {"red": 0, "blu": 1}
observations = {"red": 0, "blu": 1}
else: # otherwise it was a tie and observations is {"red": 0.5, "blu": 0.5}
observations = {"red": 0.5, "blu": 0.5}
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"]]) # calculate new scores for gl2 for red
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"]]) # calculate new scores for gl2 for blue
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"]} # calculate gl2 deltas for red
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"]} # calculate gl2 deltas for blue
for team in red: # for each team on red, add the previous score with the delta to find the new score
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: # for each team on blue, add the previous score with the delta to find the new score
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) # update the team's score with the temporay vector
temp_vector.update(blu)
self.results[match['match']] = temp_vector
d.push_metric(self.apikey, self.competition, temp_vector) # push new scores to db
print("New last match", self.match)
d.set_analysis_flags(self.apikey, 'metrics_last_match', {'metrics_last_match': self.match})
def _push_results(self):
pass
class Pit (Module):
config = None
apikey = None
tbakey = None
timestamp = None
competition = None
data = None
results = None
def __init__(self, config, apikey, tbakey, timestamp, competition):
self.config = config
self.apikey = apikey
self.tbakey = tbakey
self.timestamp = timestamp
self.competition = competition
def validate_config(self):
return True, ""
def run(self):
self._load_data()
self._process_data()
self._push_results()
def _load_data(self):
self.data = d.load_pit(self.apikey, self.competition)
def _process_data(self):
tests = self.config["tests"]
return_vector = {}
for team in self.data:
for variable in self.data[team]:
if variable in tests:
if not variable in return_vector:
return_vector[variable] = []
return_vector[variable].append(self.data[team][variable])
self.results = return_vector
def _push_results(self):
d.push_pit(self.apikey, self.competition, self.results)
class Rating (Module):
pass
class Heatmap (Module):
pass
class Sentiment (Module):
pass

63
competition/pull.py Normal file
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import requests
from exceptions import APIError
from dep import load_config
url = "https://scouting.titanrobotics2022.com"
config_tra = {}
load_config("config.json", config_tra)
trakey = config_tra['persistent']['key']['tra']
def get_team_competition():
endpoint = '/api/fetchTeamCompetition'
params = {
"CLIENT_ID": trakey['CLIENT_ID'],
"CLIENT_SECRET": trakey['CLIENT_SECRET']
}
response = requests.request("GET", url + endpoint, params=params)
json = response.json()
if json['success']:
return json['competition']
else:
raise APIError(json)
def get_team():
endpoint = '/api/fetchTeamCompetition'
params = {
"CLIENT_ID": trakey['CLIENT_ID'],
"CLIENT_SECRET": trakey['CLIENT_SECRET']
}
response = requests.request("GET", url + endpoint, params=params)
json = response.json()
if json['success']:
return json['team']
else:
raise APIError(json)
def get_team_match_data(competition, team_num):
endpoint = '/api/fetchAllTeamMatchData'
params = {
"competition": competition,
"teamScouted": team_num,
"CLIENT_ID": trakey['CLIENT_ID'],
"CLIENT_SECRET": trakey['CLIENT_SECRET']
}
response = requests.request("GET", url + endpoint, params=params)
json = response.json()
if json['success']:
return json['data'][team_num]
else:
raise APIError(json)
def get_teams_at_competition(competition):
endpoint = '/api/fetchAllTeamNicknamesAtCompetition'
params = {
"competition": competition,
"CLIENT_ID": trakey['CLIENT_ID'],
"CLIENT_SECRET": trakey['CLIENT_SECRET']
}
response = requests.request("GET", url + endpoint, params=params)
json = response.json()
if json['success']:
return list(json['data'].keys())
else:
raise APIError(json)

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cerberus
dnspython
numpy
pandas
pyinstaller
pylint
pymongo
pyparsing
python-daemon
pyzmq
requests
scikit-learn
scipy
six
tra-analysis

402
competition/superscript.py Normal file
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# Titan Robotics Team 2022: Superscript Script
# Written by Arthur Lu, Jacob Levine, and Dev Singh
# Notes:
# setup:
__version__ = "1.0.0"
# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
1.0.0:
- superscript now runs in PEP 3143 compliant well behaved daemon on Linux systems
- linux superscript daemon has integrated websocket output to monitor progress/status remotely
- linux daemon now sends stderr to errorlog.log
- added verbose option to linux superscript to allow for interactive output
- moved pymongo import to superscript.py
- added profile option to linux superscript to profile runtime of script
- reduced memory usage slightly by consolidating the unwrapped input data
- added debug option, which performs one loop of analysis and dumps results to local files
- added event and time delay options to config
- event delay pauses loop until even listener recieves an update
- time delay pauses loop until the time specified has elapsed since the BEGINNING of previous loop
- added options to pull config information from database (reatins option to use local config file)
- config-preference option selects between prioritizing local config and prioritizing database config
- synchronize-config option selects whether to update the non prioritized config with the prioritized one
- divided config options between persistent ones (keys), and variable ones (everything else)
- generalized behavior of various core components by collecting loose functions in several dependencies into classes
- module.py contains classes, each one represents a single data analysis routine
- config.py contains the Configuration class, which stores the configuration information and abstracts the getter methods
0.9.3:
- improved data loading performance by removing redundant PyMongo client creation (120s to 14s)
- passed singular instance of PyMongo client as standin for apikey parameter in all data.py functions
0.9.2:
- removed unessasary imports from data
- minor changes to interface
0.9.1:
- fixed bugs in configuration item loading exception handling
0.9.0:
- moved printing and logging related functions to interface.py (changelog will stay in this file)
- changed function return files for load_config and save_config to standard C values (0 for success, 1 for error)
- added local variables for config location
- moved dataset getting and setting functions to dataset.py (changelog will stay in this file)
- moved matchloop, metricloop, pitloop and helper functions (simplestats) to processing.py
0.8.6:
- added proper main function
0.8.5:
- added more gradeful KeyboardInterrupt exiting
- redirected stderr to errorlog.txt
0.8.4:
- added better error message for missing config.json
- added automatic config.json creation
- added splash text with version and system info
0.8.3:
- updated matchloop with new regression format (requires tra_analysis 3.x)
0.8.2:
- readded while true to main function
- added more thread config options
0.8.1:
- optimized matchloop further by bypassing GIL
0.8.0:
- added multithreading to matchloop
- tweaked user log
0.7.0:
- finished implementing main function
0.6.2:
- integrated get_team_rankings.py as get_team_metrics() function
- integrated visualize_pit.py as graph_pit_histogram() function
0.6.1:
- bug fixes with analysis.Metric() calls
- modified metric functions to use config.json defined default values
0.6.0:
- removed main function
- changed load_config function
- added save_config function
- added load_match function
- renamed simpleloop to matchloop
- moved simplestats function inside matchloop
- renamed load_metrics to load_metric
- renamed metricsloop to metricloop
- split push to database functions amon push_match, push_metric, push_pit
- moved
0.5.2:
- made changes due to refactoring of analysis
0.5.1:
- text fixes
- removed matplotlib requirement
0.5.0:
- improved user interface
0.4.2:
- removed unessasary code
0.4.1:
- fixed bug where X range for regression was determined before sanitization
- better sanitized data
0.4.0:
- fixed spelling issue in __changelog__
- addressed nan bug in regression
- fixed errors on line 335 with metrics calling incorrect key "glicko2"
- fixed errors in metrics computing
0.3.0:
- added analysis to pit data
0.2.1:
- minor stability patches
- implemented db syncing for timestamps
- fixed bugs
0.2.0:
- finalized testing and small fixes
0.1.4:
- finished metrics implement, trueskill is bugged
0.1.3:
- working
0.1.2:
- started implement of metrics
0.1.1:
- cleaned up imports
0.1.0:
- tested working, can push to database
0.0.9:
- tested working
- prints out stats for the time being, will push to database later
0.0.8:
- added data import
- removed tba import
- finished main method
0.0.7:
- added load_config
- optimized simpleloop for readibility
- added __all__ entries
- added simplestats engine
- pending testing
0.0.6:
- fixes
0.0.5:
- imported pickle
- created custom database object
0.0.4:
- fixed simpleloop to actually return a vector
0.0.3:
- added metricsloop which is unfinished
0.0.2:
- added simpleloop which is untested until data is provided
0.0.1:
- created script
- added analysis, numba, numpy imports
"""
__author__ = (
"Arthur Lu <learthurgo@gmail.com>",
"Jacob Levine <jlevine@imsa.edu>",
)
# imports:
import os, sys, time
import pymongo # soon to be deprecated
import traceback
import warnings
from config import Configuration, ConfigurationError
from data import get_previous_time, set_current_time, check_new_database_matches, clear_metrics
from interface import Logger
from module import Match, Metric, Pit
import zmq
config_path = "config.json"
def main(logger, verbose, profile, debug, socket_send = None):
def close_all():
if "client" in locals():
client.close()
warnings.filterwarnings("ignore")
logger.splash(__version__)
modules = {"match": Match, "metric": Metric, "pit": Pit}
while True:
try:
loop_start = time.time()
logger.info("current time: " + str(loop_start))
socket_send("current time: " + str(loop_start))
config = Configuration(config_path)
logger.info("found and loaded config at <" + config_path + ">")
socket_send("found and loaded config at <" + config_path + ">")
apikey, tbakey = config.database, config.tba
logger.info("found and loaded database and tba keys")
socket_send("found and loaded database and tba keys")
client = pymongo.MongoClient(apikey)
logger.info("established connection to database")
socket_send("established connection to database")
previous_time = get_previous_time(client)
logger.info("analysis backtimed to: " + str(previous_time))
socket_send("analysis backtimed to: " + str(previous_time))
config.resolve_config_conflicts(logger, client)
config_modules, competition = config.modules, config.competition
for m in config_modules:
if m in modules:
start = time.time()
current_module = modules[m](config_modules[m], client, tbakey, previous_time, competition)
valid = current_module.validate_config()
if not valid:
continue
current_module.run()
logger.info(m + " module finished in " + str(time.time() - start) + " seconds")
socket_send(m + " module finished in " + str(time.time() - start) + " seconds")
if debug:
logger.save_module_to_file(m, current_module.data, current_module.results) # logging flag check done in logger
set_current_time(client, loop_start)
close_all()
logger.info("closed threads and database client")
logger.info("finished all tasks in " + str(time.time() - loop_start) + " seconds, looping")
socket_send("closed threads and database client")
socket_send("finished all tasks in " + str(time.time() - loop_start) + " seconds, looping")
if profile:
return 0
if debug:
return 0
event_delay = config["variable"]["event-delay"]
if event_delay:
logger.info("loop delayed until database returns new matches")
socket_send("loop delayed until database returns new matches")
new_match = False
while not new_match:
time.sleep(1)
new_match = check_new_database_matches(client, competition)
logger.info("database returned new matches")
socket_send("database returned new matches")
else:
loop_delay = float(config["variable"]["loop-delay"])
remaining_time = loop_delay - (time.time() - loop_start)
if remaining_time > 0:
logger.info("loop delayed by " + str(remaining_time) + " seconds")
socket_send("loop delayed by " + str(remaining_time) + " seconds")
time.sleep(remaining_time)
except KeyboardInterrupt:
close_all()
logger.info("detected KeyboardInterrupt, exiting")
socket_send("detected KeyboardInterrupt, exiting")
return 0
except ConfigurationError as e:
str_e = "".join(traceback.format_exception(e))
logger.error("encountered a configuration error: " + str(e))
logger.error(str_e)
socket_send("encountered a configuration error: " + str(e))
socket_send(str_e)
close_all()
return 1
except Exception as e:
str_e = "".join(traceback.format_exception(e))
logger.error("encountered an exception while running")
logger.error(str_e)
socket_send("encountered an exception while running")
socket_send(str_e)
close_all()
return 1
def start(pid_path, verbose, profile, debug):
if profile:
def send(msg):
pass
logger = Logger(verbose, profile, debug)
import cProfile, pstats, io
profile = cProfile.Profile()
profile.enable()
exit_code = main(logger, verbose, profile, debug, socket_send = send)
profile.disable()
f = open("profile.txt", 'w+')
ps = pstats.Stats(profile, stream = f).sort_stats('cumtime')
ps.print_stats()
sys.exit(exit_code)
elif verbose:
def send(msg):
pass
logger = Logger(verbose, profile, debug)
exit_code = main(logger, verbose, profile, debug, socket_send = send)
sys.exit(exit_code)
elif debug:
def send(msg):
pass
logger = Logger(verbose, profile, debug)
exit_code = main(logger, verbose, profile, debug, socket_send = send)
sys.exit(exit_code)
else:
logfile = "logfile.log"
f = open(logfile, 'w+')
f.close()
e = open('errorlog.log', 'w+')
with daemon.DaemonContext(
working_directory = os.getcwd(),
pidfile = pidfile.TimeoutPIDLockFile(pid_path),
stderr = e
):
context = zmq.Context()
socket = context.socket(zmq.PUB)
socket.bind("tcp://*:5678")
socket.send(b'status')
def send(msg):
socket.send(bytes("status: " + msg, "utf-8"))
logger = Logger(verbose, profile, debug, file = logfile)
exit_code = main(logger, verbose, profile, debug, socket_send = send)
socket.close()
f.close()
sys.exit(exit_code)
def stop(pid_path):
try:
pf = open(pid_path, 'r')
pid = int(pf.read().strip())
pf.close()
except IOError:
sys.stderr.write("pidfile at <" + pid_path + "> does not exist. Daemon not running?\n")
return
try:
while True:
os.kill(pid, SIGTERM)
time.sleep(0.01)
except OSError as err:
err = str(err)
if err.find("No such process") > 0:
if os.path.exists(pid_path):
os.remove(pid_path)
else:
traceback.print_exc(file = sys.stderr)
sys.exit(1)
def restart(pid_path):
stop(pid_path)
start(pid_path, False, False, False)
if __name__ == "__main__":
if sys.platform.startswith("win"):
start(None, verbose = True)
else:
import daemon
from daemon import pidfile
from signal import SIGTERM
pid_path = "tra-daemon.pid"
if len(sys.argv) == 2:
if 'start' == sys.argv[1]:
start(pid_path, False, False, False)
elif 'stop' == sys.argv[1]:
stop(pid_path)
elif 'restart' == sys.argv[1]:
restart(pid_path)
elif 'verbose' == sys.argv[1]:
start(None, True, False, False)
elif 'profile' == sys.argv[1]:
start(None, False, True, False)
elif 'debug' == sys.argv[1]:
start(None, False, False, True)
else:
print("usage: %s start|stop|restart|verbose|profile|debug" % sys.argv[0])
sys.exit(2)
sys.exit(0)
else:
print("usage: %s start|stop|restart|verbose|profile|debug" % sys.argv[0])
sys.exit(2)

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@ -1,129 +0,0 @@
import requests
import pymongo
import pandas as pd
import time
def pull_new_tba_matches(apikey, competition, cutoff):
api_key= apikey
x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth_Key":api_key})
out = []
for i in x.json():
if i["actual_time"] != None and i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm":
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"]})
return out
def get_team_match_data(apikey, competition, team_num):
client = pymongo.MongoClient(apikey)
db = client.data_scouting
mdata = db.matchdata
out = {}
for i in mdata.find({"competition" : competition, "team_scouted": team_num}):
out[i['match']] = i['data']
return pd.DataFrame(out)
def get_team_pit_data(apikey, competition, team_num):
client = pymongo.MongoClient(apikey)
db = client.data_scouting
mdata = db.pitdata
out = {}
return mdata.find_one({"competition" : competition, "team_scouted": team_num})["data"]
def get_team_metrics_data(apikey, competition, team_num):
client = pymongo.MongoClient(apikey)
db = client.data_processing
mdata = db.team_metrics
return mdata.find_one({"competition" : competition, "team": team_num})
def get_match_data_formatted(apikey, competition):
client = pymongo.MongoClient(apikey)
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = unkeyify_2l(get_team_match_data(apikey, competition, int(i)).transpose().to_dict())
except:
pass
return out
def get_metrics_data_formatted(apikey, competition):
client = pymongo.MongoClient(apikey)
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = d.get_team_metrics_data(apikey, competition, int(i))
except:
pass
return out
def get_pit_data_formatted(apikey, competition):
client = pymongo.MongoClient(apikey)
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = get_team_pit_data(apikey, competition, int(i))
except:
pass
return out
def get_pit_variable_data(apikey, competition):
client = pymongo.MongoClient(apikey)
db = client.data_processing
mdata = db.team_pit
out = {}
return mdata.find()
def get_pit_variable_formatted(apikey, competition):
temp = get_pit_variable_data(apikey, competition)
out = {}
for i in temp:
out[i["variable"]] = i["data"]
return out
def push_team_tests_data(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
client = pymongo.MongoClient(apikey)
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "data" : data}, True)
def push_team_metrics_data(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_metrics"):
client = pymongo.MongoClient(apikey)
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "metrics" : data}, True)
def push_team_pit_data(apikey, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
client = pymongo.MongoClient(apikey)
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "variable": variable}, {"competition" : competition, "variable" : variable, "data" : data}, True)
def get_analysis_flags(apikey, flag):
client = pymongo.MongoClient(apikey)
db = client.data_processing
mdata = db.flags
return mdata.find_one({flag:{"$exists":True}})
def set_analysis_flags(apikey, flag, data):
client = pymongo.MongoClient(apikey)
db = client.data_processing
mdata = db.flags
return mdata.replace_one({flag:{"$exists":True}}, data, True)
def unkeyify_2l(layered_dict):
out = {}
for i in layered_dict.keys():
add = []
sortkey = []
for j in layered_dict[i].keys():
add.append([j,layered_dict[i][j]])
add.sort(key = lambda x: x[0])
out[i] = list(map(lambda x: x[1], add))
return out

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@ -1,151 +0,0 @@
<Launch>:
orientation: "vertical"
NavigationLayout:
ScreenManager:
id: screen_manager
HomeScreen:
name: "Home"
BoxLayout:
orientation: "vertical"
MDToolbar:
title: screen_manager.current
elevation: 10
left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
GridLayout:
cols: 1
padding: 15, 15
spacing: 20, 20
MDTextFieldRect:
hint_text: "Console Log"
# size_hint: .8, None
# align: 'center'
# Widget:
SettingsScreen:
name: "Settings"
BoxLayout:
orientation: 'vertical'
MDToolbar:
title: screen_manager.current
elevation: 10
left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
Widget:
InfoScreen:
name: "Info"
BoxLayout:
orientation: 'vertical'
MDToolbar:
title: screen_manager.current
elevation: 10
left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
# GridLayout:
# cols: 2
# padding: 15, 15
# spacing: 20, 20
BoxLayout:
orientation: "horizontal"
MDLabel:
text: "DB Key:"
halign: 'center'
MDTextField:
hint_text: "placeholder"
pos_hint: {"center_y": .5}
BoxLayout:
orientation: "horizontal"
MDLabel:
text: "TBA Key:"
halign: 'center'
MDTextField:
hint_text: "placeholder"
pos_hint: {"center_y": .5}
BoxLayout:
orientation: "horizontal"
MDLabel:
text: "CPU Use:"
halign: 'center'
MDLabel:
text: "placeholder"
halign: 'center'
BoxLayout:
orientation: "horizontal"
MDLabel:
text: "Network:"
halign: 'center'
MDLabel:
text: "placeholder"
halign: 'center'
Widget:
BoxLayout:
orientation: "horizontal"
MDLabel:
text: "Progress"
halign: 'center'
MDProgressBar:
id: progress
value: 50
StatsScreen:
name: "Stats"
MDCheckbox:
size_hint: None, None
size: "48dp", "48dp"
pos_hint: {'center_x': .5, 'center_y': .5}
on_active: Screen.test()
#Navigation Drawer -------------------------
MDNavigationDrawer:
id: nav_drawer
BoxLayout:
orientation: "vertical"
padding: "8dp"
spacing: "8dp"
MDLabel:
text: "Titan Scouting"
font_style: "Button"
size_hint_y: None
height: self.texture_size[1]
MDLabel:
text: "Data Analysis"
font_style: "Caption"
size_hint_y: None
height: self.texture_size[1]
ScrollView:
MDList:
OneLineAvatarListItem:
text: "Home"
on_press:
# nav_drawer.set_state("close")
# screen_manager.transition.direction = "left"
screen_manager.current = "Home"
IconLeftWidget:
icon: "home"
OneLineAvatarListItem:
text: "Settings"
on_press:
# nav_drawer.set_state("close")
# screen_manager.transition.direction = "right"
# screen_manager.fade
screen_manager.current = "Settings"
IconLeftWidget:
icon: "cog"
OneLineAvatarListItem:
text: "Info"
on_press:
# nav_drawer.set_state("close")
# screen_manager.transition.direction = "right"
# screen_manager.fade
screen_manager.current = "Info"
IconLeftWidget:
icon: "cog"
OneLineAvatarListItem:
text: "Stats"
on_press:
# nav_drawer.set_state("close")
# screen_manager.transition.direction = "right"
# screen_manager.fade
screen_manager.current = "Stats"
IconLeftWidget:
icon: "cog"

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@ -1,58 +0,0 @@
from kivy.lang import Builder
from kivymd.uix.screen import Screen
from kivymd.uix.list import OneLineListItem, MDList, TwoLineListItem, ThreeLineListItem
from kivymd.uix.list import OneLineIconListItem, IconLeftWidget
from kivy.uix.scrollview import ScrollView
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.screenmanager import ScreenManager, Screen
from kivy.uix.dropdown import DropDown
from kivy.uix.button import Button
from kivy.base import runTouchApp
from kivymd.uix.menu import MDDropdownMenu, MDMenuItem
from kivymd.app import MDApp
# import superscript as ss
# from tra_analysis import analysis as an
import data as d
from collections import defaultdict
import json
import math
import numpy as np
import os
from os import system, name
from pathlib import Path
from multiprocessing import Pool
import matplotlib.pyplot as plt
from concurrent.futures import ThreadPoolExecutor
import time
import warnings
# global exec_threads
# Screens
class HomeScreen(Screen):
pass
class SettingsScreen(Screen):
pass
class InfoScreen(Screen):
pass
class StatsScreen(Screen):
pass
class MyApp(MDApp):
def build(self):
self.theme_cls.primary_palette = "Red"
return Builder.load_file("design.kv")
def test():
print("test")
if __name__ == "__main__":
MyApp().run()

12
submit-debug.sh Normal file
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#!/bin/bash
#
#SBATCH --job-name=tra-superscript
#SBATCH --output=slurm-tra-superscript.out
#SBATCH --ntasks=8
#SBATCH --time=24:00:00
#SBATCH --mem-per-cpu=256
#SBATCH --mail-user=dsingh@imsa.edu
#SBATCH -p cpu-long
cd competition
python superscript.py debug

12
submit-prod.sh Normal file
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#!/bin/bash
#
#SBATCH --job-name=tra-superscript
#SBATCH --output=PROD_slurm-tra-superscript.out
#SBATCH --ntasks=8
#SBATCH --time=24:00:00
#SBATCH --mem-per-cpu=256
#SBATCH --mail-user=dsingh@imsa.edu
#SBATCH -p cpu-long
cd competition
python superscript.py verbose