separated gui and cli dev files

began refactoring superscript in cli application

build/build-CLI.bat

@@ -1,4 +1,4 @@
-set pathtospec="../src/superscript.spec"
+set pathtospec="../src/cli/superscript.spec"
 set pathtodist="../dist/"
 set pathtowork="temp/"
 

build/build-CLI.sh

@@ -1,4 +1,4 @@
-pathtospec="../src/superscript.spec"
+pathtospec="../src/cli/superscript.spec"
 pathtodist="../dist/"
 pathtowork="temp/"
 

src/cli/cli_interface.py

@@ -0,0 +1,44 @@
+import sys
+import time
+from os import system, name
+import platform
+
+empty_delim = " "
+hard_divided_delim = "|"
+soft_divided_delim = ":"
+l_brack = "["
+r_brack = "]"
+
+ERR = "[ERR]"
+INF = "[INF]"
+
+stdout = sys.stdout
+stderr = sys.stderr
+
+def log(target, level, message, code = 0):
+
+	message = time.ctime() + empty_delim + str(level) + l_brack + str(code) + r_brack + empty_delim + soft_divided_delim + empty_delim + message
+	print(message, file = target)
+
+def clear():
+	if name == "nt":
+		system("cls")
+	else:
+		system("clear")
+
+def splash(version):
+
+	def hrule():
+		print("#"+38*"-"+"#")
+	def box(s):
+		temp = "|"
+		temp += s
+		temp += (40-len(s)-2)*" "
+		temp += "|"
+		print(temp)
+	
+	hrule()
+	box(" superscript version: " + version)
+	box(" os: " + platform.system())
+	box(" python: " + platform.python_version())
+	hrule()

src/cli/superscript.py

@@ -0,0 +1,214 @@
+# Titan Robotics Team 2022: Superscript Script
+# Written by Arthur Lu, Jacob Levine, and Dev Singh
+# Notes:
+# setup:
+
+__version__ = "0.8.6"
+
+# changelog should be viewed using print(analysis.__changelog__)
+__changelog__ = """changelog:
+	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>",
+)
+
+__all__ = [
+	"load_config",
+	"save_config",
+	"get_previous_time",
+	"load_match",
+	"matchloop",
+	"load_metric",
+	"metricloop",
+	"load_pit",
+	"pitloop",
+	"push_match",
+	"push_metric",
+	"push_pit",
+]
+
+# imports:
+
+import json
+
+from cli_interface import splash, log, ERR, INF, stdout, stderr
+
+config_path = "config.json"
+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
+		}
+	}
+}"""
+
+def main():
+
+	splash(__version__)
+
+def load_config(config_vector):
+	try:
+		f = open(path, "r")
+	except:
+		log(stderr, ERR, "could not find config at <" + path + ">, generating blank config and exiting")
+		f = open(path, "w")
+		f.write(sample_json)
+		f.close()
+		return 1
+	
+	config_vector = json.load(f)
+	f.close()
+	return 0
+
+def save_config(path, config_vector):
+	try:
+		f = open(path)
+		json.dump(config_vector)
+		f.close()
+		return 0
+	except:
+		return 1
+
+if __name__ == "__main__":
+	main()

src/gui/data.py

@@ -0,0 +1,129 @@
+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