alu/tra-analysis
1
0
Fork 0
mirror of https://github.com/titanscouting/tra-analysis.git synced 2024-12-26 17:49:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

Revert "yeeted"

Browse Source 
This reverts commit 1f2edeba51.
This commit is contained in:
ltcptgeneral 2019-03-21 17:50:46 -05:00
parent e81f6052e3
commit 12cf4a55d7
2 changed files with 185 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

88
data analysis/Untitled.ipynb Normal file
View File

@ -0,0 +1,88 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import tbarequest"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2022', 'frc2358', 'frc7417']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2040', 'frc2481', 'frc81']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm70', 'match_number': 70, 'post_result_time': None, 'predicted_time': 1553357160, 'score_breakdown': None, 'set_number': 1, 'time': 1553357160, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc6237', 'frc4156', 'frc4646']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc4241', 'frc1781', 'frc2022']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm61', 'match_number': 61, 'post_result_time': None, 'predicted_time': 1553352300, 'score_breakdown': None, 'set_number': 1, 'time': 1553352300, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc1736', 'frc2022', 'frc5126']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc5690', 'frc1329', 'frc4241']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm57', 'match_number': 57, 'post_result_time': None, 'predicted_time': 1553350140, 'score_breakdown': None, 'set_number': 1, 'time': 1553350140, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc6237', 'frc2358', 'frc2039']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2022', 'frc7848', 'frc4212']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm53', 'match_number': 53, 'post_result_time': None, 'predicted_time': 1553292960, 'score_breakdown': None, 'set_number': 1, 'time': 1553292960, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc7465', 'frc4213', 'frc2704']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc1329', 'frc6055', 'frc2022']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm41', 'match_number': 41, 'post_result_time': None, 'predicted_time': 1553287200, 'score_breakdown': None, 'set_number': 1, 'time': 1553287200, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2022', 'frc4156', 'frc5442']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc5822', 'frc4143', 'frc7848']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm4', 'match_number': 4, 'post_result_time': None, 'predicted_time': 1553264820, 'score_breakdown': None, 'set_number': 1, 'time': 1553264820, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc1094', 'frc4314', 'frc6651']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc6237', 'frc2081', 'frc2022']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm38', 'match_number': 38, 'post_result_time': None, 'predicted_time': 1553285760, 'score_breakdown': None, 'set_number': 1, 'time': 1553285760, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2013', 'frc2081', 'frc6055']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc81', 'frc2022', 'frc3695']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm31', 'match_number': 31, 'post_result_time': None, 'predicted_time': 1553282400, 'score_breakdown': None, 'set_number': 1, 'time': 1553282400, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc4655', 'frc5822', 'frc2022']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc4256', 'frc323', 'frc2709']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm22', 'match_number': 22, 'post_result_time': None, 'predicted_time': 1553278080, 'score_breakdown': None, 'set_number': 1, 'time': 1553278080, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc1756', 'frc1329', 'frc1288']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc4096', 'frc2022', 'frc323']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm14', 'match_number': 14, 'post_result_time': None, 'predicted_time': 1553269860, 'score_breakdown': None, 'set_number': 1, 'time': 1553269860, 'videos': [], 'winning_alliance': ''}\n",
"{'actual_time': None, 'alliances': {'blue': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2039', 'frc2022', 'frc1288']}, 'red': {'dq_team_keys': [], 'score': -1, 'surrogate_team_keys': [], 'team_keys': ['frc2013', 'frc4096', 'frc1781']}}, 'comp_level': 'qm', 'event_key': '2019ilpe', 'key': '2019ilpe_qm10', 'match_number': 10, 'post_result_time': None, 'predicted_time': 1553267940, 'score_breakdown': None, 'set_number': 1, 'time': 1553267940, 'videos': [], 'winning_alliance': ''}\n"
]
}
],
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Response [404]>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tbarequest.req_team_matches('frc16', '2019','UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

97
data analysis/test.py Normal file
View File

@ -0,0 +1,97 @@
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import csv
import numpy as np
# Use a service account
cred = credentials.Certificate('keys/keytemp.json')
#add your own key as this is public. email me for details
firebase_admin.initialize_app(cred)
db = firestore.client()
teams=db.collection('data').document('team-2022').collection("Central 2019").get()
full=[]
tms=[]
for team in teams:
tms.append(team.id)
reports=db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").get()
for report in reports:
data=[]
data.append(db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").document(report.id).get().to_dict())
full.append(data)
quant_keys = []
list_teams = ["2022", "16", "2451"]
out = []
var = {}
for i in range(len(full)):
for j in range(len(full[i])):
for key in list(full[i][j].keys()):
if "Quantitative" in key:
quant_keys.append(key)
if full[i][j].get(key).get('teamDBRef')[5:] in list_teams:
var = {}
measured_vars = []
for k in range(len(list(full[i][j].get(key).keys()))):
individual_keys = list(full[i][j].get(key).keys())
var[individual_keys[k]] = full[i][j].get(key).get(individual_keys[k])
out.append(var)
sorted_out = []
for i in out:
j_list = []
key_list = []
sorted_keys = sorted(i.keys())
for j in sorted_keys:
key_list.append(i[j])
j_list.append(j)
sorted_out.append(key_list)
var_index = 0
team_index = 0
big_out = []
for j in range(len(i)):
big_out.append([])
for t in range(len(list_teams)):
big_out[j].append([])
for i in sorted_out:
team_index = list_teams.index(sorted_out[sorted_out.index(i)][j_list.index('teamDBRef')][5:])
for j in range(len(i)):
big_out[j][team_index].append(i[j])
for i in range(len(big_out)):
with open('data/' + j_list[i] + '.csv', "w+", newline = '') as file:
writer = csv.writer(file, delimiter = ',')
writer.writerows(big_out[i])