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# Titan Robotics Team 2022: Data Analysis Module
# Written by Arthur Lu & Jacob Levine
# Notes:
# this should be imported as a python module using 'import analysis'
# this should be included in the local directory or environment variable
# this module has not been optimized for multhreaded computing
# number of easter eggs: 2
# setup:
__version__ = "1.0.9.000"
# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
1.0.9.000:
- refactored
- numpyed everything
- removed stats in favor of numpy functions
1.0.8.005:
- minor fixes
1.0.8.004:
- removed a few unused dependencies
1.0.8.003:
- added p_value function
1.0.8.002:
- updated __all__ correctly to contain changes made in v 1.0.8.000 and v 1.0.8.001
1.0.8.001:
- refactors
- bugfixes
1.0.8.000:
- depreciated histo_analysis_old
- depreciated debug
- altered basic_analysis to take array data instead of filepath
- refactor
- optimization
1.0.7.002:
- bug fixes
1.0.7.001:
- bug fixes
1.0.7.000:
- added tanh_regression (logistical regression)
- bug fixes
1.0.6.005:
- added z_normalize function to normalize dataset
- bug fixes
1.0.6.004:
- bug fixes
1.0.6.003:
- bug fixes
1.0.6.002:
- bug fixes
1.0.6.001:
- corrected __all__ to contain all of the functions
1.0.6.000:
- added calc_overfit, which calculates two measures of overfit, error and performance
- added calculating overfit to optimize_regression
1.0.5.000:
- added optimize_regression function, which is a sample function to find the optimal regressions
- optimize_regression function filters out some overfit funtions (functions with r^2 = 1)
- planned addition: overfit detection in the optimize_regression function
1.0.4.002:
- added __changelog__
- updated debug function with log and exponential regressions
1.0.4.001:
- added log regressions
- added exponential regressions
- added log_regression and exp_regression to __all__
1.0.3.008:
- added debug function to further consolidate functions
1.0.3.007:
- added builtin benchmark function
- added builtin random (linear) data generation function
- added device initialization (_init_device)
1.0.3.006:
- reorganized the imports list to be in alphabetical order
- added search and regurgitate functions to c_entities, nc_entities, obstacles, objectives
1.0.3.005:
- major bug fixes
- updated historical analysis
- depreciated old historical analysis
1.0.3.004:
- added __version__, __author__, __all__
- added polynomial regression
- added root mean squared function
- added r squared function
1.0.3.003:
- bug fixes
- added c_entities
1.0.3.002:
- bug fixes
- added nc_entities, obstacles, objectives
- consolidated statistics.py to analysis.py
1.0.3.001:
- compiled 1d, column, and row basic stats into basic stats function
1.0.3.000:
- added historical analysis function
1.0.2.xxx:
- added z score test
1.0.1.xxx:
- major bug fixes
1.0.0.xxx:
- added loading csv
- added 1d, column, row basic stats
"""
__author__ = (
"Arthur Lu <arthurlu@ttic.edu>, "
"Jacob Levine <jlevine@ttic.edu>,"
)
__all__ = [
'_init_device',
'c_entities',
'nc_entities',
'obstacles',
'objectives',
'load_csv',
'basic_stats',
'z_score',
'z_normalize',
'stdev_z_split',
'histo_analysis',
'poly_regression',
'log_regression',
'exp_regression',
'r_squared',
'rms',
'calc_overfit',
'strip_data',
'optimize_regression',
'select_best_regression',
'basic_analysis',
# all statistics functions left out due to integration in other functions
]
# now back to your regularly scheduled programming:
# imports (now in alphabetical order! v 1.0.3.006):
from bisect import bisect_left, bisect_right
import collections
import csv
from decimal import Decimal
import functools
from fractions import Fraction
from itertools import groupby
import math
import matplotlib
import numbers
import numpy as np
import pandas
import random
import scipy
from scipy.optimize import curve_fit
from scipy import stats
from sklearn import *
# import statistics <-- statistics.py functions have been integrated into analysis.py as of v 1.0.3.002
import time
import torch
class error(ValueError):
pass
def _init_device(setting, arg): # initiates computation device for ANNs
if setting == "cuda":
try:
return torch.device(setting + ":" + str(arg) if torch.cuda.is_available() else "cpu")
except:
raise error("could not assign cuda or cpu")
elif setting == "cpu":
try:
return torch.device("cpu")
except:
raise error("could not assign cpu")
else:
raise error("specified device does not exist")
def load_csv(filepath):
with open(filepath, newline='') as csvfile:
file_array = np.array(list(csv.reader(csvfile)))
csvfile.close()
return file_array
# data=array, mode = ['1d':1d_basic_stats, 'column':c_basic_stats, 'row':r_basic_stats], arg for mode 1 or mode 2 for column or row
def basic_stats(data, method, arg):
if method == 'debug':
return "basic_stats requires 3 args: data, mode, arg; where data is data to be analyzed, mode is an int from 0 - 2 depending on type of analysis (by column or by row) and is only applicable to 2d arrays (for 1d arrays use mode 1), and arg is row/column number for mode 1 or mode 2; function returns: [mean, median, mode, stdev, variance]"
if method == "1d" or method == 0:
data_t = np.array(data).astype(float)
_mean = mean(data_t)
_median = median(data_t)
try:
_mode = mode(data_t)
except:
_mode = None
try:
_stdev = stdev(data_t)
except:
_stdev = None
try:
_variance = variance(data_t)
except:
_variance = None
return _mean, _median, _mode, _stdev, _variance
"""
elif method == "column" or method == 1:
c_data = []
c_data_sorted = []
for i in data:
try:
c_data.append(float(i[arg]))
except:
pass
_mean = mean(c_data)
_median = median(c_data)
try:
_mode = mode(c_data)
except:
_mode = None
try:
_stdev = stdev(c_data)
except:
_stdev = None
try:
_variance = variance(c_data)
except:
_variance = None
return _mean, _median, _mode, _stdev, _variance
elif method == "row" or method == 2:
r_data = []
for i in range(len(data[arg])):
r_data.append(float(data[arg][i]))
_mean = mean(r_data)
_median = median(r_data)
try:
_mode = mode(r_data)
except:
_mode = None
try:
_stdev = stdev(r_data)
except:
_stdev = None
try:
_variance = variance(r_data)
except:
_variance = None
return _mean, _median, _mode, _stdev, _variance
else:
raise error("method error")
"""
# returns z score with inputs of point, mean and standard deviation of spread
def z_score(point, mean, stdev):
score = (point - mean) / stdev
return score
# mode is either 'x' or 'y' or 'both' depending on the variable(s) to be normalized
def z_normalize(x, y, mode):
x_norm = np.array().astype(float)
y_norm = np.array().astype(float)
mean = 0
stdev = 0
if mode == 'x':
_mean, _median, _mode, _stdev, _variance = basic_stats(x, "1d", 0)
for i in range(0, len(x), 1):
x_norm.append(z_score(x[i], _mean, _stdev))
return x_norm, y
if mode == 'y':
_mean, _median, _mode, _stdev, _variance = basic_stats(y, "1d", 0)
for i in range(0, len(y), 1):
y_norm.append(z_score(y[i], _mean, _stdev))
return x, y_norm
if mode == 'both':
_mean, _median, _mode, _stdev, _variance = basic_stats(x, "1d", 0)
for i in range(0, len(x), 1):
x_norm.append(z_score(x[i], _mean, _stdev))
_mean, _median, _mode, _stdev, _variance = basic_stats(y, "1d", 0)
for i in range(0, len(y), 1):
y_norm.append(z_score(y[i], _mean, _stdev))
return x_norm, y_norm
else:
return error('method error')
# returns n-th percentile of spread given mean, standard deviation, lower z-score, and upper z-score
def stdev_z_split(mean, stdev, delta, low_bound, high_bound):
z_split = np.array().astype(float)
i = low_bound
while True:
z_split.append(float((1 / (stdev * math.sqrt(2 * math.pi))) *
math.e ** (-0.5 * (((i - mean) / stdev) ** 2))))
i = i + delta
if i > high_bound:
break
return z_split
def histo_analysis(hist_data, delta, low_bound, high_bound):
if hist_data == 'debug':
return ('returns list of predicted values based on historical data; input delta for delta step in z-score and lower and higher bounds in number of standard deviations')
derivative = []
for i in range(0, len(hist_data), 1):
try:
derivative.append(float(hist_data[i - 1]) - float(hist_data[i]))
except:
pass
derivative_sorted = sorted(derivative, key=int)
mean_derivative = basic_stats(derivative_sorted, "1d", 0)[0]
stdev_derivative = basic_stats(derivative_sorted, "1d", 0)[3]
predictions = []
pred_change = 0
i = low_bound
while True:
if i > high_bound:
break
try:
pred_change = mean_derivative + i * stdev_derivative
except:
pred_change = mean_derivative
predictions.append(float(hist_data[-1:][0]) + pred_change)
i = i + delta
return predictions
def poly_regression(x, y, power):
if x == "null": # if x is 'null', then x will be filled with integer points between 1 and the size of y
x = []
for i in range(len(y)):
print(i)
x.append(i + 1)
reg_eq = scipy.polyfit(x, y, deg=power)
eq_str = ""
for i in range(0, len(reg_eq), 1):
if i < len(reg_eq) - 1:
eq_str = eq_str + str(reg_eq[i]) + \
"*(z**" + str(len(reg_eq) - i - 1) + ")+"
else:
eq_str = eq_str + str(reg_eq[i]) + \
"*(z**" + str(len(reg_eq) - i - 1) + ")"
vals = []
for i in range(0, len(x), 1):
z = x[i]
try:
exec("vals.append(" + eq_str + ")")
except:
pass
_rms = rms(vals, y)
r2_d2 = r_squared(vals, y)
return [eq_str, _rms, r2_d2]
def log_regression(x, y, base):
x_fit = []
for i in range(len(x)):
try:
# change of base for logs
x_fit.append(np.log(x[i]) / np.log(base))
except:
pass
# y = reg_eq[0] * log(x, base) + reg_eq[1]
reg_eq = np.polyfit(x_fit, y, 1)
q_str = str(reg_eq[0]) + "* (np.log(z) / np.log(" + \
str(base) + "))+" + str(reg_eq[1])
vals = []
for i in range(len(x)):
z = x[i]
try:
exec("vals.append(" + eq_str + ")")
except:
pass
_rms = rms(vals, y)
r2_d2 = r_squared(vals, y)
return eq_str, _rms, r2_d2
def exp_regression(x, y, base):
y_fit = []
for i in range(len(y)):
try:
# change of base for logs
y_fit.append(np.log(y[i]) / np.log(base))
except:
pass
# y = base ^ (reg_eq[0] * x) * base ^ (reg_eq[1])
reg_eq = np.polyfit(x, y_fit, 1, w=np.sqrt(y_fit))
eq_str = "(" + str(base) + "**(" + \
str(reg_eq[0]) + "*z))*(" + str(base) + "**(" + str(reg_eq[1]) + "))"
vals = []
for i in range(len(x)):
z = x[i]
try:
exec("vals.append(" + eq_str + ")")
except:
pass
_rms = rms(vals, y)
r2_d2 = r_squared(vals, y)
return eq_str, _rms, r2_d2
def tanh_regression(x, y):
def tanh(x, a, b, c, d):
return a * np.tanh(b * (x - c)) + d
reg_eq = np.float64(curve_fit(tanh, np.array(x), np.array(y))[0]).tolist()
eq_str = str(reg_eq[0]) + " * np.tanh(" + str(reg_eq[1]) + \
"*(z - " + str(reg_eq[2]) + ")) + " + str(reg_eq[3])
vals = []
for i in range(len(x)):
z = x[i]
try:
exec("vals.append(" + eq_str + ")")
except:
pass
_rms = rms(vals, y)
r2_d2 = r_squared(vals, y)
return eq_str, _rms, r2_d2
def r_squared(predictions, targets): # assumes equal size inputs
return metrics.r2_score(np.array(targets), np.array(predictions))
def rms(predictions, targets): # assumes equal size inputs
_sum = 0
for i in range(0, len(targets), 1):
_sum = (targets[i] - predictions[i]) ** 2
return float(math.sqrt(_sum / len(targets)))
def calc_overfit(equation, rms_train, r2_train, x_test, y_test):
# performance overfit = performance(train) - performance(test) where performance is r^2
# error overfit = error(train) - error(test) where error is rms; biased towards smaller values
vals = []
for i in range(0, len(x_test), 1):
z = x_test[i]
exec("vals.append(" + equation + ")")
r2_test = r_squared(vals, y_test)
rms_test = rms(vals, y_test)
return r2_train - r2_test
def strip_data(data, mode):
if mode == "adam": # x is the row number, y are the data
pass
if mode == "eve": # x are the data, y is the column number
pass
else:
raise error("mode error")
# _range in poly regression is the range of powers tried, and in log/exp it is the inverse of the stepsize taken from -1000 to 1000
def optimize_regression(x, y, _range, resolution):
# usage not: for demonstration purpose only, performance is shit
if type(resolution) != int:
raise error("resolution must be int")
x_train = x
y_train = []
for i in range(len(y)):
y_train.append(float(y[i]))
x_test = []
y_test = []
for i in range(0, math.floor(len(x) * 0.5), 1):
index = random.randint(0, len(x) - 1)
x_test.append(x[index])
y_test.append(float(y[index]))
x_train.pop(index)
y_train.pop(index)
#print(x_train, x_test)
#print(y_train, y_test)
eqs = []
rmss = []
r2s = []
for i in range(0, _range + 1, 1):
try:
x, y, z = poly_regression(x_train, y_train, i)
eqs.append(x)
rmss.append(y)
r2s.append(z)
except:
pass
for i in range(1, 100 * resolution + 1):
try:
x, y, z = exp_regression(x_train, y_train, float(i / resolution))
eqs.append(x)
rmss.append(y)
r2s.append(z)
except:
pass
for i in range(1, 100 * resolution + 1):
try:
x, y, z = log_regression(x_train, y_train, float(i / resolution))
eqs.append(x)
rmss.append(y)
r2s.append(z)
except:
pass
try:
x, y, z = tanh_regression(x_train, y_train)
eqs.append(x)
rmss.append(y)
r2s.append(z)
except:
pass
# marks all equations where r2 = 1 as they 95% of the time overfit the data
for i in range(0, len(eqs), 1):
if r2s[i] == 1:
eqs[i] = ""
rmss[i] = ""
r2s[i] = ""
while True: # removes all equations marked for removal
try:
eqs.remove('')
rmss.remove('')
r2s.remove('')
except:
break
overfit = []
for i in range(0, len(eqs), 1):
overfit.append(calc_overfit(eqs[i], rmss[i], r2s[i], x_test, y_test))
return eqs, rmss, r2s, overfit
def select_best_regression(eqs, rmss, r2s, overfit, selector):
b_eq = ""
b_rms = 0
b_r2 = 0
b_overfit = 0
ind = 0
if selector == "min_overfit":
ind = np.argmin(overfit)
b_eq = eqs[ind]
b_rms = rmss[ind]
b_r2 = r2s[ind]
b_overfit = overfit[ind]
if selector == "max_r2s":
ind = np.argmax(r2s)
b_eq = eqs[ind]
b_rms = rmss[ind]
b_r2 = r2s[ind]
b_overfit = overfit[ind]
return b_eq, b_rms, b_r2, b_overfit
def p_value(x, y): # takes 2 1d arrays
return stats.ttest_ind(x, y)[1]
# assumes that rows are the independent variable and columns are the dependant. also assumes that time flows from lowest column to highest column.
def basic_analysis(data):
row = len(data)
column = []
for i in range(0, row, 1):
column.append(len(data[i]))
column_max = max(column)
row_b_stats = []
row_histo = []
for i in range(0, row, 1):
row_b_stats.append(basic_stats(data, "row", i))
row_histo.append(histo_analysis(data[i], 0.67449, -0.67449, 0.67449))
column_b_stats = []
for i in range(0, column_max, 1):
column_b_stats.append(basic_stats(data, "column", i))
return[row_b_stats, column_b_stats, row_histo]
def benchmark(x, y):
start_g = time.time()
generate_data("data/data.csv", x, y, -10, 10)
end_g = time.time()
start_a = time.time()
basic_analysis("data/data.csv")
end_a = time.time()
return [(end_g - start_g), (end_a - start_a)]
def generate_data(filename, x, y, low, high):
file = open(filename, "w")
for i in range(0, y, 1):
temp = ""
for j in range(0, x - 1, 1):
temp = str(random.uniform(low, high)) + "," + temp
temp = temp + str(random.uniform(low, high))
file.write(temp + "\n")
def mean(data):
return np.mean(data)
def median(data):
return np.median(data)
def mode(data):
return np.argmax(np.bincount(data))
def stdev(data):
return np.std(data)
def variance(data):
return np.var(data)
"""
class StatisticsError(ValueError):
pass
def _sum(data, start=0):
count = 0
n, d = _exact_ratio(start)
partials = {d: n}
partials_get = partials.get
T = _coerce(int, type(start))
for typ, values in groupby(data, type):
T = _coerce(T, typ) # or raise TypeError
for n, d in map(_exact_ratio, values):
count += 1
partials[d] = partials_get(d, 0) + n
if None in partials:
total = partials[None]
assert not _isfinite(total)
else:
total = sum(Fraction(n, d) for d, n in sorted(partials.items()))
return (T, total, count)
def _isfinite(x):
try:
return x.is_finite() # Likely a Decimal.
except AttributeError:
return math.isfinite(x) # Coerces to float first.
def _coerce(T, S):
assert T is not bool, "initial type T is bool"
if T is S:
return T
if S is int or S is bool:
return T
if T is int:
return S
if issubclass(S, T):
return S
if issubclass(T, S):
return T
if issubclass(T, int):
return S
if issubclass(S, int):
return T
if issubclass(T, Fraction) and issubclass(S, float):
return S
if issubclass(T, float) and issubclass(S, Fraction):
return T
msg = "don't know how to coerce %s and %s"
raise TypeError(msg % (T.__name__, S.__name__))
def _exact_ratio(x):
try:
if type(x) is float or type(x) is Decimal:
return x.as_integer_ratio()
try:
return (x.numerator, x.denominator)
except AttributeError:
try:
return x.as_integer_ratio()
except AttributeError:
pass
except (OverflowError, ValueError):
assert not _isfinite(x)
return (x, None)
msg = "can't convert type '{}' to numerator/denominator"
raise TypeError(msg.format(type(x).__name__))
def _convert(value, T):
if type(value) is T:
return value
if issubclass(T, int) and value.denominator != 1:
T = float
try:
return T(value)
except TypeError:
if issubclass(T, Decimal):
return T(value.numerator) / T(value.denominator)
else:
raise
def _counts(data):
table = collections.Counter(iter(data)).most_common()
if not table:
return table
maxfreq = table[0][1]
for i in range(1, len(table)):
if table[i][1] != maxfreq:
table = table[:i]
break
return table
def _find_lteq(a, x):
i = bisect_left(a, x)
if i != len(a) and a[i] == x:
return i
raise ValueError
def _find_rteq(a, l, x):
i = bisect_right(a, x, lo=l)
if i != (len(a) + 1) and a[i - 1] == x:
return i - 1
raise ValueError
def _fail_neg(values, errmsg='negative value'):
for x in values:
if x < 0:
raise StatisticsError(errmsg)
yield x
def mean(data):
if iter(data) is data:
data = list(data)
n = len(data)
if n < 1:
raise StatisticsError('mean requires at least one data point')
T, total, count = _sum(data)
assert count == n
return _convert(total / n, T)
def median(data):
data = sorted(data)
n = len(data)
if n == 0:
raise StatisticsError("no median for empty data")
if n % 2 == 1:
return data[n // 2]
else:
i = n // 2
return (data[i - 1] + data[i]) / 2
def mode(data):
table = _counts(data)
if len(table) == 1:
return table[0][0]
elif table:
raise StatisticsError(
'no unique mode; found %d equally common values' % len(table)
)
else:
raise StatisticsError('no mode for empty data')
def _ss(data, c=None):
if c is None:
c = mean(data)
T, total, count = _sum((x - c)**2 for x in data)
U, total2, count2 = _sum((x - c) for x in data)
assert T == U and count == count2
total -= total2**2 / len(data)
assert not total < 0, 'negative sum of square deviations: %f' % total
return (T, total)
def variance(data, xbar=None):
if iter(data) is data:
data = list(data)
n = len(data)
if n < 2:
raise StatisticsError('variance requires at least two data points')
T, ss = _ss(data, xbar)
return _convert(ss / (n - 1), T)
def stdev(data, xbar=None):
var = variance(data, xbar)
try:
return var.sqrt()
except AttributeError:
return math.sqrt(var)
"""

35536
data analysis/dep/2019/analysis/analysis.c
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data analysis/dep/2019/analysis/analysis.cp37-win_amd64.pyd
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data analysis/dep/2019/analysis/compile.bat
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python setup.py build_ext --inplace
pause

1
data analysis/dep/2019/analysis/compile.sh
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@ -1 +0,0 @@
python setup.py build_ext --inplace

5
data analysis/dep/2019/analysis/setup.py
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@ -1,5 +0,0 @@
from distutils.core import setup
from Cython.Build import cythonize
setup(name='analysis',
ext_modules=cythonize("analysis.py"))

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data analysis/dep/2019/apps/android/apk/1.0.0.001/app-release.apk
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data analysis/dep/2019/apps/android/apk/1.0.0.002/app-debug.apk
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data analysis/dep/2019/apps/android/apk/debug/output.json
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[{"outputType":{"type":"APK"},"apkInfo":{"type":"MAIN","splits":[],"versionCode":1,"versionName":"1.0","enabled":true,"outputFile":"app-debug.apk","fullName":"debug","baseName":"debug"},"path":"app-debug.apk","properties":{}}]

13
data analysis/dep/2019/apps/android/source/.gitignore vendored
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@ -1,13 +0,0 @@
*.iml
.gradle
/local.properties
/.idea/caches
/.idea/libraries
/.idea/modules.xml
/.idea/workspace.xml
/.idea/navEditor.xml
/.idea/assetWizardSettings.xml
.DS_Store
/build
/captures
.externalNativeBuild

29
data analysis/dep/2019/apps/android/source/.idea/codeStyles/Project.xml generated
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@ -1,29 +0,0 @@
<component name="ProjectCodeStyleConfiguration">
<code_scheme name="Project" version="173">
<Objective-C-extensions>
<file>
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Import" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Macro" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Typedef" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Enum" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Constant" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Global" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Struct" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="FunctionPredecl" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Function" />
</file>
<class>
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Property" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="Synthesize" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="InitMethod" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="StaticMethod" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="InstanceMethod" />
<option name="com.jetbrains.cidr.lang.util.OCDeclarationKind" value="DeallocMethod" />
</class>
<extensions>
<pair source="cpp" header="h" fileNamingConvention="NONE" />
<pair source="c" header="h" fileNamingConvention="NONE" />
</extensions>
</Objective-C-extensions>
</code_scheme>
</component>

18
data analysis/dep/2019/apps/android/source/.idea/gradle.xml generated
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@ -1,18 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="GradleSettings">
<option name="linkedExternalProjectsSettings">
<GradleProjectSettings>
<option name="distributionType" value="DEFAULT_WRAPPED" />
<option name="externalProjectPath" value="$PROJECT_DIR$" />
<option name="modules">
<set>
<option value="$PROJECT_DIR$" />
<option value="$PROJECT_DIR$/app" />
</set>
</option>
<option name="resolveModulePerSourceSet" value="false" />
</GradleProjectSettings>
</option>
</component>
</project>

9
data analysis/dep/2019/apps/android/source/.idea/misc.xml generated
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@ -1,9 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectRootManager" version="2" languageLevel="JDK_11" project-jdk-name="11" project-jdk-type="JavaSDK">
<output url="file://$PROJECT_DIR$/build/classes" />
</component>
<component name="ProjectType">
<option name="id" value="Android" />
</component>
</project>

12
data analysis/dep/2019/apps/android/source/.idea/runConfigurations.xml generated
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@ -1,12 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="RunConfigurationProducerService">
<option name="ignoredProducers">
<set>
<option value="org.jetbrains.plugins.gradle.execution.test.runner.AllInPackageGradleConfigurationProducer" />
<option value="org.jetbrains.plugins.gradle.execution.test.runner.TestClassGradleConfigurationProducer" />
<option value="org.jetbrains.plugins.gradle.execution.test.runner.TestMethodGradleConfigurationProducer" />
</set>
</option>
</component>
</project>

6
data analysis/dep/2019/apps/android/source/.idea/vcs.xml generated
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@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$/../../.." vcs="Git" />
</component>
</project>

1
data analysis/dep/2019/apps/android/source/app/.gitignore vendored
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@ -1 +0,0 @@
/build

28
data analysis/dep/2019/apps/android/source/app/build.gradle
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@ -1,28 +0,0 @@
apply plugin: 'com.android.application'
android {
compileSdkVersion 28
defaultConfig {
applicationId "com.example.titanscouting"
minSdkVersion 16
targetSdkVersion 28
versionCode 1
versionName "1.0"
testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
}
}
}
dependencies {
implementation fileTree(dir: 'libs', include: ['*.jar'])
implementation 'com.android.support:appcompat-v7:28.0.0'
implementation 'com.android.support.constraint:constraint-layout:1.1.3'
testImplementation 'junit:junit:4.12'
androidTestImplementation 'com.android.support.test:runner:1.0.2'
androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'
}

21
data analysis/dep/2019/apps/android/source/app/proguard-rules.pro vendored
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@ -1,21 +0,0 @@
# Add project specific ProGuard rules here.
# You can control the set of applied configuration files using the
# proguardFiles setting in build.gradle.
#
# For more details, see
# http://developer.android.com/guide/developing/tools/proguard.html
# If your project uses WebView with JS, uncomment the following
# and specify the fully qualified class name to the JavaScript interface
# class:
#-keepclassmembers class fqcn.of.javascript.interface.for.webview {
# public *;
#}
# Uncomment this to preserve the line number information for
# debugging stack traces.
#-keepattributes SourceFile,LineNumberTable
# If you keep the line number information, uncomment this to
# hide the original source file name.
#-renamesourcefileattribute SourceFile

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1
data analysis/dep/2019/apps/android/source/app/release/output.json
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[{"outputType":{"type":"APK"},"apkInfo":{"type":"MAIN","splits":[],"versionCode":1,"versionName":"1.0","enabled":true,"outputFile":"app-release.apk","fullName":"release","baseName":"release"},"path":"app-release.apk","properties":{}}]

26
data analysis/dep/2019/apps/android/source/app/src/androidTest/java/com/example/titanscouting/ExampleInstrumentedTest.java
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@ -1,26 +0,0 @@
package com.example.titanscouting;
import android.content.Context;
import android.support.test.InstrumentationRegistry;
import android.support.test.runner.AndroidJUnit4;
import org.junit.Test;
import org.junit.runner.RunWith;
import static org.junit.Assert.*;
/**
* Instrumented test, which will execute on an Android device.
*
* @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
*/
@RunWith(AndroidJUnit4.class)
public class ExampleInstrumentedTest {
@Test
public void useAppContext() {
// Context of the app under test.
Context appContext = InstrumentationRegistry.getTargetContext();
assertEquals("com.example.titanscouting", appContext.getPackageName());
}
}

28
data analysis/dep/2019/apps/android/source/app/src/main/AndroidManifest.xml
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@ -1,28 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.example.titanscouting">
<uses-permission android:name="android.permission.INTERNET" />
<application
android:allowBackup="true"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:roundIcon="@drawable/binoculars_big"
android:supportsRtl="true"
android:theme="@style/AppTheme"
android:usesCleartextTraffic="true">
<activity android:name=".tits"></activity>
<activity android:name=".launcher">
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
<activity android:name=".MainActivity">
</activity>
</application>
</manifest>

32
data analysis/dep/2019/apps/android/source/app/src/main/java/com/example/titanscouting/MainActivity.java
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@ -1,32 +0,0 @@
package com.example.titanscouting;
import android.support.v7.app.AppCompatActivity;
import android.os.Bundle;
import android.webkit.WebView;
import android.webkit.WebSettings;
import android.webkit.WebViewClient;
public class MainActivity extends AppCompatActivity {
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
WebView myWebView = (WebView) findViewById(R.id.webview);
myWebView.getSettings().setJavaScriptEnabled(true);
myWebView.setWebViewClient(new WebViewClient());
myWebView.loadUrl("http://titanrobotics.ddns.net:60080/public/");
myWebView.getSettings().setJavaScriptEnabled(true);
myWebView.getSettings().setJavaScriptCanOpenWindowsAutomatically(true);
myWebView.getSettings().setDomStorageEnabled(true);
myWebView.getSettings().setDomStorageEnabled(true);
}
}

49
data analysis/dep/2019/apps/android/source/app/src/main/java/com/example/titanscouting/launcher.java
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@ -1,49 +0,0 @@
package com.example.titanscouting;
import android.support.v7.app.AppCompatActivity;
import android.os.Bundle;
import android.app.Activity;
import android.content.Intent;
import android.view.Menu;
import android.view.View;
import android.view.View.OnClickListener;
import android.widget.Button;
import android.widget.EditText;
public class launcher extends AppCompatActivity {
Button button;
EditText passField;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_launcher);
// Locate the button in activity_main.xml
button = (Button) findViewById(R.id.launch_button);
final EditText passField = (EditText)findViewById(R.id.editText);
// Capture button clicks
button.setOnClickListener(new OnClickListener() {
public void onClick(View arg0) {
// Start NewActivity.class
if(passField.getText().toString().equals("gimmetits")){
Intent myIntent = new Intent(launcher.this,
tits.class);
startActivity(myIntent);
}
else {
Intent myIntent = new Intent(launcher.this,
MainActivity.class);
startActivity(myIntent);
}
}
});
}
}

30
data analysis/dep/2019/apps/android/source/app/src/main/java/com/example/titanscouting/tits.java
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@ -1,30 +0,0 @@
package com.example.titanscouting;
import android.content.Intent;
import android.support.v7.app.AppCompatActivity;
import android.os.Bundle;
import android.view.View;
import android.widget.Button;
import android.widget.EditText;
public class tits extends AppCompatActivity {
Button button;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_tits);
button = (Button) findViewById(R.id.button);
// Capture button clicks
button.setOnClickListener(new View.OnClickListener() {
public void onClick(View arg0) {
Intent myIntent = new Intent(tits.this,
MainActivity.class);
startActivity(myIntent);
}
});
}
}

34
data analysis/dep/2019/apps/android/source/app/src/main/res/drawable-v24/ic_launcher_foreground.xml
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@ -1,34 +0,0 @@
<vector xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:aapt="http://schemas.android.com/aapt"
android:width="108dp"
android:height="108dp"
android:viewportWidth="108"
android:viewportHeight="108">
<path
android:fillType="evenOdd"
android:pathData="M32,64C32,64 38.39,52.99 44.13,50.95C51.37,48.37 70.14,49.57 70.14,49.57L108.26,87.69L108,109.01L75.97,107.97L32,64Z"
android:strokeWidth="1"
android:strokeColor="#00000000">
<aapt:attr name="android:fillColor">
<gradient
android:endX="78.5885"
android:endY="90.9159"
android:startX="48.7653"
android:startY="61.0927"
android:type="linear">
<item
android:color="#44000000"
android:offset="0.0" />
<item
android:color="#00000000"
android:offset="1.0" />
</gradient>
</aapt:attr>
</path>
<path
android:fillColor="#FFFFFF"
android:fillType="nonZero"
android:pathData="M66.94,46.02L66.94,46.02C72.44,50.07 76,56.61 76,64L32,64C32,56.61 35.56,50.11 40.98,46.06L36.18,41.19C35.45,40.45 35.45,39.3 36.18,38.56C36.91,37.81 38.05,37.81 38.78,38.56L44.25,44.05C47.18,42.57 50.48,41.71 54,41.71C57.48,41.71 60.78,42.57 63.68,44.05L69.11,38.56C69.84,37.81 70.98,37.81 71.71,38.56C72.44,39.3 72.44,40.45 71.71,41.19L66.94,46.02ZM62.94,56.92C64.08,56.92 65,56.01 65,54.88C65,53.76 64.08,52.85 62.94,52.85C61.8,52.85 60.88,53.76 60.88,54.88C60.88,56.01 61.8,56.92 62.94,56.92ZM45.06,56.92C46.2,56.92 47.13,56.01 47.13,54.88C47.13,53.76 46.2,52.85 45.06,52.85C43.92,52.85 43,53.76 43,54.88C43,56.01 43.92,56.92 45.06,56.92Z"
android:strokeWidth="1"
android:strokeColor="#00000000" />
</vector>

BIN
data analysis/dep/2019/apps/android/source/app/src/main/res/drawable/binoculars_big.png
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data analysis/dep/2019/apps/android/source/app/src/main/res/drawable/binoculars_medium.png
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Width:  |  Height:  |  Size: 925 B

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data analysis/dep/2019/apps/android/source/app/src/main/res/drawable/binoculars_small.png
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Width:  |  Height:  |  Size: 1.6 KiB

170
data analysis/dep/2019/apps/android/source/app/src/main/res/drawable/ic_launcher_background.xml
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@ -1,170 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<vector xmlns:android="http://schemas.android.com/apk/res/android"
android:width="108dp"
android:height="108dp"
android:viewportWidth="108"
android:viewportHeight="108">
<path
android:fillColor="#008577"
android:pathData="M0,0h108v108h-108z" />
<path
android:fillColor="#00000000"
android:pathData="M9,0L9,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,0L19,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M29,0L29,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M39,0L39,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M49,0L49,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M59,0L59,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M69,0L69,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M79,0L79,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M89,0L89,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M99,0L99,108"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,9L108,9"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,19L108,19"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,29L108,29"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,39L108,39"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,49L108,49"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,59L108,59"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,69L108,69"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,79L108,79"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,89L108,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M0,99L108,99"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,29L89,29"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,39L89,39"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,49L89,49"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,59L89,59"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,69L89,69"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M19,79L89,79"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M29,19L29,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M39,19L39,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M49,19L49,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M59,19L59,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M69,19L69,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
<path
android:fillColor="#00000000"
android:pathData="M79,19L79,89"
android:strokeWidth="0.8"
android:strokeColor="#33FFFFFF" />
</vector>

42
data analysis/dep/2019/apps/android/source/app/src/main/res/layout/activity_launcher.xml
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@ -1,42 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context=".launcher">
<Button
android:id="@+id/launch_button"
android:layout_width="253dp"
android:layout_height="56dp"
android:layout_marginStart="8dp"
android:layout_marginLeft="8dp"
android:layout_marginTop="8dp"
android:layout_marginEnd="8dp"
android:layout_marginRight="8dp"
android:layout_marginBottom="8dp"
android:text="Launch Titan Scouting"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toTopOf="parent" />
<EditText
android:id="@+id/editText"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginStart="8dp"
android:layout_marginLeft="8dp"
android:layout_marginTop="8dp"
android:layout_marginEnd="8dp"
android:layout_marginRight="8dp"
android:layout_marginBottom="8dp"
android:ems="10"
android:inputType="textPassword"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toBottomOf="@+id/launch_button"
app:layout_constraintVertical_bias="0.0" />
</android.support.constraint.ConstraintLayout>

19
data analysis/dep/2019/apps/android/source/app/src/main/res/layout/activity_main.xml
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@ -1,19 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context=".MainActivity">
<WebView
android:id="@+id/webview"
android:layout_width="0dp"
android:layout_height="0dp"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toTopOf="parent"
app:layout_constraintVertical_bias="0.48000002" />
</android.support.constraint.ConstraintLayout>

36
data analysis/dep/2019/apps/android/source/app/src/main/res/layout/activity_tits.xml
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@ -1,36 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context=".tits">
<ImageView
android:id="@+id/imageView"
android:layout_width="372dp"
android:layout_height="487dp"
android:layout_marginTop="4dp"
android:layout_marginBottom="215dp"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toTopOf="parent"
app:srcCompat="@drawable/uuh" />
<Button
android:id="@+id/button"
android:layout_width="198dp"
android:layout_height="86dp"
android:layout_marginStart="8dp"
android:layout_marginLeft="8dp"
android:layout_marginTop="8dp"
android:layout_marginEnd="8dp"
android:layout_marginRight="8dp"
android:layout_marginBottom="8dp"
android:text="Fuck Get Me Out"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toBottomOf="@+id/imageView" />
</android.support.constraint.ConstraintLayout>

5
data analysis/dep/2019/apps/android/source/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml
View File

@ -1,5 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
<background android:drawable="@drawable/ic_launcher_background" />
<foreground android:drawable="@drawable/ic_launcher_foreground" />
</adaptive-icon>

5
data analysis/dep/2019/apps/android/source/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml
View File

@ -1,5 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
<background android:drawable="@drawable/ic_launcher_background" />
<foreground android:drawable="@drawable/ic_launcher_foreground" />
</adaptive-icon>

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6
data analysis/dep/2019/apps/android/source/app/src/main/res/values/colors.xml
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@ -1,6 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<resources>
<color name="colorPrimary">#008577</color>
<color name="colorPrimaryDark">#00574B</color>
<color name="colorAccent">#D81B60</color>
</resources>

3
data analysis/dep/2019/apps/android/source/app/src/main/res/values/strings.xml
View File

@ -1,3 +0,0 @@
<resources>
<string name="app_name">TitanScout</string>
</resources>

11
data analysis/dep/2019/apps/android/source/app/src/main/res/values/styles.xml
View File

@ -1,11 +0,0 @@
<resources>
<!-- Base application theme. -->
<style name="AppTheme" parent="Theme.AppCompat.Light.NoActionBar">
<!-- Customize your theme here. -->
<item name="colorPrimary">@color/colorPrimary</item>
<item name="colorPrimaryDark">@color/colorPrimaryDark</item>
<item name="colorAccent">@color/colorAccent</item>
</style>
</resources>

17
data analysis/dep/2019/apps/android/source/app/src/test/java/com/example/titanscouting/ExampleUnitTest.java
View File

@ -1,17 +0,0 @@
package com.example.titanscouting;
import org.junit.Test;
import static org.junit.Assert.*;
/**
* Example local unit test, which will execute on the development machine (host).
*
* @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
*/
public class ExampleUnitTest {
@Test
public void addition_isCorrect() {
assertEquals(4, 2 + 2);
}
}

27
data analysis/dep/2019/apps/android/source/build.gradle
View File

@ -1,27 +0,0 @@
// Top-level build file where you can add configuration options common to all sub-projects/modules.
buildscript {
repositories {
google()
jcenter()
}
dependencies {
classpath 'com.android.tools.build:gradle:3.3.0'
// NOTE: Do not place your application dependencies here; they belong
// in the individual module build.gradle files
}
}
allprojects {
repositories {
google()
jcenter()
}
}
task clean(type: Delete) {
delete rootProject.buildDir
}

15
data analysis/dep/2019/apps/android/source/gradle.properties
View File

@ -1,15 +0,0 @@
# Project-wide Gradle settings.
# IDE (e.g. Android Studio) users:
# Gradle settings configured through the IDE *will override*
# any settings specified in this file.
# For more details on how to configure your build environment visit
# http://www.gradle.org/docs/current/userguide/build_environment.html
# Specifies the JVM arguments used for the daemon process.
# The setting is particularly useful for tweaking memory settings.
org.gradle.jvmargs=-Xmx1536m
# When configured, Gradle will run in incubating parallel mode.
# This option should only be used with decoupled projects. More details, visit
# http://www.gradle.org/docs/current/userguide/multi_project_builds.html#sec:decoupled_projects
# org.gradle.parallel=true

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6
data analysis/dep/2019/apps/android/source/gradle/wrapper/gradle-wrapper.properties vendored
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@ -1,6 +0,0 @@
#Wed Feb 06 15:44:44 CST 2019
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-4.10.1-all.zip

172
data analysis/dep/2019/apps/android/source/gradlew vendored
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@ -1,172 +0,0 @@
#!/usr/bin/env sh
##############################################################################
##
## Gradle start up script for UN*X
##
##############################################################################
# Attempt to set APP_HOME
# Resolve links: $0 may be a link
PRG="$0"
# Need this for relative symlinks.
while [ -h "$PRG" ] ; do
ls=`ls -ld "$PRG"`
link=`expr "$ls" : '.*-> \(.*\)$'`
if expr "$link" : '/.*' > /dev/null; then
PRG="$link"
else
PRG=`dirname "$PRG"`"/$link"
fi
done
SAVED="`pwd`"
cd "`dirname \"$PRG\"`/" >/dev/null
APP_HOME="`pwd -P`"
cd "$SAVED" >/dev/null
APP_NAME="Gradle"
APP_BASE_NAME=`basename "$0"`
# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
DEFAULT_JVM_OPTS=""
# Use the maximum available, or set MAX_FD != -1 to use that value.
MAX_FD="maximum"
warn () {
echo "$*"
}
die () {
echo
echo "$*"
echo
exit 1
}
# OS specific support (must be 'true' or 'false').
cygwin=false
msys=false
darwin=false
nonstop=false
case "`uname`" in
CYGWIN* )
cygwin=true
;;
Darwin* )
darwin=true
;;
MINGW* )
msys=true
;;
NONSTOP* )
nonstop=true
;;
esac
CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
# Determine the Java command to use to start the JVM.
if [ -n "$JAVA_HOME" ] ; then
if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
else
JAVACMD="$JAVA_HOME/bin/java"
fi
if [ ! -x "$JAVACMD" ] ; then
die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
else
JAVACMD="java"
which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
# Increase the maximum file descriptors if we can.
if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
MAX_FD_LIMIT=`ulimit -H -n`
if [ $? -eq 0 ] ; then
if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
MAX_FD="$MAX_FD_LIMIT"
fi
ulimit -n $MAX_FD
if [ $? -ne 0 ] ; then
warn "Could not set maximum file descriptor limit: $MAX_FD"
fi
else
warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
fi
fi
# For Darwin, add options to specify how the application appears in the dock
if $darwin; then
GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
fi
# For Cygwin, switch paths to Windows format before running java
if $cygwin ; then
APP_HOME=`cygpath --path --mixed "$APP_HOME"`
CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
JAVACMD=`cygpath --unix "$JAVACMD"`
# We build the pattern for arguments to be converted via cygpath
ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
SEP=""
for dir in $ROOTDIRSRAW ; do
ROOTDIRS="$ROOTDIRS$SEP$dir"
SEP="|"
done
OURCYGPATTERN="(^($ROOTDIRS))"
# Add a user-defined pattern to the cygpath arguments
if [ "$GRADLE_CYGPATTERN" != "" ] ; then
OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
fi
# Now convert the arguments - kludge to limit ourselves to /bin/sh
i=0
for arg in "$@" ; do
CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
CHECK2=`echo "$arg"|egrep -c "^-"` ### Determine if an option
if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then ### Added a condition
eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
else
eval `echo args$i`="\"$arg\""
fi
i=$((i+1))
done
case $i in
(0) set -- ;;
(1) set -- "$args0" ;;
(2) set -- "$args0" "$args1" ;;
(3) set -- "$args0" "$args1" "$args2" ;;
(4) set -- "$args0" "$args1" "$args2" "$args3" ;;
(5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
(6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
(7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
(8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
(9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
esac
fi
# Escape application args
save () {
for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
echo " "
}
APP_ARGS=$(save "$@")
# Collect all arguments for the java command, following the shell quoting and substitution rules
eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
# by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
cd "$(dirname "$0")"
fi
exec "$JAVACMD" "$@"

84
data analysis/dep/2019/apps/android/source/gradlew.bat vendored
View File

@ -1,84 +0,0 @@
@if "%DEBUG%" == "" @echo off
@rem ##########################################################################
@rem
@rem Gradle startup script for Windows
@rem
@rem ##########################################################################
@rem Set local scope for the variables with windows NT shell
if "%OS%"=="Windows_NT" setlocal
set DIRNAME=%~dp0
if "%DIRNAME%" == "" set DIRNAME=.
set APP_BASE_NAME=%~n0
set APP_HOME=%DIRNAME%
@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
set DEFAULT_JVM_OPTS=
@rem Find java.exe
if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto init
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:findJavaFromJavaHome
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto init
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:init
@rem Get command-line arguments, handling Windows variants
if not "%OS%" == "Windows_NT" goto win9xME_args
:win9xME_args
@rem Slurp the command line arguments.
set CMD_LINE_ARGS=
set _SKIP=2
:win9xME_args_slurp
if "x%~1" == "x" goto execute
set CMD_LINE_ARGS=%*
:execute
@rem Setup the command line
set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
:end
@rem End local scope for the variables with windows NT shell
if "%ERRORLEVEL%"=="0" goto mainEnd
:fail
rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
rem the _cmd.exe /c_ return code!
if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
exit /b 1
:mainEnd
if "%OS%"=="Windows_NT" endlocal
:omega

1
data analysis/dep/2019/apps/android/source/settings.gradle
View File

@ -1 +0,0 @@
include ':app'

6
data analysis/dep/2019/data/.ipynb_checkpoints/Untitled-checkpoint.ipynb
View File

@ -1,6 +0,0 @@
{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 2
}

6
data analysis/dep/2019/data/.ipynb_checkpoints/scores-checkpoint.csv
View File

@ -1,6 +0,0 @@
2,3
6,5
5,5
5,8
6,6
6,8
1 2 3
2 6 5
3 5 5
4 5 8
5 6 6
6 6 8

53
data analysis/dep/2019/data/.ipynb_checkpoints/teams-checkpoint.csv
View File

@ -1,53 +0,0 @@
4,6,4,5
3,4,8,8
2,8,3,0
5,8,4,7
4,0,9,6
2,0,1,6
5,3,5,0
2,0,2,2
4,8
6,6,5,1
2,1,5,1
2,0,3,9
2,2,5,2
1,1,1
6,8,2,3
2,1,3,6
4,2,9,2
5,8,2,2
7,6,0,8
2,3,5,8
4,2,4,1
3,1,1,0
7,6,0,9
5,1,2,5
6,9,0,6
9,3,0
2,0,6,2
3,0,6,7
4,7,8,7
2,7,0,9
7,5,6,0
5,9,3,4
4,7,0,2
5,1,4,8
1,6
4,1,5,6
1,8,8,4
1,6,7,5
1,7,9,7
2,4,5,1
7,7,3,8
1,0,1
1,7,3,9
3,7,3,4
1,7,3,6
3,0,6,1
2,7,2,5
7,2,3,7
3,6,9,5
6,9,6,8
1,7,8,1
4,2,9,6
2,3,3,8
1 4,6,4,5
2 3,4,8,8
3 2,8,3,0
4 5,8,4,7
5 4,0,9,6
6 2,0,1,6
7 5,3,5,0
8 2,0,2,2
9 4,8
10 6,6,5,1
11 2,1,5,1
12 2,0,3,9
13 2,2,5,2
14 1,1,1
15 6,8,2,3
16 2,1,3,6
17 4,2,9,2
18 5,8,2,2
19 7,6,0,8
20 2,3,5,8
21 4,2,4,1
22 3,1,1,0
23 7,6,0,9
24 5,1,2,5
25 6,9,0,6
26 9,3,0
27 2,0,6,2
28 3,0,6,7
29 4,7,8,7
30 2,7,0,9
31 7,5,6,0
32 5,9,3,4
33 4,7,0,2
34 5,1,4,8
35 1,6
36 4,1,5,6
37 1,8,8,4
38 1,6,7,5
39 1,7,9,7
40 2,4,5,1
41 7,7,3,8
42 1,0,1
43 1,7,3,9
44 3,7,3,4
45 1,7,3,6
46 3,0,6,1
47 2,7,2,5
48 7,2,3,7
49 3,6,9,5
50 6,9,6,8
51 1,7,8,1
52 4,2,9,6
53 2,3,3,8

6
data analysis/dep/2019/data/SandstormCargoShipBalls.csv
View File

@ -1,6 +0,0 @@
0.0,1.0
2.0
0.0
0.0
0.0
0.0
1 0.0,1.0
2 2.0
3 0.0
4 0.0
5 0.0
6 0.0

6
data analysis/dep/2019/data/SandstormCargoShipHatches.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
5.0
1.0
0.0
5.0
0.0
1 0.0,0.0
2 5.0
3 1.0
4 0.0
5 5.0
6 0.0

6
data analysis/dep/2019/data/SandstormLowerRocketBalls.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
2.0
0.0
0.0
0.0
0.0
1 0.0,0.0
2 2.0
3 0.0
4 0.0
5 0.0
6 0.0

6
data analysis/dep/2019/data/SandstormLowerRocketHatches.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
1.0
1.0
0.0
2.0
0.0
1 0.0,0.0
2 1.0
3 1.0
4 0.0
5 2.0
6 0.0

6
data analysis/dep/2019/data/SandstormUpperRocketBalls.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
2.0
0.0
0.0
0.0
0.0
1 0.0,0.0
2 2.0
3 0.0
4 0.0
5 0.0
6 0.0

6
data analysis/dep/2019/data/SandstormUpperRocketHatches.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
3.0
0.0
0.0
3.0
0.0
1 0.0,0.0
2 3.0
3 0.0
4 0.0
5 3.0
6 0.0

6
data analysis/dep/2019/data/TeleopCargoShipBalls.csv
View File

@ -1,6 +0,0 @@
0.0,5.0
0.0
0.0
0.0
4.0
0.0
1 0.0,5.0
2 0.0
3 0.0
4 0.0
5 4.0
6 0.0

6
data analysis/dep/2019/data/TeleopCargoShipHatches.csv
View File

@ -1,6 +0,0 @@
0.0,1.0
0.0
0.0
1.0
0.0
1.0
1 0.0,1.0
2 0.0
3 0.0
4 1.0
5 0.0
6 1.0

6
data analysis/dep/2019/data/TeleopLowerRocketBalls.csv
View File

@ -1,6 +0,0 @@
0.0,4.0
0.0
0.0
0.0
0.0
0.0
1 0.0,4.0
2 0.0
3 0.0
4 0.0
5 0.0
6 0.0

6
data analysis/dep/2019/data/TeleopLowerRocketHatches.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
0.0
0.0
0.0
2.0
1.0
1 0.0,0.0
2 0.0
3 0.0
4 0.0
5 2.0
6 1.0

6
data analysis/dep/2019/data/TeleopUpperRocketBalls.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
0.0
0.0
0.0
0.0
0.0
1 0.0,0.0
2 0.0
3 0.0
4 0.0
5 0.0
6 0.0

6
data analysis/dep/2019/data/TeleopUpperRocketHatches.csv
View File

@ -1,6 +0,0 @@
0.0,0.0
0.0
13.0
0.0
1.0
0.0
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4 0.0
5 1.0
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6
data analysis/dep/2019/data/cargoBalls.csv
View File

@ -1,6 +0,0 @@
0.0,7.0
0.0
10.0
7.0
8.0
0.0
1 0.0,7.0
2 0.0
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5 8.0
6 0.0

6
data analysis/dep/2019/data/hatchPanels.csv
View File

@ -1,6 +0,0 @@
0.0,7.0
0.0
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0.0
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6
data analysis/dep/2019/data/match.csv
View File

@ -1,6 +0,0 @@
match-18,match-3
match-5
match-23
match-18
match-5
match-1
1 match-18,match-3
2 match-5
3 match-23
4 match-18
5 match-5
6 match-1

6
data analysis/dep/2019/data/notes.csv
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@ -1,6 +0,0 @@
,si papa
""
yeeee
nine
""
""
1 ,si papa
2
3 yeeee
4 nine
5
6

6
data analysis/dep/2019/data/observationType.csv
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@ -1,6 +0,0 @@
Quantitative,Quantitative
Quantitative
Quantitative
Quantitative
Quantitative
Quantitative
1 Quantitative,Quantitative
2 Quantitative
3 Quantitative
4 Quantitative
5 Quantitative
6 Quantitative

36
data analysis/dep/2019/data/scores.csv
View File

@ -1,36 +0,0 @@
23,57,61,28,62,31,58,42,47,61,52,54,50,68,54,44,53,26,28,68
35,58,61,39,51,51,42,31,33,70,47,55,44,55,62,43,69,69,65,51,46,68,60,78,96,58,63
14,6,9,54,48,36,59,46,30,17,68,38,35,39,48,33,43,68,60,51,53,51,67,59
46,71,40,52,68,57,60,57,60,60,65,79,55,54,47,75,80,72,45,59,64,67,57,63,77,71,72,72,77
65,43,74,59,68,59,75,62,67,55,60,79,86,67,66,77,71,75,68,67,65,41,75,68,86,92,74,64,65,29,60,78,96,58,63
56,44,26,50,49,41,33,40,45,44,39,53,74,63,65,70,71,52,71,54,75,52,61,46,53,53,51,48,55,67,46,58
15,49,53,18,53,45,20,55,36,54,49,53,64,71,82,78,67,60,67,52,52,52,57,55,64,86,71,59,79,84,52,71,85,84,66,63,64
27,16,41,64,48,21,65,61,46,68,46,72,67,61,51,52,65,55,75,54,60,56,75,55,70,55,63,77,71,72,72,77
33,51,63,85,39,59,44,45,34,89,55,34,46,47,74,54,57,52,80,42,92,60,45,81,64,63,77,71,72,72,77
42,56,53,50,37,39,52,59,38,43,56,38,42,53,52,67,52,47,45,57,69,51,63,64,48,30,58,48
21,22,59,27,33,32,14,36,53,42,58,58,67,48,43,38,62,61,42,60,59,26,70,30,46,50
10,54,36,44,40,63,41,31,46,79,40,43,55,55,65,52,74,46,48,41,81,70,70,64
50,45,49,19,55,35,15,33,68,36,48,49,66,61,69,44,60,55,46,49,58,48
26,62,45,37,42,29,59,44,40,47,67,42,64,63,54,60,88,76,80,86,78,78,76,79,69,66,57,57,43,60,60,63,64,70,64,63,76
14,12,61,24,53,39,32,15,44,47,67,48,38,41,57,52,52,53,61,46,52
47,53,34,48,42,61,34,51,34,45,50,56,46,59,54,47,53,43,62,40,80,66,94,58,64,71,82,78,67,60,67,67,58,65,75,66,74,92,65,79,55,83,60,78,96,58,63
42,55,36,34,56,46,26,35,52,70,51,71,54,33,46,57,49,71,60,46,70,30
50,17,66,53,32,60,32,39,53,68,39,43,61,41,64,49,69,52,45,28,64
36,45,44,49,49,37,49,36,46,53,36,66,61,76,80,74,53,60,61,84,68,71,85,84,66,63,64
53,48,48,41,43,54,46,49,65,46,28,57
32,45,61,52,34,47,59,62,48,57,71,49,79,50,48,51,55,54,42,55,47,76,43,65,55,104,57,85,55,75,48,44,49,50,72,71,75,55,81,83,81,70,70,64
10,44,49,20,45,32,38,41,35,69,65,69,46,57,65,53,65,64,70,83,46,50
58,41,38,64,61,39,42,40,54,66,69,63,34,47,74,65,47,43,61,52,56,62,79,63,64,46,50
42,37,62,38,51,44,41,70,41,28,32,61,54,61,66,57,60,52,75,51,65,57
35,71,43,39,76,52,45,63,55,65,41,67,46,58
19,55,58,42,22,34,44,45,43,33,45,75,39,48,39,57,61,86,46,62,64,55,64,58,48
26,31,41,26,69,34,12,25,67,52,44,69,45,61,60,45,53,61,70,49
39,45,49,44,48,49,37,39,75,40,43,41,46,64,42,44,53,64,46,55,71,85,84,66,63,64
55,45,48,19,53,32,59,56,58,79,50,52,58,45,54,76,60,60,52,64,67,64,67,46,58
33,68,12,18,49,36,39,35,49,35,21,38,51,55,48,38,57,54,49,52,51,81,29
47,51,64,50,102,40,47,31,57,15,54,50,56,64,51,37,62,60,77,62,44,52,52,72,67,52,61,43,75,62,47,72,49,62,64,84,49,81,70,70,64
53,40,45,69,50,43,49,56,60,51,55,59
9,55,26,45,33,18,52,30,53,42,58,58,52,36,65,39,55,57,54,69,65,55,63,59,63,76
32,69,45,49,52,54,74,46,74,26,63,52,63,76
47,58,66,33,45,47,46,46,65,45,46,41
32,74,54,54,41,47,65,51,60,55,46,29
1 23,57,61,28,62,31,58,42,47,61,52,54,50,68,54,44,53,26,28,68
2 35,58,61,39,51,51,42,31,33,70,47,55,44,55,62,43,69,69,65,51,46,68,60,78,96,58,63
3 14,6,9,54,48,36,59,46,30,17,68,38,35,39,48,33,43,68,60,51,53,51,67,59
4 46,71,40,52,68,57,60,57,60,60,65,79,55,54,47,75,80,72,45,59,64,67,57,63,77,71,72,72,77
5 65,43,74,59,68,59,75,62,67,55,60,79,86,67,66,77,71,75,68,67,65,41,75,68,86,92,74,64,65,29,60,78,96,58,63
6 56,44,26,50,49,41,33,40,45,44,39,53,74,63,65,70,71,52,71,54,75,52,61,46,53,53,51,48,55,67,46,58
7 15,49,53,18,53,45,20,55,36,54,49,53,64,71,82,78,67,60,67,52,52,52,57,55,64,86,71,59,79,84,52,71,85,84,66,63,64
8 27,16,41,64,48,21,65,61,46,68,46,72,67,61,51,52,65,55,75,54,60,56,75,55,70,55,63,77,71,72,72,77
9 33,51,63,85,39,59,44,45,34,89,55,34,46,47,74,54,57,52,80,42,92,60,45,81,64,63,77,71,72,72,77
10 42,56,53,50,37,39,52,59,38,43,56,38,42,53,52,67,52,47,45,57,69,51,63,64,48,30,58,48
11 21,22,59,27,33,32,14,36,53,42,58,58,67,48,43,38,62,61,42,60,59,26,70,30,46,50
12 10,54,36,44,40,63,41,31,46,79,40,43,55,55,65,52,74,46,48,41,81,70,70,64
13 50,45,49,19,55,35,15,33,68,36,48,49,66,61,69,44,60,55,46,49,58,48
14 26,62,45,37,42,29,59,44,40,47,67,42,64,63,54,60,88,76,80,86,78,78,76,79,69,66,57,57,43,60,60,63,64,70,64,63,76
15 14,12,61,24,53,39,32,15,44,47,67,48,38,41,57,52,52,53,61,46,52
16 47,53,34,48,42,61,34,51,34,45,50,56,46,59,54,47,53,43,62,40,80,66,94,58,64,71,82,78,67,60,67,67,58,65,75,66,74,92,65,79,55,83,60,78,96,58,63
17 42,55,36,34,56,46,26,35,52,70,51,71,54,33,46,57,49,71,60,46,70,30
18 50,17,66,53,32,60,32,39,53,68,39,43,61,41,64,49,69,52,45,28,64
19 36,45,44,49,49,37,49,36,46,53,36,66,61,76,80,74,53,60,61,84,68,71,85,84,66,63,64
20 53,48,48,41,43,54,46,49,65,46,28,57
21 32,45,61,52,34,47,59,62,48,57,71,49,79,50,48,51,55,54,42,55,47,76,43,65,55,104,57,85,55,75,48,44,49,50,72,71,75,55,81,83,81,70,70,64
22 10,44,49,20,45,32,38,41,35,69,65,69,46,57,65,53,65,64,70,83,46,50
23 58,41,38,64,61,39,42,40,54,66,69,63,34,47,74,65,47,43,61,52,56,62,79,63,64,46,50
24 42,37,62,38,51,44,41,70,41,28,32,61,54,61,66,57,60,52,75,51,65,57
25 35,71,43,39,76,52,45,63,55,65,41,67,46,58
26 19,55,58,42,22,34,44,45,43,33,45,75,39,48,39,57,61,86,46,62,64,55,64,58,48
27 26,31,41,26,69,34,12,25,67,52,44,69,45,61,60,45,53,61,70,49
28 39,45,49,44,48,49,37,39,75,40,43,41,46,64,42,44,53,64,46,55,71,85,84,66,63,64
29 55,45,48,19,53,32,59,56,58,79,50,52,58,45,54,76,60,60,52,64,67,64,67,46,58
30 33,68,12,18,49,36,39,35,49,35,21,38,51,55,48,38,57,54,49,52,51,81,29
31 47,51,64,50,102,40,47,31,57,15,54,50,56,64,51,37,62,60,77,62,44,52,52,72,67,52,61,43,75,62,47,72,49,62,64,84,49,81,70,70,64
32 53,40,45,69,50,43,49,56,60,51,55,59
33 9,55,26,45,33,18,52,30,53,42,58,58,52,36,65,39,55,57,54,69,65,55,63,59,63,76
34 32,69,45,49,52,54,74,46,74,26,63,52,63,76
35 47,58,66,33,45,47,46,46,65,45,46,41
36 32,74,54,54,41,47,65,51,60,55,46,29

6
data analysis/dep/2019/data/teamDBRef.csv
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@ -1,6 +0,0 @@
team-16,team-16
team-2016
team-2022
team-2451
team-3695
team-5148
1 team-16,team-16
2 team-2016
3 team-2022
4 team-2451
5 team-3695
6 team-5148

36
data analysis/dep/2019/data/teams.csv
View File

@ -1,36 +0,0 @@
31
931
938
1094
1756
1785
1806
1939
1987
1997
2164
2333
2359
2451
2773
3284
3397
3593
3931
4455
4522
4959
5006
5041
5119
5437
5454
5550
5889
5918
6424
6843
6886
7141
7662
7729
1 31
2 931
3 938
4 1094
5 1756
6 1785
7 1806
8 1939
9 1987
10 1997
11 2164
12 2333
13 2359
14 2451
15 2773
16 3284
17 3397
18 3593
19 3931
20 4455
21 4522
22 4959
23 5006
24 5041
25 5119
26 5437
27 5454
28 5550
29 5889
30 5918
31 6424
32 6843
33 6886
34 7141
35 7662
36 7729

178
data analysis/dep/2019/documentation/analysis.docs
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@ -1,178 +0,0 @@
Doccumentation of python module: analysis.py
revision version: 1.0.8.003
analysis.py{
analysis.py should be imported as a python module using "import analysis" in the tr2022 directory, or using "from tr2022 import analysis" if tr2022 modules are installed in the python Libs directory
analysis.py is a module designed for statistical analyses and artifician neural network analyses
functions{
_init_device{
initiates device for tensor flow with either a cuda device (device specified via the "arg" argument) or cpu (ignored "arg" argument)
usage{
analysis._init_device("cuda", arg) , where arg is the cuda device number
analysis._init_device("cpu", 0) , which initiates the cpu as the tensorflow device
}
}
load_csv{
loads a csv file as a 2 dimentional array
usage{
analysis.load_csv(filepath) , where filepath is the path to the csv file to be loaded
}
}
basic_stats{
performs basic stats such as mean, median, mode, standard deviation, and varaince on a set of data
the function can do stats on a 1 dimentional array, or on a specified row or column in a 2 dimentional array
the method in which it does the statistics is specified by the "method" argument
usage{
analysis.basic_stats(data, "1d", 0) , where data is a 1 dimentional array
analysis.basic_stats(data, "row", rownum) , where data is a 2 dimentional array and "rownum" is the row to run statistics on
analysis.basic_stats(data, "column", columnnum) , where data is a 2 dimentional array and "columnnum" is the column to run statistics on
}
}
z_score{
returns the z score of a point relative to the population mean and standard deviation
usage{
analysis.z_score(datapoint, mean, stdev) , where "datapoint" is the specific data point to assign a z score, mean is the mean of the entire data set, and stdev is the standard deviation of the data set
}
}
z_normalize{
used in other functions, not important
}
stdev_z_split{
used in other functions, not important
}
histo_analysis{
returns an analysis of historical data, the analysis predicts a range of possible next data poins given historical data
usage{
analysis.histo_analysis(data, delta, low, high) , where data is the historical data to be predicted, delta are the steps (in standard deviations) that the predictor uses, and the low and high bounds are the ranges of standard deviations that the function predicts within
}
}
poly_regression{
used in other functions, not important
}
log_regression{
used in other functions, not important
}
exp_regression{
used in other functions, not important
}
tanh_regression{
used in other functions, not important
}
r_squared{
used in other functions
returns the r^2 score of a curve and corresponding data
}
rms{
used in other functions
returns the root mean squared score of a curve and corresponding data
}
calc_overfit{
used in other functions, not important
}
optimize_regression{
returns a list of possible regressions given the x and y coordinates of the data
usage{
analysis.optimize_regression(x, y, range, resolution) , where x and y are the x and y values of each data point, range is the range of polynomial equations tried, and resolution is the detail of bases used for exponential and logorithmic regressions
}
}
select_best_regression{
takes a list of equations and returns the best equation, either based on minimizing overfit or based on maximizing root mean squareds
}
p_value{
returns the p value of two data sets
}
basic_analysis{
runs every stat on a given file
}
}
}

0
data analysis/dep/2019/documentation/visualizer.docs
View File

12
data analysis/dep/2019/keys/firebasekey.json
View File

@ -1,12 +0,0 @@
{
"type": "service_account",
"project_id": "titanscoutandroid",
"private_key_id": "e7cde706a13a6fade555cce2bc46ee53f05a0b11",
"private_key": "-----BEGIN PRIVATE KEY-----\(gottem)/B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\nvJCSRvjRtxyFafuX4YQzWu0=\n-----END PRIVATE KEY-----\n",
"client_email": "firebase-adminsdk-wpsvx@titanscoutandroid.iam.gserviceaccount.com",
"client_id": "114864465329268712237",
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://oauth2.googleapis.com/token",
"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
"client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-wpsvx%40titanscoutandroid.iam.gserviceaccount.com"
}

132
data analysis/dep/2019/matches/.ipynb_checkpoints/Untitled-checkpoint.ipynb
View File

@ -1,132 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import firebase_admin\n",
"from firebase_admin import credentials\n",
"from firebase_admin import firestore\n",
"import csv\n",
"import numpy as np\n",
"# Use a service account\n",
"cred = credentials.Certificate(r'../keys/fsk.json')\n",
"#add your own key as this is public. email me for details\n",
"firebase_admin.initialize_app(cred)\n",
"\n",
"db = firestore.client()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"teams=db.collection('data').document('team-2022').collection(\"Midwest 2019\").get()\n",
"full=[]\n",
"tms=[]\n",
"for team in teams:\n",
" data=[]\n",
" tms.append(team.id)\n",
" reports=db.collection('data').document('team-2022').collection(\"Midwest 2019\").document(team.id).collection(\"matches\").get()\n",
" for report in reports:\n",
" data.append(db.collection('data').document('team-2022').collection(\"Midwest 2019\").document(team.id).collection(\"matches\").document(report.id).get().to_dict())\n",
" full.append(data)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def expcsv(loc,data):\n",
" with open(loc+'.csv', 'w', newline='', encoding='utf-8') as csvfile:\n",
" w = csv.writer(csvfile, delimiter=',', quotechar=\"\\\"\", quoting=csv.QUOTE_MINIMAL)\n",
" for i in data:\n",
" w.writerow(i)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def keymatch(ld):\n",
" keys=set([])\n",
" for i in ld:\n",
" for j in i.keys():\n",
" keys.add(j)\n",
" kl=list(keys)\n",
" data=[]\n",
" for i in kl:\n",
" data.append([i])\n",
" for i in kl:\n",
" for j in ld:\n",
" try:\n",
" (data[kl.index(i)]).append(j[i])\n",
" except:\n",
" (data[kl.index(i)]).append(\"\")\n",
" return data\n",
"wn=[]\n",
"for i in full:\n",
" wn.append(np.transpose(np.array(keymatch(i))).tolist())\n",
"for i in range(len(wn)):\n",
" expcsv(tms[i],wn[i])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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
}

191
data analysis/dep/2019/matches/.ipynb_checkpoints/frc-elo-checkpoint.ipynb
View File

@ -1,191 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import operator\n",
"import csv\n",
"#constants\n",
"k=100\n",
"rdf=400\n",
"\n",
"def win_prob(yas,oas):\n",
" return 1/(1+10**(1/rdf*(oas-yas)))\n",
"def new_score(oscore,yas,oas,outcome):\n",
" return (oscore)+k*(outcome-win_prob(yas,oas))\n",
"\n",
"def readFile(filepath):\n",
"\n",
" with open(filepath) as csvfile:\n",
" lines = csv.reader(csvfile, delimiter=',', quotechar='|')\n",
" data = []\n",
" try:\n",
" for row in lines:\n",
" data.append((', '.join(row)).split(\", \"))\n",
" except:\n",
" pass\n",
"\n",
" return data\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"sb=readFile('scoreboard.csv')\n",
"teams=set([])\n",
"for i in sb:\n",
" teams.add(i[2])\n",
" teams.add(i[3])\n",
" teams.add(i[4])\n",
" teams.add(i[5])\n",
" teams.add(i[6])\n",
" teams.add(i[7])\n",
"list(teams)\n",
"tsd={}\n",
"for i in list(teams):\n",
" tsd[i]=500\n",
"for i in sb:\n",
" ras=tsd[i[2]]+tsd[i[3]]+tsd[i[4]]\n",
" bas=tsd[i[5]]+tsd[i[6]]+tsd[i[7]]\n",
" outcome=0\n",
" if i[8]>i[9]:\n",
" outcome=1\n",
" elif i[9]==i[8]:\n",
" outcome=.5\n",
" for j in range(2,5,1):\n",
" tsd[i[j]]=new_score(tsd[i[j]],ras,bas,outcome)\n",
" for j in range(5,8,1):\n",
" tsd[i[j]]=new_score(tsd[i[j]],bas,ras,1-outcome)\n",
" \n",
"rankinfs = sorted(tsd.items(), key=operator.itemgetter(1), reverse=True) "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[('5934', 833.1830859510761),\n",
" ('48', 739.9728094005745),\n",
" ('16', 705.9551102513088),\n",
" ('3061', 702.9024075826381),\n",
" ('3695', 700.1366129603175),\n",
" ('2338', 696.932652524603),\n",
" ('4096', 652.7038522070818),\n",
" ('3488', 648.9766694246662),\n",
" ('4156', 638.0881039843185),\n",
" ('101', 626.9019952260375),\n",
" ('6823', 613.1453027540894),\n",
" ('930', 610.7992869961017),\n",
" ('2062', 608.0647276785079),\n",
" ('2830', 600.0239706519325),\n",
" ('5847', 589.0350788865741),\n",
" ('1736', 584.367394696335),\n",
" ('2358', 577.5524744241919),\n",
" ('5822', 575.4792058357157),\n",
" ('1675', 569.9944280943398),\n",
" ('111', 559.5150813478114),\n",
" ('1797', 537.9429025884093),\n",
" ('5148', 533.9623603303631),\n",
" ('1781', 519.5609268991466),\n",
" ('6651', 516.3195829730869),\n",
" ('6906', 501.7408783344565),\n",
" ('2022', 482.2765218696747),\n",
" ('7237', 474.4616019824547),\n",
" ('1884', 468.87487164611116),\n",
" ('2039', 467.0990375388428),\n",
" ('2451', 462.70812165138807),\n",
" ('7608', 462.0188420364676),\n",
" ('1739', 459.00590084129664),\n",
" ('2252', 456.43201385653043),\n",
" ('2151', 439.4118535382677),\n",
" ('4702', 435.5729578944645),\n",
" ('7738', 423.16353418538296),\n",
" ('4296', 420.5085609998351),\n",
" ('3734', 418.47615429198186),\n",
" ('7609', 409.29347746836567),\n",
" ('2709', 403.9793052336144),\n",
" ('3067', 402.77020998279653),\n",
" ('2136', 386.0798688817299),\n",
" ('5350', 383.4109800245315),\n",
" ('5125', 377.1609505922246),\n",
" ('4292', 357.43188113820975),\n",
" ('3110', 344.8643460008074),\n",
" ('2725', 332.21429556184444),\n",
" ('4645', 329.6452389079341),\n",
" ('6968', 329.08368400289095),\n",
" ('4241', 315.12115012426335),\n",
" ('4787', 288.64374620808815),\n",
" ('7560', 279.7779164676232),\n",
" ('2016', 247.25607506869346)]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rankinfs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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
}

0
data analysis/dep/2019/matches/.ipynb_checkpoints/pullmatches-checkpoint.py
View File

57
data analysis/dep/2019/matches/.ipynb_checkpoints/scoreboard-checkpoint.csv
View File

@ -1,57 +0,0 @@
Match,Time,Red1,Red2,Red3,Blue1,Blue2,Blue3,RedScore,BlueScore
Qualification 1  ,Fri 3/8 - 9:00 AM,7560,3061,3488,1675,2451,5148,37,26
Qualification 2  ,Fri 3/8 - 9:09 AM,7608,1884,2338,4702,2151,111,23,33
Qualification 3  ,Fri 3/8 - 9:18 AM,2830,7609,101,2039,4292,16,45,35
Qualification 4  ,Fri 3/8 - 9:27 AM,6968,1736,4096,4645,3067,2252,40,20
Qualification 5  ,Fri 3/8 - 9:36 AM,4156,2016,3695,2022,3110,3734,46,29
Qualification 6  ,Fri 3/8 - 9:45 AM,5934,5822,1739,7738,2062,4296,38,33
Qualification 7  ,Fri 3/8 - 9:54 AM,930,5125,4787,7237,6906,1781,37,41
Qualification 8  ,Fri 3/8 - 10:03 AM,2725,5847,5350,2709,1797,4241,25,24
Qualification 9  ,Fri 3/8 - 10:12 AM,2358,6823,2136,48,6651,3734,17,40
Qualification 10  ,Fri 3/8 - 10:21 AM,3067,7608,5148,2062,4292,5822,15,39
Qualification 11  ,Fri 3/8 - 10:30 AM,111,6968,4787,16,2022,1675,41,63
Qualification 12  ,Fri 3/8 - 10:39 AM,4702,7738,2830,6906,2725,2016,52,24
Qualification 13  ,Fri 3/8 - 10:48 AM,2709,2358,7609,101,930,6823,16,42
Qualification 14  ,Fri 3/8 - 10:56 AM,2136,5934,3695,1736,7237,2151,45,25
Qualification 15  ,Fri 3/8 - 11:04 AM,3110,1781,2252,1797,2338,3488,35,65
Qualification 16  ,Fri 3/8 - 11:12 AM,48,4156,4241,4296,1884,3061,48,34
Qualification 17  ,Fri 3/8 - 11:20 AM,2039,6651,5125,4096,7560,5350,31,23
Qualification 18  ,Fri 3/8 - 11:28 AM,5847,2451,16,4645,1739,7237,62,15
Qualification 19  ,Fri 3/8 - 11:36 AM,3734,3067,1797,7609,5148,5934,18,31
Qualification 20  ,Fri 3/8 - 11:44 AM,5822,2725,4241,2338,4156,930,20,55
Qualification 21  ,Fri 3/8 - 11:52 AM,6968,2016,2709,7608,2151,6823,12,14
Qualification 22,Fri 3/8 - 1:00 PM,1736,7560,1739,4292,5350,48,43,58
Qualification 23,Fri 3/8 - 1:09 PM,2062,1781,2022,2451,4096,6651,35,45
Qualification 24,Fri 3/8 - 1:18 PM,111,4296,3488,4787,2136,2039,49,27
Qualification 25,Fri 3/8 - 1:27 PM,101,3061,5847,2252,2830,6906,53,40
Qualification 26,Fri 3/8 - 1:36 PM,1675,4645,4702,3695,3110,7738,15,71
Qualification 27,Fri 3/8 - 1:44 PM,1736,1884,2358,2016,5125,7560,25,23
Qualification 28,Fri 3/8 - 1:52 PM,4156,2725,6651,3488,7237,3067,42,39
Qualification 29,Fri 3/8 - 2:00 PM,3734,5350,2151,6906,2062,101,18,36
Qualification 30,Fri 3/8 - 2:08 PM,5847,7738,6823,2338,111,4096,54,58
Qualification 31,Fri 3/8 - 2:16 PM,2709,48,4702,5934,2039,2252,20,49
Qualification 32,Fri 3/8 - 2:24 PM,1884,930,2830,1797,1675,6968,61,49
Qualification 33,Fri 3/8 - 2:32 PM,7609,1739,3695,5148,4241,4787,85,54
Qualification 34,Fri 3/8 - 2:40 PM,5125,4645,2022,3061,2136,4292,37,39
Qualification 35,Fri 3/8 - 2:48 PM,2451,2358,7608,4296,16,3110,37,18
Qualification 36,Fri 3/8 - 2:56 PM,1781,2039,3734,5822,7237,5847,30,61
Qualification 37,Fri 3/8 - 3:04 PM,3488,5350,930,1884,3695,111,52,54
Qualification 38,Fri 3/8 - 3:12 PM,2016,5934,2338,7609,7560,4156,66,24
Qualification 39,Fri 3/8 - 3:20 PM,2252,6651,2136,4787,7608,1739,27,23
Qualification 40,Fri 3/8 - 3:28 PM,4096,4702,5148,2358,4241,101,37,28
Qualification 41,Fri 3/8 - 3:36 PM,3110,5822,2451,48,6968,6906,42,68
Qualification 42,Fri 3/8 - 3:44 PM,16,1736,1781,7738,3061,2725,56,43
Qualification 43,Fri 3/8 - 3:52 PM,1797,5125,4292,6823,2709,2062,32,42
Qualification 44,Fri 3/8 - 4:00 PM,2022,4296,3067,2151,2830,1675,26,31
Qualification 45,Fri 3/8 - 4:08 PM,4645,48,5847,5148,3488,2016,63,48
Qualification 46,Fri 3/8 - 4:16 PM,3110,4096,930,3061,4787,5934,42,56
Qualification 47,Fri 3/8 - 4:24 PM,2725,6823,2451,7608,3695,2039,29,57
Qualification 48,Fri 3/8 - 4:32 PM,2062,1675,4156,101,4702,2136,40,31
Qualification 49,Fri 3/8 - 4:40 PM,2022,7738,7237,5350,2252,7609,51,37
Qualification 50,Fri 3/8 - 4:48 PM,7560,4296,2151,1781,1797,4645,21,39
Qualification 51,Fri 3/8 - 4:56 PM,2338,1736,5822,2830,2709,6651,68,37
Qualification 52,Fri 3/8 - 5:04 PM,6906,1739,2358,4292,6968,1884,33,29
Qualification 53,Fri 3/8 - 5:12 PM,111,16,3067,4241,3734,5125,65,41
Qualification 54,Fri 3/8 - 5:20 PM,3061,1675,48,7609,5847,7608,65,42
Qualification 55,Fri 3/8 - 5:28 PM,6651,2016,2062,930,2252,4296,43,77
Qualification 56,Fri 3/8 - 5:36 PM,4292,5148,2725,2151,4787,3110,19,3
1 Match Time Red1 Red2 Red3 Blue1 Blue2 Blue3 RedScore BlueScore
2 Qualification 1   Fri 3/8 - 9:00 AM 7560 3061 3488 1675 2451 5148 37 26
3 Qualification 2   Fri 3/8 - 9:09 AM 7608 1884 2338 4702 2151 111 23 33
4 Qualification 3   Fri 3/8 - 9:18 AM 2830 7609 101 2039 4292 16 45 35
5 Qualification 4   Fri 3/8 - 9:27 AM 6968 1736 4096 4645 3067 2252 40 20
6 Qualification 5   Fri 3/8 - 9:36 AM 4156 2016 3695 2022 3110 3734 46 29
7 Qualification 6   Fri 3/8 - 9:45 AM 5934 5822 1739 7738 2062 4296 38 33
8 Qualification 7   Fri 3/8 - 9:54 AM 930 5125 4787 7237 6906 1781 37 41
9 Qualification 8   Fri 3/8 - 10:03 AM 2725 5847 5350 2709 1797 4241 25 24
10 Qualification 9   Fri 3/8 - 10:12 AM 2358 6823 2136 48 6651 3734 17 40
11 Qualification 10   Fri 3/8 - 10:21 AM 3067 7608 5148 2062 4292 5822 15 39
12 Qualification 11   Fri 3/8 - 10:30 AM 111 6968 4787 16 2022 1675 41 63
13 Qualification 12   Fri 3/8 - 10:39 AM 4702 7738 2830 6906 2725 2016 52 24
14 Qualification 13   Fri 3/8 - 10:48 AM 2709 2358 7609 101 930 6823 16 42
15 Qualification 14   Fri 3/8 - 10:56 AM 2136 5934 3695 1736 7237 2151 45 25
16 Qualification 15   Fri 3/8 - 11:04 AM 3110 1781 2252 1797 2338 3488 35 65
17 Qualification 16   Fri 3/8 - 11:12 AM 48 4156 4241 4296 1884 3061 48 34
18 Qualification 17   Fri 3/8 - 11:20 AM 2039 6651 5125 4096 7560 5350 31 23
19 Qualification 18   Fri 3/8 - 11:28 AM 5847 2451 16 4645 1739 7237 62 15
20 Qualification 19   Fri 3/8 - 11:36 AM 3734 3067 1797 7609 5148 5934 18 31
21 Qualification 20   Fri 3/8 - 11:44 AM 5822 2725 4241 2338 4156 930 20 55
22 Qualification 21   Fri 3/8 - 11:52 AM 6968 2016 2709 7608 2151 6823 12 14
23 Qualification 22 Fri 3/8 - 1:00 PM 1736 7560 1739 4292 5350 48 43 58
24 Qualification 23 Fri 3/8 - 1:09 PM 2062 1781 2022 2451 4096 6651 35 45
25 Qualification 24 Fri 3/8 - 1:18 PM 111 4296 3488 4787 2136 2039 49 27
26 Qualification 25 Fri 3/8 - 1:27 PM 101 3061 5847 2252 2830 6906 53 40
27 Qualification 26 Fri 3/8 - 1:36 PM 1675 4645 4702 3695 3110 7738 15 71
28 Qualification 27 Fri 3/8 - 1:44 PM 1736 1884 2358 2016 5125 7560 25 23
29 Qualification 28 Fri 3/8 - 1:52 PM 4156 2725 6651 3488 7237 3067 42 39
30 Qualification 29 Fri 3/8 - 2:00 PM 3734 5350 2151 6906 2062 101 18 36
31 Qualification 30 Fri 3/8 - 2:08 PM 5847 7738 6823 2338 111 4096 54 58
32 Qualification 31 Fri 3/8 - 2:16 PM 2709 48 4702 5934 2039 2252 20 49
33 Qualification 32 Fri 3/8 - 2:24 PM 1884 930 2830 1797 1675 6968 61 49
34 Qualification 33 Fri 3/8 - 2:32 PM 7609 1739 3695 5148 4241 4787 85 54
35 Qualification 34 Fri 3/8 - 2:40 PM 5125 4645 2022 3061 2136 4292 37 39
36 Qualification 35 Fri 3/8 - 2:48 PM 2451 2358 7608 4296 16 3110 37 18
37 Qualification 36 Fri 3/8 - 2:56 PM 1781 2039 3734 5822 7237 5847 30 61
38 Qualification 37 Fri 3/8 - 3:04 PM 3488 5350 930 1884 3695 111 52 54
39 Qualification 38 Fri 3/8 - 3:12 PM 2016 5934 2338 7609 7560 4156 66 24
40 Qualification 39 Fri 3/8 - 3:20 PM 2252 6651 2136 4787 7608 1739 27 23
41 Qualification 40 Fri 3/8 - 3:28 PM 4096 4702 5148 2358 4241 101 37 28
42 Qualification 41 Fri 3/8 - 3:36 PM 3110 5822 2451 48 6968 6906 42 68
43 Qualification 42 Fri 3/8 - 3:44 PM 16 1736 1781 7738 3061 2725 56 43
44 Qualification 43 Fri 3/8 - 3:52 PM 1797 5125 4292 6823 2709 2062 32 42
45 Qualification 44 Fri 3/8 - 4:00 PM 2022 4296 3067 2151 2830 1675 26 31
46 Qualification 45 Fri 3/8 - 4:08 PM 4645 48 5847 5148 3488 2016 63 48
47 Qualification 46 Fri 3/8 - 4:16 PM 3110 4096 930 3061 4787 5934 42 56
48 Qualification 47 Fri 3/8 - 4:24 PM 2725 6823 2451 7608 3695 2039 29 57
49 Qualification 48 Fri 3/8 - 4:32 PM 2062 1675 4156 101 4702 2136 40 31
50 Qualification 49 Fri 3/8 - 4:40 PM 2022 7738 7237 5350 2252 7609 51 37
51 Qualification 50 Fri 3/8 - 4:48 PM 7560 4296 2151 1781 1797 4645 21 39
52 Qualification 51 Fri 3/8 - 4:56 PM 2338 1736 5822 2830 2709 6651 68 37
53 Qualification 52 Fri 3/8 - 5:04 PM 6906 1739 2358 4292 6968 1884 33 29
54 Qualification 53 Fri 3/8 - 5:12 PM 111 16 3067 4241 3734 5125 65 41
55 Qualification 54 Fri 3/8 - 5:20 PM 3061 1675 48 7609 5847 7608 65 42
56 Qualification 55 Fri 3/8 - 5:28 PM 6651 2016 2062 930 2252 4296 43 77
57 Qualification 56 Fri 3/8 - 5:36 PM 4292 5148 2725 2151 4787 3110 19 3

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