Creates normal science backport

This commit is contained in:
LSaldyt
2017-11-18 18:25:24 -07:00
parent 1b84b22e3f
commit ee483851d8
4 changed files with 178 additions and 0 deletions

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from .copycat import Copycat, Reporter # noqa
from .problem import Problem

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copycat/problem.py Normal file
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from .copycat import Copycat
from pprint import pprint
class Problem:
def __init__(self, initial, modified, target, iterations, distributions=None, formulas=None):
self.formulas = formulas
self.initial = initial
self.modified = modified
self.target = target
self.iterations = iterations
if distributions is None:
self.distributions = self.solve()
else:
self.distributions = distributions
if formulas is not None:
assert hasattr(Copycat().workspace, 'temperature')
def test(self, comparison, expected=None):
print('-' * 120)
print('Testing copycat problem: {} : {} :: {} : _'.format(self.initial,
self.modified,
self.target))
print('expected:')
if expected is None:
expected = self.distributions
pprint(expected)
actual = self.solve()
print('actual:')
pprint(actual)
comparison(actual, expected)
print('-' * 120)
def solve(self):
copycat = Copycat()
answers = dict()
if self.formulas == None:
if hasattr(copycat.workspace, 'temperature'):
formula = copycat.workspace.temperature.getAdj()
else:
formula = None
answers[formula] = copycat.run(self.initial,
self.modified,
self.target,
self.iterations)
else:
for formula in self.formulas:
copycat.temperature.useAdj(formula)
answers[formulas] = copycat.run(self.initial,
self.modified,
self.target,
self.iterations)
return answers
def generate(self):
self.distributions = self.solve()

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copycat/statistics.py Normal file
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# CHI2 values for n degrees freedom
_chiSquared_table = {
1:3.841,
2:5.991,
3:7.815,
4:9.488,
5:11.071,
6:12.592,
7:14.067,
8:15.507,
9:16.919,
10:18.307
}
class ChiSquaredException(Exception):
pass
def chi_squared(actual, expected):
answerKeys = set(list(actual.keys()) + list(expected.keys()))
degreesFreedom = len(answerKeys)
chiSquared = 0
get_count = lambda k, d : d[k]['count'] if k in d else 0
for k in answerKeys:
E = get_count(k, expected)
O = get_count(k, actual)
if E == 0:
print('Warning! Expected 0 counts of {}, but got {}'.format(k, O))
else:
chiSquared += (O - E) ** 2 / E
return chiSquared
def cross_formula_chi_squared(actualDict, expectedDict):
for ka, actual in actualDict.items():
for ke, expected in expectedDict.items():
print('Comparing {} with {}'.format(ka, ke))
chiSquared = chi_squared(actual, expected)
if chiSquared >= _chiSquared_table[degreesFreedom]:
print('Significant difference between expected and actual answer distributions: \n' +
'Chi2 value: {} with {} degrees of freedom'.format(chiSquared, degreesFreedom))
def cross_chi_squared(problemSets):
for i, problemSetA in enumerate(problemSets):
for problemSetB in problemSets[i + 1:]:
for problemA in problemSetA:
for problemB in problemSetB:
answersA = problemA.distributions
answersB = problemB.distributions
cross_formula_chi_squared(answersA, answersB)
def iso_chi_squared(actualDict, expectedDict):
for key in expectedDict.keys():
assert key in actualDict, 'The key {} was not tested'.format(key)
actual = actualDict[key]
expected = expectedDict[key]

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tests.py Normal file
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import unittest
import os.path
import pickle
import argparse
import sys
from pprint import pprint
from copycat import Problem
from copycat.statistics import iso_chi_squared
# TODO: update test cases to use entropy
def generate():
print('Generating distributions for new file')
iterations = 30
problems = [
Problem('abc', 'abd', 'efg', iterations),
Problem('abc', 'abd', 'ijk', iterations),
Problem('abc', 'abd', 'xyz', iterations),
Problem('abc', 'abd', 'ijkk', iterations),
Problem('abc', 'abd', 'mrrjjj', iterations)]
with open(TestCopycat.Filename, 'wb') as outfile:
pickle.dump(problems, outfile)
return problems
class TestCopycat(unittest.TestCase):
Filename = None
def setUp(self):
self.longMessage = True # new in Python 2.7
def test(self):
print('Testing copycat with input file: {}'.format(TestCopycat.Filename))
try:
with open(TestCopycat.Filename, 'rb') as infile:
problems = pickle.load(infile)
except Exception as e:
print('Generating due to error:')
print(e)
problems = generate()
for problem in problems:
problem.test(iso_chi_squared)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--generate', action='store_true')
parser.add_argument('filename', default='.distributions', nargs='?')
parser.add_argument('unittest_args', default=[], nargs='?')
args = parser.parse_args()
# TODO: Go do something with args.input and args.filename
TestCopycat.Filename = args.filename
if args.generate:
generate()
# Now set the sys.argv to the unittest_args (leaving sys.argv[0] alone)
sys.argv[1:] = args.unittest_args
unittest.main()