def main():
S = Scorer(os.getcwd())
# MatrixMatrixの課題
S.test_stdout("MatrixMatrix")
# Power20の標準出力の課題
testdata = [
205485., 205485., 205485., 205484., 247793., 247789., 247792., 247788.,
269950., 269950., 269949., 269952., 325348., 325352., 325350., 325351.
]
S.test_stdout("Power20",
convert=convert_Power20,
testdata=testdata,
max_score=0.5)
# Power20の関数の課題
testdata_in = [[[0.1, 0.2, 0.3, 0.4], [0.5, 0.6, 0.7, 0.8],
[0.9, 0.10, 0.11, 0.12], [0.13, 0.14, 0.15, 0.16]]]
testdata_out = [[17.947, 11.41, 14.022, 16.633],
[49.864, 31.703, 38.959, 46.214],
[19.887, 12.644, 15.537, 18.431],
[11.37, 7.229, 8.883, 10.538]]
S.test_function("Power20",
"Power20",
convert=convert_Power20_2,
testdata_in=testdata_in,
testdata_out=testdata_out,
max_score=0.5)
print(S.score_dict)
def main():
S_basic = Scorer(os.getcwd())
# MatrixMatrixの課題
testdata_matrix = [30, 30, 45, 75, 58, 80, 75, 62, 85]
S_basic.test_stdout("MatrixMatrix",
convert=convert_Matrix,
testdata=testdata_matrix,
max_score=10)
# Power20の標準出力の課題
S_applied = Scorer(os.getcwd())
testdata_pow = [
68586, 34420, 75432, 63894, 37660, 18901, 41423, 35087, 70324, 35307,
77377, 65538, 105001, 52701, 115496, 97829
]
S_applied.test_stdout("Power20",
convert=convert_Power20,
testdata=testdata_pow,
max_score=5)
# Power20の関数の課題
testdata_in = [[[0.1, 0.2, 0.3, 0.4], [0.5, 0.6, 0.7, 0.8],
[0.9, 0.10, 0.11, 0.12], [0.13, 0.14, 0.15, 0.16]]]
testdata_out = [[17.947, 11.41, 14.022, 16.633],
[49.864, 31.703, 38.959, 46.214],
[19.887, 12.644, 15.537, 18.431],
[11.37, 7.229, 8.883, 10.538]]
S_applied.test_function("Power20",
"Power20",
convert=convert_Power20_2,
testdata_in=testdata_in,
testdata_out=testdata_out,
max_score=5)
df_basic = pd.DataFrame({
"ID": list(S_basic.score_dict.keys()),
"通常": list(S_basic.score_dict.values())
})
df_applied = pd.DataFrame({
"ID": list(S_applied.score_dict.keys()),
"応用": list(S_applied.score_dict.values())
})
df_score = pd.merge(df_basic, df_applied, on="ID", how="outer").fillna(0)
df_score.sort_values("ID")
df_score.to_csv("score.csv", index=False)
def main():
S_basic = Scorer(os.getcwd())
print("##### Density #####")
S_basic.test_stdout("Density",
convert=convert_density,
testdata=testdata_density,
max_score=10)
print("##### MonteCarlo #####")
S_basic.test_stdout("MonteCarlo",
convert=convert_montecarlo,
testdata=True,
max_score=10)
S_applied = Scorer(os.getcwd())
print("##### PrimeFactorization 1 #####")
S_applied.test_function("PrimeFactorization",
"PrimeFactorization",
testdata_in=[12],
testdata_out=[[2, 2], [3, 1]],
max_score=2)
print("##### PrimeFactorization 2 #####")
S_applied.test_function("PrimeFactorization",
"PrimeFactorization",
testdata_in=[30],
testdata_out=[[2, 1], [3, 1], [5, 1]],
max_score=2)
print("##### PrimeFactorization 3 #####")
S_applied.test_function("PrimeFactorization",
"PrimeFactorization",
testdata_in=[32],
testdata_out=[[2, 5]],
max_score=2)
print("##### PrimeFactorization 4 #####")
S_applied.test_function("PrimeFactorization",
"PrimeFactorization",
testdata_in=[111],
testdata_out=[[3, 1], [37, 1]],
max_score=2)
print("##### PrimeFactorization 5 #####")
S_applied.test_function("PrimeFactorization",
"PrimeFactorization",
testdata_in=[20200518],
testdata_out=[[2, 1], [3, 2], [13, 1], [173, 1],
[499, 1]],
max_score=2)
df_basic = pd.DataFrame({
"ID": list(S_basic.score_dict.keys()),
"通常": list(S_basic.score_dict.values())
})
df_applied = pd.DataFrame({
"ID": list(S_applied.score_dict.keys()),
"応用": list(S_applied.score_dict.values())
})
df_score = pd.merge(df_basic, df_applied, on="ID", how="outer").fillna(0)
df_score.sort_values("ID")
df_score.to_csv("score.csv", index=False)
def main():
S_basic = Scorer(os.getcwd())
print("##### Harmonic Mean #####")
S_basic.test_stdout("HarmonicMean",
convert=convert_harm,
testdata=79.902,
max_score=10)
print("##### Triangle 1 #####")
S_basic.test_stdout("Triangle",
convert=convert_tri,
testdata=6,
max_score=3,
stdin_file="triangle_stdin1.py")
print("##### Triangle 2 #####")
S_basic.test_stdout("Triangle",
convert=convert_tri,
testdata=30,
max_score=4,
stdin_file="triangle_stdin2.py")
print("##### Triangle 3 #####")
S_basic.test_stdout("Triangle",
convert=convert_tri,
testdata=60,
max_score=4,
stdin_file="triangle_stdin3.py")
S_applied = Scorer(os.getcwd())
print("##### QuadEquation 1 #####")
S_applied.test_function("QuadEquation",
"QuadEquation",
testdata_in=[0, 1, -2],
testdata_out=2,
max_score=2)
print("##### QuadEquation 2 #####")
S_applied.test_function("QuadEquation",
"QuadEquation",
convert=lambda x: (min(x), max(x)),
testdata_in=[1, -7, 12],
testdata_out=(3, 4),
max_score=2)
print("##### QuadEquation 3 #####")
S_applied.test_function("QuadEquation",
"QuadEquation",
convert=lambda x: (min(x), max(x)),
testdata_in=[1, 1, -2],
testdata_out=(-2, 1),
max_score=2)
print("##### QuadEquation 4 #####")
S_applied.test_function("QuadEquation",
"QuadEquation",
testdata_in=[3, 1, 8],
testdata_out="no solutions",
max_score=2)
print("##### QuadEquation 5 #####")
S_applied.test_function("QuadEquation",
"QuadEquation",
testdata_in=[2, 8, 8],
testdata_out=-2,
max_score=2)
df_basic = pd.DataFrame({
"ID": list(S_basic.score_dict.keys()),
"通常": list(S_basic.score_dict.values())
})
df_applied = pd.DataFrame({
"ID": list(S_applied.score_dict.keys()),
"応用": list(S_applied.score_dict.values())
})
df_score = pd.merge(df_basic, df_applied, on="ID", how="outer").fillna(0)
df_score.sort_values("ID")
df_score.to_csv("score.csv", index=False)
