def testHW2(): # Success
test, train = utils.load_and_normalize_housing_set()
df_train = pd.DataFrame(train)
df_test = pd.DataFrame(test)
print df_train.head(10)
#raw_input()
print hw2.linear_gd(df_train, df_test, 'MEDV')
def testHW2_subset(): # Success
test, train = utils.load_and_normalize_housing_set()
df_full = pd.DataFrame(train)
df_test = utils.train_subset(df_full, ['CRIM', 'TAX', 'B', 'MEDV'], n=10)
df_train = utils.train_subset(df_full, ['CRIM', 'TAX', 'B', 'MEDV'], n=10)
dfX_test = pd.DataFrame([df_test['CRIM'], df_test['TAX'], df_test['MEDV']]).transpose()
dfX_train = pd.DataFrame([df_train['CRIM'], df_train['TAX'], df_train['MEDV']]).transpose()
print hw2.linear_gd(dfX_train, dfX_test, 'MEDV')
def testHW2_allcols(): # Fail
test, train = utils.load_and_normalize_housing_set()
df_full = pd.DataFrame(train)
cols = [col for col in df_full.columns if col != 'MEDV']
df_test = utils.train_subset(df_full, cols, n=10)
df_train = utils.train_subset(df_full, cols, n=10)
#dfX_test = pd.DataFrame([df_test['CRIM'], df_test['TAX'], df_test['MEDV']]).transpose()
#dfX_train = pd.DataFrame([df_train['CRIM'], df_train['TAX'], df_train['MEDV']]).transpose()
print hw2.linear_gd(df_train, df_test, 'MEDV')