2ab8c1444facbd46df8767a5badda5b9f1a50c29,tests.py,,,#,30

Before Change

training_data["class"] = training_classes
training_data["group"] = "training"

testing_data = pd.DataFrame(testing_features)
testing_data["class"] = 0
testing_data["group"] = "testing"

training_testing_data = pd.concat([training_data, testing_data])
most_frequent_class = Counter(training_classes).most_common(1)[0][0]
training_testing_data["guess"] = most_frequent_class

for column in training_testing_data.columns.values:
    if type(column) != str:
        training_testing_data.rename(columns={column: str(column).zfill(5)}, inplace=True)

non_feature_columns = ["guess", "class", "group"]


def test_init():

After Change

// Training data group is 0 testing data group is 1
training_data = np.insert(training_features, 0, training_classes, axis=1)  // Insert the classes
training_data = np.insert(training_data, 0, np.zeros((training_data.shape[0],)), axis=1)  // Insert the group
testing_data = np.insert(testing_features, 0, np.zeros((testing_features.shape[0],)), axis=1)  // Insert the classes
testing_data = np.insert(testing_data, 0, np.ones((testing_data.shape[0],)), axis=1)  // Insert the group

// Insert guess
most_frequent_class = Counter(training_classes).most_common(1)[0][0]
data = np.concatenate([training_data, testing_data])
data = np.insert(data, 0, np.array([most_frequent_class] * data.shape[0]), axis=1)


def test_init():
    Assert that the TPOT instantiator stores the TPOT variables properly

Instances