utils.py 文件源码

def label_metadata(label_matrix, label_col):
    # Check whether the column value is given as index (number) or name (string) 
    try:
        label_col = int(label_col)

        # If given as number, take the name of the column out of it
        label_col = label_matrix.columns[label_col]
    except ValueError:
        pass

    import pandas as pd
    # Get the unique classes in the given column, and how many of them are there
    unique_classes = pd.unique(label_matrix[label_col].ravel())
    #num_classes = unique_classes.shape[0]

    # Map the unique n classes with a number from 0 to n  
    label_map = pd.DataFrame({label_col: unique_classes, label_col+'_id':range(len(unique_classes))})

    # Replace the given column's values with the mapped equivalent
    mapped_labels = label_matrix.replace(label_map[[0]].values.tolist(), label_map[[1]].values.tolist())

    # Return the mapped labels as numpy list and the label map (unique classes and number can be obtained from map)
    return np.reshape(mapped_labels[[label_col]].values, (mapped_labels.shape[0],)), np.asarray(label_map) #, unique_classes, num_classes