Labeling

The command label_table can be used to label the samples (see section Sampling). An example of using label_table is shown below:

>>> G = em.label_table(S, label_column_name='gold_labels')

The above command will first create a copy of the input table S, update the metadata, add a column with the specified column name (in label_col_name parameter) fill it with 0 (i.e non-matches) and open a GUI for you to update the labels. You must specify 0 for non-matches and 1 for matches. Once you close the GUI, the updated table will be returned.

Please refer to the API reference of label_table() for more details.

New tool for labeling (experimental)

WARNING: The new labeler is only available in python version 3.5 and above only.

A new command new_label_table has been added to label the samples. This new labeler is currently in pre-alpha stage and is still incomplete. Use at your own risk. An example use is shown below:

>>> G = em.new_label_table(S, label_column_name='gold_labels')

The new labeler completes the same task as label_table in that it will take an input table S with pairs of tuples and create a copy table G with additional label, comment, and tags columns. The command will open a GUI that allows the user to label each pair of tuples with with either ‘Yes’, ‘No’, or ‘Not-Sure’.

Please refer to the API reference of new_label_table() for more details

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