A program designed for a study involving participants' trust in an artificial intelligence. This is tested by asking the participant to "bet" on horse races where an AI has predicted the outcome. Researchers will then observe the participant's actions while choosing their bet, as an indication of trust, (i.e. choosing the AI's suggestion, amount of time taken, etc).
final_data_filename: filename for the end result to be written to
data_col_headers: a comma-separated list of features, in order, that we want to compile
raw_data_path: path to the data to be compiled
target_ai: defines which problem to compile for (not yet used)
compile_data.py now imports configuration information, writes headers to the datafile if necessary, then iterates through each csv file at least one layer deep in the data directory, writing each row of information to the final file.
It seems as though we can simply manipulate the header configuration to easily alter the final data.
Creates entries in config.yml:
final_data_filename: filename for the end result to be written todata_col_headers: a comma-separated list of features, in order, that we want to compileraw_data_path: path to the data to be compiledtarget_ai: defines which problem to compile for (not yet used)compile_data.pynow imports configuration information, writes headers to the datafile if necessary, then iterates through each csv file at least one layer deep in the data directory, writing each row of information to the final file.It seems as though we can simply manipulate the header configuration to easily alter the final data.