def set_pract_high_z_score_attr(handler_input, player_obj: object) -> None:
"""Sets attributes for high z-score practice."""
attr = handler_input.attributes_manager.session_attributes
CP_Attr.set_tbl_mean_err_list_attr(handler_input, player_obj)
tbl_list_mean_errs = attr['tbl_list_mean_errs']
tbl_means_only = [val[1] for val in tbl_list_mean_errs]
total_err_mean = mean(tbl_means_only)
total_err_stdev = stdev(tbl_means_only, xbar= total_err_mean)
practice_tables = []
for i in range(3):
table, mean_err = tbl_list_mean_errs[i]
tbl_z_score = calc_z_score(
data_point= mean_err,
data_mean= total_err_mean,
data_stdev= total_err_stdev,
)
if tbl_z_score > custom_practice.data.HIGH_Z_SCORE_ERR:
practice_tables.append( table)
attr['times_tables'] = practice_tables
return None
def get_top_z_score_err_tables(handler_input) -> list:
"""Returns list of the top 3 z-score error tables."""
attr = handler_input.attributes_manager.session_attributes
tbl_list_mean_errs = attr['tbl_list_mean_errs']
tbl_means = [ num[1] for num in tbl_list_mean_errs]
tables_to_practice = []
tbl_mean_err = mean(tbl_means)
tbl_mean_stdev = stdev(tbl_means, xbar = tbl_mean_err)
for i in range(3):
table, table_err = tbl_list_mean_errs[i]
tbl_z_score = calc_z_score(
data_point = table_err,
data_mean= tbl_mean_err,
data_stdev= tbl_mean_stdev,
)
if tbl_z_score > custom_practice.data.HIGH_Z_SCORE_ERR:
tables_to_practice.append( table )
tables_to_practice.sort()
logger.debug( tbl_list_mean_errs)
logger.debug( tables_to_practice)
return tables_to_practice
def get_higher_table_difficulty(
handler_input,
player_obj: object = None,
tables: tuple = None,
answered_tables: list = None
) -> float:
"""Returns z_score for the table with the highest difficulty.
Difficulty is a constructed measure dependent on greatness of tables,
e.g., 6 > 5."""
if not player_obj:
player_obj = PlayerDict.load_player_obj(handler_input)
if tables is None:
tables = QuestionAttr.get_question_tables(handler_input, integers=True)
if answered_tables is None:
answered_tables = player_obj.get_answered_tables(integers = True)
inflated_mean_table = mean(answered_tables) + 1
higher_table = max( [int(table) for table in tables])
z_score = calc_z_score(
data_point= higher_table,
data_mean = inflated_mean_table,
data= answered_tables,
required_data_length= stats.data.SUF_ANSWERED_TABLES
)
return z_score
def get_sm_z_score(handler_input, sm_score: int, player_obj: object = None) -> bool:
"""Returns z_score for the Survival mode score."""
if not player_obj:
player_obj = PlayerDict.load_player_obj(handler_input)
sm_average_records = [int(num) for num in player_obj._sm_average_records]
z_score = calc_z_score(
data_point= sm_score,
data = sm_average_records
)
return z_score
def get_sc_performance_z_score(player_obj: object, sc_difficulty: str,
sc_score_time: int) -> float:
"""Returns z_score for the user's relative performance in speed challenge."""
sc_average_records = player_obj.get_sc_average_records(sc_difficulty)
if len(sc_average_records) < 2:
return 0
z_score = calc_z_score(
data_point=sc_score_time,
data=sc_average_records,
)
z_score *= -1 # inversed for time records.
logger.debug(z_score)
return z_score
def check_high_err_z_score(handler_input) -> bool:
"""Returns if high error z-score table is present.
NOTE: Should probably save tbl error means list as session attr."""
attr = handler_input.attributes_manager.session_attributes
tbl_list_mean_errs = attr['tbl_list_mean_errs']
tbl_means_only = [val[1] for val in tbl_list_mean_errs]
total_err_mean = mean(tbl_means_only)
total_err_stdev = stdev(tbl_means_only, xbar= total_err_mean)
total_err_stdev = total_err_stdev if total_err_stdev else 1
first_z_score = calc_z_score(
data_point = tbl_list_mean_errs[0][1],
data_mean = total_err_mean,
data_stdev = total_err_stdev,
)
if first_z_score > custom_practice.data.HIGH_Z_SCORE_ERR:
return True
return False
def get_higher_table_error_freq(
handler_input,
player_obj: object = None,
tables: tuple = None
) -> float:
"""Returns z_score for the highest error tables."""
if not player_obj:
player_obj = PlayerDict.load_player_obj(handler_input)
if tables is None:
tables = QuestionAttr.get_question_tables(handler_input, integers=False)
times_tables_info = player_obj.get_times_table_info()
times_tables_mean_err_list = []
for table in times_tables_info.keys():
table_mean = float(times_tables_info[table]['mean'])
table_data = times_tables_info[table]['table_data']
if len(table_data) > stats.data.SUF_TABLE_DATA:
times_tables_mean_err_list.append(1 - table_mean) # inversed, so errors are higher.
## Exit if not enough data.
if len(times_tables_mean_err_list) <= stats.data.SUF_ERR_LIST:
return 0
question_tables_err = []
for table in tables:
table = str(table)
table_info = float( times_tables_info[table]['mean'])
table_info = (1 - table_info) # inverse mean.
question_tables_err.append( table_info)
max_table_err = max(question_tables_err)
z_score = calc_z_score(
data_point= max_table_err,
data= times_tables_mean_err_list,
)
return ( z_score)