rouq_mask#
- beatmap.core.rouq_mask(intercept, iso_df, nm, slope, *args, enforce_y_intercept_positive=True, enforce_pressure_increasing=True, enforce_absorbed_amount=True, enforce_relative_pressure=True, enforce_enough_datapoints=True, min_num_points=5)#
Calls all check functions and combines their masks into one “rouqerol mask”.
Rather than pass individual parameters, this function can accept
bet_results(wherebet_resultsis a named tuple output by the bet function).- Parameters:
- interceptndarray
2D array of intercept values, used in check1.
- iso_dfDataFrame
Dataframe of isotherm data, used in check2.
- nmndarray
2D array of amount in the monolayer values, used in check3 and check4.
- slopendarray
2D array of slope values, used in check4
- enforce_y_intercept_positivebool
If True, this check will be evaluated, otherwise skipped.
- enforce_pressure_increasingbool
If True, this check will be evaluated, otherwise skipped.
- enforce_absorbed_amount_validbool
If True, this check will be evaluated, otherwise skipped.
- enforce_relative_pressure_validbool
If True, this check will be evaluated, otherwise skipped.
- enforce_enough_datapointsbool
If True, this check will be evaluated, otherwise skipped.
- min_num_pointsint
The minimum number of experimental data points for a relative pressure interval to be considered valid.
- Returns:
- rouq_masknamedtuple
Contains arrays for the result of each check and a masked array that is the result of all selected checks. Fields of the named tuple are:
rouq_mask.mask(MaskedArray) : object where invalid BET results are masked.rouq_mask.check1(ndarray) : array of 1s and 0s where 0 corresponds failing check1.rouq_mask.check2(ndarray) : array of 1s and 0s where 0 corresponds failing check2.rouq_mask.check3(ndarray) : array of 1s and 0s where 0 corresponds failing check3.rouq_mask.check4(ndarray) : array of 1s and 0s where 0 corresponds failing check4.rouq_mask.check5(ndarray) : array of 1s and 0s where 0 corresponds failing check5.