NaN values in Score in Peptide mode toggels curve off in dashboard

[FloBay]

Add an OR NaN ==> True, here to make the dashboard more robust:

curve_curator/curve_curator/dashboard.py

Lines 354 to 377 in 7734ae8

	// Function to compute the product of p1 and p2
	function is_within_limits(value, limit) {
	return (value >= limit[0]) && (value <= limit[1]);
	}
	// Select data to show
	if (reg_filter > 0){
	// Deep copy required as it would otherwise overwrite the original values and only work once
	for(var i = 0; i < n_rows; i++){
	pEC50_mask = is_within_limits(pEC50s[i], pec50_limit);
	signal_mask = is_within_limits(Signals[i], signal_limit);
	score_mask = is_within_limits(Scores[i], score_limit);
	toggle_value = (significant_indicator[i] == reg_filter) && pEC50_mask && signal_mask && score_mask;
	view.filters[0].booleans[i] = toggle_value;
	};
	} else {
	for(var i = 0; i < n_rows; i++){
	pEC50_mask = is_within_limits(pEC50s[i], pec50_limit);
	signal_mask = is_within_limits(Signals[i], signal_limit);
	score_mask = is_within_limits(Scores[i], score_limit);
	toggle_value = pEC50_mask && signal_mask && score_mask;
	view.filters[0].booleans[i] = toggle_value;
	};
	};

Alternatively, could you make an extra toggle or overwrite np.nan with a constant value?

Could you add a user warning that NaN values exist in a filterable column (As this is not expected)? Likely, users are unaware of their own NaNs.

For more information, look at the Internal BUG-list: NK_not_curve_difference_v1&2