It is known that correlation-immune (CI) Boolean functions used in the framework of side-channel attacks need to have low Hamming weights. The supports of CI functions are (equivalently) simple orthogonal arrays when their elements are written as rows of an array. The minimum Hamming weight of...
Lightweight condition parsing and building of evaluation expressions pythonfilterevaluationparsing-expression-grammarconditionsboolean-function UpdatedFeb 11, 2023 Python catchr: Flexible, useful tools for dealing with conditions in R, for new users and veterans ...
The foundation of thewheremethod’s functionality lies in creating Boolean masks based on specified conditions. These masks are essentially arrays or series ofTrueandFalsevalues, representing whether each element satisfies the given condition. Given a DataFrame: import pandas as pd data = { 'Name':...
Step 3 - Apply AND logic The parentheses let you control the order of operation. We need to calculate the comparisons before we multiply the arrays. (B3:B12=D14)*(C3:C12=D15) returns {0;0;0;0;1;0;0;0;0;0}. Boolean values, when multiplied, return their numerical equivalents. TRUE...
The analyzer has detected a loop whose termination conditions do not depend on the number of iterations. Such a loop can iterate 0, 1, or an infinite number of times.
The function which decides whether an item in the original array should be included in the resulting array can contain any number of conditions – in fact, it’s a standard JavaScript function, so you can do pretty much whatever you want in it – just so long as you return a boolean TRU...
Boolean value for the condition. namestr, optional The name of the condition.Attributesargs The list of arguments associated with the component. description YAML formatted string describing the condition. fragment Fragment that the condition belongs to. gxf_cid The GXF component ID. gxf_cname The ...
As shown in the screenshot below, the formulas produce the same result, so which one to use is a matter of your personal preference. For me, the formula with the Boolean logic is easier to read and build – it allows adding as many conditions as you want without nesting additional IF ...
You can also use the size function to simply find how many values meet one of the conditions using(arr[np.where()]).sizefunction. For instance, to create a NumPy array calledarrwith values[5, 10, 15, 20, 25]and then filters the array based on a condition using boolean indexing. Spec...
neural nets have a couple of pages of weights in big arrays for all the sum of products etc. You can make them do idiotic simple stuff, like a boolean condition, and it will take several pages of weights, multiplications, lookup tables, and such to get the result. Its the old sledgeha...