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For example, the "add an object to a collection" method (Collection>>add: anObject) returns the object that was added, not the collection. Thus to use this in a cascade in an assignment statement, the cascade must end with yourself , otherwise the value will just be the last element added, not the collection itself:
Another example in JavaScript uses the built-in methods of Array: filter somethings . filter ( x => x . count > 10 ) . sort (( a , b ) => a . count - b . count ) . map ( x => x . name ) Note that in JavaScript filter and map return a new shallow copy of the preceding array but sort operates in place.
If xxx1 is omitted, we get a loop with the test at the top (a traditional while loop). If xxx2 is omitted, we get a loop with the test at the bottom, equivalent to a do while loop in many languages. If while is omitted, we get an infinite loop. The construction here can be thought of as a do loop with the while check in the middle. Hence this ...
For example, if the summands x i are uncorrelated random numbers with zero mean, the sum is a random walk and the condition number will grow proportional to . On the other hand, for random inputs with nonzero mean the condition number asymptotes to a finite constant as n → ∞ {\displaystyle n\to \infty } .
In this example, code block 1 shows loop-dependent dependence between statement S2 iteration i and statement S1 iteration i-1. This is to say that statement S2 cannot proceed until statement S1 in the previous iteration finishes. Code block 2 show loop independent dependence between statements S1 and S2 in the same iteration.
Cascading is a particular case of ensemble learning based on the concatenation of several classifiers, using all information collected from the output from a given classifier as additional information for the next classifier in the cascade. Unlike voting or stacking ensembles, which are multiexpert systems, cascading is a multistage one.
In the above example, pytest fixture dataset returns a dictionary, which is then passed into test function test_dataset for assertion. In addition to fixture detection within the same file as test cases, pytest fixtures can also be placed in the conftest.py file in the tests directory.
Loop unrolling, also known as loop unwinding, is a loop transformation technique that attempts to optimize a program's execution speed at the expense of its binary size, which is an approach known as space–time tradeoff. The transformation can be undertaken manually by the programmer or by an optimizing compiler.