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Nested means here that all terms of a smaller model occur in a larger model. What is the difference between nested and non-nested tests? Using such a function can help in minimizing the running time of code efficiently. Consequently, what is the purpose of vectorization in Python? What is Vectorization ? Vectorization is used to speed up the Python code without using loop. In my previous article I showed an order of magnitude speed boost for numpy vectorization of simple mathematical transformation.
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Just so, how to vectorize a conditional loop in Python? And it turns out one can easily vectorize simple blocks of conditional loops by first turning them into functions and then using numpy.vectorize method. Nested List Comprehensions are nothing but a list comprehension within another list comprehension which is quite similar to nested for loops. It is a smart and concise way of creating lists by iterating over an iterable object. Also, how are nested list comprehensions used in Python? List Comprehensions are one of the most amazing features of Python.
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Indeed, how to create a nested for loop in Python? Python Nested for Loop 1 The outer for loop uses the range () function to iterate over the first ten numbers 2 The inner for loop will execute ten times for each outer number 3 In the body of the inner loop, we will print the multiplication of the outer number and current number 4 The inner loop is nothing but a body of an outer loop.
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The implementation would look like this. This would be benefited by the use of broadcasting for efficiency purposes. We can also gradually build the three ranges corresponding to the shape parameters and perform the subtraction against the three elements of roi on the fly without actually creating the meshes as done earlier with np.mgrid.