Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
In this article, we will understand how to reverse a sentence using recursion. A recursive function is a function that calls itself multiple times until a particular condition is satisfied.A recursive function is a function that calls itself multiple times until a particular condition is satisfied.Recursion is the process of repeating items in a self-similar way. In programming languages, if a program allows you to call a function inside the same function, then it is called a recursive call of the function.Many programming languages implement recursion by means of stacks. Generally, whenever a function (caller) calls another function (callee) or ... Read More
To clip (limit) the values in an array, use the np.ma.clip() method in Python Numpy. The "out" parameter is where results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved. . Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Equivalent to but faster than np.minimum(a_max, np.maximum(a, a_min)).The function returns an array ... Read More
To clip (limit) the values in an array, use the np.ma.clip() method in Python Numpy. Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Equivalent to but faster than np.minimum(a_max, np.maximum(a, a_min)).The out is where the results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.The function returns an array with the ... Read More
To generate a Vandermonde matrix, use the np.ma.vander() method in Python Numpy. Set the number of columns in the output using the N parameter. If N is not specified, a square array is returned (N = len(x)).The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector raised element-wise to the power of N - i - 1. Such a matrix with a geometric progression in each row is named for Alexandre- Theophile Vandermonde.StepsAt ... Read More
In this article, we will understand how to construct a simple calculator using switch-case. The switch statement evaluates an expression, matching the expression's value to a case clause, and executes statements associated with that case.Following are the arithmetic operations we are going to perform.AdditionSubtractionMultiplicationDivisionFloor DivisionModuloBelow is a demonstration of the same −InputSuppose our input is −The two inputs: 40.0 and 12.0 Operator:%OutputThe desired output would be −The result is 40.0 % 12.0 = 4.0AlgorithmStep 1 - START Step 2 - Declare three values namely my_input_1, my_input_2 and my_result and declare a character value namely operator. Step 3 - Read the required ... Read More
To generate a Vandermonde matrix, use the np.ma.vander() method in Python Numpy. A Vandermonde matrix, named after Alexandre-Théophile Vandermonde, is a matrix with the terms of a geometric progression in each row.The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector raised element-wise to the power of N - i - 1. Such a matrix with a geometric progression in each row is named for Alexandre- Theophile Vandermonde.StepsAt first, import the required library ... Read More
To return the outer product of two masked 1D arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt first, import the required library −import ... Read More
To return the outer product of two 3D masked arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt first, import the required library −import ... Read More
To return the outer product of two masked arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt first, import the required library −import numpy ... Read More
To mask rows and/or columns of a 2D array that contain masked values, use the np.ma.mask_rowcols() method in Numpy. The function returns a modified version of the input array, masked depending on the value of the axis parameter.Mask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis parameter −If axis is None, rows and columns are masked.If axis is 0, only rows are masked.If axis is 1 or -1, only columns are masked.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with ... Read More