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Programming Articles
Page 2044 of 2547
C++ to perform certain operations on a sequence
Suppose, we are given an empty sequence and n queries that we have to process. The queries are given in the array queries and they are in the format {query, data}. The queries can be of the three following types−query = 1: Add the supplied data to the end of the sequence.query = 2: Print the element at the beginning of the sequence. After that delete the element.query = 3: Sort the sequence in ascending order.Note that, query types 2 and 3 always have data = 0.So, if the input is like n = 9, queries = {{1, 5}, {1, ...
Read MoreC++ Program to find out the maximum number of moves to reach a unblocked cell to another unblocked cell in a grid
Suppose, we are given a grid of dimensions h * w that contains two types of cells, blocked and unblocked. Blocked cells mean that the cells aren't accessible and unblocked means that the cells are accessible. We represent the grid in a 2D array where the blocked cells are given as '#' and the unblocked cells are given as '.'. Now, we have to reach from an unblocked cell to another unblocked cell in the grid. We can perform only two moves, we can either go vertical or we can go horizontal. We can't move diagonally. We have to keep ...
Read MoreReturn the result of the negative power to which the input value is raised with scimath in Python
To return the result of the power to which the input value is raised with scimath, use the scimath.power() method in Python. Returns x to the power p, i.e. the result of x**p. If x and p are scalars, so is out, otherwise an array is returned. If x contains negative values, the output is converted to the complex domain. The parameter x is the input valueThe parameter p is the power(s) to which x is raised. If x contains multiple values, p has to either be a scalar, or contain the same number of values as x. In the ...
Read MoreReplace NaN with zero and fill negative infinity for complex input values in Python
To replace NaN with zero and infinity with large finite numbers, use the numpy.nan_to_num() method in Python. The method returns, x, with the non-finite values replaced. If copy is False, this may be x itself. The 1st parameter is the input data. The 2nd parameter is copy, whether to create a copy of x (True) or to replace values in-place. The in-place operation only occurs if casting to an array does not require a copy. Default is True.The 3rd parameter is nan, the value to be used to fill NaN values. If no value is passed then NaN values will ...
Read MoreEvaluate a Hermite series at multidimensional array of points x in Python
To evaluate a Hermite series at points x, use the hermite.hermval() method in Python Numpy. The 1st parameter, x, if x is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, x or its elements must support addition and multiplication with themselves and with the elements of c.The 2nd parameter, C, an array of coefficients ordered so that the coefficients for terms of degree n are contained in c[n]. If c is multidimensional the remaining indices enumerate multiple polynomials. In the two dimensional case the coefficients ...
Read MoreGenerate a Vandermonde matrix of given degree with float array of points in Python
To generate a Vandermonde matrix of given degree, use the polynomial.polyvander() in Python Numpy. The method returns rhe Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where the last index is the power of x. The dtype will be the same as the converted x.The parameter, a is Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the resulting matrix.StepsAt first, import the required ...
Read MoreReplace NaN with zero and fill positive infinity values in Python
To replace NaN with zero and infinity with large finite numbers, use the numpy.nan_to_num() method in Python. The method returns, x, with the non-finite values replaced. If copy is False, this may be x itself. The 1st parameter is the input data. The 2nd parameter is copy, whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True.The 3rd parameter is nan, the value to be used to fill NaN values. If no value is passed then NaN values ...
Read MoreCompute a matrix transpose with Einstein summation convention in Python
The einsum() method evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a simple fashion. In implicit mode einsum computes these values. In explicit mode, einsum provides further flexibility to compute other array operations that might not be considered classical Einstein summation operations, by disabling, or forcing summation over specified subscript labels.To compute a matrix transpose with Einstein summation convention, use the numpy.einsum() method in Python. The 1st parameter is the subscript. It specifies the subscripts for summation as comma separated list of subscript labels. ...
Read MoreReturn the modified Bessel function evaluated at each of the elements of x in Python
To return the modified Bessel function evaluated at each of the elements of x, use the numpy.io() method. The parameter x is an Argument of the Bessel function. The method returns the modified Bessel function evaluated at each of the elements of x.StepsAt first, import the required libraries −import numpy as npCreate an array using the array() method −arr = np.array([10, 20, 30, 40, 50]) Display the array −print("Array...", arr)Get the type of the array −print("Our Array type...", arr.dtype) Get the dimensions of the Array −print("Our Array Dimension...", arr.ndim)Get the shape of the Array −print("Our Array Shape...", arr.shape) To return ...
Read MoreReturn the multiple vector cross product of two (arrays of) vectors in Python
To compute the cross product of two vectors, use the numpy.cross() method in Python Numpy. The method returns c, the Vector cross product(s). The 1st parameter is a, the components of the first vector(s). The 2nd parameter is b, the components of the second vector(s). The 3rd parameter is axisa, the axis of a that defines the vector(s). By default, the last axis. The 4th parameter is axisb, the axis of b that defines the vector(s). By default, the last axis.The 5th parameter is axisc, the axis of c containing the cross product vector(s). Ignored if both input vectors have ...
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