Python | Numpy np.logseries() method Last Updated : 13 Oct, 2019 Comments Improve Suggest changes Like Article Like Report With the help of np.logseries() method, we can get the log series in the form of an array by using np.logseries() method. Syntax : np.logseries(p, size) Return : Return an array of log series. Example #1 : In this example we can see that by using np.logseries() method, we are able to get an array of log series by using this method. Python3 1=1 # import numpy import numpy as np # using np.logseries() method gfg = np.random.logseries(0.4, 25) print(gfg) Output : [1 1 1 3 1 2 1 1 2 1 1 1 1 1 1 1 1 1 2 3 1 3 1 1 1] Example #2 : Python3 1=1 # import numpy import numpy as np # using np.logseries() method gfg = np.random.logseries(0.8, 25) print(gfg) Output : [ 1 1 1 2 3 1 6 3 3 3 1 2 1 1 1 5 2 1 18 1 1 1 2 2 1] Comment More infoAdvertise with us Next Article Python | Numpy np.logseries() method J Jitender_1998 Follow Improve Article Tags : Technical Scripter Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads Python | Numpy np.lognormal() method With the help of np.lognormal() method, we can get the log normal distribution values using np.lognormal() method. Syntax : np.lognormal(mean, sigma, size) Return : Return the array of log normal distribution. Example #1 : In this example we can see that by using np.lognormal() method, we are able t 1 min read Python - Numpy fromrecords() method numpy.fromrecords() method is a powerful tool in the NumPy library that allows you to create structured arrays from a sequence of tuples or other array-like objects. Let's understand the help of an example:Pythonimport numpy as np # Define a list of records records = [(1, 'Alice', 25.5), (2, 'Bob', 2 min read numpy.geomspace() in Python numpy.geomspace() is used to return numbers spaced evenly on a log scale (a geometric progression). This is similar to numpy.logspace() but with endpoints specified directly. Each output sample is a constant multiple of the previous.  Syntax : numpy.geomspace(start, stop, num=50, endpoint=True, dty 2 min read Python Pytorch logspace() method PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes. The function torch.logspace() returns a one-dimensional tensor of steps points logarithmically spaced with base base between {\text{base}}^{\text{sta 2 min read numpy.log1p() in Python numpy.log1p(arr, out = None, *, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'log1p') : This mathematical function helps user to calculate natural logarithmic value of x+1 where x belongs to all the input array elements. log1p is reverse of exp(x) - 1. Parameters : array : [ 2 min read numpy.logspace() in Python The numpy.logspace() function returns number spaces evenly w.r.t interval on a log scale. Syntax :  numpy.logspace(start, stop, num = 50, endpoint = True, base = 10.0, dtype = None) Parameters : -> start : [float] start(base ** start) of interval range. -> stop : [float] end(base ** stop) of 2 min read numpy.log() in Python The numpy.log() is a mathematical function that helps user to calculate Natural logarithm of x where x belongs to all the input array elements. Natural logarithm log is the inverse of the exp(), so that log(exp(x)) = x. The natural logarithm is log in base e. Syntax :numpy.log(x[, out] = ufunc 'log1 4 min read numpy.logaddexp() in Python numpy.logaddexp() function is used to calculate Logarithm of the sum of exponentiations of the inputs. This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases, the logarithm of the calcu 2 min read Python - PyTorch log() method PyTorch torch.log() method gives a new tensor having the natural logarithm of the elements of input tensor. Syntax: torch.log(input, out=None) Arguments input: This is input tensor. out: The output tensor. Return: It returns a Tensor. Let's see this concept with the help of few examples: Example 1: 1 min read numpy.exp() in Python numpy.exp(array, out = None, where = True, casting = 'same_kind', order = 'K', dtype = None) : This mathematical function helps user to calculate exponential of all the elements in the input array. Parameters : array : [array_like]Input array or object whose elements, we need to test. out : [ndarray 4 min read Like