Vectorizing multivariate normal distribution calculation Question: I have n points in 3D space, each with a corresponding guess and certainty attached to it. I want to calculate the multivariate normal distribution for each point given its guess and certainty. Currently, I’m using an iterative approach and the Scipy.stats multivariate_normal function, as shown in the code …
Creating arguments which are evenly distributed in $[0,pi)$ Question: I want to create arguments ${ psi_{m}}$ which are evenly distributed in $[0,pi)$ in python where $m=1,…,M$ with $M=100$. I would be appreciate if someone could help me that. Thanks in advance. Asked By: M.Ramana || Source Answers: If I understand correctly, you want to sample …
Is there a way to generate a lognormal distribution from a pre-defined normal distribution? Question: I have the code which generates a normal distribution as a pdf, centered at the mean 400, with st import numpy as np import matplotlib.pyplot as plt import scipy.stats muPrev, sigmaPrev = 400, 40. a = np.random.normal(muPrev, sigmaPrev, 100000) count, …
How to see a distribution of outcomes of a while loop? Question: Imagine you have a while loop that includes a random outcome so that the output of the while loop is different each time. How can you simulate the while loop many times and see the distribution of outcomes? I know how to run …
Why am I getting multiple curves instead of one in a pdf Question: I’m trying to plot a histogram and a pdf for a normal distribution function of data_2, but I’m getting multiple lines instead of one, like this Here is my code def normal_dist(data_list): density_func = sps.norm.pdf(data_list, np.mean(data_list), np.std(data_list)) return density_func def plot_histo(data_list, bin_count …
Creating 2-D Gaussian Distributions With Python Question: I’m trying to create 2-D Gaussian distributions based off the question in the image below. I’m using numpy’s multivariate_normal(): mu1 = [2,0] cov1 = [[1,0],[0,1]] gauss1 = np.random.multivariate_normal(mu1, cov1, 1000) print(gauss1[:5]) [[ 2.31429248 -0.66406452] [ 0.26891266 -0.6157051 ] [ 1.93124527 -1.33371758] [ 3.55936363 0.84616475] [ 2.70321679 -1.43942645]] Is …
How to get the Sigma of a Rayleigh distribution in python scipy.stats Question: Calling rayleigh_args = stats.rayleigh.fit(num_list) Returns a tuple of 2 values e.g. (-320.34, 360.77). Where I can use it to get the CDF or PDF of the distribution for a given value. I can’t find what each of those values represents. In addition, …
Seaborn plot displot with hue and dual y-scale (twinx) Question: I am trying to plot the output from the predict of a ML model, there are the classes 1,0 for the Target, and the Score. Due the dataset is not balanced, there are few 1’s. When I plot a simple displot with the Target in …
Functionally is torch.multinomial the same as torch.distributions.categorical.Categorical? Question: For example, if I provide a probability array of [0.5, 0.5], both functions will sample the index [0,1] with equal probability? Asked By: Mzq || Source Answers: Yes: [torch.distributions.categorical.Categorical()] is equivalent to the distribution that torch.multinomial() samples from. https://pytorch.org/docs/stable/distributions.html#categorical Answered By: iacob
How to draw a normal curve on seaborn displot Question: distplot was deprecated in favour of displot. The previous function had the option to draw a normal curve. import seaborn as sns import matplotlib.pyplot as plt from scipy import stats ax = sns.distplot(df.extracted, bins=40, kde=False, fit=stats.norm) the fit=stats.norm doesn’t work with displot anymore. In the …
