I am wondering how to export MATLAB function ode45 to python. According to the documentation is should be as follows: MATLAB: [t,y]=ode45(@vdp1,[0 20],[2 0])
I found a PDF document describing the income distribution in the US in 1978. Per income range I have the percentage of the population that falls in that income
I am new to python. I want to perform orthogonal distance regression by using Scipy ODR by using the code below. I do not know how can I extract slope and inter
SciPy interpolation has 3 supported methods: Supported are “linear” and “nearest”, and “splinef2d”. “splinef2d”
I've been trying to use scipy.stats.levene with no success. I have a numpy matrix with shape (2128, 45100). Each row is a sample and belongs to one of 3 cluste
Suppose I had two 2D sets of 1000 samples that look something like this: I'd like to have a metric for the amount of difference between the distributions and
import scipy.io.wavfile as wav import matplotlib.pyplot as plt import scipy sample_rate, X = wav.read("/Users/sinaastani/Downloads/partynextdoor.wav") X = scipy
I have a system of two first order ODEs, which are nonlinear, and hence difficult to solve analytically in a closed form. I want to fit the numerical solution t
I'm trying to generate a sine wave of a given frequency for a given duration and then write it into a .wav file. I'm using numpy's sin function and scipy's wavf
The gaussian_kde function in scipy.stats has a function evaluate that can returns the value of the PDF of an input point. I'm trying to use gaussian_kde to esti
I want to process quite big ARFF files in scikit-learn. The files are in a zip archive and I do not want to unpack the archive to a folder before processing. He
I'm setting up an interior positioning system, and when I request the opt.leastsq function, I have the expected result in the string, but it gives me an output
I'm looking to annotate a hierarchical clustering dendrogram, but I have some trouble associating the node indices produced by scipy.cluster.hierarchy.dendrogra
I am using python 3.3 on Windows. I downloaded scipy-0.13.2.win32-py3.3.exe from scipy-lib and installed it. However, when I tried to load scipy.linalg, interpr
I want to fit a plane to some data points and draw it. My current code is this: import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.py
For a current project I have to compute the inner product of a lot of vectors with the same matrix (which is quite sparse). The vectors are associated with a tw
I have a 6x6 matrix of data(values_master) for a 6x6 set of data points: master_x,master_y=mgrid[950:1450:6j,550:1050:6j] I then try and interpolate the data
I recently discovered Conda after I was having trouble installing SciPy, specifically on a Heroku app that I am developing. With Conda you create environments,
I am using truncated SVD from scikit-learn package. In the definition of SVD, an original matrix A is approxmated as a product A ≈ UΣV* where
I'm trying to create a uniform distribution between two numbers (lower bound and upper bound) in order to feed it to sklearn's ParameterSampler. I am using scip