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
I have been searching for an answer to this question but cannot find anything useful. I am working with the python scientific computing stack (scipy,numpy,matp
I would like to conduct a simple t-test in python, but I would like to compare all possible groups to each other. Let's say I have the following data: import p
The leastsq method in scipy lib fits a curve to some data. And this method implies that in this data Y values depends on some X argument. And calculates the min
I have an array, something like: array = np.arange(0,4,1).reshape(2,2) > [[0 1 2 3]] I want to both upsample this array as well as interpolate the re
When run in debug in PyCharm 2021.3 (Community Edition) on Mac, the code: import pandas as pd x = pd.DataFrame() from scipy.stats import poisson Generates the
I want to run python's ndimage to do some image analysis. I have a 64-bit Mac running OSX Lion and Python 2.7. When I tried to run commands from ndimage comman
I have a Pandas series. I need to get sigma_i, which is the standard deviation of a series up to index i. Is there an existing function which efficiently calcul