numerical-integration

I have a time interval from 0 to t . I want to divide this interval into a cumulative sequence in a cycle of 2.25, 2.25 and 1.5, in the following manner: input: start = 0 stop = 19 output: sequence = [0, 2.25, 4.5, 6, 8.25, 10.5, 12, 14.25, 16.5, 18, 19] How can I do this in Python? The idea is to divide a time period into cycles of 6 hours, each cycle consisting of three sequential operations that last 2.25 h, 2.25 h and 1.5 h respectively. Or is there an alternative to using 'milestones' for this purpose? You could use a generator: def interval(start, stop): cur = start yield cur # return

I'm using scipy.integrate.ode and would like to know, what happens internally when I get the message UserWarning: zvode: Excess work done on this call. (Perhaps wrong MF.) 'Unexpected istate=%s' % istate)) This appears when I call ode.integrate(t1) for too big t1 , so I'm forced to use a for -loop and incrementally integrate my equation, what lowers the speed since the solver can not use adaptive step size very effectively. I already tried different methods and setting for the integrator. The maximal number of steps nsteps=100000 is very big already but with this setting I still can't

I was wondering if anyone knew of a numpy/scipy based python package to numerically integrate a complicated numerical function over a tessellated domain (in my specific case, a 2D domain bounded by a voronoi cell)? In the past I used a couple of packages off of the matlab file exchange, but would like to stay within my current python workflow if possible. The matlab routines were http://www.mathworks.com/matlabcentral/fileexchange/9435-n-dimensional-simplex-quadrature for the quadrature and mesh generation using: http://www.mathworks.com/matlabcentral/fileexchange/25555-mesh2d-automatic-mesh

I want to numerically integrate the following: where and a , b and β are constants which for simplicity, can all be set to 1 . Neither Matlab using dblquad , nor Mathematica using NIntegrate can deal with the singularity created by the denominator. Since it's a double integral, I can't specify where the singularity is in Mathematica. I'm sure that it is not infinite since this integral is based in perturbation theory and without the has been found before (just not by me so I don't know how it's done). Any ideas? (1) It would be helpful if you provide the explicit code you use. That way others

I am trying to integrate over a multivariate distribution in python. To test it, I built this toy example with a bivariate normal distribution. I use nquad() in order to extend it to more than two variables later on. Here is the code: import numpy as np from scipy import integrate from scipy.stats import multivariate_normal def integrand(x0, x1, mean, cov): return multivariate_normal.pdf([x0, x1], mean=mean, cov=cov) mean = np.array([100, 100]) cov = np.array([[20, 0], [0, 20]]) res, err = integrate.nquad(integrand, [[-np.inf, np.inf], [-np.inf, np.inf]], args=(mean, cov)) print(res) The