mattja/nsim

Large scale simulation of ODEs or SDEs, analyze time series.

nsim's Issues

plot time scale are wrong

When you plot a simulation with timeseries.plot(),
the time axis is not scaled correctly.

if you run a simulation like this:

sim = nsim.RepeatedSim(Model, T=100, repeat=2)
sim.timeseries.plot()

The time scale of the plot should go from 0 to 100, right?.

Incompatibility with ipyparallel>=5.0

nsim works fine with ipyparallel 4 and earlier, but gives spurious messages with ipyparallel 5.0.x and breaks with ipyparallel >=5.1.x, working some of the time, and completely freezing with no error message at other times. See mattja/distob#3.

Have not yet investigated this to find whether this is a bug in ipyparallel or distob, or whether it results from a change to the AsyncResult interface in ipyparallel.
Until this issue is sorted out, temporarily require ipyparallel 4.x

Problem simulating a 2 dimensional system

Hi, I am trying to use nsim to simulate the following model:

"""
SIR Epidemic Model

S --> I --> R

X(t) = [S(t), I(t)]

Equations:

dS = -r0*S*I dt -sqrt(r0*S*I) dW1
dI = r0*S*I dt + sqrt(r0*S*I) dW1 -sqrt(I) dW2

"""

import nsim
import numpy as np

class SIR(nsim.ItoModel):
    r0 = 1.5
    y0 = np.array([0.9, 0.1]).T

    def f(self, y, t):
        A = np.array([[-self.r0*y[0]*y[1]],
                       [self.r0*y[0]*y[1] - y[1]]])
        return A

    def G(self, y, t):
        B = np.array([[-np.sqrt(self.r0*y[0]*y[1]), 0],
                       [np.sqrt(self.r0*y[0]*y[1]), - y[1]]])
        return B

To simulate it I tried the following:

s = nsim.Simulation(SIR, T=520.0)

It seems to work but when I try to plot the results, I get this error:

Traceback (most recent call last):
  File "SDE_SIR.py", line 38, in <module>
    print(s.output, dir(s))
  File "/usr/local/lib/python3.5/dist-packages/nsim/nsim.py", line 1330, in output
    self.compute()
  File "/usr/local/lib/python3.5/dist-packages/nsim/nsim.py", line 1313, in compute
    ar = self.system.integrate(tspan)
  File "/usr/local/lib/python3.5/dist-packages/nsim/nsim.py", line 870, in integrate
    ar = self.integrator[0](self.f, self.G, self.y0, tspan)
  File "/usr/local/lib/python3.5/dist-packages/sdeint/integrate.py", line 125, in itoint
    return chosenAlgorithm(f, G, y0, tspan)
  File "/usr/local/lib/python3.5/dist-packages/sdeint/integrate.py", line 305, in itoSRI2
    return _Roessler2010_SRK2(f, G, y0, tspan, Imethod, dW, I)
  File "/usr/local/lib/python3.5/dist-packages/sdeint/integrate.py", line 439, in _Roessler2010_SRK2
    H20b = np.reshape(H20, (d, 1))
  File "/usr/local/lib/python3.5/dist-packages/numpy/core/fromnumeric.py", line 225, in reshape
    return reshape(newshape, order=order)
ValueError: total size of new array must be unchanged

Is this a bug, or maybe a mistake in my model?

Python 3 compatibility

I don't know if you already support python 3, but I noticed the follwing exception when trying to run one of the examples under Python3:

   import nsim
  File "/usr/local/lib/python3.5/dist-packages/nsim/__init__.py", line 5, in <module>
    from . import analyses1
  File "/usr/local/lib/python3.5/dist-packages/nsim/analyses1/__init__.py", line 12, in <module>
    from .pyeeg import (hurst, embed_seq, in_range, bin_power, pfd, hfd, hjorth,
  File "/usr/local/lib/python3.5/dist-packages/nsim/analyses1/pyeeg.py", line 161
    print "Cannot build such a matrix, because D * Tau > N"
                                                          ^
SyntaxError: Missing parentheses in call to 'print'