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License: GNU Lesser General Public License v3.0
Python Library for Particle based estimation methods
License: GNU Lesser General Public License v3.0
Hello,
I set an instance of StdNonLin
model, with two fixed parameters, and I was able to use the simulator.Simulator class to do filtering and smoothing successfuly. Now I want to do parameter estimation for these two parameters. Do you by any chance have any examples for that?
I could not get the source code for the paramest class and also encountered the error module 'pyparticleest.paramest' has no attribute 'paramest'
when I tried to run
import pyparticleest.paramest as paramest
est = paramest.paramest.ParamEstimation(model, u=None, y=obs)
as in the API example.
Thanks for your cool package, looking forward to use it for parameter estimation too.
Hi, sorry this is more of a query than an issue. I am hoping to use Standard Nonlinear Model for filtering/smoothing 2d indoor positional coordinates. I have the corresponding blueprint map as well. Would modelling x & y (coordinates) separately make sense as current implementation seem to work-with/simulate only 1d data? also not sure how to include landmark info at each step. Many thanks!
P.S. thanks for your wonderful work and amazing explanation.
When attempting to import this library for Python3.5, I get the infamous "No module named 'exceptions'" error.
It really would be useful to see this library updated for Python3.
Hi!
Thanks for a very interesting project. I downloaded and installed it to play around with, and got a fatal warning when running setup.py:
fatal error: 'numpy/arrayobject.h' file not found
This makes the compiled C speedup unavailable. If other users encounter this it can be fixed by adding import numpy and include_dirs=[numpy.get_include()] to the extensions import in setup.py, like this:
import numpy
...
if (not on_rtd):
extensions = [Extension("pyparticleest/utils/ckalman", ["pyparticleest/utils/ckalman" + ext], include_dirs=[numpy.get_include()]),
Extension("pyparticleest/utils/cmlnlg_compute", ["pyparticleest/utils/cmlnlg_compute" + ext], include_dirs=[numpy.get_include()])]
I was trying to figure out where your expression for kalman.lognormpdf came from, so I went back to the functional expression
and took the ln of that to find
I understand how this is the same as your code
-0.5 * (S.shape[0] * l2pi + np.linalg.slogdet(S)[1] + np.linalg.solve(S, tmp).T.dot(tmp))
but if my function f is correct, then your expression is missing that summation np.sum(tmp)
Thoughts?
-ben
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