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joshspeagle / dynesty

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences
https://dynesty.readthedocs.io/
MIT License
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balls bounds error #204

Closed segasai closed 3 years ago

segasai commented 4 years ago

Hi,

while running dynesty with a complicated posterior and 'balls' bounds parameter I've encountered a following error multiple times

~/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py in run_nested(self, nlive_init, maxiter_init, maxcall_init, dlogz_init, logl_max_init, n_effective_init, nlive_batch, wt_function, wt_kwargs, maxiter_batch, maxcall_batch, maxiter, maxcall, maxbatch, n_effective, stop_function, stop_kwargs, use_stop, save_bounds, print_progress, print_func, live_points)
   1660                     # Compute our sampling bounds using the provided
   1661                     # weight function.
-> 1662                     passback = self.add_batch(nlive=nlive_batch,
   1663                                               wt_function=wt_function,
   1664                                               wt_kwargs=wt_kwargs,

~/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py in add_batch(self, nlive, wt_function, wt_kwargs, maxiter, maxcall, logl_bounds, save_bounds, print_progress, print_func, stop_val)
   1769                 if logl_bounds is None:
   1770                     logl_bounds = wt_function(res, wt_kwargs)
-> 1771                 for results in self.sample_batch(nlive_new=nlive,
   1772                                                  logl_bounds=logl_bounds,
   1773                                                  maxiter=maxiter,

~/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py in sample_batch(self, nlive_new, update_interval, logl_bounds, maxiter, maxcall, save_bounds)
   1132             loglmin = min(live_logl)
   1133             if self.sampler._beyond_unit_bound(loglmin):
-> 1134                 bound = self.sampler.update(vol / nblive)
   1135                 if save_bounds:
   1136                     self.sampler.bound.append(copy.deepcopy(bound))

~/pyenv38/lib/python3.8/site-packages/dynesty/nestedsamplers.py in update(self, pointvol)
    798 
    799         # Update the N-spheres.
--> 800         self.radfriends.update(self.live_u, pointvol=pointvol,
    801                                rstate=self.rstate, bootstrap=self.bootstrap,
    802                                pool=pool)

~/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py in update(self, points, pointvol, rstate, bootstrap, pool, mc_integrate, use_clustering)
    856         if bootstrap == 0.:
    857             # Construct radius using leave-one-out if no bootstraps used.
--> 858             radii = _friends_leaveoneout_radius(points_t, 'balls')
    859         else:
    860             # Bootstrap radius using the set of live points.

~/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py in _friends_leaveoneout_radius(points, ftype)
   1631     # Construct KDTree to enable quick nearest-neighbor lookup for
   1632     # our resampled objects.
-> 1633     kdtree = spatial.KDTree(points)
   1634 
   1635     if ftype == 'balls':

~/pyenv38/lib/python3.8/site-packages/scipy/spatial/kdtree.py in __init__(self, data, leafsize)
    240         self.data = np.asarray(data)
    241         if self.data.dtype.kind == 'c':
--> 242             raise TypeError("KDTree does not work with complex data")
    243 
    244         self.n, self.m = np.shape(self.data)

TypeError: KDTree does not work with complex data

The error presumably comes from this code 

        self.am = lalg.pinvh(self.cov)
        self.axes = lalg.sqrtm(self.cov)
        self.axes_inv = lalg.pinvh(self.axes)

in RadFriends.update() that produces complex numbers and screws up the kdtree. I'm guessing that the covariance matrix there need to be checked for being positive definite.

I don't think I know the code enough to offer a patch though.

Sergey

joshspeagle commented 4 years ago

Would you be able to test whether this still occurs on the main Github development branch? I've implemented a few stability improvements, so it would be good to know whether those are enough to resolve this or I need to work a bit harder to deal with these cases.

segasai commented 4 years ago

Thanks. I've updated the branch. I'll see if I can trigger the error again (in the previous case it happened after ~ day of running on 24 CPUs, and I'm not sure it is deterministic)

segasai commented 4 years ago

The same error occurs in the master branch. I'll run it now under pdb to get the full backtrace, but I think the sqrtm() is pretty clearly the cause.

joshspeagle commented 4 years ago

Okay, good to know. Thanks for getting the backtrace as well.

segasai commented 4 years ago

Here is the backtrace. it looks like pointvol is very low here. 

ipdb> bt                                                                        
  <ipython-input-3-fdc85590e5f4>(1)<module>()
----> 1 qq.sampler()

  /home/skoposov/science/dipper/qq.py(360)sampler()
    358                                             bound='balls'
    359                                             )
--> 360     dsampler.run_nested(dlogz_init=0.01,
    361                         nlive_init=50,
    362                         nlive_batch=50,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1660)run_nested()
   1658                     # Compute our sampling bounds using the provided
   1659                     # weight function.
-> 1660                     passback = self.add_batch(nlive=nlive_batch,
   1661                                               wt_function=wt_function,
   1662                                               wt_kwargs=wt_kwargs,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1769)add_batch()
   1767                 if logl_bounds is None:
   1768                     logl_bounds = wt_function(res, wt_kwargs)
-> 1769                 for results in self.sample_batch(nlive_new=nlive,
   1770                                                  logl_bounds=logl_bounds,
   1771                                                  maxiter=maxiter,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1132)sample_batch()
   1130             loglmin = min(live_logl)
   1131             if self.sampler._beyond_unit_bound(loglmin):
-> 1132                 bound = self.sampler.update(vol / nblive)
   1133                 if save_bounds:
   1134                     self.sampler.bound.append(copy.deepcopy(bound))

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/nestedsamplers.py(858)update()
    856 
    857         # Update the N-spheres.
--> 858         self.radfriends.update(self.live_u, pointvol=pointvol,
    859                                rstate=self.rstate, bootstrap=self.bootstrap,
    860                                pool=pool)

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(864)update()
    862         if bootstrap == 0.:
    863             # Construct radius using leave-one-out if no bootstraps used.
--> 864             radii = _friends_leaveoneout_radius(points_t, 'balls')
    865         else:
    866             # Bootstrap radius using the set of live points.

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(1674)_friends_leaveoneout_radius()
   1672     # Construct KDTree to enable quick nearest-neighbor lookup for
   1673     # our resampled objects.
-> 1674     kdtree = spatial.KDTree(points)
   1675 
   1676     if ftype == 'balls':

> /home/skoposov/pyenv38/lib/python3.8/site-packages/scipy/spatial/kdtree.py(242)__init__()
    240         self.data = np.asarray(data)
    241         if self.data.dtype.kind == 'c':
--> 242             raise TypeError("KDTree does not work with complex data")
    243 
    244         self.n, self.m = np.shape(self.data)

ipdb> bt                                                                        
  <ipython-input-3-fdc85590e5f4>(1)<module>()
----> 1 qq.sampler()

  /home/skoposov/science/dipper/qq.py(360)sampler()
    358                                             bound='balls'
    359                                             )
--> 360     dsampler.run_nested(dlogz_init=0.01,
    361                         nlive_init=50,
    362                         nlive_batch=50,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1660)run_nested()
   1658                     # Compute our sampling bounds using the provided
   1659                     # weight function.
-> 1660                     passback = self.add_batch(nlive=nlive_batch,
   1661                                               wt_function=wt_function,
   1662                                               wt_kwargs=wt_kwargs,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1769)add_batch()
   1767                 if logl_bounds is None:
   1768                     logl_bounds = wt_function(res, wt_kwargs)
-> 1769                 for results in self.sample_batch(nlive_new=nlive,
   1770                                                  logl_bounds=logl_bounds,
   1771                                                  maxiter=maxiter,

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1132)sample_batch()
   1130             loglmin = min(live_logl)
   1131             if self.sampler._beyond_unit_bound(loglmin):
-> 1132                 bound = self.sampler.update(vol / nblive)
   1133                 if save_bounds:
   1134                     self.sampler.bound.append(copy.deepcopy(bound))

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/nestedsamplers.py(858)update()
    856 
    857         # Update the N-spheres.
--> 858         self.radfriends.update(self.live_u, pointvol=pointvol,
    859                                rstate=self.rstate, bootstrap=self.bootstrap,
    860                                pool=pool)

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(864)update()
    862         if bootstrap == 0.:
    863             # Construct radius using leave-one-out if no bootstraps used.
--> 864             radii = _friends_leaveoneout_radius(points_t, 'balls')
    865         else:
    866             # Bootstrap radius using the set of live points.

  /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(1674)_friends_leaveoneout_radius()
   1672     # Construct KDTree to enable quick nearest-neighbor lookup for
   1673     # our resampled objects.
-> 1674     kdtree = spatial.KDTree(points)
   1675 
   1676     if ftype == 'balls':

> /home/skoposov/pyenv38/lib/python3.8/site-packages/scipy/spatial/kdtree.py(242)__init__()
    240         self.data = np.asarray(data)
    241         if self.data.dtype.kind == 'c':
--> 242             raise TypeError("KDTree does not work with complex data")
    243 
    244         self.n, self.m = np.shape(self.data)

ipdb> up                                                                        
> /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(1674)_friends_leaveoneout_radius()
   1672     # Construct KDTree to enable quick nearest-neighbor lookup for
   1673     # our resampled objects.
-> 1674     kdtree = spatial.KDTree(points)
   1675 
   1676     if ftype == 'balls':

ipdb> locals()                                                                  
{'points': array([[-1.19890506e+09-1.26640997e+09j, -1.00863440e+11+2.41921490e+11j,
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        -3.58442647e+12-4.23069842e+12j, -9.73886370e+09+6.20322318e+09j],
       [-1.19606889e+09-1.26495437e+09j, -1.01547627e+11+2.41744965e+11j,
        -9.93256369e+10+2.80797723e+11j, -4.20988004e+10+2.99767714e+12j,
        -4.41234995e+12-2.94109840e+12j,  1.46977364e+12+1.34610834e+12j,
         1.76993014e+12-1.47478898e+12j, -8.88756378e+10+3.28895465e+10j,
        -5.97791728e+09-3.86622550e+09j, -7.27900505e+12-8.60236930e+11j,
        -3.57066999e+12-4.22635052e+12j, -9.75432119e+09+6.19765648e+09j],
       [-1.19138309e+09-1.26347321e+09j, -1.02031029e+11+2.41695834e+11j,
        -1.00152852e+11+2.80745470e+11j, -4.27572883e+10+2.99812735e+12j,
        -4.42081231e+12-2.93456637e+12j,  1.46809221e+12+1.34842227e+12j,
         1.77001364e+12-1.47305806e+12j, -8.90132416e+10+3.28077124e+10j,
        -5.97708443e+09-3.88022470e+09j, -7.28387687e+12-8.58419595e+11j,
        -3.55085762e+12-4.22336511e+12j, -9.77995847e+09+6.19634075e+09j]]), 'ftype': 'balls'}
ipdb> up                                                                        
> /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/bounding.py(864)update()
    862         if bootstrap == 0.:
    863             # Construct radius using leave-one-out if no bootstraps used.
--> 864             radii = _friends_leaveoneout_radius(points_t, 'balls')
    865         else:
    866             # Bootstrap radius using the set of live points.

ipdb> locals()                                                                  
{'self': <dynesty.bounding.RadFriends object at 0x7f1314923b20>, 'points': array([[6.96495713e-01, 1.54036831e-01, 8.41830509e-01, 5.24293917e-01,
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ipdb> up                                                                        
> /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/nestedsamplers.py(858)update()
    856 
    857         # Update the N-spheres.
--> 858         self.radfriends.update(self.live_u, pointvol=pointvol,
    859                                rstate=self.rstate, bootstrap=self.bootstrap,
    860                                pool=pool)

ipdb> locals()                                                                  
{'self': <dynesty.nestedsamplers.RadFriendsSampler object at 0x7f1314923af0>, 'pointvol': 2.9329479373348894e-65, 'pool': <multiprocessing.pool.Pool state=RUN pool_size=8>}
ipdb> up                                                                        
> /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/nestedsamplers.py(858)update()
    856 
    857         # Update the N-spheres.
--> 858         self.radfriends.update(self.live_u, pointvol=pointvol,
    859                                rstate=self.rstate, bootstrap=self.bootstrap,
    860                                pool=pool)

ipdb> locals()                                                                  
{'self': <dynesty.nestedsamplers.RadFriendsSampler object at 0x7f1314923af0>, 'pointvol': 2.9329479373348894e-65, 'pool': <multiprocessing.pool.Pool state=RUN pool_size=8>}
ipdb> up                                                                        
> /home/skoposov/pyenv38/lib/python3.8/site-packages/dynesty/dynamicsampler.py(1132)sample_batch()
   1130             loglmin = min(live_logl)
   1131             if self.sampler._beyond_unit_bound(loglmin):
-> 1132                 bound = self.sampler.update(vol / nblive)
   1133                 if save_bounds:
   1134                     self.sampler.bound.append(copy.deepcopy(bound))

ipdb> locals()                                                                  
{'self': <dynesty.dynamicsampler.DynamicSampler object at 0x7f1314923400>, 'nlive_new': 50, 'update_interval': None, 'logl_bounds': (10007.820086721591, 10010.636094237829), 'maxiter': 9223372036854768058, 'maxcall': 9223372036854495741, 'save_bounds': True, 'h': 0.0, 'logz': -1e+300, 'logvol': 0.0, 'base_id': array([ 2, 18, 14, ..., 43, 13,  6]), 'base_u': array([[8.54572230e-01, 6.50990619e-01, 5.56838183e-01, ...,
        8.62034783e-01, 8.79231811e-01, 3.86014571e-01],
       [3.60554771e-01, 9.76101205e-01, 4.12361944e-01, ...,
        3.43085923e-02, 3.74763651e-01, 8.27309189e-01],
       [7.88402804e-01, 4.28114213e-01, 5.11364342e-01, ...,
        7.41496536e-01, 9.15710586e-01, 4.97721931e-01],
       ...,
       [6.96213123e-01, 1.52934681e-01, 8.36115852e-01, ...,
        5.04589217e-01, 3.85412539e-05, 6.18468465e-02],
       [6.96561781e-01, 1.53635971e-01, 8.40550199e-01, ...,
        5.04766889e-01, 1.42851935e-04, 2.33129293e-01],
       [6.94133626e-01, 1.53979759e-01, 8.34868007e-01, ...,
        5.04568494e-01, 4.10320727e-05, 3.49673778e-01]]), 'base_v': array([[3.66198610e+01, 8.78192452e-01, 1.74935875e+00, ...,
        5.88962783e+04, 8.79231811e+00, 8.51280828e-04],
       [1.20688062e+00, 9.99428848e-01, 1.29547325e+00, ...,
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       [2.31850700e+01, 6.72946647e-01, 1.60649846e+00, ...,
        5.79319723e+04, 9.15710586e+00, 3.08041801e-03],
       ...,
       [1.22642041e+01, 2.82480345e-01, 2.62673542e+00, ...,
        5.60367137e+04, 3.85412539e-04, 2.03814103e-05],
       [1.22937773e+01, 2.83667931e-01, 2.64066633e+00, ...,
        5.60381351e+04, 1.42851935e-03, 1.46435531e-04],
       [1.20892923e+01, 2.84249751e-01, 2.62281520e+00, ...,
        5.60365480e+04, 4.10320727e-04, 5.60233259e-04]]), 'base_logl': array([-5.89642440e+07, -5.89551581e+07, -5.88195206e+07, ...,
        1.00141217e+04,  1.00141275e+04,  1.00143576e+04]), 'base_n': array([50, 50, 50, ...,  3,  2,  1]), 'base_scale': array([1.        , 1.        , 1.        , ..., 0.23861287, 0.23861287,
       0.23861287]), 'nbase': 7749, 'nblive': 50, 'logl_min': 10007.820086721591, 'logl_max': 10010.636094237829, 'psel': False, 'vol': 1.4664739686674448e-63, 'live_u': array([[6.96495713e-01, 1.54036831e-01, 8.41830509e-01, 5.24293917e-01,
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        4.84168620e-01, 4.42616480e-01, 4.08482739e-01, 9.44078003e-01,
        4.06486390e-01, 5.05673462e-01, 1.42220519e-03, 1.04191337e-01],
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joshspeagle commented 4 years ago

Yes, that's really small. Looks like I need to put in a few more safety checks here to replicate what I've done elsewhere so that if the clustering and covariance estimation breaks down I can either regularize the matrix or just have dynesty revert to feeding in points as normal rather than points_t. Thanks for bringing this to my attention!

joshspeagle commented 3 years ago

I believe the recent improvements to the stability and behaviour of the bounding distributions (#219 and others) that you've implemented should now resolve this, so closing this for now.

ajw278 commented 1 year ago

This is still an issue in the current version of dynesty using 'cubes' as bounds. Not sure if anyone else has found this?

File "/Users/andy/Documents/DustFinder/dustmapper/dmapper.py", line 626, in <module> dmc.fit_model(r_cont=rc, I_cont=Ic, dI_cont=dIc, dI_err=dIc_err, lmbda_cont=1.3,\ File "/Users/andy/Documents/DustFinder/dustmapper/dmapper.py", line 537, in fit_model res = dnst.execute_NS(self, rstart, rend, run=run, Ngauss=Ngauss, dynamic=dynamic, nlive=nlive, nprocs=nprocs) File "/Users/andy/Documents/DustFinder/dustmapper/dsolver_ns.py", line 230, in execute_NS sampler.run_nested(maxiter=max_n,dlogz=1.0, checkpoint_file='dmaps/'+filename+'.save', resume=resume,n_effective=5000, maxcall=1000000) File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dynesty/sampler.py", line 1016, in run_nested for it, results in enumerate( File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dynesty/sampler.py", line 796, in sample bound = self.update() File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dynesty/nestedsamplers.py", line 1018, in update self.supfriends.update(self.live_u[subset, :self.ncdim], File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dynesty/bounding.py", line 1088, in update hsides = _friends_leaveoneout_radius(points_t, 'cubes') File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dynesty/bounding.py", line 1562, in _friends_leaveoneout_radius kdtree = spatial.KDTree(points) File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/scipy/spatial/_kdtree.py", line 340, in __init__ raise TypeError("KDTree does not work with complex data") TypeError: KDTree does not work with complex data

segasai commented 1 year ago

Please file a separate report (see here for information you should include https://github.com/joshspeagle/dynesty/blob/master/.github/ISSUE_TEMPLATE/bug_report.md ) if you see an issue with dynesty 2.1