Comments (16)
@CoriPegliasco in your case x & y are empty array...
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Must be solved now
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Inside method return for each given position if there are in one eddy of the list (you get an array of boolean).
So you could imagine use like this:
mask = a1.inside(x=df.longitude.values.astype('f8'), y=df.latitude.values.astype('f8'))
obs_inside = df[mask]
To get parameters of eddy which enclosed Insitu observation, use contains method which will return index of a1 observations (-1 in case of insitu obs are not enclosed by eddy) instead of a boolean:
index_eddy = a1.contains(x=df.longitude.values.astype('f8'), y=df.latitude.values.astype('f8'))
mask = index_eddy != -1
insitu_inside = df[mask]
eddy_lat_which_enclosed_insitu = a1.lat[index_eddy[mask]]
from py-eddy-tracker.
Thanks! Somehow, the last line in the following induces a segmentation fault, and I can't find the dumped core to give additional information..
for d in range(dmin,dmax):
a1=ta1.extract_with_period((d,d))
dfsub = df[df["time"]==d]
mask = a1.inside(x=dfsub.longitude.values.astype('f8'), y=dfsub.latitude.values.astype('f8'))
if any(mask):
print(d)
index_eddy = a1.contains(x=dfsub.longitude.values.astype('f8'), y=dfsub.latitude.values.astype('f8'))
from py-eddy-tracker.
All your longitude and latitude are valid? Could you share min/max? You could also skip mask computation and use directly contains to avoid double computation.
from py-eddy-tracker.
They are valid, but generally contain only 1 element.
print(dfsub.longitude.values.astype('f8'))
print(dfsub.latitude.values.astype('f8'))
works fine below the if part above
from py-eddy-tracker.
Which version of py eddy tracker did you use?
from py-eddy-tracker.
I updated everything (pull, re-install) two days ago, and used the overlap tracker (but that was before, though, the tracking files were produced some months ago)
from py-eddy-tracker.
Hi,
I also have an issue with contains
(on the latest version)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-33-d13a49993c9c> in <module>
7 dissociate_network=True,
8 correct_close_events=45,
----> 9 remove_dead_end=14
10 )
--/dev/py-eddy-tracker/src/py_eddy_tracker/observations/network.py in analysis_coherence(self, date_function, uv_params, advection_mode, dt_advect, step_mesh, output_name, dissociate_network, correct_close_events, remove_dead_end)
1368 output_name=output_name,
1369 dt_advect=dt_advect,
-> 1370 step_mesh=step_mesh,
1371 )
1372
--/dev/py-eddy-tracker/src/py_eddy_tracker/observations/network.py in segment_coherence(self, date_function, uv_params, advection_mode, dt_advect, step_mesh, output_name)
1496 i_target_b,
1497 pct_target_b,
-> 1498 n_days=-dt_advect,
1499 )
1500
--/dev/py-eddy-tracker/src/py_eddy_tracker/observations/groups.py in particle_candidate(x, y, c, eddies, t_start, i_target, pct, **kwargs)
121 translate_end = where(m_end)[0]
122 # Id eddies for each alive particle (in core and extern)
--> 123 i_end = e_end.contains(x, y)
124 # compute matrix and fill target array
125 get_matrix(i_start, i_end, translate_start, translate_end, i_target, pct)
--/dev/py-eddy-tracker/src/py_eddy_tracker/observations/observation.py in contains(self, x, y, intern)
2057 m = ~(isnan(x) + isnan(y))
2058 i = -ones(x.shape, dtype="i4")
-> 2059 i[m] = poly_indexs(x[m], y[m], self[xname], self[yname])
2060 return i
2061
~/.conda/envs/eddy37/lib/python3.7/site-packages/numba/np/arraymath.py in array_min_impl()
533 def array_min_impl(arry):
534 if arry.size == 0:
--> 535 raise ValueError(MSG)
536
537 it = np.nditer(arry)
ValueError: zero-size array to reduction operation minimum which has no identity
Could it be because I have longitudes between [-180°, 180°] and poly_indexs is waiting for [0°, 360°]?
Thus the validity for longitudes is ok if >0 ?
from py-eddy-tracker.
ok @acapet, i do some update to speed up poly_index few month ago, maybe it's a side effect ..., to understand the problem i will need a Minimal Working Example, if you are ok, you could create like that:
import pickle
a1.write_file(filename="eddy.nc")
x, y = dfsub.longitude.values.astype('f8'), dfsub.latitude.values.astype('f8')
with open("insitu_position.pkl", "wb") as pkl:
pickle.dump((x,y), pkl)
a1.contains(x=x, y=y)
from py-eddy-tracker.
The error and associated files
from py_eddy_tracker.observations.network import NetworkObservations
import pickle
n = NetworkObservations.load_file("obs_error.nc")
with open("test_particles", "rb") as pkl:
x,y= pickle.load(pkl)
i_end = n.contains(x, y)
from py-eddy-tracker.
Here are the files for the minimal example :
I have to mention that the fail is not systematic, which makes it even stranger.
Executing the following goes fine sometimes, but fails at some point if I repeat ~5-10 times.
from py_eddy_tracker.observations.network import NetworkObservations
import pickle
n = NetworkObservations.load_file("./ProfileCollocationFail/eddy.nc")
with open("./ProfileCollocationFail/insitu_position.pkl", "rb") as pkl:
x,y= pickle.load(pkl)
i_end = n.contains(x, y)
from py-eddy-tracker.
So, it's due to a specific case, which give a bad index and sometime this index is in a forbidden area...
I didn't notice this wrong indexing/code due too a numba silence (numba/numba#7045).
I will release a patch soon.
from py-eddy-tracker.
Ok. If I got this right, the problem is due to applying the method when applied on small sets (with one eddy, or one profile).
This arises from the fact that I loop on individual days, which is necessary for matching eddies and external data since "contains" only considers lon and lat, and not time.
I guess the patch will totally do for me. If that goes further, one could of a version of "contain" including the time dimension.
from py-eddy-tracker.
This arises from the fact that I loop on individual days, which is necessary for matching eddies and external data since "contains" only considers lon and lat, and not time
It come when you call contains with one or two observations to compare with eddies.
Root problem come from a bad code which was silent. So i will re-wrote it.
And this root problem is in a method which are use in several other method...
If that goes further, one could of a version of "contain" including the time dimension.
I am not pro to do that, because you must manage time sampling which could be different between your eddies and other observations. My opinion is : it's best that user manage explicitly time coherence.
Maybe, it could be build with iter_on method.
from py-eddy-tracker.
Works like a charm, thank you!
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