Comments (16)
lmcinnes
commented on April 28, 2024
2
I think the problem is that that should be sigmas[k] instead, but I'll have to trace through the whole thing to be sure.
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lmcinnes
commented on April 28, 2024
Thanks for detailed bug report! This may be the same as issue #33. I believe the latest master version should have fixed this, but I haven't put out a release on pip yet (waiting to roll a few more bug fixes and features together). If you have time to clone the master branch from github and install it (after removing the old pip version) and try that instead I would appreciate it. I believe it should fix the issue you are seeing, and if it doesn't then I clearly have a little more work to do.
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duhaime
commented on April 28, 2024
@lmcinnes thanks for your quick response. It seems the problem has been resolved on master. I've run several dozen runs since reinstalling and haven't hit the division by zero error, so I think it should be safe to close this issue. Thanks again for this great work!
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lmcinnes
commented on April 28, 2024
Thanks for checking that out so fast.
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100518832
commented on April 28, 2024
I am running to zero division errors every couple of runs, I am using CentOS, and spyder (py 3.6).
runfile('/home/anaconda3/envs/ML/scripts/beta_projects/umap_test.py', wdir='/home/anaconda3/envs/ML/scripts/beta_projects')
File "/home/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "/home/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "/home/anaconda3/envs/ML/scripts/beta_projects/umap_test.py", line 83, in <module>
embedding = umap.UMAP(n_neighbors = ideal_model['n_neighbors'], min_dist = ideal_model['min_dist'], metric = ideal_model['metric_iso'], n_components = 3).fit_transform(input_data)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 1402, in fit_transform
self.fit(X)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 1361, in fit
self.verbose
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 385, in rptree_leaf_array
angular=angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 310, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 315, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 310, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 310, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 310, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 310, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 315, in make_tree
angular)
File "/home/anaconda3/lib/python3.6/site-packages/umap/umap_.py", line 301, in make_tree
rng_state)
ZeroDivisionError: division by zero ```
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duhaime
commented on April 28, 2024
@100518832 did you git clone from master then run python setup.py install inside the directory to install the library? The latest release on PYPI (0.1.5) still has this problem I believe, so if you pip installed you may be affected, but if you run the setup.py install this should clear up...
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100518832
commented on April 28, 2024
@duhaime, I do not recall running the python setup.py install; however, I will try this. Also, I have noticed that I only get a zero division error with the following three argument parameters.
Embedding Failed - info: 15, 0.01, correlation
Embedding Failed - info: 15, 0.05, correlation
Embedding Failed - info: 20, 0.01, correlation
Here are all the parameters I am currently testing through
n_neighbors = [15,20,40]
min_dist = [0.01,0.05]
metric_iso = ['correlation','euclidean','manhattan']
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duhaime
commented on April 28, 2024
@100518832 I'd try installing from the repo's setup.py file, as the fixes for the div by zero problem are on master but not Pypi...
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paxtonfitzpatrick
commented on April 28, 2024
I'm now getting this error with the inverse_transform method. I'm using the code in the repo's master branch, at the 0.4rc1 tag (fc59aa7)
Code:
import numpy as np
from umap import UMAP
to_reduce = np.vstack(data) # shape: (1137, 25); dtype: 'float64')
np.random.seed(0)
reducer = UMAP(random_state=0).fit(to_reduce)
embeddings = reducer.transform(to_reduce)
# create a 2D grid over the embedding space
resolution = 50
x_min, y_min = embeddings.min(axis=0) // 1
x_max, y_max = embeddings.max(axis=0) // 1 + 1
x_step = (x_max - x_min) / resolution
y_step = (y_max - y_min) / resolution
xs = np.arange(x_min, x_max, x_step)
ys = np.arange(y_min, y_max, y_step)
X, Y = np.meshgrid(xs, ys)
xy_grid = np.empty((resolution, resolution, 2), dtype=np.float64)
for (x_ix, y_ix), X_val in np.ndenumerate(X):
xy_grid[x_ix, y_ix] = (X_val, Y[x_ix, y_ix])
# recover vector in original space for each gridpoint
vertices = xy_grid.reshape(resolution**2, 2)
np.random.seed(0)
high_dim_vertices = reducer.inverse_transform(vertices)
high_dim_grid = high_dim_vertices.reshape(resolution, resolution, 25)
Traceback:
ZeroDivisionError Traceback (most recent call last)
<ipython-input-127-93accc0c2718> in <module>
1 # recover vector in original space for each gridpoint
2 np.random.seed(0)
----> 3 high_dim_vertices = reducer.inverse_transform(vertices)
4 high_dim_grid = high_dim_vertices.reshape(resolution, resolution, 25)
/opt/conda/lib/python3.7/site-packages/umap/umap_.py in inverse_transform(self, X)
2203 _input_distance_func,
2204 tuple(self._metric_kwds.values()),
-> 2205 verbose=self.verbose,
2206 )
2207
ZeroDivisionError: division by zero
At first I thought it was related to #33 because I can get the error to go away by setting min_dist sufficiently high (~.5), which makes the 2D grid points spread out enough that they wouldn't get rounded off to the same value as float32's. But now I'm not so sure, because I still get the error if I do
vertices += np.random.uniform(-10, 10, vertices.shape)
before inverse_transforming them. Any help would be greatly appreciated!!
Additional info:
numpy==1.16.5
sklearn==0.21.3
scipy==1.2.1
numba==0.45.1
tbb==2020.0.133
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lmcinnes
commented on April 28, 2024
This is somewhat disconcerting, and it is non-obvious to me where exactly this could be occurring. One thing you could try, presuming the compute isn't too expensive, is turning of the numba compilation of the inverse transform related functions and running again -- that way we can get a stack trace to the exact location of the error.
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paxtonfitzpatrick
commented on April 28, 2024
So the actual error is coming from here, in optimize_layout_inverse. At least for me, it's happening when more data points are inverse transformed than were used to fit the model. To compute grad_coeff, the jth item from sigmas is used. But is sigmas is the distance to the kth nearest neighbor for each data point used to fit the model, so it has self._raw_data.shape[0] entries. Meanwhile j is row indices of the adjacency matrix for the 1-skeleton of the inverse_transformed data.
Traceback is kinda weird-looking since I ran it through the Pycharm debugger, but here it is:
Traceback (most recent call last):
File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 2060, in <module>
main()
File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 2054, in main
globals = debugger.run(setup['file'], None, None, is_module)
File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1405, in run
return self._exec(is_module, entry_point_fn, module_name, file, globals, locals)
File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1412, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "/Applications/PyCharm.app/Contents/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/Users/paxtonfitzpatrick/Documents/Dartmouth/CDL/umap/debugging.py", line 79, in <module>
topic_space_grid = reducer.inverse_transform(vertices)
File "/Users/paxtonfitzpatrick/Documents/Dartmouth/CDL/umap/umap/umap_.py", line 2270, in inverse_transform
verbose=self.verbose,
File "/Users/paxtonfitzpatrick/Documents/Dartmouth/CDL/umap/umap/layouts.py", line 510, in optimize_layout_inverse
grad_coeff = -(1 / (w_l * sigmas[j] + 1e-6))
IndexError: index 1172 is out of bounds for axis 0 with size 1137
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paxtonfitzpatrick
commented on April 28, 2024
That did it! And that makes sense based on how grad_coeff is computed just below that... Thanks so much!
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lmcinnes
commented on April 28, 2024
Can I assume that this will arrive with your upcoming PR, or should I fix it and push it myself?
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paxtonfitzpatrick
commented on April 28, 2024
I changed it on my fork, so it'll get included in my PR. I'm ready to submit that today btw -- just want to confirm about what I commented on #367
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lmcinnes
commented on April 28, 2024
Excellent -- I'm looking forward to it. Thanks for all your hard work on this!
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o1lo01ol1o
commented on April 28, 2024
Any update on this? I have a dataset that seems to be throwing it when the size of the data is large.
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