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View Code? Open in Web Editor NEWUniform Manifold Approximation with Two-phase Optimization (IEEE VIS 2022 short)
License: MIT License
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jd330 hj-n wtwong316 jeffhsu3 dfrntl abhisheka456 techthiyanes hunrotation syphonarch taehyun2017330 olayinkaadeleye gs18004umato's Issues
Example not working and mismatch between embedd and real data.
Hi. After to install manually the package (it is not longer available on pip) and try to run the example. This example doesn't work.
When I try UMATO with my data, I received this msg:
ValueError: total data # (26170) != total embedded # (26109)!
I want to compare with the example in the README to find out what it is the problem.
I hope you can help me.
Bests,
README iris example doesn't work
Hello, first of all, thank you for the paper and package which I have enjoyed studying.
The README example:
import umato
from sklearn.datasets import load_iris
X, y = load_iris(return_X_y=True)
emb = umato.UMATO(hub_num=300).fit_transform(X)unfortunately gives a ValueError with the current version on PyPI (0.1.1):
ValueError: hub_num must be less than the number of data points
Which makes sense because there are only 150 items in the iris dataset. Unfortunately, I couldn't find a setting of n_neighbors and hub_num which gave a nice layout with other default parameters. Any suggestions for good values with smaller data?
Also, there is a minor typo in the README section about the init parameter: randobm should be random.
UMATO not in PyPi?
Current error:
ERROR: Could not find a version that satisfies the requirement umato (from versions: none)
ERROR: No matching distribution found for umato
Test and Benchmark Scripts not working
Hi!
I downloaded the repository, installed via install.py and tried to run the test.py benchmark.sh and visual benchmarks. Unfortunately none of them worked out of the box on my system. Running python 3.10 via miniconda on M1 mac.
test.py has a problem with numba's function caching:
Traceback (most recent call last):
File "/Users/nf/Python/umato/test.py", line 1, in <module>
import umato
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/umato-0.0.4-py3.10.egg/umato/__init__.py", line 1, in <module>
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/umato-0.0.4-py3.10.egg/umato/umato_.py", line 28, in <module>
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/umato-0.0.4-py3.10.egg/umato/sparse.py", line 10, in <module>
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/umato-0.0.4-py3.10.egg/umato/utils.py", line 698, in <module>
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/numba/core/decorators.py", line 212, in wrapper
disp.enable_caching()
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/numba/core/dispatcher.py", line 863, in enable_caching
self._cache = FunctionCache(self.py_func)
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/numba/core/caching.py", line 601, in __init__
self._impl = self._impl_class(py_func)
File "/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/numba/core/caching.py", line 337, in __init__
raise RuntimeError("cannot cache function %r: no locator available "
RuntimeError: cannot cache function 'rdist': no locator available for file '/Users/nf/miniconda3/envs/umato/lib/python3.10/site-packages/umato-0.0.4-py3.10.egg/umato/utils.pyWhen running run-benchmark.sh, the whole script is running but complains about missing module specifications for all the methods and no results are shown:
/Users/nf/miniconda3/envs/umato/bin/python: Error while finding module specification for 'evaluation.models.umap' (ModuleNotFoundError: No module named 'evaluation')When running the svelte app for visual benchmarking as instructed:
Error: Package subpath './compiler.js' is not defined by "exports" in /Users/nf/Python/umato/visualization/node_modules/svelte/package.jsonConda environment:
conda list
# packages in environment at /Users/nikofleischer/miniconda3/envs/umato:
#
# Name Version Build Channel
anyio 3.6.2 pypi_0 pypi
appnope 0.1.3 pypi_0 pypi
argon2-cffi 21.3.0 pypi_0 pypi
argon2-cffi-bindings 21.2.0 pypi_0 pypi
asttokens 2.0.8 pypi_0 pypi
attrs 22.1.0 pypi_0 pypi
babel 2.10.3 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
beautifulsoup4 4.11.1 pypi_0 pypi
bleach 5.0.1 pypi_0 pypi
bokeh 2.4.3 pypi_0 pypi
bzip2 1.0.8 h3422bc3_4 conda-forge
ca-certificates 2022.9.24 h4653dfc_0 conda-forge
certifi 2022.9.24 pypi_0 pypi
cffi 1.15.1 pypi_0 pypi
charset-normalizer 2.1.1 pypi_0 pypi
click 8.1.3 pypi_0 pypi
cloudpickle 2.2.0 pypi_0 pypi
colorcet 3.0.1 pypi_0 pypi
contourpy 1.0.5 pypi_0 pypi
cycler 0.11.0 pypi_0 pypi
dask 2022.10.0 pypi_0 pypi
datashader 0.14.2 pypi_0 pypi
datashape 0.5.2 pypi_0 pypi
debugpy 1.6.3 pypi_0 pypi
decorator 5.1.1 pypi_0 pypi
defusedxml 0.7.1 pypi_0 pypi
distributed 2022.10.0 pypi_0 pypi
entrypoints 0.4 pypi_0 pypi
executing 1.1.1 pypi_0 pypi
fastjsonschema 2.16.2 pypi_0 pypi
fcsparser 0.2.4 pypi_0 pypi
fonttools 4.37.4 pypi_0 pypi
fsspec 2022.10.0 pypi_0 pypi
heapdict 1.0.1 pypi_0 pypi
holoviews 1.15.1 pypi_0 pypi
idna 3.4 pypi_0 pypi
ipykernel 6.16.1 pypi_0 pypi
ipython 8.5.0 pypi_0 pypi
ipython-genutils 0.2.0 pypi_0 pypi
jedi 0.18.1 pypi_0 pypi
jinja2 3.1.2 pypi_0 pypi
joblib 1.2.0 pyhd8ed1ab_0 conda-forge
json5 0.9.10 pypi_0 pypi
jsonschema 4.16.0 pypi_0 pypi
jupyter-client 7.4.3 pypi_0 pypi
jupyter-core 4.11.2 pypi_0 pypi
jupyter-server 1.21.0 pypi_0 pypi
jupyterlab 3.4.8 pypi_0 pypi
jupyterlab-pygments 0.2.2 pypi_0 pypi
jupyterlab-server 2.16.1 pypi_0 pypi
kiwisolver 1.4.4 pypi_0 pypi
libblas 3.9.0 16_osxarm64_openblas conda-forge
libcblas 3.9.0 16_osxarm64_openblas conda-forge
libcxx 14.0.6 h2692d47_0 conda-forge
libffi 3.4.2 h3422bc3_5 conda-forge
libgfortran 5.0.0 11_3_0_hd922786_25 conda-forge
libgfortran5 11.3.0 hdaf2cc0_25 conda-forge
liblapack 3.9.0 16_osxarm64_openblas conda-forge
libllvm11 11.1.0 hfa12f05_4 conda-forge
libopenblas 0.3.21 openmp_hc731615_3 conda-forge
libsqlite 3.39.4 h76d750c_0 conda-forge
libzlib 1.2.13 h03a7124_4 conda-forge
llvm-openmp 14.0.4 hd125106_0 conda-forge
llvmlite 0.39.1 py310h1e34944_0 conda-forge
locket 1.0.0 pypi_0 pypi
markdown 3.4.1 pypi_0 pypi
markupsafe 2.1.1 pypi_0 pypi
matplotlib 3.6.1 pypi_0 pypi
matplotlib-inline 0.1.6 pypi_0 pypi
mistune 2.0.4 pypi_0 pypi
msgpack 1.0.4 pypi_0 pypi
multipledispatch 0.6.0 pypi_0 pypi
nbclassic 0.4.5 pypi_0 pypi
nbclient 0.7.0 pypi_0 pypi
nbconvert 7.2.2 pypi_0 pypi
nbformat 5.7.0 pypi_0 pypi
ncurses 6.3 h07bb92c_1 conda-forge
nest-asyncio 1.5.6 pypi_0 pypi
notebook 6.5.1 pypi_0 pypi
notebook-shim 0.2.0 pypi_0 pypi
npm 0.1.1 pypi_0 pypi
numba 0.56.3 py310h3124f1e_0 conda-forge
numpy 1.23.4 py310h5d7c261_0 conda-forge
openssl 3.0.5 h03a7124_2 conda-forge
optional-django 0.1.0 pypi_0 pypi
packaging 21.3 pypi_0 pypi
pandas 1.5.1 py310h2b830bf_0 conda-forge
pandocfilters 1.5.0 pypi_0 pypi
panel 0.14.0 pypi_0 pypi
param 1.12.2 pypi_0 pypi
parso 0.8.3 pypi_0 pypi
partd 1.3.0 pypi_0 pypi
pexpect 4.8.0 pypi_0 pypi
pickleshare 0.7.5 pypi_0 pypi
pillow 9.2.0 pypi_0 pypi
pip 22.3 pyhd8ed1ab_0 conda-forge
prometheus-client 0.15.0 pypi_0 pypi
prompt-toolkit 3.0.31 pypi_0 pypi
psutil 5.9.3 pypi_0 pypi
ptyprocess 0.7.0 pypi_0 pypi
pure-eval 0.2.2 pypi_0 pypi
pycparser 2.21 pypi_0 pypi
pyct 0.4.8 pypi_0 pypi
pygments 2.13.0 pypi_0 pypi
pynndescent 0.5.7 pypi_0 pypi
pyparsing 3.0.9 pypi_0 pypi
pyrsistent 0.18.1 pypi_0 pypi
python 3.10.6 hae75cb6_0_cpython conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python_abi 3.10 2_cp310 conda-forge
pytz 2022.5 pyhd8ed1ab_0 conda-forge
pyviz-comms 2.2.1 pypi_0 pypi
pyyaml 6.0 pypi_0 pypi
pyzmq 24.0.1 pypi_0 pypi
readline 8.1.2 h46ed386_0 conda-forge
requests 2.28.1 pypi_0 pypi
scikit-learn 1.1.2 py310h3d7afdd_0 conda-forge
scipy 1.9.2 py310ha0d8a01_0 conda-forge
send2trash 1.8.0 pypi_0 pypi
setuptools 65.5.0 pyhd8ed1ab_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
sniffio 1.3.0 pypi_0 pypi
sortedcontainers 2.4.0 pypi_0 pypi
soupsieve 2.3.2.post1 pypi_0 pypi
stack-data 0.5.1 pypi_0 pypi
tblib 1.7.0 pypi_0 pypi
terminado 0.16.0 pypi_0 pypi
threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge
tinycss2 1.2.1 pypi_0 pypi
tk 8.6.12 he1e0b03_0 conda-forge
tomli 2.0.1 pypi_0 pypi
toolz 0.12.0 pypi_0 pypi
tornado 6.1 pypi_0 pypi
tqdm 4.64.1 pypi_0 pypi
traitlets 5.5.0 pypi_0 pypi
typing-extensions 4.4.0 pypi_0 pypi
tzdata 2022e h191b570_0 conda-forge
umap-learn 0.5.3 pypi_0 pypi
urllib3 1.26.12 pypi_0 pypi
wcwidth 0.2.5 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
websocket-client 1.4.1 pypi_0 pypi
wget 3.2 pypi_0 pypi
wheel 0.37.1 pyhd8ed1ab_0 conda-forge
xarray 2022.10.0 pypi_0 pypi
xz 5.2.6 h57fd34a_0 conda-forge
zict 2.2.0 pypi_0 pypi```Issue for a README figure
MNIST: ValueError
There's an issue when running umato on MNIST dataset.
import umato
from sklearn.datasets import fetch_openml
mnist = fetch_openml("mnist_784", version=1)
X = mnist.data
emb = umato.UMATO(hub_num=20).fit_transform(X)results in
ValueError: total data # (70000) != total embedded # (69992)!Recommend Projects
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