Comments (3)
Hi, i have the following suggestion until i get around to doing a proper fix.
I just installed and ran PARC with the hybrid umap construction on a clean environment and get it to work by ensuring that 1) numba is version 0.49.1 and 2) umap-learn is 0.4.3
import parc
import matplotlib.pyplot as plt
from sklearn import datasets
iris = datasets.load_iris()
X = iris.data
y = iris.target
p1 = parc.PARC(X, true_label=y, too_big_factor=0.3, resolution_parameter=1, keep_all_local_dist=True)
p1.run_PARC()
print(type(p1.labels), p1.stats_df)
graph = p1.knngraph_full()
X_umap = p1.run_umap_hnsw(X, graph)
plt.scatter(X_umap[:, 0], X_umap[:, 1], c=p1.labels)
plt.show()
plt.scatter(X_umap[:, 0], X_umap[:, 1], c=y)
plt.show()
(ParcEnv2021) shobi@shobi:~$ conda list
packages in environment at /home/shobi/anaconda3/envs/ParcEnv2021:
Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 1_gnu conda-forge
ca-certificates 2021.5.30 ha878542_0 conda-forge
certifi 2021.5.30 py37h89c1867_0 conda-forge
cycler 0.10.0 pypi_0 pypi
hnswlib 0.5.1 pypi_0 pypi
joblib 1.0.1 pypi_0 pypi
kiwisolver 1.3.1 pypi_0 pypi
ld_impl_linux-64 2.35.1 hea4e1c9_2 conda-forge
leidenalg 0.7.0 pypi_0 pypi
libffi 3.3 h58526e2_2 conda-forge
libgcc-ng 9.3.0 h2828fa1_19 conda-forge
libgomp 9.3.0 h2828fa1_19 conda-forge
libstdcxx-ng 9.3.0 h6de172a_19 conda-forge
llvmlite 0.32.1 pypi_0 pypi
matplotlib 3.4.2 pypi_0 pypi
ncurses 6.2 h58526e2_4 conda-forge
numba 0.49.1 pypi_0 pypi
numpy 1.20.3 pypi_0 pypi
openssl 1.1.1k h7f98852_0 conda-forge
pandas 1.2.4 pypi_0 pypi
parc 0.31 pypi_0 pypi
pillow 8.2.0 pypi_0 pypi
pip 21.1.2 pyhd8ed1ab_0 conda-forge
pybind11 2.6.2 pypi_0 pypi
pyparsing 2.4.7 pypi_0 pypi
python 3.7.10 hffdb5ce_100_cpython conda-forge
python-dateutil 2.8.1 pypi_0 pypi
python-igraph 0.9.4 pypi_0 pypi
python_abi 3.7 1_cp37m conda-forge
pytz 2021.1 pypi_0 pypi
readline 8.1 h46c0cb4_0 conda-forge
scikit-learn 0.24.2 pypi_0 pypi
scipy 1.6.3 pypi_0 pypi
setuptools 49.6.0 py37h89c1867_3 conda-forge
six 1.16.0 pypi_0 pypi
sqlite 3.35.5 h74cdb3f_0 conda-forge
tbb 2021.2.0 pypi_0 pypi
texttable 1.6.3 pypi_0 pypi
threadpoolctl 2.1.0 pypi_0 pypi
tk 8.6.10 h21135ba_1 conda-forge
umap-learn 0.4.3 pypi_0 pypi
wheel 0.36.2 pyhd3deb0d_0 conda-forge
xz 5.2.5 h516909a_1 conda-forge
zlib 1.2.11 h516909a_1010 conda-forge
from parc.
These are the commands in a new venv :
conda create --ParcEnv2021 python=3.7
conda install pip
pip install matplotlib
pip install umap-learn==0.4.3
pip install numba==0.49.1
pip install leidenalg #0.7.0 is faster so you could consider using 0.7.0 version for large data
pip install hnswlib
pip install python-igraph
pip install parc
from parc.
Thank you, @ShobiStassen! All is well now.
I received an compilation error when for "pip install leidanalg==0.7.0" but "pip install leidanalg" worked fine. It gave me 0.8.4. I did see your inquiry here: vtraag/leidenalg#35
It seems they fixed the slow down issue??
from parc.
Related Issues (19)
- any plan to release an R version of PARC? HOT 4
- Tips for replicating the performance on the lung cell clustering HOT 3
- Relaxation of leidenalg==0.7.0 requirement? HOT 2
- About the true labels for calculating the F1 scores HOT 2
- Question on pruning big cluster HOT 2
- Python igraph HOT 4
- Hello! I am getting AttributeError, when trying to import parc HOT 2
- RStudio crashing when clustering a large dataset HOT 12
- Questions on using PARC for identifying plasma cells HOT 1
- Hyperclustering with PARC HOT 1
- Import of umap increases PARC import time HOT 1
- Minor bug in run_toobig_subPARC
- pip install issue: Mac OS X and AWS Linux HOT 3
- np.reshape error if too many edges are pruned HOT 1
- Example Usage 2 has some code typos HOT 2
- Bugs in Example Usage 3 HOT 2
- Amazing work! HOT 6
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from parc.