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View Code? Open in Web Editor NEWtopological data analysis of population-scale microbiomes
Home Page: https://tmap.readthedocs.org
License: GNU General Public License v3.0
topological data analysis of population-scale microbiomes
Home Page: https://tmap.readthedocs.org
License: GNU General Public License v3.0
When I run the script of "Network_generator.py" or "SAFE_analysis.py", I met this report:
Import Error: cannot import name 'gcd' from 'fractions'
But when I want to troubleshoot that, others who also meet this error claimed that I should update the "networkx" to โฅ 2.5.1.
https://stackoverflow.com/questions/66174862/import-error-cant-import-name-gcd-from-fractions
https://stackoverflow.com/questions/67165725/ubuntu-error-cannot-import-name-gcd-from-fractions
However the tmap 1.2 requires networkx=2.2. I am very confused about this bug.
Hope you help me with that.
In the starter scripts of tmap, I get the error, "y contains previously unseen labels"
show(data=X, graph=graph, color=color, fig_size=(10, 10), node_size=15, mode='spring', strength=0.04)
C:\intelpython3\lib\site-packages\numpy\lib\arraysetops.py:518: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
mask &= (ar1 != a)
Traceback (most recent call last):
File "C:\intelpython3\lib\site-packages\IPython\core\interactiveshell.py", line 2963, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
show(data=X, graph=graph, color=color, fig_size=(10, 10), node_size=15, mode='spring', strength=0.04)
File "C:\intelpython3\lib\site-packages\tmap-1.0-py3.6.egg\tmap\tda\plot.py", line 201, in show
label_color = legend_lookup.get(color.label_encoder.transform([label])[0], None)
File "C:\intelpython3\lib\site-packages\sklearn\preprocessing\label.py", line 257, in transform
_, y = encode(y, uniques=self.classes, encode=True)
File "C:\intelpython3\lib\site-packages\sklearn\preprocessing\label.py", line 110, in _encode
return _encode_numpy(values, uniques, encode)
File "C:\intelpython3\lib\site-packages\sklearn\preprocessing\label.py", line 53, in _encode_numpy
% str(diff))
ValueError: y contains previously unseen labels: [0]
Consolidated script (from https://tmap.readthedocs.io/en/latest/basic.html) is:
from sklearn.cluster.dbscan_ import DBSCAN
from sklearn.preprocessing.data import MinMaxScaler, StandardScaler
from sklearn.preprocessing.data import *
from sklearn import datasets
import pandas as pd
iris = datasets.load_iris()
X = iris.data
X = pd.DataFrame(X,columns = iris.feature_names)
from tmap.tda import mapper, filter
from tmap.tda.cover import Cover
tm = mapper.Mapper(verbose=1)
lens = [filter.MDS(components=[0, 1])]
projected_X = tm.filter(X, lens=lens)
clusterer = DBSCAN(eps=0.75, min_samples=1)
cover = Cover(projected_data=MinMaxScaler().fit_transform(projected_X), resolution=20, overlap=0.75)
graph = tm.map(data=StandardScaler().fit_transform(X), cover=cover, clusterer=clusterer)
from tmap.tda.plot import show, Color
y = iris.target
color = Color(target=y, dtype="categorical")
show(data=X, graph=graph, color=color, fig_size=(10, 10), node_size=15, mode='spring', strength=0.04)
Hi,
I am having little difficulty in running "from tmap.tda import mapper, Filter" on python 3.10.
In Python 3.6 the code works perfectly fine.
I believe the problem is happening due to collections package as the Mapping is moved to collections.abc from collections. I changed that in my code.
Still the error is happening:
Importerror: cannot import name Mapping from collections (...../lib/python3.10/collections/init.py
Any idea how to fix it? Does Tmap run on python 3.10?
After updating tmap
, I'm unable to import filter
. E.g. following the "Basic usage" example:
In [3]: from tmap.tda import mapper, filter
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-3-dbbed40b8ed5> in <module>
----> 1 from tmap.tda import mapper, filter
ImportError: cannot import name 'filter'
What am I doing wrong?
3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34) [GCC 7.3.0]
tmap 1.1.3, installed via pip
Hi GPZ-Bioinfo,
I am experiencing a long runtime for pairwise_coenrichment. It appears that it will take 7 days to run on my data.
My data set is 714 samples by 1049 genus.The graph is 450 nodes.
I reduced the data set from 26000 OTU to 1049 genus in the hope of getting this running in a shorter time. Does this long runtime seem reasonable?
I see that there is a function called tmap.netx.coenrichment_analysis.coenrichment_for_nodes
that can do coenrichment for specified nodes and features. However there is no example of its use in the docs or in tmap_notebook.
Do you have a recommendation for its use?
Bye
parsifal9
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