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Exiting the context manager cleans up files in tmp #2

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e0cbc5d
exiting cm cleans up files in tmp
HekpoMaH Jun 27, 2022
85b5efa
move to the non-deprecated way of handling files
HekpoMaH Jun 27, 2022
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6 changes: 4 additions & 2 deletions scGeneFit/data_files/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,12 @@

import scipy.io
try:
import importlib.resources as importlib_resources
except ImportError:
# In PY<3.7 fall-back to backported `importlib_resources`.
import importlib_resources

def get_data(filename):
with importlib_resources.path(__name__, filename) as foo:
return str(foo)
src = importlib_resources.files(__name__).joinpath(filename)
with importlib_resources.as_file(src) as foo:
return scipy.io.loadmat(str(foo))
14 changes: 7 additions & 7 deletions scGeneFit/functions.py
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Expand Up @@ -358,40 +358,40 @@ def performance(self, markers):

def load_example_data(name):
if name=="CITEseq":
a = scipy.io.loadmat(data_files.get_data("CITEseq.mat"))
a = data_files.get_data("CITEseq.mat")
data= a['G'].T
N,d=data.shape
#transformation from integer entries
data=np.log(data+np.ones(data.shape))
for i in range(N):
data[i,:]=data[i,:]/np.linalg.norm(data[i,:])
#load labels from file
a = scipy.io.loadmat(data_files.get_data("CITEseq-labels.mat"))
a = data_files.get_data("CITEseq-labels.mat")
l_aux = a['labels']
labels = np.array([i for [i] in l_aux])
#load names from file
a = scipy.io.loadmat(data_files.get_data("CITEseq_names.mat"))
a = data_files.get_data("CITEseq_names.mat")
names=[a['citeseq_names'][i][0][0] for i in range(N)]
return [data, labels, names]
elif name=="zeisel":
#load data from file
a = scipy.io.loadmat(data_files.get_data("zeisel_data.mat"))
a = data_files.get_data("zeisel_data.mat")
data= a['zeisel_data'].T
N,d=data.shape

#load labels (first level of the hierarchy) from file
a = scipy.io.loadmat(data_files.get_data("zeisel_labels1.mat"))
a = data_files.get_data("zeisel_labels1.mat")
l_aux = a['zeisel_labels1']
l_0=[l_aux[i][0] for i in range(l_aux.shape[0])]
#load labels (second level of the hierarchy) from file
a = scipy.io.loadmat(data_files.get_data("zeisel_labels2.mat"))
a = data_files.get_data("zeisel_labels2.mat")
l_aux = a['zeisel_labels2']
l_1=[l_aux[i][0] for i in range(l_aux.shape[0])]
#construct an array with hierarchy labels
labels=np.array([l_0, l_1])

# load names from file
a = scipy.io.loadmat(data_files.get_data("zeisel_names.mat"))
a = data_files.get_data("zeisel_names.mat")
names0=[a['zeisel_names'][i][0][0] for i in range(N)]
names1=[a['zeisel_names'][i][1][0] for i in range(N)]
return [data, labels, [names0,names1]]
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