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Add an option to plot legends on ROC curve #49

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Add an option to plot legends on ROC curve #49

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d75d37f
update __init__.py
YY-SONG0718 Feb 11, 2022
5ef1009
add legend to plot_roc in __init__.py
YY-SONG0718 Mar 20, 2022
7024b41
add legend
YY-SONG0718 Sep 21, 2022
f841eb3
add option for plotting legend in plot_roc
YY-SONG0718 Sep 21, 2022
c2eea91
add option for plotting legend in plot_roc
YY-SONG0718 Sep 21, 2022
9ea9755
add option for plotting legend in plot_roc
YY-SONG0718 Sep 21, 2022
50efca6
update scanpy version
YY-SONG0718 Oct 26, 2023
05fcfca
space for indent
YY-SONG0718 Oct 27, 2023
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15 changes: 10 additions & 5 deletions SCCAF/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -694,7 +694,8 @@ def SCCAF_optimize(ad,
dist_cutoff=8,
classifier="LR",
mplotlib_backend=None,
min_acc=1):
min_acc=1,
legend=False):
"""
This is a self-projection confusion matrix directed cluster optimization function.

Expand Down Expand Up @@ -767,6 +768,8 @@ def SCCAF_optimize(ad,
PdfPages).
min_acc: `float`
the minimum total accuracy to be achieved. Above this threshold, the optimization will stop.
legend: `bool` optional (default: False)
If also plot legend for the ROC curve.

return
-----
Expand All @@ -782,7 +785,7 @@ def SCCAF_optimize(ad,
raise ValueError("`adata.obsm['X_pca']` doesn't exist. Run `sc.pp.pca` first.")
X = ad.obsm['X_pca']
elif 'X_%s'%use in ad.obsm.dtype.fields:
X = ad.obsm['X_%s'%use]
X = ad.obsm['X_%s'%use]
else:
X = ad[:,ad.var['highly_variable']].X

Expand All @@ -801,7 +804,7 @@ def SCCAF_optimize(ad,
ad.obs['%s_self-projection' % old_id] = clf.predict(X)

if plot:
aucs = plot_roc(y_prob, y_test, clf, cvsm=cvsm, acc=acc, title="Self-project ROC {}".format(old_id))
aucs = plot_roc(y_prob, y_test, clf, cvsm=cvsm, acc=acc, title="Self-project ROC {}".format(old_id), legend=legend)
if mplotlib_backend:
mplotlib_backend.savefig()
plt.clf()
Expand Down Expand Up @@ -1017,7 +1020,7 @@ def plot_heatmap_gray(X, title='', save=None, mplotlib_backend=None):
plt.show()


def plot_roc(y_prob, y_test, clf, plot='both', save=None, title='', colors=None, cvsm=None, acc=None, fontsize=16):
def plot_roc(y_prob, y_test, clf, plot='both', save=None, title='', colors=None, cvsm=None, acc=None, fontsize=16, legend=False):
"""
y_prob, y_test, clf, plot=True, save=False, title ='', colors=None, cvsm=None, acc=None, fontsize=16):
"""
Expand Down Expand Up @@ -1076,7 +1079,9 @@ def plot_roc(y_prob, y_test, clf, plot='both', save=None, title='', colors=None,
ax[1].plot(Xs[i], Ys[i], c=colors[i], lw=2, label=cell_type)
ax[1].set_xlabel('Recall')
ax[1].set_ylabel('Precision')

## add legend if required
if legend == True:
ax[1].legend(bbox_to_anchor=(1.04,0.5), loc="center left")
ax[0].annotate(r'$AUC_{min}: %.3f$' % min_auc_rc, (0.5, 0.4), fontsize=fontsize)
ax[0].annotate(r'$AUC_{max}: %.3f$' % max_auc_rc, (0.5, 0.3), fontsize=fontsize)
ax[1].annotate(r'$AUC_{min}: %.3f$' % min_auc_rp, (0.5, 0.4), fontsize=fontsize)
Expand Down
5 changes: 3 additions & 2 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ def readme():

setup(
name='SCCAF',
version='0.0.10',
version='0.0.11',
description='Single-Cell Clustering Assessment Framework',
long_description=readme(),
long_description_content_type='text/markdown',
Expand All @@ -20,9 +20,10 @@ def readme():
'louvain',
'scikit-learn',
'psutil',
'scanpy==1.4.6'],
'scanpy==1.9.2'],
scripts=['cli/sccaf', 'cli/sccaf-assess', 'cli/sccaf-assess-merger', 'cli/sccaf-regress-out'],
author='Chichau Miau',
author_email='zmiao@ebi.ac.uk',
license='MIT'
)
# modified by Yuyao Song <ysong@ebi.ac.uk> on Oct 2023 to bump scanpy version