def ex2():
"""
Answer to
http://stackoverflow.com/questions/43059781/connecting-networks-by-adding-edge-between-same-items-in-the-networks
"""
HH = ['GLI1', 'PTCH1', 'PTCH2', 'WNT5A', 'HHIP1', 'MYCN', 'CCND1', 'CCND2', 'BCL2', 'CFLAR', 'FOXF1', 'FOXL1', 'PRDM1', 'JAG2', 'GREM1']
Wnt = ['GLI1', 'PTCH1', 'WNT5A', 'HHIP1', 'MYCN', 'CCND1', 'WNT7A', 'WNT2', 'CDK1', 'CK1']
CC = ['GLI1', 'CCNDA', 'BMP4', 'BMP7', 'MTOC2', 'CCND1']
venn3_wordcloud([set(HH), set(Wnt), set(CC)],
set_labels=['Hedgehog', 'Wnt', 'Cell Cycle'])
return
def main():
gn = Granatum()
set1 = gn.get_import('set1')
set2 = gn.get_import('set2')
set3 = gn.get_import('set3')
maxScore = gn.get_arg('maxScore')
minScore = gn.get_arg('minScore')
labelSet1 = gn.get_arg("labelSet1")
labelSet2 = gn.get_arg("labelSet2")
labelSet3 = gn.get_arg("labelSet3")
wordcloud = gn.get_arg("wordcloud")
filtered_set1 = dict(filter(lambda elem: (isinstance(elem[1], numbers.Number) & (not isnan(elem[1]))) & (elem[1] >= minScore) & (elem[1] <= maxScore), set1.items()))
filtered_set2 = dict(filter(lambda elem: (isinstance(elem[1], numbers.Number) & (not isnan(elem[1]))) & (elem[1] >= minScore) & (elem[1] <= maxScore), set2.items()))
filtered_set3 = dict(filter(lambda elem: (isinstance(elem[1], numbers.Number) & (not isnan(elem[1]))) & (elem[1] >= minScore) & (elem[1] <= maxScore), set3.items()))
merged_frequencies = {**filtered_set1, **filtered_set2, **filtered_set3}
packedsets = [set(filtered_set1.keys()), set(filtered_set2.keys()), set(filtered_set3.keys())]
fig, ax = plt.subplots(1,1)
fig.set_size_inches(5,4)
caption = (
'The area weighted Venn diagram is shown for the gene sets matching the criteria'
)
if wordcloud:
out = venn3_wordcloud(packedsets, set_labels=(labelSet1, labelSet2, labelSet3), wordcloud_kwargs=dict(max_font_size=36), word_to_frequency=merged_frequencies, ax=ax)
for text in out.set_labels:
if text:
text.set_fontsize(18)
for text in out.subset_labels:
if text:
text.set_fontsize(16)
text.set_path_effects([path_effects.SimpleLineShadow(), path_effects.Normal()])
else:
out = venn3(packedsets, set_labels=(labelSet1, labelSet2, labelSet3))
venn3_circles(packedsets, linestyle='dashed', linewidth=1, color="black")
for text in out.set_labels:
if text:
text.set_fontsize(18)
for text in out.subset_labels:
if text:
text.set_fontsize(16)
text.set_path_effects([path_effects.SimpleLineShadow(), path_effects.Normal()])
gn.add_current_figure_to_results(caption)
gn.commit()
def draw_word_venn_3(datasets, dataset_name1, dataset_name2, dataset_name3):
fig, ax = plt.subplots(1, 1, figsize=(30, 30))
set1 = set(get_names_from_files(datasets[dataset_name1]))
set2 = set(get_names_from_files(datasets[dataset_name2]))
set3 = set(get_names_from_files(datasets[dataset_name3]))
v = venn3_wordcloud([set1, set2, set3], (dataset_name1, dataset_name2, dataset_name3), ax=ax,
set_colors=['blue', 'yellow', 'green'])
for text in v.set_labels:
text.set_fontsize(30)
for text in v.subset_labels:
text.set_fontsize(18)
plt.show()
def ex5():
"""
Issue #4:
https://github.com/paulbrodersen/matplotlib_venn_wordcloud/issues/4
Handle non-overlapping sets gracefully.
"""
from matplotlib import pyplot as plt
from matplotlib_venn_wordcloud import venn2_wordcloud
x = set('abcd')
y = set('efgh')
s2 = (x, y)
v2 = venn2_wordcloud(s2)
z = set('ijkl')
s3 = (x, y, z)
v3 = venn3_wordcloud(s3)
# if(v.get_patch_by_id('101')):
# v.get_patch_by_id('101').set_color('#ff00ff')
# if(v.get_patch_by_id('111')):
# v.get_patch_by_id('111').set_color('#ffffff')
path = './images/'
if not os.path.exists(path):
os.makedirs(path)
path1 = path + x + y + z
#c = venn3_circles(s, linestyle='solid')
## create venn sets filled with words
plt.rcParams["figure.figsize"] = (39, 22)
print('Generating Venn diagram with words for:', x, y, z)
v = venn3_wordcloud(s,
set_labels=(x, y, z),
alpha=0.7,
word_to_frequency=frequencies,
wordcloud_kwargs={
'max_words': 1800,
'min_font_size': 9,
'width': 3840,
'height': 2160
})
path3 = path1 + '_words'
#plt.rcParams["figure.figsize"] = (20,11)
plt.savefig(path3)
plt.close()