def venn(inp, names, title="venn", folder=''):
"""
Plots a venn diagram using the pyvenn package
Args:
-----
inp: list[set()] of sets of values (e.g. [(1,2,3,4),(2,3),(1,3,4,5)])
names: list[str] of the name of each leaf
title: str the plot title
folder: str of location where to save the plot, won't save if empty
"""
labels = pyvenn.get_labels(inp, fill=['number', 'logic'])
if len(inp) == 2:
fig, ax = pyvenn.venn2(labels, names=names)
elif len(inp) == 3:
fig, ax = pyvenn.venn3(labels, names=names)
elif len(inp) == 4:
fig, ax = pyvenn.venn4(labels, names=names)
elif len(inp) == 5:
fig, ax = pyvenn.venn5(labels, names=names)
elif len(inp) == 6:
fig, ax = pyvenn.venn6(labels, names=names)
else:
raise ValueError('need to be between 2 to 6')
ax.set_title(title)
if folder:
fig.savefig(folder + title + '_venn.pdf')
fig.show()
plt.pause(0.1)
def generate_venn_diagram(nb_dim, files, names, sep, label):
"""Cette fonction fait l'appel du fichier venn.py (qui doit être présent dans le même dossier que generate_venn.py)
pour générer les diagrammes de Venn.
:param: nombre de dimensions présent dans le diagramme de Venn (1 < nb_dim <= 6)
:param: files: liste des chemins d'accès aux fichiers contenant les résultats des modèles
:param: names: liste des noms des modèles (doit être en adéquation avec la liste des modèles files)
:param: sep: séparateur présent dans filename séparant les id-instance des label
:label: label que l'on souhaite extraire
"""
if nb_dim < 2 or nb_dim > 6:
print(
'Le diagramme de Venn ne peut être généré que pour un nombre de dimensions supérieur à un et inférieur ou égal à 6.'
)
else:
i = 0
models = []
while i < nb_dim:
models.append(
get_id_instances_title(files[i], sep=sep, label=label))
i += 1
labels = venn.get_labels(models)
if nb_dim == 2:
fig, ax = venn.venn2(labels, names=names)
plt.show()
elif nb_dim == 3:
fig, ax = venn.venn3(labels, names=names)
plt.show()
elif nb_dim == 4:
fig, ax = venn.venn4(labels, names=names)
plt.show()
elif nb_dim == 5:
fig, ax = venn.venn5(labels, names=names)
plt.show()
elif nb_dim == 6:
fig, ax = venn.venn6(labels, names=names)
plt.show()
else:
print(
'Le diagramme de Venn ne peut être généré que pour un nombre de dimensions supérieur à un et inférieur ou égal à 6.'
)
n34 = len(intersection(tp[ids[2]], tp[ids[3]]))
n35 = len(intersection(tp[ids[2]], tp[ids[4]]))
n45 = len(intersection(tp[ids[3]], tp[ids[4]]))
area5 = len(tp[ids[4]])
area4 = len(tp[ids[3]])
area3 = len(tp[ids[2]])
area2 = len(tp[ids[1]])
area1 = len(tp[ids[0]])
venn_diag_list = [area1, area2, area3, area4, area5, n12, n13, n14, n15,n23, n24, n25,
n34, n35, n45, n123, n124, n125, n134, n135, n145, n234, n235, n245, n345, n1234,
n1235, n1245, n1345, n2345, n12345]
print('Overlap list needed for VennDiagram in R')
print(venn_diag_list)
out1.write('\n\n## Overlap list needed for VennDiagram in R:\n\n%s' % venn_diag_list)
if plot.lower() == 't' or plot.lower() == 'true':
if n_comparing == 5:
labels = venn.get_labels([tp[ids[0]], tp[ids[1]], tp[ids[2]], tp[ids[3]], tp[ids[4]]], fill = ['number'])
fig, ax = venn.venn5(labels, names = ids)
elif n_comparing == 4:
labels = venn.get_labels([tp[ids[0]], tp[ids[1]], tp[ids[2]], tp[ids[3]]], fill = ['number'])
fig, ax = venn.venn4(labels, names = ids)
elif n_comparing == 3:
labels = venn.get_labels([tp[ids[0]], tp[ids[1]], tp[ids[2]]], fill = ['number'])
fig, ax = venn.venn3(labels, names = ids)
elif n_comparing == 2:
labels = venn.get_labels([tp[ids[0]], tp[ids[1]]], fill = ['number'])
fig, ax = venn.venn2(labels, names = ids)
filename = save+'_pred_compared.pdf'
fig.savefig(filename)
# -*- coding: utf-8 -*-
"""
@author: tctianchi
https://github.com/tctianchi/pyvenn
"""
import matplotlib.pyplot as plt
import venn
labels = venn.get_labels([range(10), range(5, 15)], fill=['number', 'logic'])
fig, ax = venn.venn2(labels, names=['list 1', 'list 2'])
fig.savefig('venn2.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels(
[range(10), range(5, 15), range(3, 8)], fill=['number', 'logic'])
fig, ax = venn.venn3(labels, names=['list 1', 'list 2', 'list 3'])
fig.savefig('venn3.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels(
[range(10), range(5, 15),
range(3, 8), range(8, 17)],
fill=['number', 'logic'])
fig, ax = venn.venn4(labels, names=['list 1', 'list 2', 'list 3', 'list 4'])
fig.savefig('venn4.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels(
[range(10),
range(5, 15),
n25 = len(intersection(comp[ids[1]], comp[ids[4]]))
n34 = len(intersection(comp[ids[2]], comp[ids[3]]))
n35 = len(intersection(comp[ids[2]], comp[ids[4]]))
n45 = len(intersection(comp[ids[3]], comp[ids[4]]))
area5 = len(comp[ids[4]])
area4 = len(comp[ids[3]])
area3 = len(comp[ids[2]])
area2 = len(comp[ids[1]])
area1 = len(comp[ids[0]])
venn_diag_list = [area1, area2, area3, area4, area5, n12, n13, n14, n15,n23, n24, n25,
n34, n35, n45, n123, n124, n125, n134, n135, n145, n234, n235, n245, n345, n1234,
n1235, n1245, n1345, n2345, n12345]
print('Overlap list needed for VennDiagram in R')
print(venn_diag_list)
#out1.write('\n\n## Overlap list needed for VennDiagram in R:\n\n%s' % venn_diag_list)
if n_comparing == 5:
labels = venn.get_labels([comp[ids[0]], comp[ids[1]], comp[ids[2]], comp[ids[3]], comp[ids[4]]], fill = ['number'])
fig, ax = venn.venn5(labels, names = ids)
elif n_comparing == 4:
labels = venn.get_labels([comp[ids[0]], comp[ids[1]], comp[ids[2]], comp[ids[3]]], fill = ['number'])
fig, ax = venn.venn4(labels, names = ids)
elif n_comparing == 3:
labels = venn.get_labels([comp[ids[0]], comp[ids[1]], comp[ids[2]]], fill = ['number'])
fig, ax = venn.venn3(labels, names = ids)
elif n_comparing == 2:
labels = venn.get_labels([comp[ids[0]], comp[ids[1]]], fill = ['number'])
fig, ax = venn.venn2(labels, names = ids)
filename = save+'_pred_compared.pdf'
fig.savefig(filename)
# coding: utf-8
# ipython notebook requires this
# %matplotlib inline
# python console requires this
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import venn
labels = venn.get_labels([range(10), range(5, 15)], fill=['number', 'logic'])
fig, ax = venn.venn2(labels, names=['list 1', 'list 2'])
fig.savefig('venn2.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels([range(10), range(5, 15), range(3, 8)], fill=['number', 'logic'])
fig, ax = venn.venn3(labels, names=['list 1', 'list 2', 'list 3'])
fig.savefig('venn3.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels([range(10), range(5, 15), range(3, 8), range(8, 17)], fill=['number', 'logic'])
fig, ax = venn.venn4(labels, names=['list 1', 'list 2', 'list 3', 'list 4'])
fig.savefig('venn4.png', bbox_inches='tight')
plt.close()
labels = venn.get_labels([range(10), range(5, 15), range(3, 8), range(8, 17), range(10, 20)], fill=['number', 'logic'])
fig, ax = venn.venn5(labels, names=['list 1', 'list 2', 'list 3', 'list 4', 'list 5'])
fig.savefig('venn5.png', bbox_inches='tight')
plt.close()
elif "full_model" in results_file:
all_labels.append("Full model")
for r_label in results:
# print unique TP to this result
tps = set(results[r_label]["all"]) & set(gold_pairs["all"])
for r_label2 in results:
if r_label2 == r_label:
continue
tps = tps - set(results[r_label2]["all"])
print()
print("unique to {}:".format(r_label))
print(len(tps))
print(tps)
print()
print(all_labels)
# print(results)
labels = venn.get_labels(all_pairs, fill=["number"])
if len(all_pairs) == 2:
fig, ax = venn.venn2(labels, names=all_labels)
elif len(all_pairs) == 3:
fig, ax = venn.venn3(labels, names=all_labels)
elif len(all_pairs) == 4:
fig, ax = venn.venn4(labels, names=all_labels)
elif len(all_pairs) == 5:
fig, ax = venn.venn5(labels, names=all_labels)
elif len(all_pairs) == 6:
fig, ax = venn.venn6(labels, names=all_labels)
fig.savefig("{}.png".format("_".join(all_labels)), bbox_inches="tight")
plt.close()
