Louis BECQUEY / biorseo

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Nathalie BERNARD
55bb6176 1 parent c6bdd341

Ajout de fonctions pour faire un boxplot pour les MCC de chaque séquence du benchmark

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Showing 1 changed file with 140 additions and 17 deletions
......@@ -5,6 +5,8 @@ import os.path
from math import sqrt, ceil
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
log_path = "test.log"
......@@ -22,7 +24,20 @@ def run_test(cmd, log):
log.flush()
rc = process.poll()
def create_command(name):
def create_command_E(name):
#cmd = ("python3 /mnt/c/Users/natha/Documents/IBISC/biorseo2/biorseo/biorseo.py -i " +
cmd = ("python3 /local/local/BiorseoNath/biorseo.py -i " +
"/local/local/BiorseoNath/data/fasta/" +
name + ".fa " +
"-O results/ " +
"--contacts " +
"--patternmatch " +
"--func E --MFE -v " +
"--biorseo-dir /local/local/BiorseoNath " +
"--modules-path /local/local/BiorseoNath/data/modules/ISAURE/Motifs_derniere_version ")
return cmd
def create_command_F(name):
#cmd = ("python3 /mnt/c/Users/natha/Documents/IBISC/biorseo2/biorseo/biorseo.py -i " +
cmd = ("python3 /local/local/BiorseoNath/biorseo.py -i " +
"/local/local/BiorseoNath/data/fasta/" +
......@@ -129,8 +144,8 @@ def specificity(tp, tn, fp, fn):
# ================== Code from Louis Beckey Benchark.py ==============================
def write_mcc_in_file_E(sequence_id, true_contacts, true_structure):
read_prd = open("results/test_" + sequence_id + ".json_pmE_MEA", "r")
write = open("results/test_" + sequence_id + ".mcc_E_MEA", "w")
read_prd = open("results/test_" + sequence_id + ".json_pmE_MFE", "r")
write = open("results/test_" + sequence_id + ".mcc_E_MFE", "w")
max_mcc_str = -1;
max_mcc_ctc = -1;
......@@ -223,12 +238,16 @@ def set_axis_style(ax, labels):
ax.set_xlim(0.25, len(labels) + 0.75)
ax.set_xlabel('Sample name')
def visualization(list_struct2d, list_contacts, function, color, lines_color):
def visualization_best_mcc(list_struct2d, list_contacts, function, color, lines_color):
np_struct2d = np.array(list_struct2d)
np_contacts = np.array(list_contacts)
data_to_plot = [np_struct2d, np_contacts]
median_2d = np.median(np_struct2d)
median_ctc = np.median(np_contacts)
print("mediane 2D: " + str(median_2d) + "\n")
print("mediane ctc: " + str(median_ctc) + "\n")
fig = plt.figure()
......@@ -249,14 +268,111 @@ def visualization(list_struct2d, list_contacts, function, color, lines_color):
for v in violins['bodies']:
v.set_facecolor(color)
plt.savefig('visualisation' + function + '.png', bbox_inches='tight')
plt.savefig('visualisation_16_06_MFE_' + function + '.png', bbox_inches='tight')
def get_list_structs_contacts(path_benchmark, estimator, function):
myfile = open(path_benchmark, "r")
list_name = []
complete_list_struct2d_F = []
complete_list_contacts_F = []
name = myfile.readline()
contacts = myfile.readline()
seq = myfile.readline()
structure2d = myfile.readline()
count = 0
while seq:
name = name[6:].strip()
count = count + 1
file_path = "results/test_" + name + ".json_pm" + function +"_" + estimator
if os.path.isfile(file_path):
file_result = open(file_path, "r")
list_struct2d_F = []
list_contacts_F = []
list_name.append(name)
title_prd = file_result.readline()
structure_prd = file_result.readline()
sequence = structure_prd
while structure_prd:
structure_prd = file_result.readline()
if (len(structure_prd) != 0):
mcc_tab = compare_two_structures(structure2d, structure_prd[:len(sequence)])
mcc_str = mattews_corr_coeff(mcc_tab[0], mcc_tab[1], mcc_tab[2], mcc_tab[3])
list_struct2d_F.append(mcc_str)
contacts_prd = file_result.readline()
if (len(contacts_prd) == len(contacts)):
mcc_tab = compare_two_contacts(contacts, contacts_prd)
mcc_ctc = mattews_corr_coeff(mcc_tab[0], mcc_tab[1], mcc_tab[2], mcc_tab[3])
list_contacts_F.append(mcc_ctc)
complete_list_struct2d_F.append(list_struct2d_F)
complete_list_contacts_F.append(list_contacts_F)
name = myfile.readline()
contacts = myfile.readline()
seq = myfile.readline()
structure2d = myfile.readline()
return [list_name, complete_list_struct2d_F, complete_list_contacts_F]
myfile.close()
def visualization_all_mcc(path_benchmark, estimator, function, color, lines_color):
list_name = get_list_structs_contacts(path_benchmark, estimator, function)[0]
tab_struct2d = get_list_structs_contacts(path_benchmark, estimator, function)[1]
tab_contacts = get_list_structs_contacts(path_benchmark, estimator, function)[2]
np_struct2d = np.array(tab_struct2d)
size = len(tab_struct2d)
list_median_str = []
for i in range(size):
list_median_str.append(np.median(np_struct2d[i]))
data = [x for _, x in sorted(zip(list_median_str, tab_struct2d))]
boxName = [x for _, x in sorted(zip(list_median_str, list_name))]
absciss = len(data)
plt.figure(figsize=(25,4),dpi=200)
plt.xticks(rotation=90)
plt.boxplot(data)
for i in range(absciss):
y =data[i]
x = np.random.normal(1 + i, 0.04, size=len(y))
plt.scatter(x, y)
plt.xticks(np.arange(1, absciss + 1), boxName)
plt.xlabel('nom de la séquence')
plt.ylabel('MCC')
plt.savefig('visualisation_128arn_structure2d_' + estimator + "_" + function + '.png', bbox_inches='tight')
np_contacts = np.array(tab_contacts)
size = len(tab_contacts)
list_median_ctc = []
for i in range(size):
list_median_ctc.append(np.median(np_contacts[i]))
data = [x for _, x in sorted(zip(list_median_ctc, tab_contacts))]
boxName = [x for _, x in sorted(zip(list_median_ctc, list_name))]
absciss = len(data)
plt.figure(figsize=(25, 4), dpi=200)
plt.xticks(rotation=90)
plt.boxplot(data)
for i in range(absciss):
y = data[i]
x = np.random.normal(1 + i, 0.04, size=len(y))
plt.scatter(x, y)
plt.xticks(np.arange(1, absciss + 1), boxName)
plt.xlabel('nom de la séquence')
plt.ylabel('MCC')
plt.savefig('visualisation_128arn_contacts_' + estimator + "_" + function + '.png', bbox_inches='tight')
#cmd = ("cppsrc/Scripts/create")
#cmd0 = ("cppsrc/Scripts/addDelimiter")
#cmd1 = ("cppsrc/Scripts/countPattern")
#cmd2 = ("cppsrc/Scripts/deletePdb")
myfile = open("data/modules/ISAURE/Motifs_version_initiale/benchmark.txt", "r")
"""myfile = open("data/modules/ISAURE/Motifs_version_initiale/benchmark.txt", "r")
name = myfile.readline()
contacts = myfile.readline()
seq = myfile.readline()
......@@ -266,36 +382,43 @@ list_struct2d_E = []
list_contacts_E = []
list_struct2d_F = []
list_contacts_F = []
count = 0
countE = 0
countF = 0
while seq:
name = name[6:].strip()
print(name)
"""
run_test(cmd2 + " " + name + ".fa", log)
print(cmd2 + " " + name + ".fa")
"""
cmd3 = create_command(name)
cmd3 = create_command_E(name)
os.system(cmd3)
"""file_path = "results/test_" + name + ".json_pmE_MEA"
file_path = "results/test_" + name + ".json_pmE_MFE"
if os.path.isfile(file_path):
tabE = write_mcc_in_file_E(name, contacts, structure2d)
list_contacts_E.append(tabE[0])
list_struct2d_E.append(tabE[1])"""
list_struct2d_E.append(tabE[1])
countE = countE + 1
cmd3 = create_command_F(name)
os.system(cmd3)
file_path = "results/test_" + name + ".json_pmF_MFE"
if os.path.isfile(file_path):
tabF = write_mcc_in_file_F(name, contacts, structure2d)
list_contacts_F.append(tabF[0])
list_struct2d_F.append(tabF[1])
count = count + 1
countF = countF + 1
name = myfile.readline()
contacts = myfile.readline()
seq = myfile.readline()
structure2d = myfile.readline()
"""visualization(list_struct2d_E, list_contacts_E, 'E', 'red', '#900C3F')"""
visualization(list_struct2d_F, list_contacts_F, 'F', 'blue', '#0900FF')
print("count: " + str(count) + "\n")
myfile.close()
visualization_best_mcc(list_struct2d_E, list_contacts_E, 'E', 'red', '#900C3F')
visualization_best_mcc(list_struct2d_F, list_contacts_F, 'F', 'blue', '#0900FF')
print("countE: " + str(countE) + "\n")
print("countF: " + str(countF) + "\n")
myfile.close()"""
path_benchmark = "data/modules/ISAURE/Motifs_version_initiale/benchmark.txt"
visualization_all_mcc(path_benchmark,'MEA', 'F', 'blue', '#0900FF')
\ No newline at end of file
......