diff --git a/src/processing_mapping_results/complete_processing_of_mapping_results.py b/src/processing_mapping_results/complete_processing_of_mapping_results.py
index 1f02c12bde8f83490595e97155384abbee207037..9cb03c332697b4bf723684eeb3f294863df6bde0 100644
--- a/src/processing_mapping_results/complete_processing_of_mapping_results.py
+++ b/src/processing_mapping_results/complete_processing_of_mapping_results.py
@@ -172,9 +172,8 @@ def recup_me_path_list(file, folder, number_of_files, index_tof_c):
def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
- f_view_sav=LOC,
- midfile=None,
- n_path_to_filt="nothing", modul=None, f_modul=None):
+ f_view_sav=LOC, midfile=None, n_path_to_filt="nothing",
+ modul=None, f_modul=None, bdd=None):
"""
Do the complet treatement of mapping results
4 mappeurs are usable ConsensusPathDB, MetaboAnalyst, MetExplore and RAMP
@@ -250,6 +249,7 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
actu_down += 1
else:
print(path_meta.strip())
+ print(value_modul[metabo.index(path_meta)])
if float(value_modul[metabo.index(path_meta)]) >= 0:
actu_up += 1
else:
@@ -277,13 +277,42 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
log_p_u_p = log_p[n_m_i_p*plot+n_m_i_p:]
list_path_u_p = list_path[n_m_i_p*plot+n_m_i_p:]
plot_u = up_down_path_plot(list_path_u_p, up_u_p, down_u_p, log_p_u_p)
- plt.savefig(f_view_sav+"up_down_path_plot"+str(under_plot + 1)+".png")
+ up_down_data = [list_path_u_p, up_u_p, down_u_p, log_p_u_p]
+ up_down_heads =["Pathways lists", "% metabolites up regulated",
+ "% metabolites up regulated", "-log(p-value)"]
+ for uph_pos, uph in enumerate(up_down_heads):
+ up_down_data[uph_pos].insert(0, uph)
+ df_up_down = pd.DataFrame(up_down_data).transpose()
+ if bdd is not None:
+ plt.savefig(f_view_sav+"up_down_path_plot"+str(under_plot + 1)+bdd+".png")
+ up_down_excel_f = f_view_sav + "up_down_path_plot" +str(under_plot + 1)+ bdd+".xlsx"
+ excel_file_writer(df_up_down, up_down_excel_f, sheetname="Up_down")
+ else:
+ plt.savefig(f_view_sav+"up_down_path_plot"+str(under_plot + 1)+".png")
+ up_down_excel_f = f_view_sav + "up_down_path_plot" +str(under_plot + 1)+".xlsx"
+ excel_file_writer(df_up_down, up_down_excel_f, sheetname="Up_down")
else:
plot = up_down_path_plot(list_path, up, down, log_p)
pdf_view.append(f_view_sav + mapper + "up_down_path_plot.png")
- plt.savefig(f_view_sav + mapper + "up_down_path_plot.png")
+ up_down_data = [list_path, up, down, log_p]
+ up_down_heads =["Pathways lists", "% metabolites up regulated",
+ "% metabolites up regulated", "-log(p-value)"]
+ for uph_pos, uph in enumerate(up_down_heads):
+ up_down_data[uph_pos].insert(0, uph)
+ df_up_down = pd.DataFrame(up_down_data).transpose()
+ if bdd is not None:
+ plt.savefig(f_view_sav + mapper + bdd+ "up_down_path_plot.png")
+ up_down_excel_f = f_view_sav + "up_down_path_plot" +bdd+".xlsx"
+ excel_file_writer(df_up_down, up_down_excel_f, sheetname="Up_down")
+ else:
+ plt.savefig(f_view_sav + mapper + "up_down_path_plot.png")
+ up_down_excel_f = f_view_sav + "up_down_path_plot" +".xlsx"
+ excel_file_writer(df_up_down, up_down_excel_f, sheetname="Up_down")
if midfile is not None:
- midfile_name = midfile + mapper + "_mid_file.xlsx"
+ if bdd is not None:
+ midfile_name = midfile + mapper + bdd + "_mid_file.xlsx"
+ else:
+ midfile_name = midfile + mapper + "_mid_file.xlsx"
mid_data = pd.DataFrame(l_of_pathways_list, dtype=object)
excel_file_writer(mid_data, midfile_name, sheetname="Resultats")
if mapper != "RAMP":
@@ -419,7 +448,10 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
df_matrix_table = np.array(df_matrix_table, dtype=object)
df_matrix_table = pd.DataFrame(data=df_matrix_table)
- result_out_file = outf + mapper + "resultats_traitment_mapping.xlsx"
+ if bdd is not None:
+ result_out_file = outf + mapper + bdd + "resultats_traitment_mapping.xlsx"
+ else:
+ result_out_file = outf + mapper + "resultats_traitment_mapping.xlsx"
excel_m_file_writer([patways_reco_order_for_export,
df_matrix_table, metabo_f_order_for_export,
meta_and_path_p], result_out_file,
@@ -444,7 +476,10 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
dfrecovisu, title=titlen, y_lim=y_lim,
figure_size=(22, 10))
if save_plot in ("all", "bar_plot", "bar_plot_r", "bar_r_meta_p"):
- plt.savefig(f_view_sav+titlen+".png")
+ if bdd is not None:
+ plt.savefig(f_view_sav+titlen+bdd+".png")
+ else:
+ plt.savefig(f_view_sav+titlen+".png")
plt.show()
dfrecovisu = data_reco_view[n_m_i_p*(under_plot):]
titlen = "Recouvrement moyen voies métaboliques "+str(under_plot)
@@ -452,7 +487,10 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
dfrecovisu, title=titlen,y_lim=y_lim,
figure_size=(22, 10))
if save_plot in ("all", "bar_plot", "bar_plot_r", "bar_r_meta_p"):
- plt.savefig(f_view_sav+titlen+".png")
+ if bdd is not None:
+ plt.savefig(f_view_sav+titlen+bdd+".png")
+ else:
+ plt.savefig(f_view_sav+titlen+".png")
plt.show()
else:
barplot(colnames_recovery[2], colnames_recovery[1],
@@ -460,8 +498,11 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
title="Recouvrement moyen des différentes voies métaboliques",
figure_size=(22, 10),)
if save_plot in ("all", "bar_plot", "bar_plot_r", "bar_r_meta_p"):
- plt.savefig(f_view_sav+mapper+"bar_plot_of_recovery.png")
- pdf_view.append(f_view_sav+mapper+"bar_plot_of_recovery.png")
+ if bdd is not None:
+ plt.savefig(f_view_sav+mapper+bdd+"bar_plot_of_recovery.png")
+ else:
+ plt.savefig(f_view_sav+mapper+"bar_plot_of_recovery.png")
+ pdf_view.append(f_view_sav+mapper+"bar_plot_of_recovery.png")
plt.show()
just_frequency = []
@@ -481,8 +522,11 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
figure_size=(10, 30), ax_x_label="Métabolites d'intérêt",
ax_y_label='Fréquence', decimal='%.0f')
if save_plot in ("all", "bar_plot", "bar_plot_f", "bar_f_meta_p"):
- plt.savefig(f_view_sav+mapper+"bar_plot_of_metabolites.png")
- pdf_view.append(f_view_sav+mapper+"bar_plot_of_metabolites.png")
+ if bdd is not None:
+ plt.savefig(f_view_sav+mapper+bdd+"bar_plot_of_metabolites.png")
+ else:
+ plt.savefig(f_view_sav+mapper+"bar_plot_of_metabolites.png")
+ pdf_view.append(f_view_sav+mapper+"bar_plot_of_metabolites.png")
plt.show()
if type_of_view in ("all", "meta_box", "bar_f_meta_p", "bar_r_meta_p"):
@@ -492,8 +536,11 @@ def c_p_o_m_r(file, outf, mapper, type_of_view="all", save_plot="all",
b1.set(title="Boîte à moustache des fréquences des métabolites")
plt.ylabel("fréquence des métabolites")
if save_plot in ("all", "meta_box", "bar_f_meta_p", "bar_r_meta_p"):
- plt.savefig(f_view_sav + mapper + "metabolites_bo_of_frequency.png")
- pdf_view.append(f_view_sav + mapper + "metabolites_bo_of_frequency.png")
+ if bdd is not None:
+ plt.savefig(f_view_sav + mapper + bdd+ "metabolites_bo_of_frequency.png")
+ else:
+ plt.savefig(f_view_sav + mapper + "metabolites_bo_of_frequency.png")
+ pdf_view.append(f_view_sav + mapper + "metabolites_bo_of_frequency.png")
plt.show()
return pdf_view
diff --git a/src/processing_mapping_results/main.py b/src/processing_mapping_results/main.py
index 21051a0ab58f30c2c5920af53326c54ee4f39b28..a60da64008787e5821b18dc6f0ad03d2eb952202 100644
--- a/src/processing_mapping_results/main.py
+++ b/src/processing_mapping_results/main.py
@@ -191,6 +191,28 @@ def workflow(infile, out_folder):
map_monit_dir += "\\"
vis_dir += "\\"
+ results_dir_bbb = results_dir + "base_par_base"
+ map_monit_dir_bbb = map_monit_dir + "base_par_base"
+ vis_dir_bbb = vis_dir + "base_par_base"
+ try:
+ os.mkdir(results_dir_bbb)
+ except:
+ print("base_par_base directory already exist")
+
+ try:
+ os.mkdir(map_monit_dir_bbb)
+ except:
+ print("map_monit_dir_bbb directory already exist")
+
+ try:
+ os.mkdir(vis_dir_bbb)
+ except:
+ print("vis_dir_bbb directory already exist")
+
+ results_dir_bbb += "\\"
+ map_monit_dir_bbb += "\\"
+ vis_dir_bbb += "\\"
+
datas_f_map, chebi_hori, lec_id, exa_id = shapping_data(infile,
map_monit_dir)
data_input = recup_all_inf_excel(infile)
@@ -199,7 +221,7 @@ def workflow(infile, out_folder):
data_input[i_dat_i][j] = str(dat_i[j])
result_cpdb, result_ramp, recap = opti_multimapping(datas_f_map, results_dir,
mapping="flow")
-
+ ### Global Treatment
l_visu = c_p_o_m_r(result_ramp, results_dir, "RAMP", f_view_sav=vis_dir,
modul="flow", midfile=map_monit_dir, f_modul=recap)
l_visu_c = c_p_o_m_r(result_cpdb, results_dir, "CPDB", f_view_sav=vis_dir,
@@ -224,6 +246,18 @@ def workflow(infile, out_folder):
visu_para = [100, 0, 1, 10, 1]
l_bdd = ["Wikipathways", "KEGG", "EHMN",
"HumanCyc", "INOH", "Reactome", "SMPDB"]
+ for bdd_nw in l_bdd:
+ dataset_bdd_cpdb = [[result_cpdb[X][0]] for X in range(13)]
+ for pos_lin, bdd_l in enumerate(result_cpdb[3]):
+ if bdd_l == bdd_nw:
+ for count in range(len(dataset_bdd_cpdb)):
+ dataset_bdd_cpdb[count].append(result_cpdb[count][pos_lin])
+ print(dataset_bdd_cpdb)
+ if len(dataset_bdd_cpdb[0])>3:
+ l_visu_c = c_p_o_m_r(dataset_bdd_cpdb, results_dir_bbb, "CPDB",
+ f_view_sav=vis_dir_bbb, modul="flow",
+ midfile=map_monit_dir_bbb,
+ f_modul=recap , bdd=bdd_nw)
t2 = time()
print("le temps nécessaires pour effectuer le mapping optimal a était de ",
t2-t1, "secondes.")
@@ -277,7 +311,6 @@ def workflow(infile, out_folder):
recap_augment.append(recap[i_rec-nbr_mapping])
recap_augment.append(recap[1+nbr_mapping])
-
df_recap = pd.DataFrame(recap_augment).transpose()
n_o_f = results_dir + "recap_with_mapping.xlsx"
excel_file_writer(df_recap, n_o_f, sheetname="Resultats")
@@ -287,6 +320,7 @@ def workflow(infile, out_folder):
print("le temps total pour faire tourner le programme est a était ",
t3-t1, "secondes.")
+
if __name__ == "__main__":
INFILE = FOLDER + "datas_deux_col.xlsx"
workflow(INFILE, FOLDER)