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Trabajo_ASD_OMP_MPI/Genera_graficas.py
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| print("\nGenerando Graficas\n") | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| csv = pd.read_csv("resultados.csv") | |
| grupos = csv.groupby("Prueba Realizada") | |
| for prueba, elems1 in grupos: | |
| plt.clf() | |
| #Es un caso OMP + MPI | |
| if elems1.iloc[0]["Procesos"] != 0 and elems1.iloc[0]["Hilos"] != 0: | |
| gProcs = elems1.groupby("Procesos") | |
| for name1, items1 in gProcs: | |
| plt.title(prueba) | |
| plt.xlabel("Pasos") | |
| plt.ylabel("Tiempo(s)") | |
| gHilos = items1.groupby("Hilos") | |
| for name2, items2 in gHilos: | |
| plt.semilogx(items2.to_numpy()[:,5], items2.to_numpy()[:,1], label=str(name1)+" procesos, "+str(name2)+" hilos") | |
| plt.legend() | |
| plt.grid(True) | |
| plt.savefig("./Graficas/"+prueba+str(name1)+"procs"+".png",dpi=600) | |
| plt.clf() | |
| #Es un caso de MPI | |
| elif elems1.iloc[0]["Procesos"] != 0: | |
| gProcs = elems1.groupby("Procesos") | |
| plt.title(prueba) | |
| plt.xlabel("Pasos") | |
| plt.ylabel("Tiempo(s)") | |
| for name, items in gProcs: | |
| plt.semilogx(items.to_numpy()[:,5], items.to_numpy()[:,1], label=str(name)+" proceso") | |
| plt.legend() | |
| plt.grid(True) | |
| plt.savefig("./Graficas/"+prueba+".png",dpi=600) | |
| #Es un caso de OMP | |
| elif elems1.iloc[0]["Hilos"] != 0: | |
| gProcs = elems1.groupby("Hilos") | |
| plt.title(prueba) | |
| plt.xlabel("Pasos") | |
| plt.ylabel("Tiempo(s)") | |
| for name, items in gProcs: | |
| plt.semilogx(items.to_numpy()[:,5], items.to_numpy()[:,1], label=str(name)+" hilos") | |
| plt.legend() | |
| plt.grid(True) | |
| plt.savefig("./Graficas/"+prueba+".png",dpi=600) | |
| #Es un caso secuencial | |
| else: | |
| plt.title(prueba) | |
| plt.xlabel("Pasos") | |
| plt.ylabel("Tiempo(s)") | |
| plt.semilogx(elems1.to_numpy()[:,5], elems1.to_numpy()[:,1]) | |
| plt.grid(True) | |
| plt.savefig("./Graficas/"+prueba+".png",dpi=600) | |
| print("Grafica generada para",prueba) | |
| print("\nFin de generacion de Graficas\n") |