action='store_true')
args = parser.parse_args()
# Solucion "analitica"
TbList = [0.9, 0.8, 0.7, 0.6]
Sol = []
for i in range(args.n + 1):
Sol.append(
vdw.rhoNonUniformLambda(Tt=0.99,
Tb=TbList[i],
kappa=1.0,
updateT=True,
thcond='linear'))
# Perfiles de densidad
colorList = ['r', 'b', 'g', 'y']
mklist = ['o', 's', '^', '*']
sp = 15
with plt.style.context(('thesis_classic')):
for i, mk in zip(range(args.n + 1), mklist):
# Argumentos de consola
parser = argparse.ArgumentParser(description='Resolución de vdWColumn')
parser.add_argument('-n', help='Rango de casos', type = int, default = 0)
parser.add_argument('-png', help='Imagen en formato png', action='store_true')
args = parser.parse_args()
# Solucion "analitica"
Sol = vdw.rhoNonUniformLambda( Tt = 0.99, Tb = 0.99, kappa = 1.0, updateT = False, thcond = 'linear' )
# Perfiles de densidad
colorList = ['r', 'b', 'g', 'y']
mklist = ['o', 's', '^', '*']
gridList = [300.0, 600.0, 1200.0, 2400.0]
lineList = ['-','--',':','-.']
sp = 15
parser.add_argument('-png', help='Imagen en formato png', action='store_true')
args = parser.parse_args()
# Solucion "analitica"
TbList = [0.9, 0.8, 0.7, 0.6]
Sol = []
for i in range( args.n + 1 ):
Sol.append( vdw.rhoNonUniformLambda( Tt = 0.99, Tb = TbList[i], kappa = 1.0, updateT = False, thcond = 'linear' ) )
# Perfiles de densidad
colorList = ['r', 'b', 'g', 'y']
mklist = ['o', 's', '^', '*']
sp = 15
with plt.style.context( ('thesis_classic') ):