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%matplotlib inline


    

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import numpy
import itertools
from matplotlib import pyplot as plt


    

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class r(object):
    """ Particle position
        
        Keywords Arguments:
        r0 -- initial position [m]
        v0 -- initial velocity [m/s]
        a  -- acceleration     [m/s^2]
    """
    __slots__=("r0", "v0", "a")
    
    def __init__(self, r0:"iterable<float>", v0:"iterable<float>", a:"iterable<float>"):
        self.r0 = r0
        self.v0 = v0
        self.a  = a
        
    def calculo_coordenadas(self, t:"float") -> "iterable<float>":
        return [i + j*t + k/2 * t**2 for i, j, k in itertools.zip_longest(self.r0, self.v0, self.a)]
    
    def calculo_velocidad(self, t: "float") -> "iterable<float>":
        return [i + j*t for i, j in itertools.zip_longest(self.v0, self.a)]
        
    def __repr__(self) -> "str":
        return '({}, {})i'.format(self.r0[0], self.v[0])


    

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vector = r([0, 2, 0], [0, 49, 0], [0, -9.8, 0])


    

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# Calculamos vector posicion y vector velocidad para cada
# instante de tiempo de la simulacion
t = numpy.linspace(0, 10, 50)
p = [vector.calculo_coordenadas(i) for i in t]
v = [vector.calculo_velocidad(i) for i in t]


    

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# Extraemos las componentes en cada direccion
x = [i[0] for i in p]
y = [i[1] for i in p]
z = [i[2] for i in p]

vx = [i[0] for i in v]
vy = [i[1] for i in v]
vz = [i[2] for i in v]


    

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fig, ax1 = plt.subplots()
ax1.plot(t, y, 'b-')
ax1.set_xlabel("tiempo [s]")
ax1.set_ylabel("position (y) [m]")

ax2 = ax1.twinx()
ax2.plot(t, vy, 'r')
ax2.set_ylabel("velocidad [m/s]")

# Lo hago asi, anadiendo dos dibujos vacios con label, porque si no es un lio
# importante. Explicacion para hacerlo bien y mal (asi) en:
# http://stackoverflow.com/questions/5484922/secondary-axis-with-twinx-how-to-add-to-legend
ax1.plot(0, 0, 'b-', label = 'altura')
ax1.plot(0, 0, 'r-', label = 'velocidad')
ax1.legend(loc=0)

plt.show()


    

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