fig.canvas.mpl_connect('pick_event', onpick)
"""
plt.close("IME")
UsQ, UsCH = barrios.ix[event.ind][["UsQ", "UsCH"]].values[0]
impedence_matching_exp(q, ch, UsQ, UsCH, showplot=True)
if __name__ == "__main__":
plt.ion()
plt.close('all')
# Import Polystyrene EOS data, from a HYADES EOS file, and change initial
# conditions
ch = EOS("../data/eos_32.dat")
ch._rho0 = 1.05
ch._P0 = 0
# Import Quartz EOS data and use an analytic method bases on Us vs Up
# to calculate the Hugoniot
q = EOS("../data/eos_24.dat",
hugoniot_method="analytic",
upmin=0,
upmax=29,
UsvUp=quartz_UsvUp(model="knudson"))
# Play around with different quarts release models
q.hugoniot.custom_release_model = types.MethodType(quartz_ode_mglr,
q.hugoniot)
q.hugoniot.set_release_model("custom")
#q.hugoniot.set_release_model("mg", gamma=.66)
from impediance_match import impedence_matching_exp, monte_carlo_error_prop
from util import MonteCarloVariable
def onpick(event):
plt.close("IME")
UsQ, UsGDP = knudson.ix[event.ind][["UsQ", "UsGDP"]].values[0]
impedence_matching_exp(q, GDP, UsQ, UsGDP, showplot=True)
if __name__ == "__main__":
plt.ion()
plt.close('all')
GDP = EOS("../data/eos_32.dat")
GDP._rho0 = 1.035
GDP._P0 = 0
q = EOS("../data/eos_24.dat",
hugoniot_method="analytic",
upmin=0,
upmax=50,
UsvUp=quartz_UsvUp(model="knudson")
)
# overload the quarts hugoniot with the MGLR model
q.hugoniot.custom_release_model = types.MethodType(quartz_ode_mglr, q.hugoniot)
q.hugoniot.set_release_model("custom")
knudson = pd.read_csv("../data/knudson_test.csv", index_col=False)
UsGDP = knudson.UsGDP.values