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70 lines
2.1 KiB
70 lines
2.1 KiB
'''
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Ejemplo de implementacion del Ánalisis en el plano ecuatorial
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'''
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import numpy as np
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import matplotlib.pyplot as plt
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# from Codigo1 import mcart_msph,msph_mcart,gengraficasph
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import Codigo2D_FiltroZ as c1
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import Codigo2D_Interpolacion as c2
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import Codigo2D_Coefs as c3 # Este incluye a ajuste de Helfrich y a Base
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T = 300 # temperatura
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time = 50 # tiempo para graficar
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# %% PROGRAMA ARIN
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normalizacion = 7*10**5 # No es necesaria son uds de los datos
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MATRIZ = np.load('matrizcartesianas.npy') # DATOS PROGRAMA ARIN
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MATRIZESF = c1.mcart_msph(MATRIZ)
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MATRIZESF[:,:,0] = MATRIZESF[:,:,0] / normalizacion # cambiamos el radio / normalizamos (Ver luego que tambien intorud)
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MATRIZCART = c1.msph_mcart(MATRIZESF)
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# %% FILTRO EN Z
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RMatrix = MATRIZESF[:,:,0] # radios
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VMR = np.mean(RMatrix) # Valor medio del radio
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Z1 = (VMR/10)*0.1 # Una centesima del radio medio
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FiltroCart,FiltroEsf = c1.filtroz(MATRIZ,Z1,normalizacion) # Filtramos
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# %% INTERPOLACION
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MSph = c2.newinterpolate2(FiltroEsf,2001) # Interpolamos
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MCart = c1.msph_mcart(MSph)
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MCart[:,:,2] = 0
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# %% CALCULO DE BENDING Y STRETCH
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nmax = 19
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nmin = 4 # NOTA nmin = 0, es el modo 1
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qx,u,qxnew,unew,bend,stretch = c3.calculatecoefs(MSph,nmin,nmax,T)
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# %% GRAFICA
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plt.figure()
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plt.plot(qx[nmin:nmax],u[nmin:nmax],marker = "o",color = "blue")
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plt.plot(qxnew,unew,color="red", linestyle="-.")
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plt.title("Coeficientes en función de qx", fontweight="bold")
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plt.xlabel("qx", fontweight="bold")
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plt.ylabel(r"$\langle \mathbf{|u|^2} \rangle$", fontsize=14)
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# GRAFICA FILTRO (Simplemente para ver forma)
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mask = FiltroEsf[time,:,0] != 0
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FiltroEsfmask = FiltroEsf[time,mask] # Eliminar 0's para ver mejor la grafica
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plt.figure()
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plt.plot(MSph[time, :, 2], MSph[time, :, 0], marker=".", linestyle="--", color="blue", label=r"Interpolación datos filtro ($\Delta z_1$)")
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z1_label = f"$\Delta z_1$ = {np.format_float_scientific(Z1, precision=2)}"
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plt.plot(FiltroEsfmask[:,2], FiltroEsfmask[:,0], marker="h", linestyle="none", color="red", label=z1_label)
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plt.title("Radio en función de phi", fontweight="bold")
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plt.xlabel("PHI", fontweight="bold")
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plt.ylabel("R [m]", fontweight = "bold")
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plt.legend()
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plt.show() |