# ----------------------------------------------------- # # --------------- Modules Importation ----------------- # # Importing numerical analysis package and # morgenstemning color map. import numpy as np import matplotlib.pyplot as plt from matplotlib import cm from matplotlib import rcParams from scipy import interpolate from scipy.optimize import curve_fit #from scipy.stats import pearsonr #from numpy import convolve import scipy.fftpack as fft import morgenstemning as mrg ms, msi = mrg.morgenstemning() # Setting the rc parameters. rcParams['text.usetex'] = True rcParams['text.latex.preamble'] = [r"\usepackage[charter]{mathdesign}"] rcParams['font.family'] = 'serif' rcParams['font.size'] = 8 rcParams['axes.labelsize'] = 'large' rcParams['xtick.labelsize'] = 'large' rcParams['ytick.labelsize'] = 'large' rcParams['legend.numpoints'] = 3 rcParams['figure.figsize'] = 7, 3 # ---------------- Data Importation ------------------ # # We import the data for each fibre and rescale the # frequencies to GHz.
# Date mod. : October 23rd, 2013 # # Description: We compute the (complex) time delays # # for the homoneous, circular cavity # # as a function of the complex part of # # potential. # # ----------------------------------------------------- # # --------------- Modules Importation ----------------- # import numpy as np import matplotlib.pyplot as plt from scipy.linalg import eigvals from scipy.special import jn,jvp,hankel1,h1vp,hankel2,h2vp from scipy.optimize import newton from scipy.integrate import quadrature import morgenstemning as mrg mr, mri = mrg.morgenstemning() # Setting the rc parameters. plt.rcParams['text.usetex'] = True plt.rcParams['text.latex.preamble'] = [r"\usepackage[charter]{mathdesign}"] plt.rcParams['font.family'] = 'serif' plt.rcParams['font.size'] = 10 plt.rcParams['legend.numpoints'] = 3 # --------------- Function Definition ----------------- # def timeDelayEigenfunctionRe(r,m,nc,k): eps2 = np.imag(nc*nc) return np.real(-1j*k*eps2*2.0*np.pi*r*r*np.conj(jn(m,nc*k*r))*jvp(m,nc*k*r)) def timeDelayEigenfunctionIm(r,m,nc,k): eps2 = np.imag(nc*nc)
# -------------------- Information -------------------- # # Author: Joey Dumont <*****@*****.**> # # Date created: Jun. 17th, 2014 # # Date mod.: Jun. 17th, 2014 # # Description: We plot tthe values of Ai(z) for large # # arguments. # # ----------------------------------------------------- # # --------------- Modules Importation ----------------- # import matplotlib.pyplot as plt import numpy as np import morgenstemning as mrg from matplotlib.colors import LogNorm ms,msi = mrg.morgenstemning() from scipy.special import airy # Setting the rc parameters. plt.rcParams['text.usetex'] = True plt.rcParams['text.latex.preamble'] = [r"\usepackage{amsmath}\usepackage[charter]{mathdesign}"] plt.rcParams['font.family'] = 'serif' plt.rcParams['font.size'] = 10 plt.rcParams['legend.numpoints'] = 3 ticks = np.arange(0, 1200, 200) labels = np.arange(-500, 700, 200) nbPoints = 250 x = np.linspace(-500,500,2*nbPoints+1) y = np.linspace(-500,500,2*nbPoints+1) X, Y = np.meshgrid(x,y)
# Date mod. : October 23rd, 2013 # # Description: We compute the (complex) time delays # # for the homoneous, circular cavity # # as a function of the complex part of # # potential. # # ----------------------------------------------------- # # --------------- Modules Importation ----------------- # import numpy as np import matplotlib.pyplot as plt from scipy.linalg import eigvals from scipy.special import jn, jvp, hankel1, h1vp, hankel2, h2vp from scipy.optimize import newton from scipy.integrate import quadrature import morgenstemning as mrg mr, mri = mrg.morgenstemning() # Setting the rc parameters. plt.rcParams['text.usetex'] = True plt.rcParams['text.latex.preamble'] = [r"\usepackage[charter]{mathdesign}"] plt.rcParams['font.family'] = 'serif' plt.rcParams['font.size'] = 10 plt.rcParams['legend.numpoints'] = 3 # --------------- Function Definition ----------------- # def timeDelayEigenfunctionRe(r, m, nc, k): eps2 = np.imag(nc * nc) return np.real(-1j * k * eps2 * 2.0 * np.pi * r * r * np.conj(jn(m, nc * k * r)) * jvp(m, nc * k * r))