<jupyter_start><jupyter_text>Markov et al. (2012), Figure 2Reproduced by <NAME> ([@prisae](https://github.com/prisae)).> **<NAME>., <NAME>, <NAME>, and <NAME>, 2012**  > The dielectric permittivity of carbonate formations from the unified microstructure model.  > Journal of Applied Geophysics, 76, 56 - 63; DOI: [10.1016/j.jappgeo.2011.10.006](https://doi.org/10.1016/j.jappgeo.2011.10.006). Requirements- `NumPy`- `IPython`- `Jupyter`- `matplotlib`<jupyter_code>import diemmod
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
plt.rcParams['figure.dpi'] = 300<jupyter_output><empty_output><jupyter_text>Markov et al. (2012), Figure 2 - Original![title](Figure2.jpg)<jupyter_code># Concentrations
por = np.arange(31)/100

# Electric permittivity of constituents
ecalc = 7.5
ewater = 80.+0.045j

# Get aspect ratio
aratio_m = diemmod.aspratio(por, 'Markov')
aratio_s = diemmod.aspratio(por, 'Spherical')

# Calculate
crim = diemmod.eperm_crim(por, ecalc, ewater)
sigm_m = diemmod.eperm_ema(por, ecalc, ewater, aratio_m, crim)
sigm_s = diemmod.eperm_ema(por, ecalc, ewater, aratio_s, crim)
plt.figure(figsize=(8, 3))

plt.subplot(121)
plt.title('Figure 2 A')
plt.xlabel('Porosity')
plt.ylabel(r"Real ($\varepsilon$)")
plt.plot(por, sigm_s.real, 'k:')
plt.plot(por, sigm_m.real, 'k--')
plt.plot(por, crim.real, 'k')
plt.axis([0, 0.3, 0, 30])

ax = plt.subplot(122)
plt.title('Figure 2 B')
plt.xlabel('Porosity')
plt.ylabel(r"Im ($\varepsilon$)")
plt.plot(por, sigm_s.imag, 'k:', label='EMA spherical pores')
plt.plot(por, sigm_m.imag, 'k--', label='EMA elliptic pores')
plt.plot(por, crim.imag, 'k-', label='CRIM')
plt.legend()
plt.axis([0, 0.3, 0, 0.0075])

plt.tight_layout()
plt.show()<jupyter_output><empty_output>
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