In [1]:

    

import itertools

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

import pyrvt
import pysra

%matplotlib inline


    

In [2]:

    

# Increased figure sizes
plt.rcParams['figure.dpi'] = 120


    

In [3]:

    

osc_freqs = np.logspace(-1, 2, num=91)


    

In [4]:

    

peak_calcs = [
    pyrvt.peak_calculators.CartwrightLonguetHiggins1956(),
    pyrvt.peak_calculators.Vanmarcke1975(),

]
mags = [5, 6, 7]

# Create CLH and V peak factor motions
motions = [
    pysra.motion.SourceTheoryRvtMotion(
        mag, 20, 'wna', depth=8, stress_drop=100, peak_calculator=pc)
    for pc, mag in itertools.product(peak_calcs, mags)
]

# Create WR peak factor motions.
motions += [
    pysra.motion.SourceTheoryRvtMotion(
        mag, 20, 'wna', depth=8, stress_drop=100, 
        peak_calculator=pyrvt.peak_calculators.WangRathje2018('wna', mag, 20))
    for mag in mags
]


    

In [5]:

    

for m in motions:
    m.calc_fourier_amps(freqs=np.logspace(-2, 2, 1024))


    

In [6]:

    

fig, axes = plt.subplots(
    ncols=2, 
    sharex=True, sharey=False,
    subplot_kw={'xscale': 'log'},
    figsize=(10, 6),
)

for m in motions:
    osc_resps = m.calc_osc_accels(osc_freqs)
    for ax in axes:
        ax.plot(osc_freqs, osc_resps, 
                label=f'M{m.magnitude}, {m.peak_calculator.ABBREV}')

axes[0].set(ylabel='5%-Damped, Spectral Accel. (g)', yscale='linear')
axes[1].set(yscale='log')
plt.setp(axes, xlabel='Frequency (Hz)')

ax.legend()
fig.tight_layout()


    

In [ ]: