Preprocessing

gmspy provides some preprocessing functions. Although they are not necessary, they may be useful in some situations.

In [1]:

import gmspy as gm
import matplotlib.pyplot as plt
import numpy as np

import gmspy as gm import matplotlib.pyplot as plt import numpy as np

Below is the ground motion data built into gmspy, you can also document the PEER database through loadPEER, or you can read the data from text using numpy.loadtxt.

In [2]:

ts, acc = gm.load_gm_examples("Kobe")
dt = ts[1] - ts[0]
# You can also use other acc data

ts, acc = gm.load_gm_examples("Kobe") dt = ts[1] - ts[0] # You can also use other acc data

Baseline Correction¶

In [3]:

acc_corr, vel_corr, disp_corr = gm.baselinecorr(ts, acc, poly_degree=1, plot=True)

acc_corr, vel_corr, disp_corr = gm.baselinecorr(ts, acc, poly_degree=1, plot=True)

Filtering¶

In [4]:

ts, acc = gm.load_gm_examples("ChiChi")
dt = ts[1] - ts[0]
acc2 = gm.freq_filt(
    dt,
    acc,
    ftype="Butterworth",  # 'Butterworth', 'Chebyshev', 'Bessel'
    btype="lowpass",  # 'lowpass', 'highpass', 'bandpass', 'bandstop'
    order=4,
    freq1=9,
    freq2=20,
    rp=3,
    plot=True,
)

ts, acc = gm.load_gm_examples("ChiChi") dt = ts[1] - ts[0] acc2 = gm.freq_filt( dt, acc, ftype="Butterworth", # 'Butterworth', 'Chebyshev', 'Bessel' btype="lowpass", # 'lowpass', 'highpass', 'bandpass', 'bandstop' order=4, freq1=9, freq2=20, rp=3, plot=True, )

Resampling¶

In [5]:

ts, acc = gm.load_gm_examples("Imperial_Valley")
dt = ts[1] - ts[0]
dtis = [dt / 2, 2 * dt]

colors = ["b", "r"]
fig, ax = plt.subplots(figsize=(9, 4))
ax.hlines(0, np.min(ts), np.max(ts), lw=0.5, colors="gray")
ax.plot(ts, acc, c="gray", lw=1, label=f"origin, dt={dt}, num={len(ts)}", alpha=1)
for i, dti in enumerate(dtis):
    ts2, acc2 = gm.resample(dt, acc, dti)
    ax.plot(ts2, acc2, c=colors[i], lw=1, alpha=1, label=f"dti={dti}, num={len(ts2)}")
ax.set_xlim(np.min(ts), np.max(ts))
ax.grid(False)
ax.set_ylabel("acceleration", fontsize=12)
ax.tick_params(labelsize=12)
ax.legend(fontsize=12)
plt.show()

ts, acc = gm.load_gm_examples("Imperial_Valley") dt = ts[1] - ts[0] dtis = [dt / 2, 2 * dt] colors = ["b", "r"] fig, ax = plt.subplots(figsize=(9, 4)) ax.hlines(0, np.min(ts), np.max(ts), lw=0.5, colors="gray") ax.plot(ts, acc, c="gray", lw=1, label=f"origin, dt={dt}, num={len(ts)}", alpha=1) for i, dti in enumerate(dtis): ts2, acc2 = gm.resample(dt, acc, dti) ax.plot(ts2, acc2, c=colors[i], lw=1, alpha=1, label=f"dti={dti}, num={len(ts2)}") ax.set_xlim(np.min(ts), np.max(ts)) ax.grid(False) ax.set_ylabel("acceleration", fontsize=12) ax.tick_params(labelsize=12) ax.legend(fontsize=12) plt.show()