elif method == 4:
stextreme_dist, _, bm = ecm.extremeDistribution_blockMaximaGEV(x=peaks,
t=t_peaks,
t_st=t_st)
elif method == 5:
stextreme_dist, _, bm = ecm.extremeDistribution_blockMaximaGumb(x=peaks,
t=t_peaks,
t_st=t_st)
# goodness of fit plots
if method == 1 or method == 2:
bm = ecm.blockMaxima(x=peaks, t=t_peaks, t_st=t_st)
_ = ecm.goodnessOfFitPlots(data=peaks,
prob_func=peaks_dist,
np_return=1000001,
x_pdf=x_e,
bins_pdf=20,
response_name='PTO Force',
response_name_2='Peaks',
response_units='kN')
if not method == 3:
fig_gof = ecm.goodnessOfFitPlots(data=bm,
prob_func=stextreme_dist,
np_return=10001,
x_pdf=x_e,
bins_pdf=20,
response_name='PTO Force',
response_name_2='1-hr Extreme',
response_units='kN')
if method == 3:
bm = ecm.blockMaxima(x=peaks, t=t_peaks, t_st=t_st)
_ = ecm.goodnessOfFitPlots(data=peaks[peaks > thresh_x],
ax = plt.subplot(2, 1, 1)
plt.plot(x_e, peaks_dist.pdf(x_e), 'g-', label='Peak distribution')
plt.plot(x_e, stextreme_dist.pdf(x_e), 'r-', label='Extreme distribution')
xlim = ax.get_xlim()
ylim = ax.get_ylim()
plt.ylim([0, ylim[1]])
plt.xlim([0, xlim[1]])
plt.ylabel('$PDF(x)$')
plt.ylabel('Response, $x$')
plt.grid(True)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0, 0))
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.legend()
ax = plt.subplot(2, 1, 2)
plt.plot(x_e, peaks_dist.cdf(x_e), 'g-')
plt.plot(x_e, stextreme_dist.cdf(x_e), 'r-')
xlim = ax.get_xlim()
ylim = ax.get_ylim()
plt.ylim([0, ylim[1]])
plt.xlim([0, xlim[1]])
plt.xlabel('Response, $x$')
plt.ylabel('$CDF(x)$')
plt.grid(True)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0, 0))
# goodness of fit plots
gof_plots = ste.goodnessOfFitPlots(data=peaks, prob_func=peaks_dist, np_return=1000001, x_pdf=x_e, bins_pdf=20)
plt.show()
plt.plot(x_e, peaks_dist.pdf(x_e), 'g-', label='Peak distribution')
plt.plot(x_e, stextreme_dist.pdf(x_e), 'r-', label='Extreme distribution')
xlim = ax.get_xlim()
ylim = ax.get_ylim()
plt.ylim([0, ylim[1]])
plt.xlim([0, xlim[1]])
plt.ylabel('$PDF(x)$')
plt.ylabel('Response, $x$')
plt.grid(True)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0, 0))
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.legend()
ax = plt.subplot(2, 1, 2)
plt.hold(True)
plt.plot(x_e, peaks_dist.cdf(x_e), 'g-')
plt.plot(x_e, stextreme_dist.cdf(x_e), 'r-')
xlim = ax.get_xlim()
ylim = ax.get_ylim()
plt.ylim([0, ylim[1]])
plt.xlim([0, xlim[1]])
plt.xlabel('Response, $x$')
plt.ylabel('$CDF(x)$')
plt.grid(True)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0, 0))
# goodness of fit plots
gof_plots = ecm.goodnessOfFitPlots(data=peaks, prob_func=peaks_dist, np_return=1000001, x_pdf=x_e, bins_pdf=20)
plt.show()