def run_analysis(filename,mode,method):
click.echo('Reading file : %s'%filename)
data = IOfile.parsing_input_file(filename)
click.echo('Creating class...')
theclass = TFC(data)
click.echo('Calculating transfer function using %s method'%method)
if method=='tf_kramer286_sh':
theclass.tf_kramer286_sh()
elif method=='tf_knopoff_sh':
theclass.tf_knopoff_sh()
elif method=='tf_knopoff_sh_adv':
theclass.tf_knopoff_sh_adv()
plt.plot(theclass.freq,np.abs(theclass.tf[0]),label=method)
plt.xlabel('frequency (Hz)')
plt.ylabel('Amplification')
plt.yscale('log')
plt.xscale('log')
plt.grid(True,which='both')
plt.legend(loc='best',fancybox=True,framealpha=0.5)
#plt.axis('tight')
plt.autoscale(True,axis='x',tight=True)
plt.tight_layout()
plt.savefig('test.png', format='png')
click.echo(click.style('Calculation has been finished!',fg='green'))
def calc_knopoff_psv(data):
theclass = TFC(data)
theclass.tf_knopoff_psv_adv()
return theclass
def calc_knopoff_sh(data):
theclass = TFC(data)
theclass.tf_knopoff_sh()
return theclass
def calc_kramer(data):
theclass = TFC(data)
theclass.tf_kramer286_sh()
return theclass
def calc_kennet(data):
theclass = TFC(data)
theclass.tf_kennet_sh()
return theclass
from TFCalculator import TFCalculator as TFC import TFDisplayTools # validity test for SH PSV case using S wave as an input # filename fname = 'sampleinput_linear_elastic_1layer_halfspace.dat' fname2 = 'sampleinput_psv_s_linear_elastic_1layer_halfspace.dat' # input file reading datash = IOfile.parsing_input_file(fname) datapsvs = IOfile.parsing_input_file(fname2) # kramer print 'TF calculatoin using kramer approach' theclass1 = TFC(datash) theclass1.tf_kramer286_sh() # check/verify kramer calculation print 'calculation has been finished!' # knopoff sh complete print 'TF calculation using complete knopoff sh approach' theclass3 = TFC(datash) theclass3.tf_knopoff_sh_adv() print 'calculation has been finished!' # knopoff psv-s print 'TF calculation using complete knopoff psv-s approach' theclass4 = TFC(datapsvs) theclass4.tf_knopoff_psv_adv() print theclass4.tf[1][19] print 'calculation has been finished!'
print(' --> OK')
#003 - Kramer Transfer Function
print('003 - kramer TF')
f.write('003 - kramer TF\n')
f.write('fID\telapsedrd\tstdevrd\telapsed\tstdev\tsizetf\n')
for iid in inputfileid:
elapsedRead = []
elapsedTF = []
elapsedTFbytes = []
for i in range(ntest):
start = time.clock()
data = IOfile.parsing_input_file(inputlist[iid])
elapsedRead.append(time.clock()-start)
data['inputmotion']='dirac.dat'
theclass = TFC(data)
start = time.clock()
theclass.tf_kramer286_sh()
elapsedTF.append(time.clock()-start)
elapsedTFbytes.append(numpy.array(theclass.tf).nbytes)
f.write('%d\t%.2e\t%.2e\t%.2e\t%.2e\t%d\t\n'%(iid,np.mean(elapsedRead),np.std(elapsedRead),
np.mean(elapsedTF),np.std(elapsedTF),np.max(elapsedTFbytes)))
f.write('\n')
print(' --> OK')
#004 - Knopoff SH simple Transfer Function
print('004 - knopoff SH simple TF')
f.write('004 - knopoff SH simple TF\n')
f.write('fID\telapsedrd\tstdevrd\telapsed\tstdev\tsizetf\n')
for iid in inputfileid:
