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Structure for cloud analysis
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@VSilva
VSilva committed Jan 16, 2019
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21 changes: 11 additions & 10 deletions notebooks/vulnerability/derivation_fragility/NLTHA_on_SDOF/NLTHA_on_SDOF.ipynb
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Expand Up @@ -20,18 +20,19 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"ename": "SyntaxError",
"evalue": "invalid syntax (utils.py, line 434)",
"ename": "ModuleNotFoundError",
"evalue": "No module named 'scipy'",
"output_type": "error",
"traceback": [
"Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
" File \u001b[1;32m\"/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2961\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n exec(code_obj, self.user_global_ns, self.user_ns)\n",
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-1-a0f7315c782f>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0;36m, in \u001b[0;35m<module>\u001b[0;36m\u001b[0m\n\u001b[0;31m from rmtk.vulnerability.common import utils\u001b[0m\n",
"\u001b[0;36m File \u001b[0;32m\"/Users/vitorsilva/Dropbox/GEM/git/gem/rmtk/rmtk/vulnerability/common/utils.py\"\u001b[0;36m, line \u001b[0;32m434\u001b[0m\n\u001b[0;31m print str((it+1)*100/len(T))+'%'\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-2-a0f7315c782f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mrmtk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvulnerability\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcommon\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mutils\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mrmtk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvulnerability\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mderivation_fragility\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNLTHA_on_SDOF\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mNLTHA_on_SDOF\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mrmtk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvulnerability\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mderivation_fragility\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNLTHA_on_SDOF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_pinching_parameters\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mread_parameters\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'matplotlib'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/Dropbox/GEM/git/gem/rmtk/rmtk/vulnerability/common/utils.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mscipy\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mintegrate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mshapely\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgeometry\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mLineString\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mMultiPoint\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mPoint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minterpolate\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0minterp1d\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'scipy'"
]
}
],
Expand Down Expand Up @@ -148,7 +149,7 @@
"source": [
"damping_ratio = 0.05\n",
"degradation = True\n",
"PDM, Sds = NLTHA_on_SDOF.calculate_fragility(capacity_curves, hysteresis, gmrs, damage_model, damping_ratio, degradation)\n",
"EDPs = NLTHA_on_SDOF.calculate_response(capacity_curves, hysteresis, gmrs, damage_model, damping_ratio, degradation)\n",
"utils.save_result(PDM,'../../../../../rmtk_data/PDM.csv')"
]
},
Expand All @@ -170,8 +171,8 @@
"outputs": [],
"source": [
"minT, maxT,stepT = 0.0, 2.0, 0.1\n",
"regression_method = 'least squares'\n",
"utils.evaluate_optimal_IM(gmrs,PDM,minT,maxT,stepT,damage_model,damping_ratio,regression_method)"
"regression_method = 'cloud analysis'\n",
"utils.evaluate_optimal_IM(gmrs,EDPs,minT,maxT,stepT,damage_model,damping_ratio,regression_method)"
]
},
{
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57 changes: 33 additions & 24 deletions rmtk/vulnerability/common/utils.py
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Expand Up @@ -600,7 +600,7 @@ def calculate_iml(igmr, gmrs, IMT, T, damping):

return iml

def calculate_mean_fragility(gmrs, PDM, T, damping, IMT, damage_model, method):
def calculate_mean_fragility(gmrs, EDPs, T, damping, IMT, damage_model, method):

imls = calculate_imls(gmrs, T, damping)

Expand All @@ -613,31 +613,40 @@ def calculate_mean_fragility(gmrs, PDM, T, damping, IMT, damage_model, method):
elif IMT == 'PGA':
imls = imls[2]

cumPDM = convert_damage_matrix_to_probability(PDM)
if method == 'cloud analysis':
Sds = EDPs[1]
#calculate log(SDs) versus log(IMLs)
#regression analysis using censored
#with

else:
PDM = response[0]
cumPDM = convert_damage_matrix_to_probability(PDM)

logmeans, logstddev = [], []
if method == 'least squares':
for iDS in range(len(damage_model['damage_states'])):
solution, _ = optimize.leastsq(residual_lognormal_dist,[0.1, 0.6],args=(imls, cumPDM[iDS+1]))
logmeans.append(solution[0])
logstddev.append(solution[1])

logmeans, logstddev = [], []
if method == 'least squares':
for iDS in range(len(damage_model['damage_states'])):
solution, _ = optimize.leastsq(residual_lognormal_dist,[0.1, 0.6],args=(imls, cumPDM[iDS+1]))
logmeans.append(solution[0])
logstddev.append(solution[1])

elif method == 'max likelihood':
# the imls and the PDM are sorted to be used in the maximum likelihood approach
# the PDM should be a list of integers in this approach
I = np.argsort(imls, axis=0)
imls = np.array(imls)
imls = imls[I]
PDM_mle = []
for iDS in range(len(damage_model['damage_states'])):
temp = cumPDM[iDS+1][I]*no_assets
temp2 = temp.astype(int)
PDM_mle = temp2.tolist()
solution = mle(PDM_mle,imls,no_assets,1)
logmeans.append(solution[0])
logstddev.append(solution[1])
elif method == 'max likelihood':
# the imls and the PDM are sorted to be used in the maximum likelihood approach
# the PDM should be a list of integers in this approach
I = np.argsort(imls, axis=0)
imls = np.array(imls)
imls = imls[I]
PDM_mle = []
for iDS in range(len(damage_model['damage_states'])):
temp = cumPDM[iDS+1][I]*no_assets
temp2 = temp.astype(int)
PDM_mle = temp2.tolist()
solution = mle(PDM_mle,imls,no_assets,1)
logmeans.append(solution[0])
logstddev.append(solution[1])

Rsquare = calculate_correlation(logmeans,logstddev,cumPDM,imls)
Rsquare = calculate_correlation(logmeans,logstddev,cumPDM,imls)


fragility_model = {'damage_states': None, 'logmean': None,'logstddev': None, 'IMT': None}
fragility_model['damage_states'] = damage_model['damage_states']
Expand Down
5 changes: 3 additions & 2 deletions rmtk/vulnerability/derivation_fragility/NLTHA_on_SDOF/NLTHA_on_SDOF.py
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Expand Up @@ -15,7 +15,7 @@
package_directory = os.path.dirname(os.path.abspath(__file__))


def calculate_fragility(capacity_curves, hysteresis, gmrs, damage_model,
def calculate_response(capacity_curves, hysteresis, gmrs, damage_model,
damping, degradation):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
Expand All @@ -33,7 +33,8 @@ def calculate_fragility(capacity_curves, hysteresis, gmrs, damage_model,
Sdi = max(numpy.abs(numpy.array(disps)))
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds

return [PDM, Sds]


def run_time_history_analysis(capacity_curves, hysteresis, icc, gmrs, igmr,
Expand Down

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