GALE.py

import inputProcessing
import groundShakingCalculation
import outputProcessing

eventID = 1

print('ACCESSING INGV SHAKEMAP DATABASE...')
# inputProcessing.save_online_data_to_xml(eventID)

print('SAVING INGV DATA INTO XML...')
groundShakingData, IMTs = inputProcessing.parse_INGV_xml_data(eventID)
#IMTs = ['PGA', 'SA(0.3)']

outputProcessing.save_data_to_csv(groundShakingData, 'rawtnepal.csv')

#croppedShakingData = inputProcessing.cropShakingData(groundShakingData,'box',[10.5,12,44.5,45.5])

#reducedShakingData = inputProcessing.reduceShakingData(groundShakingData,[10.5,12,44.2,45.8],0.02)

# outputProcessing.save_mean_std_to_csv(reducedShakingData,'statdata.csv')

#locations =  inputProcessing.exportLocation(reducedShakingData)
locations = inputProcessing.extract_location_exposure('exposure_test.xml')
print(locations)

print('CALCULATING CLOSEST GROUND SHAKING...')
closestGroundShaking = inputProcessing.extract_closest_ground_shaking(
    locations, groundShakingData)
outputProcessing.save_data_to_csv(closestGroundShaking, 'closestnepal.csv')
print(closestGroundShaking)

print('CALCULATING DISTANCE BETWEEN LOCATIONS...')
distanceMatrix = groundShakingCalculation.calculate_distance_matrix(locations)
print(distanceMatrix)

print('CALCULATING SPATIAL CORRELATION MATRIX...')
spatialCorrMatrices = groundShakingCalculation.\
                      calculate_spatial_correlation_matrices(
                          distanceMatrix, IMTs, 'spatial')
print(spatialCorrMatrices)

print('CALCULATING SPATIAL COVARIANCE MATRIX...')
spatialCovMatrices = groundShakingCalculation.\
                     calculate_spatial_covariance_matrices(
                         closestGroundShaking, spatialCorrMatrices)
print(spatialCovMatrices)

print('CALCULATING CROSS-CORRELATION MATRIX...')
crossCorrMatrix = groundShakingCalculation.calculate_cross_correlation_matrix(
    IMTs, 'cross')
print(crossCorrMatrix)

print('GENERATING SPATIALLY-CROSS-CORRELATED RANDOM FIEDS OF GROUND MOTION...')
gmfs = groundShakingCalculation.generate_random_fields_ground_motion(
    closestGroundShaking, spatialCovMatrices, crossCorrMatrix, 2000)
#print('SAVING GROUND MOTION FIELDS IN NRML FORMAT..')

outputProcessing.save_gmfs_to_csv(eventID, locations, gmfs)
# print(IMTs)
# print(exposureLocations)
# print(gmfs)
outputProcessing.save_gmfs_to_xml(eventID, IMTs, locations, gmfs)
# outputProcessing.calculate_percentiles_gmfs([16,50,84],IMTs,exposureLocations,gmfs)