1 SLAM Calculator Overview

area = slam.DEM(longitude=-120.160, latitude=39.438, lon_del=0.2, lat_del=0.2)

lat_min, lat_max, lon_min, lon_max = area.get_bounds()

print(lat_min, lat_max, lon_min, lon_max)

(39.238, 39.638000000000005, -119.96, -120.36)

1.1.1   Get DEM File

dem_file = area.get_dem(lat_min, lat_max, lon_min, lon_max)

Begin Downloading DEM File...  
Downloaded DEM file in 7.6 seconds  
Processing...  
Complete.

1.2 Get Quaternary Faults and Folds Shapefile

from geo_slam_calculator_v1 import qFaults

1.2.0 Instantiate QFaults Class

qfaults = qFaults.get_qfaults()

1.2.1   Different Shape Files Available via USGS

Default value for get_qfaults for the file name of the shape file is 'Qfaults_GIS'. Other files can be found on the qfaults page. However, not all of the files are shapefiles. If the selection is not a shape file, it will return an error.

1.3 Obtain Event Data

1.3.0 Instantiate the 'get_data' Class

data = slam.get_data(lat_min=lat_min, lat_max=lat_max, lon_min=lon_min, lon_max=lon_max)

1.3.1   Query for Events within the DEM Area

events_1983 = data.event_query(start_time='1983-07-02', end_time='1983-07-04', min_mag=3)

Downloaded Regional Earthquake Data in 0.6760 seconds

1.3.2 Get Individual Focal Data

focal_data_1983 = data.focal_data(earthquakes=events_1983)
focal_data_1983.focal_data

1.3.3 Viewing Error Data

focal_data_1983.error_data

1.3.4 Focal and Error Data Combined

eq1_1983 = focal_data_1983.data[focal_data_1983.data['ID']=='B2'].reset_index(drop=True)

1.4 Prepare Variables for Swath Calculations

1.4.0 Instantiate the 'swaths' Class

swaths_init = slam.swaths(elevation=dem_file.elevation)

1.4.1   Calculate Grid North Adjustment

gridNorthAdjustment_1983 = swaths_init.grid_adjustment(longitude=-120.160, latitude=39.438, zoneMeridian=-123)

Grid North Adjustment: -1.80

1.4.2 Combine Focal Data Points

focal_data_1983 = swaths_init.focal_metrics(lon=-120.206, lat=39.412, depth=11.05)

Latitude: 39.412
Longitude: -120.206
Depth: -11050.0 meters

1.4.3 Computations of the 1st Nodal Plane

nodal_comps_1983 = swaths_init.nodal_comps(strike=eq1_1983.np1_strike, grid_adjust=gridNorthAdjustment_1983, 
                                           strike_uncert=eq1_1983.np1S_uncert, plunge=eq1_1983.np1_dip,
                                           dip_ang=eq1_1983.np1D_uncert)

Dip Trend: 300.0 
Dip Trend + North Grid Adjustment: 298.2 
Dip Trend Uncertainty: 8.0 
Dip Plunge: 80.0
Dip Angle Uncertainty: 13.0

1.4.4 Determine Errors Relative to the Nodal Plane

err_comps_1983 = swaths_init.err_computations(eh1=300, eh2=300, eh1Az=45, ez=0.8, grid_adjust=gridNorthAdjustment_1983)

eh1: 300.0 meters
eh1 Azimuth: 43.2 
eh2: 300.0 meters
ez: 800.0 meters

1.4.5 Calculate Light Direction for DEM

lightDirection_1983 = swaths_init.light_direction(nodal_comps_1983[1])

Light Direction: 61.80

1.5 Calculate Swaths and Seismo-Lineament Bounds

1.5.0 Calculate Swaths

swaths_1983 = swaths_init.swath_calc(npDipPlunge=nodal_comps_1983[3], npDipAngUncert=nodal_comps_1983[4], 
                                     npDipTr=nodal_comps_1983[1], npDipTrendUncert=nodal_comps_1983[2], 
                                     widthFactor=1.5, multiplier=1.5, cellsize=dem_file.cellsize, 
                                     cellsize_res=30, eh1=err_comps_1983[0], eh1Az=err_comps_1983[1], 
                                     eh2=err_comps_1983[2], ez=err_comps_1983[3], lat=focal_data_1983[0], 
                                     lon=focal_data_1983[1], focalDepth=focal_data_1983[2], 
                                     bounds=dem_file.bounds, thin=False)

1.5.1   Determine Seismo-Lineament Bounds

swaths_shade_1983 = swaths_init.get_shade(swaths_1983.swaths, corners_fill=['NE', 'SW'])

Begin computing Seismo-Lineament boundary area
Finished assessment of Seismo-Lineament boundary area in 10.39 seconds

1.6 Visualize Seismo-Lineament Bounds

1.6.0 Instantiate the 'SLAM_Viz' Class

maps = slam.SLAM_viz(elevation=dem_file.elevation)

1.6.1   Elevation Map using Open Topography DEM File

maps.elevation_map(middle_road=swaths_1983.middle_road, swaths_shade=swaths_shade_1983, 
                   lightDirection=lightDirection_1983, altDeg=12.5, lon=-120.206, lat=39.412, 
                   lon_max=lon_max, lon_min=lon_min, lat_max=lat_max, lat_min=lat_min, 
                   strike=eq1_1983.np1_strike, dip=eq1_1983.np1_dip, rake=eq1_1983.np1_rake, 
                   faults=qfaults, title='A2')

1.6.2 Physical Map using Stamen and OpenStreetMap

maps.physical_map(middle_road=swaths_1983.middle_road, swaths_shade=swaths_shade_1983, 
                  lon=focal_data_1983[1], lat=focal_data_1983[0], lon_max=lon_max, 
                  lon_min=lon_min, lat_max=lat_max, lat_min=lat_min, strike=eq1_1983.np1_strike, 
                  dip=eq1_1983.np1_dip, rake=eq1_1983.np1_rake, title='A2', tiler_size=11, faults=qfaults)

Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL

1.6.3 Multiple Solutions - Elevation Map

These are the multiple solutions taken from section 2, the Ashburn thesis, section of this document.

Must put items into a list:

swaths_mult = [swaths.swaths, swaths_1983.swaths, swaths_1992.swaths]
middle_road_mult = [swaths.middle_road, swaths_1983.middle_road, swaths_1992.middle_road]
swaths_shade_mult = [swaths_shade, swaths_shade_1983, swaths_shade_1992]
lon_mult = [focal_data[1], focal_data_1983[1], focal_data_1992[1]]
lat_mult = [focal_data[0], focal_data_1983[0], focal_data_1992[0]]
strike_mult = [44, eq1_1983.np1_strike, eq1_1992.np1_strike]
dip_mult = [80, eq1_1983.np1_dip, eq1_1992.np1_dip]
rake_mult = [180, eq1_1983.np1_rake, eq1_1992.np1_rake]
title = ['A1', 'A2', 'A3']
colors_ = ['lightblue', 'green', 'yellow']

maps.elevation_mult(swaths_shade=swaths_shade_mult, lightDirection=lightDirection_1992, altDeg=12.5, 
                    lon=lon_mult, lat=lat_mult, lon_max=lon_max, lon_min=lon_min, 
                    lat_max=lat_max, lat_min=lat_min, strike=strike_mult, dip=dip_mult, 
                    rake=rake_mult, title=title, colors_=colors_, faults=qfaults)

1.6.4 Multiple Solutions - Physical Map

maps.physical_mult(lon=lon_mult, lat=lat_mult, lon_max=lon_max, lon_min=lon_min, 
                   lat_max=lat_max, lat_min=lat_min, strike=strike_mult, 
                   dip=dip_mult, rake=rake_mult, title=title, tiler_size=11, 
                   faults=qfaults, focal_size=0.5)

Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL

1 SLAM Calculator Overview

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