In [1]:

    

import pandas as pd
import numpy as np
import json
import sys
from importlib import reload
sys.path.append('../scripts/')
import utils


    

In [2]:

    

reload(utils)


    

    
Out[2]:





<module 'utils' from '../scripts/utils.py'>

In [3]:

    

ls ../data/fault_data/


    

    




fault_df_inv.csv              galetzka_mainshock_ramp.shp
galetzka_mainshock.cpg        galetzka_mainshock_ramp.shx
galetzka_mainshock.dbf        gurla_pts_df.csv
galetzka_mainshock.prj        gurla_tri_stresses.geojson
galetzka_mainshock.qpj        gurla_tris.geojson
galetzka_mainshock.shp        mht_rup_stresses.csv
galetzka_mainshock.shx        tib_dog_pts_df.csv
galetzka_mainshock_ramp.cpg   tib_dog_tri_stresses.geojson
galetzka_mainshock_ramp.dbf   tib_dog_tris.geojson
galetzka_mainshock_ramp.prj   wnfs_tris.csv
galetzka_mainshock_ramp.qpj

In [4]:

    

with open('../data/fault_data/tib_dog_tris.geojson') as f:
    td = json.load(f)


    

In [5]:

    

td['features'][0]


    

    
Out[5]:





{'geometry': {'coordinates': [[[124496.1, 3172901.7, 4000.0],
    [125070.3, 3172690.8, 3743.0],
    [124256.8, 3172817.9, 4156.0],
    [124496.1, 3172901.7, 4000.0]]],
  'type': 'Polygon'},
 'properties': {'POINTA': 195.0,
  'POINTB': 11.0,
  'POINTC': 12.0,
  'area_sq_km': 0.058032022780406034,
  'center': [124607.73333333334, 3172803.466666667, 3966.3333333333335],
  'dip': 31.852099159915703,
  'rake': -131.86853092923565,
  'rake_err': 10,
  'strike': 332.71822991430054},
 'type': 'Feature'}

In [6]:

    

tdz = pd.read_csv('../data/gis/tib_dog_elev_pts.csv', index_col=2)
tdz.columns = ['x', 'y', 'z']

tdz.head()


    

    
Out[6]:






  

    

      

      
x
      
y
      
z
    
    

      
id
      

      

      

    
  
  

    

      
0
      
100713.406808
      
3207692.245450
      
2162
    
    

      
1
      
100001.512969
      
3208997.384156
      
2084
    
    

      
2
      
99357.418542
      
3210099.124623
      
2069
    
    

      
3
      
98526.875729
      
3211404.263330
      
2041
    
    

      
4
      
97204.787169
      
3212336.505263
      
2129
    
  

In [47]:

    

#utils.add_tri_z_values(td['features'], tdz, 'z')


    

In [7]:

    

td['features'][0]


    

    
Out[7]:





{'geometry': {'coordinates': [[[124496.1, 3172901.7, 4000.0],
    [125070.3, 3172690.8, 3743.0],
    [124256.8, 3172817.9, 4156.0],
    [124496.1, 3172901.7, 4000.0]]],
  'type': 'Polygon'},
 'properties': {'POINTA': 195.0,
  'POINTB': 11.0,
  'POINTC': 12.0,
  'area_sq_km': 0.058032022780406034,
  'center': [124607.73333333334, 3172803.466666667, 3966.3333333333335],
  'dip': 31.852099159915703,
  'rake': -131.86853092923565,
  'rake_err': 10,
  'strike': 332.71822991430054},
 'type': 'Feature'}

In [8]:

    

utils.add_tri_centers_area(td['features'])


    

In [9]:

    

utils.add_strike_dip(td['features'])
utils.add_rake_from_trend(td['features'], 100, 10)


    

In [10]:

    

tib_dog_pts_df = utils.tri_dict_to_df(td, fault_name='tib_dog')


    

In [11]:

    

tib_dog_pts_df.head()


    

    
Out[11]:






  

    

      

      

      
x
      
y
      
z
      
fault_name
    
    

      
tri
      
vertex
      

      

      

      

    
  
  

    

      
0
      
a
      
124496.1
      
3172902
      
4000
      
tib_dog
    
    

      
b
      
125070.3
      
3172691
      
3743
      
tib_dog
    
    

      
c
      
124256.8
      
3172818
      
4156
      
tib_dog
    
    

      
m
      
124607.7
      
3172803
      
3966.333
      
tib_dog
    
    

      
1
      
a
      
124058.1
      
3173298
      
4000
      
tib_dog
    
  

In [12]:

    

tib_dog_pts_df.to_csv('../data/fault_data/tib_dog_pts_df.csv')


    

In [13]:

    

with open('../data/fault_data/tib_dog_tris.geojson', 'w') as f:
    json.dump(td, f)


    

In [14]:

    

strikes = [feat['properties']['strike'] for feat in td['features']]
dips = [feat['properties']['dip'] for feat in td['features']]
rakes = [feat['properties']['rake'] for feat in td['features']]
cx = [feat['properties']['center'][0] for feat in td['features']]
cy = [feat['properties']['center'][1] for feat in td['features']]
cz = [feat['properties']['center'][2] for feat in td['features']]


    

In [15]:

    

td['features'][120]


    

    
Out[15]:





{'geometry': {'coordinates': [[[107466.0, 3187793.9, 4000.0],
    [111001.4, 3188565.6, 2000.0],
    [107917.1, 3186682.9, 4004.0],
    [107466.0, 3187793.9, 4000.0]]],
  'type': 'Polygon'},
 'properties': {'POINTA': 202.0,
  'POINTB': 184.0,
  'POINTC': 27.0,
  'area_sq_km': 2.4518844061906653,
  'center': [108794.83333333333, 3187680.8000000003, 3334.6666666666665],
  'dip': 29.311525533043664,
  'rake': -118.99541215745927,
  'rake_err': 10,
  'strike': 337.56090898408797},
 'type': 'Feature'}

In [16]:

    

%matplotlib inline
%config InlineBackend.figure_format = 'retina'

import matplotlib.pyplot as plt


    

In [17]:

    

plt.figure(figsize=(12, 12))

plt.scatter(cx, cy, c=strikes,
           s=50, lw=0)
plt.colorbar()
plt.axis('equal')

plt.show()


    

In [18]:

    

plt.figure(figsize=(12, 12))

plt.scatter(cx, cy, c=rakes,
           s=50, lw=0)
plt.colorbar()
plt.axis('equal')

plt.show()


    

In [ ]:

    




    

In [ ]:

    




    

In [9]:

    

with open('../data/fault_data/tib_dog_tri_stresses.geojson') as f:
    td = json.load(f)


    

In [11]:

    

utils.add_rake_from_trend(td['features'], 90., 15)


    

In [13]:

    

with open('../data/fault_data/tib_dog_tri_stresses.geojson', 'w') as f:
    json.dump(td, f)


    

In [ ]: