Merge pull request #72 from mikhailsirenko/develop

Develop

config/Example.yaml

@@ -4,16 +4,16 @@ constants:
 
   # Each spatial unit has an array of outcomes that are calculated for it
   spatial_units:
+    - region_0
     - region_1
     - region_2
-    - region_3
 
   # Global economic parameters specific to the country
   economic_params:
     average_productivity: 0.25  # average of cgdpo / cn for the last 5 years from the Penn World Table https://www.rug.nl/ggdc/productivity/pwt/?lang=en
-    income_and_expenditure_growth: 0.02 # assumption source: ?
+    income_and_expenditure_growth: 0.02
     consumption_utility: 1.5 # assumption source: Hallegatte et al. (2017) choose a standard value of 1.5 to represent the elasticity of the marginal utility of consumption
-    discount_rate: 0.04 # assumption source: ?
+    discount_rate: 0.04
 
   # Recovery parameters
   recovery_params:
@@ -38,24 +38,28 @@ constants:
 
   # Estimation and randomization parameters
   income_params:
-    estimate: true
-    randomize: true
+    estimate: false
+    randomize: false
     distribution: uniform
-    inc_exp_ratio: 1.3 # assumption source?
+    inc_exp_ratio: 1.3
     delta: 0.1  # absolute deviation from the base income to expenditure ratio
   savings_params:
-    estimate: true 
-    randomize: true
+    estimate: false
+    randomize: false
     cap_with_max_savings_rate: false # whether to cap the savings rate with the maximum savings rate
     distribution: uniform
     delta: 0.01  # absolute deviation from the base savings rate
     max_savings_rate: 0.1  # maximum savings rate to prevent unrealistic values during randomization 
   rent_params:
-    estimate: true
-    randomize: true
+    estimate: false
+    randomize: false
     distribution: uniform
-    pct_of_income: 0.14 # assumption source?
+    pct_of_income: 0.3
     delta: 0.05  # absolute deviation from the base rent as a percentage of income
+  dwelling_params:
+    estimate: false
+  effective_capital_stock_params:
+    estimate: false
   dwelling_vulnerability_params:
     randomize: true
     distribution: uniform

data/generated/Example/optimal_reconstruction_rates.csv

@@ -0,0 +1,72 @@
+v,reconstruction_rate
+0.2,0.45000000000000023
+0.21,0.4300000000000002
+0.22,0.4100000000000002
+0.23,0.3900000000000002
+0.24,0.37000000000000016
+0.25,0.36000000000000015
+0.26,0.34000000000000014
+0.27,0.3200000000000001
+0.28,0.3100000000000001
+0.29,0.2900000000000001
+0.3,0.2800000000000001
+0.31,0.2700000000000001
+0.32,0.26000000000000006
+0.33,0.24000000000000007
+0.34,0.23000000000000007
+0.35,0.22000000000000006
+0.36,0.21000000000000005
+0.37,0.20000000000000004
+0.38,0.19000000000000003
+0.39,0.18000000000000002
+0.4,0.17
+0.41,0.17
+0.42,0.16
+0.43,0.15
+0.44,0.13999999999999999
+0.45,0.13999999999999999
+0.46,0.12999999999999998
+0.47,0.11999999999999998
+0.48,0.11999999999999998
+0.49,0.10999999999999999
+0.5,0.10999999999999999
+0.51,0.09999999999999999
+0.52,0.09999999999999999
+0.53,0.09
+0.54,0.09
+0.55,0.08
+0.56,0.08
+0.57,0.07
+0.58,0.07
+0.59,0.07
+0.6,0.060000000000000005
+0.61,0.060000000000000005
+0.62,0.060000000000000005
+0.63,0.05
+0.64,0.05
+0.65,0.05
+0.66,0.05
+0.67,0.04
+0.68,0.04
+0.69,0.04
+0.7,0.04
+0.71,0.04
+0.72,0.03
+0.73,0.03
+0.74,0.03
+0.75,0.03
+0.76,0.03
+0.77,0.03
+0.78,0.02
+0.79,0.02
+0.8,0.02
+0.81,0.02
+0.82,0.02
+0.83,0.02
+0.84,0.02
+0.85,0.02
+0.86,0.02
+0.87,0.01
+0.88,0.01
+0.89,0.01
+0.9,0.01

data/processed/asset_impacts/Example/earthquake.csv

@@ -1,13 +1,13 @@
 disaster_type,spatial_unit,residential,non_residential,total_exposed_stock,rp,pml,loss_fraction
-earthquake,region_0,156181017.83,97535715.32,253716733.15,10,47495618.74,0.187
-earthquake,region_1,189798772.63,57800932.02,247599704.65,10,37139955.7,0.15
-earthquake,region_2,108712541.83,93308807.29,202021349.11,10,35174240.36,0.174
-earthquake,region_0,206210886.67,51029224.71,257240111.38,50,68680790.78,0.267
-earthquake,region_1,224866396.12,60616955.53,285483351.65,50,53722969.89,0.188
-earthquake,region_2,127510676.48,65212112.15,192722788.63,50,42876126.35,0.222
-earthquake,region_0,164791752.8,64561457.01,229353209.81,100,69077812.89,0.301
-earthquake,region_1,120924079.1,64607232.43,185531311.52,100,51324674.09,0.277
-earthquake,region_2,168410497.63,89258798.07,257669295.7,100,66985611.25,0.26
-earthquake,region_0,177135165.76,79620728.44,256755894.21,250,116732794.12,0.455
-earthquake,region_1,191131727.79,58526206.18,249657933.97,250,113970134.92,0.457
-earthquake,region_2,242332830.59,98281601.65,340614432.24,250,170307216.12,0.5
+earthquake,region_0,22816317.94,7605439.31,30421757.25,10,664837.44,0.022
+earthquake,region_1,28084296.43,9361432.14,37445728.57,10,2975865.62,0.079
+earthquake,region_2,21622864.59,7207621.53,28830486.13,10,1660618.53,0.058
+earthquake,region_0,22816317.94,7605439.31,30421757.25,50,3707373.26,0.122
+earthquake,region_1,28084296.43,9361432.14,37445728.57,50,2905858.34,0.078
+earthquake,region_2,21622864.59,7207621.53,28830486.13,50,2237229.93,0.078
+earthquake,region_0,22816317.94,7605439.31,30421757.25,100,5013759.96,0.165
+earthquake,region_1,28084296.43,9361432.14,37445728.57,100,9197330.53,0.246
+earthquake,region_2,21622864.59,7207621.53,28830486.13,100,6317091.09,0.219
+earthquake,region_0,22816317.94,7605439.31,30421757.25,250,15210878.62,0.5
+earthquake,region_1,28084296.43,9361432.14,37445728.57,250,16927657.99,0.452
+earthquake,region_2,21622864.59,7207621.53,28830486.13,250,14415243.06,0.5

data/processed/asset_impacts/Example/flood.csv

@@ -1,13 +1,13 @@
 disaster_type,spatial_unit,residential,non_residential,total_exposed_stock,rp,pml,loss_fraction
-flood,region_0,156181017.83,97535715.32,253716733.15,10,21109078.49,0.083
-flood,region_1,189798772.63,57800932.02,247599704.65,10,12379985.23,0.05
-flood,region_2,108712541.83,93308807.29,202021349.11,10,14164020.06,0.07
-flood,region_0,206210886.67,51029224.71,257240111.38,50,37811977.41,0.147
-flood,region_1,224866396.12,60616955.53,285483351.65,50,19464967.69,0.068
-flood,region_2,127510676.48,65212112.15,192722788.63,50,19749391.72,0.102
-flood,region_0,164791752.8,64561457.01,229353209.81,100,36968363.51,0.161
-flood,region_1,120924079.1,64607232.43,185531311.52,100,25350290.48,0.137
-flood,region_2,168410497.63,89258798.07,257669295.7,100,30911909.85,0.12
-flood,region_0,177135165.76,79620728.44,256755894.21,250,65381615.28,0.255
-flood,region_1,191131727.79,58526206.18,249657933.97,250,64038548.12,0.257
-flood,region_2,242332830.59,98281601.65,340614432.24,250,102184329.67,0.3
+flood,region_0,22816317.94,7605439.31,30421757.25,10,152108.79,0.005
+flood,region_1,28084296.43,9361432.14,37445728.57,10,2316820.8,0.062
+flood,region_2,21622864.59,7207621.53,28830486.13,10,1153201.98,0.04
+flood,region_0,22816317.94,7605439.31,30421757.25,50,2247128.91,0.074
+flood,region_1,28084296.43,9361432.14,37445728.57,50,1108463.37,0.03
+flood,region_2,21622864.59,7207621.53,28830486.13,50,853366.59,0.03
+flood,region_0,22816317.94,7605439.31,30421757.25,100,2397488.83,0.079
+flood,region_1,28084296.43,9361432.14,37445728.57,100,5976997.87,0.16
+flood,region_2,21622864.59,7207621.53,28830486.13,100,3837669.29,0.133
+flood,region_0,22816317.94,7605439.31,30421757.25,250,9126527.17,0.3
+flood,region_1,28084296.43,9361432.14,37445728.57,250,9438512.28,0.252
+flood,region_2,21622864.59,7207621.53,28830486.13,250,8649145.84,0.3

data/processed/asset_impacts/Example/hurricane.csv

@@ -1,13 +1,13 @@
 disaster_type,spatial_unit,residential,non_residential,total_exposed_stock,rp,pml,loss_fraction
-hurricane,region_0,156181017.83,97535715.32,253716733.15,10,34302348.62,0.135
-hurricane,region_1,189798772.63,57800932.02,247599704.65,10,24759970.47,0.1
-hurricane,region_2,108712541.83,93308807.29,202021349.11,10,24669130.21,0.122
-hurricane,region_0,206210886.67,51029224.71,257240111.38,50,53246384.09,0.207
-hurricane,region_1,224866396.12,60616955.53,285483351.65,50,36593968.79,0.128
-hurricane,region_2,127510676.48,65212112.15,192722788.63,50,31312759.03,0.162
-hurricane,region_0,164791752.8,64561457.01,229353209.81,100,53023088.2,0.231
-hurricane,region_1,120924079.1,64607232.43,185531311.52,100,38337482.29,0.207
-hurricane,region_2,168410497.63,89258798.07,257669295.7,100,48948760.55,0.19
-hurricane,region_0,177135165.76,79620728.44,256755894.21,250,91057204.7,0.355
-hurricane,region_1,191131727.79,58526206.18,249657933.97,250,89004341.52,0.357
-hurricane,region_2,242332830.59,98281601.65,340614432.24,250,136245772.9,0.4
+hurricane,region_0,22816317.94,7605439.31,30421757.25,10,397125.98,0.013
+hurricane,region_1,28084296.43,9361432.14,37445728.57,10,2646343.21,0.071
+hurricane,region_2,21622864.59,7207621.53,28830486.13,10,1406910.26,0.049
+hurricane,region_0,22816317.94,7605439.31,30421757.25,50,2977251.08,0.098
+hurricane,region_1,28084296.43,9361432.14,37445728.57,50,2007160.85,0.054
+hurricane,region_2,21622864.59,7207621.53,28830486.13,50,1545298.26,0.054
+hurricane,region_0,22816317.94,7605439.31,30421757.25,100,3705624.4,0.122
+hurricane,region_1,28084296.43,9361432.14,37445728.57,100,7587164.2,0.203
+hurricane,region_2,21622864.59,7207621.53,28830486.13,100,5077380.19,0.176
+hurricane,region_0,22816317.94,7605439.31,30421757.25,250,12168702.9,0.4
+hurricane,region_1,28084296.43,9361432.14,37445728.57,250,13183085.14,0.352
+hurricane,region_2,21622864.59,7207621.53,28830486.13,250,11532194.45,0.4