Add more fields to CSV reports

docs/src/format.md

@@ -1,6 +1,7 @@
 # Input data format
 
-RELOG accepts as input a JSON file with four sections: `parameters`, `products`, `centers` and `plants`. Below, we describe each section in more detail.
+RELOG accepts as input a JSON file with four sections: `parameters`, `products`,
+`centers` and `plants`. Below, we describe each section in more detail.
 
 ## Parameters
 
@@ -24,11 +25,12 @@ RELOG accepts as input a JSON file with four sections: `parameters`, `products`,
 
 ## Products
 
-| Key                                         | Description                                                                                                                                                                                            |
-| :------------------------------------------ | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `transportation cost ($/km/tonne)`          | The cost to transport this product. Must be a time series.                                                                                                                                             |
-| `transportation energy (J/km/tonne)`        | The energy required to transport this product. Must be a time series. Optional.                                                                                                                        |
-| `transportation emissions (tonne/km/tonne)` | A dictionary mapping the name of each greenhouse gas, produced to transport one tonne of this product along one kilometer, to the amount of gas produced (in tonnes). Must be a time series. Optional. |
+| Key                                         | Description                                                                                                                                                                                                                 |
+| :------------------------------------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `transportation cost ($/km/tonne)`          | The cost to transport this product. Must be a time series.                                                                                                                                                                  |
+| `transportation energy (J/km/tonne)`        | The energy required to transport this product. Must be a time series. Optional.                                                                                                                                             |
+| `transportation emissions (tonne/km/tonne)` | A dictionary mapping the name of each greenhouse gas, produced to transport one tonne of this product along one kilometer, to the amount of gas produced (in tonnes). Must be a time series. Optional.                      |
+| `disposal limit (tonne)`                    | Global disposal limit for this product, per year, across all plants and centers. Entry may be `null` if unlimited. Note that individual plants and centers may also have their individual disposal limits for this product. |
 
 #### Example
 
@@ -41,7 +43,8 @@ RELOG accepts as input a JSON file with four sections: `parameters`, `products`,
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 0.052,
         "CH4": 0.003
-      }
+      },
+      "disposal limit (tonne)": 100.0,
     }
   }
 }

docs/src/problem.md

@@ -5,8 +5,8 @@
 The mathematical model employed by RELOG is based on three main components:
 
 1. **Products and Materials:** Inputs and outputs for both manufacturing and
-   recycling plants. This include raw materials, whether virgin or recovered, and
-   final products, whether new or at their end-of-life. Each product has
+   recycling plants. This include raw materials, whether virgin or recovered,
+   and final products, whether new or at their end-of-life. Each product has
    associated transportation parameters, such as costs, energy and emissions.
 
 2. **Manufacturing and Recycling Plants:** Facilities that take in specific
@@ -48,23 +48,24 @@ The mathematical model employed by RELOG is based on three main components:
 
 ## Constants
 
-| Symbol                      | Description                                                                                                                                                                                                      | Unit          |
-| :-------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------ |
-| $K^{\text{dist}}_{uv}$      | Distance between plants/centers $u$ and $v$                                                                                                                                                                      | km            |
-| $K^\text{cap}_{p}$          | Capacity of plant $p$, if the plant is open                                                                                                                                                                      | tonne         |
-| $K^\text{disp-limit}_{pmt}$ | Maximum amount of material $m$ that can be disposed of at plant $p$ at time $t$                                                                                                                                  | tonne         |
-| $K^\text{mix}_{pmt}$        | If plant $p$ receives one tonne of input material at time $t$, then $K^\text{mix}_{pmt}$ is the amount of product $m$ in this mix. Must be between zero and one, and the sum of these amounts must equal to one. | tonne         |
-| $K^\text{output}_{pmt}$     | Amount of material $m$ produced by plant $p$ at time $t$ for each tonne of input material processed                                                                                                              | tonne         |
-| $R^\text{tr}_{mt}$          | Cost to send material $m$ at time $t$                                                                                                                                                                            | \$/km-tonne   |
-| $R^\text{collect}_{cmt}$    | Cost of collecting material $m$ at center $c$ at time $t$                                                                                                                                                        | \$/tonne      |
-| $R^\text{disp}_{umt}$       | Cost to dispose of material at plant/center $u$ at time $t$                                                                                                                                                      | \$/tonne      |
-| $R^\text{fix}_{ut}$         | Fixed operating cost for plant/center $u$ at time $t$                                                                                                                                                            | \$            |
-| $R^\text{open}_{pt}$        | Cost to open plant $p$ at time $t$                                                                                                                                                                               | \$            |
-| $R^\text{rev}_{ct}$         | Revenue for selling the input product of center $c$ at this center at time $t$                                                                                                                                   | \$/tonne      |
-| $R^\text{var}_{pt}$         | Cost to process one tonne of input material at plant $p$ at time $t$                                                                                                                                             | \$/tonne      |
-| $K^\text{out-fix}_{cmt}$    | Fixed amount of material $m$ collected at center $m$ at time $t$                                                                                                                                                 | \$/tonne      |
-| $K^\text{out-var}_{c,m,i}$  | Factor used to calculate variable amount of material $m$ collected at center $m$. See `eq_z_collected` for more details.                                                                                         | --      |
-| $K^\text{out-var-len}_{cm}$      | Length of the $K^\text{out-var}_{c,m,*}$ vector.                                                                                                                                                                 | -- |
+| Symbol                      | Description                                                                                                                                                                                                      | Unit        |
+| :-------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------- |
+| $K^{\text{dist}}_{uv}$      | Distance between plants/centers $u$ and $v$                                                                                                                                                                      | km          |
+| $K^\text{cap}_{p}$          | Capacity of plant $p$, if the plant is open                                                                                                                                                                      | tonne       |
+| $K^\text{disp-limit}_{mt}$  | Maximum amount of material $m$ that can be disposed of (globally) at time $t$                                                                                                                                    | tonne       |
+| $K^\text{disp-limit}_{mut}$ | Maximum amount of material $m$ that can be disposed of at plant/center $u$ at time $t$                                                                                                                           | tonne       |
+| $K^\text{mix}_{pmt}$        | If plant $p$ receives one tonne of input material at time $t$, then $K^\text{mix}_{pmt}$ is the amount of product $m$ in this mix. Must be between zero and one, and the sum of these amounts must equal to one. | tonne       |
+| $K^\text{output}_{pmt}$     | Amount of material $m$ produced by plant $p$ at time $t$ for each tonne of input material processed                                                                                                              | tonne       |
+| $R^\text{tr}_{mt}$          | Cost to send material $m$ at time $t$                                                                                                                                                                            | \$/km-tonne |
+| $R^\text{collect}_{cmt}$    | Cost of collecting material $m$ at center $c$ at time $t$                                                                                                                                                        | \$/tonne    |
+| $R^\text{disp}_{umt}$       | Cost to dispose of material at plant/center $u$ at time $t$                                                                                                                                                      | \$/tonne    |
+| $R^\text{fix}_{ut}$         | Fixed operating cost for plant/center $u$ at time $t$                                                                                                                                                            | \$          |
+| $R^\text{open}_{pt}$        | Cost to open plant $p$ at time $t$                                                                                                                                                                               | \$          |
+| $R^\text{rev}_{ct}$         | Revenue for selling the input product of center $c$ at this center at time $t$                                                                                                                                   | \$/tonne    |
+| $R^\text{var}_{pt}$         | Cost to process one tonne of input material at plant $p$ at time $t$                                                                                                                                             | \$/tonne    |
+| $K^\text{out-fix}_{cmt}$    | Fixed amount of material $m$ collected at center $m$ at time $t$                                                                                                                                                 | \$/tonne    |
+| $K^\text{out-var}_{c,m,i}$  | Factor used to calculate variable amount of material $m$ collected at center $m$. See `eq_z_collected` for more details.                                                                                         | --          |
+| $K^\text{out-var-len}_{cm}$ | Length of the $K^\text{out-var}_{c,m,*}$ vector.                                                                                                                                                                 | --          |
 
 ## Decision variables
 
@@ -196,7 +197,7 @@ The goals is to minimize a linear objective function with the following terms:
 \end{align*}
 ```
 
-- Disposal limit at the plants (`eq_keep_open[p.name, t]`):
+- Disposal limit at the plants (`eq_disposal_limit[p.name, m.name, t]`):
 
 ```math
 \begin{align*}
@@ -255,3 +256,12 @@ The goals is to minimize a linear objective function with the following terms:
 & \forall c \in C, m \in M^+_c, t \in T
 \end{align*}
 ```
+
+- Global disposal limit (`eq_disposal_limit[m.name, t]`)
+
+```math
+\begin{align*}
+& \sum_{p \in P} z^\text{disp}_{pmt} + \sum_{c \in C} z^\text{disp}_{cmt} \leq K^\text{disp-limit}_{mt}
+& \forall m \in M, t \in T
+\end{align*}
+```

src/instance/parse.jl

@@ -20,9 +20,10 @@ function parse(json)::Instance
         error("Invalid distance metric: $distance_metric_str")
     end
 
-    timeseries(x::Union{Nothing,Number}) = repeat([x], time_horizon)
-    timeseries(x::Array) = x
-    timeseries(d::OrderedDict) = OrderedDict(k => timeseries(v) for (k, v) in d)
+    timeseries(::Nothing; null_val=nothing) = repeat([null_val], time_horizon)
+    timeseries(x::Number; null_val=nothing) = repeat([x], time_horizon)
+    timeseries(x::Array; null_val=nothing) = [xi === nothing ? null_val : xi for xi in x]
+    timeseries(d::OrderedDict; null_val=nothing) = OrderedDict(k => timeseries(v; null_val) for (k, v) in d)
 
     # Read products
     products = Product[]
@@ -31,7 +32,8 @@ function parse(json)::Instance
         tr_cost = timeseries(pdict["transportation cost (\$/km/tonne)"])
         tr_energy = timeseries(pdict["transportation energy (J/km/tonne)"])
         tr_emissions = timeseries(pdict["transportation emissions (tonne/km/tonne)"])
-        prod = Product(; name, tr_cost, tr_energy, tr_emissions)
+        disposal_limit = timeseries(pdict["disposal limit (tonne)"], null_val=Inf)
+        prod = Product(; name, tr_cost, tr_energy, tr_emissions, disposal_limit)
         push!(products, prod)
         products_by_name[name] = prod
     end
@@ -51,7 +53,7 @@ function parse(json)::Instance
         outputs = [products_by_name[p] for p in cdict["outputs"]]
         operating_cost = timeseries(cdict["operating cost (\$)"])
         prod_dict(key, null_val) = OrderedDict(
-            p => [v === nothing ? null_val : v for v in timeseries(cdict[key][p.name])]
+            p => timeseries(cdict[key][p.name]; null_val)
             for p in outputs
         )
         fixed_output = prod_dict("fixed output (tonne)", 0.0)

src/instance/structs.jl

@@ -14,6 +14,7 @@ Base.@kwdef struct Product
     tr_cost::Vector{Float64}
     tr_energy::Vector{Float64}
     tr_emissions::OrderedDict{String,Vector{Float64}}
+    disposal_limit::Vector{Float64}
 end
 
 Base.@kwdef struct Center

src/model/build.jl

@@ -298,6 +298,18 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
             @constraint(model, z_disp[c.name, m.name, t] <= c.disposal_limit[m][t])
     end
 
+    # Global disposal limit
+    eq_disposal_limit = _init(model, :eq_disposal_limit)
+    for m in products, t in T
+        isfinite(m.disposal_limit[t]) || continue
+        eq_disposal_limit[m.name, t] = @constraint(
+            model,
+            sum(z_disp[p.name, m.name, t] for p in plants if m in keys(p.output)) +
+            sum(z_disp[c.name, m.name, t] for c in centers if m in c.outputs) <=
+            m.disposal_limit[t]
+        )
+    end
+
     if variable_names
         _set_names!(model)
     end

src/reports/centers.jl

@@ -8,6 +8,8 @@ using CSV
 function centers_report(model)::DataFrame
     df = DataFrame()
     df."center" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
     df."year" = Int[]
     df."input product" = String[]
     df."input amount (tonne)" = Float64[]
@@ -31,14 +33,16 @@ function centers_report(model)::DataFrame
         end
         push!(
             df,
-            [
-                c.name,
-                t,
-                input_name,
-                _round(input),
-                _round(revenue),
-                _round(c.operating_cost[t]),
-            ],
+            Dict(
+                "center" => c.name,
+                "latitude" => c.latitude,
+                "longitude" => c.longitude,
+                "year" => t,
+                "input product" => input_name,
+                "input amount (tonne)" => _round(input),
+                "revenue (\$)" => _round(revenue),
+                "operating cost (\$)" => _round(c.operating_cost[t]),
+            ),
         )
     end
     return df
@@ -47,10 +51,13 @@ end
 function center_outputs_report(model)::DataFrame
     df = DataFrame()
     df."center" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
     df."output product" = String[]
     df."year" = Int[]
     df."amount collected (tonne)" = Float64[]
     df."amount disposed (tonne)" = Float64[]
+    df."disposal limit (tonne)" = Float64[]
     df."collection cost (\$)" = Float64[]
     df."disposal cost (\$)" = Float64[]
 
@@ -72,15 +79,18 @@ function center_outputs_report(model)::DataFrame
         end
         push!(
             df,
-            [
-                c.name,
-                m.name,
-                t,
-                _round(collected),
-                _round(disposed),
-                _round(collection_cost),
-                _round(disposal_cost),
-            ],
+            Dict(
+                "center" => c.name,
+                "latitude" => c.latitude,
+                "longitude" => c.longitude,
+                "output product" => m.name,
+                "year" => t,
+                "amount collected (tonne)" => _round(collected),
+                "amount disposed (tonne)" => _round(disposed),
+                "disposal limit (tonne)" => _round(c.disposal_limit[m][t]),
+                "collection cost (\$)" => _round(collection_cost),
+                "disposal cost (\$)" => _round(disposal_cost),
+            ),
         )
     end
     return df

src/reports/plants.jl

@@ -8,6 +8,10 @@ using CSV
 function plants_report(model)::DataFrame
     df = DataFrame()
     df."plant" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."initial capacity" = Float64[]
+    df."current capacity" = Float64[]
     df."year" = Int[]
     df."operational?" = Bool[]
     df."input amount (tonne)" = Float64[]
@@ -21,23 +25,36 @@ function plants_report(model)::DataFrame
     for p in plants, t in T
         operational = JuMP.value(model[:x][p.name, t]) > 0.5
         input = value(model[:z_input][p.name, t])
+
+        # Opening cost
         opening_cost = 0
         if value(model[:x][p.name, t]) > 0.5 && value(model[:x][p.name, t-1]) < 0.5
             opening_cost = p.capacities[1].opening_cost[t]
         end
+
+        # Plant size
+        curr_capacity = 0
+        if operational
+            curr_capacity = p.capacities[1].size
+        end
+
         fix_operating_cost = (operational ? p.capacities[1].fix_operating_cost[t] : 0)
         var_operating_cost = input * p.capacities[1].var_operating_cost[t]
         push!(
             df,
-            [
-                p.name,
-                t,
-                operational,
-                _round(input),
-                _round(opening_cost),
-                _round(fix_operating_cost),
-                _round(var_operating_cost),
-            ],
+            Dict(
+                "plant" => p.name,
+                "latitude" => p.latitude,
+                "longitude" => p.longitude,
+                "initial capacity" => p.initial_capacity,
+                "current capacity" => curr_capacity,
+                "year" => t,
+                "operational?" => operational,
+                "input amount (tonne)" => _round(input),
+                "opening cost (\$)" => _round(opening_cost),
+                "fixed operating cost (\$)" => _round(fix_operating_cost),
+                "variable operating cost (\$)" => _round(var_operating_cost),
+            ),
         )
     end
     return df
@@ -46,10 +63,13 @@ end
 function plant_outputs_report(model)::DataFrame
     df = DataFrame()
     df."plant" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
     df."output product" = String[]
     df."year" = Int[]
     df."amount produced (tonne)" = Float64[]
     df."amount disposed (tonne)" = Float64[]
+    df."disposal limit (tonne)" = Float64[]
     df."disposal cost (\$)" = Float64[]
 
     plants = model.ext[:instance].plants
@@ -61,7 +81,17 @@ function plant_outputs_report(model)::DataFrame
         disposal_cost = p.disposal_cost[m][t] * disposed
         push!(
             df,
-            [p.name, m.name, t, _round(produced), _round(disposed), _round(disposal_cost)],
+            Dict(
+                "plant" => p.name,
+                "latitude" => p.latitude,
+                "longitude" => p.longitude,
+                "output product" => m.name,
+                "year" => t,
+                "amount produced (tonne)" => _round(produced),
+                "amount disposed (tonne)" => _round(disposed),
+                "disposal limit (tonne)" => _round(p.disposal_limit[m][t]),
+                "disposal cost (\$)" => _round(disposal_cost),
+            ),
         )
     end
     return df

src/reports/transportation.jl

@@ -36,17 +36,17 @@ function transportation_report(model)::DataFrame
         end
         push!(
             df,
-            [
-                p1.name,
-                p2.name,
-                m.name,
-                t,
-                _round(amount),
-                _round(distance),
-                _round(tr_cost),
-                _round(revenue),
-                _round(collection_cost),
-            ],
+            Dict(
+                "source" => p1.name,
+                "destination" => p2.name,
+                "product" => m.name,
+                "year" => t,
+                "amount sent (tonne)" => _round(amount),
+                "distance (km)" => _round(distance),
+                "transportation cost (\$)" => _round(tr_cost),
+                "center revenue (\$)" => _round(revenue),
+                "center collection cost (\$)" => _round(collection_cost),
+            ),
         )
     end
     return df

test/fixtures/boat_example.jl

@@ -69,6 +69,7 @@ function run_boat_example()
         "transportation cost (\$/km/tonne)" => 0.30,
         "transportation energy (J/km/tonne)" => 7_500,
         "transportation emissions (tonne/km/tonne)" => dict("CO2" => 2.68),
+        "disposal limit (tonne)" => nothing,
     )
 
     boat_factory = dict(
@@ -121,10 +122,8 @@ function run_boat_example()
         "initial capacity (tonne)" => 0,
     )
 
-    lat_lon_dict(city_location) = dict(
-        "latitude (deg)" => city_location[1],
-        "longitude (deg)" => city_location[2],
-    )
+    lat_lon_dict(city_location) =
+        dict("latitude (deg)" => city_location[1], "longitude (deg)" => city_location[2])
 
     data = dict(
         "parameters" => parameters,
@@ -132,36 +131,29 @@ function run_boat_example()
             dict("Nail" => prod, "Wood" => prod, "NewBoat" => prod, "UsedBoat" => prod),
         "centers" => merge(
             dict(
-                "NailFactory ($city_name)" => merge(
-                    nail_factory,
-                    lat_lon_dict(city_location)
-                ) for (city_name, city_location) in cities_b
+                "NailFactory ($city_name)" =>
+                    merge(nail_factory, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_b
             ),
             dict(
-                "Forest ($city_name)" => merge(
-                    forest,
-                    lat_lon_dict(city_location)
-                ) for (city_name, city_location) in cities_b
+                "Forest ($city_name)" => merge(forest, lat_lon_dict(city_location))
+                for (city_name, city_location) in cities_b
             ),
             dict(
-                "Retail ($city_name)" => merge(
-                    retail,
-                    lat_lon_dict(city_location)
-                ) for (city_name, city_location) in cities_a
+                "Retail ($city_name)" => merge(retail, lat_lon_dict(city_location))
+                for (city_name, city_location) in cities_a
             ),
         ),
         "plants" => merge(
             dict(
-                "BoatFactory ($city_name)" => merge(
-                    boat_factory,
-                    lat_lon_dict(city_location)
-                ) for (city_name, city_location) in cities_a
+                "BoatFactory ($city_name)" =>
+                    merge(boat_factory, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_a
             ),
             dict(
-                "RecyclingPlant ($city_name)" => merge(
-                    recycling_plant,
-                    lat_lon_dict(city_location)
-                ) for (city_name, city_location) in cities_a
+                "RecyclingPlant ($city_name)" =>
+                    merge(recycling_plant, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_a
             ),
         ),
     )
@@ -186,4 +178,4 @@ function run_boat_example()
     RELOG.write_transportation_report(model, fixture("boat_example/transportation.csv"))
 
     return
-end
+end

test/fixtures/boat_example.json

@@ -12,28 +12,32 @@
       "transportation energy (J/km/tonne)": 7500,
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 2.68
-      }
+      },
+      "disposal limit (tonne)": null
     },
     "Wood": {
       "transportation cost ($/km/tonne)": 0.3,
       "transportation energy (J/km/tonne)": 7500,
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 2.68
-      }
+      },
+      "disposal limit (tonne)": null
     },
     "NewBoat": {
       "transportation cost ($/km/tonne)": 0.3,
       "transportation energy (J/km/tonne)": 7500,
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 2.68
-      }
+      },
+      "disposal limit (tonne)": null
     },
     "UsedBoat": {
       "transportation cost ($/km/tonne)": 0.3,
       "transportation energy (J/km/tonne)": 7500,
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 2.68
-      }
+      },
+      "disposal limit (tonne)": null
     }
   },
   "centers": {

test/fixtures/boat_example/center_outputs.csv

@@ -1,81 +1,81 @@
-center,output product,year,amount collected (tonne),amount disposed (tonne),collection cost ($),disposal cost ($)
-NailFactory (Chicago),Nail,1,1.0,0.0,1000.0,0.0
-NailFactory (Chicago),Nail,2,1.0,0.0,1000.0,0.0
-NailFactory (Chicago),Nail,3,1.0,-0.0,1000.0,-0.0
-NailFactory (Chicago),Nail,4,1.0,0.0,1000.0,0.0
-NailFactory (Chicago),Nail,5,1.0,0.0,1000.0,0.0
-NailFactory (Phoenix),Nail,1,1.0,0.0,1000.0,0.0
-NailFactory (Phoenix),Nail,2,1.0,0.0,1000.0,0.0
-NailFactory (Phoenix),Nail,3,1.0,0.0,1000.0,0.0
-NailFactory (Phoenix),Nail,4,1.0,0.0,1000.0,0.0
-NailFactory (Phoenix),Nail,5,1.0,0.0,1000.0,0.0
-NailFactory (Dallas),Nail,1,1.0,-0.0,1000.0,-0.0
-NailFactory (Dallas),Nail,2,1.0,-0.0,1000.0,-0.0
-NailFactory (Dallas),Nail,3,1.0,-0.0,1000.0,-0.0
-NailFactory (Dallas),Nail,4,1.0,0.0,1000.0,0.0
-NailFactory (Dallas),Nail,5,1.0,0.0,1000.0,0.0
-Forest (Chicago),Wood,1,100.0,100.0,0.0,0.0
-Forest (Chicago),Wood,2,100.0,100.0,0.0,0.0
-Forest (Chicago),Wood,3,100.0,100.0,0.0,0.0
-Forest (Chicago),Wood,4,100.0,100.0,0.0,0.0
-Forest (Chicago),Wood,5,100.0,100.0,0.0,0.0
-Forest (Phoenix),Wood,1,100.0,100.0,0.0,0.0
-Forest (Phoenix),Wood,2,100.0,100.0,0.0,0.0
-Forest (Phoenix),Wood,3,100.0,100.0,0.0,0.0
-Forest (Phoenix),Wood,4,100.0,100.0,0.0,0.0
-Forest (Phoenix),Wood,5,100.0,100.0,0.0,0.0
-Forest (Dallas),Wood,1,100.0,43.0,14250.0,0.0
-Forest (Dallas),Wood,2,100.0,43.0,14250.0,0.0
-Forest (Dallas),Wood,3,100.0,43.0,14250.0,0.0
-Forest (Dallas),Wood,4,100.0,43.0,14250.0,0.0
-Forest (Dallas),Wood,5,100.0,43.0,14250.0,0.0
-Retail (Chicago),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (Chicago),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (Chicago),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (Chicago),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (Chicago),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (New York City),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (New York City),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (New York City),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (New York City),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (New York City),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (Los Angeles),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (Los Angeles),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (Los Angeles),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (Los Angeles),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (Los Angeles),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (Houston),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (Houston),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (Houston),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (Houston),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (Houston),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (Phoenix),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (Phoenix),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (Phoenix),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (Phoenix),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (Phoenix),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (Philadelphia),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (Philadelphia),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (Philadelphia),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (Philadelphia),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (Philadelphia),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (San Antonio),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (San Antonio),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (San Antonio),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (San Antonio),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (San Antonio),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (San Diego),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (San Diego),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (San Diego),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (San Diego),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (San Diego),UsedBoat,5,0.0,0.0,0.0,0.0
-Retail (Dallas),UsedBoat,1,6.31579,0.0,631.57895,0.0
-Retail (Dallas),UsedBoat,2,22.93629,0.0,2293.62881,0.0
-Retail (Dallas),UsedBoat,3,31.7714,0.0,3177.13952,0.0
-Retail (Dallas),UsedBoat,4,33.80867,0.0,3380.86724,0.0
-Retail (Dallas),UsedBoat,5,34.54174,0.0,3454.17409,0.0
-Retail (San Jose),UsedBoat,1,0.0,0.0,0.0,0.0
-Retail (San Jose),UsedBoat,2,0.0,0.0,0.0,0.0
-Retail (San Jose),UsedBoat,3,0.0,0.0,0.0,0.0
-Retail (San Jose),UsedBoat,4,0.0,0.0,0.0,0.0
-Retail (San Jose),UsedBoat,5,0.0,0.0,0.0,0.0
+center,latitude,longitude,output product,year,amount collected (tonne),amount disposed (tonne),disposal limit (tonne),collection cost ($),disposal cost ($)
+NailFactory (Chicago),41.881832,-87.623177,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,2,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,4,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,5,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,2,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,4,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,5,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,2,1.0,-0.0,Inf,1000.0,-0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,4,1.0,-0.0,Inf,1000.0,-0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,5,1.0,-0.0,Inf,1000.0,-0.0
+Forest (Chicago),41.881832,-87.623177,Wood,1,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,2,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,3,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,4,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,5,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,1,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,2,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,3,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,4,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,5,100.0,100.0,Inf,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,1,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,2,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,3,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,4,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,5,100.0,43.0,Inf,14250.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,5,-0.0,0.0,0.0,-0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,5,-0.0,0.0,0.0,-0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,4,-0.0,0.0,0.0,-0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,5,-0.0,0.0,0.0,-0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,1,6.31579,0.0,0.0,631.57895,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,2,22.93629,0.0,0.0,2293.62881,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,3,31.7714,0.0,0.0,3177.13952,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,4,33.80867,0.0,0.0,3380.86724,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,5,34.54174,0.0,0.0,3454.17409,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,5,0.0,0.0,0.0,0.0,0.0

test/fixtures/boat_example/centers.csv

@@ -1,81 +1,81 @@
-center,year,input product,input amount (tonne),revenue ($),operating cost ($)
-NailFactory (Chicago),1,,0.0,0.0,0.0
-NailFactory (Chicago),2,,0.0,0.0,0.0
-NailFactory (Chicago),3,,0.0,0.0,0.0
-NailFactory (Chicago),4,,0.0,0.0,0.0
-NailFactory (Chicago),5,,0.0,0.0,0.0
-NailFactory (Phoenix),1,,0.0,0.0,0.0
-NailFactory (Phoenix),2,,0.0,0.0,0.0
-NailFactory (Phoenix),3,,0.0,0.0,0.0
-NailFactory (Phoenix),4,,0.0,0.0,0.0
-NailFactory (Phoenix),5,,0.0,0.0,0.0
-NailFactory (Dallas),1,,0.0,0.0,0.0
-NailFactory (Dallas),2,,0.0,0.0,0.0
-NailFactory (Dallas),3,,0.0,0.0,0.0
-NailFactory (Dallas),4,,0.0,0.0,0.0
-NailFactory (Dallas),5,,0.0,0.0,0.0
-Forest (Chicago),1,,0.0,0.0,0.0
-Forest (Chicago),2,,0.0,0.0,0.0
-Forest (Chicago),3,,0.0,0.0,0.0
-Forest (Chicago),4,,0.0,0.0,0.0
-Forest (Chicago),5,,0.0,0.0,0.0
-Forest (Phoenix),1,,0.0,0.0,0.0
-Forest (Phoenix),2,,0.0,0.0,0.0
-Forest (Phoenix),3,,0.0,0.0,0.0
-Forest (Phoenix),4,,0.0,0.0,0.0
-Forest (Phoenix),5,,0.0,0.0,0.0
-Forest (Dallas),1,,0.0,0.0,0.0
-Forest (Dallas),2,,0.0,0.0,0.0
-Forest (Dallas),3,,0.0,0.0,0.0
-Forest (Dallas),4,,0.0,0.0,0.0
-Forest (Dallas),5,,0.0,0.0,0.0
-Retail (Chicago),1,NewBoat,0.0,0.0,125000.0
-Retail (Chicago),2,NewBoat,0.0,0.0,125000.0
-Retail (Chicago),3,NewBoat,0.0,0.0,125000.0
-Retail (Chicago),4,NewBoat,0.0,0.0,125000.0
-Retail (Chicago),5,NewBoat,0.0,0.0,125000.0
-Retail (New York City),1,NewBoat,0.0,0.0,125000.0
-Retail (New York City),2,NewBoat,0.0,0.0,125000.0
-Retail (New York City),3,NewBoat,0.0,0.0,125000.0
-Retail (New York City),4,NewBoat,0.0,0.0,125000.0
-Retail (New York City),5,NewBoat,0.0,0.0,125000.0
-Retail (Los Angeles),1,NewBoat,0.0,0.0,125000.0
-Retail (Los Angeles),2,NewBoat,0.0,0.0,125000.0
-Retail (Los Angeles),3,NewBoat,0.0,0.0,125000.0
-Retail (Los Angeles),4,NewBoat,0.0,0.0,125000.0
-Retail (Los Angeles),5,NewBoat,0.0,0.0,125000.0
-Retail (Houston),1,NewBoat,0.0,0.0,125000.0
-Retail (Houston),2,NewBoat,0.0,0.0,125000.0
-Retail (Houston),3,NewBoat,0.0,0.0,125000.0
-Retail (Houston),4,NewBoat,0.0,0.0,125000.0
-Retail (Houston),5,NewBoat,0.0,0.0,125000.0
-Retail (Phoenix),1,NewBoat,0.0,0.0,125000.0
-Retail (Phoenix),2,NewBoat,0.0,0.0,125000.0
-Retail (Phoenix),3,NewBoat,0.0,0.0,125000.0
-Retail (Phoenix),4,NewBoat,0.0,0.0,125000.0
-Retail (Phoenix),5,NewBoat,0.0,0.0,125000.0
-Retail (Philadelphia),1,NewBoat,0.0,0.0,125000.0
-Retail (Philadelphia),2,NewBoat,0.0,0.0,125000.0
-Retail (Philadelphia),3,NewBoat,0.0,0.0,125000.0
-Retail (Philadelphia),4,NewBoat,0.0,0.0,125000.0
-Retail (Philadelphia),5,NewBoat,0.0,0.0,125000.0
-Retail (San Antonio),1,NewBoat,0.0,0.0,125000.0
-Retail (San Antonio),2,NewBoat,0.0,0.0,125000.0
-Retail (San Antonio),3,NewBoat,0.0,0.0,125000.0
-Retail (San Antonio),4,NewBoat,0.0,0.0,125000.0
-Retail (San Antonio),5,NewBoat,0.0,0.0,125000.0
-Retail (San Diego),1,NewBoat,0.0,0.0,125000.0
-Retail (San Diego),2,NewBoat,0.0,0.0,125000.0
-Retail (San Diego),3,NewBoat,0.0,0.0,125000.0
-Retail (San Diego),4,NewBoat,0.0,0.0,125000.0
-Retail (San Diego),5,NewBoat,0.0,0.0,125000.0
-Retail (Dallas),1,NewBoat,63.15789,757894.73684,125000.0
-Retail (Dallas),2,NewBoat,71.46814,857617.72853,125000.0
-Retail (Dallas),3,NewBoat,75.8857,910628.37148,125000.0
-Retail (Dallas),4,NewBoat,76.90434,922852.03459,125000.0
-Retail (Dallas),5,NewBoat,77.27087,927250.44516,125000.0
-Retail (San Jose),1,NewBoat,0.0,0.0,125000.0
-Retail (San Jose),2,NewBoat,0.0,0.0,125000.0
-Retail (San Jose),3,NewBoat,0.0,0.0,125000.0
-Retail (San Jose),4,NewBoat,0.0,0.0,125000.0
-Retail (San Jose),5,NewBoat,0.0,0.0,125000.0
+center,latitude,longitude,year,input product,input amount (tonne),revenue ($),operating cost ($)
+NailFactory (Chicago),41.881832,-87.623177,1,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,2,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,3,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,4,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,5,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,1,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,2,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,3,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,4,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,5,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,1,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,2,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,3,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,4,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,5,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,1,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,2,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,3,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,4,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,5,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,1,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,2,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,3,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,4,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,5,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,1,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,2,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,3,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,4,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,5,,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,1,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,2,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,3,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,4,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,5,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,1,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,2,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,3,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,4,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,5,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,1,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,2,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,3,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,4,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,5,NewBoat,-0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,1,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,2,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,3,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,4,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,5,NewBoat,-0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,1,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,2,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,3,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,4,NewBoat,-0.0,-0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,5,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,1,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,2,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,3,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,4,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,5,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,1,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,2,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,3,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,4,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,5,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,1,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,2,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,3,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,4,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,5,NewBoat,0.0,0.0,125000.0
+Retail (Dallas),32.776664,-96.796988,1,NewBoat,63.15789,757894.73684,125000.0
+Retail (Dallas),32.776664,-96.796988,2,NewBoat,71.46814,857617.72853,125000.0
+Retail (Dallas),32.776664,-96.796988,3,NewBoat,75.8857,910628.37148,125000.0
+Retail (Dallas),32.776664,-96.796988,4,NewBoat,76.90434,922852.03459,125000.0
+Retail (Dallas),32.776664,-96.796988,5,NewBoat,77.27087,927250.44516,125000.0
+Retail (San Jose),37.338208,-121.886329,1,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,2,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,3,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,4,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,5,NewBoat,0.0,0.0,125000.0

test/fixtures/boat_example/plant_outputs.csv

@@ -1,151 +1,151 @@
-plant,output product,year,amount produced (tonne),amount disposed (tonne),disposal cost ($)
-BoatFactory (Chicago),NewBoat,1,0.0,0.0,0.0
-BoatFactory (Chicago),NewBoat,2,0.0,0.0,0.0
-BoatFactory (Chicago),NewBoat,3,0.0,0.0,0.0
-BoatFactory (Chicago),NewBoat,4,0.0,0.0,0.0
-BoatFactory (Chicago),NewBoat,5,0.0,0.0,0.0
-BoatFactory (New York City),NewBoat,1,0.0,0.0,0.0
-BoatFactory (New York City),NewBoat,2,0.0,0.0,0.0
-BoatFactory (New York City),NewBoat,3,0.0,0.0,0.0
-BoatFactory (New York City),NewBoat,4,0.0,0.0,0.0
-BoatFactory (New York City),NewBoat,5,0.0,0.0,0.0
-BoatFactory (Los Angeles),NewBoat,1,0.0,0.0,0.0
-BoatFactory (Los Angeles),NewBoat,2,0.0,0.0,0.0
-BoatFactory (Los Angeles),NewBoat,3,0.0,0.0,0.0
-BoatFactory (Los Angeles),NewBoat,4,0.0,0.0,0.0
-BoatFactory (Los Angeles),NewBoat,5,0.0,0.0,0.0
-BoatFactory (Houston),NewBoat,1,0.0,0.0,0.0
-BoatFactory (Houston),NewBoat,2,0.0,0.0,0.0
-BoatFactory (Houston),NewBoat,3,0.0,0.0,0.0
-BoatFactory (Houston),NewBoat,4,0.0,0.0,0.0
-BoatFactory (Houston),NewBoat,5,0.0,0.0,0.0
-BoatFactory (Phoenix),NewBoat,1,0.0,0.0,0.0
-BoatFactory (Phoenix),NewBoat,2,0.0,0.0,0.0
-BoatFactory (Phoenix),NewBoat,3,0.0,0.0,0.0
-BoatFactory (Phoenix),NewBoat,4,0.0,0.0,0.0
-BoatFactory (Phoenix),NewBoat,5,0.0,0.0,0.0
-BoatFactory (Philadelphia),NewBoat,1,0.0,0.0,0.0
-BoatFactory (Philadelphia),NewBoat,2,0.0,0.0,0.0
-BoatFactory (Philadelphia),NewBoat,3,0.0,0.0,0.0
-BoatFactory (Philadelphia),NewBoat,4,0.0,0.0,0.0
-BoatFactory (Philadelphia),NewBoat,5,0.0,0.0,0.0
-BoatFactory (San Antonio),NewBoat,1,0.0,0.0,0.0
-BoatFactory (San Antonio),NewBoat,2,0.0,0.0,0.0
-BoatFactory (San Antonio),NewBoat,3,0.0,0.0,0.0
-BoatFactory (San Antonio),NewBoat,4,0.0,0.0,0.0
-BoatFactory (San Antonio),NewBoat,5,0.0,0.0,0.0
-BoatFactory (San Diego),NewBoat,1,0.0,0.0,0.0
-BoatFactory (San Diego),NewBoat,2,0.0,0.0,0.0
-BoatFactory (San Diego),NewBoat,3,0.0,0.0,0.0
-BoatFactory (San Diego),NewBoat,4,0.0,0.0,0.0
-BoatFactory (San Diego),NewBoat,5,0.0,0.0,0.0
-BoatFactory (Dallas),NewBoat,1,63.15789,0.0,0.0
-BoatFactory (Dallas),NewBoat,2,71.46814,0.0,0.0
-BoatFactory (Dallas),NewBoat,3,75.8857,0.0,0.0
-BoatFactory (Dallas),NewBoat,4,76.90434,0.0,0.0
-BoatFactory (Dallas),NewBoat,5,77.27087,0.0,0.0
-BoatFactory (San Jose),NewBoat,1,0.0,0.0,0.0
-BoatFactory (San Jose),NewBoat,2,0.0,0.0,0.0
-BoatFactory (San Jose),NewBoat,3,0.0,0.0,0.0
-BoatFactory (San Jose),NewBoat,4,0.0,0.0,0.0
-BoatFactory (San Jose),NewBoat,5,0.0,0.0,0.0
-RecyclingPlant (Chicago),Nail,1,0.0,0.0,0.0
-RecyclingPlant (Chicago),Nail,2,0.0,0.0,0.0
-RecyclingPlant (Chicago),Nail,3,0.0,0.0,0.0
-RecyclingPlant (Chicago),Nail,4,0.0,0.0,0.0
-RecyclingPlant (Chicago),Nail,5,0.0,0.0,0.0
-RecyclingPlant (Chicago),Wood,1,0.0,0.0,0.0
-RecyclingPlant (Chicago),Wood,2,0.0,0.0,0.0
-RecyclingPlant (Chicago),Wood,3,0.0,0.0,0.0
-RecyclingPlant (Chicago),Wood,4,0.0,0.0,0.0
-RecyclingPlant (Chicago),Wood,5,0.0,0.0,0.0
-RecyclingPlant (New York City),Nail,1,0.0,0.0,0.0
-RecyclingPlant (New York City),Nail,2,0.0,0.0,0.0
-RecyclingPlant (New York City),Nail,3,0.0,0.0,0.0
-RecyclingPlant (New York City),Nail,4,0.0,0.0,0.0
-RecyclingPlant (New York City),Nail,5,0.0,0.0,0.0
-RecyclingPlant (New York City),Wood,1,0.0,0.0,0.0
-RecyclingPlant (New York City),Wood,2,0.0,0.0,0.0
-RecyclingPlant (New York City),Wood,3,0.0,0.0,0.0
-RecyclingPlant (New York City),Wood,4,0.0,0.0,0.0
-RecyclingPlant (New York City),Wood,5,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Nail,1,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Nail,2,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Nail,3,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Nail,4,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Nail,5,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Wood,1,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Wood,2,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Wood,3,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Wood,4,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),Wood,5,0.0,0.0,0.0
-RecyclingPlant (Houston),Nail,1,0.0,0.0,0.0
-RecyclingPlant (Houston),Nail,2,0.0,0.0,0.0
-RecyclingPlant (Houston),Nail,3,0.0,0.0,0.0
-RecyclingPlant (Houston),Nail,4,0.0,0.0,0.0
-RecyclingPlant (Houston),Nail,5,0.0,0.0,0.0
-RecyclingPlant (Houston),Wood,1,0.0,0.0,0.0
-RecyclingPlant (Houston),Wood,2,0.0,0.0,0.0
-RecyclingPlant (Houston),Wood,3,0.0,0.0,0.0
-RecyclingPlant (Houston),Wood,4,0.0,0.0,0.0
-RecyclingPlant (Houston),Wood,5,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Nail,1,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Nail,2,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Nail,3,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Nail,4,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Nail,5,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Wood,1,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Wood,2,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Wood,3,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Wood,4,0.0,0.0,0.0
-RecyclingPlant (Phoenix),Wood,5,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Nail,1,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Nail,2,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Nail,3,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Nail,4,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Nail,5,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Wood,1,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Wood,2,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Wood,3,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Wood,4,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),Wood,5,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Nail,1,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Nail,2,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Nail,3,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Nail,4,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Nail,5,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Wood,1,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Wood,2,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Wood,3,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Wood,4,0.0,0.0,0.0
-RecyclingPlant (San Antonio),Wood,5,0.0,0.0,0.0
-RecyclingPlant (San Diego),Nail,1,0.0,0.0,0.0
-RecyclingPlant (San Diego),Nail,2,0.0,0.0,0.0
-RecyclingPlant (San Diego),Nail,3,0.0,0.0,0.0
-RecyclingPlant (San Diego),Nail,4,0.0,0.0,0.0
-RecyclingPlant (San Diego),Nail,5,0.0,0.0,0.0
-RecyclingPlant (San Diego),Wood,1,0.0,0.0,0.0
-RecyclingPlant (San Diego),Wood,2,0.0,0.0,0.0
-RecyclingPlant (San Diego),Wood,3,0.0,0.0,0.0
-RecyclingPlant (San Diego),Wood,4,0.0,0.0,0.0
-RecyclingPlant (San Diego),Wood,5,0.0,0.0,0.0
-RecyclingPlant (Dallas),Nail,1,0.15789,0.0,0.0
-RecyclingPlant (Dallas),Nail,2,0.57341,0.0,0.0
-RecyclingPlant (Dallas),Nail,3,0.79428,0.0,0.0
-RecyclingPlant (Dallas),Nail,4,0.84522,0.0,0.0
-RecyclingPlant (Dallas),Nail,5,0.86354,0.0,0.0
-RecyclingPlant (Dallas),Wood,1,3.0,0.0,0.0
-RecyclingPlant (Dallas),Wood,2,10.89474,0.0,0.0
-RecyclingPlant (Dallas),Wood,3,15.09141,0.0,0.0
-RecyclingPlant (Dallas),Wood,4,16.05912,0.0,0.0
-RecyclingPlant (Dallas),Wood,5,16.40733,0.0,0.0
-RecyclingPlant (San Jose),Nail,1,0.0,0.0,0.0
-RecyclingPlant (San Jose),Nail,2,0.0,0.0,0.0
-RecyclingPlant (San Jose),Nail,3,0.0,0.0,0.0
-RecyclingPlant (San Jose),Nail,4,0.0,0.0,0.0
-RecyclingPlant (San Jose),Nail,5,0.0,0.0,0.0
-RecyclingPlant (San Jose),Wood,1,0.0,0.0,0.0
-RecyclingPlant (San Jose),Wood,2,0.0,0.0,0.0
-RecyclingPlant (San Jose),Wood,3,0.0,0.0,0.0
-RecyclingPlant (San Jose),Wood,4,0.0,0.0,0.0
-RecyclingPlant (San Jose),Wood,5,0.0,0.0,0.0
+plant,latitude,longitude,output product,year,amount produced (tonne),amount disposed (tonne),disposal limit (tonne),disposal cost ($)
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,1,63.15789,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,2,71.46814,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,3,75.8857,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,4,76.90434,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,5,77.27087,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,2,-0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,2,-0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,1,0.15789,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,2,0.57341,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,3,0.79428,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,4,0.84522,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,5,0.86354,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,1,3.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,2,10.89474,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,3,15.09141,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,4,16.05912,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,5,16.40733,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,5,0.0,0.0,0.0,0.0

test/fixtures/boat_example/plants.csv

@@ -1,101 +1,101 @@
-plant,year,operational?,input amount (tonne),opening cost ($),fixed operating cost ($),variable operating cost ($)
-BoatFactory (Chicago),1,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Chicago),2,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Chicago),3,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Chicago),4,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Chicago),5,false,-0.0,0.0,0.0,-0.0
-BoatFactory (New York City),1,false,0.0,0.0,0.0,0.0
-BoatFactory (New York City),2,false,0.0,0.0,0.0,0.0
-BoatFactory (New York City),3,false,0.0,0.0,0.0,0.0
-BoatFactory (New York City),4,false,0.0,0.0,0.0,0.0
-BoatFactory (New York City),5,false,0.0,0.0,0.0,0.0
-BoatFactory (Los Angeles),1,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Los Angeles),2,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Los Angeles),3,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Los Angeles),4,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Los Angeles),5,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Houston),1,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Houston),2,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Houston),3,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Houston),4,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Houston),5,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Phoenix),1,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Phoenix),2,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Phoenix),3,false,0.0,0.0,0.0,0.0
-BoatFactory (Phoenix),4,false,-0.0,0.0,0.0,-0.0
-BoatFactory (Phoenix),5,false,0.0,0.0,0.0,0.0
-BoatFactory (Philadelphia),1,false,0.0,0.0,0.0,0.0
-BoatFactory (Philadelphia),2,false,0.0,0.0,0.0,0.0
-BoatFactory (Philadelphia),3,false,0.0,0.0,0.0,0.0
-BoatFactory (Philadelphia),4,false,0.0,0.0,0.0,0.0
-BoatFactory (Philadelphia),5,false,0.0,0.0,0.0,0.0
-BoatFactory (San Antonio),1,false,-0.0,0.0,0.0,-0.0
-BoatFactory (San Antonio),2,false,-0.0,0.0,0.0,-0.0
-BoatFactory (San Antonio),3,false,-0.0,0.0,0.0,-0.0
-BoatFactory (San Antonio),4,false,-0.0,0.0,0.0,-0.0
-BoatFactory (San Antonio),5,false,-0.0,0.0,0.0,-0.0
-BoatFactory (San Diego),1,false,0.0,0.0,0.0,0.0
-BoatFactory (San Diego),2,false,0.0,0.0,0.0,0.0
-BoatFactory (San Diego),3,false,0.0,0.0,0.0,0.0
-BoatFactory (San Diego),4,false,0.0,0.0,0.0,0.0
-BoatFactory (San Diego),5,false,0.0,0.0,0.0,0.0
-BoatFactory (Dallas),1,true,63.15789,100000.0,250000.0,315.78947
-BoatFactory (Dallas),2,true,71.46814,0.0,250000.0,357.34072
-BoatFactory (Dallas),3,true,75.8857,0.0,250000.0,379.42849
-BoatFactory (Dallas),4,true,76.90434,0.0,250000.0,384.52168
-BoatFactory (Dallas),5,true,77.27087,0.0,250000.0,386.35435
-BoatFactory (San Jose),1,false,0.0,0.0,0.0,0.0
-BoatFactory (San Jose),2,false,0.0,0.0,0.0,0.0
-BoatFactory (San Jose),3,false,0.0,0.0,0.0,0.0
-BoatFactory (San Jose),4,false,0.0,0.0,0.0,0.0
-BoatFactory (San Jose),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Chicago),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Chicago),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Chicago),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Chicago),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Chicago),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (New York City),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (New York City),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (New York City),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (New York City),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (New York City),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Los Angeles),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Houston),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Houston),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Houston),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Houston),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Houston),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Phoenix),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Phoenix),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Phoenix),3,false,-0.0,0.0,0.0,-0.0
-RecyclingPlant (Phoenix),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Phoenix),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Philadelphia),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Antonio),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Antonio),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Antonio),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Antonio),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Antonio),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Diego),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Diego),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Diego),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Diego),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Diego),5,false,0.0,0.0,0.0,0.0
-RecyclingPlant (Dallas),1,true,6.31579,500000.0,125000.0,15.78947
-RecyclingPlant (Dallas),2,true,22.93629,0.0,125000.0,57.34072
-RecyclingPlant (Dallas),3,true,31.7714,0.0,125000.0,79.42849
-RecyclingPlant (Dallas),4,true,33.80867,0.0,125000.0,84.52168
-RecyclingPlant (Dallas),5,true,34.54174,0.0,125000.0,86.35435
-RecyclingPlant (San Jose),1,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Jose),2,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Jose),3,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Jose),4,false,0.0,0.0,0.0,0.0
-RecyclingPlant (San Jose),5,false,0.0,0.0,0.0,0.0
+plant,latitude,longitude,initial capacity,current capacity,year,operational?,input amount (tonne),opening cost ($),fixed operating cost ($),variable operating cost ($)
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,1,true,63.15789,100000.0,250000.0,315.78947
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,2,true,71.46814,0.0,250000.0,357.34072
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,3,true,75.8857,0.0,250000.0,379.42849
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,4,true,76.90434,0.0,250000.0,384.52168
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,5,true,77.27087,0.0,250000.0,386.35435
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,2,false,-0.0,0.0,0.0,-0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,5,false,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,1,true,6.31579,500000.0,125000.0,15.78947
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,2,true,22.93629,0.0,125000.0,57.34072
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,3,true,31.7714,0.0,125000.0,79.42849
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,4,true,33.80867,0.0,125000.0,84.52168
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,5,true,34.54174,0.0,125000.0,86.35435
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,1,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,2,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,3,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,4,false,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,5,false,0.0,0.0,0.0,0.0

test/fixtures/simple.json

@@ -11,7 +11,8 @@
       "transportation emissions (tonne/km/tonne)": {
         "CO2": 0.052,
         "CH4": [0.003, 0.003, 0.003, 0.003]
-      }
+      },
+      "disposal limit (tonne)": 1.0
     },
     "P2": {
       "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
@@ -19,7 +20,8 @@
       "transportation emissions (tonne/km/tonne)": {
         "CO2": [0.052, 0.052, 0.052, 0.052],
         "CH4": [0.003, 0.003, 0.003, 0.003]
-      }
+      },
+      "disposal limit (tonne)": 2.0
     },
     "P3": {
       "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
@@ -27,7 +29,8 @@
       "transportation emissions (tonne/km/tonne)": {
         "CO2": [0.052, 0.052, 0.052, 0.052],
         "CH4": [0.003, 0.003, 0.003, 0.003]
-      }
+      },
+      "disposal limit (tonne)": 5.0
     },
     "P4": {
       "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
@@ -35,7 +38,8 @@
       "transportation emissions (tonne/km/tonne)": {
         "CO2": [0.052, 0.052, 0.052, 0.052],
         "CH4": [0.003, 0.003, 0.003, 0.003]
-      }
+      },
+      "disposal limit (tonne)": null
     }
   },
   "centers": {

test/src/RELOGT.jl

@@ -24,6 +24,7 @@ function runtests()
         model_dist_test()
         report_tests()
     end
+    return
 end
 
 function format()

test/src/instance/parse_test.jl

@@ -18,6 +18,7 @@ function instance_parse_test_1()
     @test p1.tr_energy == [0.12, 0.12, 0.12, 0.12]
     @test p1.tr_emissions ==
           Dict("CO2" => [0.052, 0.052, 0.052, 0.052], "CH4" => [0.003, 0.003, 0.003, 0.003])
+    @test p1.disposal_limit == [1.0, 1.0, 1.0, 1.0]
     @test instance.products_by_name["P1"] === p1
     p2 = instance.products[2]
     p3 = instance.products[3]

test/src/model/build_test.jl

@@ -109,4 +109,13 @@ function model_build_test()
     @test repr(model[:eq_disposal_limit]["C1", "P2", 1]) ==
           "eq_disposal_limit[C1,P2,1] : z_disp[C1,P2,1] ≤ 0"
     @test ("C1", "P3", 1) ∉ keys(model[:eq_disposal_limit])
+
+    # Global disposal limit
+    @test repr(model[:eq_disposal_limit]["P1", 1]) ==
+          "eq_disposal_limit[P1,1] : z_disp[C2,P1,1] ≤ 1"
+    @test repr(model[:eq_disposal_limit]["P2", 1]) ==
+          "eq_disposal_limit[P2,1] : z_disp[C1,P2,1] ≤ 2"
+    @test repr(model[:eq_disposal_limit]["P3", 1]) ==
+          "eq_disposal_limit[P3,1] : z_disp[L1,P3,1] + z_disp[C1,P3,1] ≤ 5"
+    @test ("P4", 1) ∉ keys(model[:eq_disposal_limit])
 end

test/src/model/dist_test.jl

@@ -6,8 +6,20 @@ using RELOG
 
 function model_dist_test()
     # Euclidean distance between Chicago and Indianapolis
-    @test RELOG._calculate_distance(41.866, -87.656, 39.764, -86.148, RELOG.EuclideanDistance()) == 265.818
+    @test RELOG._calculate_distance(
+        41.866,
+        -87.656,
+        39.764,
+        -86.148,
+        RELOG.EuclideanDistance(),
+    ) == 265.818
 
     # Driving distance between Chicago and Indianapolis
-    @test RELOG._calculate_distance(41.866, -87.656, 39.764, -86.148, RELOG.KnnDrivingDistance()) == 316.43
+    @test RELOG._calculate_distance(
+        41.866,
+        -87.656,
+        39.764,
+        -86.148,
+        RELOG.KnnDrivingDistance(),
+    ) == 316.43
 end