minor changes from pair program session

src/Routing.jl

@@ -23,45 +23,50 @@ end
 # Specific hillslope-channel models loaded here:
 include("MizurouteV1.jl")
 
-# only for one routing lv
+# For each routing level, do this
+# Questions: how to make this for a single step, and how to broadcast over basins 
 function update_state_from_hillslope!(
     river_state::RS,
     hillslope_model::HM,
-    env::E,
-) where {RS <: RiverState, HM <: AbstractHillslopeModel, E <: Environment}
+    static_env::SE,
+    dyn_env::DE
+) where {RS <: RiverState, HM <: AbstractHillslopeModel, SE <: StaticEnvironment, DE <: DynamicEnvironmen}
     # Constants
     day_to_s = 86400
     km²_to_m² = 1000000
 
-    routing_lv_basins = env.static_env.routing_lv_basins
-    start_date = env.dyn_env.start_date
-    end_date = env.dyn_env.end_date
-    dates = collect(start_date:Day(1):end_date)
-    attributes_df = env.static_env.attributes_df #may need to load into static_env during compute state
-    timeseries_dir = env.dyn_env.timeseries_dir
+    routing_lv_basins = static_env.routing_lv_basins
+    start_date = dyn_env.start_date
+    end_date = dyn_env.end_date
+    dates = collect(start_date:Day(1):end_date) # allocates, may not be used?
+    attributes_df = static_env.attributes_df #may need to load into static_env during compute state
+    timeseries_dir = dyn_env.timeseries_dir
 
     a, θ = hillslope_model.shape, hillslope_model.timeseries
-    max_time = 60  #60 used in mauricio's
-    distribution = [a * exp(-t / θ) for t in 0:(max_time - 1)]
+    max_time = 60  #60 used in mauricio's # -> how much history to use in the convolutional integral
+    distribution = [a * exp(-t / θ) for t in 0:(max_time - 1)] # allocates
 
     for basin_id in routing_lv_basins
         timeseries_df =
-            CSV.read(joinpath(timeseries_dir, "basin_$basin_id.csv"), DataFrame)
+            CSV.read(joinpath(timeseries_dir, "basin_$basin_id.csv"), DataFrame) # allocates
         filtered_df =
             filter(row -> start_date <= row[:date] <= end_date, timeseries_df)
         basin_area =
             attributes_df[attributes_df.HYBAS_ID .== basin_id, :area][1]
         runoff =
             (filtered_df[:, :sro_sum] .+ filtered_df[:, :ssro_sum]) .*
-            basin_area ./ day_to_s .* km²_to_m²
-
-        streamflow = DSP.conv(runoff, distribution)
+            basin_area ./ day_to_s .* km²_to_m² # allocates
 
-        river_state.hillslope[:, basin_id] = streamflow #update river_state_inplace
+        river_state.hillslope[:, basin_id] .= DSP.conv(runoff, distribution) #update river_state_inplace
     end
 
 end
 
+update_state_from_hillslope!(
+    river_state::RS,
+    hillslope_model::HM,
+    env::E,
+) where {RS <: RiverState, HM <: AbstractHillslopeModel, E <: Environment} = update_state_from_hillslope!(river_state, hillslope_model, env.static_env, env.dyn_env)
 
 
 function update_state_from_channel!() end