1_spatial.yml

target_default: 1_spatial

packages:
  - dplyr
  - meddle
  - rgdal
  - sf
  - zip
  
sources:
  - src/spatial_functions.R
  - src/fetch_filter_functions.R
  - src/file_functions.R

targets:
  1_spatial:
    depends:
      - river_metadata
      - reservoir_metadata
      - out_data/study_stream_reaches.zip
      - out_data/study_reservoirs.zip

  # this first section should be the river network - one reach for 
  # each reach we are forecasting. This might be the whole DRB NHM network or a subset. 
  modeled_network_sf:
    command: retrieve_network(network_sf_fl = 'in_data/network.rds')
  
  modeled_network_sf_filtered:
    command: filter_network_segments(network_sf = modeled_network_sf, filter_list_rds = 'in_data/forecast_segs.rds')

  river_metadata:
    command: extract_feature(modeled_network_sf_filtered)
  
  out_data/study_stream_reaches.zip:
    command: sf_to_zip(target_name,
      sf_object = modeled_network_sf_filtered,
      layer_name = I('study_stream_reaches'))
      
  # This section should include shapefiles of the 
  # Reservoirs that we modeled (Cannonsville and Pepacton)
    # Define scope of reservoir modeling data in this repo
  reservoir_modeling_site_ids:
    command: c(I(c(
      Pepacton = 'nhdhr_151957878',
      Cannonsville = 'nhdhr_120022743')))
       
  # Reservoir polygons
  reservoir_polygons:
    command: fetch_filter_res_polygons(
      out_rds = target_name,
      in_dat = "in_data/canonical_lakes_sf.rds",
      in_repo = NULL,
      site_ids = reservoir_modeling_site_ids)
  
  # output reservoir shp
  out_data/study_reservoirs.zip:
    command: sf_to_zip2(zip_filename = target_name,
      sf_object = reservoir_polygons,
      layer_name = I('study_reservoirs'))

  reservoir_metadata:
    command: extract_feature(reservoir_polygons)