Add functions for plotting a grid onto a map

src/PlotPG.jl

@@ -7,6 +7,27 @@ Function for recursively merging two dictionaries (used for updating the diction
 _recursive_merge(x::AbstractDict,y::AbstractDict) = merge(_recursive_merge,x,y)
 _recursive_merge(x,y) = y
 
+#=
+Returns the minimal and maximal values of bus longitude and latitude coordinates contained a dictionary. An offset can be used to arbitrarily increase the area.
+=#
+function _get_pg_area(pos::Dict{Int64,Tuple{Float64,Float64}}, offset=0.)
+    locs = collect(values(pos))
+    lon_min = minimum(p -> p[1], locs) - offset
+    lon_max = maximum(p -> p[1], locs) + offset
+    lat_min = minimum(p -> p[2], locs) - offset
+    lat_max = maximum(p -> p[2], locs) + offset
+    return lon_min, lon_max, lat_min, lat_max
+end
+
+function _get_pg_area(network_data::Dict{String,<:Any}, offset=0.)
+    pos = Dict(
+        b["index"] => (b["bus_lon"], b["bus_lat"]) 
+        for b in collect(values(network_data["bus"]))
+    ) # geographic bus locations
+
+    return _get_pg_area(pos, offset)
+end
+
 #=
 Returns a dictionary of default plot settings for various plotting functions.
 =#
@@ -76,6 +97,59 @@ end
 
 #*------------------------------------------------------------------------------
 
+function plot_pg_map(
+        network_data::Dict{String,<:Any},
+        settings = Dict{String,Any}(); # dictionary containing plot settings
+        figpath::String # where to save the figure
+    )
+
+    ### Python imports
+    cartopy = pyimport("cartopy")
+    cticker = pyimport("cartopy.mpl.ticker")
+    
+    ### Setup figure and plot geographic map
+    fig::Figure = plt.figure()
+    w::Float64, h::Float64 = plt.figaspect(2/3)::Vector{Float64}
+    fig.set_size_inches(1.5w, 1.5h)
+    ax = fig.add_subplot(projection=cartopy.crs.PlateCarree())
+    ax.set_aspect("equal")
+
+    ### Set area to plot
+    xmin, xmax, ymin, ymax = _get_pg_area(network_data, 0.4)
+    ax.set_extent([xmin, xmax, ymin, ymax])
+
+    ### Get state borders
+    states_provinces = cartopy.feature.NaturalEarthFeature(
+        category="cultural",
+        name="admin_1_states_provinces_lines",
+        scale="50m",
+        facecolor="none"
+    )
+    ### Add wanted features to plot
+    ax.add_feature(cartopy.feature.LAND)
+    ax.add_feature(cartopy.feature.OCEAN)
+    ax.add_feature(cartopy.feature.COASTLINE)
+    ax.add_feature(cartopy.feature.BORDERS)
+    ax.add_feature(states_provinces, edgecolor="gray")
+
+    ### Show longitude and latitude values
+    gl = ax.gridlines(crs=cartopy.crs.PlateCarree(), draw_labels=true)
+    gl.xlabels_top = false
+    gl.ylabels_right = false
+    gl.xlines = false
+    gl.ylines = false
+    gl.xformatter = cartopy.mpl.gridliner.LONGITUDE_FORMATTER
+    gl.yformatter = cartopy.mpl.gridliner.LATITUDE_FORMATTER
+
+    ### Set plot settings and plot power grid
+    settings = _recursive_merge(_default_settings(:plot_pg), settings)
+    _plot_pg!(ax, network_data, settings, figpath)
+
+    return nothing
+end
+
+#*------------------------------------------------------------------------------
+
 #=
 Plots the power grid described by the network data dictionary (NDD). Possible plot settings are shown in _default_settings.
 =#
@@ -84,13 +158,14 @@ function plot_pg(
         settings = Dict{String,Any}(); # dictionary containing plot settings
         figpath::String # where to save the figure
     )
+
     ### Setup figure
     figure::Figure, ax::PyObject = plt.subplots()::Tuple{Figure,PyObject}
-    ax.set_aspect("equal")
     w::Float64, h::Float64 = plt.figaspect(2/3)::Vector{Float64}
     figure.set_size_inches(1.5w, 1.5h)
+    ax.set_aspect("equal")
 
-    ### Set plot settings
+    ### Set plot settings and plot power grid
     settings = _recursive_merge(_default_settings(:plot_pg), settings)
     _plot_pg!(ax, network_data, settings, figpath)
     
@@ -174,13 +249,16 @@ function _draw_buses!(
         settings::Dict{String,<:Any} # dictionary containing plot settings 
     )
 
-    ### Matplotlib imports
+    ### Python imports
     nx = pyimport("networkx")
     mlines = pyimport("matplotlib.lines")
     
     bustypes = get_bustypes(network_data) # types of all buses
-    pos = get_locs(network_data) # geographic bus locations
-    bus_markes = [
+    pos = Dict(
+        b["index"] => (b["bus_lon"], b["bus_lat"]) 
+        for b in collect(values(network_data["bus"]))
+    ) # geographic bus locations
+    bus_markers = [
         mlines.Line2D([], [], color=b["color"], marker=b["marker"], ls="None")
         for b in collect(values(settings["Buses"]))
         if b["label"] != "nolabel"
@@ -253,10 +331,13 @@ function _draw_br_equal!(
         br_settings::Dict{String,<:Any} # dictionary containing plot settings 
     )
     
-    ### Matplotlib imports
+    ### Python imports
     nx = pyimport("networkx")
     
-    pos = get_locs(network_data) # geographic bus locations
+    pos = Dict(
+        b["index"] => (b["bus_lon"], b["bus_lat"]) 
+        for b in collect(values(network_data["bus"]))
+    ) # geographic bus locations
     branches = collect(values(network_data["branch"])) # branch dictionaries
     
     ### Get edges contained in the NDD
@@ -290,10 +371,13 @@ function _draw_br_branchloads!(
         br_settings::Dict{String,<:Any} # dictionary containing plot settings
     )
 
-    ### Matplotlib imports
+    ### Python imports
     nx = pyimport("networkx")
 
-    pos = get_locs(network_data) # geographic bus locations
+    pos = Dict(
+        b["index"] => (b["bus_lon"], b["bus_lat"]) 
+        for b in collect(values(network_data["bus"]))
+    ) # geographic bus locations
     branches = collect(values(network_data["branch"])) # branch dictionaries
     br_coloring = br_settings["br_coloring"] # what kind of loading to use
     br_status = br_settings["br_status"]
@@ -342,11 +426,14 @@ function _draw_br_voltage!(
         br_settings::Dict{String,<:Any} # dictionary containing plot settings
     )
     
-    ### Matplotlib imports
+    ### Python imports
     nx = pyimport("networkx")
     mlines = pyimport("matplotlib.lines")
 
-    pos = get_locs(network_data) # geographic bus locations
+    pos = Dict(
+        b["index"] => (b["bus_lon"], b["bus_lat"]) 
+        for b in collect(values(network_data["bus"]))
+    ) # geographic bus locations
     branches = collect(values(network_data["branch"])) # branch dictionaries
     br_markers = Array{PyObject,1}() # markers for legend
     br_labels = Array{String,1}() # labels for legend