Standardize interfaces

Author: ConnectedSystems

Project.toml

@@ -32,7 +32,6 @@ Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
-StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 Tar = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 YAML = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
@@ -41,14 +40,14 @@ ZipFile = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"
 [weakdeps]
 GraphMakie = "1ecd5474-83a3-4783-bb4f-06765db800d2"
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
 
 [extensions]
 GraphMakieExt = ["Makie", "GraphMakie"]
 MakieExt = "Makie"
-GraphPlotExt = ["Plots", "GraphPlot"]
-PlotsExt = "Plots"
+GraphPlotExt = ["StatsPlots", "GraphPlot"]
+PlotsExt = "StatsPlots"
 
 [compat]
 BlackBoxOptim = "0.5, 0.6"
@@ -79,3 +78,5 @@ StatsFuns = "1.3"
 YAML = "0.4"
 ZipFile = "0.10"
 julia = "1"
+StatsPlots = "0.15"
+GraphPlot = "0.6"

README.md

@@ -89,11 +89,17 @@ The examples below are run from the [examples](https://github.com/ConnectedSyste
 ```julia
 using Statistics
 using CSV, DataFrames, YAML
-using Plots
+using StatsPlots
 using Streamfall
 
+example_data_dir = joinpath(dirname(dirname(pathof(Streamfall))), "test/data")
+
 # Load data file which holds observed streamflow, precipitation and PET data
-obs_data = CSV.read("../test/data/cotter/climate/CAMELS-AUS_410730.csv", DataFrame; comment="#")
+obs_data = CSV.read(
+    joinpath(example_data_dir, "cotter/climate/CAMELS-AUS_410730.csv"), 
+    DataFrame; 
+    comment="#"
+)
 # 18808×8 DataFrame
 #    Row │ year   month  day    Date        410730_P    410730_PET  410730_max_T  410730_Q
 #        │ Int64  Int64  Int64  Date        Float64     Float64     Float64       Float64
@@ -213,17 +219,18 @@ model.
 
 ```julia
 using CSV, DataFrames, YAML
-using Plots
+using StatsPlots
 using Streamfall
 
 
 # Load a network from a file, providing a name for the network and the file path.
 # Creates a graph representation of the stream with associated metadata.
-sn = load_network("Example Network", "../test/data/campaspe/campaspe_network.yml")
+example_data_dir = joinpath(dirname(dirname(pathof(Streamfall))), "test/data")
+sn = load_network("Example Network", joinpath(example_data_dir, "campaspe/campaspe_network.yml"))
 
 # Load climate data, in this case from a CSV file with data for all nodes.
 # Indicate which columns are precipitation and evaporation data based on partial identifiers
-climate = Climate("../test/data/campaspe/climate/climate.csv", "_rain", "_evap")
+climate = Climate(joinpath(example_data_dir, "campaspe/climate/climate.csv"), "_rain", "_evap")
 
 # This runs an entire stream network
 @info "Running an example stream..."

ext/GraphPlotExt/GraphPlotExt.jl

@@ -1,6 +1,6 @@
 module GraphPlotExt
 
-using Plots, GraphPlot
+using StatsPlots, GraphPlot
 using Streamfall
 import Streamfall: vertices
 import Streamfall: StreamfallNetwork

ext/MakieExt/MakieExt.jl

@@ -71,7 +71,7 @@ function Streamfall.Viz.quickplot(
     show_range = burn_in:last_e
     return Streamfall.Viz.quickplot(obs[show_range], sim[show_range], date[show_range], label, log; metric=metric)
 end
-function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, xticklabels::Vector, label="Modeled", log=false; metric=Streamfall.mKGE)
+function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, xticklabels::Vector; label="Modeled", log=false, metric=Streamfall.mKGE)
     @assert length(xticklabels) == length(obs) || "x-axis tick label length and observed lengths do not match!"
     @assert length(xticklabels) == length(sim) || "x-axis tick label length and simulated lengths do not match!"
 

ext/PlotsExt/PlotsExt.jl

@@ -1,13 +1,14 @@
 module PlotsExt
 
-using Plots, StatsPlots
-using Plots.Measures
+using StatsPlots
+using StatsPlots.Plots.Measures
 
 using DataFrames, Dates, Statistics, Distributions, LaTeXStrings
 import Bootstrap: bootstrap, BalancedSampling
 
 using Streamfall
 import Streamfall: Analysis.TemporalCrossSection
+import Streamfall.Viz: symlog
 
 function Streamfall.Viz.plot(node::NetworkNode, climate::Climate)
     return Plots.plot(
@@ -50,23 +51,23 @@ function Streamfall.Viz.quickplot(node::NetworkNode, climate::Climate)
 
     @assert length(all_dates) == length(node.outflow) || "Date length and result lengths do not match!"
 
-    fig = plot(all_dates, node.outflow)
+    fig = Plots.plot(all_dates, node.outflow)
 
     return fig
 end
-function Streamfall.Viz.quickplot(obs, node::NetworkNode, climate::Climate, label="", log=false; burn_in=1, limit=nothing, metric=Streamfall.mKGE)
-    return Streamfall.Viz.quickplot(obs, node.outflow, climate, label, log; burn_in=burn_in, limit=limit, metric=metric)
+function Streamfall.Viz.quickplot(obs::Vector, node::NetworkNode, climate::Climate; label::String="", log::Bool=false, burn_in=1, limit=nothing, metric=Streamfall.mKGE)
+    return Streamfall.Viz.quickplot(obs, node.outflow, climate; label, log, burn_in, limit, metric)
 end
-function Streamfall.Viz.quickplot(obs::DataFrame, sim::Vector, climate::Climate, label="", log=false; burn_in=1, limit=nothing, metric=Streamfall.mKGE)
+function Streamfall.Viz.quickplot(obs::DataFrame, sim::Vector, climate::Climate; label::String="", log::Bool=false, burn_in=1, limit=nothing, metric=Streamfall.mKGE)
     return Streamfall.Viz.quickplot(Matrix(obs[:, Not("Date")])[:, 1], sim, climate, label, log; burn_in, limit, metric)
 end
-function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, climate::Climate, label="", log=false; burn_in=1, limit=nothing, metric=Streamfall.mKGE)
+function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, climate::Climate; label::String="", log::Bool=false, burn_in=1, limit=nothing, metric=Streamfall.mKGE)
     date = timesteps(climate)
     last_e = !isnothing(limit) ? limit : lastindex(obs)
     show_range = burn_in:last_e
-    return quickplot(obs[show_range], sim[show_range], date[show_range], label, log; metric=metric)
+    return quickplot(obs[show_range], sim[show_range], date[show_range]; label, log, metric)
 end
-function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, xticklabels::Vector, label="Modeled", log=false; metric=Streamfall.mKGE)
+function Streamfall.Viz.quickplot(obs::Vector, sim::Vector, xticklabels::Vector; label="Modeled", log=false, metric=Streamfall.mKGE)
     @assert length(xticklabels) == length(obs) || "x-axis tick label length and observed lengths do not match!"
     @assert length(xticklabels) == length(sim) || "x-axis tick label length and simulated lengths do not match!"
 
@@ -167,7 +168,7 @@ function Streamfall.Viz.temporal_cross_section(
     logscale = [:log, :log10]
     tmp = nothing
 
-    xsect_res = TemporalCrossSection(dates, obs, period)
+    xsect_res = TemporalCrossSection(dates, obs; period)
 
     if :yscale in arg_keys || :yaxis in arg_keys
         tmp = (:yscale in arg_keys) ? kwargs[:yscale] : kwargs[:yaxis]
@@ -178,7 +179,7 @@ function Streamfall.Viz.temporal_cross_section(
             # Format function for y-axis tick labels (e.g., 10^x)
             format_func = y -> (y != 0) ? L"%$(Int(round(sign(y)) * 10))^{%$(round(abs(y), digits=1))}" : L"0"
 
-            log_xsect_res = TemporalCrossSection(dates, log_obs, period)
+            log_xsect_res = TemporalCrossSection(dates, log_obs; period)
             target = log_xsect_res.cross_section
         else
             target = xsect_res.cross_section
@@ -273,7 +274,7 @@ function Streamfall.Viz.temporal_cross_section(
     logscale = [:log, :log10]
     tmp = nothing
 
-    xsect_res = TemporalCrossSection(dates, obs, sim, period)
+    xsect_res = TemporalCrossSection(dates, obs, sim; period)
     target = xsect_res.cross_section
 
     if :yscale in arg_keys || :yaxis in arg_keys
@@ -286,7 +287,7 @@ function Streamfall.Viz.temporal_cross_section(
             # Format function for y-axis tick labels (e.g., 10^x)
             format_func = y -> (y != 0) ? L"%$(Int(round(sign(y)) * 10))^{%$(round(abs(y), digits=1))}" : L"0"
 
-            log_xsect_res = TemporalCrossSection(dates, log_obs, log_sim, period)
+            log_xsect_res = TemporalCrossSection(dates, log_obs, log_sim; period)
             target = log_xsect_res.cross_section
         end
     end

src/Analysis/uncertainty.jl

@@ -4,23 +4,23 @@ using OrderedCollections
 import ..ME, ..MAE
 
 
-mutable struct TemporalCrossSection{A<:Dates.Date, B<:Real, D<:OrderedDict}
+mutable struct TemporalCrossSection{A<:Dates.Date,B<:Real,D<:OrderedDict}
     dates::Array{A}
     ts::Array{B}
     subperiods::D
-    cross_section::Union{DataFrame, Nothing}
+    cross_section::Union{DataFrame,Nothing}
 end
 
 
-function TemporalCrossSection(dates::Array, ts::Array, period::Function=monthday)
+function TemporalCrossSection(dates::Array, ts::Array; period::Function=monthday)
     df = DataFrame(Date=dates, data=ts)
     sp = sort(unique(period.(dates)))
 
     # Remove leap days (when using monthday)
-    deleteat!(sp, findall(x -> x == (2,29), sp))
+    deleteat!(sp, findall(x -> x == (2, 29), sp))
 
     res = OrderedDict(
-        sp_i => df[period.(df.Date) .== [sp_i], :].data for sp_i in sp
+        sp_i => df[period.(df.Date).==[sp_i], :].data for sp_i in sp
     )
 
     return TemporalCrossSection(dates, ts, res, nothing)
@@ -30,10 +30,12 @@ end
 """
 TemporalCrossSection constructor that handles two time series
 """
-function TemporalCrossSection(dates::Array, obs::Array, sim::Array,
-                              period::Function=monthday)
+function TemporalCrossSection(
+    dates::Array, obs::Array, sim::Array;
+    period::Function=monthday
+)
     Y = ME.(obs, sim)
-    return TemporalCrossSection(dates, Y, period)
+    return TemporalCrossSection(dates, Y; period)
 end
 
 
@@ -56,7 +58,7 @@ function cross_section(tr::TemporalCrossSection)
     end
 
     cols = [:abs_min, :lower_95, :lower_75, :median,
-            :upper_75, :upper_95, :abs_max, :mean, :std]
+        :upper_75, :upper_95, :abs_max, :mean, :std]
 
     x_section = DataFrame(boxframe, cols)
     x_section[:, :subperiod] = collect(keys(sp))

src/Streamfall.jl

@@ -4,8 +4,6 @@ using Statistics
 using Graphs, MetaGraphs, Distributed, DataFrames
 
 
-const MODPATH = @__DIR__
-
 include("Network.jl")
 include("Nodes/Node.jl")
 include("Climate.jl")

src/viz/Viz.jl

@@ -12,6 +12,16 @@ function plot_residuals end
 function save_figure end
 function save_figure! end
 
+
+"""Symmetrical log values.
+
+https://kar.kent.ac.uk/32810/2/2012_Bi-symmetric-log-transformation_v5.pdf
+https://discourse.julialang.org/t/symmetrical-log-plot/45709/3
+"""
+function symlog(y)
+    return sign.(y) .* log10.(1.0 .+ abs.(y))
+end
+
 export plot, plot!, quickplot
 export temporal_cross_section, plot_residuals
 export save_figure, save_figure!

src/viz/_plotting.jl

@@ -1,6 +1,6 @@
-using Plots, StatsPlots
-using Plots.Measures
-import Plots: plot, plot!
+using StatsPlots
+using StatsPlots.Plots
+import StatsPlots: plot, plot!
 using DataFrames, Dates, Statistics, Distributions, LaTeXStrings
 import Bootstrap: bootstrap, BalancedSampling
 
@@ -142,7 +142,7 @@ function temporal_cross_section(dates, obs;
     logscale = [:log, :log10]
     tmp = nothing
 
-    xsect_res = TemporalCrossSection(dates, obs, period)
+    xsect_res = TemporalCrossSection(dates, obs; period)
 
     if :yscale in arg_keys || :yaxis in arg_keys
         tmp = (:yscale in arg_keys) ? kwargs[:yscale] : kwargs[:yaxis]
@@ -153,7 +153,7 @@ function temporal_cross_section(dates, obs;
             # Format function for y-axis tick labels (e.g., 10^x)
             format_func = y -> (y != 0) ? L"%$(Int(round(sign(y)) * 10))^{%$(round(abs(y), digits=1))}" : L"0"
 
-            log_xsect_res = TemporalCrossSection(dates, log_obs, period)
+            log_xsect_res = TemporalCrossSection(dates, log_obs; period)
             target = log_xsect_res.cross_section
         else
             target = xsect_res.cross_section
@@ -250,7 +250,7 @@ function temporal_cross_section(
     logscale = [:log, :log10]
     tmp = nothing
 
-    xsect_res = TemporalCrossSection(dates, obs, sim, period)
+    xsect_res = TemporalCrossSection(dates, obs, sim; period)
     target = xsect_res.cross_section
 
     if :yscale in arg_keys || :yaxis in arg_keys
@@ -263,7 +263,7 @@ function temporal_cross_section(
             # Format function for y-axis tick labels (e.g., 10^x)
             format_func = y -> (y != 0) ? L"%$(Int(round(sign(y)) * 10))^{%$(round(abs(y), digits=1))}" : L"0"
 
-            log_xsect_res = TemporalCrossSection(dates, log_obs, log_sim, period)
+            log_xsect_res = TemporalCrossSection(dates, log_obs, log_sim; period)
             target = log_xsect_res.cross_section
         end
     end