add examples

docs/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
+PML = "6d0293b8-e749-48b5-896f-0ef93cd51027"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

docs/make.jl

@@ -0,0 +1,86 @@
+using Documenter
+
+if haskey(ENV, "GITHUB_ACTIONS")
+  ENV["JULIA_DEBUG"] = "Documenter"
+end
+
+deployconfig = Documenter.auto_detect_deploy_system()
+Documenter.post_status(deployconfig; type="pending", repo="github.com/gee-hydro/PML.jl.git")
+using Literate
+using Plots # to not capture precompilation output
+
+# generate examples
+EXAMPLE = joinpath(@__DIR__, "..", "examples", "ex-calib_IGBP.jl")
+OUTPUT = joinpath(@__DIR__, "src/generated")
+
+function preprocess(str)
+  str = replace(str, "x = 123" => "y = 321"; count=1)
+  return str
+end
+
+Literate.markdown(EXAMPLE, OUTPUT, preprocess=preprocess)
+Literate.notebook(EXAMPLE, OUTPUT, preprocess=preprocess)
+Literate.script(EXAMPLE, OUTPUT, preprocess=preprocess)
+
+# generate the example notebook for the documentation, keep in sync with outputformats.md
+Literate.markdown(joinpath(@__DIR__, "src/outputformats.jl"), OUTPUT; credit=false, name="name")
+Literate.notebook(joinpath(@__DIR__, "src/outputformats.jl"), OUTPUT; name="notebook")
+Literate.script(joinpath(@__DIR__, "src/outputformats.jl"), OUTPUT; credit=false)
+
+# Replace the link in outputformats.md
+# since that page is not "literated"
+if haskey(ENV, "GITHUB_ACTIONS")
+  folder = Base.CoreLogging.with_logger(Base.CoreLogging.NullLogger()) do
+    Documenter.deploy_folder(
+      deployconfig;
+      repo="github.com/gee-hydro/PML.jl.git",
+      devbranch="master",
+      push_preview=true,
+      devurl="dev",
+    ).subfolder
+  end
+  url = "https://nbviewer.jupyter.org/github/gee-hydro/PML.jl/blob/gh-pages/$(folder)/"
+  str = read(joinpath(@__DIR__, "src/outputformats.md"), String)
+  str = replace(str, "[notebook.ipynb](generated/notebook.ipynb)." => "[notebook.ipynb]($(url)generated/notebook.ipynb).")
+  write(joinpath(@__DIR__, "src/outputformats.md"), str)
+end
+
+# # Generate changelog
+# using Changelog
+# clog = joinpath(@__DIR__, "src", "changelog.md")
+# Changelog.generate(
+#   Changelog.Documenter(),
+#   joinpath(@__DIR__, "..", "CHANGELOG.md"),
+#   clog;
+#   repo="gee-hydro/PML.jl",
+# )
+# write(clog, replace(read(clog, String), r"^# Literate.jl changelog"m => "# **9.** Changelog"))
+
+
+makedocs(
+  format=Documenter.HTML(
+    assets=["assets/custom.css", "assets/favicon.ico"],
+    prettyurls=true, # haskey(ENV, "GITHUB_ACTIONS"),
+    canonical="https://fredrikekre.github.io/Literate.jl/v2",
+  ),
+  modules=[Literate],
+  sitename="Literate.jl",
+  pages=Any[
+    # "index.md",
+    # "fileformat.md",
+    # "pipeline.md",
+    # "outputformats.md",
+    # "customprocessing.md",
+    # "documenter.md",
+    # "tips.md",
+    "generated/example.md",
+    # "changelog.md",
+  ],
+)
+
+deploydocs(
+  repo="github.com/gee-hydro/PML.jl.git",
+  push_preview=true,
+  versions=["v2" => "v^", "v#.#", "dev" => "dev"],
+  deploy_config=deployconfig,
+)

docs/src/generated/ex-calib_IGBP.md

@@ -0,0 +1,29 @@
+```@meta
+EditURL = "../../../examples/ex-calib_IGBP.jl"
+```
+
+````@example ex-calib_IGBP
+using PML, Ipaper
+
+dir_proj = "$(@__DIR__)/.."
+df_out, df, par = deserialize("$dir_proj/data/CRO/FLUXNET_CRO")
+df.GPP_obs = df.GPPobs
+df.ET_obs = df.ETobs
+````
+
+r = PMLV2_sites(df; par)
+
+````@example ex-calib_IGBP
+theta, goal, flag = model_calib(df, par0)
+df_out = PMLV2_sites(df; par=theta2par(theta))
+
+gof = [
+  (; var="ET", GOF(df.ET_obs, df_out.ET)...),
+  (; var="GPP", GOF(df.GPP_obs, df_out.GPP)...)] |> DataFrame
+DataFrame(gof)
+````
+
+---
+
+*This page was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*
+

examples/ex-calib_IGBP.jl

@@ -0,0 +1,14 @@
+using PML, Ipaper
+
+df_out, df, par = deserialize(file_FLUXNET_CRO)
+df.GPP_obs = df.GPPobs
+df.ET_obs = df.ETobs
+
+# r = PMLV2_sites(df; par)
+theta, goal, flag = model_calib(df, par0)
+df_out = PMLV2_sites(df; par=theta2par(theta))
+
+gof = [
+  (; var="ET", GOF(df.ET_obs, df_out.ET)...),
+  (; var="GPP", GOF(df.GPP_obs, df_out.GPP)...)] |> DataFrame
+DataFrame(gof)  

examples/run.jl

@@ -0,0 +1,4 @@
+using Literate
+
+
+Literate.markdown("examples/README.jl", "."; flavor=Literate.CommonMarkFlavor())

src/PML.jl

@@ -2,13 +2,17 @@ module PML
 
 export PMLV2_sites
 export PMLV2, T_adjust_Vm25, f_VPD_Zhang2019
-export GOF
+export DataFrame, GOF
+export file_FLUXNET_CRO
 
 using DocStringExtensions
 using Parameters, DataFrames
-import HydroTools: cal_Uz, ET0_eq, 
-  Cp, atm, 
-  GOF, sceua
+import HydroTools: cal_Uz, ET0_eq, Cp, atm, GOF, sceua
+
+## global data
+dir_proj = "$(@__DIR__)/.."
+file_FLUXNET_CRO = "$dir_proj/data/CRO/FLUXNET_CRO" |> abspath
+
 
 # lambda: [MJ kg-1]
 W2mm(Ra; λ) = Ra * 86400 / 1e6 / λ

src/Utilize/Utilize.jl

@@ -1,4 +1,4 @@
 include("DataType.jl")
-include("PMLV2_sites.jl")
+# include("PMLV2_sites.jl")
 include("model_calib.jl")
 include("model_gof.jl")

src/Utilize/model_calib.jl

@@ -25,6 +25,10 @@ end
 
 
 ## 最后一步，参数率定模块
+"""
+    model_calib(df::AbstractDataFrame, par0::AbstractETParam; 
+        IGBPcode=nothing, maxn=2500, of_gof=:NSE, kw...)
+"""
 function model_calib(df::AbstractDataFrame, par0::AbstractETParam; IGBPcode=nothing, maxn=2500, of_gof=:NSE, kw...)
   parRanges = get_bounds(par0)
   lower = parRanges[:, 1]
@@ -35,6 +39,4 @@ function model_calib(df::AbstractDataFrame, par0::AbstractETParam; IGBPcode=noth
     theta0, lower, upper; maxn, kw...) # theta, goal, flag
 end
 
-
-# rounded_data = NamedTuple((field => round(value) for (field, value) in data))
 export model_goal, model_calib

src/main_Ipaper.jl

@@ -1,5 +1,6 @@
 using Statistics
 
+# rounded_data = NamedTuple((field => round(value) for (field, value) in data))
 round2(x::NamedTuple, digits=3; kw...) = map(val -> round(val; digits), x)
 
 
@@ -20,7 +21,7 @@ function movmean2(y::AbstractVector{T}, win_left::Integer, win_right::Integer=wi
     end
     z[i] = count > 0 ? ∑ / count : T(NaN)
   end
-  z
+  return z
 end
 
 function nanmean2(x::T1, y::T2) where {T1<:Real, T2<:Real}

src/model_PMLV2.jl

@@ -11,8 +11,8 @@
 - `U2`   : m/s
 - `LAI`  : m2 m-2
 - `Pa`   : kPa
-- `Ca`   : ppm
-- `Ω`    : clamping index, default is 1.0
+- `Ca`   : ppm, default `380`
+- `Ω`    : clamping index, default is `1.0`
 
 # Examples
 ```julia
@@ -120,3 +120,19 @@ function PMLV2(d::AbstractDataFrame; par::Param_PMLV2=Param_PMLV2(), kw...)
     d.VPD, d.U2, d.LAI,
     d.Pa, d.Ca; par, kw...) |> to_df
 end
+
+# 相同植被类型多个站点一起的计算
+function PMLV2_sites(df::AbstractDataFrame; par::Param_PMLV2=Param_PMLV2(), kw...)
+  sites = df.site
+  grps = unique(sites)
+
+  # ! 这里有优化空间，但程序会写的很复杂
+  res = []
+  for grp in grps
+    inds = sites .== grp
+    d = df[inds, :]
+    r = PMLV2(d; par, kw...)
+    push!(res, r)
+  end
+  vcat(res...)
+end