Reference

Docstrings for SpatRasters.

`DataFrame`

DataFrame <: AbstractDataFrame

An AbstractDataFrame that stores a set of named columns.

The columns are normally AbstractVectors stored in memory, particularly a Vector, PooledVector or CategoricalVector.

Constructors

DataFrame(pairs::Pair...; makeunique::Bool=false, copycols::Bool=true)
DataFrame(pairs::AbstractVector{<:Pair}; makeunique::Bool=false, copycols::Bool=true)
DataFrame(ds::AbstractDict; copycols::Bool=true)
DataFrame(; kwargs..., copycols::Bool=true)

DataFrame(table; copycols::Union{Bool, Nothing}=nothing)
DataFrame(table, names::AbstractVector;
          makeunique::Bool=false, copycols::Union{Bool, Nothing}=nothing)
DataFrame(columns::AbstractVecOrMat, names::AbstractVector;
          makeunique::Bool=false, copycols::Bool=true)

DataFrame(::DataFrameRow; copycols::Bool=true)
DataFrame(::GroupedDataFrame; copycols::Bool=true, keepkeys::Bool=true)

Keyword arguments

copycols : whether vectors passed as columns should be copied; by default set to true and the vectors are copied; if set to false then the constructor will still copy the passed columns if it is not possible to construct a DataFrame without materializing new columns. Note the copycols=nothing default in the Tables.jl compatible constructor; it is provided as certain input table types may have already made a copy of columns or the columns may otherwise be immutable, in which case columns are not copied by default. To force a copy in such cases, or to get mutable columns from an immutable input table (like Arrow.Table), pass copycols=true explicitly.
makeunique : if false (the default), an error will be raised

(note that not all constructors support these keyword arguments)

Details on behavior of different constructors

It is allowed to pass a vector of Pairs, a list of Pairs as positional arguments, or a list of keyword arguments. In this case each pair is considered to represent a column name to column value mapping and column name must be a Symbol or string. Alternatively a dictionary can be passed to the constructor in which case its entries are considered to define the column name and column value pairs. If the dictionary is a Dict then column names will be sorted in the returned DataFrame.

In all the constructors described above column value can be a vector which is consumed as is or an object of any other type (except AbstractArray). In the latter case the passed value is automatically repeated to fill a new vector of the appropriate length. As a particular rule values stored in a Ref or a 0-dimensional AbstractArray are unwrapped and treated in the same way.

It is also allowed to pass a vector of vectors or a matrix as as the first argument. In this case the second argument must be a vector of Symbols or strings specifying column names, or the symbol :auto to generate column names x1, x2, … automatically. Note that in this case if the first argument is a matrix and copycols=false the columns of the created DataFrame will be views of columns the source matrix.

If a single positional argument is passed to a DataFrame constructor then it is assumed to be of type that implements the Tables.jl interface using which the returned DataFrame is materialized.

If two positional arguments are passed, where the second argument is an AbstractVector, then the first argument is taken to be a table as described in the previous paragraph, and columns names of the resulting data frame are taken from the vector passed as the second positional argument.

Finally it is allowed to construct a DataFrame from a DataFrameRow or a GroupedDataFrame. In the latter case the keepkeys keyword argument specifies whether the resulting DataFrame should contain the grouping columns of the passed GroupedDataFrame and the order of rows in the result follows the order of groups in the GroupedDataFrame passed.

Notes

The DataFrame constructor by default copies all columns vectors passed to it. Pass the copycols=false keyword argument (where supported) to reuse vectors without copying them.

By default an error will be raised if duplicates in column names are found. Pass makeunique=true keyword argument (where supported) to accept duplicate names, in which case they will be suffixed with _i (i starting at 1 for the first duplicate).

If an AbstractRange is passed to a DataFrame constructor as a column it is always collected to a Vector (even if copycols=false). As a general rule AbstractRange values are always materialized to a Vector by all functions in DataFrames.jl before being stored in a DataFrame.

DataFrame can store only columns that use 1-based indexing. Attempting to store a vector using non-standard indexing raises an error.

The DataFrame type is designed to allow column types to vary and to be dynamically changed also after it is constructed. Therefore DataFrames are not type stable. For performance-critical code that requires type-stability either use the functionality provided by select/transform/combine functions, use Tables.columntable and Tables.namedtupleiterator functions, use barrier functions, or provide type assertions to the variables that hold columns extracted from a DataFrame.

Metadata: this function preserves all table and column-level metadata. As a special case if a GroupedDataFrame is passed then only :note-style metadata from parent of the GroupedDataFrame is preserved.

Examples

julia> DataFrame((a=[1, 2], b=[3, 4])) # Tables.jl table constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      3
   2 │     2      4

julia> DataFrame([(a=1, b=0), (a=2, b=0)]) # Tables.jl table constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame("a" => 1:2, "b" => 0) # Pair constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame([:a => 1:2, :b => 0]) # vector of Pairs constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame(Dict(:a => 1:2, :b => 0)) # dictionary constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame(a=1:2, b=0) # keyword argument constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame([[1, 2], [0, 0]], [:a, :b]) # vector of vectors constructor
2×2 DataFrame
 Row │ a      b
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

julia> DataFrame([1 0; 2 0], :auto) # matrix constructor
2×2 DataFrame
 Row │ x1     x2
     │ Int64  Int64
─────┼──────────────
   1 │     1      0
   2 │     2      0

`GOF`

No documentation found for public symbol.

HydroTools.GOF is a Function.

# 1 method for generic function "GOF" from HydroTools:
 [1] GOF(obs::AbstractVector{T}, sim::AbstractVector{T}) where T<:Real
     @ ~/.julia/packages/HydroTools/DJBjN/src/GOF.jl:67

`ModelCalib`

ModelCalib(df::AbstractDataFrame, par0::AbstractETParam; 
    IGBPcode=nothing, maxn=2500, of_gof=:NSE, kw...)

`ModelCalib_IGBPs`

No documentation found for public symbol.

PenmanMonteithLeuning.ModelCalib_IGBPs is a Function.

# 1 method for generic function "ModelCalib_IGBPs" from PenmanMonteithLeuning:
 [1] ModelCalib_IGBPs(data::DataFrames.AbstractDataFrame; parNames, of_gof, maxn)
     @ ~/work/PML.jl/PML.jl/src/ModelCalib.jl:6

`PMLV2`

PMLV2 (Penman–Monteith–Leuning Version 2) Evapotranspiration model

Arguments

Prcp : mm/d
Tavg : degC
Rs : W m-2
Rn : W m-2
VPD : W m-2
U2 : m/s
LAI : m2 m-2
Pa : kPa
Ca : ppm, default 380
Ω : clamping index, default is 1.0

Examples

References

Gan Rong, 2018, Ecohydrology
Zhang Yongqiang, 2019, RSE
Kong Dongdong, 2019, ISPRS

PMLV2(Prcp, Tavg, Rs, Rn, VPD, U2, LAI, Pa, Ca; par=param0, frame=3)

Notes

一个站点的计算。注意，不同植被类型，参数不同。

Arguments

frame: in 8-days

Arguments

kw: named keyword arguments
- r: interm_PML

`PMLV2_sites`

No documentation found for public symbol.

PenmanMonteithLeuning.PMLV2_sites is a Function.

# 1 method for generic function "PMLV2_sites" from PenmanMonteithLeuning:
 [1] PMLV2_sites(df::DataFrames.AbstractDataFrame; par, kw...)
     @ ~/work/PML.jl/PML.jl/src/PMLV2.jl:134

`ParNames`

No documentation found for public symbol.

PenmanMonteithLeuning.ParNames is of type Vector{Symbol}.

Summary

mutable struct Vector{Symbol}

Fields

ref  :: MemoryRef{Symbol}
size :: Tuple{Int64}

Supertype Hierarchy

Vector{Symbol} <: DenseVector{Symbol} <: AbstractVector{Symbol} <: Any

`Param_PMLV2`

struct Param_PMLV2{FT<:AbstractFloat} <: AbstractETParam{FT}

Fields

α::Real: initial slope of the light response curve to assimilation rate, (i.e., quantum efficiency; μmol CO2 [μmol PAR]⁻¹)` Default: 0.06
η::Real: initial slope of the CO2 response curve to assimilation rate, (i.e., carboxylation efficiency; μmol m⁻² s⁻¹ [μmol m⁻² s⁻¹]⁻¹) Default: 0.04
g1::Real: stomatal conductance coefficient, μmol m⁻² s⁻¹ Default: 10.0
VCmax25::Real: carbon saturated rate of photosynthesis at 25 °C, μmol m⁻² s⁻¹ Default: 50.0
VPDmin::Real: parameter to constrain gc, kPa Default: 0.9
VPDmax::Real: parameter to constrain gc, kPa Default: 4.0
D0::Real: 水汽压参数 Default: 0.7
kQ::Real: extinction coefficients for visible radiation Default: 0.45
kA::Real: extinction coefficients for available energy Default: 0.7
S_sls::Real: Specific leaf storage, van Dijk, A.I.J.M, 2001, Eq2 Default: 0.1
fER0::Real: Canopy cover fraction related parameter Default: 0.1
hc::Real: canopy height, [m] Default: 1.0
d_pc::Real: photoperiod constraint Default: 2.0
_hc::Vector{FT} where FT<:Real: Default: [1.0, 1.0, 1.0]
_η::Vector{FT} where FT<:Real: Default: [0.04, 0.04, 0.04]
_α::Vector{FT} where FT<:Real: Default: [0.06, 0.06, 0.06]
_g1::Vector{FT} where FT<:Real: Default: [10.0, 10.0, 10.0]
_VCmax25::Vector{FT} where FT<:Real: Default: [50.0, 50.0, 50.0]

`T_adjust_Vm25`

No documentation found for public symbol.

PenmanMonteithLeuning.T_adjust_Vm25 is a Function.

# 1 method for generic function "T_adjust_Vm25" from PenmanMonteithLeuning:
 [1] T_adjust_Vm25(Tavg::T) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/photosynthesis.jl:47

`aerodynamic_conductance`

aerodynamic_conductance(U2, hc)

Arguments

U2: wind speed at 2m
hc: canopy height

Return

Ga: aerodynamic conductance in m/s

`bounds`

No documentation found for private symbol.

FieldMetadata.bounds is a Function.

# 27 methods for generic function "bounds" from FieldMetadata:
  [1] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:α}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [2] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:_g1}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [3] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:g1}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [4] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:kA}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [5] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:VPDmin}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [6] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:D0}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [7] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:_hc}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [8] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:kQ}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
  [9] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:VPDmax}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [10] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:d_pc}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [11] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:_α}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [12] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:_VCmax25}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [13] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:S_sls}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [14] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:fER0}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [15] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:_η}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [16] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:hc}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [17] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:η}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [18] bounds(::Type{<:Param_PMLV2}, ::Type{Val{:VCmax25}})
     @ PenmanMonteithLeuning ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:214
 [19] bounds(::Type{var"#214#X"}, keys::Tuple{}) where var"#214#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:66
 [20] bounds(::Type{var"#211#X"}, keys::Tuple) where var"#211#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:64
 [21] bounds(x::Type, key::Type)
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:56
 [22] bounds(::Type{var"#204#X"}, key::Symbol) where var"#204#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:59
 [23] bounds(x::Type{var"#208#X"}) where var"#208#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:63
 [24] bounds(::var"#198#X", key::Symbol) where var"#198#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:57
 [25] bounds(::var"#201#X", key::Type) where var"#201#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:58
 [26] bounds(x, key)
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:55
 [27] bounds(::var"#206#X") where var"#206#X"
     @ ~/.julia/packages/FieldMetadata/oeQwS/src/FieldMetadata.jl:62

`cal_Ei_Dijk2021`

cal_Ei_Dijk2021(Prcp::T, LAI::T, par::Param_PMLV2) where {T<:Real}

References

van Dijk, A.I.J.M, 2001, Eq2.

`f_VPD_Zhang2019`

No documentation found for public symbol.

PenmanMonteithLeuning.f_VPD_Zhang2019 is a Function.

# 1 method for generic function "f_VPD_Zhang2019" from PenmanMonteithLeuning:
 [1] f_VPD_Zhang2019(VPD::T, par::Param_PMLV2) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/water_constrain.jl:2

`file_FLUXNET_CRO`

No documentation found for public symbol.

PenmanMonteithLeuning.file_FLUXNET_CRO is of type String.

Summary

mutable struct String

Supertype Hierarchy

String <: AbstractString <: Any

`file_FLUXNET_CRO_USTwt`

No documentation found for public symbol.

PenmanMonteithLeuning.file_FLUXNET_CRO_USTwt is of type String.

Summary

mutable struct String

Supertype Hierarchy

String <: AbstractString <: Any

`fread`

fread(file::AbstractString; header=true, kw...)

Arguments

file: the csv file to read
header: whether the csv file has header?
kw: other parameters for CSV.File

Examaple

fread("a.csv")

`fwrite`

fwrite(df, file; kw...)

df = DataFrame(A=1:3, B=4:6, C=7:9)
fwrite(df, "a.csv")
fwrite(df, "a.csv", append=true)

`getDataType`

No documentation found for public symbol.

PenmanMonteithLeuning.getDataType is a Function.

# 1 method for generic function "getDataType" from PenmanMonteithLeuning:
 [1] getDataType(x)
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:42

`get_bounds`

No documentation found for public symbol.

PenmanMonteithLeuning.get_bounds is a Function.

# 2 methods for generic function "get_bounds" from PenmanMonteithLeuning:
 [1] get_bounds(parNames::Vector{Symbol})
     @ ~/work/PML.jl/PML.jl/src/Parameter.jl:65
 [2] get_bounds()
     @ ~/work/PML.jl/PML.jl/src/Parameter.jl:65

`hc_raw`

No documentation found for public symbol.

PenmanMonteithLeuning.hc_raw is of type Vector{Float64}.

Summary

mutable struct Vector{Float64}

Fields

ref  :: MemoryRef{Float64}
size :: Tuple{Int64}

Supertype Hierarchy

Vector{Float64} <: DenseVector{Float64} <: AbstractVector{Float64} <: Any

`interm_PML`

No documentation found for public symbol.

Summary

mutable struct interm_PML{T}

Fields

ET        :: T
GPP       :: T
Ec        :: T
Ecr       :: T
Eca       :: T
Ei        :: T
Pi        :: T
Es_eq     :: T
Eeq       :: T
ET_water  :: T
Ga        :: T
Gc_w      :: T
fval_soil :: T
Es        :: T

`map_df_tuple`

No documentation found for public symbol.

PenmanMonteithLeuning.map_df_tuple is a Function.

# 1 method for generic function "map_df_tuple" from PenmanMonteithLeuning:
 [1] map_df_tuple(fun::Function, lst::DataFrames.GroupedDataFrame{DataFrame}, args...; kw...)
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:62

`melt_list`

melt_list(list; deepcopy=false, kw...)

Arguments

list: list of DataFrames

Examples

d = data.table(; x=1, y=2)
l = [d, d, d, d]

r1 = melt_list(l, id=1:4) # id all is 4
r2 = melt_list(l, id=1:4, deepcopy=true)

melt_list(l; a = 1, b = 2)

`model_goal`

No documentation found for public symbol.

PenmanMonteithLeuning.model_goal is a Function.

# 1 method for generic function "model_goal" from PenmanMonteithLeuning:
 [1] model_goal(df, theta, parNames; IGBPcode, of_gof, verbose)
     @ ~/work/PML.jl/PML.jl/src/ModelCalib.jl:54

`model_gof`

No documentation found for public symbol.

PenmanMonteithLeuning.model_gof is a Function.

# 1 method for generic function "model_gof" from PenmanMonteithLeuning:
 [1] model_gof(df_out::DataFrame; all)
     @ ~/work/PML.jl/PML.jl/src/ModelCalib.jl:80

`movmean2`

No documentation found for public symbol.

PenmanMonteithLeuning.movmean2 is a Function.

# 2 methods for generic function "movmean2" from PenmanMonteithLeuning:
 [1] movmean2(y::AbstractVector{T}, win_left::Integer, win_right::Integer) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:10
 [2] movmean2(y::AbstractVector{T}, win_left::Integer) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:10

`nanmean2`

No documentation found for public symbol.

PenmanMonteithLeuning.nanmean2 is a Function.

# 1 method for generic function "nanmean2" from PenmanMonteithLeuning:
 [1] nanmean2(x::T1, y::T2) where {T1<:Real, T2<:Real}
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:30

`output_PML`

No documentation found for public symbol.

Summary

mutable struct output_PML{T}

Fields

n         :: Integer
ET        :: Array{T, 1}
GPP       :: Array{T, 1}
Ec        :: Array{T, 1}
Ecr       :: Array{T, 1}
Eca       :: Array{T, 1}
Ei        :: Array{T, 1}
Pi        :: Array{T, 1}
Es_eq     :: Array{T, 1}
Eeq       :: Array{T, 1}
ET_water  :: Array{T, 1}
Ga        :: Array{T, 1}
Gc_w      :: Array{T, 1}
fval_soil :: Array{T, 1}
Es        :: Array{T, 1}

`par0`

No documentation found for public symbol.

PenmanMonteithLeuning.par0 is of type Param_PMLV2{Float64}.

Summary

mutable struct Param_PMLV2{Float64}

Fields

α        :: Float64
η        :: Float64
g1       :: Float64
VCmax25  :: Float64
VPDmin   :: Float64
VPDmax   :: Float64
D0       :: Float64
kQ       :: Float64
kA       :: Float64
S_sls    :: Float64
fER0     :: Float64
hc       :: Float64
d_pc     :: Float64
_hc      :: Vector{Float64}
_η       :: Vector{Float64}
_α       :: Vector{Float64}
_g1      :: Vector{Float64}
_VCmax25 :: Vector{Float64}

Supertype Hierarchy

Param_PMLV2{Float64} <: PenmanMonteithLeuning.AbstractETParam{Float64} <: Any

`photosynthesis`

photosynthesis(Tavg::T, Rs::T, VPD::T, LAI::T, Ca=380.0; par)

Example

# GPP, Gc_w = photosynthesis(Tavg, Rs, VPD, LAI, Ca; par)

`round2`

No documentation found for public symbol.

PenmanMonteithLeuning.round2 is a Function.

# 2 methods for generic function "round2" from PenmanMonteithLeuning:
 [1] round2(x::NamedTuple, digits; kw...)
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:7
 [2] round2(x::NamedTuple; ...)
     @ ~/work/PML.jl/PML.jl/src/utilize.jl:7

`select_param`

No documentation found for public symbol.

PenmanMonteithLeuning.select_param is a Function.

# 1 method for generic function "select_param" from PenmanMonteithLeuning:
 [1] select_param(par::PenmanMonteithLeuning.AbstractETParam, parNames)
     @ ~/work/PML.jl/PML.jl/src/Parameter.jl:91

`theta0`

No documentation found for public symbol.

PenmanMonteithLeuning.theta0 is of type Vector{Any}.

Summary

mutable struct Vector{Any}

Fields

ref  :: MemoryRef{Any}
size :: Tuple{Int64}

Supertype Hierarchy

Vector{Any} <: DenseVector{Any} <: AbstractVector{Any} <: Any

`theta2par`

No documentation found for public symbol.

PenmanMonteithLeuning.theta2par is a Function.

# 1 method for generic function "theta2par" from PenmanMonteithLeuning:
 [1] theta2par(theta::Vector, parNames::Vector{Symbol})
     @ ~/work/PML.jl/PML.jl/src/Parameter.jl:87

`theta2param`

No documentation found for public symbol.

PenmanMonteithLeuning.theta2param is a Function.

# 1 method for generic function "theta2param" from PenmanMonteithLeuning:
 [1] theta2param(params::Array{Vector{T}, 1}, IGBPs) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/Parameter.jl:102

`to_mat`

No documentation found for public symbol.

PenmanMonteithLeuning.to_mat is a Function.

# 1 method for generic function "to_mat" from PenmanMonteithLeuning:
 [1] to_mat(res::output_PML{T}) where T<:Real
     @ ~/work/PML.jl/PML.jl/src/DataType.jl:70

DataFrame

Constructors

Keyword arguments

Details on behavior of different constructors

Notes

Examples

GOF

ModelCalib

ModelCalib_IGBPs

PMLV2

Arguments

Examples

References

Notes

Arguments

Arguments

PMLV2_sites

ParNames

Summary

Fields

Supertype Hierarchy

Param_PMLV2

Fields

PenmanMonteithLeuning

Public names

Displaying contents of readme found at /home/runner/work/PML.jl/PML.jl/README.md

Penman-Monteith-Leuning (PML) Evapotranspiration in Julia

TODO

冠层结构

模型结构

模型表现

T_adjust_Vm25

aerodynamic_conductance

Arguments

Return

bounds

cal_Ei_Dijk2021

References

f_VPD_Zhang2019

file_FLUXNET_CRO

Summary

Supertype Hierarchy

file_FLUXNET_CRO_USTwt

Summary

Supertype Hierarchy

fread

Arguments

Examaple

fwrite

getDataType

get_bounds

hc_raw

Summary

Fields

Supertype Hierarchy

interm_PML

Summary

Fields

map_df_tuple

melt_list

Arguments

Examples

model_goal

model_gof

movmean2

nanmean2

output_PML

Summary

Fields

par0

Summary

Fields

Supertype Hierarchy

photosynthesis

Example

round2

select_param

theta0

Summary

Fields

`DataFrame`

`GOF`

`ModelCalib`

`ModelCalib_IGBPs`

`PMLV2`

`PMLV2_sites`

`ParNames`

`Param_PMLV2`

`PenmanMonteithLeuning`

Displaying contents of readme found at `/home/runner/work/PML.jl/PML.jl/README.md`

`T_adjust_Vm25`

`aerodynamic_conductance`

`bounds`

`cal_Ei_Dijk2021`

`f_VPD_Zhang2019`

`file_FLUXNET_CRO`

`file_FLUXNET_CRO_USTwt`

`fread`

`fwrite`

`getDataType`

`get_bounds`

`hc_raw`

`interm_PML`

`map_df_tuple`

`melt_list`

`model_goal`

`model_gof`

`movmean2`

`nanmean2`

`output_PML`

`par0`

`photosynthesis`

`round2`

`select_param`

`theta0`

`theta2par`

`theta2param`

`to_mat`