Versatile rt tolerance

src/io.jl

@@ -212,7 +212,6 @@ function Base.show(io::IO, ::MIME"text/plain", class::T) where {T <: ClassSP}
  print(io, repr(class), isempty(str) ? "" : "($str)")
  end : print(io, repr(class))
 end
-
 Base.show(io::IO, ::T) where {T <: ClassSP} = print(io, replace(repr(T), r"_$" => "", "SphingolipidsID." => ""))
 
 Base.show(io::IO, ion::Ion) = print(io, repr_adduct(ion.adduct), " of ", ion.molecule)
@@ -248,8 +247,6 @@ print_comp(io::IO, sc::LCBIS) = print(io, ncb(sc), ":", ndb(sc), repr_ox(sc), re
 #Base.show(io::IO, ::MIME"text/plain", sc::LCB) = print(io, "SPB ", sc)
 #Base.show(io::IO, ::MIME"text/plain", sc::ACYL) = print(io, "Acyl ", sc)
 Base.show(io::IO, sc::Acyl) = (print(io, "Acyl "); print_comp(io, sc))
-
-
 print_comp(io::IO, sc::ACYL) = print(io, ncb(sc), ":", ndb(sc), repr_ox(sc))
 print_comp(io::IO, sc::ACYLIS) = print(io, ncb(sc), ":", ndb(sc), repr_ox(sc), repr_is(sc.isotope))
 
@@ -334,20 +331,58 @@ end
 Base.show(io::IO, analyte::AnalyteID) = print(io, isempty(analyte.compound) ? "?" : last(analyte), " @", round(analyte.rt, digits = 2), " MW=", round(mw(analyte), digits = 4))
 Base.show(io::IO, transition::TransitionID) = print(io, transition.compound, transition.quantifier ? "" : " (qualifier)")
 
-function Base.show(io::IO, data::PreIS)
- println(io, "PreIS with $(length(data.mz2)) products: ")
+Base.show(io::IO, data::PreIS) = print(io, "PreIS in ", data.polarity ? "positive" : "negative", " ion mode with $(length(data.mz2)) products")
+function Base.show(io::IO, ::MIME"text/plain", data::PreIS)
+ print(io, data, ":\n")
  for dt in zip(data.range, data.mz2)
  println(io, " ", dt[1], " -> ", round(dt[2]; digits = 4))
  end
 end
 
-function Base.show(io::IO, pj::Project)
- println(io, "Project with ", length(pj), " analytes:")
+Base.show(io::IO, data::MRM) = print(io, "MRM in ", data.polarity ? "positive" : "negative", " ion mode with $(length(data.mz2)) products")
+function Base.show(io::IO, ::MIME"text/plain", data::MRM)
+ print(io, data, ":\n")
+ for (i, m) in enumerate(data.mz2)
+ v = @view data.table.mz1[data.table.mz2_id == i]
+ v = length(v) > 10 ? string(join(round.(v[1:5]; digits = 4), ", "), ", ..., ", join(round.(v[end - 4:end]; digits = 4))) : join(round.(v; digits = 4), ", ")
+ println(io, " ", v, " -> ", round(m; digits = 4))
+ end
+end
+
+Base.show(io::IO, data::QuantData{T}) where T = print(io, "QuantData{$T} ", data.raw)
+function Base.show(io::IO, ::MIME"text/plain", data::QuantData{T}) where T 
+ print(io, data, ":\n")
+ show(io, MIME"text/plain"(), data.table)
+end
+Base.show(io::IO, data::QCData{T}) where T = print(io, "QCData{$T} ", data.raw)
+function Base.show(io::IO, ::MIME"text/plain", data::QCData{T}) where T 
+ print(io, data, ":\n")
+ show(io, MIME"text/plain"(), qualitytable(data))
+end
+Base.show(io::IO, data::SerialDilution{T}) where T = print(io, "SerialDilution{$T} ", data.raw)
+function Base.show(io::IO, ::MIME"text/plain", data::SerialDilution{T}) where T 
+ print(io, data, ":\n")
+ show(io, MIME"text/plain"(), qualitytable(data))
+end
+Base.show(io::IO, qt::Quantification) = print(io, "Quantification")
+function Base.show(io::IO, ::MIME"text/plain", qt::Quantification)
+ print(io, qt, ":\n")
+ show(io, MIME"text/plain"(), qt.batch)
+end
+Base.show(io::IO, rtcor::RTCorrection) = print(io, "RTCorrection")
+function Base.show(io::IO, ::MIME"text/plain", rtcor::RTCorrection)
+ print(io, rtcor, ":\n")
+ show(io, MIME"text/plain"(), rtcor.fn)
+end
+
+Base.show(io::IO, pj::Project) = print(io, "Project with ", length(pj), " analytes")
+function Base.show(io::IO, ::MIME"text/plain", pj::Project)
+ print(io, pj, ":\n")
  println(io, "∘ Salt: ", get(pj.appendix, :anion, "unknown"))
  println(io, "∘ Signal: ", get(pj.appendix, :signal, "unknown"))
  println(io, "∘ Data: ")
  for data in pj.data
- show(io, data)
+ show(io, MIME"text/plain"(), data)
  end
  print(io, "∘ Analytes: ")
  if length(pj) > 10

src/rt.jl

@@ -149,7 +149,7 @@ end
  @model(expr)
  @model(expr...)
 
-Create function(s) taking data as input and return a regression model.
+Create function(s) taking data as input and returning a regression model.
  
 # Arguuments
 * `()` or no input represent current model, i.e., `preject.appendix[:model_formula]`.
@@ -321,16 +321,19 @@ end
  apply_rt!(aquery::AbstractQuery; kwargs...)
  apply_rt!(project::Project; analyte = project.analyte, atol = 0.25, rtol = 0.05)
 
-Apply rt prediction to each analyte. `analyte.state[state_id(:rt)]` is set as `1` if the prediction error is under certain value; `-1` if the prediction error is too large; `0` if there is no prediction can be made. Prediction is based on `project.appendix[:rt_model]`.
+Apply rt prediction to each analyte. `analyte.state[state_id(:rt)]` is set as `1` if the prediction error is under certain value; `-1` if the prediction error is too large; `0` if there is no prediction can be made. 
+Prediction is based on `project.appendix[:rt_model]`. `atol` and `rtol` can be a number or a function taking `analyte` as input and returning a number.
 """
 apply_rt!(aquery::AbstractQuery; kwargs...) = (apply_rt!(aquery.project; analyte = aquery.result, kwargs...); aquery)
 function apply_rt!(project::Project; analyte = project.analyte, atol = 0.5, rtol = 0.05)
+ atol_fn = atol isa Number ? (x -> atol) : atol
+ rtol_fn = rtol isa Number ? (x -> rtol) : rtol
  tbl = Table(; (project.appendix[:rt_model].fn.nmterms .=> map(x -> eval(x).(analyte), project.appendix[:rt_model].fn.fnterms))...)
  include_id = find_predictable(project.appendix[:rt_model].model, tbl)
  ŷ = predict(project.appendix[:rt_model].model, tbl[include_id])
  y = @view getproperty(tbl, first(propertynames(tbl)))[include_id]
  for (v, v̂, ana) in zip(y, ŷ, view(analyte, include_id))
- ana.state[state_id(:rt)] = (abs(v - v̂) < atol || abs(v - v̂) / v < rtol) ? 1 : -1
+ ana.state[state_id(:rt)] = (abs(v - v̂) < atol_fn(ana) || abs(v - v̂) / v < rtol_fn(ana)) ? 1 : -1
  end
  project
 end