Muonscanfit

src/hits.jl

@@ -41,10 +41,6 @@ HitL1(m::DetectorModule, hits) = HitL1(m.id, hits)
 HitL2(m::DetectorModule, hits) = HitL2(m.id, hits)
 Base.length(c::AbstractCoincidenceHit) = length(c.hits)
 Base.eltype(c::AbstractCoincidenceHit) = HitL0
-function Base.show(io::IO, c::AbstractCoincidenceHit)
-    times = [time(h) for h in c]
-    print(io, "$(c.dom_id) $(minimum(times)) $(length(c))")
-end
 function Base.iterate(c::AbstractCoincidenceHit, state=1)
     @inbounds state > length(c) ? nothing : (c.hits[state], state+1)
 end
@@ -66,11 +62,11 @@ struct HitR1 <: AbstractReducedHit
 end
 Base.isless(lhs::HitR1, rhs::HitR1) = lhs.dom_id == rhs.dom_id ? time(lhs) < time(rhs) : lhs.dom_id < rhs.dom_id
 const HitR2 = HitR1
-function HitR1(m::DetectorModule, hits::Vector{HitL0})
+function HitR1(dom_id::Integer, hits::Vector{HitL0})
     combined_hit = combine(hits)
     h = first(hits)
     count = weight = length(hits)
-    HitR1(m.id, h.pos, combined_hit.t, combined_hit.tot, count, weight)
+    HitR1(dom_id, h.pos, combined_hit.t, combined_hit.tot, count, weight)
 end
 # function HitR1(m::DetectorModule, hit::HitL1)
 #     count = weight = length(hit)
@@ -292,16 +288,16 @@ end
 """
 Calibrates hits.
 """
-function calibrate(T::Type{HitR1}, det::Detector, hits)
+function KM3io.calibrate(T::Type{HitR1}, det::Detector, hits)
     rhits = sizehint!(Vector{T}(), length(hits))
     for hit ∈ hits
         pmt = det[hit.dom_id][hit.channel_id]
         t = hit.t + pmt.t₀
-        push!(rhits, T(hit.dom_id, pmt.pos, Hit(t, hit.tot)))
+        push!(rhits, T(hit.dom_id, pmt.pos, t, hit.tot, 1, 0))
     end
     rhits
 end
-function calibrate(T::Type{HitL0}, m::DetectorModule, hits)
+function KM3io.calibrate(T::Type{HitL0}, m::DetectorModule, hits)
     chits = sizehint!(Vector{T}(), length(hits))
     for hit ∈ hits
         pmt = m[hit.channel_id]
@@ -377,7 +373,7 @@ function _findL1!(out::Vector{H}, m::DetectorModule, hits, Δt, combine::Bool) w
                 if ref_idx != end_idx
                     coincident_hits = [chits[i] for i ∈ ref_idx:end_idx]
                     # push!(out, H(m, HitL1(m.id, coincident_hits)))
-                    push!(out, H(m, coincident_hits))
+                    push!(out, H(m.id, coincident_hits))
                     if combine
                         ref_idx = end_idx
                     end
@@ -550,12 +546,12 @@ function (m::Match1D)(hit1, hit2)
 
       x = hit1.pos.x - hit2.pos.x
       y = hit1.pos.y - hit2.pos.y
-      d = √(m.x*m.x + m.y*m.y);
+      d = √(x^2 + y^2)
 
-      if m.d <= 0.5 * m.roadwidth
-          return m.t <=  m.d  * KM3io.Constants.TAN_THETA_C_WATER * KM3io.Constants.C_INVERSE  +  m.tmaxextra
-      elseif m.d <= m.roadwidth
-          return m.t <= (m.roadwidth - m.d) * KM3io.Constants.TAN_THETA_C_WATER * KM3io.Constants.C_INVERSE  +  m.tmaxextra
+      if d <= 0.5 * m.roadwidth
+          return m.t <=  d  * KM3io.Constants.TAN_THETA_C_WATER * KM3io.Constants.C_INVERSE  +  m.tmaxextra
+      elseif d <= m.roadwidth
+          return m.t <= (m.roadwidth - d) * KM3io.Constants.TAN_THETA_C_WATER * KM3io.Constants.C_INVERSE  +  m.tmaxextra
       end
 
       false
@@ -570,7 +566,7 @@ end
 Clique clusterizer which takes a matcher algorithm like `Match3B` as input.
 """
 struct Clique{T<:AbstractMatcher}
-    m::T
+    match::T
     weights::Vector{Float64}
     Clique(m::T) where T = new{T}(m, Float64[])
 end
@@ -592,7 +588,7 @@ function clusterize!(hits::Vector{T}, c::Clique) where T<:AbstractSpecialHit
     @inbounds for i ∈ 1:N
         @inbounds for j ∈ i:N
             j == i && continue
-            if c.m(hits[i], hits[j])
+            if c.match(hits[i], hits[j])
                 c.weights[i] += weight(hits[j])
                 c.weights[j] += weight(hits[i])
             end
@@ -626,7 +622,7 @@ function clusterize!(hits::Vector{T}, c::Clique) where T<:AbstractSpecialHit
         # Decrease weight of associated hits for each associated hit.
         @inbounds for i ∈ 1:n
             c.weights[n] <= weight(hits[n]) && break
-            if c.m(hits[i], hits[n])
+            if c.match(hits[i], hits[n])
                 c.weights[i] -= weight(hits[n])
                 c.weights[n] -= weight(hits[i])
             end