update(examples): skew_stats (change bin width, add skew time dependency analysis)

This commit is contained in:
Wataru Otsubo 2024-12-13 19:28:59 +09:00
parent ece30043c9
commit 9ca974405e
3 changed files with 497 additions and 62 deletions

View file

@ -17,11 +17,13 @@ begin
using PSBoardDataBase
using SQLite
using DataFrames
using FHist
using DBInterface
using Tables
using CairoMakie
using Statistics
using PlutoUI
using Dates
using Random
using Printf
end
@ -70,7 +72,11 @@ md"""
"""
# ╔═╡ f379d43c-9300-41f4-b0fc-3c9d749e3105
qaqc_runs = DBInterface.execute(db, sql"select * from qaqc_runs") |> DataFrame
qaqc_runs = let df
df = DBInterface.execute(db, sql"select * from qaqc_runs") |> DataFrame
transform!(df, :run_datetime => ByRow(passmissing(s -> DateTime(s))) => :run_datetime)
df
end
# ╔═╡ 33e099bc-ac4b-4b5f-88e7-20f4463c98ef
md"""
@ -103,7 +109,7 @@ clk_files =
filter(endswith("_clk.txt")) |>
filter(!contains("nagoya")) |>
filter(!contains("630_190")) |>
filter(!contains("627_344"))
filter(!contains("627_344"))
# ╔═╡ 3e5607fd-2a8a-4a1a-9e7b-3f23ef216fad
"""
@ -180,7 +186,7 @@ let
title = "skews of all measurements (n_meas = $(length(skews)), n_psb = $(npsbid))",
xlabel = "skew / ns",
)
stephist!(ax, skews, bins = range(minimum(skews), maximum(skews), step = 1 / 57))
stephist!(ax, skews, bins = range(minimum(skews), maximum(skews), step = 1 / 56))
fig
end
@ -192,7 +198,7 @@ md"""
# ╔═╡ 420dce0e-4757-48d9-84ec-7ddfac2fdff6
let
skew_widths = df_skews.width |> skipmissing |> collect
bins = range(0, maximum(skew_widths) + 1 / 57, step = 1 / 57)# .- 0.01
bins = range(0, maximum(skew_widths) + 1 / 56, step = 1 / 56)# .- 0.01
hist(
skew_widths,
bins = bins,
@ -211,13 +217,61 @@ let
end
# ╔═╡ 99902640-fee3-4502-9c7e-cb08834bad0b
maximum(skipmissing(df_skews.width)) / (1 / 57)
maximum(skipmissing(df_skews.width)) / (1 / 56)
# ╔═╡ c79c6684-1b03-41b5-aa90-ef8c7a8eb69c
md"""
この結果を元に、クロック試験のしきい値は$(round(9 * 1 / 57; digits = 2))ns以上に設定
この結果を元に、クロック試験のしきい値は$(round(9 * 1 / 56; digits = 2))ns以上に設定
"""
# ╔═╡ a1056aba-e484-4594-908b-4709896d0da0
let
fig = Figure()
ax = Axis(
fig[1, 1],
limits = ((-0.5, 1), nothing),
title = "turn on curves for PSBID 1166",
xlabel = "delay / ns (position dependency is removed)",
ylabel = "counts",
)
clk_files_1166 = filter(clk_files) do filename
psbid, runid = parse_filename(filename)
psbid == 1166
end
for clk_file in clk_files_1166
psbid, runid = parse_filename(clk_file)
single_runs = filter(
[:psboard_id, :runid] => (
(ref_psbid, ref_runid) -> begin
psbid == ref_psbid && runid == ref_runid
end
),
qaqc_single_results,
)
offset_pos = let
qaqc_positions.rising_ns[single_runs.position[1]]
end
points =
eachline(clk_file) .|>
PSBoardDataBase.ClockParser._parse_line .|>
(x -> (x[1] - offset_pos, x[2]))
@info "" single_runs points
stds = map(points) do ((time, count))
sqrt(count * (1000 - count) / 1000)
end
scatterlines!(ax, points, label = "psbid $(psbid), runid $(runid)")
errorbars!(ax, points, stds)
end
axislegend(ax, position = :rb)
fig
end
# ╔═╡ 875bec26-e576-4f48-ba14-464bce503d75
filter(:width => (x -> ismissing(x) || x < 0.06), df_skews)
@ -239,11 +293,15 @@ md"""
combine(filter(groupby(qaqc_single_results, [:psboard_id, :position])) do sdf
nrow(dropmissing(sdf, [:lvds_tx_skew])) > 1
end) do sdf
sdf = dropmissing(sdf, [:lvds_tx_skew])
# @info "" select(sdf, [:psboard_id, :position, :lvds_tx_skew])
(skew_mean = mean(sdf.lvds_tx_skew), skew_std = std(sdf.lvds_tx_skew), nrow = nrow(sdf))
end |> (df -> begin
filter(:skew_std => >(0.5), df)
sdf = dropmissing(sdf, [:lvds_tx_skew])
# @info "" select(sdf, [:psboard_id, :position, :lvds_tx_skew])
(
skew_mean = mean(sdf.lvds_tx_skew),
skew_std = std(sdf.lvds_tx_skew),
nrow = nrow(sdf),
)
end |> (df -> begin
filter(:skew_std => >(0.5), df)
end)
# ╔═╡ 25688d24-5aee-43d3-aff9-b9efa0556070
@ -418,57 +476,70 @@ md"""
"""
# ╔═╡ 38d472ca-6347-4096-828d-fd1256130a59
df_skews_selected = combine(
gdf_skews_on_psbid,
sdf -> begin
all(ismissing, sdf.skew) && @info "" sdf
if nrow(sdf) == 1
@assert sdf.skew |> first |> !ismissing
(
skew = sdf.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
)
else
if sdf.psbid[1] == 291
df = filter(:runid => ==(94), sdf)
@assert nrow(df) == 1
df_skews_selected = let df
df = combine(
gdf_skews_on_psbid,
sdf -> begin
all(ismissing, sdf.skew) && @info "" sdf
if nrow(sdf) == 1
@assert sdf.skew |> first |> !ismissing
(
skew = df.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
)
elseif sdf.psbid[1] == 460
df = filter(:runid => ==(132), sdf)
@assert nrow(df) == 1
(
skew = df.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
)
elseif sdf.psbid[1] == 545
df = filter(:runid => ==(132), sdf)
@assert nrow(df) == 1
(
skew = df.skew |> first,
skew = sdf.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
runid = sdf.runid |> first,
)
else
# assume that runid is chronological
i = argmax(sdf.runid .|> (id -> ismissing(id) ? -1 : id))
(skew = sdf.skew[i], width = sdf.width[i], riseup = sdf.riseup[i])
if sdf.psbid[1] == 291
df = filter(:runid => ==(94), sdf)
@assert nrow(df) == 1
(
skew = df.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
runid = sdf.runid |> first,
)
elseif sdf.psbid[1] == 460
df = filter(:runid => ==(132), sdf)
@assert nrow(df) == 1
(
skew = df.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
runid = sdf.runid |> first,
)
elseif sdf.psbid[1] == 545
df = filter(:runid => ==(132), sdf)
@assert nrow(df) == 1
(
skew = df.skew |> first,
width = sdf.width |> first,
riseup = sdf.riseup |> first,
runid = sdf.runid |> first,
)
else
# assume that runid is chronological
i = argmax(sdf.runid .|> (id -> ismissing(id) ? -1 : id))
(
skew = sdf.skew[i],
width = sdf.width[i],
riseup = sdf.riseup[i],
runid = sdf.runid[1],
)
end
end
end
end,
)
end,
)
leftjoin!(df, select(qaqc_runs, [:id, :campaign_id]), on = :runid => :id)
df
end
# ╔═╡ 310710da-ebb2-4f54-b238-38d493a6a533
let
skews = df_skews_selected.skew |> skipmissing |> collect
fig = Figure()
ax = Axis(fig[1, 1], title = "skews (n = $(length(skews)))", xlabel = "skew / ns")
stephist!(ax, skews, bins = range(minimum(skews), maximum(skews), step = 1 / 57))
stephist!(ax, skews, bins = range(minimum(skews), maximum(skews), step = 1 / 56))
fig
end
@ -530,7 +601,7 @@ md"""
# ╔═╡ 939aba6b-b03c-42b6-83b3-9cea5f4eb858
let
skew_widths = df_skews_selected.width |> skipmissing |> collect
bins = range(0, maximum(skew_widths), step = 1 / 57)# .- 0.01
bins = range(0, maximum(skew_widths), step = 1 / 56)# .- 0.01
hist(
skew_widths,
bins = bins,
@ -551,6 +622,221 @@ end
# ╔═╡ aa9b78bc-8d66-4df2-bd06-1cbf21190488
filter(:width => (x -> ismissing(x) || x < 0.06), df_skews_selected)
# ╔═╡ 76f44129-34c6-451d-af3f-4593dd1dda5c
md"""
## skewの時間依存性
以下のrun
- 382: ファームウェア最新
"""
# ╔═╡ 446a1b05-b24a-46d8-94a1-bd449245075d
df_extra_measurements = let
df_configs = DataFrame(
position_name = ["B-$(i)-$(j)" for j in 1:9 for i in 0:1],
psbid = [
001142,
000973,
000990,
000992,
001113,
001030,
001121,
001141,
001050,
001053,
001110,
001248,
001242,
001276,
000872,
000861,
000525,
000862,
],
position = [1, 10, 2, 11, 3, 12, 4, 13, 5, 14, 6, 15, 7, 16, 8, 17, 9, 18],
)
transform!(
df_configs,
[:psbid, :position] =>
ByRow(
(psbid, position) -> begin
runid = 382
clkfile = "../test/input/slavelogs/main/$(psbid)_$(runid)_clk.txt"
skew, width =
PSBoardDataBase.ClockParser.get_skew_and_riseup(clkfile)
offset = qaqc_positions.rising_ns[findfirst(
==(position),
qaqc_positions.id,
)]
[skew - offset, width]
end,
) => [:skew, :width],
)
end
# ╔═╡ 148e42fc-d168-4e07-b4f8-f9c3f8c18efc
df_compare = let
df_old_measurements =
filter(:psbid => in(df_extra_measurements.psbid), df_skews_selected)
df_combined = leftjoin!(
df_old_measurements,
df_extra_measurements,
on = :psbid,
makeunique = true,
)
rename!(
df_combined,
:skew => :skew_old,
:width => :width_old,
:runid => :runid_old,
:campaign_id => :campaign_id_old,
:skew_1 => :skew_new,
:width_1 => :width_new,
)
select!(
df_combined,
[
:psbid,
:runid_old,
:campaign_id_old,
:skew_old,
:width_old,
:skew_new,
:width_new,
],
)
dropmissing!(df_combined)
end
# ╔═╡ 3266d1fd-b8f0-4eb0-9a8e-2050bc9a626f
let
fig = Figure(size = (600, 500))
grd1 = fig[1, 1] = GridLayout()
Label(grd1[0, 1:2], "skew firmware dependency", tellwidth = false)
ax1 = Axis(
grd1[1, 1],
limits = ((-0.15, 1.15), nothing),
xticks = (0:1, ["old", "new(382)"]),
ylabel = "skew / ns",
)
ax2 = Axis(
grd1[1:2, 2],
limits = ((2.9, 6.7), nothing),
ylabel = "Δskew / ns",
# xgridvisible = false,
# xticksvisible = false,
# xticklabelsvisible = false,
xticks = (3:6, string.(3:6)),
xlabel = "campaign",
yminorticksvisible = true,
yminorgridvisible = true,
)
colsize!(grd1, 2, Relative(0.4))
for row in eachrow(df_compare)
scatterlines!(
ax1,
0:1,
[row.skew_old, row.skew_new],
color = Makie.wong_colors()[row.campaign_id_old],
)
scatter!(
ax2,
row.campaign_id_old,
row.skew_new - row.skew_old,
marker = :x,
color = Makie.wong_colors()[row.campaign_id_old],
alpha = 0.7,
)
end
text!(
ax1,
fill(1, nrow(df_compare)),
df_compare.skew_new,
text = string.(df_compare.psbid),
color = (:black, 0.5),
align = (:left, :center),
)
text!(
ax2,
df_compare.campaign_id_old,
df_compare.skew_new .- df_compare.skew_old,
text = string.(df_compare.psbid),
color = (:black, 0.5),
align = (:left, :center),
# fontsize = 17,
)
campaigns = df_compare.campaign_id_old |> unique |> sort!
Legend(
grd1[2, 1],
[
[LineElement(color = color), MarkerElement(color = color, marker = :circle)] for
color in Makie.wong_colors()[campaigns]
],
string.(campaigns),
"campaign id for old measurements",
orientation = :horizontal,
)
fig
end
# ╔═╡ 660f2bd1-d4bc-45a8-9cf6-4e875aa9f7a2
let
df = filter(:campaign_id => ==(6), df_skews_selected)
leftjoin!(df, select(qaqc_runs, [:id, :run_datetime]), on = :runid => :id)
# from UTC to JST(+9h)
transform!(df, :run_datetime => ByRow(dt -> dt + Hour(9)) => :run_datetime)
@assert all(!ismissing, df.run_datetime)
dropmissing!(df, :run_datetime)
transform!(df, :run_datetime => ByRow(Date) => :run_date)
fig = Figure()
gdf = groupby(df, :run_date)
for (i, sdf) in enumerate(gdf)
unit_converter = Makie.DateTimeConversion(Time)
ax = Axis(
fig[i, 1],
title = string(keys(gdf)[i]),
dim1_conversion = unit_converter,
limits = (
(
Makie.convert_dim_value(unit_converter, Time(9)),
Makie.convert_dim_value(unit_converter, Time(20)),
),
(-2, 1),
),
)
scatter!(ax, sdf.run_datetime .|> Time, sdf.skew, markersize = 7, alpha = 0.7)
mean_runs = Union{Float64, Missing}[]
std_runs = Union{Float64, Missing}[]
datetime_runs = Time[]
for sdf_samerun in groupby(sdf, :runid)
push!(mean_runs, mean(sdf_samerun.skew |> skipmissing))
push!(std_runs, std(sdf_samerun.skew |> skipmissing))
push!(datetime_runs, sdf_samerun.run_datetime |> first)
end
@info "" mean_runs std_runs datetime_runs
scatterlines!(
ax,
datetime_runs,
mean_runs,
marker = :hline,
markersize = 10,
color = Makie.wong_colors()[2],
)
errorbars!(
ax,
datetime_runs,
mean_runs,
std_runs,
color = Makie.wong_colors()[2],
)
end
fig
end
# ╔═╡ 86437ee6-ccea-43fa-bd93-d86fe055f28d
md"""
# プロットまとめ
@ -569,6 +855,12 @@ df_skews_selected_valids = let
df
end
# ╔═╡ 2dde2b39-8f8c-473b-8fed-393a9e3286d8
sort(df_skews_selected_valids, :skew)
# ╔═╡ 2a579bc2-79f8-4773-8588-a413acb8a6d6
sort(df_skews_selected_valids, :skew, rev = true)
# ╔═╡ cf658de8-a4c5-413e-b5e3-56b77a80336f
sort(df_skews_selected, :width)
@ -582,12 +874,17 @@ begin
@assert all(==(1), df_skews_selected_valids.riseup)
end
# ╔═╡ 92d701aa-ab90-4c91-977d-2ce92823d130
md"""
## skew分布
"""
# ╔═╡ 4a4ef945-b312-44ed-ab62-ce01fc33f926
let
bins = range(
minimum(df_skews_selected_valids.skew) - 5 / 57,
maximum(df_skews_selected_valids.skew) + 5 / 57,
step = 2 / 57,
minimum(df_skews_selected_valids.skew) - 5 / 56,
maximum(df_skews_selected_valids.skew) + 5 / 56,
step = 2 / 56,
)
fig = Figure()
ax = Axis(
@ -615,15 +912,92 @@ let
fig
end
# ╔═╡ 82063c4b-c0cf-4524-83fe-5207bb8363d8
md"""
### skew分布のcampaign依存性
"""
# ╔═╡ dff359b1-4827-40c6-86e4-0915974ef27d
let
bins = range(
minimum(df_skews_selected_valids.skew) - 5 / 56,
maximum(df_skews_selected_valids.skew) + 5 / 56,
step = 8 / 56,
)
fig = Figure()
ax = Axis(
fig[1, 1],
title = "skews",
limits = (nothing, (nothing, nothing)),
xlabel = "skew / ns",
)
hists = Hist1D[]
for gdf in groupby(df_skews_selected_valids, :campaign_id)
push!(hists, Hist1D(gdf.skew, binedges = bins))
end
sh1 = stackedhist!(ax, hists, error_color = Pattern('/'))
labels = ["campaign $i" for i in 1:6]
elements =
[PolyElement(polycolor = sh1.attributes.color[][i]) for i in 1:length(labels)]
Legend(
fig[1, 1],
elements,
labels,
["""
n = $(nrow(df_skews_selected_valids))
μ = $(@sprintf "%.2g" mean(df_skews_selected_valids.skew))
σ = $(@sprintf "%.2g" std(df_skews_selected_valids.skew))
"""],
tellwidth = false,
tellheight = false,
halign = :left,
valign = :top,
margin = (10, 10, 10, 10),
)
fig
end
# ╔═╡ 7920b03b-1d1a-4b51-bfc0-86d1361f2ff1
let
fig = Figure()
ax = Axis(
fig[1, 1],
xlabel = "psbid",
ylabel = "skew / ns",
title = "clock skew time dependency",
)
scatter!(ax, df_skews_selected_valids.psbid, df_skews_selected_valids.skew)
fig
end
# ╔═╡ e640424b-7f7b-4cca-a634-92749ceee170
let
fig = Figure()
ax = Axis(
fig[1, 1],
xlabel = "runid",
ylabel = "skew / ns",
title = "clock skew time dependency",
)
@info "" qaqc_runs
scatter!(ax, df_skews_selected_valids.runid, df_skews_selected_valids.skew)
fig
end
# ╔═╡ 46b2a3cd-d2e6-4277-8b65-9c61f25f69e8
3 / 57
3 / 56
# ╔═╡ 55bad662-cfdd-45c8-81bf-4e65e5c8434e
md"""
## 立ち上がり時間分布
"""
# ╔═╡ 13bb4978-b98d-44a3-a4b6-4241cadc609b
let
bins = range(
minimum(df_skews_selected_valids.width) - 1 / 57,
maximum(df_skews_selected_valids.width) + 2 / 57,
step = 1 / 57,
minimum(df_skews_selected_valids.width) - 1 / 56,
maximum(df_skews_selected_valids.width) + 2 / 56,
step = 1 / 56,
)
fig = Figure()
ax = Axis(
@ -632,7 +1006,7 @@ let
xlabel = "time / ns",
xticks = (
bins,
string.(round.(bins, digits = 3)),# .* "," .* string.(round.(Int64, bins * 57)),
string.(round.(bins, digits = 3)),# .* "," .* string.(round.(Int64, bins * 56)),
),
xticklabelrotation = π / 3,
)
@ -779,6 +1153,7 @@ end
# ╠═420dce0e-4757-48d9-84ec-7ddfac2fdff6
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