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# Dissertation Visualisations
```elixir
Mix.install([
{:tucan, "~> 0.3.0"},
{:kino_vega_lite, "~> 0.1.8"},
{:json, "~> 1.4"},
{:explorer, "~> 0.8.0"},
{:kino_explorer, "~> 0.1.11"}
])
```
## Variables
```elixir
require Explorer.DataFrame
require Explorer.Series
alias Explorer.DataFrame, as: DF
alias Explorer.Series, as: SE
job_id = "1147"
job_dir = Path.expand(~c"./" ++ job_id) |> Path.absname()
sections_dir = Path.join(job_dir, "sections")
criterion_dir = Path.join(job_dir, "criterion")
```
## Read cost model data
```elixir
{:ok, cost_model_files} = File.ls(sections_dir)
cost_model_files =
cost_model_files
|> Enum.filter(fn name -> String.contains?(name, "cost-model") end)
|> Enum.map(fn fname -> Path.join(sections_dir, fname) |> Path.absname() end)
cost_model_files
```
<!-- livebook:{"reevaluate_automatically":true} -->
```elixir
# Parse cost model information
cost_models =
cost_model_files
|> Enum.map(fn fname ->
{:ok, contents} = File.read(fname)
[_, table | _] = String.split(contents, "line\n")
[rows | _] = String.split(table, "\n\\end")
rows = String.split(rows, "\n")
[_, impl] = String.split(fname, "cost-model-")
impl = String.replace(impl, "-", ":")
rows
|> Enum.map(fn row ->
[name, x0, x1, x2, x3, nmrse] = String.split(row, " & ")
[nmrse | _] = String.split(nmrse)
%{
op: name,
x0: String.to_float(x0),
x1: String.to_float(x1),
x2: String.to_float(x2),
x3: String.to_float(x3),
nmrse: String.to_float(nmrse)
}
end)
|> Enum.map(fn d -> d |> Map.put(:impl, impl) end)
|> DF.new()
end)
|> DF.concat_rows()
```
```elixir
Tucan.histogram(cost_models, "nmrse")
```
```elixir
cost_models
|> DF.filter(op == "contains")
```
## Cost model exploratory plots
```elixir
startn = 0
endn = 200_000
resolution = 100
points_for = fn impl, op ->
%{"x0" => [x0], "x1" => [x1], "x2" => [x2], "x3" => [x3]} =
DF.filter(cost_models, impl == ^impl and op == ^op)
|> DF.to_columns()
Enum.map(startn..endn//resolution, fn n ->
%{
impl: String.split(impl, "::") |> List.last(),
op: op,
n: n,
t: x0 + n * x1 + n * n * x2 + n * n * n * x3
}
end)
|> DF.new()
end
```
<!-- livebook:{"reevaluate_automatically":true} -->
```elixir
inspect_op = "contains"
cost_models
|> DF.filter(op == ^inspect_op)
|> DF.distinct(["impl"])
|> DF.to_rows()
|> Enum.map(fn %{"impl" => impl} -> points_for.(impl, inspect_op) end)
|> DF.concat_rows()
|> Tucan.lineplot("n", "t", color_by: "impl", clip: true)
|> Tucan.Scale.set_y_domain(0, 200)
```
## Read benchmark data
```elixir
benchmarks =
File.ls!(criterion_dir)
|> Enum.map(fn name ->
File.ls!(Path.join(criterion_dir, name))
|> Enum.map(fn p -> %{bench: name, subbench: p} end)
end)
|> List.flatten()
|> Enum.map(fn %{bench: bench, subbench: subbench} ->
File.ls!(Path.join([criterion_dir, bench, subbench]))
|> Enum.filter(fn x -> String.contains?(x, "Mapping2D") end)
|> Enum.map(fn x -> Path.join([criterion_dir, bench, subbench, x]) end)
|> Enum.map(fn dir ->
raw_results =
Path.join(dir, "estimates.json")
|> File.read!()
|> JSON.decode!()
%{
bench_id: bench <> "/" <> subbench,
using:
Regex.scan(~r/\"(\w*)\", ([\w:]*)/, Path.basename(dir))
|> Enum.map(fn [_, ctn, impl] -> %{ctn: ctn, impl: impl} end),
mean: raw_results["mean"]["point_estimate"] / 10 ** 9
}
end)
end)
|> List.flatten()
|> DF.new()
```
```elixir
# Cost estimates by project, ctn, and implementation
projs =
benchmarks["bench_id"]
|> SE.split("-")
|> SE.transform(&hd/1)
|> SE.split("/")
|> SE.transform(&hd/1)
benchmarks = DF.put(benchmarks, "proj", projs)
cost_estimates =
SE.transform(projs |> SE.distinct(), fn proj_name ->
[_, table | _] =
Path.join(sections_dir, "compare-" <> proj_name)
|> File.read!()
|> String.split("& file \\\\\n\\hline\n")
table
|> String.split("\n\\end{tabular}")
|> hd
|> String.split("\n")
|> Enum.map(fn x -> String.split(x, " & ") end)
|> Enum.map(fn [ctn, impl, cost | _] ->
%{
proj: proj_name,
ctn: ctn,
impl:
impl
|> String.replace("\\_", "_"),
cost:
if String.contains?(cost, ".") do
String.to_float(cost)
else
String.to_integer(cost)
end
}
end)
end)
|> SE.to_list()
|> List.flatten()
|> DF.new()
```
```elixir
# Get cost of assignment from cost estimates
cost_of_assignment = fn proj, assignment ->
assignment
|> Enum.map(fn %{"ctn" => ctn, "impl" => impl} ->
DF.filter(cost_estimates, proj == ^proj and ctn == ^ctn and impl == ^impl)["cost"][0]
end)
|> Enum.sum()
end
cost_of_assignment.("example_stack", [%{"ctn" => "StackCon", "impl" => "std::vec::Vec"}])
```
```elixir
# Estimate cost for each benchmarked assignment
estimated_costs =
benchmarks
|> DF.to_rows_stream()
# TODO
|> Enum.filter(fn %{"proj" => proj} -> String.contains?(proj, "example") end)
|> Enum.map(fn %{"bench_id" => bench_id, "proj" => proj, "using" => using} ->
%{
bench_id: bench_id,
using: using,
estimated_cost: cost_of_assignment.(proj, using)
}
end)
|> DF.new()
```
```elixir
# Compare each assignments position in the estimates to its position in the results
sorted_estimates =
estimated_costs
|> DF.group_by(["bench_id"])
|> DF.sort_by(estimated_cost)
sorted_results =
benchmarks
|> DF.group_by(["bench_id"])
|> DF.sort_by(mean)
position_comparison =
sorted_estimates
|> DF.to_rows_stream()
|> Enum.map(fn %{"bench_id" => bench_id, "using" => using} ->
%{
bench_id: bench_id,
using: using,
pos_estimate:
DF.filter(sorted_estimates, bench_id == ^bench_id)["using"]
|> SE.to_list()
|> Enum.find_index(fn u -> u == using end),
pos_results:
DF.filter(sorted_results, bench_id == ^bench_id)["using"]
|> SE.to_list()
|> Enum.find_index(fn u -> u == using end)
}
end)
|> DF.new()
```
```elixir
position_comparison
|> DF.filter(pos_estimate != pos_results)
|> DF.collect()
```
<!-- livebook:{"reevaluate_automatically":true} -->
```elixir
# Difference in execution time between worst and best selection
Tucan.bar(
benchmarks
|> DF.group_by("bench_id")
|> DF.summarise(range: max(mean) - min(mean)),
"bench_id",
"range",
orient: :horizontal,
clip: true
)
|> Tucan.Scale.set_x_domain(0, 5)
```
|