1 files changed, 26 insertions, 16 deletions
diff --git a/analysis/vis.livemd b/analysis/vis.livemd
index f4b2ca6..727a459 100644
--- a/analysis/vis.livemd
+++ b/analysis/vis.livemd
@@ -6,7 +6,10 @@ Mix.install([
   {:kino_vega_lite, "~> 0.1.8"},
   {:json, "~> 1.4"},
   {:explorer, "~> 0.8.0"},
-  {:kino_explorer, "~> 0.1.11"}
+  {:kino_explorer, "~> 0.1.11"},
+  {:nx, "~> 0.5"},
+  {:scholar, "~> 0.2.1"},
+  {:math, "~> 0.7.0"}
 ])
 ```
 
@@ -17,7 +20,7 @@ require Explorer.DataFrame
 require Explorer.Series
 alias Explorer.DataFrame, as: DF
 alias Explorer.Series, as: SE
-job_id = "1177"
+job_id = "other"
 job_dir = Path.expand(~c"./" ++ job_id) |> Path.absname()
 sections_dir = Path.join(job_dir, "sections")
 cm_dir = Path.join([job_dir, "candelabra", "benchmark_results"])
@@ -93,9 +96,9 @@ cost_models
 ## Cost model exploratory plots
 
 ```elixir
-startn = 0
-endn = 60_000
-resolution = 100
+startn = 200
+endn = 2000
+resolution = 50
 
 points_for = fn impl, op ->
   %{"coeffs" => [coeffs]} =
@@ -103,16 +106,18 @@ points_for = fn impl, op ->
     |> DF.to_columns()
 
   Enum.map(startn..endn//resolution, fn n ->
+    t =
+      (coeffs
+       |> Enum.take(3)
+       |> Enum.with_index()
+       |> Enum.map(fn {coeff, idx} -> coeff * n ** idx end)
+       |> Enum.sum()) + Enum.at(coeffs, 3) * Math.log2(n)
+
     %{
       impl: String.split(impl, "::") |> List.last(),
       op: op,
       n: n,
-      t:
-        coeffs
-        |> Enum.with_index()
-        |> Enum.map(fn {coeff, idx} -> coeff * n ** idx end)
-        |> Enum.sum()
-        |> max(0)
+      t: t
     }
   end)
   |> DF.new()
@@ -123,6 +128,7 @@ end
 
 ```elixir
 inspect_op = "insert"
+impls = ["BTreeSet", "EagerSortedVec", "EagerUniqueVec", "HashSet"]
 
 Tucan.layers([
   cost_models
@@ -131,19 +137,23 @@ Tucan.layers([
   |> 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),
+  |> DF.filter(impl in ^impls)
+  |> Tucan.lineplot("n", "t", color_by: "impl", clip: true),
+  # |> Tucan.Scale.set_y_domain(0, 200)
   Tucan.scatter(
     cost_model_points
-    |> DF.filter(op == ^inspect_op)
-    |> DF.group_by(["impl", "n"])
-    |> DF.summarise(t: mean(t)),
+    |> DF.filter(op == ^inspect_op and impl in ^impls)
+    |> DF.group_by(["impl", "n"]),
+    # |> DF.summarise(t: mean(t)),
     "n",
     "t",
     color_by: "impl",
     clip: true
   )
 ])
+|> Tucan.Scale.set_x_domain(startn, endn)
+|> Tucan.Scale.set_y_domain(0, 200)
+|> Tucan.set_size(500, 500)
 ```
 
 ## Read benchmark data