analysis.convex.measure ⟷ Mathlib.Analysis.Convex.Measure

mathlib commit https://github.com/leanprover-community/mathlib/commit/65a1391a0106c9204fe45bc73a039f056558cb83

@@ -43,7 +43,7 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
     exact
       frontier_subset_closure.trans
         (closure_minimal (subset_affineSpan _ _) (affineSpan ℝ s).closed_of_finiteDimensional)
-  rw [← hs.interior_nonempty_iff_affine_span_eq_top] at hspan 
+  rw [← hs.interior_nonempty_iff_affine_span_eq_top] at hspan
   rcases hspan with ⟨x, hx⟩
   /- Without loss of generality, `s` is bounded. Indeed, `∂s ⊆ ⋃ n, ∂(s ∩ ball x (n + 1))`, hence it
     suffices to prove that `∀ n, μ (s ∩ ball x (n + 1)) = 0`; the latter set is bounded.

mathlib commit https://github.com/leanprover-community/mathlib/commit/ce64cd319bb6b3e82f31c2d38e79080d377be451

@@ -3,9 +3,9 @@ Copyright (c) 2022 Yury Kudryashov. All rights reserved.
 Released under Apache 2.0 license as described in the file LICENSE.
 Authors: Yury Kudryashov
 -/
-import Mathbin.Analysis.Convex.Topology
-import Mathbin.Analysis.NormedSpace.AddTorsorBases
-import Mathbin.MeasureTheory.Measure.Lebesgue.EqHaar
+import Analysis.Convex.Topology
+import Analysis.NormedSpace.AddTorsorBases
+import MeasureTheory.Measure.Lebesgue.EqHaar
 
 #align_import analysis.convex.measure from "leanprover-community/mathlib"@"fd4551cfe4b7484b81c2c9ba3405edae27659676"
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/8ea5598db6caeddde6cb734aa179cc2408dbd345

@@ -2,16 +2,13 @@
 Copyright (c) 2022 Yury Kudryashov. All rights reserved.
 Released under Apache 2.0 license as described in the file LICENSE.
 Authors: Yury Kudryashov
-
-! This file was ported from Lean 3 source module analysis.convex.measure
-! leanprover-community/mathlib commit fd4551cfe4b7484b81c2c9ba3405edae27659676
-! Please do not edit these lines, except to modify the commit id
-! if you have ported upstream changes.
 -/
 import Mathbin.Analysis.Convex.Topology
 import Mathbin.Analysis.NormedSpace.AddTorsorBases
 import Mathbin.MeasureTheory.Measure.Lebesgue.EqHaar
 
+#align_import analysis.convex.measure from "leanprover-community/mathlib"@"fd4551cfe4b7484b81c2c9ba3405edae27659676"
+
 /-!
 # Convex sets are null-measurable
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/2fe465deb81bcd7ccafa065bb686888a82f15372

@@ -35,9 +35,9 @@ variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpac
 
 namespace Convex
 
-#print Convex.add_haar_frontier /-
+#print Convex.addHaar_frontier /-
 /-- Haar measure of the frontier of a convex set is zero. -/
-theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
+theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
   by
   /- If `s` is included in a hyperplane, then `frontier s ⊆ closure s` is included in the same
     hyperplane, hence it has measure zero. -/
@@ -95,14 +95,14 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
           _ _ _).mono_left
       nhdsWithin_le_nhds
   simp
-#align convex.add_haar_frontier Convex.add_haar_frontier
+#align convex.add_haar_frontier Convex.addHaar_frontier
 -/
 
 #print Convex.nullMeasurableSet /-
 /-- A convex set in a finite dimensional real vector space is null measurable with respect to an
 additive Haar measure on this space. -/
 protected theorem nullMeasurableSet (hs : Convex ℝ s) : NullMeasurableSet s μ :=
-  nullMeasurableSet_of_null_frontier (hs.add_haar_frontier μ)
+  nullMeasurableSet_of_null_frontier (hs.addHaar_frontier μ)
 #align convex.null_measurable_set Convex.nullMeasurableSet
 -/
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/9fb8964792b4237dac6200193a0d533f1b3f7423

@@ -35,6 +35,7 @@ variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpac
 
 namespace Convex
 
+#print Convex.add_haar_frontier /-
 /-- Haar measure of the frontier of a convex set is zero. -/
 theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
   by
@@ -95,6 +96,7 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
       nhdsWithin_le_nhds
   simp
 #align convex.add_haar_frontier Convex.add_haar_frontier
+-/
 
 #print Convex.nullMeasurableSet /-
 /-- A convex set in a finite dimensional real vector space is null measurable with respect to an

mathlib commit https://github.com/leanprover-community/mathlib/commit/c471da714c044131b90c133701e51b877c246677

@@ -4,7 +4,7 @@ Released under Apache 2.0 license as described in the file LICENSE.
 Authors: Yury Kudryashov
 
 ! This file was ported from Lean 3 source module analysis.convex.measure
-! leanprover-community/mathlib commit fd5edc43dc4f10b85abfe544b88f82cf13c5f844
+! leanprover-community/mathlib commit fd4551cfe4b7484b81c2c9ba3405edae27659676
 ! Please do not edit these lines, except to modify the commit id
 ! if you have ported upstream changes.
 -/
@@ -15,6 +15,9 @@ import Mathbin.MeasureTheory.Measure.Lebesgue.EqHaar
 /-!
 # Convex sets are null-measurable
 
+> THIS FILE IS SYNCHRONIZED WITH MATHLIB4.
+> Any changes to this file require a corresponding PR to mathlib4.
+
 Let `E` be a finite dimensional real vector space, let `μ` be a Haar measure on `E`, let `s` be a
 convex set in `E`. Then the frontier of `s` has measure zero (see `convex.add_haar_frontier`), hence
 `s` is a `measure_theory.null_measurable_set` (see `convex.null_measurable_set`).

mathlib commit https://github.com/leanprover-community/mathlib/commit/7e5137f579de09a059a5ce98f364a04e221aabf0

@@ -93,11 +93,13 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
   simp
 #align convex.add_haar_frontier Convex.add_haar_frontier
 
+#print Convex.nullMeasurableSet /-
 /-- A convex set in a finite dimensional real vector space is null measurable with respect to an
 additive Haar measure on this space. -/
 protected theorem nullMeasurableSet (hs : Convex ℝ s) : NullMeasurableSet s μ :=
   nullMeasurableSet_of_null_frontier (hs.add_haar_frontier μ)
 #align convex.null_measurable_set Convex.nullMeasurableSet
+-/
 
 end Convex
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/5f25c089cb34db4db112556f23c50d12da81b297

@@ -28,7 +28,7 @@ open FiniteDimensional (finrank)
 open scoped Topology NNReal ENNReal
 
 variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
-  [FiniteDimensional ℝ E] (μ : Measure E) [AddHaarMeasure μ] {s : Set E}
+  [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E}
 
 namespace Convex
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/cca40788df1b8755d5baf17ab2f27dacc2e17acb

@@ -42,7 +42,7 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
     exact
       frontier_subset_closure.trans
         (closure_minimal (subset_affineSpan _ _) (affineSpan ℝ s).closed_of_finiteDimensional)
-  rw [← hs.interior_nonempty_iff_affine_span_eq_top] at hspan
+  rw [← hs.interior_nonempty_iff_affine_span_eq_top] at hspan 
   rcases hspan with ⟨x, hx⟩
   /- Without loss of generality, `s` is bounded. Indeed, `∂s ⊆ ⋃ n, ∂(s ∩ ball x (n + 1))`, hence it
     suffices to prove that `∀ n, μ (s ∩ ball x (n + 1)) = 0`; the latter set is bounded.

mathlib commit https://github.com/leanprover-community/mathlib/commit/cca40788df1b8755d5baf17ab2f27dacc2e17acb

@@ -28,7 +28,7 @@ open FiniteDimensional (finrank)
 open scoped Topology NNReal ENNReal
 
 variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
-  [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E}
+  [FiniteDimensional ℝ E] (μ : Measure E) [AddHaarMeasure μ] {s : Set E}
 
 namespace Convex
 

mathlib commit https://github.com/leanprover-community/mathlib/commit/917c3c072e487b3cccdbfeff17e75b40e45f66cb

@@ -25,7 +25,7 @@ open MeasureTheory MeasureTheory.Measure Set Metric Filter
 
 open FiniteDimensional (finrank)
 
-open Topology NNReal ENNReal
+open scoped Topology NNReal ENNReal
 
 variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
   [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E}

mathlib commit https://github.com/leanprover-community/mathlib/commit/917c3c072e487b3cccdbfeff17e75b40e45f66cb

@@ -56,22 +56,17 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
           H _ (hs.inter (convex_ball _ _)) _ (bounded_ball.mono (inter_subset_right _ _))
       rw [interior_inter, is_open_ball.interior_eq]
       exact ⟨hx, mem_ball_self (add_pos_of_nonneg_of_pos n.cast_nonneg zero_lt_one)⟩
-    refine' measure_mono_null (fun y hy => _) this
-    clear this
+    refine' measure_mono_null (fun y hy => _) this; clear this
     set N : ℕ := ⌊dist y x⌋₊
     refine' mem_Union.2 ⟨N, _⟩
-    have hN : y ∈ B N := by
-      simp only [B, N]
-      simp [Nat.lt_floor_add_one]
-    suffices : y ∈ frontier (s ∩ B N) ∩ B N
-    exact this.1
+    have hN : y ∈ B N := by simp only [B, N]; simp [Nat.lt_floor_add_one]
+    suffices : y ∈ frontier (s ∩ B N) ∩ B N; exact this.1
     rw [frontier_inter_open_inter is_open_ball]
     exact ⟨hy, hN⟩
-  clear hx hs s
-  intro s hs hx hb
+  clear hx hs s; intro s hs hx hb
   /- Since `s` is bounded, we have `μ (interior s) ≠ ∞`, hence it suffices to prove
     `μ (closure s) ≤ μ (interior s)`. -/
-  replace hb : μ (interior s) ≠ ∞
+  replace hb : μ (interior s) ≠ ∞;
   exact (hb.mono interior_subset).measure_lt_top.Ne
   suffices μ (closure s) ≤ μ (interior s) by
     rwa [frontier, measure_diff interior_subset_closure is_open_interior.measurable_set hb,

mathlib commit https://github.com/leanprover-community/mathlib/commit/f51de8769c34652d82d1c8e5f8f18f8374782bed

@@ -4,13 +4,13 @@ Released under Apache 2.0 license as described in the file LICENSE.
 Authors: Yury Kudryashov
 
 ! This file was ported from Lean 3 source module analysis.convex.measure
-! leanprover-community/mathlib commit f2ce6086713c78a7f880485f7917ea547a215982
+! leanprover-community/mathlib commit fd5edc43dc4f10b85abfe544b88f82cf13c5f844
 ! Please do not edit these lines, except to modify the commit id
 ! if you have ported upstream changes.
 -/
 import Mathbin.Analysis.Convex.Topology
 import Mathbin.Analysis.NormedSpace.AddTorsorBases
-import Mathbin.MeasureTheory.Measure.HaarLebesgue
+import Mathbin.MeasureTheory.Measure.Lebesgue.EqHaar
 
 /-!
 # Convex sets are null-measurable

mathlib commit https://github.com/leanprover-community/mathlib/commit/92c69b77c5a7dc0f7eeddb552508633305157caa

@@ -101,7 +101,7 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
 /-- A convex set in a finite dimensional real vector space is null measurable with respect to an
 additive Haar measure on this space. -/
 protected theorem nullMeasurableSet (hs : Convex ℝ s) : NullMeasurableSet s μ :=
-  nullMeasurableSetOfNullFrontier (hs.add_haar_frontier μ)
+  nullMeasurableSet_of_null_frontier (hs.add_haar_frontier μ)
 #align convex.null_measurable_set Convex.nullMeasurableSet
 
 end Convex

mathlib commit https://github.com/leanprover-community/mathlib/commit/eb0cb4511aaef0da2462207b67358a0e1fe1e2ee

@@ -25,7 +25,7 @@ open MeasureTheory MeasureTheory.Measure Set Metric Filter
 
 open FiniteDimensional (finrank)
 
-open Topology NNReal Ennreal
+open Topology NNReal ENNReal
 
 variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
   [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E}
@@ -85,13 +85,13 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 :=
     intro r hr
     refine'
       (measure_mono <| hs.closure_subset_image_homothety_interior_of_one_lt hx r hr).trans_eq _
-    rw [add_haar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, Ennreal.ofReal_coe_nNReal]
+    rw [add_haar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, ENNReal.ofReal_coe_nnreal]
   have : ∀ᶠ r in 𝓝[>] (1 : ℝ≥0), μ (closure s) ≤ ↑(r ^ d) * μ (interior s) :=
     mem_of_superset self_mem_nhdsWithin this
   -- Taking the limit as `r → 1`, we get `μ (closure s) ≤ μ (interior s)`.
   refine' ge_of_tendsto _ this
   refine'
-    (((Ennreal.continuous_mul_const hb).comp
+    (((ENNReal.continuous_mul_const hb).comp
               (ennreal.continuous_coe.comp (continuous_pow d))).tendsto'
           _ _ _).mono_left
       nhdsWithin_le_nhds

mathlib commit https://github.com/leanprover-community/mathlib/commit/bd9851ca476957ea4549eb19b40e7b5ade9428cc

Co-authored-by: Scott Morrison <scott.morrison@gmail.com>

@@ -52,7 +52,7 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
     refine' measure_mono_null (fun y hy => _) this; clear this
     set N : ℕ := ⌊dist y x⌋₊
     refine' mem_iUnion.2 ⟨N, _⟩
-    have hN : y ∈ B N := by simp [Nat.lt_floor_add_one]
+    have hN : y ∈ B N := by simp [B, N, Nat.lt_floor_add_one]
     suffices y ∈ frontier (s ∩ B N) ∩ B N from this.1
     rw [frontier_inter_open_inter isOpen_ball]
     exact ⟨hy, hN⟩

No changes to tactic file, it's just boring fixes throughout the library.

This follows on from #6964.

Co-authored-by: sgouezel <sebastien.gouezel@univ-rennes1.fr> Co-authored-by: Eric Wieser <wieser.eric@gmail.com>

@@ -42,8 +42,8 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
   /- Without loss of generality, `s` is bounded. Indeed, `∂s ⊆ ⋃ n, ∂(s ∩ ball x (n + 1))`, hence it
     suffices to prove that `∀ n, μ (s ∩ ball x (n + 1)) = 0`; the latter set is bounded.
     -/
-  suffices H : ∀ t : Set E, Convex ℝ t → x ∈ interior t → IsBounded t → μ (frontier t) = 0
-  · let B : ℕ → Set E := fun n => ball x (n + 1)
+  suffices H : ∀ t : Set E, Convex ℝ t → x ∈ interior t → IsBounded t → μ (frontier t) = 0 by
+    let B : ℕ → Set E := fun n => ball x (n + 1)
     have : μ (⋃ n : ℕ, frontier (s ∩ B n)) = 0 := by
       refine' measure_iUnion_null fun n =>
         H _ (hs.inter (convex_ball _ _)) _ (isBounded_ball.subset (inter_subset_right _ _))
@@ -53,7 +53,7 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
     set N : ℕ := ⌊dist y x⌋₊
     refine' mem_iUnion.2 ⟨N, _⟩
     have hN : y ∈ B N := by simp [Nat.lt_floor_add_one]
-    suffices : y ∈ frontier (s ∩ B N) ∩ B N; exact this.1
+    suffices y ∈ frontier (s ∩ B N) ∩ B N from this.1
     rw [frontier_inter_open_inter isOpen_ball]
     exact ⟨hy, hN⟩
   intro s hs hx hb

Use Bornology.IsBounded instead.

@@ -18,7 +18,7 @@ convex set in `E`. Then the frontier of `s` has measure zero (see `Convex.addHaa
 -/
 
 
-open MeasureTheory MeasureTheory.Measure Set Metric Filter
+open MeasureTheory MeasureTheory.Measure Set Metric Filter Bornology
 
 open FiniteDimensional (finrank)
 
@@ -42,11 +42,11 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
   /- Without loss of generality, `s` is bounded. Indeed, `∂s ⊆ ⋃ n, ∂(s ∩ ball x (n + 1))`, hence it
     suffices to prove that `∀ n, μ (s ∩ ball x (n + 1)) = 0`; the latter set is bounded.
     -/
-  suffices H : ∀ t : Set E, Convex ℝ t → x ∈ interior t → Bounded t → μ (frontier t) = 0
+  suffices H : ∀ t : Set E, Convex ℝ t → x ∈ interior t → IsBounded t → μ (frontier t) = 0
   · let B : ℕ → Set E := fun n => ball x (n + 1)
     have : μ (⋃ n : ℕ, frontier (s ∩ B n)) = 0 := by
       refine' measure_iUnion_null fun n =>
-        H _ (hs.inter (convex_ball _ _)) _ (bounded_ball.mono (inter_subset_right _ _))
+        H _ (hs.inter (convex_ball _ _)) _ (isBounded_ball.subset (inter_subset_right _ _))
       rw [interior_inter, isOpen_ball.interior_eq]
       exact ⟨hx, mem_ball_self (add_pos_of_nonneg_of_pos n.cast_nonneg zero_lt_one)⟩
     refine' measure_mono_null (fun y hy => _) this; clear this
@@ -59,8 +59,7 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
   intro s hs hx hb
   /- Since `s` is bounded, we have `μ (interior s) ≠ ∞`, hence it suffices to prove
     `μ (closure s) ≤ μ (interior s)`. -/
-  replace hb : μ (interior s) ≠ ∞
-  exact (hb.mono interior_subset).measure_lt_top.ne
+  replace hb : μ (interior s) ≠ ∞ := (hb.subset interior_subset).measure_lt_top.ne
   suffices μ (closure s) ≤ μ (interior s) by
     rwa [frontier, measure_diff interior_subset_closure isOpen_interior.measurableSet hb,
       tsub_eq_zero_iff_le]
@@ -68,8 +67,7 @@ theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
     `closure s ⊆ homothety x r '' interior s`, hence `μ (closure s) ≤ r ^ d * μ (interior s)`,
     where `d = finrank ℝ E`. -/
   set d : ℕ := FiniteDimensional.finrank ℝ E
-  have : ∀ r : ℝ≥0, 1 < r → μ (closure s) ≤ ↑(r ^ d) * μ (interior s) := by
-    intro r hr
+  have : ∀ r : ℝ≥0, 1 < r → μ (closure s) ≤ ↑(r ^ d) * μ (interior s) := fun r hr ↦ by
     refine' (measure_mono <|
       hs.closure_subset_image_homothety_interior_of_one_lt hx r hr).trans_eq _
     rw [addHaar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, ENNReal.ofReal_coe_nnreal]

We remove all possible occurences of Type _ and Sort _ in favor of Type* and Sort*.

This has nice performance benefits.

@@ -24,7 +24,7 @@ open FiniteDimensional (finrank)
 
 open scoped Topology NNReal ENNReal
 
-variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
+variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
   [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E}
 
 namespace Convex

• depends on: #5966

Co-authored-by: Eric Wieser <wieser.eric@gmail.com> Co-authored-by: Scott Morrison <scott.morrison@gmail.com>

@@ -2,16 +2,13 @@
 Copyright (c) 2022 Yury Kudryashov. All rights reserved.
 Released under Apache 2.0 license as described in the file LICENSE.
 Authors: Yury Kudryashov
-
-! This file was ported from Lean 3 source module analysis.convex.measure
-! leanprover-community/mathlib commit fd5edc43dc4f10b85abfe544b88f82cf13c5f844
-! Please do not edit these lines, except to modify the commit id
-! if you have ported upstream changes.
 -/
 import Mathlib.Analysis.Convex.Topology
 import Mathlib.Analysis.NormedSpace.AddTorsorBases
 import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
 
+#align_import analysis.convex.measure from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
+
 /-!
 # Convex sets are null-measurable
 

This is supposed to mean "an additive Haar measure", not adding something to Haar, so it should be one word and not two.

@@ -16,7 +16,7 @@ import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
 # Convex sets are null-measurable
 
 Let `E` be a finite dimensional real vector space, let `μ` be a Haar measure on `E`, let `s` be a
-convex set in `E`. Then the frontier of `s` has measure zero (see `Convex.add_haar_frontier`), hence
+convex set in `E`. Then the frontier of `s` has measure zero (see `Convex.addHaar_frontier`), hence
 `s` is a `NullMeasurableSet` (see `Convex.nullMeasurableSet`).
 -/
 
@@ -33,11 +33,11 @@ variable {E : Type _} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpac
 namespace Convex
 
 /-- Haar measure of the frontier of a convex set is zero. -/
-theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
+theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
   /- If `s` is included in a hyperplane, then `frontier s ⊆ closure s` is included in the same
     hyperplane, hence it has measure zero. -/
   cases' ne_or_eq (affineSpan ℝ s) ⊤ with hspan hspan
-  · refine' measure_mono_null _ (add_haar_affineSubspace _ _ hspan)
+  · refine' measure_mono_null _ (addHaar_affineSubspace _ _ hspan)
     exact frontier_subset_closure.trans
       (closure_minimal (subset_affineSpan _ _) (affineSpan ℝ s).closed_of_finiteDimensional)
   rw [← hs.interior_nonempty_iff_affineSpan_eq_top] at hspan
@@ -75,7 +75,7 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
     intro r hr
     refine' (measure_mono <|
       hs.closure_subset_image_homothety_interior_of_one_lt hx r hr).trans_eq _
-    rw [add_haar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, ENNReal.ofReal_coe_nnreal]
+    rw [addHaar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, ENNReal.ofReal_coe_nnreal]
   have : ∀ᶠ (r : ℝ≥0) in 𝓝[>] 1, μ (closure s) ≤ ↑(r ^ d) * μ (interior s) :=
     mem_of_superset self_mem_nhdsWithin this
   -- Taking the limit as `r → 1`, we get `μ (closure s) ≤ μ (interior s)`.
@@ -83,12 +83,12 @@ theorem add_haar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
   refine' (((ENNReal.continuous_mul_const hb).comp
     (ENNReal.continuous_coe.comp (continuous_pow d))).tendsto' _ _ _).mono_left nhdsWithin_le_nhds
   simp
-#align convex.add_haar_frontier Convex.add_haar_frontier
+#align convex.add_haar_frontier Convex.addHaar_frontier
 
 /-- A convex set in a finite dimensional real vector space is null measurable with respect to an
 additive Haar measure on this space. -/
 protected theorem nullMeasurableSet (hs : Convex ℝ s) : NullMeasurableSet s μ :=
-  nullMeasurableSet_of_null_frontier (hs.add_haar_frontier μ)
+  nullMeasurableSet_of_null_frontier (hs.addHaar_frontier μ)
 #align convex.null_measurable_set Convex.nullMeasurableSet
 
 end Convex