yes.

2026-01-11 15:46:11 +01:00
parent 69e9c61fc3
commit e66e78522e
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--- a/exercise4/uiua-modules/Omnikar/uiua-math/.github/workflows/deploy-docs.yml
+++ b/exercise4/uiua-modules/Omnikar/uiua-math/.github/workflows/deploy-docs.yml
@@ -1,62 +0,0 @@
-name: Deploy to GitHub Pages
-
-on:
-  # Trigger the workflow every time you push to the `main` branch
-  # Using a different branch name? Replace `main` with your branch's name
-  push:
-    branches: [ main ]
-  # Allows you to run this workflow manually from the Actions tab on GitHub.
-  workflow_dispatch:
-
-# Allow this job to clone the repo and create a page deployment
-permissions:
-  contents: read
-  pages: write
-  id-token: write
-
-# Allow only one concurrent deployment
-concurrency:
-  group: "pages"
-  cancel-in-progress: true
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout your repository using git
-        uses: actions/checkout@v4
-        
-      - name: Setup Pages
-        uses: actions/configure-pages@v4
-        
-      - name: Install Rust
-        uses: actions-rs/toolchain@v1
-        with:
-          toolchain: stable
-          profile: minimal
-          
-      - name: Clone and build uiua-doc-gen
-        run: |
-          git clone -b dev https://github.com/Marcos-cat/uiua-doc-gen.git
-          cd uiua-doc-gen
-          cargo build
-          echo "$(pwd)/target/debug" >> $GITHUB_PATH
-        
-      - name: Generate Documentation
-        run: uiua-doc-gen --name ${{ github.event.repository.name }}
-        
-      - name: Upload artifact
-        uses: actions/upload-pages-artifact@v3
-        with:
-          path: ./doc-site
-
-  deploy:
-    needs: build
-    runs-on: ubuntu-latest
-    environment:
-      name: github-pages
-      url: ${{ steps.deployment.outputs.page_url }}
-    steps:
-      - name: Deploy to GitHub Pages
-        id: deployment
-        uses: actions/deploy-pages@v4
--- a/exercise4/uiua-modules/Omnikar/uiua-math/LICENSE
+++ b/exercise4/uiua-modules/Omnikar/uiua-math/LICENSE
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2024 Omnikar
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
--- a/exercise4/uiua-modules/Omnikar/uiua-math/README.md
+++ b/exercise4/uiua-modules/Omnikar/uiua-math/README.md
@@ -1,62 +0,0 @@
-# uiua-math
-`uiua-math` is a library of mathematical functions for the [Uiua](https://uiua.org) programming language.
-
-The library requires `# Experimental!` due to internal usage of experimental stack manipulation modifiers.
-
-Import the whole lib
-```uiua
-Math ~ "git: github.com/Omnikar/uiua-math"
-```
-or import select functions
-```uiua
-~ "git: github.com/Omnikar/uiua-math" ~ QRot Qqp RQuat
-```
-
-Feel free to PR
-
-Functions list (see in-code documentation for more detail)
-| Function | Description     |
-|----------|-----------------|
-| `Mean`   | Arithmetic mean |
-| `GMean` | Geometric mean |
-| `HMean` | Harmonic mean |
-| `QMean` | Quadratic mean |
-| `Median` | Median |
-| `Var` | Variance |
-| `Stdev` | Standard deviation |
-| `MDet` | Matrix determinant |
-| `Mgje` | Matrix Gauss-Jordan Elimination |
-| `MCof` | Matrix cofactors |
-| `MInv` | Matrix inverse |
-| `Dot` | Dot product |
-| `Cross` | Cross product |
-| `Mmp` | Matrix product |
-| `Mvp` | Matrix-vector product |
-| `Mpow` | Matrix power |
-| `Qqp` | Quaternion product |
-| `RQuat` | Create 3D rotation quaternions |
-| `QRot` | Rotate a 3D vector array using a quaternion array |
-| `Fact` | Pervasive factorial |
-| `Gamma` | Gamma function |
-| `GCD` | Greatest common divisor |
-| `LCM` | Least common multiple |
-| `Base` | Encode an array of numbers into digits of a given base |
-| `ModInv` | Inverse of N modulo M |
-| `ModOrd` | Multiplicative order of N modulo M |
-| `CFrac` | Convert a number X to a continued fraction to N terms |
-| `Divisors` | Divisors of N (including 1 and N) |
-| `Erf` | Error function |
-| `DistRand` | Seeded random indices from a distribution array |
-| `BoxMuller` | Box-muller transform: generate pairs of normally distributed values given pairs of uniformly distributed values |
-| `Gaussian` | Generate a 2 dimensional square Gaussian kernel |
-| `BinomPmf` | Binomial distribution |
-| `BinomCmf` | Cumulative binomial distribution |
-| `GeomPmf` | Geometric distribution (0-indexed) |
-| `GeomCmf` | Cumulative geometric distribution (0-indexed) |
-| `PoissonPmf` | Poisson distribution |
-| `PoissonCmf` | Cumulative Poisson distribution |
-| `NormalPdf` | Normal distribution |
-| `NormalCdf` | Cumulative normal distribution |
-| `Quad` | Po-Shen quadratic solver |
-| `PSet` | Powerset of a list |
-| `FFTConvolve` | Rank-polymorphic convolution using fast fourier transform |
--- a/exercise4/uiua-modules/Omnikar/uiua-math/lib.ua
+++ b/exercise4/uiua-modules/Omnikar/uiua-math/lib.ua
@@ -1,428 +0,0 @@
-# Experimental!
-# Various math functions
-
-# Extract real
-R ↚ ◌°ℂ
-
-# -- Averages --
-
-# Arithmetic mean
-Mean ← ÷⧻⟜/+
-# Geometric mean
-GMean ← ⁿ˜÷1⧻⟜/×
-# Harmonic mean
-HMean ← ÷/+⟜⧻˜÷1
-# Quadratic mean
-QMean ← √÷⧻⟜/+˙×
-# Median
-# TODO: O(n) median algorithm?
-Median ← ÷2/+⊏⊟⊃⌊⌈÷2-1⊸⧻⍆
-
-# Variance
-Var ← -˙×∩÷∩⊃⧻/+⟜˙×
-# Standard deviation
-Stdev ← √Var
-
-# -- Matrices/Vectors --
-
-# ? SwappedRows Pivot
-GaussEliminate‼ ↚ ∧(
-  ⊢⍖⊸⌵⍜⊙↙×0⟜⊡⤚⊸⊙⍉
-  ⍜⊏⇌ ⊃⊙⊙∘^0 ⊟⤙⊙⊙∘ ⊙(⊃⋅⊙∘^1 ⍤.≥ε⊸⌵) ⟜⊡
-  ⊸⍜⊡(÷⊸⊡:)⊸:
-  ⍜(°⊂↻|𝄐⌞-˜⊸⊞×⊙(⊡⤚˜⊙⍉))⊸:
-)°⊏
-
-# Matrix Determinant
-MDet ← ◌⍣GaussEliminate‼(⍥¯𝄐𝄐/≠)𝄐𝄐× ⊙0⊙1
-
-# Perform Gauss-Jordan elimination
-Mgje ← ⊏⍏˜⨂1>1e-13⊸⌵ ⍥(
-  ↻₁⍣(⍜⊙⊢÷⟜(-⊞×⊙⊸⊢⊂0÷)°⊂⊸≡⊏⊢)◌⊚>1e-13⌵⊸⊢
-)⊸⧻
-# Mgje ← ⍣GaussEliminate‼(|)(⍤"Elimination cannot be completed"0)
-
-# Matrix Inverse
-MInv ← |1 ⌅(⍜⍉(↘÷2⊸⧻) ⍣Mgje(⍤"Matrix has no inverse"0) ˜≡⊂˙⊞=°⊏|MInv)
-
-┌─╴test
-  ⍤⤙≍ 5 ⁅₃ MDet [1_¯3_¯1 1_¯1_¯2 1_0_0]
-  ⍤⤙≍ [0_0_1 ¯0.4_0.2_0.2 0.2_¯0.6_0.4] ⁅₃ MInv [1_¯3_¯1 1_¯1_¯2 1_0_0]
-  ⍤⤙≍ ˙⊞=⇡3 ⁅₃ Mgje [1_¯3_¯1 1_¯1_¯2 1_0_0]
-
-  Mgje [1_5_5
-        4_5_¯10]
-  ⍤⤙≍ [1_0_¯5
-       0_1_2]
-
-  ⁅₉ Mgje [3_¯1_10
-           ¯2_4_5
-           1_1_8]
-  ⍤⤙≍ [1_0_4.5
-       0_1_3.5
-       0_0_0]
-
-  ⁅₉ Mgje [0_0_2_¯4_¯5
-           0_1_¯1_1_3
-           0_6_0_¯6_5]
-  ⍤⤙≍ [0_1_0_¯1_0
-       0_0_1_¯2_0
-       0_0_0_0_1]
-└─╴
-
-MSquarify ↚ ⍜△[.√⊢]
-# Matrix Cofactors
-MCof ← ⍥¯⊞≠.◿2°⊏MSquarify≡(MDet MSquarify≡⊡⊙¤⊚¬⊞↥°⊟)⊙¤⬚0≡₀°⊚⊚⊸=.
-
-# Dot product
-Dot ← /+×
-# Cross product
-Cross ← ↻2-∩(×↻2)◡:
-# Matrix product
-#
-# Computes AB
-# ? A B
-Mmp ← |2 ⌅(˜⍜⍉⊞Dot|Mmp MInv)
-# Matrix-vector product
-#
-# Computes MV where V is represented as a 1D list of numbers
-# ? M V
-Mvp ← |2 ⌅(Dot⍉|Mvp MInv)
-# Matrix power
-# ? P M
-Mpow ← ◌⍥⟜Mmp⊙(:˙⊞=°⊏)
-# TODO: Change to this if it comes to work with negative powers
-# Mpow ← ⍥⟜Mmp⊙(˙⊞=°⊏)
-
-┌─╴test
-  ⍤⤙≍ [3_7 ¯6_2] ⌝Mmp [1_0 0_1] [3_7 ¯6_2]
-  ⍤⤙≍ [1_0 0_1] ⁅ ⌝Mmp . [1_2 3_4]
-  ⍤⤙≍ 3 ⁅ MDet [5_6 2_3]
-
-  ⍤⤙≍ [¯8 5 ¯3 2 ¯1 1 0 1 1 2 3 5 8] ≡(⊢♭Mpow) ⍜-⇡¯7 6 ¤ [1_1 1_0]
-└─╴
-
-QqpMask ↚ [1_2_3_4
-           2_¯1_4_¯3
-           3_¯4_¯1_2
-           4_3_¯2_¯1]
-# Quaternion product
-#
-# Computes PQ for quaternion arrays P and Q.
-#
-# Semi-pervasive; the last axis of the inputs must be of length 4,
-# and will be interpreted as the input quaternions' real, i, j, and k.
-# ```uiua
-# # Computes (1+2i+3j+4k)(1+3i+5j+7k) and (2+4i+6j+8k)(5+6i+7j+8k)
-# Qqp [1_2_3_4 2_4_6_8] [1_3_5_7 5_6_7_8]
-# ## ╭─
-# ## ╷  ¯48  6  6 12
-# ##   ¯120 24 60 48
-# ##                 ╯
-# ```
-# ? P Q
-Qqp ← ⍉⊕/+-1⌵⊙×⟜±QqpMask⊞×∩°⍉
-# Create 3D rotation quaternions.
-#
-# Expects an angle array θ and a unit vector axis array U.
-#
-# Semi-pervasive; the unit vector array must have one extra trailing
-# axis compared to the angle array, and that axis must be length 3.
-#
-# For each angle-vector pair, computes cos(θ/2) + Usin(θ/2).
-# ```uiua
-# # Creates two rotation quaternions:
-# # - η radians about 0_0_1
-# # - π radians about 3/5_4/5_0
-# RQuat η_π [0_0_1 3/5_4/5_0]
-# ```
-# To use rotation quaternions created by `RQuat` to rotate 3D
-# vectors, see `QRot`.
-# ? θ U
-RQuat ← ⍜⊙°⍉⊂𝄐⌞×°∠÷2
-# Quaternion rotation implementation
-QRotImpl ↚ ⍜⊙°⍉↘1 Qqp Qqp ⟜⍜∩°⍉(⬚0↙¯4:⍜↘¯ 1)
-# Rotate a 3D vector array using a quaternion array.
-#
-# To create rotation quaternions to use with `QRot`, see `RQuat`.
-#
-# Expects a quaternion array Q and a 3D vector array V.
-#
-# Semi-pervasive; the input arrays should have matching shapes aside
-# from the final axis, which should be of lengths 4 and 3 respectively.
-#
-# For each quaternion-vector pair, computes Q * V * Q'.
-# ```uiua
-# RQuat η 0_0_1        # Create a rotation by η radians about 0_0_1
-# QRot ¤:[3_2_0 1_3_2] # Use the quaternion to rotate 3_2_0 and 1_3_2
-# ```
-# `QRot` can be used with ⍜ to undo the rotations afterward.
-# ? Q V
-QRot ← ⌅(QRotImpl|QRotImpl⍜(↘1°⍉)¯)
-
-┌─╴test
-  ⍤⤙≍ [¯48_6_6_12 ¯120_24_60_48] Qqp [1_2_3_4 2_4_6_8] [1_3_5_7 5_6_7_8]
-  ⍤⤙≍ [¯2_3_0 ¯3_1_2] ⁅ QRot ¤:[3_2_0 1_3_2] RQuat η 0_0_1
-└─╴
-
-# -- Number theory --
-
-# Pervasive factorial
-Fact ← /×°⍉+1⬚0≡₀⇡
-
-┌─╴test
-  ⍤⤙≍ [1 1 2 6 24 120 720 5040] Fact [0 1 2 3 4 5 6 7]
-└─╴
-
-# Gamma function
-# Γ(z)
-Gamma ← (
-  -1/2 ⟜(
-    -1
-    # From https://en.wikipedia.org/wiki/Lanczos_approximation
-    °⊏[
-      0.9999999999999999
-      1975.3739023578853
-      ¯4397.382392792243
-      3462.6328459862716
-      ¯1156.9851431631168
-      154.53815050252774
-      ¯6.253671612368916
-      0.034642762454736804
-      ¯7.477617197444297e-7
-      6.304125382185226e-8
-      ¯2.7405717035683877e-8
-      4.048694881756761e-9
-    ]
-    /+÷⍜⊢⋅1≡+⊙¤⊙:
-  )
-  ××× √τ ₑ¯ ⤙ⁿ ⤙+ 8 # g
-)
-
-┌─╴test
-  ⍤⤙(<1e¯10 ⌵-) √π Gamma 1/2
-  ⍤⤙(<1e¯10 ⌵-) 24 Gamma 5
-  ⍤⤙(<1e¯10 ⌵-) ℂ¯0.09161772311294437 0.024480267015440246 Gamma ℂ.¯√2
-└─╴
-
-# Greatest common divisor
-# 
-# Ignores sign
-GCD ← ◌⍢⤚◿±⌵
-# Least common multiple
-# 
-# Ignores sign
-LCM ← ⌵÷⊃GCD×
-
-┌─╴test
-  ⍤⤙≍ 6 GCD 18 24
-  ⍤⤙≍ 24 LCM 8 12
-└─╴
-
-# Encode an array of numbers into digits of a given base
-# 
-# Analogous to `⋯` for base 2; the least significant digit is first.
-# 
-# `Base` allows multiple bases as input.
-# ```uiua
-# # Encodes 6 in base 2, 7 in base 3, 8 in base 4, and 9 in base 5.
-# Base [2_3 4_5] [6_7 8_9]
-# ## ╭─
-# ## ╷ 0 1 1
-# ## ╷ 1 2 0
-# ##
-# ##   0 2 0
-# ##   4 1 0
-# ##         ╯
-# ```
-# 
-# You can use `⌝Base` to decode from a base/bases.
-# ```uiua
-# # Decodes 6 in base 2, 7 in base 3, 8 in base 4, and 9 in base 5.
-# ⌝Base [2_3 4_5] [[0_1_1 1_2_0] [0_2_0 4_1_0]]
-# ## ╭─
-# ## ╷ 6 7
-# ##   8 9
-# ##       ╯
-# ```
-Base ← ⌅(
-  ⍉◌∧⊃◿(⊂¤⌊÷)ⁿ⊙¤⇌⇡/↥♭+1⌊⊃⌝˜ⁿ⊙⊙[]
-| /+×ⁿ⊙¤⇡◡⋅⧻⊙°⍉)
-
-┌─╴test
-  ⍤⤙≍ [[2_2 1_0][3_1 1_1]] Base 5 [12_1 8_6]
-  ⍤⤙≍ [[0_1_1 1_2_0][0_2_0 4_1_0]] Base [2_3 4_5] [6_7 8_9]
-  ⍤⤙≍ [12_1 8_6] ⌝Base 5 [[2_2 1_0][3_1 1_1]]
-  ⍤⤙≍ [6_7 8_9] ⌝Base [2_3 4_5] [[0_1_1 1_2_0][0_2_0 4_1_0]]
-└─╴
-
-# Inverse of N modulo M (M if nonexistent)
-# ? N M
-ModInv ← ˜⨂1˜◿×◡⋅⇡
-# Multiplicative order of N modulo M
-# ? N M
-ModOrd ← ⊡1⊚=1˜◿ⁿ◡⋅⇡
-
-┌─╴test
-  ⍤⤙≍ 2 ModInv 4 7
-└─╴
-
-# Binomial coefficient aka N choose K
-# ? K N
-# Deprecated! Use `⧅<` instead.
-Binom ← /×÷+1⟜-⇡
-
-# Convert a number X to a continued fraction to N terms.
-# 
-# Use `°CFrac` to convert to a number from a continued fraction.
-# ? N X
-CFrac ← ⌅(⍥⊃(÷⤚◿1)⌊|⊃⧻/(+˜÷1)⇌)
-
-┌─╴test
-  ⍤⤙≍ [3 7 15 1 292 1 1 1] CFrac 8 π
-  ⍤⤙≍ e ◌°CFrac CFrac 100 e
-└─╴
-
-# Divisors of N (including 1 and N)
-# The values are in increasing order and distinct.
-# ? N
-Divisors ← ◌°▽⊂⊃÷⇌ ▽=0⊸⊃◿÷ +1⇡⌊⊸√
-
-┌─╴test
-  ⍤⤙≍ [1] Divisors 1
-  ⍤⤙≍ [1 2 3 4 6 9 12 18 36] Divisors 36
-  ⍤⤙≍ [1 2 4 5 8 10 20 25 40 50 100 125 200 250 500 1000] Divisors 1000
-└─╴
-
-# -- Probability --
-
-# Error function
-Erf ← (
-  ˜÷1+1×0.3275911 ⟜(˜ⁿe¯×.) ⌵⟜±
-  :[1.061405429 ¯1.453152027 1.421413741
-    ¯0.284496736 0.254829592
-  ]:0
-  ×¬×∧(×⊙+)¤
-)
-
-┌─╴test
-  ⍤⤙≍ 0 Erf 0
-  ⍤⤙≍ 1 Erf 1000
-  ⍤⤙≍ ¯1 Erf ¯1000
-  ⍤⤙(<1e-6⌵-) 0.5204998778130465 Erf 0.5
-  ⍤⤙(<1e-6⌵-) ¯0.5204998778130465 Erf ¯0.5
-└─╴
-
-# Seeded random indices from a distribution array
-# 
-# Given a seed, a shape, and a probability distribution array
-# of any rank containing positive numbers, `DistRand` normalizes
-# the distribution if necessary so it sums to 1, then returns
-# an array of deep indices into the distribution arrays, chosen
-# randomly weighted by the distribution. The generated random
-# indices will fill the shape given to the function. If the
-# distribution array is rank 1, the output will have the shape
-# given. If the distribution array is rank >1, the output will
-# have a shape equal to the shape given suffixed with the rank of
-# the distribution array.
-# 
-# ```uiua
-# # Generate random indices in the shape 2_3 with a seed of 8
-# DistRand [0.1 0.4 0.3 0.2] 2_3 8
-# ## ╭─
-# ## ╷ 1 2 3
-# ##   2 1 2
-# ##         ╯
-# ```
-# Indices ? Distribution Shape Seed
-DistRand ← ˜⍜♭≡(⊢⊚>)⊓¤gen⍜♭\+÷/+⊸♭
-
-# Box-Muller transform
-# 
-# Converts uniformly distributed pairs of input values to
-# standard normally distributed pairs of output values
-BoxMuller ← ∩×⤙⊓°∠∘×τ:√×¯2°ₑ¬
-
-# Generate a 2 dimensional square Gaussian kernel
-# ? Size StandardDeviation
-Gaussian ← ÷/+⊸♭ₑ¯÷2˙×˜÷⌵⊞ℂ.-÷2-1⟜⇡
-
-# Binomial distribution
-# 
-# Probability that n Bernoulli trials each with success probability p will amount to X successes
-# ? p n X
-BinomPmf ← ××⊃(≡₀⧅>|𝄐ⁿ|ⁿ⊓-¬) ⤚⋅:
-# Cumulative binomial distribution
-# 
-# Probability that n Bernoulli trials each with success probability p will amount to X or fewer successes
-# 
-# **NOTE:** This function only accepts scalars for X. Use `each` or `rows` if multiple X values are desired
-# ? p n X
-BinomCmf ← /+BinomPmf⊓∩¤(⇡+1)
-
-# Geometric distribution
-# 
-# Probability of X failures before the first success of repeated trials with success probability p
-# ? p X
-GeomPmf ← ×˜ⁿ¬⟜:
-# Cumulative geometric distribution
-# 
-# Probability of X or fewer failures before the first success of repeated trials with success probability p
-# ? p X
-GeomCmf ← ⍜¬˜ⁿ⊙(+1)
-
-# Poisson distribution
-# 
-# Probability of X occurrences of an unlikely event over many trials with expected value λ
-# ? λ X
-PoissonPmf ← ÷⊙×⊃(⋅Fact|˜ⁿ|ₑ¯)
-# Cumulative Poisson distribution
-# 
-# Probability of X or fewer occurrences of an unlikely event over many trials with expected value λ
-# ? λ X
-PoissonCmf ← /+PoissonPmf⊓¤(⇡+1)
-
-# Normal distribution
-# 
-# Probability density of a gaussian/bell curve with mean μ and standard deviation σ
-# ? σ μ X
-NormalPdf ← ÷⊃(×√τ|ₑ÷2¯˙×÷⊙-)
-# Cumulative normal distribution
-# 
-# Probability that a normally distributed random variable with mean μ and standard deviation σ is less than X
-# ? σ μ X
-NormalCdf ← ÷2+1Erf÷×√2⊙-
-
-# -- Misc --
-
-# Po-Shen quadratic solver
-# 
-# Returns roots as a list
-# 
-# Outputs complex-typed numbers only if the roots are complex
-# ? A B C
-Quad ← ⍥R⌵↥₀:⊟⊃-+⊙:√⟜±˜-˙×⟜:ℂ₀¯÷₂∩⌞÷
-
-┌─╴test
-  ⍤⤙≍ [1 2] Quad 1 ¯3 2
-  ⍤⤙≍ [¯i i] Quad 1 0 1
-  ⍤⤙≍ ∩⍆ [ℂ3 ¯1 ℂ¯1 2] ⁅₃ Quad 1 ℂ¯2 ¯1 ℂ7 1
-└─╴
-
-# Powerset of a list
-PSet ← ⍚▽⋯⇡˜ⁿ2⧻⟜¤
-
-# Rank-polymorphic fast fourier transform
-# Deprecated! `fft` has been updated to be rank-polymorphic by default. Use that instead.
-RPFFT ← ⌅(⍥(⍉fft)⧻△.|⍥°(⍉fft)⧻△.)
-
-# Rank-polymorphic convolution using fast fourier transform
-┌─╴FFTConvolve
-  # Full convolution wherever any overlap between the inputs exists
-  Full ← ⍥R=0↥⊃∩type(×√/×⊸△⍜∩fft×∩⌞⬚0↙-1+◡∩△)
-  Call ← Full
-  # Convolution of only instances of complete overlap between inputs
-  Valid ← ⍥R=0↥⊃∩type(↘-+1⌵⊙⟜(×√/×⊸△⍜∩fft×∩⌞⬚0↙)⊃-↥◡∩△)
-  # Convolution that maintains the largest of the input dimensions
-  Same ← ↙⟜(↻⌊÷₂-)⊙⊸△↥⊃∩△Full
-└─╴
--- a/exercise4/uiua-modules/Omnikar/uiua-math/todo.md
+++ b/exercise4/uiua-modules/Omnikar/uiua-math/todo.md
@@ -1,3 +0,0 @@
- Runge-Kutta-Fehlberg variable step size numerical integration macro?
- Improve matrix product `anti`s to use direct Gaussian elimination instead of going through the inverse first
-  - This will help prevent numerical imprecision errors for large matrices