From d8284164db4b6cfb19eb3d6edec1619b342c0fdf Mon Sep 17 00:00:00 2001 From: stanislav Date: Wed, 5 Jun 2024 23:54:51 +0500 Subject: [PATCH] =?UTF-8?q?Release=20TimeArrays=20v1.0.0=20=F0=9F=92=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .JuliaFormatter.toml | 9 + .gitattributes | 1 + .github/CODEOWNERS | 7 + .github/ISSUE_TEMPLATE/bug_report.md | 41 + .github/ISSUE_TEMPLATE/feature_request.md | 32 + .github/PULL_REQUEST_TEMPLATE.md | 6 + .github/dependabot.yml | 8 + .github/workflows/CI.yml | 81 + .github/workflows/CompatHelper.yml | 18 + .github/workflows/TagBot.yml | 31 + .gitignore | 30 + CHANGELOG.md | 3 + LICENSE | 21 + Project.toml | 11 + README.md | 216 + assets/high_price_sample_data.csv | 2417 +++++++ assets/low_price_sample_data.csv | 2397 +++++++ assets/price_sample_data.csv | 7778 +++++++++++++++++++++ docs/Project.toml | 3 + docs/make.jl | 36 + docs/src/assets/animation_dark.gif | Bin 0 -> 119309 bytes docs/src/assets/animation_light.gif | Bin 0 -> 121809 bytes docs/src/assets/favicon.ico | Bin 0 -> 4686 bytes docs/src/assets/middle_price.png | Bin 0 -> 125710 bytes docs/src/assets/price_to_candles.png | Bin 0 -> 112644 bytes docs/src/assets/smoothed_prices.png | Bin 0 -> 158764 bytes docs/src/index.md | 213 + docs/src/pages/arithmetic.md | 94 + docs/src/pages/array.md | 8 + docs/src/pages/custom_types.md | 168 + docs/src/pages/interface.md | 22 + docs/src/pages/resample.md | 176 + docs/src/pages/rolling.md | 8 + src/TimeArrays.jl | 74 + src/arithmetic.jl | 227 + src/array.jl | 196 + src/interface.jl | 408 ++ src/reduce.jl | 25 + src/resample.jl | 288 + src/rolling.jl | 242 + src/sample_data.jl | 38 + test/Project.toml | 5 + test/array.jl | 117 + test/custom_type.jl | 192 + test/interface.jl | 190 + test/math.jl | 429 ++ test/resample.jl | 1140 +++ test/rolling.jl | 311 + test/runtests.jl | 14 + 49 files changed, 17731 insertions(+) create mode 100644 .JuliaFormatter.toml create mode 100644 .gitattributes create mode 100644 .github/CODEOWNERS create mode 100644 .github/ISSUE_TEMPLATE/bug_report.md create mode 100644 .github/ISSUE_TEMPLATE/feature_request.md create mode 100644 .github/PULL_REQUEST_TEMPLATE.md create mode 100644 .github/dependabot.yml create mode 100644 .github/workflows/CI.yml create mode 100644 .github/workflows/CompatHelper.yml create mode 100644 .github/workflows/TagBot.yml create mode 100644 .gitignore create mode 100644 CHANGELOG.md create mode 100644 LICENSE create mode 100644 Project.toml create mode 100644 README.md create mode 100644 assets/high_price_sample_data.csv create mode 100644 assets/low_price_sample_data.csv create mode 100644 assets/price_sample_data.csv create mode 100644 docs/Project.toml create mode 100644 docs/make.jl create mode 100644 docs/src/assets/animation_dark.gif create mode 100644 docs/src/assets/animation_light.gif create mode 100644 docs/src/assets/favicon.ico create mode 100644 docs/src/assets/middle_price.png create mode 100644 docs/src/assets/price_to_candles.png create mode 100644 docs/src/assets/smoothed_prices.png create mode 100644 docs/src/index.md create mode 100644 docs/src/pages/arithmetic.md create mode 100644 docs/src/pages/array.md create mode 100644 docs/src/pages/custom_types.md create mode 100644 docs/src/pages/interface.md create mode 100644 docs/src/pages/resample.md create mode 100644 docs/src/pages/rolling.md create mode 100644 src/TimeArrays.jl create mode 100644 src/arithmetic.jl create mode 100644 src/array.jl create mode 100644 src/interface.jl create mode 100644 src/reduce.jl create mode 100644 src/resample.jl create mode 100644 src/rolling.jl create mode 100644 src/sample_data.jl create mode 100644 test/Project.toml create mode 100644 test/array.jl create mode 100644 test/custom_type.jl create mode 100644 test/interface.jl create mode 100644 test/math.jl create mode 100644 test/resample.jl create mode 100644 test/rolling.jl create mode 100644 test/runtests.jl diff --git a/.JuliaFormatter.toml b/.JuliaFormatter.toml new file mode 100644 index 0000000..6f2d942 --- /dev/null +++ b/.JuliaFormatter.toml @@ -0,0 +1,9 @@ +# .JuliaFormatter.toml + +margin = 92 # The maximum line length for code +short_to_long_function_def = true # Whether to use short or long function definitions +always_use_return = true # Whether to always use the return keyword in functions +separate_kwargs_with_semicolon = false # Whether to separate keyword arguments with semicolons instead of commas +join_lines_based_on_source = false # Whether to join lines based on source code instead of formatting rules +whitespace_in_kwargs = true # Whether to include whitespace around keyword argument separators +remove_extra_newlines = true # Whether to remove extra newlines in code diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..4ce54a6 --- /dev/null +++ b/.gitattributes @@ -0,0 +1 @@ +assets/* linguist-generated=true diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 0000000..6f01dae --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1,7 @@ +/.github/ @gryumov +/src/ @gryumov +/test/ @gryumov +/.JuliaFormatter.toml @gryumov +/.gitignore @gryumov +/LICENSE @gryumov +/Project.toml @gryumov diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md new file mode 100644 index 0000000..9398e23 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -0,0 +1,41 @@ +--- +name: 'Bug report' +about: Create a report to help us improve +title: '' +labels: bug +assignees: '' + +--- + +Describe the bug +--- +> A clear and concise description of what the bug is. + + + +To Reproduce +--- +> Add a Minimal, Complete, and Verifiable example (for more details, see e.g. https://stackoverflow.com/help/mcve) +> +> If the code is too long, feel free to put it in a public gist and link +it in the issue: https://gist.github.com + +```julia +# Past your code here. +``` + + + +Expected behavior +--- +> A clear and concise description of what you expected to happen. + + + +Additional context +--- +> Add any other context about the problem here.\ +> Please include the output of\ +> `julia> versioninfo()`\ +> and\ +> `pkg> st` \ No newline at end of file diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md new file mode 100644 index 0000000..730a65b --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -0,0 +1,32 @@ +--- +name: Feature request +about: Suggest an idea for this project +title: '' +labels: 'feature' +assignees: '' + +--- + +Is your feature request related to a problem? Please describe. +--- +> A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] + + + +Describe the solution you'd like +--- +> A clear and concise description of what you want to happen. + + + +Describe alternatives you've considered +--- +> A clear and concise description of any alternative solutions or features you've considered. + + + +Additional context +--- +> Add any other context or screenshots about the feature request here. + + diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md new file mode 100644 index 0000000..fd44682 --- /dev/null +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -0,0 +1,6 @@ +### Pull request checklist + +- [ ] Did you bump the project version? +- [ ] Did you add a description to the Pull Request? +- [ ] Did you add new tests? +- [ ] Did you add reviewers? diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 0000000..d4109f8 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,8 @@ +# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates +version: 2 +updates: + - package-ecosystem: "github-actions" + directory: "/" # Location of package manifests + schedule: + interval: "weekly" + \ No newline at end of file diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml new file mode 100644 index 0000000..e962c65 --- /dev/null +++ b/.github/workflows/CI.yml @@ -0,0 +1,81 @@ +name: CI + +on: + push: + branches: + - master + tags: ['*'] + pull_request: + workflow_dispatch: + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }} + +jobs: + test: + name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }} + runs-on: ${{ matrix.os }} + timeout-minutes: 60 + permissions: + actions: write + contents: read + strategy: + fail-fast: false + matrix: + version: + - '1' + - '1.8' + - '1.9' + - '1.10' + os: + - ubuntu-latest + arch: + - x64 + steps: + - uses: actions/checkout@v4 + - uses: julia-actions/setup-julia@v2 + with: + version: ${{ matrix.version }} + arch: ${{ matrix.arch }} + - uses: julia-actions/cache@v2 + - uses: julia-actions/julia-buildpkg@v1 + - uses: julia-actions/julia-runtest@v1 + - uses: julia-actions/julia-processcoverage@v1 + - uses: codecov/codecov-action@v4 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + with: + files: lcov.info + + docs: + permissions: + contents: write + statuses: write + actions: write + pull-requests: write + name: Documentation + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: julia-actions/setup-julia@latest + - uses: julia-actions/cache@v2 + - name: Install dependencies + run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(; path = pwd())); Pkg.instantiate();' + - name: Build and deploy + env: + GITHUB_TOKEN: ${{ github.token }} + run: julia --project=docs/ docs/make.jl + - name: Make comment with preview link + if: ${{ github.event_name == 'pull_request' && github.event.action == 'opened'}} + uses: actions/github-script@v7 + with: + script: | + github.rest.issues.createComment({ + issue_number: context.issue.number, + owner: context.repo.owner, + repo: context.repo.repo, + body: ':blue_book: A preview of the documentation will be [here](${{env.preview_url}}) soon' + }) + env: + preview_url: https://${{ github.repository_owner }}.github.io/${{ github.event.repository.name }}/previews/PR${{ github.event.number }}/ diff --git a/.github/workflows/CompatHelper.yml b/.github/workflows/CompatHelper.yml new file mode 100644 index 0000000..062291a --- /dev/null +++ b/.github/workflows/CompatHelper.yml @@ -0,0 +1,18 @@ +name: CompatHelper + +on: + schedule: + - cron: 0 0 * * * + workflow_dispatch: + +jobs: + CompatHelper: + runs-on: ubuntu-latest + steps: + - name: Pkg.add("CompatHelper") + run: julia -e 'using Pkg; Pkg.add("CompatHelper")' + - name: CompatHelper.main() + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + COMPATHELPER_PRIV: ${{ secrets.DOCUMENTER_KEY }} + run: julia -e 'using CompatHelper; CompatHelper.main()' diff --git a/.github/workflows/TagBot.yml b/.github/workflows/TagBot.yml new file mode 100644 index 0000000..e948a35 --- /dev/null +++ b/.github/workflows/TagBot.yml @@ -0,0 +1,31 @@ +name: TagBot +on: + issue_comment: + types: + - created + workflow_dispatch: + inputs: + lookback: + default: 3 +permissions: + actions: read + checks: read + contents: write + deployments: read + issues: read + discussions: read + packages: read + pages: read + pull-requests: read + repository-projects: read + security-events: read + statuses: read +jobs: + TagBot: + if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot' + runs-on: ubuntu-latest + steps: + - uses: JuliaRegistries/TagBot@v1 + with: + token: ${{ secrets.GITHUB_TOKEN }} + ssh: ${{ secrets.DOCUMENTER_KEY }} \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..cc84253 --- /dev/null +++ b/.gitignore @@ -0,0 +1,30 @@ +# MacOS +.DS_Store + +# Visual Studio Code +.vscode + +# Files generated by invoking Julia with --code-coverage +*.jl.cov +*.jl.*.cov + +# Files generated by invoking Julia with --track-allocation +*.jl.mem + +# System-specific files and directories generated by the BinaryProvider and BinDeps packages +# They contain absolute paths specific to the host computer, and so should not be committed +deps/deps.jl +deps/build.log +deps/downloads/ +deps/usr/ +deps/src/ + +# Build artifacts for creating documentation generated by the Documenter package +docs/build/ +docs/site/ + +# File generated by Pkg, the package manager, based on a corresponding Project.toml +# It records a fixed state of all packages used by the project. As such, it should not be +# committed for packages, but should be committed for applications that require a static +# environment. +Manifest.toml diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..d5e93a9 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,3 @@ +# TimeArrays.jl Changelog + +The latest version of this file can be found at the master branch of the [TimeArrays.jl repository](https://github.com/bhftbootcamp/TimeArrays.jl). diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..fda1be7 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Betterhand AG + +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. diff --git a/Project.toml b/Project.toml new file mode 100644 index 0000000..4539f0c --- /dev/null +++ b/Project.toml @@ -0,0 +1,11 @@ +name = "TimeArrays" +uuid = "058eeebf-2231-41de-8410-62311c15f51e" +version = "1.0.0" + +[deps] +Dates = "ade2ca70-3891-5945-98fb-dc099432e06a" +Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" + +[compat] +Statistics = "1" +julia = "1.8" diff --git a/README.md b/README.md new file mode 100644 index 0000000..9f61bf4 --- /dev/null +++ b/README.md @@ -0,0 +1,216 @@ + + + + + + +# TimeArrays.jl + +[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://bhftbootcamp.github.io/TimeArrays.jl/stable/) +[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://bhftbootcamp.github.io/TimeArrays.jl/dev/) +[![Build Status](https://github.com/bhftbootcamp/TimeArrays.jl/actions/workflows/CI.yml/badge.svg?branch=master)](https://github.com/bhftbootcamp/TimeArrays.jl/actions/workflows/CI.yml?query=branch%3Amaster) +[![Coverage](https://codecov.io/gh/bhftbootcamp/TimeArrays.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/bhftbootcamp/TimeArrays.jl) +[![Registry](https://img.shields.io/badge/registry-General-4063d8)](https://github.com/JuliaRegistries/General) + +TimeArrays simplifies working with time series data. It offers features like basic math operations, sliding window techniques, data resampling, and handling of missing values. + +## Installation +To install TimeArrays, simply use the Julia package manager: + +```julia +] add TimeArrays +``` + +## Usage + +In this example we perform math operations on several sets of time series. + +```julia +using Dates +using TimeArrays + +a = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-02"), 4.0), + TimeTick(DateTime("2024-01-05"), 2.0), + TimeTick(DateTime("2024-01-07"), 5.0), +]) + +b = TimeArray{DateTime,Float64}([ + (DateTime("2024-01-02"), 4.0), + (DateTime("2024-01-06"), 2.0), + (DateTime("2024-01-10"), 1.0), +]) + +c = TimeArray{DateTime,Float64}([ + DateTime("2024-01-01") => 2.0, + DateTime("2024-01-09") => 5.0, + DateTime("2024-01-11") => 4.0, +]) + +julia> 2(a * b) + b / c +8-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-02T00:00:00, 34.0) + ⋮ + TimeTick(2024-01-11T00:00:00, 10.25) +``` + +> [!NOTE] +> Since our implementation of arithmetic operations between elements of two TimeArray's is somewhat different from the usual work with arrays, a diagram is provided below that shows how exactly the elements of the time series are related to each other. For more information see [arithmetic section](https://bhftbootcamp.github.io/TimeArrays.jl/stable/pages/arithmetic/) in documentation. + +
+time:     - - - 1 - - - - 2 - - - - 3 - - - - 4 - - - - 5 - - - - 6 - - - - 7 - - - >
+
+               2.0                 4.0﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉⤵                   6.0
+t_array1:       ● - - - - - - - - - ● - - - - - - - - - - - - - - - - - - - ● - - - >
+                ┊                   ┊                   ┊                   ┊
+   +       [2.0 + NaN]         [4.0 + 3.0]         [4.0 + 5.0]         [6.0 + 5.0]
+                ┊                   ┊                   ┊                   ┊
+t_array2:       X                   ● - - - - - - - - - ● - - - - - - - - - - - - - >
+               NaN                 3.0                 5.0 ﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍⤴
+
+result:         ● - - - - - - - - - ● - - - - - - - - - ● - - - - - - - - - ● - - - >
+               NaN                 7.0                 9.0                11.0
+
+ + +TimeArrays can also deal with missing values. + +```julia +using Dates +using TimeArrays + +nan_values = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-02"), 2.0), + TimeTick(DateTime("2024-01-04"), NaN), + TimeTick(DateTime("2024-01-06"), NaN), + TimeTick(DateTime("2024-01-08"), 8.0), +]) + +julia> ta_forward_fill(nan_values) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-04T00:00:00, 8.0) + TimeTick(2024-01-06T00:00:00, 8.0) + TimeTick(2024-01-08T00:00:00, 8.0) + +julia> ta_linear_fill(nan_values) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-04T00:00:00, 4.0) + TimeTick(2024-01-06T00:00:00, 6.0) + TimeTick(2024-01-08T00:00:00, 8.0) +``` + +Here we calculate the average price between two time series of high and low prices. + +```julia +using TimeArrays + +julia> high_prices = ta_high_price_sample_data() +2416-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.998, 0.2457) + TimeTick(2023-01-01T00:00:43.315, 0.2458) + ⋮ + TimeTick(2023-01-01T23:59:43.246, 0.25) + +julia> low_prices = ta_low_price_sample_data() +2396-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.995, 0.2456) + TimeTick(2023-01-01T00:00:43.319, 0.2457) + ⋮ + TimeTick(2023-01-01T23:59:43.252, 0.2499) + +julia> (low_prices + high_prices) / 2 +3930-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.995, NaN) + TimeTick(2023-01-01T00:00:08.998, 0.24565) + ⋮ + TimeTick(2023-01-01T23:59:43.252, 0.24995) +``` + +
+ + +Visualized with [LightweightCharts.jl](https://github.com/bhftbootcamp/LightweightCharts.jl). +
+ +
+ +You can smooth the price data by using [Simple Moving Average](https://en.wikipedia.org/wiki/Moving_average) function. + +```julia +using Dates +using TimeArrays + +julia> prices = ta_price_sample_data() +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, 0.6501) + TimeTick(2024-04-01T00:05:57.481, 0.6505) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4417) + +julia> smoothed_prices = ta_sma(prices, Hour(3)) +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, NaN) + TimeTick(2024-04-01T00:05:57.481, NaN) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4408) +``` + +
+ + +Visualized with [LightweightCharts.jl](https://github.com/bhftbootcamp/LightweightCharts.jl). +
+ +
+ +You can also use custom types with TimeArrays. Below we convert prices into four-hour candlesticks using resampling. + +```julia +using Dates +using TimeArrays + +struct OHLC + open::Float64 + high::Float64 + low::Float64 + close::Float64 +end + +TimeArrays.ta_nan(::Type{OHLC}) = OHLC(NaN, NaN, NaN, NaN) + +function ohlc(x::AbstractVector{<:Number}) + return if isempty(x) + ta_nan(OHLC) + else + OHLC(x[1], maximum(x), minimum(x), x[end]) + end +end + +julia> prices = ta_price_sample_data() +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, 0.6501) + TimeTick(2024-04-01T00:05:57.481, 0.6505) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4417) + +julia> ta_resample(ohlc, prices, Hour(2); closed = CLOSED_RIGHT, label = LABEL_RIGHT) +360-element TimeArray{DateTime, OHLC}: + TimeTick(2024-04-01T02:00:00, OHLC(0.6501, 0.6505, 0.6462, 0.6491)) + TimeTick(2024-04-01T04:00:00, OHLC(0.6478, 0.6480, 0.6443, 0.6452)) + ⋮ + TimeTick(2024-05-01T00:00:00, OHLC(0.4396, 0.4436, 0.4396, 0.4417)) +``` + +
+ + +Visualized with [LightweightCharts.jl](https://github.com/bhftbootcamp/LightweightCharts.jl). +
+ +## Contributing + +Contributions to TimeArrays are welcome! If you encounter a bug, have a feature request, or would like to contribute code, please open an issue or a pull request on GitHub. diff --git a/assets/high_price_sample_data.csv b/assets/high_price_sample_data.csv new file mode 100644 index 0000000..47ecf2c --- /dev/null +++ b/assets/high_price_sample_data.csv @@ -0,0 +1,2417 @@ +time,value +2023-01-01T00:00:08.998,0.2457 +2023-01-01T00:00:43.315,0.2458 +2023-01-01T00:00:57.585,0.2459 +2023-01-01T00:01:47.673,0.2459 +2023-01-01T00:02:35.558,0.2458 +2023-01-01T00:03:25.623,0.2458 +2023-01-01T00:03:56.396,0.2457 +2023-01-01T00:04:31.462,0.2456 +2023-01-01T00:04:32.566,0.2455 +2023-01-01T00:04:46.901,0.2456 +2023-01-01T00:04:46.945,0.2457 +2023-01-01T00:05:37.073,0.2457 +2023-01-01T00:06:30.410,0.2456 +2023-01-01T00:07:26.842,0.2455 +2023-01-01T00:08:14.589,0.2454 +2023-01-01T00:09:04.623,0.2454 +2023-01-01T00:09:14.945,0.2453 +2023-01-01T00:09:18.406,0.2452 +2023-01-01T00:09:26.751,0.2453 +2023-01-01T00:10:22.982,0.2454 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+1,3 @@ +[deps] +Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" +TimeArrays = "058eeebf-2231-41de-8410-62311c15f51e" diff --git a/docs/make.jl b/docs/make.jl new file mode 100644 index 0000000..be1302f --- /dev/null +++ b/docs/make.jl @@ -0,0 +1,36 @@ +using TimeArrays +using Documenter + +DocMeta.setdocmeta!(TimeArrays, :DocTestSetup, :(using TimeArrays); recursive = true) + +makedocs( + modules = [TimeArrays], + sitename = "TimeArrays.jl", + format = Documenter.HTML(; + repolink = "https://github.com/bhftbootcamp/TimeArrays.jl", + canonical = "https://bhftbootcamp.github.io/TimeArrays.jl", + edit_link = "master", + assets = ["assets/favicon.ico"], + sidebar_sitename = true, # Set to 'false' if the package logo already contain its name + ), + pages = [ + "Home" => "index.md", + "API Reference" => [ + "pages/interface.md", + "pages/arithmetic.md", + "pages/array.md", + "pages/rolling.md", + "pages/resample.md", + ], + "For Developers" => [ + "pages/custom_types.md", + ] + ], + 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It offers features like basic math operations, sliding window techniques, data resampling, and handling of missing values. + +## Installation +To install TimeArrays, simply use the Julia package manager: + +```julia +] add TimeArrays +``` + +## Usage + +In this example we perform math operations on several sets of time series. + +```julia +using Dates +using TimeArrays + +a = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-02"), 4.0), + TimeTick(DateTime("2024-01-05"), 2.0), + TimeTick(DateTime("2024-01-07"), 5.0), +]) + +b = TimeArray{DateTime,Float64}([ + (DateTime("2024-01-02"), 4.0), + (DateTime("2024-01-06"), 2.0), + (DateTime("2024-01-10"), 1.0), +]) + +c = TimeArray{DateTime,Float64}([ + DateTime("2024-01-01") => 2.0, + DateTime("2024-01-09") => 5.0, + DateTime("2024-01-11") => 4.0, +]) + +julia> 2(a * b) + b / c +8-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-02T00:00:00, 34.0) + ⋮ + TimeTick(2024-01-11T00:00:00, 10.25) +``` + +!!! note + Since our implementation of arithmetic operations between elements of two TimeArray's is somewhat different from the usual work with arrays, a diagram is provided below that shows how exactly the elements of the time series are related to each other. For more information see [arithmetic section](https://bhftbootcamp.github.io/TimeArrays.jl/stable/pages/arithmetic/) in documentation. + +```@raw html +

+
+ time:     - - - 1 - - - - 2 - - - - 3 - - - - 4 - - - - 5 - - - - 6 - - - - 7 - - - >
+ 
+                2.0                 4.0﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉⤵                   6.0
+ t_array1:       ● - - - - - - - - - ● - - - - - - - - - - - - - - - - - - - ● - - - >
+                 ┊                   ┊                   ┊                   ┊
+    +       [2.0 + NaN]         [4.0 + 3.0]         [4.0 + 5.0]         [6.0 + 5.0]
+                 ┊                   ┊                   ┊                   ┊
+ t_array2:       X                   ● - - - - - - - - - ● - - - - - - - - - - - - - >
+                NaN                 3.0                 5.0 ﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍⤴
+ 
+ result:         ● - - - - - - - - - ● - - - - - - - - - ● - - - - - - - - - ● - - - > 
+                NaN                 7.0                 9.0                11.0
+
+
+``` + +TimeArrays can also deal with missing values. + +```julia +using Dates +using TimeArrays + +nan_values = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-02"), 2.0), + TimeTick(DateTime("2024-01-04"), NaN), + TimeTick(DateTime("2024-01-06"), NaN), + TimeTick(DateTime("2024-01-08"), 8.0), +]) + +julia> ta_forward_fill(nan_values) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-04T00:00:00, 8.0) + TimeTick(2024-01-06T00:00:00, 8.0) + TimeTick(2024-01-08T00:00:00, 8.0) + +julia> ta_linear_fill(nan_values) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-04T00:00:00, 4.0) + TimeTick(2024-01-06T00:00:00, 6.0) + TimeTick(2024-01-08T00:00:00, 8.0) +``` + +Here we calculate the average price between two time series of high and low prices. + +```julia +using TimeArrays + +julia> high_prices = ta_high_price_sample_data() +2416-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.998, 0.2457) + TimeTick(2023-01-01T00:00:43.315, 0.2458) + ⋮ + TimeTick(2023-01-01T23:59:43.246, 0.25) + +julia> low_prices = ta_low_price_sample_data() +2396-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.995, 0.2456) + TimeTick(2023-01-01T00:00:43.319, 0.2457) + ⋮ + TimeTick(2023-01-01T23:59:43.252, 0.2499) + +julia> (low_prices + high_prices) / 2 +3930-element TimeArray{DateTime, Float64}: + TimeTick(2023-01-01T00:00:08.995, NaN) + TimeTick(2023-01-01T00:00:08.998, 0.24565) + ⋮ + TimeTick(2023-01-01T23:59:43.252, 0.24995) +``` + +```@raw html +
+ + +Visualized with LightweightCharts.jl. +
+ +
+``` + +You can smooth the price data by using [Simple Moving Average](https://en.wikipedia.org/wiki/Moving_average) function. + +```julia +using Dates +using TimeArrays + +julia> prices = ta_price_sample_data() +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, 0.6501) + TimeTick(2024-04-01T00:05:57.481, 0.6505) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4417) + +julia> smoothed_prices = ta_sma(prices, Hour(3)) +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, NaN) + TimeTick(2024-04-01T00:05:57.481, NaN) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4408) +``` + +```@raw html +
+ + +Visualized with LightweightCharts.jl. +
+ +
+``` + +You can also use custom types with TimeArrays. Below we convert prices into four-hour candlesticks using resampling. + +```julia +using Dates +using TimeArrays + +struct OHLC + open::Float64 + high::Float64 + low::Float64 + close::Float64 +end + +TimeArrays.ta_nan(::Type{OHLC}) = OHLC(NaN, NaN, NaN, NaN) + +function ohlc(x::AbstractVector{<:Number}) + return if isempty(x) + ta_nan(OHLC) + else + OHLC(x[1], maximum(x), minimum(x), x[end]) + end +end + +julia> prices = ta_price_sample_data() +7777-element TimeArray{DateTime, Float64}: + TimeTick(2024-04-01T00:00:00.661, 0.6501) + TimeTick(2024-04-01T00:05:57.481, 0.6505) + ⋮ + TimeTick(2024-04-30T23:42:11.920, 0.4417) + +julia> ta_resample(ohlc, prices, Hour(2); closed = CLOSED_RIGHT, label = LABEL_RIGHT) +360-element TimeArray{DateTime, OHLC}: + TimeTick(2024-04-01T02:00:00, OHLC(0.6501, 0.6505, 0.6462, 0.6491)) + TimeTick(2024-04-01T04:00:00, OHLC(0.6478, 0.6480, 0.6443, 0.6452)) + ⋮ + TimeTick(2024-05-01T00:00:00, OHLC(0.4396, 0.4436, 0.4396, 0.4417)) +``` + +```@raw html +
+ + +Visualized with LightweightCharts.jl. +
+``` diff --git a/docs/src/pages/arithmetic.md b/docs/src/pages/arithmetic.md new file mode 100644 index 0000000..45126d6 --- /dev/null +++ b/docs/src/pages/arithmetic.md @@ -0,0 +1,94 @@ +# Arithmetic + +Time series support basic arithmetic operations, allowing you to perform the necessary calculations. +However, it is worth noting that such operations are performed in a slightly different way than on ordinary arrays, in which elements identical by index or value are compared. +In our implementation, time series values ​​are matched by the last known time value. + +To better understand the idea of ​​time series matching, let's look at the following simple example of adding two time series: + +```julia-repl +julia> t_array1 = TimeArray([ + TimeTick(1, 2.0), + TimeTick(3, 4.0), + TimeTick(7, 6.0), + ]); + +julia> t_array2 = TimeArray([ + TimeTick(3, 3.0), + TimeTick(5, 5.0), + ]); +``` + +Visually, these time series can be represented as follows: + +```@raw html +
+
+ time:   - - - 1 - - - - 2 - - - - 3 - - - - 4 - - - - 5 - - - - 6 - - - - 7 - - - >
+ 
+              2.0                 4.0                                     6.0
+ t_array1:     ● - - - - - - - - - ● - - - - - - - - - - - - - - - - - - - ● - - - > 
+ 
+ t_array2:                         ● - - - - - - - - - ● - - - - - - - - - - - - - >
+                                  3.0                 5.0
+
+
+``` + +Let's apply the addition operation to them. + +```julia-repl +julia> t_array1 + t_array2 +4-element TimeArray{Int64, Float64}: + TimeTick(1, NaN) + TimeTick(3, 7.0) + TimeTick(5, 9.0) + TimeTick(7, 11.0) +``` + +The expected behavior will be as follows: +- For the first timestamp `1` from the `t_array1` there is no time value from the `t_array2` one, so the resulting value of this timestamp will be `2.0 + NaN = NaN`. +- Then for timestamp `3` in both arrays there are values ​​(`4.0` and `3.0`), so as a result of addition we get `7.0`. +- At timestamp `5` in the `t_array2` a new value appears `5.0` for which in the `t_array1` the current value will be `4.0`. As a result we get `9.0`. +- Finally, at timestamp `7` happens the opposite of the previous case. + +```@raw html +
+
+ time:     - - - 1 - - - - 2 - - - - 3 - - - - 4 - - - - 5 - - - - 6 - - - - 7 - - - >
+ 
+                2.0                 4.0﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉﹉⤵                   6.0
+ t_array1:       ● - - - - - - - - - ● - - - - - - - - - - - - - - - - - - - ● - - - >
+                 ┊                   ┊                   ┊                   ┊
+    +       [2.0 + NaN]         [4.0 + 3.0]         [4.0 + 5.0]         [6.0 + 5.0]
+                 ┊                   ┊                   ┊                   ┊
+ t_array2:       X                   ● - - - - - - - - - ● - - - - - - - - - - - - - >
+                NaN                 3.0                 5.0 ﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍﹍⤴
+ 
+ result:         ● - - - - - - - - - ● - - - - - - - - - ● - - - - - - - - - ● - - - > 
+                NaN                 7.0                 9.0                11.0
+
+
+``` + +Supported mathematical operations on time series: +- between two TimeArrays: + - `+`: addition + - `-`: subtraction + - `*`: multiplication + - `/`: division +- between TimeArray and other values + - `+`: addition + - `-`: subtraction + - `*`: multiplication + - `/`: division + - `^`: exponentiation + +For more flexible arithmetic work on TimeArrays, you can use functions [`ta_mergewith`](@ref) and [`ta_merge`](@ref). + +## API + +```@docs +ta_mergewith +ta_merge +``` diff --git a/docs/src/pages/array.md b/docs/src/pages/array.md new file mode 100644 index 0000000..00ddd54 --- /dev/null +++ b/docs/src/pages/array.md @@ -0,0 +1,8 @@ +# Replace & Fill + +```@docs +replace +ta_backward_fill +ta_forward_fill +ta_linear_fill +``` diff --git a/docs/src/pages/custom_types.md b/docs/src/pages/custom_types.md new file mode 100644 index 0000000..01416af --- /dev/null +++ b/docs/src/pages/custom_types.md @@ -0,0 +1,168 @@ +# Custom types + +Not only Numbers, but also custom types can be used as time series values. +However, it is worth noting that for the full correct use of custom types as `TimeArrays` values, it is necessary to define some methods, which will be listed below. + +## Required metods + +To work with the main functions of the package, you need to define the following methods: + +| Required methods | Description | +|:-----------------|:------------| +| `Base.zero(::Type{T})` | Returns an object of a custom type `T` that is treated as a zero value. | +| `Base.isnan(::Type{T})` | Checks whether an object of type `T` is considered `NaN` | +| `TimeArray.ta_nan(::Type{T})` | Returns an object of a custom type `T` that is treated as a `NaN` value. | + +## Optional methods + +The following methods are useful to define for a custom type: + +| Optional methods | Description | +|:-----------------|:------------| +| `Base.isless(x::T, y::T)` | See [`isless`](https://docs.julialang.org/en/v1/base/base/#Base.isless). | +| `Base.isequal(x::T, y::T)` | See [`isequal`](https://docs.julialang.org/en/v1/base/base/#Base.isequal). | +| `Base.:(==)(x::T, y::T)` | See [`==`](https://docs.julialang.org/en/v1/base/math/#Base.:==). | +| `Base.:(+)(x::T, y::T)` | Addition between custom types. | +| `Base.:(-)(x::T, y::T)` | Subtraction between custom types. | +| `Base.:(*)(x::T, y::T)` | Multiplication between custom types. | +| `Base.:(/)(x::T, y::T)` | Division between custom types. | + +## Example + +Let's look at the necessary method overloads for our custom type that describes a candle: + +```julia +struct OHLC + o::Float64 + h::Float64 + l::Float64 + c::Float64 +end +``` + +Next we will define the necessary methods: + +```julia +Base.zero(::Type{OHLC}) = OHLC(0.0, 0.0, 0.0, 0.0) +Base.isnan(x::OHLC) = isnan(x.o) && isnan(x.h) && isnan(x.l) && isnan(x.c) +TimeArrays.ta_nan(::Type{OHLC}) = OHLC(NaN, NaN, NaN, NaN) + +Base.isless(x::OHLC, y::OHLC) = isless(x.h, y.h) + +function Base.isequal(x::OHLC, y::OHLC) + return all([ + isequal(x.o, y.o), + isequal(x.h, y.h), + isequal(x.l, y.l), + isequal(x.c, y.c), + ]) +end + +function Base.:(==)(x::OHLC, y::OHLC) + return all([ + x.o == y.o, + x.h == y.h, + x.l == y.l, + x.c == y.c, + ]) +end + +Base.:+(left::OHLC, right::OHLC) = OHLC(left.o + right.o, left.h + right.h, left.l + right.l, left.c + right.c) +Base.:-(left::OHLC, right::OHLC) = OHLC(left.o - right.o, left.h - right.h, left.l - right.l, left.c - right.c) +Base.:*(left::OHLC, right::OHLC) = OHLC(left.o * right.o, left.h * right.h, left.l * right.l, left.c * right.c) +Base.:*(left::Number, right::OHLC) = OHLC(left * right.o, left * right.h, left * right.l, left * right.c) +Base.:*(left::OHLC, right::Number) = right * left +Base.:/(left::Number, right::OHLC) = OHLC(left / right.o, left / right.h, left / right.l, left / right.c) +Base.:/(left::OHLC, right::Number) = OHLC(left.o / right, left.h / right, left.l / right, left.c / right) +``` + +Now we can use `OHLC` as the time series value and use all the available functions: + +```julia-repl +julia> t_left = TimeArray([ + TimeTick(DateTime("2024-1-1T1"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-1T2"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-1T3"), OHLC(1, 2, 3, 4)), + ]); + +julia> t_right = TimeArray([ + TimeTick(DateTime("2024-1-1T2"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-1T3"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-1T4"), OHLC(1, 2, 3, 4)), + ]); + +julia> t_left + t_right +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-01T01:00:00, OHLC(NaN, NaN, NaN, NaN)) + TimeTick(2024-01-01T02:00:00, OHLC(2.0, 4.0, 6.0, 8.0)) + TimeTick(2024-01-01T03:00:00, OHLC(2.0, 4.0, 6.0, 8.0)) + TimeTick(2024-01-01T04:00:00, OHLC(2.0, 4.0, 6.0, 8.0)) +``` + +```julia-repl +julia> t_nan = TimeArray([ + TimeTick(DateTime("2024-01-02"), OHLC(1, 1, 1, 1)), + TimeTick(DateTime("2024-01-03"), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime("2024-01-04"), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime("2024-01-05"), OHLC(10, 10, 10, 10)), + ]); + +julia> ta_forward_fill(t_nan) +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-02T00:00:00, OHLC(1.0, 1.0, 1.0, 1.0)) + TimeTick(2024-01-03T00:00:00, OHLC(10.0, 10.0, 10.0, 10.0)) + TimeTick(2024-01-04T00:00:00, OHLC(10.0, 10.0, 10.0, 10.0)) + TimeTick(2024-01-05T00:00:00, OHLC(10.0, 10.0, 10.0, 10.0)) + +julia> ta_backward_fill(t_nan) +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-02T00:00:00, OHLC(1.0, 1.0, 1.0, 1.0)) + TimeTick(2024-01-03T00:00:00, OHLC(1.0, 1.0, 1.0, 1.0)) + TimeTick(2024-01-04T00:00:00, OHLC(1.0, 1.0, 1.0, 1.0)) + TimeTick(2024-01-05T00:00:00, OHLC(10.0, 10.0, 10.0, 10.0)) + +julia> ta_linear_fill(t_nan) +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-02T00:00:00, OHLC(1.0, 1.0, 1.0, 1.0)) + TimeTick(2024-01-03T00:00:00, OHLC(4.0, 4.0, 4.0, 4.0)) + TimeTick(2024-01-04T00:00:00, OHLC(7.0, 7.0, 7.0, 7.0)) + TimeTick(2024-01-05T00:00:00, OHLC(10.0, 10.0, 10.0, 10.0)) +``` + +```julia-repl +julia> t_ohlc = TimeArray([ + TimeTick(DateTime("2024-1-01"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-02"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-03"), OHLC(1, 2, 3, 4)), + TimeTick(DateTime("2024-1-04"), OHLC(1, 2, 3, 4)), + ]); + +julia> ta_lag(t_ohlc, 2) +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-01T00:00:00, OHLC(NaN, NaN, NaN, NaN)) + TimeTick(2024-01-02T00:00:00, OHLC(NaN, NaN, NaN, NaN)) + TimeTick(2024-01-03T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) + TimeTick(2024-01-04T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) + +julia> ta_rolling(sum, t_ohlc, 3) +4-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-01T00:00:00, OHLC(NaN, NaN, NaN, NaN)) + TimeTick(2024-01-02T00:00:00, OHLC(NaN, NaN, NaN, NaN)) + TimeTick(2024-01-03T00:00:00, OHLC(3.0, 6.0, 9.0, 12.0)) + TimeTick(2024-01-04T00:00:00, OHLC(3.0, 6.0, 9.0, 12.0)) + +julia> ta_resample(x -> isempty(x) ? ta_nan(x) : sum(x), t_ohlc, Day(2)) +2-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-01T00:00:00, OHLC(2.0, 4.0, 6.0, 8.0)) + TimeTick(2024-01-03T00:00:00, OHLC(2.0, 4.0, 6.0, 8.0)) + +julia> ta_resample(sum, t_ohlc, Hour(12)) +7-element TimeArray{DateTime, OHLC}: + TimeTick(2024-01-01T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) + TimeTick(2024-01-01T12:00:00, OHLC(0.0, 0.0, 0.0, 0.0)) + TimeTick(2024-01-02T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) + TimeTick(2024-01-02T12:00:00, OHLC(0.0, 0.0, 0.0, 0.0)) + TimeTick(2024-01-03T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) + TimeTick(2024-01-03T12:00:00, OHLC(0.0, 0.0, 0.0, 0.0)) + TimeTick(2024-01-04T00:00:00, OHLC(1.0, 2.0, 3.0, 4.0)) +``` diff --git a/docs/src/pages/interface.md b/docs/src/pages/interface.md new file mode 100644 index 0000000..36e0ea8 --- /dev/null +++ b/docs/src/pages/interface.md @@ -0,0 +1,22 @@ +# Types + +```@docs +TimeArrays.TimeLike +TimeArrays.PeriodLike +``` + +## TimeTick + +```@docs +TimeArrays.AbstractTick +TimeTick +TimeTick(::Tuple) +``` + +## TimeArray + +```@docs +TimeArrays.AbstractTimeArray +TimeArray +TimeArray(::Vector) +``` diff --git a/docs/src/pages/resample.md b/docs/src/pages/resample.md new file mode 100644 index 0000000..e5564bc --- /dev/null +++ b/docs/src/pages/resample.md @@ -0,0 +1,176 @@ +# [Resample](@id resample) + +Let's assume that you have some time series with arbitrary timestamps and you need to bring the values to a new aligned grid with a fixed period in time. +For example, like this: + +```@raw html +
+
+ value:         1.0   2.0         3.0               4.0   5.0   6.0   7.0
+ grid:      - - X - - X - - - - - X - - - - - - - - X - - X - - X - - X - -
+ time:          1     2           4                 7     8     9     10
+
+
+``` + +To do this you will need a resampling method, which we will now look at in more detail. +The resampling method can be broken down into four steps: +- selecting the origin of the time grid. +- dividing the new grid into sub-intervals. +- defining the parameters of these sub-intervals, such as the closed side and the label side. +- Aggregation of values ​​falling into a new subinterval. + +## Origin of the new time grid + +First you need to select the `origin` of the new grid: +- `ORIGIN_OF_WINDOW (default)`: Origin of coordinates for the corresponding time type (Beginning of the year for dates, zero for numbers). +- `START_OF_WINDOW`: The first timestamp in the current time series. +- `END_OF_WINDOW`: The last timestamp in the current time series. + +```@raw html +
+
+ value:        1.0   2.0         3.0               4.0   5.0   6.0   7.0
+ grid:    X - - X - - X - - - - - X - - - - - - - - X - - X - - X - - X - -
+ time:    0     1     2           4                 7     8     9     10
+          ^     ^                                                     ^
+          |     |                                                     |
+          |     START_OF_WINDOW                           END_OF_WINDOW
+          ORIGIN_OF_WINDOW (default)
+
+
+``` + +## Period of the new time grid + +Then, relative to the selected origin, a grid with a step of the specified `period` will be created + +```@raw html +
+
+ value:            1.0   2.0         3.0               4.0   5.0   6.0   7.0
+ grid:        X - - X - - X - - - - - X - - - - - - - - X - - X - - X - - X - -
+ time:        0     1     2           4                 7     8     9     10
+
+
+ +
+
+ preiod = 2:  | - - - - - | - - - - - | - - - - - | - - - - - | - - - - - | - -
+              0           2           4           6           8           10
+
+ preiod = 3:  | - - - - - - - - | - - - - - - - - | - - - - - - - - | - - - - -
+              0                 3                 6                 9
+              ^
+              |
+              ORIGIN_OF_WINDOW (default)
+
+
+ +
+
+ preiod = 2:  - - - | - - - - - | - - - - - | - - - - - | - - - - - | - - - - - 
+                    1           3           5           7           9           
+
+ preiod = 3:  - - - | - - - - - - - - | - - - - - - - - | - - - - - - - - | - - 
+                    1                 4                 7                 10
+                    ^
+                    |
+                    START_OF_WINDOW
+
+
+ +
+
+ preiod = 2:  | - - - - - | - - - - - | - - - - - | - - - - - | - - - - - | - -
+              0           2           4           6           8           10
+
+ preiod = 3:  - - - | - - - - - - - - | - - - - - - - - | - - - - - - - - | - - 
+                    1                 4                 7                 10
+                                                                          ^
+                                                                          |
+                                                              END_OF_WINDOW
+
+
+``` + +## Parameters of sub-intervals + +Finally, it only remains to determine which side of the subintervals will be closed, as well as on which side the aggregation of the values ​​falling within the interval will occur. +The following example shows how parameters `CLOSED_LEFT` and `CLOSED_RIGHT`, as well as `LABEL_LEFT` and `LABEL_RIGHT`, determine the behavior of the subintervals. + +An example of the obtained sub-intervals with parameters `origin = ORIGIN_OF_WINDOW` and `period = 2`: + +```@raw html +
+
+ value:      1.0       2.0       3.0                       1.0       2.0       3.0
+ grid:    - - X - - - - X - - - - X - -   ➤   - - | - - - - X - - - - | - - - - X - - - - | - -
+ time:        1         2         3               0                   2                   4
+
+
+``` + +Possible options for decomposing values ​​into new sub-intervals for subsequent aggregation: + +```@raw html + + + + + + + + + + + + + + + + +
CLOSED_LEFT (default)CLOSED_RIGHT
LABEL_LEFT
(default)		 +
+
+ value:       1.0       2.0   3.0
+ grid:   [ - - - - - )[ - - - - - )  
+ time:    ⤷ 0          ⤷ 2 
+
+
+ 		+
+
+ value:    1.0   2.0       3.0
+ grid:   ( - - - - - ]( - - - - - ]  
+ time:    ⤷ 0          ⤷ 2 
+
+
+
LABEL_RIGHT +
+
+ value:       1.0       2.0   3.0
+ grid:   [ - - - - - )[ - - - - - )  
+ time:            2 ⤶          4 ⤶ 
+
+
+ 		+
+
+ value:    1.0   2.0       3.0
+ grid:   ( - - - - - ]( - - - - - ]  
+ time:            2 ⤶          4 ⤶
+
+
+
+``` + +## Values aggregation + +Finally, the old values ​​that fall into the new subinterval can be aggregated by applying some function, such as `sum`, `maximum`, `minimum`, `mean`, `median`, etc. + +## API + +```@docs +ta_resample +``` diff --git a/docs/src/pages/rolling.md b/docs/src/pages/rolling.md new file mode 100644 index 0000000..4770327 --- /dev/null +++ b/docs/src/pages/rolling.md @@ -0,0 +1,8 @@ +# Rolling window + +```@docs +ta_rolling +ta_sma +ta_lag +ta_lead +``` diff --git a/src/TimeArrays.jl b/src/TimeArrays.jl new file mode 100644 index 0000000..b554476 --- /dev/null +++ b/src/TimeArrays.jl @@ -0,0 +1,74 @@ +module TimeArrays + +export TimeArray, + TimeTick, + ta_timestamp, + ta_value, + ta_values + +export ta_mergewith, + ta_merge + +export ta_backward_fill, + ta_forward_fill, + ta_linear_fill + +export ta_rolling, + ta_sma, + ta_lag, + ta_lead + +export ta_resample + +export ta_nan + +export START_OF_WINDOW, + END_OF_WINDOW, + ORIGIN_OF_WINDOW + +export CLOSED_LEFT, + CLOSED_RIGHT + +export LABEL_LEFT, + LABEL_RIGHT + +using Dates +using Statistics + +""" + TimeLike <: Union{Dates.TimeType,Real} + +`TimeArray`'s timestamp type that accepts `Dates.TimeType` and `Real`. +""" +const TimeLike = Union{Real,TimeType} + +""" + PeriodLike <: Union{Dates.Period,Real} + +`TimeArray`'s period type that accepts `Dates.Period` and `Real`. +""" +const PeriodLike = Union{Real,Period} + +ta_nan(::AbstractVector{T}) where {T} = ta_nan(T) +ta_nan(::Type{T}) where {T<:Complex} = Complex(NaN, NaN) +ta_nan(::Type{T}) where {T<:Number} = NaN + +promote_nan(::Type{T}) where {T} = promote_type(T, typeof(ta_nan(T))) + +function return_type(f::Function, ::Type{V1}, ::Type{V2}) where {V1,V2} + return typeof(f(zero(V1), zero(V2))) +end + +function return_type(f::Function, ::Type{V}) where {V} + return typeof(f([zero(V)])) +end + +include("interface.jl") +include("array.jl") +include("arithmetic.jl") +include("reduce.jl") +include("rolling.jl") +include("resample.jl") +include("sample_data.jl") + +end diff --git a/src/arithmetic.jl b/src/arithmetic.jl new file mode 100644 index 0000000..cf1d8d9 --- /dev/null +++ b/src/arithmetic.jl @@ -0,0 +1,227 @@ +# arithmetic + +""" + ta_mergewith(f, l_array::TimeArray, r_array::TimeArray; kw...) -> TimeArray + +Creates a new TimeArray object by applying a binary function `f` on elements of `left` and `right` TimeArrays. +TimeArrays uses the following rules to establish corresponding elements: +- An element of the first array is matched to the nearest smaller or equal element of the second array. +- If there is no such element in the second array, then the resulting element will be `NaN`. + +## Keyword arguments +- `l_merge::Bool = true`: Use `left` timestamps in resulting TimeArray. +- `r_merge::Bool = true`: Use `right` timestamps in resulting TimeArray. +- `padding::Bool = true`: Preserve first timestamps with `NaN` values. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_left = TimeArray([ + TimeTick(DateTime("2024-01-02"), 0.2), + TimeTick(DateTime("2024-01-05"), 0.5), + ]); + +julia> t_right = TimeArray([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-05"), 5.0), + TimeTick(DateTime("2024-01-07"), 7.0), + ]); + +julia> ta_mergewith(+, t_left, t_right) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-02T00:00:00, 1.2) + TimeTick(2024-01-05T00:00:00, 5.5) + TimeTick(2024-01-07T00:00:00, 7.5) + +julia> ta_mergewith(-, t_left, t_right; l_merge = false) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-05T00:00:00, -4.5) + TimeTick(2024-01-07T00:00:00, -6.5) + +julia> ta_mergewith(*, t_left, t_right, r_merge = false, padding = false) +2-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 0.2) + TimeTick(2024-01-05T00:00:00, 2.5) +``` +""" +function ta_mergewith( + f::Function, + l_array::TimeArray{T1,V1}, + r_array::TimeArray{T2,V2}; + l_merge::Bool = true, + r_merge::Bool = true, + padding::Bool = true, +)::TimeArray where {T1,V1,T2,V2} + T = promote_type(T1, T2) + + V = if padding && ta_timestamp(l_array[1]) != ta_timestamp(r_array[1]) + promote_nan(return_type(f, V1, V2)) + else + return_type(f, V1, V2) + end + + if !l_merge && !r_merge || isempty(l_array) || isempty(r_array) + return TimeArray{T,V}() + end + + n_index = 0 + n_length = length(l_array) + length(r_array) + new_ticks = Vector{TimeTick{T,V}}(undef, n_length) + + l_index, r_index = length(l_array), length(r_array) + l_timestamp, l_value = l_array[l_index] + r_timestamp, r_value = r_array[r_index] + + while n_index <= n_length + n_tick = if l_index < 1 && r_index < 1 + break + elseif l_index < 1 + if r_merge && padding + r_timestamp, r_value = r_array[r_index] + r_index -= 1 + TimeTick{T,V}(r_timestamp, ta_nan(V)) + else + break + end + elseif r_index < 1 + if l_merge && padding + l_timestamp, l_value = l_array[l_index] + l_index -= 1 + TimeTick{T,V}(l_timestamp, ta_nan(V)) + else + break + end + else + r_timestamp, r_value = r_array[r_index] + l_timestamp, l_value = l_array[l_index] + n_value = f(l_value, r_value) + if r_timestamp > l_timestamp + r_index -= 1 + if r_merge + TimeTick{T,V}(r_timestamp, n_value) + else + continue + end + elseif l_timestamp > r_timestamp + l_index -= 1 + if l_merge + TimeTick{T,V}(l_timestamp, n_value) + else + continue + end + elseif l_timestamp == r_timestamp + l_index -= 1 + r_index -= 1 + TimeTick{T,V}(l_timestamp, n_value) + end + end + + new_ticks[n_index += 1] = n_tick + end + + return TimeArray{T,V}(reverse!(resize!(new_ticks, n_index))) +end + +function Base.:+(l_array::TimeArray, r_array::TimeArray) + return ta_mergewith(+, l_array, r_array) +end + +function Base.:-(l_array::TimeArray, r_array::TimeArray) + return ta_mergewith(-, l_array, r_array) +end + +function Base.:*(l_array::TimeArray, r_array::TimeArray) + return ta_mergewith(*, l_array, r_array) +end + +function Base.:/(l_array::TimeArray, r_array::TimeArray) + return ta_mergewith(/, l_array, r_array) +end + +""" + ta_merge(f::Function, t_array::TimeArray, value) -> TimeArray + ta_merge(f::Function, value, t_array::TimeArray) -> TimeArray + +Creates a new TimeArray by applying a binary function `f` with `value` on elements of `t_array`. + +## Examples +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-03"), 2.0), + TimeTick(DateTime("2024-01-04"), 3.0), + TimeTick(DateTime("2024-01-08"), 6.0), + ]); + +julia> ta_merge(+, t_array, 2.0) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-03T00:00:00, 4.0) + TimeTick(2024-01-04T00:00:00, 5.0) + TimeTick(2024-01-08T00:00:00, 8.0) + +julia> ta_merge(/, 18.0, t_array) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-03T00:00:00, 9.0) + TimeTick(2024-01-04T00:00:00, 6.0) + TimeTick(2024-01-08T00:00:00, 3.0) +``` +""" +function ta_merge end + +function ta_merge(f::Function, t_array::TimeArray{T,V1}, value::V2) where {T,V1,V2} + V3 = promote_type(V1, V2) + new_ticks = Vector{TimeTick{T,V3}}(undef, length(t_array)) + for i in eachindex(new_ticks) + new_ticks[i] = TimeTick{T,V3}(ta_timestamp(t_array[i]), f(ta_value(t_array[i]), value)) + end + return TimeArray{T,V3}(new_ticks, length(new_ticks)) +end + +function ta_merge(f::Function, value::V2, t_array::TimeArray{T,V1}) where {T,V1,V2} + return ta_merge((x, y) -> f(y, x), t_array, value) +end + +function Base.:+(l_array::TimeArray, r_array::Number) + return ta_merge(+, l_array, r_array) +end + +function Base.:+(l_array::Number, r_array::TimeArray) + return ta_merge(+, l_array, r_array) +end + +function Base.:-(l_array::TimeArray, r_array::Number) + return ta_merge(-, l_array, r_array) +end + +function Base.:-(l_array::Number, r_array::TimeArray) + return ta_merge(-, l_array, r_array) +end + +function Base.:*(l_array::TimeArray, r_array::Number) + return ta_merge(*, l_array, r_array) +end + +function Base.:*(l_array::Number, r_array::TimeArray) + return ta_merge(*, l_array, r_array) +end + +function Base.:/(l_array::TimeArray, r_array::Number) + return ta_merge(/, l_array, r_array) +end + +function Base.:/(l_array::Number, r_array::TimeArray) + return ta_merge(/, l_array, r_array) +end + +function Base.:^(l_array::TimeArray, r_array::Number) + return ta_merge(^, l_array, r_array) +end + +function Base.:-(t_array::TimeArray) + return -1 * t_array +end diff --git a/src/array.jl b/src/array.jl new file mode 100644 index 0000000..f9021c4 --- /dev/null +++ b/src/array.jl @@ -0,0 +1,196 @@ +# array + +""" + replace(t_array::TimeArray, old_new::Pair...; [, count]) -> TimeArray + +Return a copy of `t_array` which has all values of `old` replaced by `new` in accordance with `old_new` pair. +If `count` is specified, then replace at most `count` occurrences in total. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-02"), 2.0), + TimeTick(DateTime("2024-01-03"), 3.0), + ]); + +julia> replace(t_array, 1.0 => 10.0, 2.0 => -2.0) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, 10.0) + TimeTick(2024-01-02T00:00:00, -2.0) + TimeTick(2024-01-03T00:00:00, 3.0) +``` +""" +function Base.replace(t_array::TimeArray, old_new::Pair...; count = length(t_array)) + values = ta_values(t_array) + timestamps = map(ta_timestamp, values) + timevalues = map(ta_value, values) + return TimeArray(timestamps, replace(timevalues, old_new...; count)) +end + +""" + replace(f::Function, t_array::TimeArray; [, count]) -> TimeArray + +Return a new array where each element is the result of function `f` applied to elements of `t_array`. +If `count` is specified, then replace at most `count` occurrences in total. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-02"), 2.0), + TimeTick(DateTime("2024-01-03"), 3.0), + ]); + +julia> replace(x -> isodd(x) ? -x : x, t_array) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, -1.0) + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-03T00:00:00, -3.0) +``` +""" +function Base.replace(f::Function, t_array::TimeArray; count = length(t_array)) + values = ta_values(t_array) + timestamps = map(ta_timestamp, values) + timevalues = map(ta_value, values) + return TimeArray(timestamps, replace(f, timevalues; count)) +end + +""" + ta_backward_fill([, pattern::Function], t_array::TimeArray) -> TimeArray + +Return an array where elements that match `pattern` are replaced by nearest previous non-pattern value in `t_array`. +By default `pattern` is `isnan` function. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-03"), 1.0), + TimeTick(DateTime("2024-01-07"), NaN), + TimeTick(DateTime("2024-01-09"), NaN), + TimeTick(DateTime("2024-01-10"), 5.0), + ]); + +julia> ta_backward_fill(t_array) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-03T00:00:00, 1.0) + TimeTick(2024-01-07T00:00:00, 1.0) + TimeTick(2024-01-09T00:00:00, 1.0) + TimeTick(2024-01-10T00:00:00, 5.0) +``` +""" +function ta_backward_fill(pattern::Function, t_array::TimeArray{T,V}) where {T,V} + new_ticks = Vector{TimeTick{T,V}}(undef, length(t_array)) + for i in eachindex(t_array) + prev = findprev(x -> !pattern(x), t_array, i) + new_ticks[i] = TimeTick{T,V}( + ta_timestamp(t_array[i]), + ta_value(t_array[isnothing(prev) ? i : prev]), + ) + end + return TimeArray{T,V}(new_ticks) +end + +function ta_backward_fill(t_array::TimeArray) + return ta_backward_fill(isnan, t_array) +end + +""" + ta_forward_fill([, pattern::Function], t_array::TimeArray) -> TimeArray + +Return an array where elements that match `pattern` are replaced by nearest next non-pattern value in `t_array`. +By default `pattern` is `isnan` function. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-01"), 2.0), + TimeTick(DateTime("2024-01-03"), NaN), + TimeTick(DateTime("2024-01-04"), NaN), + TimeTick(DateTime("2024-01-08"), 7.0), + ]); + +julia> ta_forward_fill(t_array) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, 2.0) + TimeTick(2024-01-03T00:00:00, 7.0) + TimeTick(2024-01-04T00:00:00, 7.0) + TimeTick(2024-01-08T00:00:00, 7.0) +``` +""" +function ta_forward_fill(pattern::Function, t_array::TimeArray{T,V}) where {T,V} + new_ticks = Vector{TimeTick{T,V}}(undef, length(t_array)) + for i in reverse(eachindex(t_array)) + next = findnext(x -> !pattern(x), t_array, i) + new_ticks[i] = TimeTick{T,V}( + ta_timestamp(t_array[i]), + ta_value(t_array[isnothing(next) ? i : next]), + ) + end + return TimeArray{T,V}(new_ticks) +end + +function ta_forward_fill(t_array::TimeArray) + return ta_forward_fill(isnan, t_array) +end + +""" + ta_linear_fill([, pattern::Function], t_array::TimeArray) -> TimeArray + +Return an array where elements that match `pattern` are replaced by linear interpolation between nearest not-pattern values in `t_array`. +By default `pattern` is `isnan` function. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-02"), 2.0), + TimeTick(DateTime("2024-01-04"), NaN), + TimeTick(DateTime("2024-01-06"), NaN), + TimeTick(DateTime("2024-01-08"), 8.0), + ]); + +julia> ta_linear_fill(t_array) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-04T00:00:00, 4.0) + TimeTick(2024-01-06T00:00:00, 6.0) + TimeTick(2024-01-08T00:00:00, 8.0) +``` +""" +function ta_linear_fill(pattern::Function, t_array::TimeArray{T,V}) where {T,V} + new_ticks = Vector{TimeTick{T,V}}(undef, length(t_array)) + for i in eachindex(t_array) + prev = findprev(x -> !pattern(x), t_array, i) + next = findnext(x -> !pattern(x), t_array, i) + new_ticks[i] = if isnothing(prev) || isnothing(next) || prev == next + t_array[i] + else + l_timestamp, l_value = t_array[prev] + r_timestamp, r_value = t_array[next] + i_timestamp, i_value = t_array[i] + k = (i_timestamp - l_timestamp) / (r_timestamp - l_timestamp) + i_value = l_value + k * (r_value - l_value) + TimeTick{T,V}(i_timestamp, i_value) + end + end + return TimeArray{T,V}(new_ticks) +end + +function ta_linear_fill(t_array::TimeArray) + return ta_linear_fill(isnan, t_array) +end diff --git a/src/interface.jl b/src/interface.jl new file mode 100644 index 0000000..1b3fdb7 --- /dev/null +++ b/src/interface.jl @@ -0,0 +1,408 @@ +# interface + +#__ TimeTick + +""" + AbstractTick{T,V} + +Supertype for `TimeTick{T,V}` with timestmap of type `T` and value of type `V`. +""" +abstract type AbstractTick{T,V} end + +""" + TimeTick{T,V} <: AbstractTick{T,V} + +A type describing a timestamp of type `T<:TimeLike` and its value of type `V`. + +## Fields +- `timestamp::T`: The timestamp. +- `value::V`: The value. + +## Accessors +- `ta_timestamp(x::TimeTick)` -> `x.timestamp` +- `ta_value(x::TimeTick)` -> `x.value` +""" +struct TimeTick{T<:TimeLike,V<:Any} <: AbstractTick{T,V} + timestamp::T + value::V + + function TimeTick{T,V}(timestamp::TimeLike, value) where {T<:TimeLike,V} + return new{T,V}(timestamp, value) + end + + function TimeTick{T,V}(x::Tuple{TimeLike,Any}) where {T<:TimeLike,V} + return new{T,V}(x...) + end + + function TimeTick{T,V}(x::NamedTuple{names,<:Tuple{TimeLike,Any}} where {names}) where {T<:TimeLike,V} + return new{T,V}(x...) + end + + function TimeTick{T,V}(x::Pair{<:TimeLike,<:Any}) where {T<:TimeLike,V} + return new{T,V}(x.first, x.second) + end + + function TimeTick{T,V}(x::TimeTick) where {T<:TimeLike,V} + return new{T,V}(ta_timestamp(x), ta_value(x)) + end +end + +""" + TimeTick{T,V}(timestamp::TimeLike, value) + TimeTick(timestamp::T, value::V) + +Constructs a [`TimeTick`](@ref) object with the passed `timestamp` and `value`. + +## Examples +```jldoctest +julia> using Dates + +julia> TimeTick{Date,Float64}(DateTime("2024-01-01T00:00:00"), 100) +TimeTick(2024-01-01, 100.0) + +julia> TimeTick(DateTime("2024-01-01T00:00:00"), 100) +TimeTick(2024-01-01T00:00:00, 100) +``` +""" +function TimeTick(timestamp::T, value::V) where {T<:TimeLike,V} + return TimeTick{T,V}(timestamp, value) +end + +""" + TimeTick{T,V}(x::Tuple{TimeLike,Any}) + TimeTick(x::Tuple{T,V}) + +Constructs a [`TimeTick`](@ref) object from tuple `x` which contains the timestamp and value. + +## Examples +```jldoctest +julia> using Dates + +julia> TimeTick{Date,Float64}((DateTime("2024-01-01T00:00:00"), 100)) +TimeTick(2024-01-01, 100.0) + +julia> TimeTick((DateTime("2024-01-01T00:00:00"), 100)) +TimeTick(2024-01-01T00:00:00, 100) +``` +""" +function TimeTick(x::Tuple{T,V}) where {T<:TimeLike,V} + return TimeTick{T,V}(x...) +end + +""" + TimeTick{T,V}(x::NamedTuple{_,Tuple{TimeLike,Any}}) + TimeTick(x::NamedTuple{_,Tuple{TimeLike,Any}}) + +Constructs a [`TimeTick`](@ref) object from named tuple `x` which contains the timestamp and value. + +## Examples +```jldoctest +julia> using Dates + +julia> TimeTick{Date,Float64}((timestmap = DateTime("2024-01-01T00:00:00"), value = 100)) +TimeTick(2024-01-01, 100.0) + +julia> TimeTick((timestmap = DateTime("2024-01-01T00:00:00"), value = 100)) +TimeTick(2024-01-01T00:00:00, 100) +``` +""" +function TimeTick(x::NamedTuple{names,Tuple{T,V}}) where {names,T<:TimeLike,V} + return TimeTick{T,V}(x...) +end + +""" + TimeTick{T,V}(x::Pair{TimeLike,Number}) + TimeTick(x::Pair{T,V}) + +Constructs a [`TimeTick`](@ref) object from pair `x` which contains the timestamp and value. + +## Examples +```jldoctest +julia> using Dates + +julia> TimeTick{Date,Float64}(DateTime("2024-01-01T00:00:00") => 100) +TimeTick(2024-01-01, 100.0) + +julia> TimeTick(DateTime("2024-01-01T00:00:00") => 100) +TimeTick(2024-01-01T00:00:00, 100) +``` +""" +function TimeTick(x::Pair{T,V}) where {T<:TimeLike,V} + return TimeTick{T,V}(x.first, x.second) +end + +function Base.show(io::IO, x::TimeTick{T,V}) where {T<:TimeLike,V} + print(io, "TimeTick(", ta_timestamp(x), ", ", ta_value(x), ")") +end + +ta_timestamp(x::TimeTick) = x.timestamp +ta_value(x::TimeTick) = x.value + +Base.keytype(::TimeTick{T,V}) where {T,V} = T +Base.valtype(::TimeTick{T,V}) where {T,V} = V +Base.eltype(::Type{TimeTick{T,V}}) where {T,V} = Union{T,V} +Base.isnan(x::TimeTick) = isnan(ta_value(x)) +Base.isinf(x::TimeTick) = isinf(ta_value(x)) + +function Base.convert(::Type{TimeTick{T,V}}, value::TimeTick{T,V}) where {T<:TimeLike,V} + return value +end + +function Base.convert(::Type{TimeTick{T,V}}, value::TimeTick{TimeLike,Any}) where {T<:TimeLike,V} + return TimeTick{T,V}(value) +end + +function Base.convert(::Type{TimeTick{T,V}}, value::Tuple{T,V}) where {T<:TimeLike,V} + return TimeTick{T,V}(value) +end + +function Base.convert(::Type{TimeTick{T,V}}, value::Tuple{TimeLike,Number}) where {T<:TimeLike,V} + return TimeTick{T,V}(value) +end + +function Base.convert(::Type{TimeTick{T,V}}, value::Pair{T,V}) where {T<:TimeLike,V} + return TimeTick{T,V}(value) +end + +function Base.convert(::Type{TimeTick{T,V}}, value::Pair{TimeLike,Any}) where {T<:TimeLike,V} + return TimeTick{T,V}(value) +end + +function Base.getindex(t::TimeTick, i::Integer) + i == 1 && return ta_timestamp(t) + i == 2 && return ta_value(t) + throw(BoundsError(t, i)) +end + +Base.firstindex(::TimeTick) = 1 +Base.lastindex(::TimeTick) = 2 +Base.length(::TimeTick) = 2 +Base.isless(l::TimeTick, r::TimeTick) = isless(ta_value(l), ta_value(r)) + +function Base.iterate(value::TimeTick) + return (ta_timestamp(value), 2) +end + +function Base.iterate(value::TimeTick, index::Integer) + index == 2 && return (ta_value(value), 3) + return nothing +end + +function Base.:(==)(left::TimeTick, right::TimeTick)::Bool + return ta_timestamp(left) == ta_timestamp(right) && ta_value(left) == ta_value(right) +end + +function Base.isequal(left::TimeTick, right::TimeTick)::Bool + return isequal(ta_timestamp(left), ta_timestamp(right)) && isequal(ta_value(left), ta_value(right)) +end + +#__ TimeArray + +""" + AbstractTimeArray{T,V} <: AbstractVector{TimeTick{T,V}} + +Supertype for `TimeArray{T,V}` with timestmaps of type `T` and values of type `V`. +""" +abstract type AbstractTimeArray{T,V} <: AbstractVector{TimeTick{T,V}} end + +""" + TimeArray{T,V} <: AbstractTimeArray{T,V} + +Type describing a time series with timestmaps of type `T` and values of type `V`. + +## Fields +- `values::Vector{TimeTick{T,V}}`: Elements of a time series. +- `length::Int64`: The length of the underlying array. + +## Accessors +- `ta_values(x::TimeArray)` -> `x.values` +""" +struct TimeArray{T<:TimeLike,V} <: AbstractTimeArray{T,V} + values::Vector{TimeTick{T,V}} + length::Int64 + + function TimeArray{T,V}(values::AbstractVector{TimeTick{T,V}} = TimeTick{T,V}[]) where {T<:TimeLike,V} + issorted(values, by = ta_timestamp) || sort!(values, by = ta_timestamp) + return new{T,V}(values, length(values)) + end + + function TimeArray{T,V}(values::AbstractVector{TimeTick{T,V}}, length::Integer) where {T<:TimeLike,V} + return new{T,V}(values, length) + end + + function TimeArray{T,V}(values::AbstractVector) where {T<:TimeLike,V} + return TimeArray{T,V}(TimeTick{T,V}.(values)) + end +end + +""" + TimeArray{T,V}(values::Vector{TimeTick}) + TimeArray(values::Vector{TimeTick{T,V}}) + +Creates a `TimeArray{T,V}` object from `values` and sorts them by date in ascending order. + +## Examples +```jldoctest +julia> using Dates + +julia> values = [ + TimeTick(DateTime("2022-1-1T00:00:00"), 3), + TimeTick(DateTime("2023-1-1T00:00:00"), 1), + TimeTick(DateTime("2021-1-1T00:00:00"), 2), + ]; + +julia> TimeArray{Date,Float64}(values) +3-element TimeArray{Date, Float64}: + TimeTick(2021-01-01, 2.0) + TimeTick(2022-01-01, 3.0) + TimeTick(2023-01-01, 1.0) + +julia> TimeArray(values) +3-element TimeArray{DateTime, Int64}: + TimeTick(2021-01-01T00:00:00, 2) + TimeTick(2022-01-01T00:00:00, 3) + TimeTick(2023-01-01T00:00:00, 1) +``` +""" +function TimeArray(values::AbstractVector{TimeTick{T,V}}) where {T<:TimeLike,V} + return TimeArray{T,V}(values) +end + +""" + TimeArray(values::Vector{Pair{T,V}}) + TimeArray(values::Vector{Tuple{TimeLike,Any}}) + TimeArray(values::Vector{NamedTuple{_,Tuple{T,V}}}) + +Creates a `TimeArray{T,V}` object from `values` and sorts them by date in ascending order. + +## Examples +```jldoctest +julia> using Dates + +julia> TimeArray([ + DateTime("2024-01-02T00:00:00") => 3, + DateTime("2024-01-03T00:00:00") => 1, + DateTime("2024-01-01T00:00:00") => 2, + ]) +3-element TimeArray{DateTime, Int64}: + TimeTick(2024-01-01T00:00:00, 2) + TimeTick(2024-01-02T00:00:00, 3) + TimeTick(2024-01-03T00:00:00, 1) + +julia> TimeArray([ + (DateTime("2024-01-02T00:00:00"), 3), + (DateTime("2024-01-03T00:00:00"), 1), + (DateTime("2024-01-01T00:00:00"), 2), + ]) +3-element TimeArray{DateTime, Int64}: + TimeTick(2024-01-01T00:00:00, 2) + TimeTick(2024-01-02T00:00:00, 3) + TimeTick(2024-01-03T00:00:00, 1) + +julia> TimeArray([ + (time = DateTime("2024-01-02T00:00:00"), value = 3), + (time = DateTime("2024-01-03T00:00:00"), value = 1), + (time = DateTime("2024-01-01T00:00:00"), value = 2), + ]) +3-element TimeArray{DateTime, Int64}: + TimeTick(2024-01-01T00:00:00, 2) + TimeTick(2024-01-02T00:00:00, 3) + TimeTick(2024-01-03T00:00:00, 1) +``` +""" +function TimeArray(values::AbstractVector{Tuple{T,V}}) where {T<:TimeLike,V} + return TimeArray{T,V}(values) +end + +function TimeArray(values::AbstractVector{NamedTuple{names,Tuple{T,V}}} where {names}) where {T<:TimeLike,V} + return TimeArray{T,V}(values) +end + +function TimeArray(values::AbstractVector{Pair{T,V}}) where {T<:TimeLike,V} + return TimeArray{T,V}(values) +end + +""" + TimeArray(timestamps::Vector{TimeLike}, values::Vector{Any}) + +Creates a `TimeArray` by "zipping" together elements of `timestamps` and `values`. + +## Examples +```jldoctest +julia> using Dates + +julia> timestamps = [ + DateTime("2024-01-02"), + DateTime("2024-01-03"), + DateTime("2024-01-01"), + ]; + +julia> values = [2.0, 1.0, 3.0]; + +julia> TimeArray(timestamps, values) +3-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, 3.0) + TimeTick(2024-01-02T00:00:00, 2.0) + TimeTick(2024-01-03T00:00:00, 1.0) +``` +""" +function TimeArray(timestamp::AbstractVector{T}, values::AbstractVector{V}) where {T<:TimeLike,V} + return TimeArray{T,V}(TimeTick{T,V}.(timestamp, values)) +end + +""" + TimeArray{T,V}(values::AbstractVector) + +Creates a `TimeArrays{T,V}` from a `values` that contains any elements that can be passed to [`TimeTick{T,V}`](@ref TimeTick) constructors. + +!!! warning + This approach greatly reduces performance. Use at your own discretion. + +## Examples +```jldoctest +julia> using Dates + +julia> values = [ + TimeTick(Date("2024-01-02"), 3.0), + (DateTime("2024-01-03"), 1.0), + Date("2024-01-01") => 2, + ]; + +julia> TimeArray{Date,Int64}(values) +3-element TimeArray{Date, Int64}: + TimeTick(2024-01-01, 2) + TimeTick(2024-01-02, 3) + TimeTick(2024-01-03, 1) +``` +""" +function TimeArray(::AbstractVector) end + +ta_values(x::TimeArray) = x.values + +Base.values(t_array::TimeArray) = ta_values(t_array) +Base.keytype(::TimeArray{T,V}) where {T,V} = T +Base.valtype(::TimeArray{T,V}) where {T,V} = V +Base.eltype(t_array::TimeArray) = eltype(t_array.values) + +Base.length(t_array::TimeArray) = t_array.length +Base.isempty(t_array::TimeArray) = length(t_array) == 0 || isempty(ta_values(t_array)) +Base.size(t_array::TimeArray) = size(ta_values(t_array)) +Base.IndexStyle(::Type{TimeArray}) = Base.IndexLinear() +Base.firstindex(t_array::TimeArray) = 1 +Base.lastindex(t_array::TimeArray) = length(t_array) +Base.eachindex(t_array::TimeArray) = Base.oneto(length(t_array)) +Base.getindex(t_array::TimeArray, i::Integer) = ta_values(t_array)[i] +Base.getindex(t_array::TimeArray, i::UnitRange{<:Integer}) = TimeArray(ta_values(t_array)[i]) +Base.getindex(t_array::TimeArray, i::AbstractVector{<:Integer}) = TimeArray(ta_values(t_array)[i]) + +function Base.iterate(t_array::TimeArray, index::Integer = 1) + return index <= length(t_array) ? iterate(ta_values(t_array), index) : nothing +end + +function Base.:(==)(left::TimeArray, right::TimeArray) + return ta_values(left) == ta_values(right) +end + +function Base.isequal(left::TimeArray, right::TimeArray) + return isequal(ta_values(left), ta_values(right)) +end diff --git a/src/reduce.jl b/src/reduce.jl new file mode 100644 index 0000000..d5464db --- /dev/null +++ b/src/reduce.jl @@ -0,0 +1,25 @@ +# reduce + +function Base.reduce(f::Function, t_array::AbstractVector{TimeTick{T,V}}; kw...) where {T,V} + return reduce(f, map(ta_value, t_array; kw...)) +end + +function Base.sum(t_array::AbstractVector{TimeTick{T,V}}; init::V = zero(V)) where {T,V} + return sum(ta_value, t_array; init) +end + +function Base.prod(t_array::AbstractVector{TimeTick{T,V}}; init::V = one(V)) where {T,V} + return prod(ta_value, t_array; init) +end + +function Base.any(f::Function, t_array::AbstractVector{TimeTick{T,V}}) where {T,V} + return any(f, map(ta_value, t_array)) +end + +function Base.all(f::Function, t_array::AbstractVector{TimeTick{T,V}}) where {T,V} + return all(f, map(ta_value, t_array)) +end + +function Base.count(f::Function, t_array::AbstractVector{TimeTick{T,V}}) where {T,V} + return count(f, map(ta_value, t_array)) +end diff --git a/src/resample.jl b/src/resample.jl new file mode 100644 index 0000000..e4ffb72 --- /dev/null +++ b/src/resample.jl @@ -0,0 +1,288 @@ +# resample + +#__ TimeGrid + +struct TimeGrid{T<:TimeLike,P<:PeriodLike} + origin::T + period::P + + function TimeGrid(origin::T, period::P) where {T<:TimeLike,P<:PeriodLike} + @assert hasmethod(+, (T, P)) "Origin type $T is not compatible with period type $P." + return new{T,P}(origin, period) + end +end + +function Base.getindex(t_grid::TimeGrid, i::Integer) + return t_grid.origin + i * t_grid.period +end + +function Base.findnext(predicate::Function, t_grid::TimeGrid, i::Integer = 0) + tᵢ = t_grid[i] + while !predicate(tᵢ) + i += 1 + tᵢ = t_grid[i] + end + return i +end + +function Base.findprev(predicate::Function, t_grid::TimeGrid, i::Integer = 0) + tᵢ = t_grid[i] + while !predicate(tᵢ) + i -= 1 + tᵢ = t_grid[i] + end + return i +end + +function fit_to_grid(timestamp::TimeLike, t_grid::TimeGrid, closed_left::Bool = true) + i = if timestamp <= t_grid.origin + cmp = closed_left ? (<=) : (<) + findprev(cmp(timestamp), t_grid) + elseif timestamp > t_grid.origin + cmp = closed_left ? (>) : (>=) + findnext(cmp(timestamp), t_grid) - 1 + end + return (t_grid[i], i) +end + +#__ Origin + +@enum ORIGIN_TYPE begin + START_OF_WINDOW + END_OF_WINDOW + ORIGIN_OF_WINDOW +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{ORIGIN_OF_WINDOW}) where {T<:Time,V<:Any} + return typemin(T) +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{ORIGIN_OF_WINDOW}) where {T<:Date,V<:Any} + return trunc(ta_timestamp(t_array[begin]), Year) +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{ORIGIN_OF_WINDOW}) where {T<:DateTime,V<:Any} + return trunc(ta_timestamp(t_array[begin]), Year) +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{ORIGIN_OF_WINDOW}) where {T<:Real,V<:Any} + return zero(T) +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{START_OF_WINDOW}) where {T<:Any,V<:Any} + return ta_timestamp(t_array[begin]) +end + +@inline function fit_origin(t_array::TimeArray{T,V}, ::Val{END_OF_WINDOW}) where {T<:Any,V<:Any} + return ta_timestamp(t_array[end]) +end + +function fit_time_interval( + t_array::TimeArray, + period::PeriodLike, + origin_type::ORIGIN_TYPE, + closed_left::Bool = true, +) + origin = fit_origin(t_array, Val(origin_type)) + t_grid = TimeGrid(origin, period) + + t₀, i₀ = fit_to_grid(ta_timestamp(t_array[begin]), t_grid, closed_left) + tₙ, iₙ = fit_to_grid(ta_timestamp(t_array[end]), t_grid, closed_left) + + return t₀, tₙ, iₙ - i₀ + 1 +end + +#__ TimeInterval + +struct TimeInterval{T<:TimeLike} + left::T + right::T + closed::T + label::T + + function TimeInterval( + l_timestamp::T, + r_timestamp::T; + closed_left::Bool = true, + label_left::Bool = true, + ) where {T<:TimeLike} + return new{T}( + l_timestamp, + r_timestamp, + closed_left ? l_timestamp : r_timestamp, + label_left ? l_timestamp : r_timestamp, + ) + end +end + +function Base.in(timestamp::T, t_interval::TimeInterval{T}) where {T<:TimeLike} + return isequal(timestamp, t_interval.closed) || + isless(t_interval.left, timestamp) && + isless(timestamp, t_interval.right) +end + +#__ IntervalIterator + +struct IntervalIterator{T<:TimeLike,P<:PeriodLike} + t₀::T + tₙ::T + Δt::P + closed_left::Bool + label_left::Bool + + function IntervalIterator( + t₀::T, + tₙ::T, + Δt::P; + closed_left::Bool = true, + label_left::Bool = true, + ) where {T<:TimeLike,P<:PeriodLike} + return new{T,P}(t₀, tₙ, Δt, closed_left, label_left) + end +end + +function Base.iterate(iter::IntervalIterator, i::Integer = 0) + tᵢ = iter.t₀ + i * iter.Δt + if tᵢ <= iter.tₙ + return ( + TimeInterval( + tᵢ, + tᵢ + iter.Δt; + closed_left = iter.closed_left, + label_left = iter.label_left, + ), + i + 1, + ) + else + return nothing + end +end + +#__ Resampling + +@enum CLOSED_SIDE begin + CLOSED_RIGHT = false + CLOSED_LEFT = true +end + +@enum LABEL_SIDE begin + LABEL_RIGHT = false + LABEL_LEFT = true +end + +""" + ta_resample(f::Function, t_array::TimeArray{T,V}, period::PeriodLike; kw...) -> TimeArray + +Brings the values of `t_array` to a new time grid with new `period` using the function `f` on intermediate values of the old grid. + +Function `f` must accept a vector with elements of type `V` as input and return a new value, which will be assigned to the corresponding timestamp of the each window. +If it is impossible to calculate a new value based on the received vector (for example, the vector is empty), then the `NaN` value or an equivalent value (for custom types) must be returned. + +## Keyword arguments +- `origin::ORIGIN_TYPE = ORIGIN_OF_WINDOW`: Start of new grid (Possible values: `ORIGIN_OF_WINDOW`, `START_OF_WINDOW`, `END_OF_WINDOW`). +- `closed::CLOSED_SIDE = CLOSED_LEFT`: Closed side of the half-open subintervals of new grid (Possible values: `CLOSED_LEFT`, `CLOSED_RIGHT`). +- `label::LABEL_SIDE = LABEL_LEFT`: Label side of the subintervals of new grid (Possible values: `LABEL_LEFT`, `LABEL_RIGHT`). + +For more information see [`resample section`](@ref resample). + +## Examples + +```jldoctest +julia> t_array = TimeArray{Int64,Int64}([(i, i) for i in 3:13]) +11-element TimeArray{Int64, Int64}: + TimeTick(3, 3) + TimeTick(4, 4) + TimeTick(5, 5) + TimeTick(6, 6) + TimeTick(7, 7) + TimeTick(8, 8) + TimeTick(9, 9) + TimeTick(10, 10) + TimeTick(11, 11) + TimeTick(12, 12) + TimeTick(13, 13) + +julia> ta_resample(sum, t_array, 4, closed = CLOSED_LEFT, label = LABEL_LEFT) +4-element TimeArray{Int64, Float64}: + TimeTick(0, 3.0) + TimeTick(4, 22.0) + TimeTick(8, 38.0) + TimeTick(12, 25.0) + +julia> ta_resample(sum, t_array, 4, closed = CLOSED_LEFT, label = LABEL_RIGHT) +4-element TimeArray{Int64, Float64}: + TimeTick(4, 3.0) + TimeTick(8, 22.0) + TimeTick(12, 38.0) + TimeTick(16, 25.0) + +julia> ta_resample(sum, t_array, 4, closed = CLOSED_RIGHT, label = LABEL_LEFT) +4-element TimeArray{Int64, Float64}: + TimeTick(0, 7.0) + TimeTick(4, 26.0) + TimeTick(8, 42.0) + TimeTick(12, 13.0) + +julia> ta_resample(sum, t_array, 4, closed = CLOSED_RIGHT, label = LABEL_RIGHT) +4-element TimeArray{Int64, Float64}: + TimeTick(4, 7.0) + TimeTick(8, 26.0) + TimeTick(12, 42.0) + TimeTick(16, 13.0) +``` + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray{DateTime,Int64}([ + TimeTick(DateTime("2024-01-01"), 1), + TimeTick(DateTime("2024-01-02"), 2), + TimeTick(DateTime("2024-01-03"), 3), + TimeTick(DateTime("2024-01-09"), 4), + TimeTick(DateTime("2024-01-12"), 5), + TimeTick(DateTime("2024-01-13"), 6), + TimeTick(DateTime("2024-01-20"), 7), + ]); + +julia> ta_resample(x -> isempty(x) ? NaN : maximum(x), t_array, Day(3)) +7-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, 3.0) + TimeTick(2024-01-04T00:00:00, NaN) + TimeTick(2024-01-07T00:00:00, 4.0) + TimeTick(2024-01-10T00:00:00, 5.0) + TimeTick(2024-01-13T00:00:00, 6.0) + TimeTick(2024-01-16T00:00:00, NaN) + TimeTick(2024-01-19T00:00:00, 7.0) +``` +""" +function ta_resample( + f::Function, + t_array::TimeArray{T,V}, + period::PeriodLike; + origin::ORIGIN_TYPE = ORIGIN_OF_WINDOW, + closed::CLOSED_SIDE = CLOSED_LEFT, + label::LABEL_SIDE = LABEL_LEFT, +) where {T<:TimeLike,V} + isempty(t_array) && return t_array + V2 = promote_nan(return_type(f, V)) + + t₀, tₙ, n = fit_time_interval(t_array, period, origin, Bool(closed)) + closed_left = Bool(closed) + label_left = Bool(label) + + values = ta_value.(t_array) + new_ticks = Vector{TimeTick{T,V2}}(undef, n) + i = 1 + for (j, interval) in enumerate(IntervalIterator(t₀, tₙ, period; closed_left, label_left)) + window_start = i + while i <= length(t_array) && ta_timestamp(t_array[i]) in interval + i += 1 + end + window_end = i - 1 + window = view(values, window_start:window_end) + sampled_value = f(window) + new_ticks[j] = TimeTick{T,V2}(interval.label, sampled_value) + end + + return TimeArray{T,V2}(new_ticks, length(new_ticks)) +end diff --git a/src/rolling.jl b/src/rolling.jl new file mode 100644 index 0000000..e5210be --- /dev/null +++ b/src/rolling.jl @@ -0,0 +1,242 @@ +# rolling + +""" + ta_rolling(f::Function, t_array::TimeArray{T,V}, n::Integer) -> TimeArray + ta_rolling(f::Function, t_array::TimeArray{T,V}, p::Period) -> TimeArray + +Applies function `f` in a sliding window of length `n` or period `p` to the elements of `t_array`. +Function `f` must accept a vector with elements of type `V` as input and return a new value, which will be assigned to the corresponding timestamp of each window. + +Function signature: +```julia +f(x::AbstractVector{V})::Any = ... +``` + +If it is impossible to calculate a new value based on the received vector (for example, the vector is empty), then the `NaN` value or an equivalent value (for custom types) must be returned. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-03"), 2.0), + TimeTick(DateTime("2024-01-04"), 3.0), + TimeTick(DateTime("2024-01-07"), 4.0), + TimeTick(DateTime("2024-01-09"), 5.0), + ]); + +julia> ta_rolling(sum, t_array, 3) +5-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-03T00:00:00, NaN) + TimeTick(2024-01-04T00:00:00, 6.0) + TimeTick(2024-01-07T00:00:00, 9.0) + TimeTick(2024-01-09T00:00:00, 12.0) + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-01"), 1.0), + TimeTick(DateTime("2024-01-03"), 2.0), + TimeTick(DateTime("2024-01-04"), 3.0), + TimeTick(DateTime("2024-01-07"), 4.0), + TimeTick(DateTime("2024-01-09"), 5.0), + ]); + +julia> ta_rolling(sum, t_array, Day(3)) +5-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-01T00:00:00, NaN) + TimeTick(2024-01-03T00:00:00, 3.0) + TimeTick(2024-01-04T00:00:00, 5.0) + TimeTick(2024-01-07T00:00:00, 4.0) + TimeTick(2024-01-09T00:00:00, 9.0) +``` +""" +function ta_rolling end + +function ta_rolling(f::Function, t_array::TimeArray{T,V}, window::Integer) where {T,V} + len = length(t_array) + V2 = promote_nan(return_type(f, V)) + values = map(ta_value, t_array) + new_ticks = Vector{TimeTick{T,V2}}(undef, len) + + for i in 1:min(window - 1, len) + t = ta_timestamp(t_array[i]) + v = ta_nan(V2) + new_ticks[i] = TimeTick{T,V2}(t, v) + end + + for i in window:len + t = ta_timestamp(t_array[i]) + v = f(view(values, (i - window + 1):i)) + new_ticks[i] = TimeTick{T,V2}(t, v) + end + + return TimeArray{T,V2}(new_ticks, len) +end + +function ta_rolling(f::Function, t_array::TimeArray{T,V}, window::Period) where {T,V} + len = length(t_array) + V2 = promote_nan(return_type(f, V)) + values = map(ta_value, t_array) + new_ticks = Vector{TimeTick{T,V2}}(undef, len) + + l_index = len + l_timestamp = ta_timestamp(t_array[l_index]) + + for r_index in len:-1:1 + r_timestamp = ta_timestamp(t_array[r_index]) + + while l_index > 0 + l_timestamp = ta_timestamp(t_array[l_index]) + if l_timestamp > r_timestamp - window + l_index -= 1 + else + break + end + end + + value = if l_index > 0 + f(view(values, l_index+1:r_index)) + elseif l_index == 0 + l_index = -1 + f(view(values, 1:r_index)) + else + ta_nan(V2) + end + + new_ticks[r_index] =TimeTick{T,V2}(r_timestamp, value) + end + + return TimeArray{T,V2}(new_ticks, len) +end + +""" + ta_sma(t_array::TimeArray, n::Integer) -> TimeArray + ta_sma(t_array::TimeArray, p::Period) -> TimeArray + +Applies [Simple Moving Average](https://en.wikipedia.org/wiki/Moving_average) algorithm of length `n` or period `p` to the elements of `t_array`. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-02"), 1.0), + TimeTick(DateTime("2024-01-03"), 2.0), + TimeTick(DateTime("2024-01-05"), 3.0), + TimeTick(DateTime("2024-01-06"), 4.0), + TimeTick(DateTime("2024-01-09"), 5.0), + ]); + +julia> ta_sma(t_array, 2) +5-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, NaN) + TimeTick(2024-01-03T00:00:00, 1.5) + TimeTick(2024-01-05T00:00:00, 2.5) + TimeTick(2024-01-06T00:00:00, 3.5) + TimeTick(2024-01-09T00:00:00, 4.5) + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-01-02"), 1.0), + TimeTick(DateTime("2024-01-03"), 2.0), + TimeTick(DateTime("2024-01-05"), 3.0), + TimeTick(DateTime("2024-01-06"), 4.0), + TimeTick(DateTime("2024-01-09"), 5.0), + ]); + +julia> ta_sma(t_array, Day(3)) +5-element TimeArray{DateTime, Float64}: + TimeTick(2024-01-02T00:00:00, NaN) + TimeTick(2024-01-03T00:00:00, 1.5) + TimeTick(2024-01-05T00:00:00, 2.5) + TimeTick(2024-01-06T00:00:00, 3.5) + TimeTick(2024-01-09T00:00:00, 5.0) +``` +""" +function ta_sma(t_array::TimeArray, window::Union{Integer,Period}) + return ta_rolling(mean, t_array, window) +end + +""" + ta_lag(t_array::TimeArray, n::Integer) -> TimeArray + +Shifts the values of `t_array` elements by `n` positions forward. +Displaced elements that remain without a value are set to `NaN`. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-03-01"), 1.0), + TimeTick(DateTime("2024-03-02"), 2.0), + TimeTick(DateTime("2024-03-03"), 3.0), + TimeTick(DateTime("2024-03-04"), 4.0), + ]); + +julia> ta_lag(t_array, 2) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-03-01T00:00:00, NaN) + TimeTick(2024-03-02T00:00:00, NaN) + TimeTick(2024-03-03T00:00:00, 1.0) + TimeTick(2024-03-04T00:00:00, 2.0) +``` +""" +function ta_lag(t_array::TimeArray{T,V}, n::Integer) where {T,V} + len = length(t_array) + V2 = promote_nan(V) + values = map(ta_value, t_array) + new_ticks = Vector{TimeTick{T,V2}}(undef, len) + + for i in eachindex(new_ticks) + t = ta_timestamp(t_array[i]) + v = i <= n ? ta_nan(V2) : values[i - n] + new_ticks[i] = TimeTick{T,V2}(t, v) + end + + return TimeArray(new_ticks) +end + +""" + ta_lead(t_array::TimeArray{T,V}, n::Integer) -> TimeArray + +Shifts the values of `t_array` elements by `n` positions backward. +Displaced elements that remain without a value are set to `NaN`. + +## Examples + +```jldoctest +julia> using Dates + +julia> t_array = TimeArray([ + TimeTick(DateTime("2024-03-01"), 1.0), + TimeTick(DateTime("2024-03-02"), 2.0), + TimeTick(DateTime("2024-03-03"), 3.0), + TimeTick(DateTime("2024-03-04"), 4.0), + ]); + +julia> ta_lead(t_array, 2) +4-element TimeArray{DateTime, Float64}: + TimeTick(2024-03-01T00:00:00, 3.0) + TimeTick(2024-03-02T00:00:00, 4.0) + TimeTick(2024-03-03T00:00:00, NaN) + TimeTick(2024-03-04T00:00:00, NaN) +``` +""" +function ta_lead(t_array::TimeArray{T,V}, n::Integer) where {T,V} + len = length(t_array) + V2 = promote_nan(V) + values = map(ta_value, t_array) + new_ticks = Vector{TimeTick{T,V2}}(undef, len) + + for i in eachindex(new_ticks) + t = ta_timestamp(t_array[i]) + v = i > len - n ? ta_nan(V2) : values[i + n] + new_ticks[i] = TimeTick{T,V2}(t, v) + end + + return TimeArray(new_ticks) +end diff --git a/src/sample_data.jl b/src/sample_data.jl new file mode 100644 index 0000000..ffc94b8 --- /dev/null +++ b/src/sample_data.jl @@ -0,0 +1,38 @@ +# sample_data + +export ta_price_sample_data, + ta_low_price_sample_data, + ta_high_price_sample_data + +function parse_csv(x::String; types::Dict = Dict{String,Any}()) + rows = split(x, '\n'; keepempty = false) + names = Tuple(Symbol.(split(rows[begin], ','))) + + return map(rows[2:end]) do x + vals = split(x, ',') + outs = [] + for (i, name) in enumerate(names) + T = get(types, String(name), nothing) + push!(outs, isnothing(T) ? vals[i] : T(vals[i])) + end + NamedTuple{names}(outs) + end +end + +function ta_price_sample_data() + str = read(joinpath(@__DIR__, "../assets/price_sample_data.csv"), String) + csv = parse_csv(str, types = Dict("time" => DateTime, "value" => x -> parse(Float64, x))) + return TimeArray(csv) +end + +function ta_high_price_sample_data() + str = read(joinpath(@__DIR__, "../assets/high_price_sample_data.csv"), String) + csv = parse_csv(str, types = Dict("time" => DateTime, "value" => x -> parse(Float64, x))) + return TimeArray(csv) +end + +function ta_low_price_sample_data() + str = read(joinpath(@__DIR__, "../assets/low_price_sample_data.csv"), String) + csv = parse_csv(str, types = Dict("time" => DateTime, "value" => x -> parse(Float64, x))) + return TimeArray(csv) +end diff --git a/test/Project.toml b/test/Project.toml new file mode 100644 index 0000000..6f707c9 --- /dev/null +++ b/test/Project.toml @@ -0,0 +1,5 @@ +[deps] +Dates = "ade2ca70-3891-5945-98fb-dc099432e06a" +Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" +Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" +NanoDates = "46f1a544-deae-4307-8689-c12aa3c955c6" diff --git a/test/array.jl b/test/array.jl new file mode 100644 index 0000000..7c90256 --- /dev/null +++ b/test/array.jl @@ -0,0 +1,117 @@ +# t_array + +@testset verbose = true "TimeArray modification" begin + @testset "Case №1: Replace TimeTick's" begin + a = TimeArray([ + TimeTick(Time(1), -2.0), + TimeTick(Time(2), -4.0), + TimeTick(Time(3), -6.0), + ]) + + @test replace( + x -> -2.0x, + TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(2), 2.0), + TimeTick(Time(3), 3.0), + ]), + ) == a +end + @testset "Case №2: Replacing NaN's" begin + a = TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(2), 1.0), + TimeTick(Time(3), 1.0), + ]) + + @test replace(TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(2), NaN), + TimeTick(Time(3), 1.0), + ]), NaN => 1.0) == a + + @test replace(TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), NaN), + TimeTick(Time(3), NaN), + ]), NaN => 1.0) == a + end + + @testset "Case №3: Fill methods" begin + ta_nan = TimeArray{Time,Float64}([ + (Time(1), 5), + (Time(2), NaN), + (Time(3), 3), + (Time(4), Inf), + (Time(5), 7), + (Time(6), Inf), + (Time(7), NaN), + (Time(8), 10), + ]) + + @test isequal(TimeArray{Time,Float64}([ + TimeTick(Time(1), 5.0), + TimeTick(Time(2), 3.0), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), Inf), + TimeTick(Time(5), 7.0), + TimeTick(Time(6), Inf), + TimeTick(Time(7), 10.0), + TimeTick(Time(8), 10.0), + ]), + ta_forward_fill(ta_nan), + ) + + @test isequal(TimeArray{Time,Float64}([ + TimeTick(Time(1), 5.0), + TimeTick(Time(2), 5.0), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), Inf), + TimeTick(Time(5), 7.0), + TimeTick(Time(6), Inf), + TimeTick(Time(7), Inf), + TimeTick(Time(8), 10.0), + ]), + ta_backward_fill(ta_nan), + ) + + @test isequal(TimeArray{Time,Float64}([ + TimeTick(Time(1), 5.0), + TimeTick(Time(2), 4.0), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), Inf), + TimeTick(Time(5), 7.0), + TimeTick(Time(6), Inf), + TimeTick(Time(7), NaN), + TimeTick(Time(8), 10.0), + ]), + ta_linear_fill(ta_nan), + ) + + @test isequal(TimeArray{Time,Float64}([ + TimeTick(Time(1), 5.0), + TimeTick(Time(2), 3.0), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), 7.0), + TimeTick(Time(5), 7.0), + TimeTick(Time(6), 10.0), + TimeTick(Time(7), 10.0), + TimeTick(Time(8), 10.0), + ]), + ta_forward_fill(x -> isinf(x) || isnan(x), ta_nan), + ) + + @test isequal(TimeArray{Time,Float64}([ + TimeTick(Time(1), 5.0), + TimeTick(Time(2), NaN), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), 7.0), + TimeTick(Time(5), 7.0), + TimeTick(Time(6), NaN), + TimeTick(Time(7), NaN), + TimeTick(Time(8), 10.0), + ]), + ta_forward_fill(isinf, ta_nan), + ) + end +end diff --git a/test/custom_type.jl b/test/custom_type.jl new file mode 100644 index 0000000..dff26fa --- /dev/null +++ b/test/custom_type.jl @@ -0,0 +1,192 @@ +# custom_type + +@testset verbose = true "Custom type TimeTick" begin + + struct OHLC + o::Float64 + h::Float64 + l::Float64 + c::Float64 + end + + # Interface + Base.isless(left::OHLC, right::OHLC) = left.h < right.h + TimeArrays.ta_nan(::Type{OHLC}) = OHLC(NaN, NaN, NaN, NaN) + Base.isnan(x::OHLC) = isnan(x.o) && isnan(x.h) && isnan(x.l) && isnan(x.c) + Base.zero(::Type{OHLC}) = OHLC(0.0, 0.0, 0.0, 0.0) + + function merge_ohlc(left, right) + return OHLC(left.o + right.o, left.h - left.h, left.l * right.l, left.c / right.c) + end + + Base.:/(left::Number, right::OHLC) = OHLC(left / right.o, left / right.h, left / right.l, left / right.c) + Base.:/(left::OHLC, right::Number) = OHLC(left.o / right, left.h / right, left.l / right, left.c / right) + + @testset "Case №1: Merge functions" begin + left = TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1, 2, 3, 4)), + ]) + + right = TimeArray([ + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1, 2, 3, 4)), + ]) + + @test isequal( + ta_mergewith(merge_ohlc, left, right), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(2.0, 0.0, 9.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(2.0, 0.0, 9.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(2.0, 0.0, 9.0, 1.0)), + ]), + ) + end + + Base.:+(left::OHLC, right::OHLC) = OHLC(left.o + right.o, left.h + right.h, left.l + right.l, left.c + right.c) + Base.:-(left::OHLC, right::OHLC) = OHLC(left.o - right.o, left.h - right.h, left.l - right.l, left.c - right.c) + Base.:*(left::OHLC, right::OHLC) = OHLC(left.o * right.o, left.h * right.h, left.l * right.l, left.c * right.c) + Base.:*(left::Number, right::OHLC) = OHLC(left * right.o, left * right.h, left * right.l, left * right.c) + Base.:*(left::OHLC, right::Number) = right * left + + @testset "Case №2: Fill functions" begin + ta_nan = TimeArray([ + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1, 1, 1, 1)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(10, 10, 10, 10)), + ]) + + @test isequal( + ta_forward_fill(ta_nan), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1.0, 1.0, 1.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(10.0, 10.0, 10.0, 10.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(10.0, 10.0, 10.0, 10.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(10.0, 10.0, 10.0, 10.0)), + ]), + ) + + @test isequal( + ta_backward_fill(ta_nan), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1.0, 1.0, 1.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1.0, 1.0, 1.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1.0, 1.0, 1.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(10.0, 10.0, 10.0, 10.0)), + ]), + ) + + @test isequal( + ta_linear_fill(ta_nan), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1.0, 1.0, 1.0, 1.0)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(4.0, 4.0, 4.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(7.0, 7.0, 7.0, 7.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(10.0, 10.0, 10.0, 10.0)), + ]), + ) + end + + @testset "Case №3: Window functions" begin + ta_ohlc = TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(1, 2, 3, 4)), + ]) + + @test isequal( + ta_lag(ta_ohlc, 3), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(1.0, 2.0, 3.0, 4.0)), + ]), + ) + + @test isequal( + ta_sma(ta_ohlc, 3), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(1.0, 2.0, 3.0, 4.0)), + ]), + ) + + @test isequal( + ta_rolling(sum, ta_ohlc, 3), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(3.0, 6.0, 9.0, 12.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(3.0, 6.0, 9.0, 12.0)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(3.0, 6.0, 9.0, 12.0)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(3.0, 6.0, 9.0, 12.0)), + ]), + ) + end + + @testset "Case №4: Resample functions" begin + + ta_ohlc = TimeArray([ + TimeTick(DateTime(2024, 1, 1, 1), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 3), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 5), OHLC(1, 2, 3, 4)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(1, 2, 3, 4)), + ]) + + @test isequal( + ta_resample(sum, ta_ohlc, Hour(2)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 2), OHLC(2.0, 4.0, 6.0, 8.0)), + TimeTick(DateTime(2024, 1, 1, 4), OHLC(2.0, 4.0, 6.0, 8.0)), + TimeTick(DateTime(2024, 1, 1, 6), OHLC(1.0, 2.0, 3.0, 4.0)), + ]), + ) + + @test isequal( + ta_resample(x -> isempty(x) ? ta_nan(x) : maximum(x), ta_ohlc, Minute(40)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 0, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 1, 20), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 2, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 2, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 3, 20), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 4, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 4, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 5, 20), OHLC(NaN, NaN, NaN, NaN)), + TimeTick(DateTime(2024, 1, 1, 6, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + ]), + ) + + @test isequal( + ta_resample(sum, ta_ohlc, Minute(40)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1, 0, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 1, 20), OHLC(0.0, 0.0, 0.0, 0.0)), + TimeTick(DateTime(2024, 1, 1, 2, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 2, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 3, 20), OHLC(0.0, 0.0, 0.0, 0.0)), + TimeTick(DateTime(2024, 1, 1, 4, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 4, 40), OHLC(1.0, 2.0, 3.0, 4.0)), + TimeTick(DateTime(2024, 1, 1, 5, 20), OHLC(0.0, 0.0, 0.0, 0.0)), + TimeTick(DateTime(2024, 1, 1, 6, 0), OHLC(1.0, 2.0, 3.0, 4.0)), + ]), + ) + end +end diff --git a/test/interface.jl b/test/interface.jl new file mode 100644 index 0000000..c490af5 --- /dev/null +++ b/test/interface.jl @@ -0,0 +1,190 @@ +# interface + +@testset verbose = true "TimeTick constructors" begin + @testset "Case №1: TimeTick from timestamp and value" begin + @test TimeTick{Int64,Int64}(1.0, 2.0) == TimeTick(1, 2) + @test TimeTick{Float64,Float64}(1, 2) == TimeTick(1.0, 2.0) + @test TimeTick{Date,Float64}(DateTime("2023-01-01"), 2.0) == TimeTick(Date("2023-01-01"), 2.0) + @test TimeTick{DateTime,Float64}(Date("2023-01-01"), 2.0) == TimeTick(DateTime("2023-01-01"), 2.0) + @test TimeTick{DateTime,Float64}(DateTime("2023-01-01"), 2.0) == TimeTick(DateTime("2023-01-01"), 2.0) + @test TimeTick{NanoDate,Float64}(Date("2023-01-01"), 2.0) == TimeTick(NanoDate("2023-01-01"), 2.0) + @test TimeTick{Date,Float64}(DateTime("2023-01-01"), 2.0) == TimeTick(Date("2023-01-01"), 2.0) + @test TimeTick{Time,Float64}(DateTime("2023-01-01"), 2.0) == TimeTick(Time("00:00:00"), 2.0) + end + + @testset "Case №2: TimeTick from Tuple" begin + @test TimeTick{Int64,Int64}((1.0, 2.0)) == TimeTick((1, 2)) + @test TimeTick{Float64,Float64}((1, 2)) == TimeTick((1.0, 2.0)) + @test TimeTick{Date,Float64}((DateTime("2023-01-01"), 2.0)) == TimeTick((Date("2023-01-01"), 2.0)) + @test TimeTick{DateTime,Float64}((Date("2023-01-01"), 2.0)) == TimeTick((DateTime("2023-01-01"), 2.0)) + @test TimeTick{DateTime,Float64}((DateTime("2023-01-01"), 2.0)) == TimeTick((DateTime("2023-01-01"), 2.0)) + @test TimeTick{NanoDate,Float64}((Date("2023-01-01"), 2.0)) == TimeTick((NanoDate("2023-01-01"), 2.0)) + @test TimeTick{Date,Float64}((DateTime("2023-01-01"), 2.0)) == TimeTick((Date("2023-01-01"), 2.0)) + @test TimeTick{Time,Float64}((DateTime("2023-01-01"), 2.0)) == TimeTick((Time("00:00:00"), 2.0)) + end + + @testset "Case №3: TimeTick from Pair" begin + @test TimeTick{Int64,Int64}(1.0 => 2.0) == TimeTick(1 => 2) + @test TimeTick{Float64,Float64}(1 => 2) == TimeTick(1.0 => 2.0) + @test TimeTick{Date,Float64}(DateTime("2023-01-01") => 2.0) == TimeTick(Date("2023-01-01") => 2.0) + @test TimeTick{DateTime,Float64}(Date("2023-01-01") => 2.0) == TimeTick(DateTime("2023-01-01") => 2.0) + @test TimeTick{DateTime,Float64}(DateTime("2023-01-01") => 2.0) == TimeTick(DateTime("2023-01-01") => 2.0) + @test TimeTick{NanoDate,Float64}(Date("2023-01-01") => 2.0) == TimeTick(NanoDate("2023-01-01") => 2.0) + @test TimeTick{Date,Float64}(DateTime("2023-01-01") => 2.0) == TimeTick(Date("2023-01-01") => 2.0) + @test TimeTick{Time,Float64}(DateTime("2023-01-01") => 2.0) == TimeTick(Time("00:00:00") => 2.0) + end + + @testset "Case №4: TimeTick from TimeTick" begin + @test TimeTick{Float64,Int64}(TimeTick{Int64,Float64}(1.0, 2)) == TimeTick(1.0, 2) + @test TimeTick{Date,Int64}(TimeTick{NanoDate,Float64}(DateTime("2023-01-01"), 2)) == TimeTick(Date("2023-01-01"), 2.0) + @test TimeTick{Time,Int64}(TimeTick{NanoDate,Float64}(DateTime("2023-01-01"), 2)) == TimeTick(Time("00:00:00"), 2.0) + @test TimeTick{DateTime,Int64}(TimeTick{NanoDate,Float64}(DateTime("2023-01-01"), 2)) == TimeTick(DateTime("2023-01-01"), 2.0) + end +end + +@testset verbose = true "TimeArrays constructors" begin + @testset "Case №1: TimeArray from TimeTicks" begin + date_ticks = [ + TimeTick{Date,Float64}(Date(2021), 1.0), + TimeTick{Date,Float64}(Date(2022), 2.0), + TimeTick{Date,Float64}(Date(2023), 3.0), + TimeTick{Date,Float64}(Date(2024), 4.0), + TimeTick{Date,Float64}(Date(2025), 5.0), + ] + + time_ticks = [ + TimeTick{Time,Float64}(Time(1), 1.0), + TimeTick{Time,Float64}(Time(2), 2.0), + TimeTick{Time,Float64}(Time(3), 3.0), + TimeTick{Time,Float64}(Time(4), 4.0), + TimeTick{Time,Float64}(Time(5), 5.0), + ] + + value_ticks = [ + TimeTick{Int64,Float64}(1, 1.0), + TimeTick{Int64,Float64}(2, 2.0), + TimeTick{Int64,Float64}(3, 3.0), + TimeTick{Int64,Float64}(4, 4.0), + TimeTick{Int64,Float64}(5, 5.0), + ] + + @test TimeArray{Date,Float64}(date_ticks) == TimeArray(date_ticks) + @test TimeArray{Date,Float64}(date_ticks) == TimeArray(reverse(date_ticks)) + + @test TimeArray{Time,Float64}(time_ticks) == TimeArray(time_ticks) + @test TimeArray{Time,Float64}(time_ticks) == TimeArray(reverse(time_ticks)) + + @test TimeArray{Int64,Float64}(value_ticks) == TimeArray(value_ticks) + @test TimeArray{Int64,Float64}(value_ticks) == TimeArray(reverse(value_ticks)) + end + + @testset "Case №2: TimeArray from Tuples" begin + date_tuples = [ + (Date(2021), 1.0), + (Date(2022), 2.0), + (Date(2023), 3.0), + (Date(2024), 4.0), + (Date(2025), 5.0), + ] + + time_tuples = [ + (Time(1), 1.0), + (Time(2), 2.0), + (Time(3), 3.0), + (Time(4), 4.0), + (Time(5), 5.0), + ] + + value_tuples = [ + (1, 1.0), + (2, 2.0), + (3, 3.0), + (4, 4.0), + (5, 5.0), + ] + + @test TimeArray{Date,Float64}(date_tuples) == TimeArray(date_tuples) + @test TimeArray{Date,Float64}(date_tuples) == TimeArray(reverse(date_tuples)) + + @test TimeArray{Time,Float64}(time_tuples) == TimeArray(time_tuples) + @test TimeArray{Time,Float64}(time_tuples) == TimeArray(reverse(time_tuples)) + + @test TimeArray{Int64,Float64}(value_tuples) == TimeArray(value_tuples) + @test TimeArray{Int64,Float64}(value_tuples) == TimeArray(reverse(value_tuples)) + end + + @testset "Case №3: TimeArray from Pairs" begin + date_pairs = [ + Date(2021) => 1.0, + Date(2022) => 2.0, + Date(2023) => 3.0, + Date(2024) => 4.0, + Date(2025) => 5.0, + ] + + time_pairs = [ + Time(1) => 1.0, + Time(2) => 2.0, + Time(3) => 3.0, + Time(4) => 4.0, + Time(5) => 5.0, + ] + + value_pairs = [ + 1 => 1.0, + 2 => 2.0, + 3 => 3.0, + 4 => 4.0, + 5 => 5.0, + ] + + @test TimeArray{Date,Float64}(date_pairs) == TimeArray(date_pairs) + @test TimeArray{Date,Float64}(date_pairs) == TimeArray(reverse(date_pairs)) + + @test TimeArray{Time,Float64}(time_pairs) == TimeArray(time_pairs) + @test TimeArray{Time,Float64}(time_pairs) == TimeArray(reverse(time_pairs)) + + @test TimeArray{Int64,Float64}(value_pairs) == TimeArray(value_pairs) + @test TimeArray{Int64,Float64}(value_pairs) == TimeArray(reverse(value_pairs)) + end + + @testset "Case №3: TimeArray from Anything" begin + date_anything = [ + TimeTick(Date(2021), 1.0), + (Date(2022), 2.0), + Date(2023) => 3.0, + ] + + time_anything = [ + TimeTick(Time(1), 1.0), + (Time(2), 2.0), + Time(3) => 3.0, + ] + + value_anything = [ + TimeTick(1, 1.0), + (2, 2.0), + 3 => 3.0, + ] + + @test TimeArray{Date,Float64}(date_anything) == TimeArray{Date,Float64}(reverse(date_anything)) + + @test TimeArray{Time,Float64}(time_anything) == TimeArray{Time,Float64}(reverse(time_anything)) + + @test TimeArray{Int64,Float64}(value_anything) == TimeArray{Int64,Float64}(reverse(value_anything)) + end + + @testset "Case №4: TimeArray from timestamps and values" begin + date_timestamps = [Date(2021), Date(2022), Date(2023), Date(2024), Date(2025)] + time_timestamps = [Time(1), Time(2), Time(3), Time(4), Time(5)] + value_timestamps = [1, 2, 3, 4, 5] + + values = [1.0, 2.0, 3.0, 4.0, 5.0] + + @test TimeArray(date_timestamps, values) == TimeArray(reverse(date_timestamps), reverse(values)) + + @test TimeArray(time_timestamps, values) == TimeArray(reverse(time_timestamps), reverse(values)) + + @test TimeArray(value_timestamps, values) == TimeArray(reverse(value_timestamps), reverse(values)) + end +end diff --git a/test/math.jl b/test/math.jl new file mode 100644 index 0000000..52aac64 --- /dev/null +++ b/test/math.jl @@ -0,0 +1,429 @@ +# math + +@testset verbose = true "Merge TimeArrays" begin + + left = TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(3), -2.0), + TimeTick(Time(4), 0.0), + ]) + + right = TimeArray([ + TimeTick(Time(2), -1.0), + TimeTick(Time(3), 0.0), + TimeTick(Time(5), 3.0), + ]) + + @testset "Case №1: Custom merge functions" begin + merged_max = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 1.0), + TimeTick(Time(3), 0.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(5), 3.0), + ]) + + @test isequal(merged_max, ta_mergewith(max, left, right)) + + merged_min = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), -1.0), + TimeTick(Time(3), -2.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(5), 0.0), + ]) + + @test isequal(merged_min, ta_mergewith(min, left, right)) + + merged_avg = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 0.0), + TimeTick(Time(3), -1.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(5), 1.5), + ]) + + @test isequal(merged_avg, ta_mergewith((x, y) -> (x + y) / 2.0, left, right)) + + merged_nan = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), NaN), + TimeTick(Time(3), NaN), + TimeTick(Time(4), NaN), + TimeTick(Time(5), NaN), + ]) + + @test isequal(merged_nan, ta_mergewith((x, y) -> NaN, left, right)) + end + + @testset "Case №2: Merge left timestamps" begin + left_avg = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(3), -1.0), + TimeTick(Time(4), 0.0), + ]) + + @test isequal(left_avg, ta_mergewith((x, y) -> (x + y) / 2.0, left, right, r_merge = false)) + end + + @testset "Case №3: Merge right timestamps" begin + right_avg = TimeArray([ + TimeTick(Time(2), 0.0), + TimeTick(Time(3), -1.0), + TimeTick(Time(5), 1.5), + ]) + + @test isequal(right_avg, ta_mergewith((x, y) -> (x + y) / 2.0, left, right, l_merge = false)) + end +end + +@testset verbose = true "Base arithmetic" begin + + a = TimeArray([ + TimeTick(Time(2), 1.0), + TimeTick(Time(4), 2.0), + TimeTick(Time(6), 3.0), + ]) + + @testset verbose = true "Scalar arithmetic" begin + + value = 2.0 + @testset "Case №1: Plus" begin + a_plus_value = TimeArray([ + TimeTick(Time(2), 3.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 5.0), + ]) + + @test isequal(a_plus_value, a + value) + end + + @testset "Case №2: Minus" begin + a_minus_value = TimeArray([ + TimeTick(Time(2), -1.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(6), 1.0), + ]) + + @test isequal(a_minus_value, a - value) + end + + @testset "Case №3: Multiply" begin + a_mul_value = TimeArray([ + TimeTick(Time(2), 2.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 6.0), + ]) + + @test isequal(a_mul_value, a * value) + end + + @testset "Case №4: Division" begin + a_div_value = TimeArray([ + TimeTick(Time(2), 0.5), + TimeTick(Time(4), 1.0), + TimeTick(Time(6), 3.0/2.0), + ]) + + @test isequal(a_div_value, a / value) + end + end + + @testset verbose = true "Identical timestamps" begin + @testset "Case №1: Plus" begin + a_plus_a = TimeArray([ + TimeTick(Time(2), 2.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 6.0), + ]) + + @test isequal(a_plus_a, ta_mergewith(+, a, a)) + @test isequal(a_plus_a, a + a) + end + + @testset "Case №2: Minus" begin + a_minus_a = TimeArray([ + TimeTick(Time(2), 0.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(6), 0.0), + ]) + + @test isequal(a_minus_a, ta_mergewith(-, a, a)) + @test isequal(a_minus_a, a - a) + end + + @testset "Case №3: Multiply" begin + a_mul_a = TimeArray([ + TimeTick(Time(2), 1.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 9.0), + ]) + + @test isequal(a_mul_a, ta_mergewith(*, a, a)) + @test isequal(a_mul_a, a * a) + end + + @testset "Case №4: Division" begin + a_div_a = TimeArray([ + TimeTick(Time(2), 1.0), + TimeTick(Time(4), 1.0), + TimeTick(Time(6), 1.0), + ]) + + @test isequal(a_div_a, ta_mergewith(/, a, a)) + @test isequal(a_div_a, a / a) + end + end + + @testset verbose = true "Shifted forward timestamps" begin + + b = TimeArray([ + TimeTick(Time(3), 1.0), + TimeTick(Time(5), 2.0), + TimeTick(Time(7), 3.0), + ]) + + @testset "Case №1: Plus" begin + a_plus_b = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 2.0), + TimeTick(Time(4), 3.0), + TimeTick(Time(5), 4.0), + TimeTick(Time(6), 5.0), + TimeTick(Time(7), 6.0), + ]) + + @test isequal(a_plus_b, ta_mergewith(+, a, b)) + @test isequal(a_plus_b, a + b) + end + + @testset "Case №2: Minus" begin + a_minus_b = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 0.0), + TimeTick(Time(4), 1.0), + TimeTick(Time(5), 0.0), + TimeTick(Time(6), 1.0), + TimeTick(Time(7), 0.0), + ]) + + @test isequal(a_minus_b, ta_mergewith(-, a, b)) + @test isequal(a_minus_b, a - b) + end + + @testset "Case №3: Multiply" begin + a_mul_b = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 1.0), + TimeTick(Time(4), 2.0), + TimeTick(Time(5), 4.0), + TimeTick(Time(6), 6.0), + TimeTick(Time(7), 9.0), + ]) + + @test isequal(a_mul_b, ta_mergewith(*, a, b)) + @test isequal(a_mul_b, a * b) + end + + @testset "Case №4: Division" begin + a_div_b = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 1.0), + TimeTick(Time(4), 2.0), + TimeTick(Time(5), 1.0), + TimeTick(Time(6), 1.5), + TimeTick(Time(7), 1.0), + ]) + + @test isequal(a_div_b, ta_mergewith(/, a, b)) + @test isequal(a_div_b, a / b) + end + end + + @testset verbose = true "Shifted backward timestamps" begin + + c = TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(3), 2.0), + TimeTick(Time(5), 3.0), + ]) + + @testset "Case №1: Plus" begin + a_plus_c = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 2.0), + TimeTick(Time(3), 3.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(5), 5.0), + TimeTick(Time(6), 6.0), + ]) + + @test isequal(a_plus_c, ta_mergewith(+, a, c)) + @test isequal(a_plus_c, a + c) + end + + @testset "Case №2: Minus" begin + a_minus_c = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 0.0), + TimeTick(Time(3), -1.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(5), -1.0), + TimeTick(Time(6), 0.0), + ]) + + @test isequal(a_minus_c, ta_mergewith(-, a, c)) + @test isequal(a_minus_c, a - c) + end + + @testset "Case №3: Multiply" begin + a_mul_c = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 1.0), + TimeTick(Time(3), 2.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(5), 6.0), + TimeTick(Time(6), 9.0), + ]) + + @test isequal(a_mul_c, ta_mergewith(*, a, c)) + @test isequal(a_mul_c, a * c) + end + + @testset "Case №4: Division" begin + a_div_c = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 1.0), + TimeTick(Time(3), 0.5), + TimeTick(Time(4), 1.0), + TimeTick(Time(5), 2/3), + TimeTick(Time(6), 1.0), + ]) + + @test isequal(a_div_c, ta_mergewith(/, a, c)) + @test isequal(a_div_c, a / c) + end + end + + @testset verbose = true "Outer bounds timestamps" begin + + d = TimeArray([ + TimeTick(Time(1), 1.0), + TimeTick(Time(4), 2.0), + TimeTick(Time(7), 3.0), + ]) + + @testset "Case №1: Plus" begin + a_plus_d = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 2.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 5.0), + TimeTick(Time(7), 6.0), + ]) + + @test isequal(a_plus_d, ta_mergewith(+, a, d)) + @test isequal(a_plus_d, a + d) + end + + @testset "Case №2: Minus" begin + a_minus_d = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 0.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(6), 1.0), + TimeTick(Time(7), 0.0), + ]) + + @test isequal(a_minus_d, ta_mergewith(-, a, d)) + @test isequal(a_minus_d, a - d) + end + + @testset "Case №3: Multiply" begin + a_mul_d = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 1.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(6), 6.0), + TimeTick(Time(7), 9.0), + ]) + + @test isequal(a_mul_d, ta_mergewith(*, a, d)) + @test isequal(a_mul_d, a * d) + end + + @testset "Case №4: Division" begin + a_div_d = TimeArray([ + TimeTick(Time(1), NaN), + TimeTick(Time(2), 1.0), + TimeTick(Time(4), 1.0), + TimeTick(Time(6), 1.5), + TimeTick(Time(7), 1.0), + ]) + + @test isequal(a_div_d, ta_mergewith(/, a, d)) + @test isequal(a_div_d, a / d) + end + end + + @testset verbose = true "Inner bounds timestamps" begin + + e = TimeArray([ + TimeTick(Time(3), 1.0), + TimeTick(Time(4), 2.0), + TimeTick(Time(5), 3.0), + ]) + + @testset "Case №1: Plus" begin + a_plus_e = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 2.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(5), 5.0), + TimeTick(Time(6), 6.0), + ]) + + @test isequal(a_plus_e, ta_mergewith(+, a, e)) + @test isequal(a_plus_e, a + e) + end + + @testset "Case №2: Minus" begin + a_minus_e = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 0.0), + TimeTick(Time(4), 0.0), + TimeTick(Time(5), -1.0), + TimeTick(Time(6), 0.0), + ]) + + @test isequal(a_minus_e, ta_mergewith(-, a, e)) + @test isequal(a_minus_e, a - e) + end + + @testset "Case №3: Multiply" begin + a_mul_e = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 1.0), + TimeTick(Time(4), 4.0), + TimeTick(Time(5), 6.0), + TimeTick(Time(6), 9.0), + ]) + + @test isequal(a_mul_e, ta_mergewith(*, a, e)) + @test isequal(a_mul_e, a * e) + end + + @testset "Case №4: Division" begin + a_div_e = TimeArray([ + TimeTick(Time(2), NaN), + TimeTick(Time(3), 1.0), + TimeTick(Time(4), 1.0), + TimeTick(Time(5), 2/3), + TimeTick(Time(6), 1.0), + ]) + + @test isequal(a_div_e, ta_mergewith(/, a, e)) + @test isequal(a_div_e, a / e) + end + end +end diff --git a/test/resample.jl b/test/resample.jl new file mode 100644 index 0000000..2487824 --- /dev/null +++ b/test/resample.jl @@ -0,0 +1,1140 @@ +# resample + +@testset verbose = true "Resampling" begin + + @testset "Case №1: Resample empty" begin + @test ta_resample(sum, TimeArray{DateTime,Float64}(), Day(1)) |> isempty + end + + @testset "Case №3: Resample custom func" begin + custom_ta = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("1978-10-15T00:00:00"), 1), + TimeTick(DateTime("1978-10-15T03:00:00"), 2), + TimeTick(DateTime("1978-10-15T12:00:00"), 3), + TimeTick(DateTime("1978-10-16T00:00:00"), 4), + ]) + + @test isequal(TimeArray{DateTime,Float64}([ + TimeTick(DateTime("1978-10-15T00:00:00"), 42.0), + TimeTick(DateTime("1978-10-16T00:00:00"), 42.0), + ]), + ta_resample(vec -> 42, custom_ta, Day(1)) + ) + + @test isequal(TimeArray{DateTime,Float64}([ + TimeTick(DateTime("1978-10-15T00:00:00"), 14), + TimeTick(DateTime("1978-10-16T00:00:00"), 16), + ]), + ta_resample(vec -> sum(vec .^ 2), custom_ta, Day(1)), + ) + end + + @testset "Case №4: Resample custom func with empty" begin + empty_custom_ta = TimeArray{DateTime,Float64}([ + TimeTick(DateTime("1978-10-15T00:00:00"), 1), + TimeTick(DateTime("1978-10-16T00:00:00"), 4), + ]) + + @test isequal(TimeArray{DateTime,Float64}([ + TimeTick(DateTime("1978-10-15T00:00:00"), 1.0), + TimeTick(DateTime("1978-10-15T12:00:00"), 0.0), + TimeTick(DateTime("1978-10-16T00:00:00"), 16.0), + ]), + ta_resample(vec -> sum(vec .^ 2), empty_custom_ta, Hour(12)) + ) + end + + @testset "Case №5: Resample Real timestamps" begin + real_ta = TimeArray{Int64,Float64}([(1, 1), (2, 2), (3, 3)]) + + @test ta_resample(first, real_ta, 1) == real_ta + @test ta_resample(first, real_ta, 2) == TimeArray{Int64,Float64}([(0, 1.0), (2, 2.0)]) + end + + @testset "Case №6: Resample Date" begin + date_ta = TimeArray{Date,Float64}([ + TimeTick(Date("2022-02-01"), 1), + TimeTick(Date("2022-02-17"), 2), + TimeTick(Date("2022-03-02"), 3), + ]) + + @test isequal(TimeArray{Date,Float64}([ + TimeTick(Date("2022-01-31"), 1.0), + TimeTick(Date("2022-02-15"), 2.0), + TimeTick(Date("2022-03-02"), 3.0), + ]), + ta_resample(first, date_ta, Day(15)) + ) + + @test isequal(TimeArray{Date,Float64}([ + TimeTick(Date("2022-01-29"), 1.0), + TimeTick(Date("2022-02-12"), 2.0), + TimeTick(Date("2022-02-26"), 3.0), + ]), + ta_resample(first, date_ta, Week(2)) + ) + + @test isequal(TimeArray{Date,Float64}([ + TimeTick(Date("2022-02-01"), 1.0), + TimeTick(Date("2022-03-01"), 3.0), + ]), + ta_resample(first, date_ta, Month(1)) + ) + end +end + +@testset verbose = true "Pandas resampling" begin + test_ta = TimeArray{DateTime,Float64}([ + (DateTime("2024-01-01T00:01:00"), 508), + (DateTime("2024-01-01T00:29:00"), 925), + (DateTime("2024-01-01T00:44:00"), 911), + (DateTime("2024-01-01T01:12:00"), 998), + (DateTime("2024-01-01T01:17:00"), 93), + (DateTime("2024-01-01T01:28:00"), 928), + (DateTime("2024-01-01T01:29:00"), 9), + (DateTime("2024-01-01T01:31:00"), 587), + (DateTime("2024-01-01T02:24:00"), 527), + (DateTime("2024-01-01T03:04:00"), 836), + (DateTime("2024-01-01T03:16:00"), 469), + (DateTime("2024-01-01T03:25:00"), 750), + (DateTime("2024-01-01T03:53:00"), 259), + (DateTime("2024-01-01T04:14:00"), 843), + (DateTime("2024-01-01T04:49:00"), 792), + ]) + + @testset "Case №1:{'closed': 'left', 'label': 'left', 'origin': 'start'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_LEFT, + label = LABEL_LEFT, + origin = START_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 716.5), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 507.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 685.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 1433.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 2028.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 0.0), + TimeTick(DateTime("2024-01-01T03:01:00"), 2055.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 9.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 9.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 2), + TimeTick(DateTime("2024-01-01T00:31:00"), 1), + TimeTick(DateTime("2024-01-01T01:01:00"), 4), + TimeTick(DateTime("2024-01-01T01:31:00"), 1), + TimeTick(DateTime("2024-01-01T02:01:00"), 1), + TimeTick(DateTime("2024-01-01T02:31:00"), 0), + TimeTick(DateTime("2024-01-01T03:01:00"), 3), + TimeTick(DateTime("2024-01-01T03:31:00"), 1), + TimeTick(DateTime("2024-01-01T04:01:00"), 1), + TimeTick(DateTime("2024-01-01T04:31:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №2:{'closed': 'right', 'label': 'left', 'origin': 'start'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_RIGHT, + label = LABEL_LEFT, + origin = START_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 523.0), + TimeTick(DateTime("2024-01-01T01:31:00"), NaN), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 685.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 2615.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 0.0), + TimeTick(DateTime("2024-01-01T03:01:00"), 2055.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:31:00"), NaN), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 9.0), + TimeTick(DateTime("2024-01-01T01:31:00"), NaN), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:31:00"), NaN), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:01:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T01:31:00"), NaN), + TimeTick(DateTime("2024-01-01T02:01:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:31:00"), NaN), + TimeTick(DateTime("2024-01-01T03:01:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:31:00"), 1), + TimeTick(DateTime("2024-01-01T00:01:00"), 1), + TimeTick(DateTime("2024-01-01T00:31:00"), 1), + TimeTick(DateTime("2024-01-01T01:01:00"), 5), + TimeTick(DateTime("2024-01-01T01:31:00"), 0), + TimeTick(DateTime("2024-01-01T02:01:00"), 1), + TimeTick(DateTime("2024-01-01T02:31:00"), 0), + TimeTick(DateTime("2024-01-01T03:01:00"), 3), + TimeTick(DateTime("2024-01-01T03:31:00"), 1), + TimeTick(DateTime("2024-01-01T04:01:00"), 1), + TimeTick(DateTime("2024-01-01T04:31:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №3:{'closed': 'left', 'label': 'right', 'origin': 'start'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_LEFT, + label = LABEL_RIGHT, + origin = START_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 716.5), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 507.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 685.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 1433.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 2028.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), 0.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 2055.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 998.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 836.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 9.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 469.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 508.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 998.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 836.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 9.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:31:00"), 2), + TimeTick(DateTime("2024-01-01T01:01:00"), 1), + TimeTick(DateTime("2024-01-01T01:31:00"), 4), + TimeTick(DateTime("2024-01-01T02:01:00"), 1), + TimeTick(DateTime("2024-01-01T02:31:00"), 1), + TimeTick(DateTime("2024-01-01T03:01:00"), 0), + TimeTick(DateTime("2024-01-01T03:31:00"), 3), + TimeTick(DateTime("2024-01-01T04:01:00"), 1), + TimeTick(DateTime("2024-01-01T04:31:00"), 1), + TimeTick(DateTime("2024-01-01T05:01:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №4:{'closed': 'right', 'label': 'right', 'origin': 'start'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_RIGHT, + label = LABEL_RIGHT, + origin = START_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 523.0), + TimeTick(DateTime("2024-01-01T02:01:00"), NaN), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 685.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(sum, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 2615.0), + TimeTick(DateTime("2024-01-01T02:01:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), 0.0), + TimeTick(DateTime("2024-01-01T03:31:00"), 2055.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 998.0), + TimeTick(DateTime("2024-01-01T02:01:00"), NaN), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 836.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 9.0), + TimeTick(DateTime("2024-01-01T02:01:00"), NaN), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 469.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 998.0), + TimeTick(DateTime("2024-01-01T02:01:00"), NaN), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 836.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:31:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:01:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:31:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:01:00"), NaN), + TimeTick(DateTime("2024-01-01T02:31:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:01:00"), NaN), + TimeTick(DateTime("2024-01-01T03:31:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:01:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:31:00"), 843.0), + TimeTick(DateTime("2024-01-01T05:01:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = START_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:01:00"), 1), + TimeTick(DateTime("2024-01-01T00:31:00"), 1), + TimeTick(DateTime("2024-01-01T01:01:00"), 1), + TimeTick(DateTime("2024-01-01T01:31:00"), 5), + TimeTick(DateTime("2024-01-01T02:01:00"), 0), + TimeTick(DateTime("2024-01-01T02:31:00"), 1), + TimeTick(DateTime("2024-01-01T03:01:00"), 0), + TimeTick(DateTime("2024-01-01T03:31:00"), 3), + TimeTick(DateTime("2024-01-01T04:01:00"), 1), + TimeTick(DateTime("2024-01-01T04:31:00"), 1), + TimeTick(DateTime("2024-01-01T05:01:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №5:{'closed': 'left', 'label': 'left', 'origin': 'end'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_LEFT, + label = LABEL_LEFT, + origin = END_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 918.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 545.5), + TimeTick(DateTime("2024-01-01T01:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 652.5), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 551.0), + TimeTick(DateTime("2024-01-01T04:19:00"), NaN), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 1836.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 1091.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 1524.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 1305.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 1102.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 0.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 928.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:19:00"), NaN), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 911.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 9.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:19:00"), NaN), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 928.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:19:00"), NaN), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 911.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 587.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:19:00"), NaN), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(length, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 1), + TimeTick(DateTime("2024-01-01T00:19:00"), 2), + TimeTick(DateTime("2024-01-01T00:49:00"), 2), + TimeTick(DateTime("2024-01-01T01:19:00"), 3), + TimeTick(DateTime("2024-01-01T01:49:00"), 0), + TimeTick(DateTime("2024-01-01T02:19:00"), 1), + TimeTick(DateTime("2024-01-01T02:49:00"), 2), + TimeTick(DateTime("2024-01-01T03:19:00"), 1), + TimeTick(DateTime("2024-01-01T03:49:00"), 2), + TimeTick(DateTime("2024-01-01T04:19:00"), 0), + TimeTick(DateTime("2024-01-01T04:49:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №6:{'closed': 'right', 'label': 'left', 'origin': 'end'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_RIGHT, + label = LABEL_LEFT, + origin = END_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 918.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 545.5), + TimeTick(DateTime("2024-01-01T01:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 652.5), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 551.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 1836.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 1091.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 1524.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 1305.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 1102.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 928.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 911.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 9.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 925.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 928.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:19:00"), 911.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 587.0), + TimeTick(DateTime("2024-01-01T01:49:00"), NaN), + TimeTick(DateTime("2024-01-01T02:19:00"), 527.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 750.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_LEFT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2023-12-31T23:49:00"), 1), + TimeTick(DateTime("2024-01-01T00:19:00"), 2), + TimeTick(DateTime("2024-01-01T00:49:00"), 2), + TimeTick(DateTime("2024-01-01T01:19:00"), 3), + TimeTick(DateTime("2024-01-01T01:49:00"), 0), + TimeTick(DateTime("2024-01-01T02:19:00"), 1), + TimeTick(DateTime("2024-01-01T02:49:00"), 2), + TimeTick(DateTime("2024-01-01T03:19:00"), 1), + TimeTick(DateTime("2024-01-01T03:49:00"), 2), + TimeTick(DateTime("2024-01-01T04:19:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №7:{'closed': 'left', 'label': 'right', 'origin': 'end'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_LEFT, + label = LABEL_RIGHT, + origin = END_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 918.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 545.5), + TimeTick(DateTime("2024-01-01T01:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 652.5), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 551.0), + TimeTick(DateTime("2024-01-01T04:49:00"), NaN), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 1836.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 1091.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 1524.0), + TimeTick(DateTime("2024-01-01T02:19:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 1305.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 1102.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 0.0), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 928.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:49:00"), NaN), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 9.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:49:00"), NaN), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 928.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:49:00"), NaN), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:49:00"), NaN), + TimeTick(DateTime("2024-01-01T05:19:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_LEFT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 1), + TimeTick(DateTime("2024-01-01T00:49:00"), 2), + TimeTick(DateTime("2024-01-01T01:19:00"), 2), + TimeTick(DateTime("2024-01-01T01:49:00"), 3), + TimeTick(DateTime("2024-01-01T02:19:00"), 0), + TimeTick(DateTime("2024-01-01T02:49:00"), 1), + TimeTick(DateTime("2024-01-01T03:19:00"), 2), + TimeTick(DateTime("2024-01-01T03:49:00"), 1), + TimeTick(DateTime("2024-01-01T04:19:00"), 2), + TimeTick(DateTime("2024-01-01T04:49:00"), 0), + TimeTick(DateTime("2024-01-01T05:19:00"), 1), + ]), + sampled, + ) + end + + @testset "Case №8:{'closed': 'right', 'label': 'right', 'origin': 'end'}" begin + sampled = ta_resample( + x -> isempty(x) ? NaN : mean(x), + test_ta, + Minute(30), + closed = CLOSED_RIGHT, + label = LABEL_RIGHT, + origin = END_OF_WINDOW, + ) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 918.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 545.5), + TimeTick(DateTime("2024-01-01T01:49:00"), 508.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 652.5), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 551.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(sum, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 1836.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 1091.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 1524.0), + TimeTick(DateTime("2024-01-01T02:19:00"), 0.0), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 1305.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 1102.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : maximum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 928.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : minimum(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 9.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(x -> isempty(x) ? NaN : first(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 925.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 998.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 928.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 836.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 259.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = ta_resample(x -> isempty(x) ? NaN : last(x), test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 508.0), + TimeTick(DateTime("2024-01-01T00:49:00"), 911.0), + TimeTick(DateTime("2024-01-01T01:19:00"), 93.0), + TimeTick(DateTime("2024-01-01T01:49:00"), 587.0), + TimeTick(DateTime("2024-01-01T02:19:00"), NaN), + TimeTick(DateTime("2024-01-01T02:49:00"), 527.0), + TimeTick(DateTime("2024-01-01T03:19:00"), 469.0), + TimeTick(DateTime("2024-01-01T03:49:00"), 750.0), + TimeTick(DateTime("2024-01-01T04:19:00"), 843.0), + TimeTick(DateTime("2024-01-01T04:49:00"), 792.0), + ]), + sampled, + ) + sampled = + ta_resample(length, test_ta, Minute(30), closed = CLOSED_RIGHT, label = LABEL_RIGHT, origin = END_OF_WINDOW) + @test isequal( + TimeArray{DateTime,Float64}([ + TimeTick(DateTime("2024-01-01T00:19:00"), 1), + TimeTick(DateTime("2024-01-01T00:49:00"), 2), + TimeTick(DateTime("2024-01-01T01:19:00"), 2), + TimeTick(DateTime("2024-01-01T01:49:00"), 3), + TimeTick(DateTime("2024-01-01T02:19:00"), 0), + TimeTick(DateTime("2024-01-01T02:49:00"), 1), + TimeTick(DateTime("2024-01-01T03:19:00"), 2), + TimeTick(DateTime("2024-01-01T03:49:00"), 1), + TimeTick(DateTime("2024-01-01T04:19:00"), 2), + TimeTick(DateTime("2024-01-01T04:49:00"), 1), + ]), + sampled, + ) + end +end diff --git a/test/rolling.jl b/test/rolling.jl new file mode 100644 index 0000000..ee80773 --- /dev/null +++ b/test/rolling.jl @@ -0,0 +1,311 @@ +# rolling + +@testset verbose = true "" begin + @testset "Case №1: Fixed window" begin + ta_for_window = TimeArray([ + TimeTick(DateTime(2024, 1, 1), 1.0), + TimeTick(DateTime(2024, 1, 2), 2.0), + TimeTick(DateTime(2024, 1, 5), 3.0), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]) + + @test isequal( + ta_rolling(sum, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 10.0), + TimeTick(DateTime(2024, 1, 7), 14.0), + TimeTick(DateTime(2024, 1, 15), 18.0), + ]), + ) + + @test isequal( + ta_rolling(mean, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 2.5), + TimeTick(DateTime(2024, 1, 7), 3.5), + TimeTick(DateTime(2024, 1, 15), 4.5), + ]), + ) + + @test isequal( + ta_rolling(maximum, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(minimum, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 1.0), + TimeTick(DateTime(2024, 1, 7), 2.0), + TimeTick(DateTime(2024, 1, 15), 3.0), + ]), + ) + + @test isequal( + ta_rolling(first, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 1.0), + TimeTick(DateTime(2024, 1, 7), 2.0), + TimeTick(DateTime(2024, 1, 15), 3.0), + ]), + ) + + @test isequal( + ta_rolling(last, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(median, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 2.5), + TimeTick(DateTime(2024, 1, 7), 3.5), + TimeTick(DateTime(2024, 1, 15), 4.5), + ]), + ) + + @test isequal( + ta_rolling(std, ta_for_window, 4), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), 1.2909944487358056), + TimeTick(DateTime(2024, 1, 7), 1.2909944487358056), + TimeTick(DateTime(2024, 1, 15), 1.2909944487358056), + ]), + ) + end + + @testset "Case №2: Periodic window" begin + ta_for_window = TimeArray([ + TimeTick(DateTime(2024, 1, 1), 1.0), + TimeTick(DateTime(2024, 1, 2), 2.0), + TimeTick(DateTime(2024, 1, 5), 3.0), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]) + + @test isequal( + ta_rolling(sum, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 3.0), + TimeTick(DateTime(2024, 1, 5), 5.0), + TimeTick(DateTime(2024, 1, 6), 7.0), + TimeTick(DateTime(2024, 1, 7), 12.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(mean, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 1.5), + TimeTick(DateTime(2024, 1, 5), 2.5), + TimeTick(DateTime(2024, 1, 6), 3.5), + TimeTick(DateTime(2024, 1, 7), 4.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(maximum, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 2.0), + TimeTick(DateTime(2024, 1, 5), 3.0), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(minimum, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 1.0), + TimeTick(DateTime(2024, 1, 5), 2.0), + TimeTick(DateTime(2024, 1, 6), 3.0), + TimeTick(DateTime(2024, 1, 7), 3.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(first, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 1.0), + TimeTick(DateTime(2024, 1, 5), 2.0), + TimeTick(DateTime(2024, 1, 6), 3.0), + TimeTick(DateTime(2024, 1, 7), 3.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(last, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 2.0), + TimeTick(DateTime(2024, 1, 5), 3.0), + TimeTick(DateTime(2024, 1, 6), 4.0), + TimeTick(DateTime(2024, 1, 7), 5.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(median, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 1.5), + TimeTick(DateTime(2024, 1, 5), 2.5), + TimeTick(DateTime(2024, 1, 6), 3.5), + TimeTick(DateTime(2024, 1, 7), 4.0), + TimeTick(DateTime(2024, 1, 15), 6.0), + ]), + ) + + @test isequal( + ta_rolling(std, ta_for_window, Day(4)), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), 0.7071067811865476), + TimeTick(DateTime(2024, 1, 5), 0.7071067811865476), + TimeTick(DateTime(2024, 1, 6), 0.7071067811865476), + TimeTick(DateTime(2024, 1, 7), 1.0), + TimeTick(DateTime(2024, 1, 15), NaN), + ]), + ) + end + + @testset "Case №3: SMA" begin + sma_date = TimeArray([ + TimeTick(DateTime(2021, 7), 1.0), + TimeTick(DateTime(2021, 12), 2.0), + TimeTick(DateTime(2022, 2), 3.0), + TimeTick(DateTime(2023, 3), 4.0), + TimeTick(DateTime(2023, 4), 5.0), + TimeTick(DateTime(2024, 6), 6.0), + ]) + + @test isequal( + ta_sma(sma_date, 2), + TimeArray([ + TimeTick(DateTime(2021, 7), NaN), + TimeTick(DateTime(2021, 12), 1.5), + TimeTick(DateTime(2022, 2), 2.5), + TimeTick(DateTime(2023, 3), 3.5), + TimeTick(DateTime(2023, 4), 4.5), + TimeTick(DateTime(2024, 6), 5.5), + ]), + ) + + @test isequal( + ta_sma(sma_date, 4), + TimeArray([ + TimeTick(DateTime(2021, 7), NaN), + TimeTick(DateTime(2021, 12), NaN), + TimeTick(DateTime(2022, 2), NaN), + TimeTick(DateTime(2023, 3), 2.5), + TimeTick(DateTime(2023, 4), 3.5), + TimeTick(DateTime(2024, 6), 4.5), + ]), + ) + + @test isequal( + ta_sma(sma_date, Month(6)), + TimeArray([ + TimeTick(DateTime(2021, 7), NaN), + TimeTick(DateTime(2021, 12), 1.5), + TimeTick(DateTime(2022, 2), 2.5), + TimeTick(DateTime(2023, 3), 4.0), + TimeTick(DateTime(2023, 4), 4.5), + TimeTick(DateTime(2024, 6), 6.0), + ]), + ) + + @test isequal( + ta_sma(sma_date, Year(1)), + TimeArray([ + TimeTick(DateTime(2021, 7), NaN), + TimeTick(DateTime(2021, 12), NaN), + TimeTick(DateTime(2022, 2), 2.0), + TimeTick(DateTime(2023, 3), 4.0), + TimeTick(DateTime(2023, 4), 4.5), + TimeTick(DateTime(2024, 6), 6.0), + ]), + ) + end + + @testset "Case №4: Lag" begin + ta_for_lag = TimeArray([ + TimeTick(DateTime(2024, 1, 1), 1.0), + TimeTick(DateTime(2024, 1, 2), 2.0), + TimeTick(DateTime(2024, 1, 3), 3.0), + TimeTick(DateTime(2024, 1, 4), 4.0), + TimeTick(DateTime(2024, 1, 5), 5.0), + TimeTick(DateTime(2024, 1, 6), 6.0), + ]) + + @test isequal( + ta_lag(ta_for_lag, 3), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 3), NaN), + TimeTick(DateTime(2024, 1, 4), 1.0), + TimeTick(DateTime(2024, 1, 5), 2.0), + TimeTick(DateTime(2024, 1, 6), 3.0), + ]), + ) + + @test isequal( + ta_lag(ta_for_lag, 10), + TimeArray([ + TimeTick(DateTime(2024, 1, 1), NaN), + TimeTick(DateTime(2024, 1, 2), NaN), + TimeTick(DateTime(2024, 1, 3), NaN), + TimeTick(DateTime(2024, 1, 4), NaN), + TimeTick(DateTime(2024, 1, 5), NaN), + TimeTick(DateTime(2024, 1, 6), NaN), + ]), + ) + end +end diff --git a/test/runtests.jl b/test/runtests.jl new file mode 100644 index 0000000..6daf159 --- /dev/null +++ b/test/runtests.jl @@ -0,0 +1,14 @@ +# runtests + +using Test +using Dates +using NanoDates +using Statistics +using TimeArrays + +include("interface.jl") +include("math.jl") +include("array.jl") +include("rolling.jl") +include("resample.jl") +include("custom_type.jl")