diff --git a/.github/workflows/quarto-publish.yml b/.github/workflows/quarto-publish.yml new file mode 100644 index 0000000..662bcd4 --- /dev/null +++ b/.github/workflows/quarto-publish.yml @@ -0,0 +1,43 @@ +on: + push: + branches: main + +name: Render and Publish + +jobs: + build-deploy: + runs-on: ubuntu-latest + steps: + - name: Check out repository + uses: actions/checkout@v2 + + - name: Set up Quarto + uses: quarto-dev/quarto-actions/setup@v2 + with: + tinytex: true + # Uncomment below and fill to pin a version + # version: 0.9.600 + + # Set up Python + - name: Set up Python + uses: actions/setup-python@v2 + with: + python-version: '3.x' # or specify a specific version like '3.8' + + # Add your Python dependencies installation here if needed + - name: Install Python dependencies + run: | + python -m pip install --upgrade pip + # Add any other dependencies you need, for example: + pip install jupyter numpy scipy + + # If you need to run a Python script before rendering the Quarto file + #- name: Run Python Script + # run: python path_to_your_script.py + + - name: Publish to GitHub Pages (and render) + uses: quarto-dev/quarto-actions/publish@v2 + with: + target: gh-pages + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # This secret is always available for GitHub actions diff --git a/01-Introduction/LICENSE b/01-Introduction/LICENSE deleted file mode 100644 index 72a6d36..0000000 --- a/01-Introduction/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -The MIT License (MIT) - -Copyright (c) 2016 Carmine Spagnuolo - -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/05-Regression/03-Scipts/Survival-Analysis-Basics.html b/05-Regression/03-Scipts/Survival-Analysis-Basics.html deleted file mode 100644 index fc51017..0000000 --- a/05-Regression/03-Scipts/Survival-Analysis-Basics.html +++ /dev/null @@ -1,887 +0,0 @@ - - - - - - - - - - - - - - - -Kiến thức cơ bản về phân tích Survival - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Phân tích sự sống sót tương ứng với tập hợp các phương pháp thống kê được sử dụng để điều tra thời gian xảy ra một sự kiện quan tâm.

-

Phân tích sự sống sót được sử dụng trong nhiều lĩnh vực như:

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    -
  • Các nghiên cứu ung thư phân tích thời gian sống sót của bệnh nhân,
    • -
  • Xã hội học để “phân tích lịch sử sự kiện”,
    • -
  • Trong kỹ thuật “phân tích thời gian thất bại”,
    • -
  • Và trong lĩnh vực Ngân hàng “phân tích thời gian khách hàng vỡ nợ”.
    • -
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Trong các bài toán về rủi ro ngân hàng, các câu hỏi nghiên cứu điển hình như:

-
    -
  • Tác động của các đặc điểm của khách hàng nhất định đối đối với khả năng vỡ nợ là gì ?
    • -
  • Xác suất để một khách hàng vỡ nợ sau 12 tháng là bao nhiêu?
    • -
  • Có sự khác biệt về khả năng vỡ nợ giữa các nhóm khách hàng không?
    • -
-
-

1 Mục tiêu

-

Mục đích của chương này là mô tả các khái niệm cơ bản của phân tích sự sống còn. Trong các nghiên cứu ung thư, hầu hết các phân tích tỷ lệ sống sót sử dụng các phương pháp sau:

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    -
  • Biểu đồ Kaplan-Meier vẽ các đường cong sinh tồn
    • -
  • Log-rank test để so sánh các đường cong sống sót của hai hoặc nhiều nhóm
    • -
  • Hồi quy mối nguy theo tỷ lệ cox để mô tả ảnh hưởng của các biến đối với tỷ lệ sống sót. Mô hình Cox được thảo luận trong chương tiếp theo: Mô hình mối nguy theo tỷ lệ Cox .
    • -
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Ở đây, chúng ta sẽ bắt đầu bằng cách giải thích các khái niệm cơ bản về phân tích sự sống còn, bao gồm:

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    -
  • Cách tạo và diễn giải các đường cong sinh tồn,
    • -
  • và cách định lượng và kiểm tra sự khác biệt về khả năng sống sót giữa hai hoặc nhiều nhóm bệnh nhân.
    • -
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Sau đó, chúng ta sẽ tiếp tục bằng cách mô tả phân tích đa biến sử dụng mô hình nguy cơ tỷ lệ Cox .

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2 Các khái niệm cơ bản

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Ở đây, chúng ta bắt đầu bằng cách xác định các thuật ngữ cơ bản của phân tích sự sống còn bao gồm:

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    -
  • Thời gian tồn tại và sự kiện
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  • Nhóm kiểm chứng (censoring)
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  • Hàm sinh tồn và hàm nguy cơ
    • -
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2.1 Thời gian sống sót và loại sự kiện trong nghiên cứu ung thư

-

Có nhiều loại sự kiện khác nhau, bao gồm:

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    -
  • Tái phát (Relapse)
    • -
  • Sự tiến triển (Progression)
    • -
  • Cái chết (Death)
    • -
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Hai thước đo quan trọng nhất trong nghiên cứu ung thư bao gồm: i) thời gian chết ; và ii) thời gian sống sót không tái phát, tương ứng với thời gian từ khi đáp ứng điều trị đến khi bệnh tái phát. Nó còn được gọi là thời gian sống sót không bệnh tật và thời gian sống sót không biến cố.

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2.2 Nhóm kiểm chứng (censoring)

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Như đã đề cập ở trên, phân tích khả năng sống sót tập trung vào khoảng thời gian dự kiến cho đến khi xảy ra một sự kiện quan tâm (tái phát hoặc tử vong). Tuy nhiên, sự kiện có thể không xảy ra đối với một số cá nhân trong khoảng thời gian nghiên cứu, gọi là quan sát được kiểm chứng.

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Nhóm kiểm chứng có thể phát sinh theo những cách sau:

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    -
  • một bệnh nhân chưa trải qua sự kiện đang quan tâm, chẳng hạn như tái phát hoặc tử vong, trong khoảng thời gian nghiên cứu;
    • -
  • một bệnh nhân bị mất theo dõi trong thời gian nghiên cứu;
    • -
  • một bệnh nhân trải qua một sự kiện khác khiến không thể theo dõi thêm.
    • -
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Loại kiểm chứng này, được đặt tên là right censoring, được xử lý trong phân tích Sống sót.

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2.3 Hàm sinh tồn và nguy cơ (survival and hazard functions)

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Hai xác suất liên quan được sử dụng để mô tả dữ liệu sống sót: xác suất sống sót và xác suất nguy cơ.

-

Xác suất sống sót, còn được gọi là hàm sống sót, là xác suất mà một cá nhân sống sót từ thời gian gốc (ví dụ chẩn đoán ung thư) đến một thời điểm cụ thể trong tương lai.S(t)

-

Nguy cơ, được ký hiệu là h(t), là xác suất mà một cá nhân đang được quan sát tại thời điểm t xảy ra sự kiện trong thời gian quan sát.

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-
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3 Ước tính sống sót của Kaplan-Meier

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Phương pháp Kaplan-Meier (KM) là một phương pháp phi tham số được sử dụng để ước tính xác suất sống sót từ các thời gian sống sót đã được quan sát (Kaplan và Meier, 1958).

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Xác suất sống sót tại thời điểm \(t_i\), \(S(t_i)\), được tính như sau:

-

\[S(t_i) = S(t_{i-1})(1-\frac{d_i}{n_i})\]

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Trong đó:

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    -
  • \(S(t_{i-1})\): xác suất sống sót tại \(t_i\)
    • -
  • \(n_i\): số bệnh nhân còn sống ngay trước \(t_i\)
    • -
  • \(d_i\): số sự kiện tại \(t_i\)
    • -
  • \(t_0 = 0\), \(S (0) = 1\)
    • -
-

Xác suất ước tính (\(S(t)\)) là một step function chỉ thay đổi giá trị tại thời điểm của mỗi sự kiện. Cũng có thể tính toán khoảng tin cậy cho xác suất sống sót.

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Đường cong tỷ lệ sống sót của KM, một biểu đồ về xác suất sống sót của KM theo thời gian, cung cấp một bản tóm tắt hữu ích về dữ liệu có thể được sử dụng để ước tính các biện pháp như thời gian sống sót trung bình.

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4 Phân tích sống sót trên R

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-

4.1 Cài đặt và sử dụng 2 packages

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    -
  • survival cho tính toán các phân tích tồn tại
    • -
  • survminer cho để tóm tắt và vẽ hình kết quả phân tích sự sống sót
    • -
-
library("survival")
-library("survminer")
-
## Loading required package: ggplot2
-
## Loading required package: ggpubr
-
## 
-## Attaching package: 'survminer'
-
## The following object is masked from 'package:survival':
-## 
-##     myeloma
-
-
-

4.2 Dữ liệu

-

Chúng tôi sẽ sử dụng dữ liệu ung thư phổi có sẵn trong gói survival.

-
head(lung)
-
##   inst time status age sex ph.ecog ph.karno pat.karno meal.cal wt.loss
-## 1    3  306      2  74   1       1       90       100     1175      NA
-## 2    3  455      2  68   1       0       90        90     1225      15
-## 3    3 1010      1  56   1       0       90        90       NA      15
-## 4    5  210      2  57   1       1       90        60     1150      11
-## 5    1  883      2  60   1       0      100        90       NA       0
-## 6   12 1022      1  74   1       1       50        80      513       0
-
    -
  • inst: Mã tổ chức
    • -
  • time: Thời gian tồn tại tính bằng ngày
    • -
  • status: trạng thái kiểm chứng 1 = kiểm chứng, 2 = chết
    • -
  • age: Tuổi tính theo năm
    • -
  • sex: Nam = 1, Nữ = 2
    • -
  • ph.ecog: Điểm hiệu suất ECOG (0 = tốt 5 = chết)
    • -
  • ph.karno: Điểm hiệu suất của Karnofsky (xấu = 0-tốt = 100) do bác sĩ đánh giá
    • -
  • pat.karno: Điểm hiệu suất của Karnofsky theo đánh giá của bệnh nhân
    • -
  • meal.cal: Lượng calo tiêu thụ trong bữa ăn
    • -
  • wt.loss: Giảm cân trong sáu tháng qua
    • -
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-
-

4.3 Tính toán các đường cong sinh tồn: survfit ()

-

Hàm survfit() (trong gói survival) có thể được sử dụng để tính toán ước lượng sống sót theo Kaplan-Meier. Các đối số chính của nó bao gồm:

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    -
  • một đối tượng survival được tạo bằng cách sử dụng hàm Surv()
    • -
  • và tập dữ liệu chứa các biến.
    • -
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Để tính toán các đường cong survival, hãy nhập cái này:

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fit <- survfit(Surv(time, status) ~ sex, data = lung)
-print(fit)
-
## Call: survfit(formula = Surv(time, status) ~ sex, data = lung)
-## 
-##         n events median 0.95LCL 0.95UCL
-## sex=1 138    112    270     212     310
-## sex=2  90     53    426     348     550
-

Nếu bạn muốn hiển thị bản tóm tắt đầy đủ hơn về các đường cong sinh tồn, hãy nhập vào:

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# Summary of survival curves
-summary(fit)
-# Access to the sort summary table
-summary(fit)$table
-
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4.4 Tiếp cận giá trị được trả về bởi survfit()

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Hàm survfit() trả về danh sách các biến, bao gồm các thành phần sau:

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    -
  • n: tổng số chủ thể trong mỗi đường cong.
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  • time: các điểm thời gian trên đường cong.
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  • n.risk: số đối tượng gặp rủi ro tại thời điểm t
    • -
  • n.event: số sự kiện xảy ra tại thời điểm t.
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  • n.censor: số đối tượng bị kiểm duyệt, thoát khỏi nhóm rủi ro, không có sự kiện, tại thời điểm t.
    • -
  • lower,upper: giới hạn tin cậy dưới và trên cho đường cong, tương ứng.
    • -
  • strata: chỉ ra sự phân tầng của ước lượng đường cong. Nếu phân tầng is not NULL, có nhiều đường cong trong kết quả. Các mức của phân tầng (factor) là nhãn cho các đường cong.
    • -
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Các thành phần có thể được truy cập như sau:

-
d <- data.frame(time = fit$time,
-                  n.risk = fit$n.risk,
-                  n.event = fit$n.event,
-                  n.censor = fit$n.censor,
-                  surv = fit$surv,
-                  upper = fit$upper,
-                  lower = fit$lower
-                  )
-head(d)
-
##   time n.risk n.event n.censor      surv     upper     lower
-## 1   11    138       3        0 0.9782609 1.0000000 0.9542301
-## 2   12    135       1        0 0.9710145 0.9994124 0.9434235
-## 3   13    134       2        0 0.9565217 0.9911586 0.9230952
-## 4   15    132       1        0 0.9492754 0.9866017 0.9133612
-## 5   26    131       1        0 0.9420290 0.9818365 0.9038355
-## 6   30    130       1        0 0.9347826 0.9768989 0.8944820
-
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4.5 Vẽ hình các đường cong sinh tồn

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Chúng ta sẽ sử dụng hàm ggsurvplot() (trong gói Survminer) để tạo ra các đường cong sinh tồn cho hai nhóm đối tượng.

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Nó cũng có thể hiển thị:

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    -

  • giới hạn tin cậy 95% của hàm Survivor bằng cách sử dụng đối số conf.int = TRUE .

    • -

  • số lượng và/hoặc tỷ lệ cá nhân gặp rủi ro theo thời gian sử dụng lựa chọn risk.table. Các giá trị được phép cho rủi ro. Bảng bao gồm:

    -
      -
    • TRUE hoặc FALSE xác định có hiển thị hay không bảng rủi ro. Mặc định là FALSE.
      • -
    • “absolute” or “percentage”: để hiển thị số tuyệt đối và tỷ lệ phần trăm đối tượng gặp rủi ro tương ứng theo thời gian. Sử dụng “abs_pct” để hiển thị cả số tuyệt đối và tỷ lệ phần trăm.
      • -
    • -

  • p-value của Log-Rank test so sánh các nhóm bằng cách sử dụng pval = TRUE .

    • -

  • đường ngang / dọc ở mức tồn tại trung bình bằng cách sử dụng đối số surv.median.line. Các giá trị được phép bao gồm một trong c (“none”, “hv”, “h”, “v”). v: dọc, h: ngang.

    • -
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# Change color, linetype by strata, risk.table color by strata
-ggsurvplot(fit,
-          pval = TRUE, conf.int = TRUE,
-          risk.table = TRUE, # Add risk table
-          risk.table.col = "strata", # Change risk table color by groups
-          linetype = "strata", # Change line type by groups
-          surv.median.line = "hv", # Specify median survival
-          ggtheme = theme_bw(), # Change ggplot2 theme
-          palette = c("#E7B800", "#2E9FDF"))
-

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Biểu đồ có thể được tùy chỉnh thêm bằng cách sử dụng các đối số sau:

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    -
  • conf.int.style = “step” để thay đổi kiểu của dải khoảng tin cậy.
    • -
  • xlab để thay đổi nhãn trục x.
    • -
  • break.time.by = 200 ngắt trục x trong khoảng thời gian 200.
    • -
  • risk.table = “abs_pct” để hiển thị cả số lượng tuyệt đối và tỷ lệ phần trăm các cá nhân có nguy cơ.
    • -
  • risk.table.y.text.col = TRUE và risk.table.y.text = FALSE để cung cấp các thanh thay vì tên trong chú thích văn bản của chú giải bảng rủi ro.
    • -
  • ncensor.plot = TRUE để vẽ biểu đồ số đối tượng bị kiểm duyệt tại thời điểm t. Theo đề xuất của Marcin - Kosinski, Đây là một phản hồi bổ sung tốt cho các đường cong sinh tồn, để người ta có thể nhận ra: đường cong sinh tồn trông như thế nào, số lượng rủi ro là bao nhiêu VÀ nguyên nhân khiến tập hợp rủi ro trở nên nhỏ hơn: có phải gây ra bởi các sự kiện hoặc bởi các sự kiện được kiểm duyệt?
    • -
  • Legend.labs để thay đổi nhãn chú giải.
    • -
-
ggsurvplot(
-   fit,                     # survfit object with calculated statistics.
-   pval = TRUE,             # show p-value of log-rank test.
-   conf.int = TRUE,         # show confidence intervals for 
-                            # point estimaes of survival curves.
-   conf.int.style = "step",  # customize style of confidence intervals
-   xlab = "Time in days",   # customize X axis label.
-   break.time.by = 200,     # break X axis in time intervals by 200.
-   ggtheme = theme_light(), # customize plot and risk table with a theme.
-   risk.table = "abs_pct",  # absolute number and percentage at risk.
-  risk.table.y.text.col = T,# colour risk table text annotations.
-  risk.table.y.text = FALSE,# show bars instead of names in text annotations
-                            # in legend of risk table.
-  ncensor.plot = TRUE,      # plot the number of censored subjects at time t
-  surv.median.line = "hv",  # add the median survival pointer.
-  legend.labs = 
-    c("Male", "Female"),    # change legend labels.
-  palette = 
-    c("#E7B800", "#2E9FDF") # custom color palettes.
-)
-

-

Biểu đồ Kaplan-Meier có thể được hiểu như sau:

-

Trục hoành (trục x) biểu thị thời gian tính bằng ngày và trục tung (trục y) thể hiện xác suất sống sót hoặc tỷ lệ người sống sót. Các đường biểu diễn đường cong sinh tồn của hai nhóm. Sự sụt giảm thẳng đứng trong các đường cong biểu thị một sự kiện. Dấu tick dọc trên các đường cong có nghĩa là bệnh nhân đã được kiểm duyệt vào thời điểm này.

-
    -
  • Tại thời điểm 0, xác suất sống sót là 1,0 (hoặc 100% người tham gia còn sống).
    • -
  • Tại thời điểm 250, xác suất sống sót là khoảng 0,55 (hoặc 55%) đối với giới tính = 1 và 0,75 (hoặc 75%) đối với giới tính = 2.
    • -
  • Thời gian sống sót trung bình là khoảng 270 ngày đối với giới tính = 1 và 426 ngày đối với giới tính = 2, cho thấy thời gian sống sót đối với giới tính = 2 tốt hơn so với giới tính = 1
    • -
-

Thời gian sống sót trung bình cho mỗi nhóm có thể được lấy bằng cách sử dụng mã dưới đây:

-
summary(fit)$table
-
##       records n.max n.start events    rmean se(rmean) median 0.95LCL 0.95UCL
-## sex=1     138   138     138    112 326.0841  22.91156    270     212     310
-## sex=2      90    90      90     53 460.6473  34.68985    426     348     550
-

Thời gian sống sót trung bình cho giới tính = 1 (Nhóm nam) là 270 ngày, trái ngược với 426 ngày cho giới tính = 2 (Nữ). Có vẻ như có một lợi thế sống sót cho phụ nữ bị ung thư phổi so với nam giới. Tuy nhiên, để đánh giá liệu sự khác biệt này có ý nghĩa về mặt thống kê hay không đòi hỏi một bài kiểm tra thống kê chính thức, một chủ đề sẽ được thảo luận trong các phần tiếp theo.

-
-
-

Lưu ý rằng, các giới hạn tin cậy rất rộng ở phần đuôi của các đường cong, khiến cho việc diễn giải có ý nghĩa trở nên khó khăn. Điều này có thể được giải thích là do trong thực tế, thường có những bệnh nhân mất khả năng theo dõi hoặc còn sống khi kết thúc theo dõi. Do đó, có thể hợp lý để rút ngắn biểu đồ trước khi kết thúc quá trình theo dõi trên trục x (Pocock và cộng sự, 2002).

-
-
-

Các đường cong sự tồn tại có thể được rút ngắn bằng cách sử dụng đối số xlim như sau:

-
ggsurvplot(fit,
-          conf.int = TRUE,
-          risk.table.col = "strata", # Change risk table color by groups
-          ggtheme = theme_bw(), # Change ggplot2 theme
-          palette = c("#E7B800", "#2E9FDF"),
-          xlim = c(0, 600))
-

-
-
-

Lưu ý rằng, ba phép biến đổi thường được sử dụng có thể được chỉ định bằng cách sử dụng đối số fun : “Log”: log transformation của hàm sống sót, “event”: biểu đồ các sự kiện tích lũy (f (y) = 1-y). Nó còn được gọi là tỷ lệ tích lũy, “Cumhaz”: vẽ biểu đồ của hàm nguy cơ tích lũy (f (y) = -log (y))

-
-
-

Ví dụ: để vẽ các sự kiện tích lũy

-
ggsurvplot(fit,
-          conf.int = TRUE,
-          risk.table.col = "strata", # Change risk table color by groups
-          ggtheme = theme_bw(), # Change ggplot2 theme
-          palette = c("#E7B800", "#2E9FDF"),
-          fun = "event")
-

-

Nguy cơ tích lũy thường được sử dụng để ước tính xác suất nguy hiểm. Nó được định nghĩa là \(H(t) = -log(survival function) = -log(S(t))\). Nguy cơ tích lũy H(t) có thể được hiểu là tử vong tích lũy. Nói cách khác, nó tương ứng với số lượng sự kiện sẽ được mong đợi đối với mỗi cá nhân tại thời điểm t nếu sự kiện đó là một quá trình lặp lại.

-

Để vẽ biểu đồ nguy cơ tích lũy

-
ggsurvplot(fit,
-          conf.int = TRUE,
-          risk.table.col = "strata", # Change risk table color by groups
-          ggtheme = theme_bw(), # Change ggplot2 theme
-          palette = c("#E7B800", "#2E9FDF"),
-          fun = "cumhaz")
-

-
-
-

4.6 Kaplan-Meier life table: tóm tắt các đường cong sinh tồn

-

Như đã đề cập ở trên, bạn có thể sử dụng hàm summary() để có một bản tóm tắt hoàn chỉnh về các đường cong tồn tại:

-
summary(fit)
-
## Call: survfit(formula = Surv(time, status) ~ sex, data = lung)
-## 
-##                 sex=1 
-##  time n.risk n.event survival std.err lower 95% CI upper 95% CI
-##    11    138       3   0.9783  0.0124       0.9542        1.000
-##    12    135       1   0.9710  0.0143       0.9434        0.999
-##    13    134       2   0.9565  0.0174       0.9231        0.991
-##    15    132       1   0.9493  0.0187       0.9134        0.987
-##    26    131       1   0.9420  0.0199       0.9038        0.982
-##    30    130       1   0.9348  0.0210       0.8945        0.977
-##    31    129       1   0.9275  0.0221       0.8853        0.972
-##    53    128       2   0.9130  0.0240       0.8672        0.961
-##    54    126       1   0.9058  0.0249       0.8583        0.956
-##    59    125       1   0.8986  0.0257       0.8496        0.950
-##    60    124       1   0.8913  0.0265       0.8409        0.945
-##    65    123       2   0.8768  0.0280       0.8237        0.933
-##    71    121       1   0.8696  0.0287       0.8152        0.928
-##    81    120       1   0.8623  0.0293       0.8067        0.922
-##    88    119       2   0.8478  0.0306       0.7900        0.910
-##    92    117       1   0.8406  0.0312       0.7817        0.904
-##    93    116       1   0.8333  0.0317       0.7734        0.898
-##    95    115       1   0.8261  0.0323       0.7652        0.892
-##   105    114       1   0.8188  0.0328       0.7570        0.886
-##   107    113       1   0.8116  0.0333       0.7489        0.880
-##   110    112       1   0.8043  0.0338       0.7408        0.873
-##   116    111       1   0.7971  0.0342       0.7328        0.867
-##   118    110       1   0.7899  0.0347       0.7247        0.861
-##   131    109       1   0.7826  0.0351       0.7167        0.855
-##   132    108       2   0.7681  0.0359       0.7008        0.842
-##   135    106       1   0.7609  0.0363       0.6929        0.835
-##   142    105       1   0.7536  0.0367       0.6851        0.829
-##   144    104       1   0.7464  0.0370       0.6772        0.823
-##   147    103       1   0.7391  0.0374       0.6694        0.816
-##   156    102       2   0.7246  0.0380       0.6538        0.803
-##   163    100       3   0.7029  0.0389       0.6306        0.783
-##   166     97       1   0.6957  0.0392       0.6230        0.777
-##   170     96       1   0.6884  0.0394       0.6153        0.770
-##   175     94       1   0.6811  0.0397       0.6076        0.763
-##   176     93       1   0.6738  0.0399       0.5999        0.757
-##   177     92       1   0.6664  0.0402       0.5922        0.750
-##   179     91       2   0.6518  0.0406       0.5769        0.736
-##   180     89       1   0.6445  0.0408       0.5693        0.730
-##   181     88       2   0.6298  0.0412       0.5541        0.716
-##   183     86       1   0.6225  0.0413       0.5466        0.709
-##   189     83       1   0.6150  0.0415       0.5388        0.702
-##   197     80       1   0.6073  0.0417       0.5309        0.695
-##   202     78       1   0.5995  0.0419       0.5228        0.687
-##   207     77       1   0.5917  0.0420       0.5148        0.680
-##   210     76       1   0.5839  0.0422       0.5068        0.673
-##   212     75       1   0.5762  0.0424       0.4988        0.665
-##   218     74       1   0.5684  0.0425       0.4909        0.658
-##   222     72       1   0.5605  0.0426       0.4829        0.651
-##   223     70       1   0.5525  0.0428       0.4747        0.643
-##   229     67       1   0.5442  0.0429       0.4663        0.635
-##   230     66       1   0.5360  0.0431       0.4579        0.627
-##   239     64       1   0.5276  0.0432       0.4494        0.619
-##   246     63       1   0.5192  0.0433       0.4409        0.611
-##   267     61       1   0.5107  0.0434       0.4323        0.603
-##   269     60       1   0.5022  0.0435       0.4238        0.595
-##   270     59       1   0.4937  0.0436       0.4152        0.587
-##   283     57       1   0.4850  0.0437       0.4065        0.579
-##   284     56       1   0.4764  0.0438       0.3979        0.570
-##   285     54       1   0.4676  0.0438       0.3891        0.562
-##   286     53       1   0.4587  0.0439       0.3803        0.553
-##   288     52       1   0.4499  0.0439       0.3716        0.545
-##   291     51       1   0.4411  0.0439       0.3629        0.536
-##   301     48       1   0.4319  0.0440       0.3538        0.527
-##   303     46       1   0.4225  0.0440       0.3445        0.518
-##   306     44       1   0.4129  0.0440       0.3350        0.509
-##   310     43       1   0.4033  0.0441       0.3256        0.500
-##   320     42       1   0.3937  0.0440       0.3162        0.490
-##   329     41       1   0.3841  0.0440       0.3069        0.481
-##   337     40       1   0.3745  0.0439       0.2976        0.471
-##   353     39       2   0.3553  0.0437       0.2791        0.452
-##   363     37       1   0.3457  0.0436       0.2700        0.443
-##   364     36       1   0.3361  0.0434       0.2609        0.433
-##   371     35       1   0.3265  0.0432       0.2519        0.423
-##   387     34       1   0.3169  0.0430       0.2429        0.413
-##   390     33       1   0.3073  0.0428       0.2339        0.404
-##   394     32       1   0.2977  0.0425       0.2250        0.394
-##   428     29       1   0.2874  0.0423       0.2155        0.383
-##   429     28       1   0.2771  0.0420       0.2060        0.373
-##   442     27       1   0.2669  0.0417       0.1965        0.362
-##   455     25       1   0.2562  0.0413       0.1868        0.351
-##   457     24       1   0.2455  0.0410       0.1770        0.341
-##   460     22       1   0.2344  0.0406       0.1669        0.329
-##   477     21       1   0.2232  0.0402       0.1569        0.318
-##   519     20       1   0.2121  0.0397       0.1469        0.306
-##   524     19       1   0.2009  0.0391       0.1371        0.294
-##   533     18       1   0.1897  0.0385       0.1275        0.282
-##   558     17       1   0.1786  0.0378       0.1179        0.270
-##   567     16       1   0.1674  0.0371       0.1085        0.258
-##   574     15       1   0.1562  0.0362       0.0992        0.246
-##   583     14       1   0.1451  0.0353       0.0900        0.234
-##   613     13       1   0.1339  0.0343       0.0810        0.221
-##   624     12       1   0.1228  0.0332       0.0722        0.209
-##   643     11       1   0.1116  0.0320       0.0636        0.196
-##   655     10       1   0.1004  0.0307       0.0552        0.183
-##   689      9       1   0.0893  0.0293       0.0470        0.170
-##   707      8       1   0.0781  0.0276       0.0390        0.156
-##   791      7       1   0.0670  0.0259       0.0314        0.143
-##   814      5       1   0.0536  0.0239       0.0223        0.128
-##   883      3       1   0.0357  0.0216       0.0109        0.117
-## 
-##                 sex=2 
-##  time n.risk n.event survival std.err lower 95% CI upper 95% CI
-##     5     90       1   0.9889  0.0110       0.9675        1.000
-##    60     89       1   0.9778  0.0155       0.9478        1.000
-##    61     88       1   0.9667  0.0189       0.9303        1.000
-##    62     87       1   0.9556  0.0217       0.9139        0.999
-##    79     86       1   0.9444  0.0241       0.8983        0.993
-##    81     85       1   0.9333  0.0263       0.8832        0.986
-##    95     83       1   0.9221  0.0283       0.8683        0.979
-##   107     81       1   0.9107  0.0301       0.8535        0.972
-##   122     80       1   0.8993  0.0318       0.8390        0.964
-##   145     79       2   0.8766  0.0349       0.8108        0.948
-##   153     77       1   0.8652  0.0362       0.7970        0.939
-##   166     76       1   0.8538  0.0375       0.7834        0.931
-##   167     75       1   0.8424  0.0387       0.7699        0.922
-##   182     71       1   0.8305  0.0399       0.7559        0.913
-##   186     70       1   0.8187  0.0411       0.7420        0.903
-##   194     68       1   0.8066  0.0422       0.7280        0.894
-##   199     67       1   0.7946  0.0432       0.7142        0.884
-##   201     66       2   0.7705  0.0452       0.6869        0.864
-##   208     62       1   0.7581  0.0461       0.6729        0.854
-##   226     59       1   0.7452  0.0471       0.6584        0.843
-##   239     57       1   0.7322  0.0480       0.6438        0.833
-##   245     54       1   0.7186  0.0490       0.6287        0.821
-##   268     51       1   0.7045  0.0501       0.6129        0.810
-##   285     47       1   0.6895  0.0512       0.5962        0.798
-##   293     45       1   0.6742  0.0523       0.5791        0.785
-##   305     43       1   0.6585  0.0534       0.5618        0.772
-##   310     42       1   0.6428  0.0544       0.5447        0.759
-##   340     39       1   0.6264  0.0554       0.5267        0.745
-##   345     38       1   0.6099  0.0563       0.5089        0.731
-##   348     37       1   0.5934  0.0572       0.4913        0.717
-##   350     36       1   0.5769  0.0579       0.4739        0.702
-##   351     35       1   0.5604  0.0586       0.4566        0.688
-##   361     33       1   0.5434  0.0592       0.4390        0.673
-##   363     32       1   0.5265  0.0597       0.4215        0.658
-##   371     30       1   0.5089  0.0603       0.4035        0.642
-##   426     26       1   0.4893  0.0610       0.3832        0.625
-##   433     25       1   0.4698  0.0617       0.3632        0.608
-##   444     24       1   0.4502  0.0621       0.3435        0.590
-##   450     23       1   0.4306  0.0624       0.3241        0.572
-##   473     22       1   0.4110  0.0626       0.3050        0.554
-##   520     19       1   0.3894  0.0629       0.2837        0.534
-##   524     18       1   0.3678  0.0630       0.2628        0.515
-##   550     15       1   0.3433  0.0634       0.2390        0.493
-##   641     11       1   0.3121  0.0649       0.2076        0.469
-##   654     10       1   0.2808  0.0655       0.1778        0.443
-##   687      9       1   0.2496  0.0652       0.1496        0.417
-##   705      8       1   0.2184  0.0641       0.1229        0.388
-##   728      7       1   0.1872  0.0621       0.0978        0.359
-##   731      6       1   0.1560  0.0590       0.0743        0.328
-##   735      5       1   0.1248  0.0549       0.0527        0.295
-##   765      3       1   0.0832  0.0499       0.0257        0.270
-

Cũng có thể sử dụng hàm surv_summary() [trong gói survminer ] để nhận tóm tắt về các đường cong sinh tồn. So với hàm summary() mặc định, surv_summary() tạo một khung dữ liệu chứa một bản tóm tắt đẹp từ các kết quả survfit.

-
res.sum <- surv_summary(fit)
-
## Warning in .get_data(x, data = data): The `data` argument is not provided. Data
-## will be extracted from model fit.
-
head(res.sum)
-
##   time n.risk n.event n.censor      surv    std.err     upper     lower strata
-## 1   11    138       3        0 0.9782609 0.01268978 1.0000000 0.9542301  sex=1
-## 2   12    135       1        0 0.9710145 0.01470747 0.9994124 0.9434235  sex=1
-## 3   13    134       2        0 0.9565217 0.01814885 0.9911586 0.9230952  sex=1
-## 4   15    132       1        0 0.9492754 0.01967768 0.9866017 0.9133612  sex=1
-## 5   26    131       1        0 0.9420290 0.02111708 0.9818365 0.9038355  sex=1
-## 6   30    130       1        0 0.9347826 0.02248469 0.9768989 0.8944820  sex=1
-##   sex
-## 1   1
-## 2   1
-## 3   1
-## 4   1
-## 5   1
-## 6   1
-

Hàm surv_summary() trả về một khung dữ liệu với các cột sau:

-
    -
  • time: thời điểm mà đường cong có một bước.
    • -
  • n.risk: số đối tượng gặp rủi ro tại thời điểm t.
    • -
  • n.event: số sự kiện xảy ra tại thời điểm t.
    • -
  • n.censor: số lượng sự kiện được kiểm duyệt.
    • -
  • surv: ước tính xác suất sống sót.
    • -
  • std.err: sai số tiêu chuẩn của xác suất sống sót.
    • -
  • upper: cận trên của khoảng tin cậy
    • -
  • lower: cận dưới của khoảng tin cậy
    • -
  • strata: chỉ ra sự phân tầng của ước lượng đường cong. Các mức của phần tầng (factor) là nhãn cho các đường cong.
    • -
-

Trong một tình huống, khi các đường cong tồn tại đã được gắn với một hoặc nhiều biến, đối tượng surv_summary chứa các cột bổ sung đại diện cho các biến. Điều này làm cho nó có thể đối mặt với đầu ra của ggsurvplot theo tầng hoặc theo một số kết hợp của các yếu tố.

-

Đối tượng surv_summary cũng có một thuộc tính có tên là ‘table’ chứa thông tin về các đường cong sinh tồn, bao gồm các đường trung vị của sự sống sót với khoảng tin cậy, cũng như, tổng số đối tượng và số lượng sự kiện trong mỗi đường cong. Để tiếp cận vào thuộc tính ‘table’, hãy nhập vào:

-
attr(res.sum, "table")
-
##       records n.max n.start events    rmean se(rmean) median 0.95LCL 0.95UCL
-## sex=1     138   138     138    112 326.0841  22.91156    270     212     310
-## sex=2      90    90      90     53 460.6473  34.68985    426     348     550
-
-
-

4.7 Log-Rank test so sánh các đường cong sống sót: survdiff()

-

Log-Rank test là phương pháp được sử dụng rộng rãi nhất để so sánh hai hoặc nhiều đường cong sống sót. Giả thuyết không (null hypothesis) là không có sự khác biệt về khả năng sống sót giữa hai nhóm. Log-Rank test là kiểm định phi tham số, không đưa ra giả định nào về các phân phối tồn tại. Về cơ bản, Log-Rank test so sánh số lượng sự kiện quan sát được trong mỗi nhóm với những gì sẽ được mong đợi nếu giả thuyết vô hiệu là đúng (tức là, nếu các đường cong sống sót giống hệt nhau). Thống kê thứ hạng Log-Rank được phân phối gần đúng dưới dạng thống kê kiểm định Chi-square.

-

Hàm survdiff() [trong gói survival] có thể được sử dụng để tính toán Log-Rank test so sánh hai hoặc nhiều đường cong sinh tồn.

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survdiff() có thể được sử dụng như sau:

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surv_diff <- survdiff(Surv(time, status) ~ sex, data = lung)
-surv_diff
-
## Call:
-## survdiff(formula = Surv(time, status) ~ sex, data = lung)
-## 
-##         N Observed Expected (O-E)^2/E (O-E)^2/V
-## sex=1 138      112     91.6      4.55      10.3
-## sex=2  90       53     73.4      5.68      10.3
-## 
-##  Chisq= 10.3  on 1 degrees of freedom, p= 0.001
-

Hàm trả về danh sách các thành phần, bao gồm:

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    -
  • n: số chủ thể trong mỗi nhóm.
    • -
  • obs: số lượng sự kiện được quan sát có trọng số trong mỗi nhóm.
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  • exp: số lượng sự kiện dự kiến có trọng số trong mỗi nhóm.
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  • chisq: thống kê chisquare để kiểm tra sự bằng nhau.
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  • strata: (tùy chọn) số lượng đối tượng có trong mỗi tầng.
    • -
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Log-Rank test về sự khác biệt trong khả năng sống sót cho giá trị p là p = 0,0013, cho thấy rằng các nhóm giới tính có sự khác biệt đáng kể về khả năng sống sót.

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4.8 Fit complex survival curves

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Trong phần này, chúng tôi sẽ tính toán các đường cong sống sót bằng cách sử dụng kết hợp nhiều yếu tố. Tiếp theo, chúng ta sẽ đối mặt với đầu ra của ggsurvplot() bằng sự kết hợp của các yếu tố

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Điều chỉnh các đường cong tồn tại (phức tạp) bằng cách sử dụng tập dữ liệu colon

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require("survival")
-fit2 <- survfit( Surv(time, status) ~ sex + rx + adhere,
-                data = colon )
-

Biểu diễn kết quả đầu ra bằng survminer. Biểu đồ dưới đây cho thấy các đường cong sống sót của biến giới tính được biểu thị theo các giá trị của rx & adhere.

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# Plot survival curves by sex and facet by rx and adhere
-ggsurv <- ggsurvplot(fit2, fun = "event", conf.int = TRUE,
-                     ggtheme = theme_bw())
-   
-ggsurv$plot +theme_bw() + 
-  theme (legend.position = "right")+
-  facet_grid(rx ~ adhere)
-

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5 Tóm tắt

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Phân tích tồn tại là một tập hợp các phương pháp tiếp cận thống kê để phân tích dữ liệu trong đó biến kết quả được quan tâm là thời gian cho đến khi một sự kiện xảy ra.

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Dữ liệu tồn tại thường được mô tả và mô hình hóa theo hai hàm liên quan:

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    -

  • Hàm sống sót đại diện cho xác suất mà một cá nhân sống sót từ thời điểm xuất phát đến một thời điểm nào đó ngoài thời gian t. Nó thường được ước tính bằng phương pháp Kaplan-Meier. logrank test có thể được sử dụng để kiểm tra sự khác biệt giữa các đường cong sống sót cho các nhóm, chẳng hạn như nhóm điều trị.

    • -

  • Hàm nguy cơ cung cấp khả năng xảy ra tức thời của một sự kiện tại một thời điểm, cho khả năng tồn tại cho đến thời điểm đó. Nó được sử dụng chủ yếu như một công cụ chẩn đoán hoặc xác định một mô hình toán học để phân tích tỷ lệ sống sót.

    • -
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Trong bài viết này, chúng tôi trình bày cách thực hiện và trực quan hóa các phân tích tỷ lệ sống bằng cách sử dụng kết hợp hai gói R: survival (để phân tích) và survminer (để hiển thị).

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6 Tham khảo

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  • Clark TG, Bradburn MJ, Love SB and Altman DG. Survival Analysis Part I: Basic concepts and first analyses. British Journal of Cancer (2003) 89, 232 – 238

    • -

  • Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53: 457–481.

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  • Pocock S, Clayton TC, Altman DG (2002) Survival plots of time-to-event outcomes in clinical trials: good practice and pitfalls. Lancet 359: 1686– 1689.

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- - - - - - - - - - - - - - - - - diff --git a/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Document.dcf b/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Document.dcf deleted file mode 100644 index cd4242c..0000000 --- a/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Document.dcf +++ /dev/null @@ -1,11 +0,0 @@ -name: Document -title: -username: -account: rpubs -server: rpubs.com -hostUrl: rpubs.com -appId: https://api.rpubs.com/api/v1/document/863086/1e0a1a5fdb164ee398523d40693e1502 -bundleId: https://api.rpubs.com/api/v1/document/863086/1e0a1a5fdb164ee398523d40693e1502 -url: http://rpubs.com/publish/claim/863086/12105261e41146289606d570ea983019 -when: 1644223992.93856 -lastSyncTime: 1644223992.93856 diff --git a/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Publish Document.dcf b/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Publish Document.dcf deleted file mode 100644 index 3ac9d24..0000000 --- a/05-Regression/03-Scipts/rsconnect/documents/Survival Analysis Basics.Rmd/rpubs.com/rpubs/Publish Document.dcf +++ /dev/null @@ -1,11 +0,0 @@ -name: Publish Document -title: -username: -account: rpubs -server: rpubs.com -hostUrl: rpubs.com -appId: https://api.rpubs.com/api/v1/document/863086/1e0a1a5fdb164ee398523d40693e1502 -bundleId: https://api.rpubs.com/api/v1/document/863086/1e0a1a5fdb164ee398523d40693e1502 -url: http://rpubs.com/nguyenngocbinhneu/863086 -when: 1644486952.88239 -lastSyncTime: 1644486952.88239 diff --git a/05-Regression/03-Scipts/Survival Analysis Basics.Rmd b/05-Regression/Survival Analysis Basics.Rmd similarity index 100% rename from 05-Regression/03-Scipts/Survival Analysis Basics.Rmd rename to 05-Regression/Survival Analysis Basics.Rmd diff --git a/06-Timeseries/Multiple_Time_Series_Forecast.html b/06-Timeseries/Multiple_Time_Series_Forecast.html deleted file mode 100644 index fb8b878..0000000 --- a/06-Timeseries/Multiple_Time_Series_Forecast.html +++ /dev/null @@ -1,921 +0,0 @@ - - - - - - - - - - - - - - - -Dự báo nhiều chuỗi thời gian (phần 2) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Phân tích chuỗi thời gian là một phương pháp được sử dụng rộng rãi trong kinh doanh để có được những thông tin hữu ích như dự báo nhu cầu, dự báo giá cổ phiếu, giá tiền mã hóa và các phân tích dự báo khác.

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Trong phần này, tôi sẽ giải thích cách dự báo hàng nghìn chuỗi (1000+) sử dụng mô hình Thống kê / Máy học / Học sâu để dự đoán giá trị trong tương lai) & phân loại mô hình nhu cầu (phân loại sản phẩm dựa trên số lượng và thời gian).

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Chuỗi phân tích này bao gồm 5 phần:

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    -

  • Phần 1: Làm sạch dữ liệu và tạo features đơn giản.

    • -

  • Phần 2: Mô hình Chuỗi thời gian với phương pháp thống kê (ARIMA, ETS, CROSTON, v.v.) sử dụng gói fable R.

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  • Phần 3: Time Series Feature Engineering sử dụng gói timetk R.

    • -

  • Phần 4: Các mô hình Machine Learning (XGBoost, Random Forest, v.v.) & điều chỉnh Hyperparameter bằng cách sử dụng các gói modeltime & tidymodels R.

    • -

  • Phần 5: Mô hình Deeplearning (NBeats & DeepAR) & điều chỉnh Hyperparameter bằng cách sử dụng các gói modeltime, modeltime.gluonts R.

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# install.packages("devtools")
-# devtools::install_github("nguyenngocbinh/vndirect")
-pacman::p_load(knitr,
-               vndirect,
-               tidyverse,
-               magrittr,
-               hrbrthemes,
-               # Tidy Temporal Data Frames and Tools
-               tsibble,
-               # Feature Extraction and Statistics for Time Series
-               feasts,
-               fable,
-               fable.prophet)
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1 Dữ liệu

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Sử dụng dữ liệu giá cổ phiếu nguồn vndirect. Trong phần này sẽ sử dụng chuỗi số liệu của 3 cổ phiếu TCB, LPB, BCC

-
# get data from vndirect source
-rawdata <- vndirect::vnd_get_list_data(c('TCB', 'LPB', 'BCC'), 1000)
-

Kiểm tra số lượng quan sát từng chuỗi

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rawdata$ticker_name %>% 
-  table()
-
## .
-##  BCC  LPB  TCB 
-## 1000 1000  939
-
-
-

2 Tiền xử lý dữ liệu

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Sử dụng giá đóng cửa hàng ngày để phân tích và dự báo. gói tsibble cho phép định dạng nhiều chuỗi trên cùng 1 bảng (tương tự như group_by trên dplyr). Bằng việc chọn key và index phù hợp ta sẽ định dạng được bảng dữ liệu gồm nhiều chuỗi thời gian

-
# convert to tsibble format
-dt <- rawdata %>% 
-  # select target variable
-  rename(value = adClose) %>% 
-  # convert to tsibble format
-  as_tsibble(key = ticker_name, index = date) %>% 
-  fill_gaps()
-

Xử lý missing nếu có trong dữ liệu. Do fable yêu cầu fill_gaps, tức là điền các khoảng thời gian thiếu vào chuỗi. Vì vậy, sẽ có nhiều ngày không có dữ liệu (ví dụ, thứ 7, chủ nhật không có giao dịch). Phần dưới sẽ điền những giá trị missing này bằng giá trị ngày gần nhất.

-
fnc_na_vars <- function(x) {any(is.na(x))}
-
-na_vars <- dt %>%
-  select_if(fnc_na_vars) %>% 
-  names() 
-
-dt <- dt %>%
-  fill(all_of(na_vars), .direction = 'down')
-

Chia dữ liệu thành nhiều tập train (fable không hỗ trợ chia train, test), sau đó sử dụng chuỗi dữ liệu ban đầu để đánh giá performance của mô hình.

-
# split data to cross validation
-cv_dt <- dt %>% 
-  stretch_tsibble(.init = 370, .step = 100)
-
-
-

3 Modelling

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3.1 Các loại mô hình

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Các loại mô hình được tham khảo từ Forecasting: Principles and Practice

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3.1.1 Naive

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Mô hình Naive gán tất cả các giá trị trong tương lai bằng giá trị quan sát cuối cùng.

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3.1.2 Seasonal Naive

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Mô hình Naive theo mùa được sử dụng cho dữ liệu theo mùa. Trong tình huống này, mỗi giá trị tương lai bằng giá trị cuối cùng của cùng một mùa.

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3.1.3 Drift

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Mô hình drift là một biến thể của mô hình Naive, cho phép dự báo tăng giảm theo thời gian.

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3.1.4 Simple Exponential Smooth (SES)

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Mô hình trơn theo cấp số nhân đơn giản được sử dụng khi không thể xác định được xu hướng rõ ràng hoặc mô hình theo mùa.

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\[\begin{align*} - \text{Forecast equation} && \hat{y}_{t+h|t} & = \ell_{t}\\ - \text{Smoothing equation} && \ell_{t} & = \alpha y_{t} + (1 - \alpha)\ell_{t-1}, -\end{align*}\]

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    -

  • Trong đó:

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    • \(\ell_{t}\): giá trị làm trơn tại thời gian t
      • -
    • h: thời gian dự báo ngoài mẫu
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    • \(\alpha\): tham số làm trơn \(0\le\alpha\le1\)
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3.1.5 Holt’s Linear

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Mô hình Holt’s Linear là một phiên bản mở rộng của SES cho phép dự báo theo xu hướng.

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\[\begin{align*} - \text{Forecast equation}&& \hat{y}_{t+h|t} &= \ell_{t} + hb_{t} \\ - \text{Level equation} && \ell_{t} &= \alpha y_{t} + (1 - \alpha)(\ell_{t-1} + b_{t-1})\\ - \text{Trend equation} && b_{t} &= \beta^*(\ell_{t} - \ell_{t-1}) + (1 -\beta^*)b_{t-1}, -\end{align*}\]

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3.1.6 Damped Holt’s Linear

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Là phiên bản mở rộng của Holt’s Linear. Mô hình Holt’s Linear cho ra chuỗi liên tục tăng hoặc liên tục giảm vô hạn trong tương lai vì vậy có thể dự báo quá mức (đặc biệt với chuỗi thời gian dài). Gardner & McKenzie (1985) đưa ra 1 tham số điều chỉnh xu hướng, cho phép xu hướng thay đổi theo thời gian với một tham số \(\phi\).

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\[\begin{align*} - \hat{y}_{t+h|t} &= \ell_{t} + (\phi+\phi^2 + \dots + \phi^{h})b_{t} \\ - \ell_{t} &= \alpha y_{t} + (1 - \alpha)(\ell_{t-1} + \phi b_{t-1})\\ - b_{t} &= \beta^*(\ell_{t} - \ell_{t-1}) + (1 -\beta^*)\phi b_{t-1}. -\end{align*}\]

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  • \(0<\phi<1\), \(\phi=1\) ~ Holt’s Linear
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3.1.7 Forecasting with Decomposition

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Mô hình này được sử dụng để phân rã chuỗi thời gian theo mùa và theo xu hướng bằng cách sử dụng phương pháp lowess (Seasonal and Trend decomposition using Loess - STL). Sau đó, sử dụng ETS để dự báo dữ liệu được điều chỉnh theo mùa, và thành phần theo mùa có thể được thêm vào dữ liệu dự báo.

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    -
  • Dạng mô hình cộng:
    • -
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\[y_{t} = S_{t} + T_{t} + R_t\]

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    -
  • Dạng mô hình nhân:
    • -
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\[y_{t} = S_{t} \times T_{t} \times R_t\]

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3.1.8 ARIMA

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Mô hình ARIMA cung cấp một cách tiếp cận khác để dự báo chuỗi thời gian. Các mô hình ARIMA và ETS là hai cách tiếp cận được sử dụng rộng rãi nhất để dự báo chuỗi thời gian. Trong khi các mô hình ETS dựa trên đặc điểm về xu hướng và tính thời vụ trong dữ liệu, thì các mô hình ARIMA hướng tới tự tương quan trong dữ liệu. Ở đây, chúng tôi sẽ chọn mô hình ARIMA tự động bằng cách sử dụng AICC tối thiểu.

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3.1.9 Timeseries Regression

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Mô hình hồi quy, cho phép sử dụng biến độc lập khác.

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\[ -\begin{equation} - y_t = \beta_{0} + \beta_{1} x_{1,t} + \beta_{2} x_{2,t} + \cdots + \beta_{k} x_{k,t} + \varepsilon_t, - \tag{7.1} -\end{equation} -\]

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-
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3.1.10 Dynamic Harmonic Regression

-

Các phiên bản theo mùa của mô hình ARIMA và ETS được thiết kế cho các khoảng thời gian ngắn, chẳng hạn như 12 cho dữ liệu hàng tháng hoặc 4 cho dữ liệu hàng quý. Mô hình ETS() giới hạn thời vụ là khoảng thời gian tối đa là 24 để cho phép dữ liệu hàng giờ nhưng không cho phép dữ liệu có khoảng thời gian theo mùa lớn hơn. Hàm ARIMA () sẽ cho phép khoảng thời gian theo mùa lên đến m =350, nhưng trong thực tế, thường sẽ hết bộ nhớ bất cứ khi nào khoảng thời gian theo mùa nhiều hơn 200. Vì vậy, đối với chuỗi thời gian mà chia nhỏ đến phút hoặc giây thì 2 mô hình này không đáp ứng được.

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Trong trường hợp này, sử dụng phương pháp hồi quy hài hòa trong đó mô hình theo mùa được mô hình hóa bằng cách sử dụng thuật ngữ Fourier với chuỗi thời gian ngắn hạn được xử lý bằng ARMA.

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Đối với dữ liệu có nhiều hơn một khoảng thời gian theo mùa, có thể sử dụng Fourier với các mức khác nhau; độ mượt của mô hình theo mùa có thể được kiểm soát bởi K, bao gồm các cặp Fourier sin và cos - mô hình theo mùa mượt hơn đối với các giá trị nhỏ hơn của K. Chuỗi thời gian ngắn hạn dễ dàng được xử lý với mô hình ARMA đơn giản.

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3.1.11 Ensemble

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Mô hình tổng hợp chỉ đơn giản là sử dụng một số mô hình khác nhau cùng một lúc và tính toán giá trị trung bình của các dự báo kết quả. Ví dụ: ở đây, các mô hình ARIMA, SES & Decomposition được sử dụng cùng nhau để tính toán giá trị dự báo trung bình.

-
model_single_var_table <- cv_dt %>%
-  model(
-    ## Model 1: Naive ----
-    naive_mod = NAIVE(log(value + 1)),
-    
-    ## Model 2: Snaive ----
-    snaive_mod = SNAIVE(log(value + 1)),
-    
-    ## Model 3: Drift ----
-    drift_mod = RW(log(value + 1) ~ drift()),
-    
-    ## Model 4: SES ----
-    ses_mod = ETS(log(value + 1) ~ error("A") + trend("N") + season("N"),
-                  opt_crit = "mse"),
-    
-    ## Model 5: Holt's Linear ----
-    hl_mod = ETS(log(value + 1) ~ error("A") + trend("A") + season("N"),
-                 opt_crit = "mse"),
-    
-    ## Model 6: Damped Holt's Linear ----
-    hldamp_mod = ETS(log(value + 1) ~ error("A") + trend("Ad") + season("N"),
-                     opt_crit = "mse"),
-    
-    ## Model 7: STL decomposition with ETS ----
-    stl_ets_mod = decomposition_model(
-      STL(log(value + 1), ~ season(window = 7)),
-      ETS(season_adjust ~ season("N")),
-      NAIVE(season_week),
-      SNAIVE(season_year)
-    ),
-    
-    ## Model 8: ARIMA ----
-    arima_mod = ARIMA(log(value + 1)),
-    
-    ## Model 9: Dynamic harmonic regression ----
-    dhr_mod = ARIMA(
-      log(value + 1) ~ PDQ(0, 0, 0) + fourier(K = 3)+ lag(basicPrice) + lag(high)
-    ),
-    
-    ## Model 10: TSLM ----
-    tslm_mod = TSLM(
-      log(value + 1) ~ lag(basicPrice) + lag(high) + lag(low) + lag(nmVolume)
-    )
-    
-  ) %>%
-  ## Model 99: Ensemble Model ----
-mutate(ensemble_sm_mod = combination_ensemble(arima_mod, ses_mod, stl_ets_mod))
-
## Warning in sqrt(diag(best$var.coef)): NaNs produced
-
-## Warning in sqrt(diag(best$var.coef)): NaNs produced
-
-## Warning in sqrt(diag(best$var.coef)): NaNs produced
-
## Warning: 12 errors (1 unique) encountered for stl_ets_mod
-## [12] object 'season_year' not found
-
-
-
-
-

4 Đánh giá khả năng dự báo

-
-

4.1 Training set accuracy

-

Do mô hình kết hợp không sử dụng cùng hàm accuracy(). Vì vậy, tôi viết lại hàm kết hợp các giá trị accuracy

-
comb_accuracy <- function(.model){
-  train_acc_single1 <- .model %>% 
-    select(-ensemble_sm_mod) %>% # not include ensemble_sm_mod
-    accuracy()
-  
-  train_acc_single2 <- .model %>% 
-    select(ensemble_sm_mod) %>% 
-    accuracy()
-  
-  train_acc_single <- bind_rows(train_acc_single1, train_acc_single2)
-  return(train_acc_single)
-}
-
training_acc <- comb_accuracy(model_single_var_table) %>% 
-  select(.id, ticker_name, .model, .type, RMSE, MAE, MAPE)
-
-training_acc %>% head(15) %>% kable()
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
.idticker_name.model.typeRMSEMAEMAPE
1BCCnaive_modTraining0.11954880.06473711.063419
1BCCsnaive_modTraining0.28393780.19589263.194357
1BCCdrift_modTraining0.11955290.06529331.072899
1BCCses_modTraining0.11920450.06652151.092302
1BCChl_modTraining0.11921490.06678071.096848
1BCChldamp_modTraining0.11892440.06679261.097196
1BCCstl_ets_modTrainingNaNNaNNaN
1BCCarima_modTraining0.11920650.06655561.092881
1BCCdhr_modTraining0.12047910.08020471.320086
1BCCtslm_modTraining0.13060860.08855451.454254
1LPBnaive_modTraining0.16431820.09158541.097041
1LPBsnaive_modTraining0.45201460.32167773.806460
1LPBdrift_modTraining0.16371090.09533671.145566
1LPBses_modTraining0.16381370.09277751.111481
1LPBhl_modTraining0.16315100.09533281.144763
-
-
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4.2 TSCV accuracy

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Do mô hình Dynamic Harmonic Regression và Timeseries Regression không có dữ liệu trong tương lai, nên sẽ không forecast để tính accuracy

-
test_acc_single1 <- model_single_var_table %>%
-  select(-ensemble_sm_mod, -dhr_mod, -tslm_mod) %>% # not include ensemble_sm_mod, dhr_mod, tslm_mod
-  forecast(h = "3 months") %>%
-  accuracy(dt)
-
## Warning: The future dataset is incomplete, incomplete out-of-sample data will be treated as missing. 
-## 81 observations are missing between 2022-03-04 and 2022-05-23
-
test_acc_single2 <- model_single_var_table %>%
-  select(ensemble_sm_mod) %>%
-  forecast(h = "3 months") %>%
-  accuracy(dt)
-
## Warning: The future dataset is incomplete, incomplete out-of-sample data will be treated as missing. 
-## 81 observations are missing between 2022-03-04 and 2022-05-23
-
test_acc_single <- test_acc_single1 %>% 
-  bind_rows(test_acc_single2) %>% 
-  select(ticker_name, .model, .type, RMSE, MAE, MAPE)
-
-
-

4.3 Mô hình tốt nhất theo MAPE

-
best_mod_training_acc <- training_acc %>% 
-  group_by(ticker_name, .type) %>%
-  summarise(MAPE = min(MAPE, na.rm = T)) %>%
-  inner_join(training_acc)
-
## `summarise()` has grouped output by 'ticker_name'. You can override using the
-## `.groups` argument.
-## Joining, by = c("ticker_name", ".type", "MAPE")
-
best_mod_test_acc <- test_acc_single %>%
-  group_by(ticker_name, .type) %>%
-  summarise(MAPE = min(MAPE, na.rm = T)) %>%
-  inner_join(test_acc_single)
-
## `summarise()` has grouped output by 'ticker_name'. You can override using the
-## `.groups` argument.
-## Joining, by = c("ticker_name", ".type", "MAPE")
-
best_mod_acc <- best_mod_training_acc %>% bind_rows(best_mod_test_acc) 
-
-best_mod_acc %>% kable()
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
ticker_name.typeMAPE.id.modelRMSEMAE
BCCTraining1.04186654naive_mod0.12159650.0677534
LPBTraining0.89771304naive_mod0.13133280.0682048
TCBTraining0.83687153ses_mod0.40665990.2173702
BCCTest13.7929232NAnaive_mod2.97902621.7796963
LPBTest8.6506065NAsnaive_mod2.47147921.3628243
TCBTest8.7966750NAsnaive_mod4.01900352.8563180
-

Hơi bất ngờ khi các mô hình Naive lại có performance tốt nhất

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5 Dự báo

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5.1 Fit lại mô hình với toàn bộ chuỗi dữ liệu

-
final_model_single_var_table <- dt %>%
-  model(
-    ## Model 1: Naive ----
-    naive_mod = NAIVE(log(value + 1)),
-    
-    ## Model 2: Snaive ----
-    snaive_mod = SNAIVE(log(value + 1)),
-    
-    ## Model 3: Drift ----
-    drift_mod = RW(log(value + 1) ~ drift()),
-    
-    ## Model 4: SES ----
-    ses_mod = ETS(log(value + 1) ~ error("A") + trend("N") + season("N"),
-                  opt_crit = "mse"),
-    
-    ## Model 5: Holt's Linear ----
-    hl_mod = ETS(log(value + 1) ~ error("A") + trend("A") + season("N"),
-                 opt_crit = "mse"),
-    
-    ## Model 6: Damped Holt's Linear ----
-    hldamp_mod = ETS(log(value + 1) ~ error("A") + trend("Ad") + season("N"),
-                     opt_crit = "mse"),
-    
-    ## Model 7: STL decomposition with ETS ----
-    stl_ets_mod = decomposition_model(
-      STL(log(value + 1), ~ season(window = 7)),
-      ETS(season_adjust ~ season("N")),
-      NAIVE(season_week),
-      SNAIVE(season_year)
-    ),
-    
-    ## Model 8: ARIMA ----
-    arima_mod = ARIMA(log(value + 1)),
-    
-    ## Model 9: Dynamic harmonic regression ----
-    dhr_mod = ARIMA(
-      log(value + 1) ~ PDQ(0, 0, 0) + fourier(K = 3)+ lag(basicPrice) + lag(high)
-    ),
-    
-    ## Model 10: TSLM ----
-    tslm_mod = TSLM(
-      log(value + 1) ~ lag(basicPrice) + lag(high) + lag(low) + lag(nmVolume)
-    )
-    
-  ) %>%
-  ## Model 99: Ensemble Model ----
-mutate(ensemble_sm_mod = combination_ensemble(arima_mod, ses_mod, stl_ets_mod))
-
-
-

5.2 Dự báo 3 tháng tiếp theo

-
final_fc <- final_model_single_var_table %>% 
-  select(-dhr_mod, -tslm_mod) %>% 
-  forecast(h = "3 months")
-
final_fc %>% 
-  filter(ticker_name =='BCC') %>% 
-  autoplot(dt)+
-  theme_ipsum()+
-  labs(title = 'BCC')
-

-
final_fc %>% 
-  filter(ticker_name =='LPB' & .model == 'snaive_mod') %>% 
-  autoplot(dt)+
-  theme_ipsum()+
-  labs(title = 'LPB')
-

-
final_fc %>% 
-  filter(ticker_name =='TCB' & .model == 'snaive_mod') %>% 
-  autoplot(dt)+
-  theme_ipsum()+
-  labs(title = 'TCB')
-

-
-
-

5.3 Kết quả dự báo với mô hình có MAPE tốt nhất

-
best_fc <- best_mod_acc %>% 
-  filter(.type == 'Test') %>% 
-  inner_join(final_fc)
-
## Joining, by = c("ticker_name", ".model")
-
-
- - - -
-
- -
- - - - - - - - - - - - - - - - - diff --git a/06-Timeseries/STL_decomposition.html b/06-Timeseries/STL_decomposition.html deleted file mode 100644 index c01f0a9..0000000 --- a/06-Timeseries/STL_decomposition.html +++ /dev/null @@ -1,479 +0,0 @@ - - - - - - - - - - - - - - - -STL phân rã chuỗi thời gian - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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- -
- - - - - - - -
-

1 Giới thiệu

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  • Dự báo chuỗi thời gian là một lĩnh vực nhỏ của phân tích chuỗi thời gian, trong đó các phép đo lịch sử được lập mô hình để mô tả các đặc điểm cơ bản của những thứ có thể quan sát được và được ngoại suy trong tương lai.

    • -

  • Trong một vài thập kỷ, lĩnh vực phân tích chuỗi thời gian đã bị thống trị bởi phương pháp thống kê. Một trong những mô hình quan trọng nhất và thường được sử dụng là Đường trung bình động tích hợp tự hồi quy (AutoRegressive Integrated Moving Average - ARIMA), có thể được xây dựng nhanh chóng nhờ phương pháp Box – Jenkins. Họ mô hình ARIMA có tính linh hoạt tuyệt vời để trình bày các chuỗi thời gian khác nhau. Tuy nhiên, nó có giới hạn do giả định về độ tuyến tính của chuỗi thời gian.

    • -

  • Một phương pháp thống kê thống trị khác và được sử dụng rộng rãi là ExponenTial Smoothing (ETS), được đề xuất vào những năm 1950. Nó thường được coi là một giải pháp thay thế cho các mô hình ARIMA. Trong khi họ ARIMA phát triển một mô hình trong đó dự đoán là tổng tuyến tính có trọng số của các quan sát trong quá khứ gần đây hoặc độ trễ, thì các dự báo do ETS tạo ra là trung bình có trọng số của các quan sát trong quá khứ, với trọng số giảm dần theo cấp số nhân với các quan sát xa hơn.

    • -

  • Cuộc thi M do giáo sư Spyros Makridakis khởi xướng. Có các cuộc thi mở khác nhau (M1 – M5) dành riêng cho việc so sánh hiệu suất của các phương pháp dự báo khác nhau. Đặc biệt, phương pháp Theta đã thành công ấn tượng trong Cuộc thi M3 và do đó được sử dụng trong Cuộc thi M4 như một tiêu chuẩn. Nó được đề xuất lần đầu tiên bởi Assimakopoulos et al. và sau đó được mở rộng sang dự báo chuỗi thời gian kinh tế vĩ mô và tài chính đa biến. Hyndman đã chứng minh phương pháp Theta được áp dụng trong Cuộc thi M3 tương đương với phương pháp làm mịn hàm mũ đơn giản với độ lệch.

    • -

  • Chuỗi thời gian cũng có thể có nhiều mẫu cơ bản và việc phân tích có thể tiết lộ chúng bằng cách chia chuỗi thời gian thành nhiều thành phần. Trong phần này, tôi tập trung vào phân rã STL. STL là viết tắt của phân tích theo mùa-xu hướng bằng cách sử dụng LOESS ( Seasonal-Trend decomposition), trong đó LOESS là LOcal regrESSion, được đề xuất bởi Robert et al.(1990) đóng góp vào một phương pháp phân rã mạnh đối với các bất thường.

    • -

  • Trí tuệ nhân tạo (AI) đã đạt được sự nổi bật đáng kể trong thập kỷ qua, đặc biệt là trong nhận dạng đối tượng, xử lý ngôn ngữ tự nhiên (NLP) và lái xe tự động. Mạng Nơ-ron phức hợp (CNN) đã cách mạng hóa lĩnh vực thị giác máy tính. Mạng Nơ-ron định kỳ (RNN) được hưởng lợi từ rất nhiều thành quả NLP, chẳng hạn như dịch máy và nhận dạng giọng nói. Trong lĩnh vực chuỗi thời gian, nhiều phương pháp học máy như hồi quy vectơ hỗ trợ (SVR), mạng nơ-ron, cây phân loại và hồi quy (CART), và hồi quy k -lân cận (kNN) đã được chứng minh là có thể lập mô hình và dự báo chuỗi thời gian.

    • -

  • Có một số cuộc thảo luận về việc so sánh hiệu suất của các phương pháp dự báo khác nhau. Ahmed và cộng sự đã thực hiện một so sánh thực nghiệm của tám mô hình học máy trong chuỗi 1045 tháng liên quan đến Cuộc thi M3, nhưng chỉ thực hiện dự báo trước một bước. Makrirdakis và cộng sự đã thực hiện một số công trình tương tự, so sánh các phương pháp thống kê và học máy, nhưng không có bất kỳ phương pháp phân rã nào được đưa vào như một bước tiền xử lý. Sử dụng tập dữ liệu cuộc thi M1, Theodosieu đã so sánh phương pháp dựa trên STL mới với một số điểm chuẩn phổ biến nhưng không kết hợp STL với chúng và chỉ xem xét dự báo tối đa 18 tháng.

    • -

  • Vì bước tiền xử lý thường đóng một phần không thể thiếu trong các mô hình dự báo và tác động đáng kể đến kết quả, chúng tôi đề xuất tiến hành một công việc so sánh mới để xác định lợi ích của nó: (1) bằng cách khám phá sự phân rã STL khi sử dụng nó như một bước tiền xử lý cho tất cả các phương pháp; và (2) bằng cách xem xét thời gian dự báo dài.

    • -

  • Phần còn lại của bài này được tổ chức như sau. Trong phần tiếp theo, tôi trình bày một mô tả ngắn gọn về tất cả các mô hình liên quan và các phương pháp phân rã. Phần 3 trình bày cách tôi tổ chức và tiến hành các thực nghiệm. Trong Phần 4, tôi trình bày các kết quả so sánh và các cuộc thảo luận dựa trên các kết quả này. Phần 5 đưa ra kết luận.

    • -
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2 Phương pháp

-

Mặc dù có nhiều biến thể khác nhau của mỗi mô hình, chúng tôi chỉ xem xét các phiên bản ban đầu của mỗi mô hình trong các thử nghiệm của mình. Phần này dựa theo các Cuộc thi M3 và M4, tôi đã giữ nguyên sáu phương pháp tiêu chuẩn được sử dụng trong hai cuộc thi này bởi nhà tổ chức.

-
-

2.1 Tiêu chuẩn hiện có trong Cuộc thi M4

-

Dưới đây là danh sách mô tả các điểm chuẩn được sử dụng trong Cuộc thi M4.

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    -
  • Naive 1. giả định các giá trị trong tương lai giống hệt với lần quan sát cuối cùng.
    • -
  • Naive S. giả định các giá trị trong tương lai giống với các giá trị trong kỳ đã biết gần đây nhất, trong trường hợp của chúng tôi, là 12 tháng.
    • -
  • Naive 2. tương tự như Naive 1, ngoại trừ dữ liệu được điều chỉnh theo mùa bằng cách phân rã nhân thông thường nếu được thử nghiệm theo mùa. Chúng tôi đã thực hiện kiểm tra tự tương quan 90% ở độ trễ 12 cho mỗi chuỗi.
    • -
  • Làm trơn theo cấp số nhân đơn giản (Simple Exponential Smoothing - SES). SES dự báo các giá trị trong tương lai dưới dạng giá trị trung bình có trọng số giảm dần theo cấp số nhân của các quan sát trong quá khứ.
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  • Holt. Phương pháp xu hướng tuyến tính của Holt mở rộng SES cho dữ liệu có xu hướng.
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  • Damped. Mô hình giảm chấn làm giảm xu hướng trong phương pháp của Holt.
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2.2 Phân rã thông thường và phân rã STL

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Ở đây, chúng tôi giới thiệu hai phương pháp phân rã thường được sử dụng.

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2.2.1 Phân rã thông thường

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Thuật toán phân rã cổ điển nhân số thông thường cho một chuỗi có chu kỳ theo mùa m có bốn bước:

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  1. Tính thành phần xu hướng \(\hat{T_t}\) bằng phương pháp trung bình động đơn giản.
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  2. Triệt tiêu xu hướng: \(y_t/\hat{T_t}\) .
    3. -
  3. Tính thành phần theo mùa \(\hat{S_t}\) bằng cách lấy trung bình các giá trị mùa tương ứng và sau đó điều chỉnh để đảm bảo rằng chúng cộng với m .
    4. -
  4. Tính thành phần phần dư \(\hat{R_t}\): \(\hat{R_t} = y_t/(\hat{T_t}\hat{S_t})\)
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2.2.2 Phân rã STL

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Phân rã STL bao gồm hai thủ tục đệ quy: một vòng lặp bên trong và một vòng lặp bên ngoài. Vòng bên trong phù hợp với xu hướng và tính toán thành phần theo mùa. Mỗi vòng lặp bên trong bao gồm tổng cộng sáu bước:

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  1. Detrend. Tính chuỗi detrend \(y_v - T_v^{(k)}\). Đối với giá trị đầu tiên, \(T_v^{(0)} = 0\).
    2. -
  2. Cycle-Subseries Smoothing. Sử dụng LOESS để làm trơn các nhóm con giá trị tại mỗi vị trí của chu kỳ theo mùa. Kết quả được đánh dấu là \(C_v^{(k+1)}\) .
    3. -
  3. Low-Pass Filtering of Smoothed Cycle-Subseries. Quy trình này bao gồm hai bộ lọc MA và làm trơn LOESS. Kết quả được đánh dấu là \(L_v^{(k+1)}\) .
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  4. Detrending of Smoothed Cycle-Subseries. \(S_v^{(k+1)} = C_v^{(k+1)} - L_v^{(k+1)}\).
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  5. Deseasonalizing. \(y_v -S_v^{(k+1)}\) .
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  6. Trend Smoothing. Sử dụng LOESS để làm mịn chuỗi không mùa vụ để có được thành phần xu hướng của chuỗi này \(T_v^{(k+1)}\) .
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Nếu phát hiện bất thường nào, một vòng lặp bên ngoài sẽ được áp dụng và thay thế LOESS ở bước thứ hai và thứ sáu của vòng lặp bên trong bằng LOESS.

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2.3 ARIMA, ETS và Theta

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  • ARIMA. Mô hình ARIMA giả định các giá trị trong tương lai là sự kết hợp tuyến tính của các giá trị trong quá khứ và mẫu ngẫu nhiên, đóng góp vào các thành phần AR và MA, tương ứng. SARIMA (ARIMA theo mùa) là một phần mở rộng của ARIMA hỗ trợ dữ liệu chuỗi thời gian với thành phần theo mùa rõ ràng. Sau khi phân tách STL được áp dụng, các mô hình SARIMA biến đổi thành các mô hình ARIMA thông thường khi STL xử lý phần theo mùa.

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  • ETS. Mô hình ETS là một họ các mô hình chuỗi thời gian với mô hình không gian trạng thái cơ bản bao gồm nhiều cấp thành phần, thành phần xu hướng (T), thành phần theo mùa (S) và thành phần sai số (E). Các dự báo được tạo ra bằng cách sử dụng phương pháp làm trơn hàm mũ là giá trị trung bình có trọng số của các quan sát trong quá khứ, với trọng số giảm dần theo cấp số nhân với các quan sát xa hơn. Sau khi ghép STL trên mô hình ETS, mô hình ETS đầy đủ suy biến thành phương pháp của Holt vì phương trình theo mùa được xử lý bởi STL.

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  • Phương pháp Theta. được đề xuất ban đầu vào năm 2000 bởi Assimakopoulos et al., hoạt động đặc biệt xuất sắc trong Cuộc thi M3 và được sử dụng làm tiêu chuẩn trong Cuộc thi M4. Phương pháp Theta dựa trên khái niệm điều chỉnh độ cong cục bộ của chuỗi thời gian thông qua hệ số \(\theta\) , được áp dụng trực tiếp cho sai phân bậc hai của dữ liệu. Hyndman đã chứng minh rằng dự báo h chu kỳ tiếp thu được bằng phương pháp Theta tương đương với SES có độ lệch phụ thuộc vào giá trị tham số làm mịn của SES, số kỳ dự báo h và dữ liệu.

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2.4 Phương pháp học máy

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Để áp dụng các phương pháp học máy thực hiện trong các nhiệm vụ dự báo chuỗi thời gian, sử dụng chiến lược nhúng để chuyển nhiệm vụ này thành vấn đề học tập có giám sát. Sau đây giới thiệu ngắn gọn các phương pháp học máy được sử dụng trong thử nghiệm này.

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  • k-NN. là một phương pháp phi tham số được sử dụng để phân loại và hồi quy. Trong cả hai trường hợp, đầu vào bao gồm k ví dụ huấn luyện gần nhất trong không gian đặc trưng. Trong hồi quy k -NN, đầu ra là giá trị thuộc tính cho đối tượng. Giá trị này là giá trị trung bình của k lân cận gần nhất dựa trên khoảng cách Euclidian.

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  • SVR. Support Vector Machine (SVM) là một phương pháp thành công cố gắng tìm một siêu phẳng tách biệt để tối đa hóa lề giữa hai lớp, trong khi SVR tìm kiếm một siêu phẳng để giảm thiểu lề giữa các vectơ hỗ trợ và siêu phẳng.

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  • CART. là một trong những phương pháp học máy được sử dụng phổ biến nhất và có thể được sử dụng để phân loại và hồi quy. CART phân đôi từng tính năng một cách đệ quy và chia không gian đầu vào thành nhiều ô. CART tính toán các phân phối xác suất của dự đoán tương ứng trong đó.

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  • RF. là một thuật toán học tập hợp dựa trên Cây quyết định. Tương tự như CART, Rừng Ngẫu nhiên có thể được sử dụng cho cả phân loại và hồi quy. Nó hoạt động bằng cách xây dựng nhiều cây quyết định tại thời điểm đào tạo và tính toán các dự đoán trung bình từ các cây riêng lẻ.

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  • GP. là một tổng quát của phân phối xác suất Gaussian. Nó sử dụng để đo tính đồng nhất giữa các điểm như một hàm nhân để dự đoán giá trị của một điểm chưa biết từ dữ liệu huấn luyện đầu vào. Kết quả dự đoán của nó chứa giá trị của điểm và thông tin về độ không đảm bảo, tức là phân bố Gaussian một chiều của nó.

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2.5 Phương pháp học sâu

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Đối với khả năng ghi nhớ giá trị lâu dài của RNNs đầy hứa hẹn, chúng tôi quyết định thử nghiệm mô hình học sâu. Ở đây, chúng tôi trình bày hai cấu trúc của RNN được thực hiện trong thử nghiệm của chúng tôi. Cái đầu tiên là CNNs nổi tiếng được xếp chồng lên nhau với các ô Bộ nhớ Ngắn hạn Dài (LSTM), và cái còn lại là cấu trúc ConvLSTM do Xingjian Shi et al đề xuất. trong NeurIPS 2015.

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  • CNN-LSTM. Chúng tôi sử dụng CNN 1D để xử lý chuỗi thời gian đơn biến. Nó có một lớp phức hợp ẩn lặp lại trên chuỗi 1D và theo sau một lớp tổng hợp để trích xuất các tính năng nổi bật nhất, sau đó được giải thích bởi một lớp được kết nối đầy đủ. Sau đó, chúng tôi xếp chồng nó với một số lớp LSTM, đây là một mô hình RNN được sử dụng rộng rãi, cung cấp giải pháp cho vấn đề gradient biến mất cho RNN. Nó được đề xuất bởi Sepp Hochreiter et al. vào năm 1997.

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  • Convolutional LSTM. ConvLSTM là một RNN có cấu trúc tích hợp trong cả chuyển đổi đầu vào trạng thái và trạng thái sang trạng thái. Nó xác định trạng thái tương lai của một ô nhất định trong lưới bằng đầu vào của các hàng xóm cục bộ và trạng thái trong quá khứ của nó. Điều này đạt được bằng cách sử dụng toán tử tích chập trong các chuyển đổi trạng thái sang trạng thái và đầu vào sang trạng thái. Thay vì đọc và trích xuất các tính năng bằng CNN và sau đó giải thích chúng bằng LSTM, ConvLSTM đọc và giải thích chúng cùng một lúc.

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3 Thực nghiệm

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Phần này trình bày cách chúng tôi tổ chức và thực hiện thử nghiệm của mình.

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3.1 Dữ liệu

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3.2 Các bước thực hiện với các phương pháp học máy và học sâu

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3.2.1 Tiền xử lý dữ liệu (Preprocessing)

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Trong thử nghiệm của chúng tôi, ba kỹ thuật tiền xử lý đã được thực hiện trên tất cả các chuỗi:

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  1. Deseasonalizing: Kiểm tra tự tương quan 90% ở độ trễ 12 được thực hiện để quyết định xem chuỗi có theo mùa hay không. Chúng tôi thực hiện phân rã thông thường hoặc phân rã STL nếu chuỗi theo mùa và trích xuất phần theo mùa.

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  2. Detrending: Thông thường để loại bỏ xu hướng người ta thường lấy sai phân bậc một. Trong phần này chúng tôi tính tốc độ tăng trưởng.

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  3. Scaling: Một cách chuẩn hóa được áp dụng, bằng cách trừ giá trị trung bình rồi chia cho độ lệch chuẩn.

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3.2.2 Thiết lập mô hình học tập có giám sát

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Bài toán dự đoán chuỗi thời gian có thể được chuyển đổi thành một mô hình học tập có giám sát mà phương pháp học máy và học sâu có thể thực hiện. Một cách tiếp cận thường được sử dụng là xây dựng tập huấn luyện bằng cách lấy trễ (lagging) và xếp chồng (stacking) chuỗi lịch sử nhiều lần, thường được gọi là kỹ thuật nhúng khi thực hiện trên R.

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3.2.3 Hậu xử lý dữ liệu ( Post-Processing)

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Phần xử lý sau bao gồm các bước đảo ngược của ba bước tiền xử lý:

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  1. Rescaling: Đảo ngược chuẩn hóa dữ liệu.
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Phương pháp thống kê không yêu cầu tiền xử lý hoặc hậu xử lý như yêu cầu của phương pháp học máy và học sâu. Tuy nhiên, các bước deseasonalization và reseasonalization là cần thiết cho các phương pháp dựa trên STL.

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Trong thử nghiệm của chúng tôi, chúng tôi đã thực hiện phân rã STL và xây dựng Các mô hình ARIMA, ETS và Theta dựa trên chuỗi điều chỉnh theo mùa để tính toán các dự báo điểm. Nó bao gồm ba thủ tục sau:

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  1. Deseasonalizing. Tính toán chuỗi mùa vụ bằng cách trích xuất thành phần theo mùa được tính bằng cách phân hủy STL.

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  2. Dự báo điểm. Xây dựng các mô hình ARIMA, ETS và Theta trên dữ liệu được điều chỉnh theo mùa và tính toán các giá trị dự báo.

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  3. Reseasonalizing. Tích hợp thành phần thời vụ trở lại để tính toán kết quả dự báo cuối cùng.

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Tác động của việc áp dụng phân tích STL trên các phương pháp thống kê là nó bỏ các phương pháp xử lý tính thời vụ nội tại của các phương pháp thống kê này.

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3.4 Lựa chọn và điều chỉnh tham số

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3.5 Đánh giá mô hình

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1 Phương pháp Holt-Winters là gì?

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Phương pháp Holt-Winters còn được gọi là làm trơn ba hàm mũ - là một phương pháp cực kỳ phổ biến và tương đối đơn giản để dự báo chuỗi thời gian.

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Phương pháp này phát triển dự trên ý tưởng của phương pháp san mũ ExponenTial Smoothing (ETS). Trong đó, chuỗi thời gian được chia ra làm 3 thành phần: giá trịtrung bình (mean), độ dốc (trend) theo thời gian và tính thời vụ (hoặc chu kỳ).

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2 Giải thích công thức làm mịn ba hàm mũ của Holt-Winters

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Phương pháp Holt-Winters sử dụng làm trơn theo cấp số nhân để mã hóa nhiều giá trị trong quá khứ và sử dụng chúng để dự đoán các giá trị cho hiện tại và tương lai. Làm trơn theo cấp số nhân đề cập đến việc sử dụng đường trung bình động có trọng số theo cấp số nhân (EWMA) để làm mượt một chuỗi thời gian. Nếu bạn có một số chuỗi thời gian x_t , bạn có thể xác định một chuỗi thời gian mới s t đó là một phiên bản làm mịn của x t . s t = α x t + (1− α ) s t −1 Vào cuối những năm 1950, Charles Holt đã nhận ra vấn đề với mô hình EWMA đơn giản với chuỗi thời gian theo xu hướng. Ông đã sửa đổi mô hình làm trơn hàm mũ đơn giản để giải thích cho xu hướng tuyến tính. Điều này được gọi là làm mịn theo cấp số nhân của Holt. Mô hình này phức tạp hơn một chút. Nó bao gồm hai EWMA: một cho các giá trị được làm mịn của xt và một cho độ dốc của nó . Mức độ điều khoản và xu hướng cũng được sử dụng. s t = α x t + (1− α ) ( s t −1+ b t −1) b t = β ( s t - s t - 1) + ( 1− β ) b t −1 Lưu ý rằng các giá trị được làm mịn tốt hơn nhiều như thế nào khi tuân theo chuỗi thời gian gốc với việc làm mịn theo cấp số nhân kép. Điều này có nghĩa là bạn sẽ nhận được nhiều dự báo tốt hơn. Để dự báo với mô hình này, bạn phải thực hiện một chút điều chỉnh. Bởi vì có một thuật ngữ khác cho độ dốc, bạn sẽ phải xem xét điều đó trong dự báo. Giả sử bạn đang cố gắng dự báo giá trị theo m bước thời gian trong tương lai. Công thức cho dự báo trước m , F t + m , là: F t + m = s t + mb t Lưu ý về cơ bản nó là công thức cho một dòng. Điều gì sẽ xảy ra nếu chuỗi thời gian của bạn không có xu hướng tuyến tính mà thay vào đó là một số kiểu thời vụ? Đối với điều này, bạn sẽ cần một EWMA khác. Học sinh của Holt, Peter Winters, đã mở rộng mô hình của giáo viên của mình bằng cách giới thiệu một thuật ngữ bổ sung cho yếu tố thời vụ. Lưu ý rằng có một biến L khác , phụ thuộc vào khoảng thời gian của tính thời vụ và phải được biết trước. Ba khía cạnh của hành vi chuỗi thời gian — giá trị, xu hướng và tính thời vụ — được biểu thị dưới dạng ba loại làm mịn theo cấp số nhân, vì vậy Holt-Winters được gọi là làm trơn ba cấp số nhân. Mô hình dự đoán giá trị hiện tại hoặc tương lai bằng cách tính toán các tác động tổng hợp của ba ảnh hưởng này. Mô hình yêu cầu một số tham số: một tham số cho mỗi lần làm mịn (ɑ, β, γ), độ dài của một mùa và số chu kỳ trong một mùa. Ví dụ về dự báo Holt-Winters Phần khó nhất của dự báo Holt-Winters là hiểu cách hoạt động của mô hình và chọn các thông số tốt. Để giải quyết vấn đề đầu tiên, chúng ta sẽ xem qua một mô hình ví dụ bằng cách thực hiện Holt-Winters “bằng tay”. Cách thông thường để giải thích Holt-Winters là hiển thị một loạt các phương trình phức tạp với các chữ cái Hy Lạp và ký tự con. Chúng tôi sẽ bỏ qua phép toán và chỉ ra cách thức hoạt động của nó, đơn giản hơn rất nhiều. Chúng tôi sẽ làm việc với chuỗi thời gian này: Đây là mã R tôi đã sử dụng để tạo mã đó. Mô hình là rõ ràng: âm mưu lặp lại các giá trị [0, 1, 0, 0, 0]. Bạn có thể cho tôi biết năm giá trị tiếp theo sẽ là gì không? Tất nhiên bạn có thể, bởi vì tôi vừa nói với bạn! Chúng là [0, 1, 0, 0, 0]. Sẽ như thế nào nếu chúng ta tạo các giá trị so với giá trị trung bình của năm điểm đó? Trung bình của (0 + 1 + 0 + 0 + 0) / 5 là 0,2, chúng tôi sẽ vẽ biểu đồ dưới dạng một đường ngang: Holt-Winters có một thành phần xu hướng. Nếu chúng ta đặt tham số của nó bằng 0, Holt-Winters bỏ qua xu hướng (độ dốc), do đó mô hình đơn giản hóa. Bây giờ, nó chỉ là một loạt các giá trị so với giá trị trung bình. Trong biểu đồ của chúng tôi, các giá trị liên quan đến 0,2 là [-0,2, 0,8, -0,2, -0,2, -0,2]. Nếu chúng tôi làm Holt-Winters mà không có xu hướng, thì đó là kiểu mô hình chúng tôi sẽ xây dựng. Đây là những gì chức năng Holt-Winters trong R mang lại, với một số chú thích màu xanh lam mà tôi đã thêm theo cách thủ công: Dự báo với xu hướng chỉ là một cải tiến của điều này. Thay vì sử dụng giá trị trung bình cố định làm nền tảng, bạn phải kết hợp độ dốc của đường. Đây là một mô hình có xu hướng: Tính thời vụ trong dự báo là gì? Tính thời vụ đề cập đến một mô hình tuần hoàn hoặc một khoảng thời gian cố định có chứa sự lặp lại đầy đủ. Tuy nhiên, tính thời vụ có thể gây nhầm lẫn. Bạn có thể nghĩ rằng dữ liệu của mình lặp lại hàng ngày (có cao điểm vào lúc 2 giờ chiều mỗi ngày), nhưng nếu cuối tuần có hành vi khác (không có cao điểm lúc 2 giờ chiều vào Chủ nhật) thì mùa của bạn thực sự là một tuần chứ không phải một ngày. Trong mùa giải, có những khoảng thời gian, đó là mức độ chi tiết của dự đoán. Nếu bạn muốn lập mô hình giá trị cho mỗi giờ hàng ngày trong vòng một tuần, thì mùa của bạn dài 168 giờ và chu kỳ của bạn là 1 giờ. Bạn đã biết, theo định nghĩa, chuỗi ví dụ lặp lại sau mỗi năm điểm, tức là, mùa là năm giai đoạn. Điều gì sẽ xảy ra nếu bạn không biết mùa là gì cho một chuỗi thời gian? Làm thế nào bạn có thể tìm ra nó? Hậu quả của việc làm sai là gì? Thời vụ thích hợp là yếu tố quyết định đối với dự báo của Holt-Winters. Để minh họa điều này, hãy xem điều gì sẽ xảy ra khi bạn sử dụng một mùa gồm sáu giai đoạn, một mùa lớn hơn một mùa thực tế là năm giai đoạn: Dự báo, là đường màu đỏ trong biểu đồ, trở nên kém chính xác hơn và biến thành rác. Để có được kết quả tốt, bạn cần cung cấp cho mô hình các thông số tốt. Đây là thách thức thứ hai với Holt-Winters dự báo. Xác định các tham số tối ưu cho các phép tính công thức Holt-Winters Chọn thời vụ là một vấn đề khó khăn. Dự báo mục đích chung là khó vì nó phải sẵn sàng để sử dụng trên bất kỳ tập dữ liệu nào, có thể có bất kỳ sự kết hợp nào giữa các giá trị, xu hướng và tính thời vụ. Nó thậm chí có thể không có một số thành phần đó. Đây thường là những ẩn số trừ khi bạn đang kiểm tra dữ liệu theo cách thủ công và tùy chỉnh mô hình cho nó. Tại SolarWinds , chúng tôi cần chức năng dự báo hoạt động mà không cần bất kỳ giả định hoặc kiến thức nào về đặc điểm của dữ liệu. Có nhiều cách tiếp cận khác nhau cho vấn đề này: máy học, phân tích Fourier, v.v. Giải pháp của chúng tôi cho vấn đề này là thử nhiều cách kết hợp khác nhau, sử dụng các kỹ thuật như tối ưu hóa Nelder -Mead để chọn ra người chiến thắng. Điều này tận dụng lợi thế của việc máy tính xử lý nhanh những việc đơn giản, vì vậy chúng tôi hình thành vấn đề một cách đơn giản: tôi có thể định lượng mức độ tốt của một dự báo không và tôi có thể so sánh các dự báo không? Sau đó, chúng tôi thử các kết hợp khác nhau của các tham số và xem những gì giành chiến thắng. Hãy định lượng mức độ tốt của một dự báo. Dự báo cuối cùng là tệ, nhưng tệ đến mức nào? Cách thông thường để định lượng độ chính xác của dự báo là tính toán sự khác biệt giữa giá trị dự đoán và giá trị thực tế. Các mũi tên màu xanh lam trong biểu đồ sau biểu thị mức độ chênh lệch của dự đoán so với giá trị thực tế. Để định lượng độ chính xác tổng thể, bạn có thể kết hợp những khác biệt này thành một giá trị duy nhất bằng cách lấy giá trị trung bình hoặc tổng bình phương. Kết quả là một giá trị nhỏ hơn nếu dự báo tốt hơn và lớn hơn nếu dự báo kém hơn. Điều này cung cấp cho bạn một cách tốt để so sánh kết quả dự báo. Mã dự báo của chúng tôi thử rất nhiều kết hợp (nhiều!) Với các tham số khác nhau và chọn những tham số tạo ra điểm lỗi kết hợp thấp nhất. Để minh họa điều này, đây là một loạt các dự báo trên cùng một chuỗi thời gian, thử các tần số khác nhau. Phương án có tính thời vụ phù hợp (năm khoảng thời gian mỗi mùa) dễ dàng nhận ra bằng mắt thường vì sự khác biệt giữa dữ liệu và dự báo là nhỏ. Đây là một ví dụ trực quan về những gì dự báo của chúng tôi thực hiện thông qua tối ưu hóa. Nó cũng tối ưu hóa các thông số khác, chẳng hạn như xu hướng. Phương pháp dự báo Holt-Winters để phát hiện sự bất thường của cơ sở dữ liệu Dự báo Holt-Winters có sức mạnh đáng ngạc nhiên mặc dù nó đơn giản. Nó có thể xử lý rất nhiều mẫu phức tạp theo mùa bằng cách đơn giản là tìm giá trị trung tâm, sau đó thêm vào các hiệu ứng của độ dốc và tính thời vụ. Bí quyết là cung cấp cho nó các thông số phù hợp. Đây là một vấn đề khó, nhưng chúng tôi nhận thấy rằng tối ưu hóa số có thể chọn các giá trị tốt một cách nhanh chóng. Giải pháp này dễ xây dựng và dễ hiểu, có giá trị cho các mục đích của chúng tôi. Nếu bạn muốn khám phá thêm, đây là một số tài nguyên khác: • https://www.otexts.org/fpp/7/5 • https://grisha.org/blog/2016/01/29/triple-exponential-smoothing-forecasting/ • http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc435.htm SolarWinds Database Performance Monitor cung cấp khả năng phát hiện bất thường truy vấn dựa trên các thuật toán thống kê nâng cao như dự báo Holt-Winters được thiết kế để tính đến một số loại thời vụ để tránh dương tính giả tốt hơn. Bắt đầu dùng thử DPM miễn phí 14 ngày để xem tính năng này hoạt động.

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Slides/css/tpb_background.PNG b/10-Publication/1. Slides/css/tpb_background.PNG deleted file mode 100644 index e9a62b8..0000000 Binary files a/10-Publication/1. Slides/css/tpb_background.PNG and /dev/null differ diff --git a/10-Publication/1. Slides/css/tpb_title_background.PNG b/10-Publication/1. Slides/css/tpb_title_background.PNG deleted file mode 100644 index 1d80821..0000000 Binary files a/10-Publication/1. Slides/css/tpb_title_background.PNG and /dev/null differ diff --git a/10-Publication/1. Slides/xaringanthemer.Rmd b/10-Publication/1. Slides/xaringanthemer.Rmd deleted file mode 100644 index ec24769..0000000 --- a/10-Publication/1. Slides/xaringanthemer.Rmd +++ /dev/null @@ -1,386 +0,0 @@ ---- -title: "Xaringanthemer" -subtitle: "⚔️ xaringan +
😎 xaringanthemer" -author: - - "Nguyen Ngoc Binh" -date: '`r Sys.Date()`' -output: - xaringan::moon_reader: - css: ["css/tpb.css", "default"] - seal: true - nature: - slideNumberFormat: "%current%" - highlightStyle: github - highlightLines: true - ratio: 16:9 - countIncrementalSlides: true ---- - -```{r setup, include=FALSE} -options(htmltools.dir.version = FALSE) -knitr::opts_chunk$set( - fig.width=9, fig.height=3.5, fig.retina=3, - out.width = "100%", - cache = FALSE, - echo = TRUE, - message = FALSE, - warning = FALSE, - hiline = TRUE -) -``` - - -```{r xaringan-themer, include=FALSE, warning=FALSE, eval=FALSE} -library(xaringanthemer) -# style_duo_accent( -# primary_color= "#3e2f5b", -# secondary_color= "#3e2f5b", -# inverse_header_color= "#FFFFFF", -# background_image= "css/tpb_background.PNG", -# title_slide_background_image= "css/tpb_title_background.PNG", -# header_background_padding = "right", -# outfile = "nnb.css" -# ) -``` - - - -## Kiểu chữ - -Text can be **bold**, _italic_, ~~strikethrough~~, or `inline code`. - -[Link to another slide](#colors). - -### Lorem Ipsum - -Dolor imperdiet nostra sapien scelerisque praesent curae metus facilisis dignissim tortor. -Lacinia neque mollis nascetur neque urna velit bibendum. -Himenaeos suspendisse leo varius mus risus sagittis aliquet venenatis duis nec. - -- Dolor cubilia nostra nunc sodales - -- Consectetur aliquet mauris blandit - -- Ipsum dis nec porttitor urna sed - ---- -name: colors - -## Colors - -.left-column[ -Text color - -[Link Color](#3) - -**Bold Color** - -_Italic Color_ - -`Inline Code` -] - -.right-column[ -Lorem ipsum dolor sit amet, [consectetur adipiscing elit (link)](#3), -sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. -Erat nam at lectus urna. -Pellentesque elit ullamcorper **dignissim cras tincidunt (bold)** lobortis feugiat. -_Eros donec ac odio tempor_ orci dapibus ultrices. -Id porta nibh venenatis cras sed felis eget velit aliquet. -Aliquam id diam maecenas ultricies mi. -Enim sit amet -`code_color("inline")` -venenatis urna cursus eget nunc scelerisque viverra. -] - ---- - -# Big Topic or Inverse Slides `#` - -## Slide Headings `##` - -### Sub-slide Headings `###` - -#### Bold Call-Out `####` - -This is a normal paragraph text. Only use header levels 1-4. - -##### Possible, but not recommended `#####` - -###### Definitely don't use h6 `######` - ---- - -# Left-Column Headings - -.left-column[ -## First - -## Second - -## Third -] - -.right-column[ -Dolor quis aptent mus a dictum ultricies egestas. - -Amet egestas neque tempor fermentum proin massa! - -Dolor elementum fermentum pharetra lectus arcu pulvinar. -] - ---- - -class: inverse center middle - -# Topic Changing Interstitial - --- - -``` -class: inverse center middle -``` - ---- -layout: true - -## Blocks - ---- - -### Blockquote - -> This is a blockquote following a header. -> -> When something is important enough, you do it even if the odds are not in your favor. - ---- - -### Code Blocks - -#### R Code - -```{r eval=FALSE} -ggplot(gapminder) + - aes(x = gdpPercap, y = lifeExp, size = pop, color = country) + - geom_point() + - facet_wrap(~year) -``` - -#### JavaScript - -```js -var fun = function lang(l) { - dateformat.i18n = require('./lang/' + l) - return true; -} -``` - ---- - -### More R Code - -```{r eval=FALSE} -dplyr::starwars %>% dplyr::slice_sample(n = 4) -``` - ---- - -```{r message=TRUE, eval=requireNamespace("cli", quietly = TRUE)} -cli::cli_alert_success("It worked!") -``` - --- - -```{r message=TRUE} -message("Just a friendly message") -``` - --- - -```{r warning=TRUE} -warning("This could be bad...") -``` - --- - -```{r error=TRUE} -stop("I hope you're sitting down for this") -``` - - ---- -layout: true - -## Tables - ---- -exclude: `r if (requireNamespace("tibble", quietly=TRUE)) "false" else "true"` - -```{r eval=requireNamespace("tibble", quietly=TRUE)} -tibble::as_tibble(mtcars) -``` - ---- - -```{r} -knitr::kable(head(mtcars), format = 'html') -``` - ---- -exclude: `r if (requireNamespace("DT", quietly=TRUE)) "false" else "true"` - -```{r eval=requireNamespace("DT", quietly=TRUE)} -DT::datatable(head(mtcars), fillContainer = FALSE, options = list(pageLength = 4)) -``` - ---- -layout: true - -## Lists - ---- - -.pull-left[ -#### Here is an unordered list: - -* Item foo -* Item bar -* Item baz -* Item zip -] - -.pull-right[ - -#### And an ordered list: - -1. Item one -1. Item two -1. Item three -1. Item four -] - ---- - -### And a nested list: - -- level 1 item - - level 2 item - - level 2 item - - level 3 item - - level 3 item -- level 1 item - - level 2 item - - level 2 item - - level 2 item -- level 1 item - - level 2 item - - level 2 item -- level 1 item - ---- - -### Nesting an ol in ul in an ol - -- level 1 item (ul) - 1. level 2 item (ol) - 1. level 2 item (ol) - - level 3 item (ul) - - level 3 item (ul) -- level 1 item (ul) - 1. level 2 item (ol) - 1. level 2 item (ol) - - level 3 item (ul) - - level 3 item (ul) - 1. level 4 item (ol) - 1. level 4 item (ol) - - level 3 item (ul) - - level 3 item (ul) -- level 1 item (ul) - ---- -layout: true - -## Plots - ---- - -```{r plot-example, eval=requireNamespace("ggplot2", quietly=TRUE)} -library(ggplot2) -(g <- ggplot(mpg) + aes(hwy, cty, color = class) + geom_point()) -``` - ---- - -```{r plot-example-themed, eval=requireNamespace("showtext", quietly=TRUE) && requireNamespace("ggplot2", quietly=TRUE)} -g + xaringanthemer::theme_xaringan(text_font_size = 16, title_font_size = 18) + - ggtitle("A Plot About Cars") -``` - -.footnote[Requires `{showtext}`] - ---- -layout: false - -## Square image - -
GithHub Octocat
- -.footnote[GitHub Octocat] - ---- - -### Wide image - -![A wide image with a diagram of branching in git.](https://docs.github.com/assets/images/help/repository/branching.png) - -.footnote[Wide images scale to 100% slide width] - ---- - -## Two images - -.pull-left[ -![A GitHub Octocat, style "mother hubber"](https://octodex.github.com/images/motherhubbertocat.png) -] - -.pull-right[ -![A GitHub Octocat, style "dinotcat"](https://octodex.github.com/images/dinotocat.png) -] - ---- - -### Definition lists can be used with HTML syntax. - -
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Name
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- ---- - -class: title-slide - -# Thanks! - -## RDM - - - ---- -class: center, middle - -# Thanks! - -Slides created via the R packages: - -[**xaringan**](https://github.com/yihui/xaringan)
-[gadenbuie/xaringanthemer](https://github.com/gadenbuie/xaringanthemer) - -The chakra comes from [remark.js](https://remarkjs.com), [**knitr**](http://yihui.name/knitr), and [R Markdown](https://rmarkdown.rstudio.com). diff --git a/10-Publication/README.Rmd b/10-Publication/README.Rmd deleted file mode 100644 index c5f8b62..0000000 --- a/10-Publication/README.Rmd +++ /dev/null @@ -1,25 +0,0 @@ ---- -title: "10-Publication" -output: github_document ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE) -``` - -# Rmarkdown - -### Slide - -- html slide: [xaringanthemer](https://github.com/gadenbuie/xaringanthemer) -- pptx slide: [officedown](https://github.com/davidgohel/officedown) - -### Document - -- docx: [officedown](https://github.com/davidgohel/officedown), [flextable](https://github.com/davidgohel/flextable) - -### Html - -- html_document: [rmarkdown](https://github.com/rstudio/rmarkdown) - -# Shiny \ No newline at end of file diff --git a/13-Database/2. Scripts/R/push_data_to_db.R b/99-Practice/2. Scripts/R/push_data_to_db.R similarity index 100% rename from 13-Database/2. Scripts/R/push_data_to_db.R rename to 99-Practice/2. Scripts/R/push_data_to_db.R diff --git a/02-Data Manipulation/1. Slides/css/nnb.css b/99-Practice/Slides/css/nnb.css similarity index 100% rename from 02-Data Manipulation/1. Slides/css/nnb.css rename to 99-Practice/Slides/css/nnb.css diff --git a/02-Data Manipulation/1. Slides/css/tpb_background.PNG b/99-Practice/Slides/css/tpb_background.PNG similarity index 100% rename from 02-Data Manipulation/1. Slides/css/tpb_background.PNG rename to 99-Practice/Slides/css/tpb_background.PNG diff --git a/02-Data Manipulation/1. Slides/css/tpb_title_background.PNG b/99-Practice/Slides/css/tpb_title_background.PNG similarity index 100% rename from 02-Data Manipulation/1. Slides/css/tpb_title_background.PNG rename to 99-Practice/Slides/css/tpb_title_background.PNG diff --git a/02-Data Manipulation/1. 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Slides/xaringanthemer.Rmd rename to 99-Practice/Slides/xaringanthemer.Rmd diff --git a/01-Introduction/Vitae.Rmd b/99-Practice/Vitae/Vitae.Rmd similarity index 100% rename from 01-Introduction/Vitae.Rmd rename to 99-Practice/Vitae/Vitae.Rmd diff --git a/01-Introduction/Vitae.tex b/99-Practice/Vitae/Vitae.tex similarity index 100% rename from 01-Introduction/Vitae.tex rename to 99-Practice/Vitae/Vitae.tex diff --git a/01-Introduction/mariecurie.jpg b/99-Practice/Vitae/mariecurie.jpg similarity index 100% rename from 01-Introduction/mariecurie.jpg rename to 99-Practice/Vitae/mariecurie.jpg diff --git a/01-Introduction/packages.bib b/99-Practice/Vitae/packages.bib similarity index 100% rename from 01-Introduction/packages.bib rename to 99-Practice/Vitae/packages.bib diff --git a/01-Introduction/twentysecondcv.cls b/99-Practice/Vitae/twentysecondcv.cls similarity index 100% rename from 01-Introduction/twentysecondcv.cls rename to 99-Practice/Vitae/twentysecondcv.cls diff --git a/README.md b/README.md index ca6a089..e4d72c6 100644 --- a/README.md +++ b/README.md @@ -73,3 +73,148 @@ Bao gồm các chủ đề quan trọng để phát triển kỹ năng và kiế - Xử lý dữ liệu trích xuất từ web để sử dụng trong khoa học dữ liệu. ## 15-Crypto + +``` +BMLB +├─ 01-Introduction +│ ├─ Index.md +│ └─ README.md +├─ 02-Data Manipulation +│ └─ README.md +├─ 03-Data Visualization +│ └─ README.md +├─ 04-Basic Statistics +│ ├─ README.md +│ └─ statistics.md +├─ 05-Regression +│ ├─ README.md +│ └─ Survival Analysis Basics.Rmd +├─ 06-Timeseries +│ ├─ history_of_timeseries_models.Rmd +│ ├─ holt-winters.Rmd +│ ├─ Multiple_Time_Series_Forecast.Rmd +│ ├─ README.md +│ └─ STL_decomposition.Rmd +├─ 07-Panel Data Models +│ └─ README.md +├─ 08-Machine Learning +│ └─ README.md +├─ 09-Model Deployment +│ └─ README.md +├─ 10-Publication +│ └─ README.md +├─ 11-Git +│ └─ README.md +├─ 12-Docker +│ └─ README.md +├─ 13-Database +│ ├─ README.md +│ └─ README.Rmd +├─ 14-Web Craping +│ └─ README.md +├─ 15-Blogdown +│ └─ blogdown_dev.R +├─ 99-Practice +│ ├─ 2. Scripts +│ │ └─ R +│ │ └─ push_data_to_db.R +│ ├─ Slides +│ │ ├─ css +│ │ │ ├─ nnb.css +│ │ │ ├─ tpb_background.PNG +│ │ │ └─ tpb_title_background.PNG +│ │ └─ xaringanthemer.Rmd +│ ├─ tuning_models_with_workflowsets.Rmd +│ └─ Vitae +│ ├─ mariecurie.jpg +│ ├─ packages.bib +│ ├─ twentysecondcv.cls +│ ├─ Vitae.Rmd +│ └─ Vitae.tex +├─ bml.lectures.Rproj +├─ dev +│ └─ templates +│ ├─ Power point +│ │ └─ facet.pptx +│ └─ Rmd +│ ├─ powerpoint.pptx +│ ├─ powerpoint.Rmd +│ ├─ r-presentation-figure +│ │ └─ unnamed-chunk-2-1.png +│ ├─ r-presentation.md +│ └─ r-presentation.Rpres +├─ images +│ ├─ b_hex.png +│ ├─ faylab-manual-quarto-yml.png +│ ├─ faylab-manual.png +│ ├─ github-action-green.png +│ ├─ github-action-orange.png +│ ├─ github-edit-readme.png +│ ├─ github-source-gh-pages.png +│ ├─ openscapes_hex.png +│ ├─ quarto-files-github.png +│ ├─ quarto-yml-site-side-by-side.png +│ ├─ quarto-yml-site-side-by-side2.png +│ ├─ rstudio-insert-citation-doi.png +│ └─ rstudio-insert-citation.png +├─ include-files.lua +├─ index.qmd +├─ LICENSE +├─ README.html +├─ README.md +├─ _quarto.yml +└─ _site + ├─ images + │ ├─ github-action-green.png + │ ├─ github-action-orange.png + │ ├─ github-edit-readme.png + │ ├─ github-source-gh-pages.png + │ ├─ openscapes_hex.png + │ ├─ quarto-files-github.png + │ └─ quarto-yml-site-side-by-side2.png + ├─ index.html + ├─ learning-more.html + ├─ quarto-workflows + │ ├─ browser.html + │ ├─ images + │ │ ├─ github-commit.png + │ │ ├─ github-edit-index.png + │ │ ├─ github-preview-show-diff.png + │ │ ├─ jupyter-execute-cell.png + │ │ ├─ jupyter-python-example.png + │ │ ├─ jupyter-raw-chunk.png + │ │ ├─ jupyter-side-by-side.png + │ │ ├─ quarto-yml-site-side-by-side3.png + │ │ └─ rstudio-orientation.png + │ ├─ index.html + │ ├─ jupyter.html + │ └─ rstudio.html + ├─ robots.txt + ├─ search.json + ├─ sitemap.xml + ├─ site_libs + │ ├─ bootstrap + │ │ ├─ bootstrap-dark.min.css + │ │ ├─ bootstrap-icons.css + │ │ ├─ bootstrap-icons.woff + │ │ ├─ bootstrap.min.css + │ │ └─ bootstrap.min.js + │ ├─ clipboard + │ │ └─ clipboard.min.js + │ ├─ quarto-html + │ │ ├─ anchor.min.js + │ │ ├─ popper.min.js + │ │ ├─ quarto-syntax-highlighting-dark.css + │ │ ├─ quarto-syntax-highlighting.css + │ │ ├─ quarto.js + │ │ ├─ tippy.css + │ │ └─ tippy.umd.min.js + │ ├─ quarto-nav + │ │ └─ quarto-nav.js + │ └─ quarto-search + │ ├─ autocomplete.umd.js + │ ├─ fuse.min.js + │ └─ quarto-search.js + └─ transition-from-rmarkdown.html + +``` \ No newline at end of file diff --git a/_quarto.yml b/_quarto.yml new file mode 100644 index 0000000..5bec854 --- /dev/null +++ b/_quarto.yml @@ -0,0 +1,76 @@ +project: + type: website + +website: + page-navigation: true + title: "Making sharable documents with Quarto" + site-url: "https://nguyenngocbinh.github.io/bmlb" + repo-url: https://github.com/nguyenngocbinh/bmlb + repo-actions: [edit, issue] + + page-footer: + right: "This page is built with ❤️ and [Quarto](https://quarto.org/)." + left: "© CC-By NguyenNgocBinh, 2023" + + sidebar: + logo: "images/b_hex.png" + pinned: true + align: center + tools: + - icon: globe + href: https://nguyenngocbinh.github.io/bmlb + text: "nguyenngocbinh.github.io/bmlb" + - icon: github + href: https://github.com/nguyenngocbinh/bmlb + text: "github" + - icon: twitter + href: https://twitter.com/nanabi88 + text: "nanabi88 Twitter" + + style: "docked" + search: true + collapse-level: 1 + contents: + - href: index.qmd + text: Welcome + - section: 01-Introduction/Index.md + - section: 02-Data Manipulation/README.md + - section: 03-Data Visualization/README.md + - section: 04-Basic Statistics/README.md + contents: + - 04-Basic Statistics/statistics.md + - section: 05-Regression/README.md + contents: + - 05-Regression/Survival Analysis Basics.Rmd + - section: 06-Timeseries/README.md + contents: + - 06-Timeseries/history_of_timeseries_models.Rmd + - 06-Timeseries/holt-winters.Rmd + - 06-Timeseries/Multiple_Time_Series_Forecast.Rmd + - 06-Timeseries/STL_decomposition.Rmd + - section: 07-Panel Data Models/README.md + - section: 08-Machine Learning/README.md + - section: 09-Model Deployment/README.md + - section: 10-Publication/README.md + - section: 11-Git/README.md + - section: 12-Docker/README.md + - section: 13-Database/README.md + - section: 14-Web Craping/README.md + - section: 15-Blogdown/README.md + - section: 99-Practice/README.md + +format: + html: + theme: + light: [cosmo, theme.scss] # from https://github.com/sta210-s22/website/blob/main/_quarto.yml + dark: [cosmo, theme-dark.scss] + code-copy: true + code-overflow: wrap + toc: true + + +filters: + - include-files.lua + - quarto + + diff --git a/_site/images/github-action-green.png b/_site/images/github-action-green.png new file mode 100644 index 0000000..24bb016 Binary files /dev/null and b/_site/images/github-action-green.png differ diff --git a/_site/images/github-action-orange.png b/_site/images/github-action-orange.png new file mode 100644 index 0000000..598f390 Binary files /dev/null and b/_site/images/github-action-orange.png differ diff --git a/_site/images/github-edit-readme.png b/_site/images/github-edit-readme.png new file mode 100644 index 0000000..47f0620 Binary files /dev/null and b/_site/images/github-edit-readme.png differ diff --git a/_site/images/github-source-gh-pages.png b/_site/images/github-source-gh-pages.png new file mode 100644 index 0000000..ea1bccd Binary files /dev/null and b/_site/images/github-source-gh-pages.png differ diff --git a/_site/images/openscapes_hex.png b/_site/images/openscapes_hex.png new file mode 100644 index 0000000..61bd103 Binary files /dev/null and b/_site/images/openscapes_hex.png differ diff --git a/_site/images/quarto-files-github.png b/_site/images/quarto-files-github.png new file mode 100644 index 0000000..44968cc Binary files /dev/null and b/_site/images/quarto-files-github.png differ diff --git a/_site/images/quarto-yml-site-side-by-side2.png b/_site/images/quarto-yml-site-side-by-side2.png new file mode 100644 index 0000000..37d64f5 Binary files /dev/null and b/_site/images/quarto-yml-site-side-by-side2.png differ diff --git a/_site/index.html b/_site/index.html new file mode 100644 index 0000000..a90cdad --- /dev/null +++ b/_site/index.html @@ -0,0 +1,410 @@ + + + + + + + + + +Making sharable documents with Quarto - 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Making shareable documents with Quarto

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Create open-source tutorials, onboarding docs, and much more

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Welcome

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It’s possible to create beautiful documentation to share online with Quarto that auto-updates with Github. This is very new and incredibly cool. This tutorial is an example of a quarto website — it is a really powerful way to create and share your work. You can communicate about science using the same reproducible workflow you and/or your colleagues use for analyses, whether or not you write code.

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Creating websites with Quarto can be done without knowing R, Python or HTML, CSS, etc, and that’s where we’ll start. However, Quarto integrates with these tools so you can make your websites as complex and beautiful as you like as you see examples and reuse and remix from others in the open community. This tutorial borrows heavily from a lot of great tutorials and resources you should check out too – there are links throughout.

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What is Quarto?

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Quarto helps you have your ideas and your code in one place, and present it in a beautiful way.

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Quarto unifies and extends the RMarkdown ecosystem - it unifies by combining the functionality of R Markdown, bookdown, distill, xaringian, etc into a single consistent system. And it extends in several ways: all features are possible beyond R too, including Python and Javascript. It also has more “guardrails”: accessibility and inclusion are centered in the design. Quarto is for people who love RMarkdown, and it’s for people who have never used RMarkdown.

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The ability for Quarto to streamline collaboration has been so cool and important for our NASA Openscapes project. Quarto has been a common place for us to collaborate - across R and Pyahon languages and coding expertise.

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What is this tutorial?

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Here, we’ll introduce Quarto by exploring this tutorial website, and practicing the basic Quarto workflow using different tools (GitHub browser, RStudio, and Jupyter) for editing your website.

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We’ll start off from the browser so you don’t need to install any additional software, however this approach is very limited and you will soon outgrow its capabilities. If you don’t already have a workflow and to edit files and sync to GitHub from your computer, I recommend RStudio. You don’t need to know R to use RStudio, and it has powerful editor features that make for happy workflows.

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Quarto.org is the go-to place for full documentation and more tutorials!

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Example Quarto sites

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A few Quarto websites from Openscapes - wo far we have been using Quarto for documentation using Quarto and Markdown files and Jupyter Notebooks.

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About

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Openscapes is about better science for future us. We help researchers reimagine data analysis, develop modern skills that are of immediate value to them, and cultivate collaborative and inclusive research teams as part of the broader global open movement.

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We’re developing this tutorial to help folks of different technical skills use Quarto for documentation and tutorial building. This tutorial was originally created for several different audiences: NASA-Openscapes researcher support engineers using Python, communications directors at organizations promoting open science who do not identify as coders, and fisheries scientists curious about transitioning from RMarkdown. We’re hoping it’s useful to folks with backgrounds as wide as these; if you find it useful or have suggestions for improvement, please let us know by clicking “Edit this page” or “Report an issue” at the upper right side of any page.

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Learning more

+
+ + + +
+ + + +
+ + +
+ +
+

Learn more

+

An excellent overview: Reproducible authoring with Quarto - Mine Çetinkaya-Rundel, Feb 2022 - slides, youtube

+
+

Examples in the wild:

+ +

See many more examples at the quarto gallery!

+
+
+

Inspiration

+

Are you making onboarding documentation? Check out The Fay Lab Manual for inspiration on structure - you could also start there and make it your own.

+ + +
+
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/_site/quarto-workflows/browser.html b/_site/quarto-workflows/browser.html new file mode 100644 index 0000000..91edb48 --- /dev/null +++ b/_site/quarto-workflows/browser.html @@ -0,0 +1,413 @@ + + + + + + + + + +Making sharable documents with Quarto - From the Browser + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + + +
+ +
+
+

From the Browser

+
+ + + +
+ + + +
+ + +
+ +

A workflow from the browser if good for getting started (since you do not need to install additional software) and for making small contributions, but is definitely limited. Once you feel comfortable here, you can move to a different setup.

+

Here’s an example of editing content on an existing page.

+
+

Edit content on an existing page

+

Let’s change the date on the home page of this website.

+

In your repository, navigate to index.md. Then, click the pencil icon in the top left to edit directly.

+
+
+

+
+
+

We are now in the “Edit file” tab of the editor, where we can make modifications. Let’s change the date to today’s date. Click the “Preview” tab to see your changes. You can even check the “Show diff” box on the right side to see the changes you’ve made.

+
+
+

+
+
+

While you’re here, see if there are additional changes to the text you’d like to make. Maybe changing the title or author at the top, or for the main text on the home page of the website.

+

Our index.md file is written in Markdown, which enables you to make simple text formatting. As you go back and forth from “Edit file” to “Preview”, notice the patterns of how the Markdown text looks when it is as source (“Edit file”) and when it is formatted (“Preview”). For example, in Markdown, you can make text as a header with # symbols, bold or italic with * symbols, and hyperlinks with [](). Notice that spacing is important: for example, there are carriage returns (when you hit the “return” key) before any bullet points. You can learn the short list of Markdown rules here: https://quarto.org/docs/authoring/markdown-basics.

+
+
+

Commit and publish

+

Commit your changes by scrolling to the bottom of the page and writing a commit message - a note to yourself and others about what happened. Write your commit message and then click the green “Commit changes” button.

+
+
+

+
+
+

Now, click back to the main page of your GitHub repository. You should see the orange dot confirming your website is published. You’ll have to wait for the GitHub Action to tell quarto to build your site for you to see the update, but it will be there!

+
+
+

Limitations

+

While awesome that we can edit using GitHub directly from the browser, there are obvious limitations. One is that to see your edits show up in your book, you have to publish using the GitHub Action. This is slow. Another limitation is that we can only work on one file at a time and commit them each separately, which also is slow. Using additional software can make things much better, as we explore in subsequent chapters.

+ + +
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/_site/quarto-workflows/images/github-commit.png b/_site/quarto-workflows/images/github-commit.png new file mode 100644 index 0000000..e4d61a7 Binary files /dev/null and b/_site/quarto-workflows/images/github-commit.png differ diff --git a/_site/quarto-workflows/images/github-edit-index.png b/_site/quarto-workflows/images/github-edit-index.png new file mode 100644 index 0000000..c7e46d8 Binary files /dev/null and b/_site/quarto-workflows/images/github-edit-index.png differ diff --git a/_site/quarto-workflows/images/github-preview-show-diff.png b/_site/quarto-workflows/images/github-preview-show-diff.png new file mode 100644 index 0000000..cfba685 Binary files /dev/null and b/_site/quarto-workflows/images/github-preview-show-diff.png differ diff --git a/_site/quarto-workflows/images/jupyter-execute-cell.png b/_site/quarto-workflows/images/jupyter-execute-cell.png new file mode 100644 index 0000000..aa1953f Binary files /dev/null and b/_site/quarto-workflows/images/jupyter-execute-cell.png differ diff --git a/_site/quarto-workflows/images/jupyter-python-example.png b/_site/quarto-workflows/images/jupyter-python-example.png new file mode 100644 index 0000000..056538c Binary files /dev/null and b/_site/quarto-workflows/images/jupyter-python-example.png differ diff --git a/_site/quarto-workflows/images/jupyter-raw-chunk.png b/_site/quarto-workflows/images/jupyter-raw-chunk.png new file mode 100644 index 0000000..f4ff786 Binary files /dev/null and b/_site/quarto-workflows/images/jupyter-raw-chunk.png differ diff --git a/_site/quarto-workflows/images/jupyter-side-by-side.png b/_site/quarto-workflows/images/jupyter-side-by-side.png new file mode 100644 index 0000000..0e37e18 Binary files /dev/null and b/_site/quarto-workflows/images/jupyter-side-by-side.png differ diff --git a/_site/quarto-workflows/images/quarto-yml-site-side-by-side3.png b/_site/quarto-workflows/images/quarto-yml-site-side-by-side3.png new file mode 100644 index 0000000..e2a4469 Binary files /dev/null and b/_site/quarto-workflows/images/quarto-yml-site-side-by-side3.png differ diff --git a/_site/quarto-workflows/images/rstudio-orientation.png b/_site/quarto-workflows/images/rstudio-orientation.png new file mode 100644 index 0000000..ff7a718 Binary files /dev/null and b/_site/quarto-workflows/images/rstudio-orientation.png differ diff --git a/_site/quarto-workflows/index.html b/_site/quarto-workflows/index.html new file mode 100644 index 0000000..16847f8 --- /dev/null +++ b/_site/quarto-workflows/index.html @@ -0,0 +1,508 @@ + + + + + + + + + +Making sharable documents with Quarto - Quarto workflows + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + + +
+ +
+
+

Quarto workflows

+
+ + + +
+ + + +
+ + +
+ + +
+

Basic Workflow

+

How do you work in Quarto? You can use whichever tool you’re comfortable with (RStudio, Jupyter, GitHub, VS Code, etc). Developing your quarto site will have the same basic workflow, no matter which tool you use. It is very iterative, and each is explored more below.

+
    +
  1. Authoring: write text, code, images, etc in a file. Supported files include .md, .Rmd, .qmd, .ipynb…
    2. +
  2. Update _quarto.yml as needed (for example, if you’ve created a new file you’d like included in your site)
    3. +
  3. Render individual files and/or the whole website
    4. +
  4. Repeat, repeat, repeat
    5. +
  5. Commit and push your website to GitHub, your updates will publish automatically!
    6. +
  6. Repeat all of the above to make the website as you’d like!
    7. +
+

Note: if editing from your internet Browser we won’t render in Step 3 will not be separate but combined with Step 5, which will only require a commit, not a push)

+
+
+

Authoring

+

As an author, you have a lot of options of how your text will be formatted, arranged, and interlinked. You will be writing in Markdown, which is a lightweight text formatting language. The Quarto documentation about authoring introduces markdown-basics that will get you started.

+

Each page of our site has a similar first few lines - this YAML, like we saw in our _quarto.yml and it is indicated by two sets of 3 dashes --- :

+
---
+title: My title
+---
+

You’re able to add more features to individual pages by including it in the YAML, which for the most part here only includes a title. See Quarto excecution options for more information of what you can include in the YAML.

+
+
+

Update _quarto.yml

+

Let’s have a closer look at the _quarto.yml file.

+

This type of file (.yml or .yaml) is written in YAML (“Yet Another Markup Language”). You’ll be able to shift the arrangement of webpages by reordering/adding/deleting them in the _quarto.yml file following the patterns you see in this example.

+
+
+

_quarto.yml and website side-by-side

+

+
+
+

Notice that there are multiple ways in the _quarto.yml for you to include a file in your website. For example, in the above image, the “First Observations” we see in the left sidebar of the published website (right image) is represented in _quarto.yml (left image) over two lines, with line 36 indicating the file reference and line 37 indicating the text to show up in the left sidebar. However, “From RStudio” is only represented in one line of _quarto.yml, on line 43. This represents two strategies for including a file in your website. By default, the title of a specified file will show up in the website’s sidebar, which is what is happening with the “From RStudio” example. If you would like more control over what is written in the sidebar vs the title of your files, then the approach we took with “First Observations” is what you’ll want to do: you’ll see that only “First Observations” shows up in the sidebar as we specified in _quarto.yml, but the page’s title says “First Observations & Setup” (which in our preference was too long for the sidebar).

+
+
+
+ +
+
+Note +
+
+
+

As you modify _quarto.yml, the most important thing to know is that spacing matters. Pay attention to whether text is indented by one, two, four, or other spaces, and make sure you follow it; if your site is not looking as expected it is likely a silent error in your YAML. Some text editors like RStudio provide debugging support for YAML and are highly recommended to save you time and heartache.

+
+
+
+
+

Install Quarto

+

https://quarto.org/docs/get-started/ describes how to install Quarto, which will depend on your operating system. We’ll walk through installation for each tool in the next chapters.

+ + +
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/_site/quarto-workflows/jupyter.html b/_site/quarto-workflows/jupyter.html new file mode 100644 index 0000000..ac8009c --- /dev/null +++ b/_site/quarto-workflows/jupyter.html @@ -0,0 +1,719 @@ + + + + + + + + + +Making sharable documents with Quarto - From Jupyter + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + + +
+ +
+
+

From Jupyter

+
+ + + +
+ + + +
+ + +
+ +

You can interact with Quarto through JupyterLab or JupyterHub. Your Jupyter setup will involve .ipynb notebooks and the command line. Quarto’s JupyterLab tutorials has great instructions on getting started with JupyterLab, including computations and authoring.

+

Here we will demonstrate how to work with this Quarto tutorial site in JupyterHub and add a Jupyter Notebook (.ipynb file). This example uses the NASA-Openscapes JupyterHub that already has all python environments as well as Quarto installed.

+
+

Setup

+
+

JupyterHub

+

Our JupyterHub is already setup with python environments as well as Quarto (through nasa-openscapes/corn), so there is no further installation required.

+
+
+

Clone your repo

+

You’ll start by cloning your repository into JupyterHub. Do this by opening a terminal (File > New > Terminal). In the Terminal, git clone your repository and cd into it:

+
git clone https://github.com/openscapes/quarto-website-tutorial
+cd quarto-website-tutorial
+
+
+

Install Quarto

+

Not needed - Quarto is already installed on the NASA-Openscapes JupyterHub! But to install elsewhere you would do so from https://quarto.org/docs/get-started/.

+

Quarto is a Command Line Interface (CLI), like git. Once download is complete, follow the installation prompts on your computer like you do for other software. You won’t see an application to click on when it is installed.

+

Note for Mac users: If you do not have administrative privileges, please select “Install for me only” during the Destination Selection installation step (you will first click on “Change Install Location” at the Installation Type step).

+

You can check to confirm that Quarto is installed properly from the command line:

+
quarto check install
+
+ +
+
+

You can also run:

+
    +
  • quarto check knitr to locate R, verify we have the rmarkdown package, and do a basic render
    • +
  • quarto check jupyter to locate Python, verify we have Jupyter, and do a basic render
    • +
  • quarto check to run all of these checks together
    • +
+
+
+
+
+ +
+
+

In Summer 2021 some NASA Mentors trying to install quarto locally was not an option, but they were able to install it inside a container using the following Dockerfile:

+
#| fold: true
+#| summary: "Show the Dockerfile"
+
+##############################
+# This Dockerfile installs quarto and then runs quarto serve against the
+# internal /home/quarto/to_serve.
+#
+# BUILD
+# -----
+# To build this container, run
+#
+#     docker build -t quarto_serve .
+#
+# Add the --no-cache option to force docker to build fresh and get the most
+# recent version of quarto.
+#
+#
+# RUN
+# ---
+# 1. Find the directory you want quarto to serve. Let's call this /PATH/TO/earthdata-cloud-cookbook.
+# 2. Run docker:
+#
+#     docker run --rm -it -p 4848:4848 -v /PATH/TO/earthdata-cloud-cookbook:/home/quarto/to_serve quarto_serve
+#
+# 3. Open your browser and go to http://127.0.0.1:4848/
+#
+##############################
+
+FROM ubuntu:hirsute
+
+######
+# Install some command line tools we'll need
+######
+RUN apt-get update
+RUN apt-get -y install wget
+RUN apt-get -y install gdebi-core
+RUN apt-get -y install git
+
+
+######
+# Install quarto (https://quarto.org/)
+######
+
+# This is a quick and dirty way of getting the newest version number from
+# https://github.com/quarto-dev/quarto-cli/releases/latest. What's happening is
+# we're pulling the version number out of the redirect URL. This will end up
+# with QVER set to something like 0.2.11.
+RUN QVER=`wget --max-redirect 0 https://github.com/quarto-dev/quarto-cli/releases/latest 2>&1 | grep "Location" | sed 's/L.*tag\/v//' | sed 's/ .*//'` \
+    && wget -O quarto.deb "https://github.com/quarto-dev/quarto-cli/releases/download/v$QVER/quarto-$QVER-amd64.deb"
+RUN gdebi -n quarto.deb
+
+# Run this to make sure quarto installed correctly
+RUN quarto check install
+
+
+######
+# Create a non-root user called quarto
+######
+RUN useradd -ms /bin/bash quarto
+USER quarto
+RUN mkdir /home/quarto/to_serve
+WORKDIR /home/quarto/to_serve
+
+
+######
+# Start quarto serve
+######
+
+CMD quarto serve --no-browse --host 0.0.0.0 --port 4848
+
+
+
+
+
+
+

Quarto preview

+

Let’s start off by previewing our quarto site locally. In Terminal, type quarto preview, which will provide a URL with a preview of our site!

+
quarto preview
+# Preparing to preview
+# Watching files for changes
+# Browse at https://openscapes.2i2c.cloud/user/jules32/proxy/4593/
+

Copy this URL into another browser window; and arrange them so you can see them both. I make a bit more space in Jupyter by collapsing the left file menu by clicking on the file icon at the top of the left sidebar.

+
+
+

+
+
+
+

Make a small change and preview it

+

Now we’ll be able to see live changes in the preview as we edit in our .md files. Let’s try it: Change the date in index.md by opening it from the file directory. Change to today’s date, and save. Your preview window will refresh automatically! If it does not, you can also refresh the page manually. The refreshed previewed site will now display your changes!

+
+
+
+

Create a new .ipynb page

+

Let’s add a new page to our site. Instead of an .md file like the others, let’s add a .ipynb file.

+

File > New > Notebook. Accept the default kernel by clicking Select.

+
+

First chunk: raw yaml

+

By default, this Notebook will give us a first chunk that is code. Let’s change it to raw so that we can write our yaml at the top.

+
+
+

+
+
+

In our Raw code chunk, let’s write the title of this document. We need three dashes --- on separate lines preceding and following the title:, which you can name as you’d like.

+
---
+title: Python Example
+---
+
+
+

Second chunk: Markdown

+

Let’s add a new chunk that is Markdown so we can write some description of what this page will be.

+

Click the + symbol at the top of the document, and this will add a new chunk, which by default again is a Code chunk. Change it to a Markdown Chunk following the steps we did above when switching to Raw.

+

Here, write a little bit of text in Markdown. Since your title is effectively a level-1 header, avoid using level-1 headers in the rest of your document. Here is some example text I wrote:

+
## Introduction
+
+This example has some Python code that will be a part of our Quarto site.
+
+
+

Third chunk: Code

+

Now let’s create a new chunk with the default Code setting.

+

Paste the following code (or write some of your own to test):

+
#| label: fig-polar
+#| fig-cap: "A line plot on a polar axis"
+import numpy as np
+import matplotlib.pyplot as plt
+r = np.arange(0, 2, 0.01)
+theta = 2 * np.pi * r
+fig, ax = plt.subplots(
+  subplot_kw = {'projection': 'polar'} 
+)
+ax.plot(theta, r)
+ax.set_rticks([0.5, 1, 1.5, 2])
+ax.grid(True)
+plt.show()
+

Now, go ahead and execute this code chunk like you normally would, by clicking the cursor in a code block and clicking the sideways “play” triangle to run the selected cells (and advance to the next cell). This code produces a plot.

+

Note that the code runs as it normally would; the code options in the comments are just comments.

+
+
+

Save your file

+

Save your document - I’ll call mine python-example.ipynb in the main repository.

+
+
+
+

Update _quarto.yml

+

Now we’ll add python-example.ipynb to our _quarto.yml file; this is where we register of all files to include in our site. Let’s add it after the section called “Basic Workflows”.

+

Open _quarto.yml by clicking on it from the file directory.

+

Scroll down to review the current contents in the sidebar: section. It’s there we see all the file arrangement that we see in the previewed site.

+

Add - python-example.ipynb to line 46, making sure that your indentation aligns with the other pages.

+
+
+

+
+
+

You’ll see that our new page shows up in our Preview, and the code is executed since we did that in the Jupyter Notebook itself. By default, Quarto will not execute code chunks since your computations will likely become more complex and you will want to control when they are executed (or “run”).

+

Since Quarto is still previewing our website and the python-example.ipynb, the plot also displays in the notebook after the code is run and the file is saved, as shown below.

+
+
+

+
+
+

So, your normal workflow for creating and running code blocks in your Jupyter Notebook is the same one you’ll use as Quarto displays the preview.

+
+
+

Quarto render

+

So far we have used Quarto preview view our website as we develop it. Quarto render will build the html elements of the website that we can see when we preview. Rendering will format the markdown text and code nicely as a website (or however is indicated in the _quarto.yml).

+

By default, Quarto render does not execute code in a Jupyter notebook. It will never run .ipynb files unless you tell it to.

+
+

Render whole notebook

+

If you would like it to specifically execute code in a Jupyter notebook, you can do so in Terminal.

+

Our Terminal is still busy previewing our website, so let’s open a new Terminal.

+

File > New > Terminal. Then type:

+
cd quarto-website-tutorial
+quarto render python-example.ipynb --execute
+
+
+
+

Authoring tips

+

Quarto.org has details about authoring, including specific instructions about authoring in Jupyter: quarto.org/docs/reference/cells/cells-jupyter.

+
+
+

Commit and push!

+

Committing and pushing will make the changes you see locally live on your website (using the GitHub Action we set up earlier).

+
+
+

Troubleshooting

+
+

My changes don’t show up in preview

+

Make sure you’ve saved your file! There might be a slight delay depending on your JupyterHub/Lab setup.

+
+
+

Quarto render hangs / does not complete

+

Check the specific notebook, are there any `—` throughout to denote line breaks rather than yaml? They might be causing the issue; consider deleting those.

+

Also check how long the first raw cell is. Are there level-1 headers (#)? Try removing them.

+ + +
+
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/_site/quarto-workflows/rstudio.html b/_site/quarto-workflows/rstudio.html new file mode 100644 index 0000000..bbe3467 --- /dev/null +++ b/_site/quarto-workflows/rstudio.html @@ -0,0 +1,520 @@ + + + + + + + + + +Making sharable documents with Quarto - From RStudio + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + + +
+ +
+
+

From RStudio

+
+ + + +
+ + + +
+ + +
+ +

The RStudio software (called an IDE, integrated development environment) is an excellent way to edit files and interface with GitHub. Plus, as it is made by the same folks who make Quarto, it has many integrated features for streamlining your workflow with Quarto, including how it previews your edits and provides debugging support for yaml! Quarto's RStudio tutorials has great instructions on getting started with JupyterLab, including computations and authoring.

+

Here is what you’ll need to do to set up and use RStudio with Quarto.

+
+

Setup

+
+

RStudio and GitHub

+

For a workflow with RStudio and GitHub on your local computer, you will need four things:

+
    +
  1. R
    2. +
  2. RStudio
    3. +
  3. Git
    4. +
  4. GitHub
    5. +
+

Follow the UCSB MEDS Installation Guide for detailed instructions on how to create accounts, download, install, and configure on Mac and Windows. This takes about 20 minutes. (For an even more detailed walk-through, see Allison Horst’s ESM 206 Google Doc).

+
+
+

Clone your repo

+

You’ll start by cloning your repository into RStudio.

+

File > New Project > Version Control > Git > paste your repository name.

+

R for Excel Users: Clone your repository using RStudio has detailed instructions and screenshots of these steps.

+
+
+

Install Quarto

+

Next, you’ll install Quarto: https://quarto.org/docs/get-started/. After downloading, follow the installation wizard on your computer. When it is complete, you won’t see an application or any new software, but it is now available to RStudio (as well as all other applications on your computer, including the command line).

+
+
+

RStudio orientation

+

Now let’s take a moment to get oriented. This is an RStudio project, which is indicated in the top-right. The bottom right pane shows all the files in your project; everything we’ve cloned from GitHub. We can open any RStudio project by opening its .Rproj file, or from RStudio File > Open Project ….

+
+
+

Screenshot of the RStudio IDE highlighting the project name and files pane

+

+
+
+
+
+

Visual Editor

+

The RStudio Visual Editor is quite new and has features that improve your writing experience. Working in the Visual Editor feels a bit like working in a Google Doc.

+

Here’s an example showing the same file in the original Source Editor with content in markdown format and in the Visual Editor with content that looks more like it will appear in a live site. You can switch freely between these modes.

+
+
+
+
+
+

Screenshot of the RStudio IDE with red oval highlighting the Source button.

+

+
+
+
+
+
+
+

Screenshot of the RStudio IDE with red oval highlighting the Visual button.

+

+
+
+
+
+
+

Already have some content formatted in a Google Doc? You can copy-paste it into the Visual Editor and most formatting will be retained.

+

The editing bar provides familiar point and click access to text formatting options like bulleted or numbered lists.

+
+
+

RStudio IDE Visual Editor editing bar is highlighted by a red rectangle

+

+
+
+
+

Keyboard shortcuts

+

The Visual Editor also lets you use many keyboard shortcuts that might be familiar for adding boldface (command-b), italics (command-i), or headers. On a Mac, option-command-2 will make a level 2 header. Try it with option-command-1, or option-command-0 for normal text!

+
+
+

Insert an image or figure

+

To insert an image (called a figure in Quarto), click the image icon. This brings up a window in which we can select the image, set its alignment, give it a caption and alt text, hyperlink it, or edit other metadata.

+
+
+

Pop-up window appears when image icon is clicked

+

+
+
+

Once an image is added, clicking on that image gives us editing options. We can resize it dynamically by clicking in the image and dragging a corner or side to resize. When an image is selected, its dimensions are displayed for editing. Clicking on the gray ellipsis to the right of the dimensions opens the pop-up window to access more metadata edits.

+
+
+

Insert a table

+

Similar to adding an image, to insert a table, we click the Table dropdown.

+
+
+
+
+

Quarto render

+

In the Build tab in the top-right pane, click “Render Website”. This will build the .html files and preview your website. It’s equivalent to “knitting” in RMarkdown.

+

Note that you can also click “Preview Website”. With “Render Website” in RStudio, Quarto is able to render and preview in one step.

+

If you’d ever like to stop the preview, in the bottom-left, click on the Jobs tab and then the red Stop button.

+
+

Make a small change and render it

+

Click on index.md. This will open this markdown file in a fourth pane; the editor pane. Make a small change, for example change to today’s date on Line 4. Then, save your file; there is a disc icon at the top of the file.

+

Then, render this file: press “Render” which is to the right of the disc icon that saves the file. This will render only this single file, as opposed to rerendering the whole website like when we clicked “Render Website” in the top right pane. Checking Render on Save (between the disc icon and the Render button) is a great strategy for doing this in one step.

+
+
+
+

Create a new .Rmd page

+

New > RMarkdown document > OK

+

The starter RMarkdown document has some R code inside: it displays a summary of the cars dataset that is pre-loaded into R (summary(cars)) and plots the pressure data that is also pre-loaded (plot(pressure)).

+

Save this document as r-example.rmd.

+
+
+

Update _quarto.yml

+

Now we’ll add r-example.rmd to our _quarto.yml file; this is where we register all files to include in our site. Let’s add it after the section called “Quarto Workflows”.

+

Open _quarto.yml by clicking on it from the file directory.

+

Scroll down to review the current contents in the sidebar: section under contents:. It’s there we see all the file arrangement that we see in the previewed site.

+

Add - r-example.rmd in its own line, making sure that your indentation aligns with the other pages.

+

From the Build tab, clicking Preview Website will recreate your website!

+
+
+

Authoring tips

+

Checking “Render on Save” is really helpful when iterating quickly on a document.

+

If the document is very code-heavy, consider using freeze that will not run the code each time.

+

Quarto.org has details about authoring, including specific instructions about authoring in RStudio.

+
+
+

Commit and push!

+

Committing and pushing will make the changes you see locally live on your website (using the GitHub Action we set up earlier).

+
+
+

Troubleshooting

+

If you have trouble rendering your website after for example changing the extenstion of a file from .md to .qmd, refreshing your RStudio often helps. Do this by clicking the project name at the upper right of the RStudio window (in this case, quarto-website-tutorial), and underneath the “close project” section, click the same name of your project: quarto-website-tutorial. This will relaunch your whole project afresh.

+ + +
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/_site/robots.txt b/_site/robots.txt new file mode 100644 index 0000000..cdf1385 --- /dev/null +++ b/_site/robots.txt @@ -0,0 +1 @@ +Sitemap: https://openscapes.github.io/quarto-website-tutorial/sitemap.xml diff --git a/_site/search.json b/_site/search.json new file mode 100644 index 0000000..a975ac4 --- /dev/null +++ b/_site/search.json @@ -0,0 +1,303 @@ +[ + { + "objectID": "transition-from-rmarkdown.html", + "href": "transition-from-rmarkdown.html", + "title": "Transition from RMarkdown", + "section": "", + "text": "You may already have workflows in RMarkdown and are interested in transitioning to Quarto.\nThere’s no hurry to migrate to Quarto. Keep using Rmarkdown and when you’re ready the migration will be fine.\nHere are some notes as we migrate RMarkdown sites.\nTODO: translating R code chunks" + }, + { + "objectID": "transition-from-rmarkdown.html#bookdown-to-quarto", + "href": "transition-from-rmarkdown.html#bookdown-to-quarto", + "title": "Transition from RMarkdown", + "section": "Bookdown to quarto", + "text": "Bookdown to quarto\ncreate _quarto.yml\nProject options > build tools > project build tools > none\nReload project\nDon’t need to delete anything immediately, but look at output.yml, purge afterbody.\nBookdown might be most challenging because of citations and cross-refs but still not that hard\n\nGitHub actions\nR" + }, + { + "objectID": "transition-from-rmarkdown.html#distill-to-quarto", + "href": "transition-from-rmarkdown.html#distill-to-quarto", + "title": "Transition from RMarkdown", + "section": "Distill to quarto", + "text": "Distill to quarto\nWe transitioned our events site from distill to quarto in May 2022 (github view before and after). We followed excellent notes and examples from Nick Tierney and Danielle Navarro.\nAfter we had changed all the files, the Build tab in the RStudio IDE still showed “Build website” rather then “Render Website” and “Preview Website”, and would error when we pushed them (because that button was expecting a distill site, not a quarto site). To fix this, we updated the .Rproj file. Clicking on the .Rproj file in the RStudio IDE will open a dialog box where you can click things you want (you can also open these in a text editor or from the GitHub website to see the actual text). To fix this situation with the Build tab: Project Options > Build Tools > Project Build Tools > None.\nLooking at files /posts/_metadata.yml and _quarto.yml helps see where things are defined. For example, to make event post citations appear, we added citation: true to /posts/_metadata.yml and in _quarto.yml under the website key we set site-url: https://openscapes.github.io/events. We deleted footer.html used with distill because footer is now defined in quarto.yml.\n\nPublishing notes\n\nBackground: Our distill site had been set up to output to a docs folder, and had GitHub Settings > Pages set to look there rather gh-pages branch. (Julie note: this was a new-to-me capability when we set up the events distill site in Spring 2021 so I had forgotten that was an option). We’ve inititally kept this same set-up for now with our events page in _quarto.yml: output-dir: docs. However, this is sub-optimal; better to not have to commit and push these files but to instead have a GitHub Action generate them upon a commit. So the following is what we did -\n\nDon’t specify output-dir in _quarto.yml. The output directory default is _site/, which is what we’d like.\nIf you currently have a docs/ folder (like we did as we were experimenting), delete it.\nUpdate .gitignore to ignore _site/. At the same time, we have it ignore caches and a .quarto file:\n/.quarto/\n*_cache/\n_site/\nPush these changes, merge into main.\nOn GitHub.com, in your repo, set up GitHub publishing\nFollow instructions from the explore and setup chapter." + }, + { + "objectID": "transition-from-rmarkdown.html#troubleshooting", + "href": "transition-from-rmarkdown.html#troubleshooting", + "title": "Transition from RMarkdown", + "section": "Troubleshooting", + "text": "Troubleshooting\n\nGitHub Action fails, says you need RMarkdown but you don’t have R code!\nAnd you changed all .Rmds to .qmds!\nYou likely have a few setup code chunks from RMarkdown, that look like this:\n{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = FALSE)\nYou can find them by opening each of your files and having a look, or use GitHub’s search for the keyword knitr" + }, + { + "objectID": "index.html", + "href": "index.html", + "title": "Making shareable documents with Quarto", + "section": "", + "text": "It’s possible to create beautiful documentation to share online with Quarto that auto-updates with Github. This is very new and incredibly cool. This tutorial is an example of a quarto website — it is a really powerful way to create and share your work. You can communicate about science using the same reproducible workflow you and/or your colleagues use for analyses, whether or not you write code.\nCreating websites with Quarto can be done without knowing R, Python or HTML, CSS, etc, and that’s where we’ll start. However, Quarto integrates with these tools so you can make your websites as complex and beautiful as you like as you see examples and reuse and remix from others in the open community. This tutorial borrows heavily from a lot of great tutorials and resources you should check out too – there are links throughout." + }, + { + "objectID": "index.html#what-is-quarto", + "href": "index.html#what-is-quarto", + "title": "Making shareable documents with Quarto", + "section": "What is Quarto?", + "text": "What is Quarto?\nQuarto helps you have your ideas and your code in one place, and present it in a beautiful way.\nQuarto unifies and extends the RMarkdown ecosystem - it unifies by combining the functionality of R Markdown, bookdown, distill, xaringian, etc into a single consistent system. And it extends in several ways: all features are possible beyond R too, including Python and Javascript. It also has more “guardrails”: accessibility and inclusion are centered in the design. Quarto is for people who love RMarkdown, and it’s for people who have never used RMarkdown.\nThe ability for Quarto to streamline collaboration has been so cool and important for our NASA Openscapes project. Quarto has been a common place for us to collaborate - across R and Pyahon languages and coding expertise." + }, + { + "objectID": "index.html#what-is-this-tutorial", + "href": "index.html#what-is-this-tutorial", + "title": "Making shareable documents with Quarto", + "section": "What is this tutorial?", + "text": "What is this tutorial?\nHere, we’ll introduce Quarto by exploring this tutorial website, and practicing the basic Quarto workflow using different tools (GitHub browser, RStudio, and Jupyter) for editing your website.\nWe’ll start off from the browser so you don’t need to install any additional software, however this approach is very limited and you will soon outgrow its capabilities. If you don’t already have a workflow and to edit files and sync to GitHub from your computer, I recommend RStudio. You don’t need to know R to use RStudio, and it has powerful editor features that make for happy workflows.\nQuarto.org is the go-to place for full documentation and more tutorials!" + }, + { + "objectID": "index.html#example-quarto-sites", + "href": "index.html#example-quarto-sites", + "title": "Making shareable documents with Quarto", + "section": "Example Quarto sites", + "text": "Example Quarto sites\nA few Quarto websites from Openscapes - wo far we have been using Quarto for documentation using Quarto and Markdown files and Jupyter Notebooks.\n\nChampions Lessons Series\nOpenscapes Approach Guide\n\n2021 NASA Cloud Hackathon" + }, + { + "objectID": "index.html#about", + "href": "index.html#about", + "title": "Making shareable documents with Quarto", + "section": "About", + "text": "About\nOpenscapes is about better science for future us. We help researchers reimagine data analysis, develop modern skills that are of immediate value to them, and cultivate collaborative and inclusive research teams as part of the broader global open movement.\nWe’re developing this tutorial to help folks of different technical skills use Quarto for documentation and tutorial building. This tutorial was originally created for several different audiences: NASA-Openscapes researcher support engineers using Python, communications directors at organizations promoting open science who do not identify as coders, and fisheries scientists curious about transitioning from RMarkdown. We’re hoping it’s useful to folks with backgrounds as wide as these; if you find it useful or have suggestions for improvement, please let us know by clicking “Edit this page” or “Report an issue” at the upper right side of any page." + }, + { + "objectID": "learning-more.html", + "href": "learning-more.html", + "title": "Learning more", + "section": "", + "text": "An excellent overview: Reproducible authoring with Quarto - Mine Çetinkaya-Rundel, Feb 2022 - slides, youtube\n\n\n\nOpenscapes Champions Lessons Series\nOpenscapes Approach Guide\n\nNASA Earthdata Cloud Cookbook\n\nSee many more examples at the quarto gallery!\n\n\n\nAre you making onboarding documentation? Check out The Fay Lab Manual for inspiration on structure - you could also start there and make it your own." + }, + { + "objectID": "explore.html", + "href": "explore.html", + "title": "Explore and setup", + "section": "", + "text": "With this tutorial, we have a working example website that we will explore together. We’ll learn a few rules and look for patterns to get an understanding of what things do to help you start customizing and making it your own. And you can continue to use this website as a reference after the tutorial, along with Quarto documentation.\nWe’ll start our exploration online looking at the website architecture and GitHub repository. Then we’ll setup a copy for ourselves so that we can modify from a working example, which is a great way to learn something new. We’ll set it up so that any modifications (commits) will automatically be republished via GitHub Actions. Subsequent chapters will describe how to modify your repo using different tools (browser, RStudio, Jupyter)." + }, + { + "objectID": "explore.html#exploring-online", + "href": "explore.html#exploring-online", + "title": "Explore and setup", + "section": "Exploring online", + "text": "Exploring online\n\nThe website itself\nThis website has 5 things you can see on the left sidebar:\n\nWelcome\nExploring our website\nQuarto workflows\nLearning more\nTransition from Rmd\n\nMost of these are pages, but you’ll see that “Quarto Workflows” has an arrow; it is a folder with additional pages inside.\n\n\nThe website’s repo\nLet’s go to this website’s GitHub repository (also called a “repo”), https://github.com/openscapes/quarto-website-tutorial. You can also click there from this page this tutorial website by clicking the GitHub octocat icon underneath the Openscapes logo in the left navbar (click it holding command on Mac, or control on a PC to open it in a different tab in your browser).\nHave a look at the filenames. We can recognize the names of the webpages we’ve seen above, and they have red arrows marking them in the image below. You’ll see the “quarto-workflows” folder and the rest in this site are .qmd files, which are plain text Quarto files that can combine Markdown text with code. index.qmd is the home page. If you click inside “quarto-workflows” you’ll see a mix of filetypes!\n\n\n\nquarto-website-tutorial GitHub repository with files for webpages marked with red arrows\n\n\nThe _site folder has html files with names that should be familiar: they match the . md files we were just exploring. This folder is where Quarto stores files to build the website." + }, + { + "objectID": "explore.html#quarto.yml-intro", + "href": "explore.html#quarto.yml-intro", + "title": "Explore and setup", + "section": "_quarto.yml intro", + "text": "_quarto.yml intro\nThere is also a _quarto.yml file, which is the website’s configuration file. It is essentially metadata for the website that includes the order that the pages/chapters will be in. This is where you update the organization of your website: which page comes before another. If we compare side-by-side, you’ll see that the pages that appear on our website are listed there.\n\n\n\n_quarto.yml and website side-by-side\n\n\nWe’ll learn more about how to interact with _quarto.yml in Quarto Workflows." + }, + { + "objectID": "explore.html#fork-to-your-account", + "href": "explore.html#fork-to-your-account", + "title": "Explore and setup", + "section": "Fork to your account", + "text": "Fork to your account\nLet’s start with an existing Quarto site and copy it into your space to edit. You’ll need a free GitHub account that you create at github.com (follow this advice about choosing your username).\nFirst, choose an existing website to copy. The simplest option is to start with this site: quarto-website-tutorial.\nOther options of potential interest:\n\n2021-Cloud-Hackathon\n2022-SWOT-Ocean-Cloud-Workshop\nApproach-Guide\n\nNext, follow these steps to fork and setup your repo with GitHub Actions from Gavin Fay, using the repo you chose. These instructions will take ~5 minutes.\nNow you’ve got a copy of your repo of choice in your own GitHub account, and you’re set to start making your own edits. Your GitHub repo is set up with a GitHub Action that will use Quarto to rebuild and republish your site anytime you make a commit: committing will trigger the GitHub Action to rebuild and republish the book.\nNote that the GitHub Action for this book does not include R or Python so those will need to be added if your website relies on code. See https://github.com/r-lib/actions for more details and examples.\n\nDownload instead of fork\nForking might not always be the way to go - you can’t fork into the same GitHub user account or organization so if for example you want to make a copy of 2021-Cloud-Hackathon repo within the same NASA-Openscapes GitHub Organization, you’ll need to download instead of fork. In this case, follow these steps to download and copy into a new repository, and set up the GitHub Action separately.\n\nDownload github repo files\nNavigate to https://github.com/openscapes/quarto-website-tutorial (or any other quarto site repo of choice). Click the green “Code” button and select “Download ZIP”. When it downloads on your computer, unzip the files.\n\n\nCreate a new GitHub repo\nNavigate to your GitHub account or organization, and create a new repository, naming it what you’d like. You’ll need a free GitHub account that you create at github.com (follow this advice about choosing your username). When you’re logged in, github.com will show a green button that says “New” which you’ll also see as you navigate to your username’s repository page.\n\n\nAdd original site files\nTo use the GitHub file uploader, click the button next to the green “Code” button that says “Add file”. Add file > Upload files. Then, on your computer, select all the files in unzipped folder (command-A or control-A), and drag them to the GitHub uploader page. Scroll down to write a commit message, which effectively saves your files when you’re working in the browser.\nNote: if you’re comfortable cloning the new repository and copying files into it locally before committing and pushing back to GitHub, that can be preferable to the uploader, which does have limitations with complex repos (although the uploader works fine with this tutorial repo)." + }, + { + "objectID": "explore.html#setup-github-action", + "href": "explore.html#setup-github-action", + "title": "Explore and setup", + "section": "Set up GitHub publishing", + "text": "Set up GitHub publishing\nIf you’ve used the GitHub uploader, you’ll need to set up GitHub publishing separately. We’ll do this in a few steps: we’ll set up a GitHub Action within your repo, and create a gh-pages branch.\nFirst, the GitHub Action. Go back to your main view of your GitHub repository by clicking on the name of your repository in blue at the top-left (the url in your browser window should say https://github.com/username/repo-name).\nNext to the green code button, click Add file > Create new file. Name it exactly this: .github/workflows/quarto-publish.yml . In detail: start by typing the . with github and when you type the / it will give you a new text box to type workflows (plural!), then another /, and finally, quarto-publish.yml.\nNow you’ll have an empty new file. Paste the following in this empty file - you can click on the top-right of this box to copy all the code inside this code box:\non:\n push:\n branches: main\n\nname: Render and Publish\n\njobs:\n build-deploy:\n runs-on: ubuntu-latest\n steps:\n - name: Check out repository\n uses: actions/checkout@v2 \n \n - name: Set up Quarto\n uses: quarto-dev/quarto-actions/setup@v2\n with:\n # To install LaTeX to build PDF book \n tinytex: true \n # uncomment below and fill to pin a version\n # version: 0.9.600\n \n # add software dependencies here\n\n - name: Publish to GitHub Pages (and render)\n uses: quarto-dev/quarto-actions/publish@v2\n with:\n target: gh-pages\n env:\n GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # this secret is always available for github actions\nCommit this to save your new quarto-publish.yml file. This is your GitHub Action.\nNext, we’ll create a new gh-pages branch. Go back to the main view of your GitHub repository. On the far left from the green “Code” button, click the button that says “main”. In the pull-down menu, type gh-pages - all lowercase, with a hyphen. Click the bold text that says “Create branch: gh-pages from main”.\nNow click on the Settings tab in the top right of your repository. On the left sidebar, click Pages. At the top of Pages under “Source”, select gh-pages root, and press Save. You’ll then see a green highlighted text saying that your site is published at a “github.io” url." + }, + { + "objectID": "explore.html#confirm", + "href": "explore.html#confirm", + "title": "Explore and setup", + "section": "Confirm your website is published", + "text": "Confirm your website is published\nTo confirm that your website is published, go back to your main repository page. You’ll now see an orange dot showing that the GitHub Action is beginning to publish the page.\n\n\n\nOur repo with orange dot indicating in-progress GitHub Action build\n\n\nIf you do not see this orange dot, you might need to make a small commit to trigger the GitHub Actions build. If this is the case, click the pencil on the top-right of the README.md file as circled in the image below, add some small edit (like a space after a period), and scroll down to click commit. Now you should see the orange dot.\n\n\n\n\n\nWhen your orange do becomes a green check, you can go inspect your published site at “https://username.github.io/your-repo). For example: https://openscapes.github.io/quarto-website-tutorial.\n\n\n\nOur repo with green check indicating successful GitHub Action build" + }, + { + "objectID": "explore.html#renaming-your-repo", + "href": "explore.html#renaming-your-repo", + "title": "Explore and setup", + "section": "Renaming your repo", + "text": "Renaming your repo\nIf you’d like to rename your repo, go to Settings and the option to rename is on the top of the main settings page." + }, + { + "objectID": "explore.html#onward", + "href": "explore.html#onward", + "title": "Explore and setup", + "section": "Onward!", + "text": "Onward!\nNow you are ready to start editing and publishing! The next chapter describes how starting off from the browser, using Markdown." + }, + { + "objectID": "quarto-workflows/browser.html", + "href": "quarto-workflows/browser.html", + "title": "From the Browser", + "section": "", + "text": "A workflow from the browser if good for getting started (since you do not need to install additional software) and for making small contributions, but is definitely limited. Once you feel comfortable here, you can move to a different setup.\nHere’s an example of editing content on an existing page." + }, + { + "objectID": "quarto-workflows/browser.html#edit-content-on-an-existing-page", + "href": "quarto-workflows/browser.html#edit-content-on-an-existing-page", + "title": "From the Browser", + "section": "Edit content on an existing page", + "text": "Edit content on an existing page\nLet’s change the date on the home page of this website.\nIn your repository, navigate to index.md. Then, click the pencil icon in the top left to edit directly.\n\n\n\n\n\nWe are now in the “Edit file” tab of the editor, where we can make modifications. Let’s change the date to today’s date. Click the “Preview” tab to see your changes. You can even check the “Show diff” box on the right side to see the changes you’ve made.\n\n\n\n\n\nWhile you’re here, see if there are additional changes to the text you’d like to make. Maybe changing the title or author at the top, or for the main text on the home page of the website.\nOur index.md file is written in Markdown, which enables you to make simple text formatting. As you go back and forth from “Edit file” to “Preview”, notice the patterns of how the Markdown text looks when it is as source (“Edit file”) and when it is formatted (“Preview”). For example, in Markdown, you can make text as a header with # symbols, bold or italic with * symbols, and hyperlinks with [](). Notice that spacing is important: for example, there are carriage returns (when you hit the “return” key) before any bullet points. You can learn the short list of Markdown rules here: https://quarto.org/docs/authoring/markdown-basics." + }, + { + "objectID": "quarto-workflows/browser.html#commit-and-publish", + "href": "quarto-workflows/browser.html#commit-and-publish", + "title": "From the Browser", + "section": "Commit and publish", + "text": "Commit and publish\nCommit your changes by scrolling to the bottom of the page and writing a commit message - a note to yourself and others about what happened. Write your commit message and then click the green “Commit changes” button.\n\n\n\n\n\nNow, click back to the main page of your GitHub repository. You should see the orange dot confirming your website is published. You’ll have to wait for the GitHub Action to tell quarto to build your site for you to see the update, but it will be there!" + }, + { + "objectID": "quarto-workflows/browser.html#limitations", + "href": "quarto-workflows/browser.html#limitations", + "title": "From the Browser", + "section": "Limitations", + "text": "Limitations\nWhile awesome that we can edit using GitHub directly from the browser, there are obvious limitations. One is that to see your edits show up in your book, you have to publish using the GitHub Action. This is slow. Another limitation is that we can only work on one file at a time and commit them each separately, which also is slow. Using additional software can make things much better, as we explore in subsequent chapters." + }, + { + "objectID": "quarto-workflows/jupyter.html", + "href": "quarto-workflows/jupyter.html", + "title": "From Jupyter", + "section": "", + "text": "You can interact with Quarto through JupyterLab or JupyterHub. Your Jupyter setup will involve .ipynb notebooks and the command line. Quarto’s JupyterLab tutorials has great instructions on getting started with JupyterLab, including computations and authoring.\nHere we will demonstrate how to work with this Quarto tutorial site in JupyterHub and add a Jupyter Notebook (.ipynb file). This example uses the NASA-Openscapes JupyterHub that already has all python environments as well as Quarto installed." + }, + { + "objectID": "quarto-workflows/jupyter.html#setup", + "href": "quarto-workflows/jupyter.html#setup", + "title": "From Jupyter", + "section": "Setup", + "text": "Setup\n\nJupyterHub\nOur JupyterHub is already setup with python environments as well as Quarto (through nasa-openscapes/corn), so there is no further installation required.\n\n\nClone your repo\nYou’ll start by cloning your repository into JupyterHub. Do this by opening a terminal (File > New > Terminal). In the Terminal, git clone your repository and cd into it:\ngit clone https://github.com/openscapes/quarto-website-tutorial\ncd quarto-website-tutorial\n\n\nInstall Quarto\nNot needed - Quarto is already installed on the NASA-Openscapes JupyterHub! But to install elsewhere you would do so from https://quarto.org/docs/get-started/.\nQuarto is a Command Line Interface (CLI), like git. Once download is complete, follow the installation prompts on your computer like you do for other software. You won’t see an application to click on when it is installed.\nNote for Mac users: If you do not have administrative privileges, please select “Install for me only” during the Destination Selection installation step (you will first click on “Change Install Location” at the Installation Type step).\nYou can check to confirm that Quarto is installed properly from the command line:\nquarto check install\n\n\n\n\n\n\nAdditional checks\n\n\n\n\n\nYou can also run:\n\nquarto check knitr to locate R, verify we have the rmarkdown package, and do a basic render\nquarto check jupyter to locate Python, verify we have Jupyter, and do a basic render\nquarto check to run all of these checks together\n\n\n\n\n\n\n\n\n\n\nHistorical aside: Install Quarto in a docker container\n\n\n\n\n\nIn Summer 2021 some NASA Mentors trying to install quarto locally was not an option, but they were able to install it inside a container using the following Dockerfile:\n#| fold: true\n#| summary: \"Show the Dockerfile\"\n\n##############################\n# This Dockerfile installs quarto and then runs quarto serve against the\n# internal /home/quarto/to_serve.\n#\n# BUILD\n# -----\n# To build this container, run\n#\n# docker build -t quarto_serve .\n#\n# Add the --no-cache option to force docker to build fresh and get the most\n# recent version of quarto.\n#\n#\n# RUN\n# ---\n# 1. Find the directory you want quarto to serve. Let's call this /PATH/TO/earthdata-cloud-cookbook.\n# 2. Run docker:\n#\n# docker run --rm -it -p 4848:4848 -v /PATH/TO/earthdata-cloud-cookbook:/home/quarto/to_serve quarto_serve\n#\n# 3. Open your browser and go to http://127.0.0.1:4848/\n#\n##############################\n\nFROM ubuntu:hirsute\n\n######\n# Install some command line tools we'll need\n######\nRUN apt-get update\nRUN apt-get -y install wget\nRUN apt-get -y install gdebi-core\nRUN apt-get -y install git\n\n\n######\n# Install quarto (https://quarto.org/)\n######\n\n# This is a quick and dirty way of getting the newest version number from\n# https://github.com/quarto-dev/quarto-cli/releases/latest. What's happening is\n# we're pulling the version number out of the redirect URL. This will end up\n# with QVER set to something like 0.2.11.\nRUN QVER=`wget --max-redirect 0 https://github.com/quarto-dev/quarto-cli/releases/latest 2>&1 | grep \"Location\" | sed 's/L.*tag\\/v//' | sed 's/ .*//'` \\\n && wget -O quarto.deb \"https://github.com/quarto-dev/quarto-cli/releases/download/v$QVER/quarto-$QVER-amd64.deb\"\nRUN gdebi -n quarto.deb\n\n# Run this to make sure quarto installed correctly\nRUN quarto check install\n\n\n######\n# Create a non-root user called quarto\n######\nRUN useradd -ms /bin/bash quarto\nUSER quarto\nRUN mkdir /home/quarto/to_serve\nWORKDIR /home/quarto/to_serve\n\n\n######\n# Start quarto serve\n######\n\nCMD quarto serve --no-browse --host 0.0.0.0 --port 4848" + }, + { + "objectID": "quarto-workflows/jupyter.html#quarto-preview", + "href": "quarto-workflows/jupyter.html#quarto-preview", + "title": "From Jupyter", + "section": "Quarto preview", + "text": "Quarto preview\nLet’s start off by previewing our quarto site locally. In Terminal, type quarto preview, which will provide a URL with a preview of our site!\nquarto preview\n# Preparing to preview\n# Watching files for changes\n# Browse at https://openscapes.2i2c.cloud/user/jules32/proxy/4593/\nCopy this URL into another browser window; and arrange them so you can see them both. I make a bit more space in Jupyter by collapsing the left file menu by clicking on the file icon at the top of the left sidebar.\n\n\n\n\n\n\nMake a small change and preview it\nNow we’ll be able to see live changes in the preview as we edit in our .md files. Let’s try it: Change the date in index.md by opening it from the file directory. Change to today’s date, and save. Your preview window will refresh automatically! If it does not, you can also refresh the page manually. The refreshed previewed site will now display your changes!" + }, + { + "objectID": "quarto-workflows/jupyter.html#create-a-new-.ipynb-page", + "href": "quarto-workflows/jupyter.html#create-a-new-.ipynb-page", + "title": "From Jupyter", + "section": "Create a new .ipynb page", + "text": "Create a new .ipynb page\nLet’s add a new page to our site. Instead of an .md file like the others, let’s add a .ipynb file.\nFile > New > Notebook. Accept the default kernel by clicking Select.\n\nFirst chunk: raw yaml\nBy default, this Notebook will give us a first chunk that is code. Let’s change it to raw so that we can write our yaml at the top.\n\n\n\n\n\nIn our Raw code chunk, let’s write the title of this document. We need three dashes --- on separate lines preceding and following the title:, which you can name as you’d like.\n---\ntitle: Python Example\n---\n\n\nSecond chunk: Markdown\nLet’s add a new chunk that is Markdown so we can write some description of what this page will be.\nClick the + symbol at the top of the document, and this will add a new chunk, which by default again is a Code chunk. Change it to a Markdown Chunk following the steps we did above when switching to Raw.\nHere, write a little bit of text in Markdown. Since your title is effectively a level-1 header, avoid using level-1 headers in the rest of your document. Here is some example text I wrote:\n## Introduction\n\nThis example has some Python code that will be a part of our Quarto site.\n\n\nThird chunk: Code\nNow let’s create a new chunk with the default Code setting.\nPaste the following code (or write some of your own to test):\n#| label: fig-polar\n#| fig-cap: \"A line plot on a polar axis\"\nimport numpy as np\nimport matplotlib.pyplot as plt\nr = np.arange(0, 2, 0.01)\ntheta = 2 * np.pi * r\nfig, ax = plt.subplots(\n subplot_kw = {'projection': 'polar'} \n)\nax.plot(theta, r)\nax.set_rticks([0.5, 1, 1.5, 2])\nax.grid(True)\nplt.show()\nNow, go ahead and execute this code chunk like you normally would, by clicking the cursor in a code block and clicking the sideways “play” triangle to run the selected cells (and advance to the next cell). This code produces a plot.\nNote that the code runs as it normally would; the code options in the comments are just comments.\n\n\nSave your file\nSave your document - I’ll call mine python-example.ipynb in the main repository." + }, + { + "objectID": "quarto-workflows/jupyter.html#update-_quarto.yml", + "href": "quarto-workflows/jupyter.html#update-_quarto.yml", + "title": "From Jupyter", + "section": "Update _quarto.yml", + "text": "Update _quarto.yml\nNow we’ll add python-example.ipynb to our _quarto.yml file; this is where we register of all files to include in our site. Let’s add it after the section called “Basic Workflows”.\nOpen _quarto.yml by clicking on it from the file directory.\nScroll down to review the current contents in the sidebar: section. It’s there we see all the file arrangement that we see in the previewed site.\nAdd - python-example.ipynb to line 46, making sure that your indentation aligns with the other pages.\n\n\n\n\n\nYou’ll see that our new page shows up in our Preview, and the code is executed since we did that in the Jupyter Notebook itself. By default, Quarto will not execute code chunks since your computations will likely become more complex and you will want to control when they are executed (or “run”).\nSince Quarto is still previewing our website and the python-example.ipynb, the plot also displays in the notebook after the code is run and the file is saved, as shown below.\n\n\n\n\n\nSo, your normal workflow for creating and running code blocks in your Jupyter Notebook is the same one you’ll use as Quarto displays the preview." + }, + { + "objectID": "quarto-workflows/jupyter.html#quarto-render", + "href": "quarto-workflows/jupyter.html#quarto-render", + "title": "From Jupyter", + "section": "Quarto render", + "text": "Quarto render\nSo far we have used Quarto preview view our website as we develop it. Quarto render will build the html elements of the website that we can see when we preview. Rendering will format the markdown text and code nicely as a website (or however is indicated in the _quarto.yml).\nBy default, Quarto render does not execute code in a Jupyter notebook. It will never run .ipynb files unless you tell it to.\n\nRender whole notebook\nIf you would like it to specifically execute code in a Jupyter notebook, you can do so in Terminal.\nOur Terminal is still busy previewing our website, so let’s open a new Terminal.\nFile > New > Terminal. Then type:\ncd quarto-website-tutorial\nquarto render python-example.ipynb --execute" + }, + { + "objectID": "quarto-workflows/jupyter.html#authoring-tips", + "href": "quarto-workflows/jupyter.html#authoring-tips", + "title": "From Jupyter", + "section": "Authoring tips", + "text": "Authoring tips\nQuarto.org has details about authoring, including specific instructions about authoring in Jupyter: quarto.org/docs/reference/cells/cells-jupyter." + }, + { + "objectID": "quarto-workflows/jupyter.html#commit-and-push", + "href": "quarto-workflows/jupyter.html#commit-and-push", + "title": "From Jupyter", + "section": "Commit and push!", + "text": "Commit and push!\nCommitting and pushing will make the changes you see locally live on your website (using the GitHub Action we set up earlier)." + }, + { + "objectID": "quarto-workflows/jupyter.html#troubleshooting", + "href": "quarto-workflows/jupyter.html#troubleshooting", + "title": "From Jupyter", + "section": "Troubleshooting", + "text": "Troubleshooting\n\nMy changes don’t show up in preview\nMake sure you’ve saved your file! There might be a slight delay depending on your JupyterHub/Lab setup.\n\n\nQuarto render hangs / does not complete\nCheck the specific notebook, are there any `—` throughout to denote line breaks rather than yaml? They might be causing the issue; consider deleting those.\nAlso check how long the first raw cell is. Are there level-1 headers (#)? Try removing them." + }, + { + "objectID": "quarto-workflows/index.html", + "href": "quarto-workflows/index.html", + "title": "Quarto workflows", + "section": "", + "text": "How do you work in Quarto? You can use whichever tool you’re comfortable with (RStudio, Jupyter, GitHub, VS Code, etc). Developing your quarto site will have the same basic workflow, no matter which tool you use. It is very iterative, and each is explored more below.\n\nAuthoring: write text, code, images, etc in a file. Supported files include .md, .Rmd, .qmd, .ipynb…\nUpdate _quarto.yml as needed (for example, if you’ve created a new file you’d like included in your site)\nRender individual files and/or the whole website\nRepeat, repeat, repeat\nCommit and push your website to GitHub, your updates will publish automatically!\nRepeat all of the above to make the website as you’d like!\n\nNote: if editing from your internet Browser we won’t render in Step 3 will not be separate but combined with Step 5, which will only require a commit, not a push)" + }, + { + "objectID": "quarto-workflows/index.html#authoring", + "href": "quarto-workflows/index.html#authoring", + "title": "Quarto workflows", + "section": "Authoring", + "text": "Authoring\nAs an author, you have a lot of options of how your text will be formatted, arranged, and interlinked. You will be writing in Markdown, which is a lightweight text formatting language. The Quarto documentation about authoring introduces markdown-basics that will get you started.\nEach page of our site has a similar first few lines - this YAML, like we saw in our _quarto.yml and it is indicated by two sets of 3 dashes --- :\n---\ntitle: My title\n---\nYou’re able to add more features to individual pages by including it in the YAML, which for the most part here only includes a title. See Quarto excecution options for more information of what you can include in the YAML." + }, + { + "objectID": "quarto-workflows/index.html#update-_quarto.yml", + "href": "quarto-workflows/index.html#update-_quarto.yml", + "title": "Quarto workflows", + "section": "Update _quarto.yml", + "text": "Update _quarto.yml\nLet’s have a closer look at the _quarto.yml file.\nThis type of file (.yml or .yaml) is written in YAML (“Yet Another Markup Language”). You’ll be able to shift the arrangement of webpages by reordering/adding/deleting them in the _quarto.yml file following the patterns you see in this example.\n\n\n\n_quarto.yml and website side-by-side\n\n\nNotice that there are multiple ways in the _quarto.yml for you to include a file in your website. For example, in the above image, the “First Observations” we see in the left sidebar of the published website (right image) is represented in _quarto.yml (left image) over two lines, with line 36 indicating the file reference and line 37 indicating the text to show up in the left sidebar. However, “From RStudio” is only represented in one line of _quarto.yml, on line 43. This represents two strategies for including a file in your website. By default, the title of a specified file will show up in the website’s sidebar, which is what is happening with the “From RStudio” example. If you would like more control over what is written in the sidebar vs the title of your files, then the approach we took with “First Observations” is what you’ll want to do: you’ll see that only “First Observations” shows up in the sidebar as we specified in _quarto.yml, but the page’s title says “First Observations & Setup” (which in our preference was too long for the sidebar).\n\n\n\n\n\n\nNote\n\n\n\nAs you modify _quarto.yml, the most important thing to know is that spacing matters. Pay attention to whether text is indented by one, two, four, or other spaces, and make sure you follow it; if your site is not looking as expected it is likely a silent error in your YAML. Some text editors like RStudio provide debugging support for YAML and are highly recommended to save you time and heartache." + }, + { + "objectID": "quarto-workflows/index.html#install-quarto", + "href": "quarto-workflows/index.html#install-quarto", + "title": "Quarto workflows", + "section": "Install Quarto", + "text": "Install Quarto\nhttps://quarto.org/docs/get-started/ describes how to install Quarto, which will depend on your operating system. We’ll walk through installation for each tool in the next chapters." + }, + { + "objectID": "quarto-workflows/rstudio.html", + "href": "quarto-workflows/rstudio.html", + "title": "From RStudio", + "section": "", + "text": "The RStudio software (called an IDE, integrated development environment) is an excellent way to edit files and interface with GitHub. Plus, as it is made by the same folks who make Quarto, it has many integrated features for streamlining your workflow with Quarto, including how it previews your edits and provides debugging support for yaml! Quarto's RStudio tutorials has great instructions on getting started with JupyterLab, including computations and authoring.\nHere is what you’ll need to do to set up and use RStudio with Quarto." + }, + { + "objectID": "quarto-workflows/rstudio.html#setup", + "href": "quarto-workflows/rstudio.html#setup", + "title": "From RStudio", + "section": "Setup", + "text": "Setup\n\nRStudio and GitHub\nFor a workflow with RStudio and GitHub on your local computer, you will need four things:\n\nR\nRStudio\nGit\nGitHub\n\nFollow the UCSB MEDS Installation Guide for detailed instructions on how to create accounts, download, install, and configure on Mac and Windows. This takes about 20 minutes. (For an even more detailed walk-through, see Allison Horst’s ESM 206 Google Doc).\n\n\nClone your repo\nYou’ll start by cloning your repository into RStudio.\nFile > New Project > Version Control > Git > paste your repository name.\nR for Excel Users: Clone your repository using RStudio has detailed instructions and screenshots of these steps.\n\n\nInstall Quarto\nNext, you’ll install Quarto: https://quarto.org/docs/get-started/. After downloading, follow the installation wizard on your computer. When it is complete, you won’t see an application or any new software, but it is now available to RStudio (as well as all other applications on your computer, including the command line).\n\n\nRStudio orientation\nNow let’s take a moment to get oriented. This is an RStudio project, which is indicated in the top-right. The bottom right pane shows all the files in your project; everything we’ve cloned from GitHub. We can open any RStudio project by opening its .Rproj file, or from RStudio File > Open Project ….\n\n\n\nRStudio IDE highlighting the project name and files pane\n\n\n\n\nVisual Editor\nThe RStudio Visual Editor is quite new and has features that improve your writing experience. Working in the Visual Editor feels a bit like working in a Google Doc.\nHere’s an example showing the same file in the original Source Editor with content in markdown format and in the Visual Editor with content that looks more like it will appear in a live site. You can switch freely between these modes.\n\n\n\n\n\n\nRStudio IDE highlighting the Source Editor\n\n\n\n\n\n\n\nRStudio IDE highlighting the Visual Editor\n\n\n\n\n\nAlready have some content formatted in a Google Doc? You can copy-paste it into the Visual Editor and most formatting will be retained.\nThe editing bar provides familiar point and click access to text formatting options like bulleted or numbered lists.\n\n\n\nRStudio IDE highlighting the point and click editing bar\n\n\n\nKeyboard shortcuts\nThe Visual Editor also lets you use many keyboard shortcuts that might be familiar for adding boldface (command-b), italics (command-i), or headers. On a Mac, option-command-2 will make a level 2 header. Try it with option-command-1, or option-command-0 for normal text!\n\n\nInsert an image or figure\nTo insert an image (called a figure in Quarto), click the image icon. This brings up a window in which we can select the image, set its alignment, give it a caption and alt text, hyperlink it, or edit other metadata.\n\n\n\nInsert image or figure using the Visual Editor\n\n\nOnce an image is added, clicking on that image gives us editing options. We can resize it dynamically by clicking in the image and dragging a corner or side to resize. When an image is selected, its dimensions are displayed for editing. Clicking on the gray ellipsis to the right of the dimensions opens the pop-up window to access more metadata edits.\n\n\nInsert a table\nSimilar to adding an image, to insert a table, we click the Table dropdown." + }, + { + "objectID": "quarto-workflows/rstudio.html#quarto-render", + "href": "quarto-workflows/rstudio.html#quarto-render", + "title": "From RStudio", + "section": "Quarto render", + "text": "Quarto render\nIn the Build tab in the top-right pane, click “Render Website”. This will build the .html files and preview your website. It’s equivalent to “knitting” in RMarkdown.\nNote that you can also click “Preview Website”. With “Render Website” in RStudio, Quarto is able to render and preview in one step.\nIf you’d ever like to stop the preview, in the bottom-left, click on the Jobs tab and then the red Stop button.\n\nMake a small change and render it\nClick on index.md. This will open this markdown file in a fourth pane; the editor pane. Make a small change, for example change to today’s date on Line 4. Then, save your file; there is a disc icon at the top of the file.\nThen, render this file: press “Render” which is to the right of the disc icon that saves the file. This will render only this single file, as opposed to rerendering the whole website like when we clicked “Render Website” in the top right pane. Checking Render on Save (between the disc icon and the Render button) is a great strategy for doing this in one step." + }, + { + "objectID": "quarto-workflows/rstudio.html#create-a-new-.rmd-page", + "href": "quarto-workflows/rstudio.html#create-a-new-.rmd-page", + "title": "From RStudio", + "section": "Create a new .Rmd page", + "text": "Create a new .Rmd page\nNew > RMarkdown document > OK\nThe starter RMarkdown document has some R code inside: it displays a summary of the cars dataset that is pre-loaded into R (summary(cars)) and plots the pressure data that is also pre-loaded (plot(pressure)).\nSave this document as r-example.rmd." + }, + { + "objectID": "quarto-workflows/rstudio.html#update-_quarto.yml", + "href": "quarto-workflows/rstudio.html#update-_quarto.yml", + "title": "From RStudio", + "section": "Update _quarto.yml", + "text": "Update _quarto.yml\nNow we’ll add r-example.rmd to our _quarto.yml file; this is where we register all files to include in our site. Let’s add it after the section called “Quarto Workflows”.\nOpen _quarto.yml by clicking on it from the file directory.\nScroll down to review the current contents in the sidebar: section under contents:. It’s there we see all the file arrangement that we see in the previewed site.\nAdd - r-example.rmd in its own line, making sure that your indentation aligns with the other pages.\nFrom the Build tab, clicking Preview Website will recreate your website!" + }, + { + "objectID": "quarto-workflows/rstudio.html#authoring-tips", + "href": "quarto-workflows/rstudio.html#authoring-tips", + "title": "From RStudio", + "section": "Authoring tips", + "text": "Authoring tips\nChecking “Render on Save” is really helpful when iterating quickly on a document.\nIf the document is very code-heavy, consider using freeze that will not run the code each time.\nQuarto.org has details about authoring, including specific instructions about authoring in RStudio." + }, + { + "objectID": "quarto-workflows/rstudio.html#commit-and-push", + "href": "quarto-workflows/rstudio.html#commit-and-push", + "title": "From RStudio", + "section": "Commit and push!", + "text": "Commit and push!\nCommitting and pushing will make the changes you see locally live on your website (using the GitHub Action we set up earlier)." + }, + { + "objectID": "quarto-workflows/rstudio.html#troubleshooting", + "href": "quarto-workflows/rstudio.html#troubleshooting", + "title": "From RStudio", + "section": "Troubleshooting", + "text": "Troubleshooting\nIf you have trouble rendering your website after for example changing the extenstion of a file from .md to .qmd, refreshing your RStudio often helps. Do this by clicking the project name at the upper right of the RStudio window (in this case, quarto-website-tutorial), and underneath the “close project” section, click the same name of your project: quarto-website-tutorial. 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Be={placement:"bottom",modifiers:[],strategy:"absolute"};function Re(){for(var t=arguments.length,e=new Array(t),i=0;ij.on(t,"mouseover",d))),this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Je),this._element.classList.add(Je),j.trigger(this._element,"shown.bs.dropdown",t)}hide(){if(c(this._element)||!this._isShown(this._menu))return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){j.trigger(this._element,"hide.bs.dropdown",t).defaultPrevented||("ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._popper&&this._popper.destroy(),this._menu.classList.remove(Je),this._element.classList.remove(Je),this._element.setAttribute("aria-expanded","false"),U.removeDataAttribute(this._menu,"popper"),j.trigger(this._element,"hidden.bs.dropdown",t))}_getConfig(t){if(t={...this.constructor.Default,...U.getDataAttributes(this._element),...t},a(Ue,t,this.constructor.DefaultType),"object"==typeof t.reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ue.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(t){if(void 0===Fe)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let e=this._element;"parent"===this._config.reference?e=t:o(this._config.reference)?e=r(this._config.reference):"object"==typeof this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;ie+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void 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this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof 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t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:''},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const 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e=n(this._element),i=this._element.closest(".nav, .list-group");if(i){const e="UL"===i.nodeName||"OL"===i.nodeName?Ln:kn;t=V.find(e,i),t=t[t.length-1]}const s=t?j.trigger(t,"hide.bs.tab",{relatedTarget:this._element}):null;if(j.trigger(this._element,"show.bs.tab",{relatedTarget:t}).defaultPrevented||null!==s&&s.defaultPrevented)return;this._activate(this._element,i);const o=()=>{j.trigger(t,"hidden.bs.tab",{relatedTarget:this._element}),j.trigger(this._element,"shown.bs.tab",{relatedTarget:t})};e?this._activate(e,e.parentNode,o):o()}_activate(t,e,i){const n=(!e||"UL"!==e.nodeName&&"OL"!==e.nodeName?V.children(e,kn):V.find(Ln,e))[0],s=i&&n&&n.classList.contains(On),o=()=>this._transitionComplete(t,n,i);n&&s?(n.classList.remove(Cn),this._queueCallback(o,t,!0)):o()}_transitionComplete(t,e,i){if(e){e.classList.remove(Tn);const t=V.findOne(":scope > .dropdown-menu 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Dn="toast",Sn="hide",Nn="show",In="showing",Pn={animation:"boolean",autohide:"boolean",delay:"number"},jn={animation:!0,autohide:!0,delay:5e3};class Mn extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get DefaultType(){return Pn}static get Default(){return jn}static get NAME(){return 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t&&t?t:{}},a(Dn,t,this.constructor.DefaultType),t}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){j.on(this._element,"mouseover.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"mouseout.bs.toast",(t=>this._onInteraction(t,!1))),j.on(this._element,"focusin.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"focusout.bs.toast",(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=Mn.getOrCreateInstance(this,t);if("string"==typeof 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t=e.state,n=e.name,r=t.rects.reference,o=t.rects.popper,i=t.modifiersData.preventOverflow,a=Y(t,{elementContext:"reference"}),s=Y(t,{altBoundary:!0}),f=he(a,r),c=he(s,o,i),p=me(f),u=me(c);t.modifiersData[n]={referenceClippingOffsets:f,popperEscapeOffsets:c,isReferenceHidden:p,hasPopperEscaped:u},t.attributes.popper=Object.assign({},t.attributes.popper,{"data-popper-reference-hidden":p,"data-popper-escaped":u})}},ge=K({defaultModifiers:[Z,$,ne,re]}),ye=[Z,$,ne,re,oe,pe,le,de,ve],be=K({defaultModifiers:ye});e.applyStyles=re,e.arrow=de,e.computeStyles=ne,e.createPopper=be,e.createPopperLite=ge,e.defaultModifiers=ye,e.detectOverflow=Y,e.eventListeners=Z,e.flip=pe,e.hide=ve,e.offset=oe,e.popperGenerator=K,e.popperOffsets=$,e.preventOverflow=le,Object.defineProperty(e,"__esModule",{value:!0})})); + diff --git a/_site/site_libs/quarto-html/quarto-syntax-highlighting-dark.css b/_site/site_libs/quarto-html/quarto-syntax-highlighting-dark.css new file mode 100644 index 0000000..941c9df --- /dev/null +++ b/_site/site_libs/quarto-html/quarto-syntax-highlighting-dark.css @@ -0,0 +1,187 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-al-color: #f07178; + --quarto-hl-an-color: #d4d0ab; + --quarto-hl-at-color: #00e0e0; + --quarto-hl-bn-color: #d4d0ab; + --quarto-hl-bu-color: #abe338; + --quarto-hl-ch-color: #abe338; + --quarto-hl-co-color: #f8f8f2; + --quarto-hl-cv-color: #ffd700; + --quarto-hl-cn-color: #ffd700; + --quarto-hl-cf-color: #ffa07a; + --quarto-hl-dt-color: #ffa07a; + --quarto-hl-dv-color: #d4d0ab; + --quarto-hl-do-color: #f8f8f2; + --quarto-hl-er-color: #f07178; + --quarto-hl-ex-color: #00e0e0; + --quarto-hl-fl-color: #d4d0ab; + --quarto-hl-fu-color: #ffa07a; + --quarto-hl-im-color: #abe338; + --quarto-hl-in-color: #d4d0ab; + --quarto-hl-kw-color: #ffa07a; + --quarto-hl-op-color: #ffa07a; + --quarto-hl-ot-color: #00e0e0; + --quarto-hl-pp-color: #dcc6e0; + --quarto-hl-re-color: #00e0e0; + --quarto-hl-sc-color: #abe338; + --quarto-hl-ss-color: #abe338; + --quarto-hl-st-color: #abe338; + --quarto-hl-va-color: #00e0e0; + --quarto-hl-vs-color: #abe338; + --quarto-hl-wa-color: #dcc6e0; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +code span.al { + font-weight: bold; + color: #f07178; +} + +code span.an { + color: #d4d0ab; +} + +code span.at { + color: #00e0e0; +} + +code span.bn { + color: #d4d0ab; +} + +code span.bu { + color: #abe338; +} + +code span.ch { + color: #abe338; +} + +code span.co { + font-style: italic; + color: #f8f8f2; +} + +code span.cv { + color: #ffd700; +} + +code span.cn { + color: #ffd700; +} + +code span.cf { + font-weight: bold; + color: #ffa07a; +} + +code span.dt { + color: #ffa07a; +} + +code span.dv { + color: #d4d0ab; +} + +code span.do { + color: #f8f8f2; +} + +code span.er { + color: #f07178; + text-decoration: underline; +} + +code span.ex { + font-weight: bold; + color: #00e0e0; +} + +code span.fl { + color: #d4d0ab; +} + +code span.fu { + color: #ffa07a; +} + +code span.im { + color: #abe338; +} + +code span.in { + color: #d4d0ab; +} + +code span.kw { + font-weight: bold; + color: #ffa07a; +} + +pre > code.sourceCode > span { + color: #f8f8f2; +} + +code span { + color: #f8f8f2; +} + +code.sourceCode > span { + color: #f8f8f2; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #f8f8f2; +} + +code span.op { + color: #ffa07a; +} + +code span.ot { + color: #00e0e0; +} + +code span.pp { + color: #dcc6e0; +} + +code span.re { + color: #00e0e0; +} + +code span.sc { + color: #abe338; +} + +code span.ss { + color: #abe338; +} + +code span.st { + color: #abe338; +} + +code span.va { + color: #00e0e0; +} + +code span.vs { + color: #abe338; +} + +code span.wa { + color: #dcc6e0; +} + +.prevent-inlining { + content: " code.sourceCode > span { + color: #003B4F; +} + +code span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +code span.ot { + color: #003B4F; +} + +code span.at { + color: #657422; +} + +code span.ss { + color: #20794D; +} + +code span.an { + color: #5E5E5E; +} + +code span.fu { + color: #4758AB; +} + +code span.st { + color: #20794D; +} + +code span.cf { + color: #003B4F; +} + +code span.op { + color: #5E5E5E; +} + +code span.er { + color: #AD0000; +} + +code span.bn { + color: #AD0000; +} + +code span.al { + color: #AD0000; +} + +code span.va { + color: #111111; +} + +code span.pp { + color: #AD0000; +} + +code span.in { + color: #5E5E5E; +} + +code span.vs { + color: #20794D; +} + +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +code span.do { + color: #5E5E5E; + font-style: italic; +} + +code span.im { + color: #00769E; +} + +code span.ch { + color: #20794D; +} + +code span.dt { + color: #AD0000; +} + +code span.fl { + color: #AD0000; +} + +code span.co { + color: #5E5E5E; +} + +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +code span.cn { + color: #8f5902; +} + +code span.sc { + color: #5E5E5E; +} + +code span.dv { + color: #AD0000; +} + +code span.kw { + color: #003B4F; +} + +.prevent-inlining { + content: " { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) + function fireSlideEnter(e) { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id=${anchor}]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + sectionIndex = 0; + } else { + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + const currentPagePath = offsetAbsoluteUrl(window.location.href); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + if ( + item === currentPagePath || + item === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.display = "none"; + } + + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append(titleEl.innerText, toggleIcon); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + const elRect = el.getBoundingClientRect(); + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + positionToggle(); + }, 50) + ); + positionToggle(); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + clone.style.display = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > * " + ); + let lastBottom = 0; + for (const marginChild of marginChildren) { + const top = marginChild.getBoundingClientRect().top; + if (top < lastBottom) { + const margin = lastBottom - top; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const top = + el.getBoundingClientRect().top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightSideConflictEls)); + sidebarScrollVisiblity(toRegions(leftSideConflictEls)); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility(toRegions(leftSideConflictEls)); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (depth === 1 || hasActiveChild || prevSiblingIsActiveLink(el)) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + + if (tocEl) { + walk(tocEl, 0); + updateActiveLink(); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} diff --git a/_site/site_libs/quarto-html/tippy.css b/_site/site_libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/_site/site_libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 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b/_site/site_libs/quarto-nav/quarto-nav.js new file mode 100644 index 0000000..024fb1f --- /dev/null +++ b/_site/site_libs/quarto-nav/quarto-nav.js @@ -0,0 +1,221 @@ +const headroomChanged = new CustomEvent("quarto-hrChanged", { + detail: {}, + bubbles: true, + cancelable: false, + composed: false, +}); + +window.document.addEventListener("DOMContentLoaded", function () { + let init = false; + + function throttle(func, wait) { + var timeout; + return function () { + const context = this; + const args = arguments; + const later = function () { + clearTimeout(timeout); + timeout = null; + func.apply(context, args); + }; + + if (!timeout) { + timeout = setTimeout(later, wait); + } + }; + } + + function headerOffset() { + // Set an offset if there is are fixed top navbar + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl) { + return headerEl.clientHeight; + } else { + return 0; + } + } + + function footerOffset() { + const footerEl = window.document.querySelector("footer.footer"); + if (footerEl) { + return footerEl.clientHeight; + } else { + return 0; + } + } + + function updateDocumentOffsetWithoutAnimation() { + updateDocumentOffset(false); + } + + function updateDocumentOffset(animated) { + // set body offset + const topOffset = headerOffset(); + const bodyOffset = topOffset + footerOffset(); + const bodyEl = window.document.body; + bodyEl.setAttribute("data-bs-offset", topOffset); + bodyEl.style.paddingTop = topOffset + "px"; + + // deal with sidebar offsets + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + if (!animated) { + sidebar.classList.add("notransition"); + // Remove the no transition class after the animation has time to complete + setTimeout(function () { + sidebar.classList.remove("notransition"); + }, 201); + } + + if (window.Headroom && sidebar.classList.contains("sidebar-unpinned")) { + sidebar.style.top = "0"; + sidebar.style.maxHeight = "100vh"; + } else { + sidebar.style.top = topOffset + "px"; + sidebar.style.maxHeight = "calc(100vh - " + topOffset + "px)"; + } + }); + + // allow space for footer + const mainContainer = window.document.querySelector(".quarto-container"); + if (mainContainer) { + mainContainer.style.minHeight = "calc(100vh - " + bodyOffset + "px)"; + } + + // link offset + let linkStyle = window.document.querySelector("#quarto-target-style"); + if (!linkStyle) { + linkStyle = window.document.createElement("style"); + window.document.head.appendChild(linkStyle); + } + while (linkStyle.firstChild) { + linkStyle.removeChild(linkStyle.firstChild); + } + if (topOffset > 0) { + linkStyle.appendChild( + window.document.createTextNode(` + section:target::before { + content: ""; + display: block; + height: ${topOffset}px; + margin: -${topOffset}px 0 0; + }`) + ); + } + if (init) { + window.dispatchEvent(headroomChanged); + } + init = true; + } + + // initialize headroom + var header = window.document.querySelector("#quarto-header"); + if (header && window.Headroom) { + const headroom = new window.Headroom(header, { + tolerance: 5, + onPin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.remove("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + onUnpin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.add("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + }); + headroom.init(); + + let frozen = false; + window.quartoToggleHeadroom = function () { + if (frozen) { + headroom.unfreeze(); + frozen = false; + } else { + headroom.freeze(); + frozen = true; + } + }; + } + + // Observe size changed for the header + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl && window.ResizeObserver) { + const observer = new window.ResizeObserver( + throttle(updateDocumentOffsetWithoutAnimation, 50) + ); + observer.observe(headerEl, { + attributes: true, + childList: true, + characterData: true, + }); + } else { + window.addEventListener( + "resize", + throttle(updateDocumentOffsetWithoutAnimation, 50) + ); + setTimeout(updateDocumentOffsetWithoutAnimation, 500); + } + + // fixup index.html links if we aren't on the filesystem + if (window.location.protocol !== "file:") { + const links = window.document.querySelectorAll("a"); + for (let i = 0; i < links.length; i++) { + links[i].href = links[i].href.replace(/\/index\.html/, "/"); + } + + // Fixup any sharing links that require urls + // Append url to any sharing urls + const sharingLinks = window.document.querySelectorAll( + "a.sidebar-tools-main-item" + ); + for (let i = 0; i < sharingLinks.length; i++) { + const sharingLink = sharingLinks[i]; + const href = sharingLink.getAttribute("href"); + if (href) { + sharingLink.setAttribute( + "href", + href.replace("|url|", window.location.href) + ); + } + } + + // Scroll the active navigation item into view, if necessary + const navSidebar = window.document.querySelector("nav#quarto-sidebar"); + if (navSidebar) { + // Find the active item + const activeItem = navSidebar.querySelector("li.sidebar-item a.active"); + if (activeItem) { + // Wait for the scroll height and height to resolve by observing size changes on the + // nav element that is scrollable + const resizeObserver = new ResizeObserver((_entries) => { + // The bottom of the element + const elBottom = activeItem.offsetTop; + const viewBottom = navSidebar.scrollTop + navSidebar.clientHeight; + + // The element height and scroll height are the same, then we are still loading + if (viewBottom !== navSidebar.scrollHeight) { + // Determine if the item isn't visible and scroll to it + if (elBottom >= viewBottom) { + navSidebar.scrollTop = elBottom; + } + + // stop observing now since we've completed the scroll + resizeObserver.unobserve(navSidebar); + } + }); + resizeObserver.observe(navSidebar); + } + } + } +}); diff --git a/_site/site_libs/quarto-search/autocomplete.umd.js b/_site/site_libs/quarto-search/autocomplete.umd.js new file mode 100644 index 0000000..3f2dcf0 --- /dev/null +++ b/_site/site_libs/quarto-search/autocomplete.umd.js @@ -0,0 +1,3 @@ +/*! @algolia/autocomplete-js 1.5.3 | MIT License | © Algolia, Inc. and contributors | https://github.com/algolia/autocomplete */ +!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?t(exports):"function"==typeof define&&define.amd?define(["exports"],t):t((e="undefined"!=typeof globalThis?globalThis:e||self)["@algolia/autocomplete-js"]={})}(this,(function(e){"use strict";function t(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,r)}return n}function n(e){for(var 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a/_site/site_libs/quarto-search/quarto-search.js b/_site/site_libs/quarto-search/quarto-search.js new file mode 100644 index 0000000..6fd4b5b --- /dev/null +++ b/_site/site_libs/quarto-search/quarto-search.js @@ -0,0 +1,1123 @@ +const kQueryArg = "q"; +const kResultsArg = "show-results"; + +// If items don't provide a URL, then both the navigator and the onSelect +// function aren't called (and therefore, the default implementation is used) +// +// We're using this sentinel URL to signal to those handlers that this +// item is a more item (along with the type) and can be handled appropriately +const kItemTypeMoreHref = "0767FDFD-0422-4E5A-BC8A-3BE11E5BBA05"; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Ensure that search is available on this page. If it isn't, + // should return early and not do anything + var searchEl = window.document.getElementById("quarto-search"); + if (!searchEl) return; + + const { autocomplete } = window["@algolia/autocomplete-js"]; + + let quartoSearchOptions = {}; + let language = {}; + const searchOptionEl = window.document.getElementById( + "quarto-search-options" + ); + if (searchOptionEl) { + const jsonStr = searchOptionEl.textContent; + quartoSearchOptions = JSON.parse(jsonStr); + language = quartoSearchOptions.language; + } + + // note the search mode + if (quartoSearchOptions.type === "overlay") { + searchEl.classList.add("type-overlay"); + } else { + searchEl.classList.add("type-textbox"); + } + + // Used to determine highlighting behavior for this page + // A `q` query param is expected when the user follows a search + // to this page + const currentUrl = new URL(window.location); + const query = currentUrl.searchParams.get(kQueryArg); + const showSearchResults = currentUrl.searchParams.get(kResultsArg); + const mainEl = window.document.querySelector("main"); + + // highlight matches on the page + if (query !== null && mainEl) { + // perform any highlighting + highlight(query, mainEl); + + // fix up the URL to remove the q query param + const replacementUrl = new URL(window.location); + replacementUrl.searchParams.delete(kQueryArg); + window.history.replaceState({}, "", replacementUrl); + } + + // function to clear highlighting on the page when the search query changes + // (e.g. if the user edits the query or clears it) + let highlighting = true; + const resetHighlighting = (searchTerm) => { + if (mainEl && highlighting && query !== null && searchTerm !== query) { + clearHighlight(query, mainEl); + highlighting = false; + } + }; + + // Clear search highlighting when the user scrolls sufficiently + const resetFn = () => { + resetHighlighting(""); + window.removeEventListener("quarto-hrChanged", resetFn); + window.removeEventListener("quarto-sectionChanged", resetFn); + }; + + // Register this event after the initial scrolling and settling of events + // on the page + window.addEventListener("quarto-hrChanged", resetFn); + window.addEventListener("quarto-sectionChanged", resetFn); + + // Responsively switch to overlay mode if the search is present on the navbar + // Note that switching the sidebar to overlay mode requires more coordinate (not just + // the media query since we generate different HTML for sidebar overlays than we do + // for sidebar input UI) + const detachedMediaQuery = + quartoSearchOptions.type === "overlay" + ? "all" + : quartoSearchOptions.location === "navbar" + ? "(max-width: 991px)" + : "none"; + + // If configured, include the analytics client to send insights + const plugins = configurePlugins(quartoSearchOptions); + + let lastState = null; + const { setIsOpen } = autocomplete({ + container: searchEl, + detachedMediaQuery: detachedMediaQuery, + defaultActiveItemId: 0, + panelContainer: "#quarto-search-results", + panelPlacement: quartoSearchOptions["panel-placement"], + debug: false, + plugins, + classNames: { + form: "d-flex", + }, + translations: { + clearButtonTitle: language["search-clear-button-title"], + detachedCancelButtonText: language["search-detached-cancel-button-title"], + submitButtonTitle: language["search-submit-button-title"], + }, + initialState: { + query, + }, + getItemUrl({ item }) { + return item.href; + }, + onStateChange({ state }) { + // Perhaps reset highlighting + resetHighlighting(state.query); + + // If the panel just opened, ensure the panel is positioned properly + if (state.isOpen) { + if (lastState && !lastState.isOpen) { + setTimeout(() => { + positionPanel(quartoSearchOptions["panel-placement"]); + }, 150); + } + } + + // Perhaps show the copy link + showCopyLink(state.query, quartoSearchOptions); + + lastState = state; + }, + reshape({ sources, state }) { + return sources.map((source) => { + try { + const items = source.getItems(); + + // Validate the items + validateItems(items); + + // group the items by document + const groupedItems = new Map(); + items.forEach((item) => { + const hrefParts = item.href.split("#"); + const baseHref = hrefParts[0]; + const isDocumentItem = hrefParts.length === 1; + + const items = groupedItems.get(baseHref); + if (!items) { + groupedItems.set(baseHref, [item]); + } else { + // If the href for this item matches the document + // exactly, place this item first as it is the item that represents + // the document itself + if (isDocumentItem) { + items.unshift(item); + } else { + items.push(item); + } + groupedItems.set(baseHref, items); + } + }); + + const reshapedItems = []; + let count = 1; + for (const [_key, value] of groupedItems) { + const firstItem = value[0]; + reshapedItems.push({ + ...firstItem, + type: kItemTypeDoc, + }); + + const collapseMatches = quartoSearchOptions["collapse-after"]; + const collapseCount = + typeof collapseMatches === "number" ? collapseMatches : 1; + + if (value.length > 1) { + const target = `search-more-${count}`; + const isExpanded = + state.context.expanded && + state.context.expanded.includes(target); + + const remainingCount = value.length - collapseCount; + + for (let i = 1; i < value.length; i++) { + if (collapseMatches && i === collapseCount) { + reshapedItems.push({ + target, + title: isExpanded + ? language["search-hide-matches-text"] + : remainingCount === 1 + ? `${remainingCount} ${language["search-more-match-text"]}` + : `${remainingCount} ${language["search-more-matches-text"]}`, + type: kItemTypeMore, + href: kItemTypeMoreHref, + }); + } + + if (isExpanded || !collapseMatches || i < collapseCount) { + reshapedItems.push({ + ...value[i], + type: kItemTypeItem, + target, + }); + } + } + } + count += 1; + } + + return { + ...source, + getItems() { + return reshapedItems; + }, + }; + } catch (error) { + // Some form of error occurred + return { + ...source, + getItems() { + return [ + { + title: error.name || "An Error Occurred While Searching", + text: + error.message || + "An unknown error occurred while attempting to perform the requested search.", + type: kItemTypeError, + }, + ]; + }, + }; + } + }); + }, + navigator: { + navigate({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.location.assign(itemUrl); + } + }, + navigateNewTab({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + const windowReference = window.open(itemUrl, "_blank", "noopener"); + if (windowReference) { + windowReference.focus(); + } + } + }, + navigateNewWindow({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.open(itemUrl, "_blank", "noopener"); + } + }, + }, + getSources({ state, setContext, setActiveItemId, refresh }) { + return [ + { + sourceId: "documents", + getItemUrl({ item }) { + if (item.href) { + return offsetURL(item.href); + } else { + return undefined; + } + }, + onSelect({ + item, + state, + setContext, + setIsOpen, + setActiveItemId, + refresh, + }) { + if (item.type === kItemTypeMore) { + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + + // Toggle more + setIsOpen(true); + } + }, + getItems({ query }) { + const limit = quartoSearchOptions.limit; + if (quartoSearchOptions.algolia) { + return algoliaSearch(query, limit, quartoSearchOptions.algolia); + } else { + // Fuse search options + const fuseSearchOptions = { + isCaseSensitive: false, + shouldSort: true, + minMatchCharLength: 2, + limit: limit, + }; + + return readSearchData().then(function (fuse) { + return fuseSearch(query, fuse, fuseSearchOptions); + }); + } + }, + templates: { + noResults({ createElement }) { + return createElement( + "div", + { class: "quarto-search-no-results" }, + language["search-no-results-text"] + ); + }, + header({ items, createElement }) { + // count the documents + const count = items.filter((item) => { + return item.type === kItemTypeDoc; + }).length; + + if (count > 0) { + return createElement( + "div", + { class: "search-result-header" }, + `${count} ${language["search-matching-documents-text"]}` + ); + } else { + return createElement( + "div", + { class: "search-result-header-no-results" }, + `` + ); + } + }, + footer({ _items, createElement }) { + if ( + quartoSearchOptions.algolia && + quartoSearchOptions.algolia["show-logo"] + ) { + const libDir = quartoSearchOptions.algolia["libDir"]; + const logo = createElement("img", { + src: offsetURL( + `${libDir}/quarto-search/search-by-algolia.svg` + ), + class: "algolia-search-logo", + }); + return createElement( + "a", + { href: "http://www.algolia.com/" }, + logo + ); + } + }, + + item({ item, createElement }) { + return renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh + ); + }, + }, + }, + ]; + }, + }); + + // Remove the labeleledby attribute since it is pointing + // to a non-existent label + if (quartoSearchOptions.type === "overlay") { + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + if (inputEl) { + inputEl.removeAttribute("aria-labelledby"); + } + } + + // If the main document scrolls dismiss the search results + // (otherwise, since they're floating in the document they can scroll with the document) + window.document.body.onscroll = () => { + setIsOpen(false); + }; + + if (showSearchResults) { + setIsOpen(true); + focusSearchInput(); + } +}); + +function configurePlugins(quartoSearchOptions) { + const autocompletePlugins = []; + const algoliaOptions = quartoSearchOptions.algolia; + if ( + algoliaOptions && + algoliaOptions["analytics-events"] && + algoliaOptions["search-only-api-key"] && + algoliaOptions["application-id"] + ) { + const apiKey = algoliaOptions["search-only-api-key"]; + const appId = algoliaOptions["application-id"]; + + // Aloglia insights may not be loaded because they require cookie consent + // Use deferred loading so events will start being recorded when/if consent + // is granted. + const algoliaInsightsDeferredPlugin = deferredLoadPlugin(() => { + if ( + window.aa && + window["@algolia/autocomplete-plugin-algolia-insights"] + ) { + window.aa("init", { + appId, + apiKey, + useCookie: true, + }); + + const { createAlgoliaInsightsPlugin } = + window["@algolia/autocomplete-plugin-algolia-insights"]; + // Register the insights client + const algoliaInsightsPlugin = createAlgoliaInsightsPlugin({ + insightsClient: window.aa, + onItemsChange({ insights, insightsEvents }) { + const events = insightsEvents.map((event) => { + const maxEvents = event.objectIDs.slice(0, 20); + return { + ...event, + objectIDs: maxEvents, + }; + }); + + insights.viewedObjectIDs(...events); + }, + }); + return algoliaInsightsPlugin; + } + }); + + // Add the plugin + autocompletePlugins.push(algoliaInsightsDeferredPlugin); + return autocompletePlugins; + } +} + +// For plugins that may not load immediately, create a wrapper +// plugin and forward events and plugin data once the plugin +// is initialized. This is useful for cases like cookie consent +// which may prevent the analytics insights event plugin from initializing +// immediately. +function deferredLoadPlugin(createPlugin) { + let plugin = undefined; + let subscribeObj = undefined; + const wrappedPlugin = () => { + if (!plugin && subscribeObj) { + plugin = createPlugin(); + if (plugin && plugin.subscribe) { + plugin.subscribe(subscribeObj); + } + } + return plugin; + }; + + return { + subscribe: (obj) => { + subscribeObj = obj; + }, + onStateChange: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onStateChange) { + plugin.onStateChange(obj); + } + }, + onSubmit: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onSubmit) { + plugin.onSubmit(obj); + } + }, + onReset: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onReset) { + plugin.onReset(obj); + } + }, + getSources: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.getSources) { + return plugin.getSources(obj); + } else { + return Promise.resolve([]); + } + }, + data: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.data) { + plugin.data(obj); + } + }, + }; +} + +function validateItems(items) { + // Validate the first item + if (items.length > 0) { + const item = items[0]; + const missingFields = []; + if (item.href == undefined) { + missingFields.push("href"); + } + if (!item.title == undefined) { + missingFields.push("title"); + } + if (!item.text == undefined) { + missingFields.push("text"); + } + + if (missingFields.length === 1) { + throw { + name: `Error: Search index is missing the ${missingFields[0]} field.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items include the ${missingFields[0]} field or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } else if (missingFields.length > 1) { + const missingFieldList = missingFields + .map((field) => { + return `${field}`; + }) + .join(", "); + + throw { + name: `Error: Search index is missing the following fields: ${missingFieldList}.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items includes the following fields: ${missingFieldList}, or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } + } +} + +let lastQuery = null; +function showCopyLink(query, options) { + const language = options.language; + lastQuery = query; + // Insert share icon + const inputSuffixEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix" + ); + + if (inputSuffixEl) { + let copyButtonEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix .aa-CopyButton" + ); + + if (copyButtonEl === null) { + copyButtonEl = window.document.createElement("button"); + copyButtonEl.setAttribute("class", "aa-CopyButton"); + copyButtonEl.setAttribute("type", "button"); + copyButtonEl.setAttribute("title", language["search-copy-link-title"]); + copyButtonEl.onmousedown = (e) => { + e.preventDefault(); + e.stopPropagation(); + }; + + const linkIcon = "bi-clipboard"; + const checkIcon = "bi-check2"; + + const shareIconEl = window.document.createElement("i"); + shareIconEl.setAttribute("class", `bi ${linkIcon}`); + copyButtonEl.appendChild(shareIconEl); + inputSuffixEl.prepend(copyButtonEl); + + const clipboard = new window.ClipboardJS(".aa-CopyButton", { + text: function (_trigger) { + const copyUrl = new URL(window.location); + copyUrl.searchParams.set(kQueryArg, lastQuery); + copyUrl.searchParams.set(kResultsArg, "1"); + return copyUrl.toString(); + }, + }); + clipboard.on("success", function (e) { + // Focus the input + + // button target + const button = e.trigger; + const icon = button.querySelector("i.bi"); + + // flash "checked" + icon.classList.add(checkIcon); + icon.classList.remove(linkIcon); + setTimeout(function () { + icon.classList.remove(checkIcon); + icon.classList.add(linkIcon); + }, 1000); + }); + } + + // If there is a query, show the link icon + if (copyButtonEl) { + if (lastQuery && options["copy-button"]) { + copyButtonEl.style.display = "flex"; + } else { + copyButtonEl.style.display = "none"; + } + } + } +} + +/* Search Index Handling */ +// create the index +var fuseIndex = undefined; +async function readSearchData() { + // Initialize the search index on demand + if (fuseIndex === undefined) { + // create fuse index + const options = { + keys: [ + { name: "title", weight: 20 }, + { name: "section", weight: 20 }, + { name: "text", weight: 10 }, + ], + ignoreLocation: true, + threshold: 0.1, + }; + const fuse = new window.Fuse([], options); + + // fetch the main search.json + const response = await fetch(offsetURL("search.json")); + if (response.status == 200) { + return response.json().then(function (searchDocs) { + searchDocs.forEach(function (searchDoc) { + fuse.add(searchDoc); + }); + fuseIndex = fuse; + return fuseIndex; + }); + } else { + return Promise.reject( + new Error( + "Unexpected status from search index request: " + response.status + ) + ); + } + } + return fuseIndex; +} + +function inputElement() { + return window.document.body.querySelector(".aa-Form .aa-Input"); +} + +function focusSearchInput() { + setTimeout(() => { + const inputEl = inputElement(); + if (inputEl) { + inputEl.focus(); + } + }, 50); +} + +/* Panels */ +const kItemTypeDoc = "document"; +const kItemTypeMore = "document-more"; +const kItemTypeItem = "document-item"; +const kItemTypeError = "error"; + +function renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh +) { + switch (item.type) { + case kItemTypeDoc: + return createDocumentCard( + createElement, + "file-richtext", + item.title, + item.section, + item.text, + item.href + ); + case kItemTypeMore: + return createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh + ); + case kItemTypeItem: + return createSectionCard( + createElement, + item.section, + item.text, + item.href + ); + case kItemTypeError: + return createErrorCard(createElement, item.title, item.text); + default: + return undefined; + } +} + +function createDocumentCard(createElement, icon, title, section, text, href) { + const iconEl = createElement("i", { + class: `bi bi-${icon} search-result-icon`, + }); + const titleEl = createElement("p", { class: "search-result-title" }, title); + const titleContainerEl = createElement( + "div", + { class: "search-result-title-container" }, + [iconEl, titleEl] + ); + + const textEls = []; + if (section) { + const sectionEl = createElement( + "p", + { class: "search-result-section" }, + section + ); + textEls.push(sectionEl); + } + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + textEls.push(descEl); + + const textContainerEl = createElement( + "div", + { class: "search-result-text-container" }, + textEls + ); + + const containerEl = createElement( + "div", + { + class: "search-result-container", + }, + [titleContainerEl, textContainerEl] + ); + + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + containerEl + ); + + const classes = ["search-result-doc", "search-item"]; + if (!section) { + classes.push("document-selectable"); + } + + return createElement( + "div", + { + class: classes.join(" "), + }, + linkEl + ); +} + +function createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh +) { + const moreCardEl = createElement( + "div", + { + class: "search-result-more search-item", + onClick: (e) => { + // Handle expanding the sections by adding the expanded + // section to the list of expanded sections + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + e.stopPropagation(); + }, + }, + item.title + ); + + return moreCardEl; +} + +function toggleExpanded(item, state, setContext, setActiveItemId, refresh) { + const expanded = state.context.expanded || []; + if (expanded.includes(item.target)) { + setContext({ + expanded: expanded.filter((target) => target !== item.target), + }); + } else { + setContext({ expanded: [...expanded, item.target] }); + } + + refresh(); + setActiveItemId(item.__autocomplete_id); +} + +function createSectionCard(createElement, section, text, href) { + const sectionEl = createSection(createElement, section, text, href); + return createElement( + "div", + { + class: "search-result-doc-section search-item", + }, + sectionEl + ); +} + +function createSection(createElement, title, text, href) { + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { class: "search-result-section" }, title); + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + [titleEl, descEl] + ); + return linkEl; +} + +function createErrorCard(createElement, title, text) { + const descEl = createElement("p", { + class: "search-error-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { + class: "search-error-title", + dangerouslySetInnerHTML: { + __html: ` ${title}`, + }, + }); + const errorEl = createElement("div", { class: "search-error" }, [ + titleEl, + descEl, + ]); + return errorEl; +} + +function positionPanel(pos) { + const panelEl = window.document.querySelector( + "#quarto-search-results .aa-Panel" + ); + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + + if (panelEl && inputEl) { + panelEl.style.top = `${Math.round(panelEl.offsetTop)}px`; + if (pos === "start") { + panelEl.style.left = `${Math.round(inputEl.left)}px`; + } else { + panelEl.style.right = `${Math.round(inputEl.offsetRight)}px`; + } + } +} + +/* Highlighting */ +// highlighting functions +function highlightMatch(query, text) { + if (text) { + const start = text.toLowerCase().indexOf(query.toLowerCase()); + if (start !== -1) { + const startMark = ""; + const endMark = ""; + + const end = start + query.length; + text = + text.slice(0, start) + + startMark + + text.slice(start, end) + + endMark + + text.slice(end); + const startInfo = clipStart(text, start); + const endInfo = clipEnd( + text, + startInfo.position + startMark.length + endMark.length + ); + text = + startInfo.prefix + + text.slice(startInfo.position, endInfo.position) + + endInfo.suffix; + + return text; + } else { + return text; + } + } else { + return text; + } +} + +function clipStart(text, pos) { + const clipStart = pos - 50; + if (clipStart < 0) { + // This will just return the start of the string + return { + position: 0, + prefix: "", + }; + } else { + // We're clipping before the start of the string, walk backwards to the first space. + const spacePos = findSpace(text, pos, -1); + return { + position: spacePos.position, + prefix: "", + }; + } +} + +function clipEnd(text, pos) { + const clipEnd = pos + 200; + if (clipEnd > text.length) { + return { + position: text.length, + suffix: "", + }; + } else { + const spacePos = findSpace(text, clipEnd, 1); + return { + position: spacePos.position, + suffix: spacePos.clipped ? "…" : "", + }; + } +} + +function findSpace(text, start, step) { + let stepPos = start; + while (stepPos > -1 && stepPos < text.length) { + const char = text[stepPos]; + if (char === " " || char === "," || char === ":") { + return { + position: step === 1 ? stepPos : stepPos - step, + clipped: stepPos > 1 && stepPos < text.length, + }; + } + stepPos = stepPos + step; + } + + return { + position: stepPos - step, + clipped: false, + }; +} + +// removes highlighting as implemented by the mark tag +function clearHighlight(searchterm, el) { + const childNodes = el.childNodes; + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + if (node.nodeType === Node.ELEMENT_NODE) { + if ( + node.tagName === "MARK" && + node.innerText.toLowerCase() === searchterm.toLowerCase() + ) { + el.replaceChild(document.createTextNode(node.innerText), node); + } else { + clearHighlight(searchterm, node); + } + } + } +} + +// highlight matches +function highlight(term, el) { + const termRegex = new RegExp(term, "ig"); + const childNodes = el.childNodes; + + // walk back to front avoid mutating elements in front of us + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + + if (node.nodeType === Node.TEXT_NODE) { + // Search text nodes for text to highlight + const text = node.nodeValue; + + let startIndex = 0; + let matchIndex = text.search(termRegex); + if (matchIndex > -1) { + const markFragment = document.createDocumentFragment(); + while (matchIndex > -1) { + const prefix = text.slice(startIndex, matchIndex); + markFragment.appendChild(document.createTextNode(prefix)); + + const mark = document.createElement("mark"); + mark.appendChild( + document.createTextNode( + text.slice(matchIndex, matchIndex + term.length) + ) + ); + markFragment.appendChild(mark); + + startIndex = matchIndex + term.length; + matchIndex = text.slice(startIndex).search(new RegExp(term, "ig")); + if (matchIndex > -1) { + matchIndex = startIndex + matchIndex; + } + } + if (startIndex < text.length) { + markFragment.appendChild( + document.createTextNode(text.slice(startIndex, text.length)) + ); + } + + el.replaceChild(markFragment, node); + } + } else if (node.nodeType === Node.ELEMENT_NODE) { + // recurse through elements + highlight(term, node); + } + } +} + +/* Link Handling */ +// get the offset from this page for a given site root relative url +function offsetURL(url) { + var offset = getMeta("quarto:offset"); + return offset ? offset + url : url; +} + +// read a meta tag value +function getMeta(metaName) { + var metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; +} + +function algoliaSearch(query, limit, algoliaOptions) { + const { getAlgoliaResults } = window["@algolia/autocomplete-preset-algolia"]; + + const applicationId = algoliaOptions["application-id"]; + const searchOnlyApiKey = algoliaOptions["search-only-api-key"]; + const indexName = algoliaOptions["index-name"]; + const indexFields = algoliaOptions["index-fields"]; + const searchClient = window.algoliasearch(applicationId, searchOnlyApiKey); + const searchParams = algoliaOptions["params"]; + const searchAnalytics = !!algoliaOptions["analytics-events"]; + + return getAlgoliaResults({ + searchClient, + queries: [ + { + indexName: indexName, + query, + params: { + hitsPerPage: limit, + clickAnalytics: searchAnalytics, + ...searchParams, + }, + }, + ], + transformResponse: (response) => { + if (!indexFields) { + return response.hits.map((hit) => { + return hit.map((item) => { + return { + ...item, + text: highlightMatch(query, item.text), + }; + }); + }); + } else { + const remappedHits = response.hits.map((hit) => { + return hit.map((item) => { + const newItem = { ...item }; + ["href", "section", "title", "text"].forEach((keyName) => { + const mappedName = indexFields[keyName]; + if ( + mappedName && + item[mappedName] !== undefined && + mappedName !== keyName + ) { + newItem[keyName] = item[mappedName]; + delete newItem[mappedName]; + } + }); + newItem.text = highlightMatch(query, newItem.text); + return newItem; + }); + }); + return remappedHits; + } + }, + }); +} + +function fuseSearch(query, fuse, fuseOptions) { + return fuse.search(query, fuseOptions).map((result) => { + const addParam = (url, name, value) => { + const anchorParts = url.split("#"); + const baseUrl = anchorParts[0]; + const sep = baseUrl.search("\\?") > 0 ? "&" : "?"; + anchorParts[0] = baseUrl + sep + name + "=" + value; + return anchorParts.join("#"); + }; + + return { + title: result.item.title, + section: result.item.section, + href: addParam(result.item.href, kQueryArg, query), + text: highlightMatch(query, result.item.text), + }; + }); +} diff --git a/_site/sitemap.xml b/_site/sitemap.xml new file mode 100644 index 0000000..88b9443 --- /dev/null +++ b/_site/sitemap.xml @@ -0,0 +1,35 @@ + + + + https://openscapes.github.io/quarto-website-tutorial/transition-from-rmarkdown.html + 2022-07-08T00:04:57.906Z + + + https://openscapes.github.io/quarto-website-tutorial/index.html + 2022-07-08T00:04:58.299Z + + + https://openscapes.github.io/quarto-website-tutorial/learning-more.html + 2022-07-08T00:04:58.634Z + + + https://openscapes.github.io/quarto-website-tutorial/explore.html + 2022-07-08T00:04:59.049Z + + + https://openscapes.github.io/quarto-website-tutorial/quarto-workflows/browser.html + 2022-07-08T00:04:59.372Z + + + https://openscapes.github.io/quarto-website-tutorial/quarto-workflows/jupyter.html + 2022-07-08T00:04:59.806Z + + + https://openscapes.github.io/quarto-website-tutorial/quarto-workflows/index.html + 2022-07-08T00:05:00.127Z + + + https://openscapes.github.io/quarto-website-tutorial/quarto-workflows/rstudio.html + 2022-07-08T00:05:00.487Z + + diff --git a/_site/transition-from-rmarkdown.html b/_site/transition-from-rmarkdown.html new file mode 100644 index 0000000..d615d71 --- /dev/null +++ b/_site/transition-from-rmarkdown.html @@ -0,0 +1,495 @@ + + + + + + + + + +Making sharable documents with Quarto - Transition from RMarkdown + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + + +
+ +
+
+

Transition from RMarkdown

+
+ + + +
+ + + +
+ + +
+ +

You may already have workflows in RMarkdown and are interested in transitioning to Quarto.

+

There’s no hurry to migrate to Quarto. Keep using Rmarkdown and when you’re ready the migration will be fine.

+

Here are some notes as we migrate RMarkdown sites.

+

TODO: translating R code chunks

+
+

Bookdown to quarto

+

create _quarto.yml

+

Project options > build tools > project build tools > none

+

Reload project

+

Don’t need to delete anything immediately, but look at output.yml, purge afterbody.

+

Bookdown might be most challenging because of citations and cross-refs but still not that hard

+
+

GitHub actions

+

R

+
+
+
+

Distill to quarto

+

We transitioned our events site from distill to quarto in May 2022 (github view before and after). We followed excellent notes and examples from Nick Tierney and Danielle Navarro.

+

After we had changed all the files, the Build tab in the RStudio IDE still showed “Build website” rather then “Render Website” and “Preview Website”, and would error when we pushed them (because that button was expecting a distill site, not a quarto site). To fix this, we updated the .Rproj file. Clicking on the .Rproj file in the RStudio IDE will open a dialog box where you can click things you want (you can also open these in a text editor or from the GitHub website to see the actual text). To fix this situation with the Build tab: Project Options > Build Tools > Project Build Tools > None.

+

Looking at files /posts/_metadata.yml and _quarto.yml helps see where things are defined. For example, to make event post citations appear, we added citation: true to /posts/_metadata.yml and in _quarto.yml under the website key we set site-url: https://openscapes.github.io/events. We deleted footer.html used with distill because footer is now defined in quarto.yml.

+
+

Publishing notes

+
+

Background: Our distill site had been set up to output to a docs folder, and had GitHub Settings > Pages set to look there rather gh-pages branch. (Julie note: this was a new-to-me capability when we set up the events distill site in Spring 2021 so I had forgotten that was an option). We’ve inititally kept this same set-up for now with our events page in _quarto.yml: output-dir: docs. However, this is sub-optimal; better to not have to commit and push these files but to instead have a GitHub Action generate them upon a commit. So the following is what we did -

+
+

Don’t specify output-dir in _quarto.yml. The output directory default is _site/, which is what we’d like.

+

If you currently have a docs/ folder (like we did as we were experimenting), delete it.

+

Update .gitignore to ignore _site/. At the same time, we have it ignore caches and a .quarto file:

+
/.quarto/
+*_cache/
+_site/
+

Push these changes, merge into main.

+

On GitHub.com, in your repo, set up GitHub publishing

+

Follow instructions from the explore and setup chapter.

+
+
+
+

Troubleshooting

+
+

GitHub Action fails, says you need RMarkdown but you don’t have R code!

+

And you changed all .Rmds to .qmds!

+

You likely have a few setup code chunks from RMarkdown, that look like this:

+

{r setup, include=FALSE}

+

knitr::opts_chunk$set(echo = FALSE)

+

You can find them by opening each of your files and having a look, or use GitHub’s search for the keyword knitr

+ + +
+
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+ + +
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b/images/quarto-yml-site-side-by-side2.png new file mode 100644 index 0000000..37d64f5 Binary files /dev/null and b/images/quarto-yml-site-side-by-side2.png differ diff --git a/images/rstudio-insert-citation-doi.png b/images/rstudio-insert-citation-doi.png new file mode 100644 index 0000000..bbc5a75 Binary files /dev/null and b/images/rstudio-insert-citation-doi.png differ diff --git a/images/rstudio-insert-citation.png b/images/rstudio-insert-citation.png new file mode 100644 index 0000000..c3ed1d2 Binary files /dev/null and b/images/rstudio-insert-citation.png differ diff --git a/include-files.lua b/include-files.lua new file mode 100644 index 0000000..b933836 --- /dev/null +++ b/include-files.lua @@ -0,0 +1,115 @@ +--- include-files.lua – filter to include Markdown files +--- +--- Copyright: © 2019–2021 Albert Krewinkel +--- License: MIT – see LICENSE file for details + +-- Module pandoc.path is required and was added in version 2.12 +PANDOC_VERSION:must_be_at_least '2.12' + +local List = require 'pandoc.List' +local path = require 'pandoc.path' +local system = require 'pandoc.system' + +--- Get include auto mode +local include_auto = false +function get_vars (meta) + if meta['include-auto'] then + include_auto = true + end +end + +--- Keep last heading level found +local last_heading_level = 0 +function update_last_level(header) + last_heading_level = header.level +end + +--- Update contents of included file +local function update_contents(blocks, shift_by, include_path) + local update_contents_filter = { + -- Shift headings in block list by given number + Header = function (header) + if shift_by then + header.level = header.level + shift_by + end + return header + end, + -- If image paths are relative then prepend include file path + Image = function (image) + if path.is_relative(image.src) then + image.src = path.normalize(path.join({include_path, image.src})) + end + return image + end, + -- Update path for include-code-files.lua filter style CodeBlocks + CodeBlock = function (cb) + if cb.attributes.include and path.is_relative(cb.attributes.include) then + cb.attributes.include = + path.normalize(path.join({include_path, cb.attributes.include})) + end + return cb + end + } + + return pandoc.walk_block(pandoc.Div(blocks), update_contents_filter).content +end + +--- Filter function for code blocks +local transclude +function transclude (cb) + -- ignore code blocks which are not of class "include". + if not cb.classes:includes 'include' then + return + end + + -- Markdown is used if this is nil. + local format = cb.attributes['format'] + + -- Attributes shift headings + local shift_heading_level_by = 0 + local shift_input = cb.attributes['shift-heading-level-by'] + if shift_input then + shift_heading_level_by = tonumber(shift_input) + else + if include_auto then + -- Auto shift headings + shift_heading_level_by = last_heading_level + end + end + + --- keep track of level before recusion + local buffer_last_heading_level = last_heading_level + + local blocks = List:new() + for line in cb.text:gmatch('[^\n]+') do + if line:sub(1,2) ~= '//' then + local fh = io.open(line) + if not fh then + io.stderr:write("Cannot open file " .. line .. " | Skipping includes\n") + else + local contents = pandoc.read(fh:read '*a', format).blocks + last_heading_level = 0 + -- recursive transclusion + contents = system.with_working_directory( + path.directory(line), + function () + return pandoc.walk_block( + pandoc.Div(contents), + { Header = update_last_level, CodeBlock = transclude } + ) + end).content + --- reset to level before recursion + last_heading_level = buffer_last_heading_level + blocks:extend(update_contents(contents, shift_heading_level_by, + path.directory(line))) + fh:close() + end + end + end + return blocks +end + +return { + { Meta = get_vars }, + { Header = update_last_level, CodeBlock = transclude } +} diff --git a/index.qmd b/index.qmd new file mode 100644 index 0000000..c75ef74 --- /dev/null +++ b/index.qmd @@ -0,0 +1,78 @@ +--- +title: "Quick read for Data Sciences" +--- + +>Bao gồm các chủ đề quan trọng để phát triển kỹ năng và kiến thức trong lĩnh vực khoa học dữ liệu và phân tích dữ liệu. + +## 01-Introduction +- Giới thiệu về khoa học dữ liệu và vai trò của nó trong thế giới hiện đại. +- Lý do tại sao khoa học dữ liệu là một lĩnh vực quan trọng. +- Các nguyên tắc cơ bản và các khái niệm quan trọng trong khoa học dữ liệu. +- Ngôn ngữ python +- Ngôn ngữ R + +## 02-Data Manipulation +- Hướng dẫn cách trích xuất dữ liệu từ các nguồn khác nhau. +- Xử lý, biến đổi và làm sạch dữ liệu. +- Sử dụng các thư viện như Pandas trong Python để thao tác dữ liệu. + +## 03-Data Visualization +- Phân tích và trực quan hóa dữ liệu bằng các biểu đồ và biểu đồ khác nhau. +- Sử dụng các công cụ như Matplotlib và Seaborn để tạo đồ thị. +- Làm thế nào để trình bày thông tin dữ liệu một cách rõ ràng và hấp dẫn. + +## 04-Basic Statistics +- Các khái niệm cơ bản về thống kê, như trung bình, phương sai và độ lệch chuẩn. +- Phân tích phân phối dữ liệu. +- Ứng dụng các phương pháp thống kê trong khoa học dữ liệu. + +## 05-Regression +- Hướng dẫn về mô hình hồi quy và các loại hồi quy khác nhau. +- Sử dụng mô hình hồi quy để dự đoán giá trị. +- Đánh giá hiệu suất của mô hình hồi quy. + +## 06-Timeseries +- Làm thế nào để xử lý dữ liệu chuỗi thời gian. +- Mô hình hóa và dự đoán xu hướng và mùa vụ trong dữ liệu chuỗi thời gian. +- Sử dụng các thư viện như Time Series Analysis trong Python. + +## 07-Panel Data Models +- Giới thiệu về mô hình dữ liệu bảng và ứng dụng của chúng trong khoa học dữ liệu. +- Làm thế nào để xử lý dữ liệu bảng có cấu trúc phức tạp. +- Sử dụng mô hình dữ liệu bảng cho các vấn đề phức tạp. + +## 08-Machine Learning +- Tổng quan về học máy và các thuật toán học máy phổ biến. +- Tiếp cận và giải quyết các vấn đề thực tế bằng học máy. +- Đánh giá hiệu suất của các mô hình học máy. + +## 09-Model Deployment +- Cách triển khai các mô hình học máy vào sản phẩm hoặc ứng dụng thực tế. +- Giới thiệu về các nền tảng triển khai mô hình như AWS, Azure, và Google Cloud. +- Quản lý và duy trì mô hình đã triển khai. + +## 10-Publication +- Cách viết bài báo khoa học và báo cáo dự án trong lĩnh vực khoa học dữ liệu. +- Làm thế nào để trình bày kết quả của dự án khoa học dữ liệu một cách chuyên nghiệp. + +## 11-Git +- Hướng dẫn về Git và quản lý phiên bản dự án. +- Làm thế nào để làm việc với kho lưu trữ Git và GitHub. +- Quy trình làm việc cộng tác trong nhóm sử dụng Git. + +## 12-Docker +- Giới thiệu về Docker và containerization. +- Tạo và quản lý các container Docker cho các ứng dụng khoa học dữ liệu. +- Triển khai ứng dụng trong các môi trường container Docker. + +## 13-Database +- Cơ sở dữ liệu và các loại cơ sở dữ liệu khác nhau (SQL, NoSQL, ...) +- Làm thế nào để truy xuất dữ liệu từ cơ sở dữ liệu. +- Sử dụng SQL và các thao tác cơ sở dữ liệu trong khoa học dữ liệu. + +## 14-Web Scraping +- Cách trích xuất dữ liệu từ các trang web bằng web scraping. +- Sử dụng các thư viện như BeautifulSoup và Scrapy trong Python. +- Xử lý dữ liệu trích xuất từ web để sử dụng trong khoa học dữ liệu. + +## 15-Crypto