ENH: Update Build Software (jb==1.04) and anaconda=2025.05

.github/workflows/cache.yml

@@ -14,7 +14,7 @@ jobs:
           auto-update-conda: true
           auto-activate-base: true
           miniconda-version: 'latest'
-          python-version: "3.12"
+          python-version: "3.13"
           environment-file: environment.yml
           activate-environment: quantecon
       - name: Build HTML

.github/workflows/ci.yml

@@ -11,7 +11,7 @@ jobs:
           auto-update-conda: true
           auto-activate-base: true
           miniconda-version: 'latest'
-          python-version: "3.12"
+          python-version: "3.13"
           environment-file: environment.yml
           activate-environment: quantecon
       - name: Install latex dependencies
@@ -33,13 +33,13 @@ jobs:
       - name: Display Pip Versions
         shell: bash -l {0}
         run: pip list
-      - name: Download "build" folder (cache)
-        uses: dawidd6/action-download-artifact@v11
-        with:
-          workflow: cache.yml
-          branch: main
-          name: build-cache
-          path: _build
+      # - name: Download "build" folder (cache)
+      #   uses: dawidd6/action-download-artifact@v11
+      #   with:
+      #     workflow: cache.yml
+      #     branch: main
+      #     name: build-cache
+      #     path: _build
       # Build Assets (Download Notebooks and PDF via LaTeX)
       - name: Build Download Notebooks (sphinx-tojupyter)
         shell: bash -l {0}

.github/workflows/execution-linux.yml

@@ -11,7 +11,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["ubuntu-latest"]
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.github/workflows/execution-osx.yml

@@ -11,7 +11,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["macos-latest"]
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.github/workflows/execution-win.yml

@@ -11,7 +11,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["windows-latest"]
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.github/workflows/publish.yml

@@ -16,7 +16,7 @@ jobs:
           auto-update-conda: true
           auto-activate-base: true
           miniconda-version: 'latest'
-          python-version: "3.12"
+          python-version: "3.13"
           environment-file: environment.yml
           activate-environment: quantecon
       - name: Install latex dependencies

environment.yml

@@ -2,17 +2,16 @@ name: quantecon
 channels:
   - default
 dependencies:
-  - python=3.12
-  - anaconda=2024.10
+  - python=3.13
+  - anaconda=2025.06
   - pip
   - pip:
-    - jupyter-book==1.0.3
-    - quantecon-book-theme==0.8.2
-    - sphinx-tojupyter==0.3.0
+    - jupyter-book==1.0.4post1
+    - quantecon-book-theme==0.8.3
+    - sphinx-tojupyter==0.3.1
     - sphinxext-rediraffe==0.2.7
     - sphinx-exercise==1.0.1
-    - ghp-import==2.1.0
-    - sphinxcontrib-youtube==1.3.0  #Version 1.3.0 is required as quantecon-book-theme is only compatible with sphinx<=5
+    - sphinxcontrib-youtube==1.4.1
     - sphinx-togglebutton==0.3.2
 
 

lectures/matplotlib.md

@@ -462,8 +462,9 @@ Place all the curves in the same figure.
 
 The output should look like this
 
-```{figure} /_static/lecture_specific/matplotlib/matplotlib_ex1.png
+```{image} /_static/lecture_specific/matplotlib/matplotlib_ex1.png
 :scale: 130
+:align: center
 ```
 
 ```{exercise-end}

lectures/numba.md

@@ -563,7 +563,8 @@ Suppose that the volatility of returns on an asset can be in one of two regimes
 
 The transition probabilities across states are as follows
 
-```{figure} /_static/lecture_specific/sci_libs/nfs_ex1.png
+```{image} /_static/lecture_specific/sci_libs/nfs_ex1.png
+:align: center
 ```
 
 For example, let the period length be one day, and suppose the current state is high.

lectures/pandas.md

@@ -682,8 +682,9 @@ ticker = read_data(ticker_list)
 
 Complete the program to plot the result as a bar graph like this one:
 
-```{figure} /_static/lecture_specific/pandas/pandas_share_prices.png
+```{image} /_static/lecture_specific/pandas/pandas_share_prices.png
 :scale: 80
+:align: center
 ```
 
 ```{exercise-end}
@@ -748,8 +749,9 @@ indices_list = {'^GSPC': 'S&P 500',
 
 Complete the program to show summary statistics and plot the result as a time series graph like this one:
 
-```{figure} /_static/lecture_specific/pandas/pandas_indices_pctchange.png
+```{image} /_static/lecture_specific/pandas/pandas_indices_pctchange.png
 :scale: 80
+:align: center
 ```
 
 ```{exercise-end}