docs: executed markdown pages for HowToGalaxy Chapter 1 (+ setup_notebook fix)

README.md

@@ -2,6 +2,7 @@
 
 [Installation Guide](https://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html) |
 [PyAutoGalaxy readthedocs](https://pyautogalaxy.readthedocs.io/en/latest/index.html) |
+[Browse Chapter 1 With Images](markdown/README.md) |
 [autogalaxy_workspace](https://github.com/PyAutoLabs/autogalaxy_workspace)
 
 <img src="https://github.com/Jammy2211/PyAutoLogo/blob/main/gifs/pyautogalaxy.gif?raw=true" width="900" />

config/build/markdown_examples.yaml

@@ -0,0 +1,15 @@
+# Curated examples rendered to executed markdown pages (markdown/) with real
+# output images, for GitHub browsing. Built by PyAutoBuild's generate_markdown.py.
+# Batch 2b: chapter_1_introduction (no non-linear searches — fast).
+- script: scripts/chapter_1_introduction/tutorial_0_visualization.py
+  max_minutes: 30
+- script: scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py
+  max_minutes: 30
+- script: scripts/chapter_1_introduction/tutorial_2_data.py
+  max_minutes: 30
+- script: scripts/chapter_1_introduction/tutorial_3_fitting.py
+  max_minutes: 30
+- script: scripts/chapter_1_introduction/tutorial_4_methods.py
+  max_minutes: 30
+- script: scripts/chapter_1_introduction/tutorial_5_summary.py
+  max_minutes: 30

markdown/README.md

@@ -0,0 +1,12 @@
+# HowToGalaxy examples, executed — browse with output images
+
+Every page below is the corresponding example script **fully executed**, rendered to markdown with its real output images, so you can read the examples on GitHub exactly as they run. Each page links back to the `.py` script and Jupyter notebook it was generated from.
+
+- [Tutorial 0: Visualization](chapter_1_introduction/tutorial_0_visualization.md) — from `scripts/chapter_1_introduction/tutorial_0_visualization.py`
+- [HowToGalaxy: Introduction](chapter_1_introduction/tutorial_1_grids_and_galaxies.md) — from `scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py`
+- [Tutorial 2: Data](chapter_1_introduction/tutorial_2_data.md) — from `scripts/chapter_1_introduction/tutorial_2_data.py`
+- [Tutorial 3: Fitting](chapter_1_introduction/tutorial_3_fitting.md) — from `scripts/chapter_1_introduction/tutorial_3_fitting.py`
+- [tutorial_4_methods](chapter_1_introduction/tutorial_4_methods.md) — from `scripts/chapter_1_introduction/tutorial_4_methods.py`
+- [Tutorial 9: Summary](chapter_1_introduction/tutorial_5_summary.md) — from `scripts/chapter_1_introduction/tutorial_5_summary.py`
+
+These pages are regenerated manually by PyAutoBuild's `generate_markdown.py` when a curated script changes.

markdown/chapter_1_introduction/tutorial_0_visualization.md

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+> ✏️ **This page is auto-generated from [`scripts/chapter_1_introduction/tutorial_0_visualization.py`](../../scripts/chapter_1_introduction/tutorial_0_visualization.py) — do not edit it directly.**
+> It shows the example fully executed, with its real output images.
+> Run it yourself via the [Python script](../../scripts/chapter_1_introduction/tutorial_0_visualization.py) or the [Jupyter notebook](../../notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb).
+
+Tutorial 0: Visualization
+=========================
+
+In this tutorial, we quickly cover visualization in **PyAutoGalaxy** and make sure images display clearly in your
+Jupyter notebook and on your computer screen.
+
+__Contents__
+
+- **Directories:** Set the working directory so PyAutoGalaxy can find configs, data and output folders.
+- **Dataset:** Load an example imaging dataset of a galaxy.
+- **Plot Customization:** Customize matplotlib options like title, figure size and colormap.
+- **Subplots:** Plot all components of a dataset simultaneously using subplots.
+- **Visuals:** Add visual overlays like masks and grids to figures.
+- **Wrap Up:** Summary of visualization in PyAutoGalaxy.
+
+
+```python
+
+from autoconf import setup_notebook; setup_notebook()
+```
+
+    2026-07-11 16:20:09,770 - matplotlib.font_manager - INFO - Failed to extract font properties from /usr/share/fonts/truetype/noto/NotoColorEmoji.ttf: Can not load face (unknown file format; error code 0x2)
+
+
+    2026-07-11 16:20:09,868 - matplotlib.font_manager - INFO - generated new fontManager
+
+
+    Working Directory has been set to `HowToGalaxy`
+
+
+If the printed working directory does not match the workspace path on your computer, you can manually set it
+as follows (the example below shows the path I would use on my laptop. The code is commented out so you do not
+use this path in this tutorial!
+
+
+```python
+# workspace_path = "/Users/Jammy/Code/PyAuto/autogalaxy_workspace"
+# #%cd $workspace_path
+# print(f"Working Directory has been set to `{workspace_path}`")
+```
+
+__Dataset__
+
+The `dataset_path` specifies where the dataset is located, which is the
+directory `autogalaxy_workspace/dataset/imaging/simple__sersic`.
+
+There are many example simulated images of galaxies in this directory that will be used throughout the
+**HowToGalaxy** lectures.
+
+
+```python
+from pathlib import Path
+
+import autogalaxy as ag
+import autogalaxy.plot as aplt
+
+dataset_path = Path("dataset", "imaging", "simple__sersic")
+```
+
+__Dataset Auto-Simulation__
+
+If the dataset does not already exist on your system, it will be created by running the corresponding
+simulator script. This ensures that all example scripts can be run without manually simulating data first.
+
+
+```python
+if not dataset_path.exists():
+    import subprocess
+    import sys
+
+    subprocess.run(
+        [sys.executable, "scripts/simulators/sersic.py"],
+        check=True,
+    )
+
+```
+
+We now load this dataset from .fits files and create an instance of an `imaging` object.
+
+
+```python
+dataset = ag.Imaging.from_fits(
+    data_path=dataset_path / "data.fits",
+    noise_map_path=dataset_path / "noise_map.fits",
+    psf_path=dataset_path / "psf.fits",
+    pixel_scales=0.1,
+)
+```
+
+We can plot the data as follows:
+
+
+```python
+aplt.plot_array(array=dataset.data, title="Data")
+```
+
+
+
+![png](tutorial_0_visualization_files/tutorial_0_visualization_11_0.png)
+
+
+
+__Plot Customization__
+
+Does the figure display correctly on your computer screen?
+
+If not, you can customize common matplotlib options by passing them directly to `plot_array`:
+
+ - `title=`: Set the figure title.
+ - `figsize=`: Control the figure size as a `(width, height)` tuple.
+ - `colormap=`: Set the matplotlib colormap name (e.g. `"jet"`, `"gray"`).
+ - `xlabel=`, `ylabel=`: Override the default axis labels.
+
+
+```python
+aplt.plot_array(
+    array=dataset.data,
+    title="Data",
+)
+```
+
+
+
+![png](tutorial_0_visualization_files/tutorial_0_visualization_13_0.png)
+
+
+
+Many matplotlib options can be customized, but for now we're only concerned with making sure figures display clear in
+your Jupyter Notebooks. Nevertheless, a comprehensive API reference guide of all available plot arguments can
+be found in the `autogalaxy_workspace/*/guides/plot` package. You should check this out once you are more familiar with
+**PyAutoGalaxy**.
+
+Ideally, we would not specify a `figsize` every time we plot an image. Fortunately, default values can be fully
+customized via the config files.
+
+Checkout the `mat_wrap.yaml` file in `autogalaxy_workspace/config/visualize/mat_wrap`.
+
+All default matplotlib values are here. There are a lot of entries, so lets focus on whats important for displaying
+figures:
+
+ - mat_wrap.yaml -> Figure -> figure: -> figsize
+ - mat_wrap.yaml -> YLabel -> figure: -> fontsize
+ - mat_wrap.yaml -> XLabel -> figure: -> fontsize
+ - mat_wrap.yaml -> TickParams -> figure: -> labelsize
+ - mat_wrap.yaml -> YTicks -> figure: -> labelsize
+ - mat_wrap.yaml -> XTicks -> figure: -> labelsize
+
+Don't worry about all the other files or options listed for now, as they'll make a lot more sense once you are familiar
+with **PyAutoGalaxy**.
+
+If you had to change any of the above settings to get the figures to display clearly, you should update their values
+in the corresponding config files above (you will need to reset your Jupyter notebook server for these changes to
+take effect, so make sure you have the right values using the `figsize` argument in the cell above beforehand!).
+
+__Subplots__
+
+In addition to plotting individual figures, **PyAutoGalaxy** can also plot subplots showing all components of a
+dataset simultaneously.
+
+Lets plot a subplot of our `Imaging` data:
+
+
+```python
+aplt.subplot_imaging_dataset(dataset=dataset)
+```
+
+
+
+![png](tutorial_0_visualization_files/tutorial_0_visualization_15_0.png)
+
+
+
+__Visuals__
+
+Visuals can be added to any figure by passing them as keyword arguments directly to `plot_array`.
+
+For example, we can plot a mask on the image above by passing `mask=mask`.
+
+The `visuals` example illustrates every overlay argument, for example `mask=`, `grid=`, `positions=`, `lines=`, etc.
+
+
+```python
+mask = ag.Mask2D.circular_annular(
+    shape_native=dataset.shape_native,
+    pixel_scales=dataset.pixel_scales,
+    inner_radius=0.3,
+    outer_radius=3.0,
+)
+
+aplt.plot_array(array=dataset.data, title="Data")
+```
+
+
+
+![png](tutorial_0_visualization_files/tutorial_0_visualization_17_0.png)
+
+
+
+__Wrap Up__
+
+Throughout lectures you'll see lots more visuals that are plotted on figures and subplots.
+
+Great! Hopefully, visualization in **PyAutoGalaxy** is displaying nicely for us to get on with the **HowToGalaxy**
+lecture series.
+
+
+```python
+
+```