PyAutoLabs · Jammy2211 · Jul 24, 2026 · Jul 24, 2026
diff --git a/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb b/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb
@@ -298,13 +298,6 @@
     "Great! Hopefully, visualization in **PyAutoLens** is displaying nicely for us to get on with the\n",
     "**HowToLens** lecture series."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb b/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb
@@ -1106,13 +1106,6 @@
     "Once you are more experienced, you should read up on over-sampling in more detail via\n",
     "the `autolens_workspace/*/guides/over_sampling.ipynb` notebook."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb b/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb
@@ -672,13 +672,6 @@
     "In the next tutorial, we'll extend these ideas to more complex mass and light distributions, building towards the\n",
     "realistic strong lens systems we observe in real data."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb b/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb
@@ -449,20 +449,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Lets have a quick look at the appearance of our lens galaxy and its satellite."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
+    "Lets have a quick look at the appearance of our lens galaxy and its satellite.\n",
+    "\n",
     "And their deflection angles, noting that the satellite does not contribute as much to the deflections."
    ]
   },
@@ -524,20 +512,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Lets look at our source galaxies (before lensing)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
+    "Lets look at our source galaxies (before lensing)\n",
+    "\n",
     "__Multi Galaxy Ray Tracing__\n",
     "\n",
     "Now lets pass our 4 galaxies to a `Tracer`, which means the following will occur:\n",
@@ -640,13 +616,6 @@
     " 3) The tracer has a small delay in being computed, whereas other tracers were almost instant. What do you think \n",
     " is the cause of this slow-down?"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb b/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb
@@ -78,13 +78,6 @@
    "source": [
     "__Wrap Up__"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb b/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb
@@ -79,13 +79,6 @@
    "source": [
     "__Wrap Up__"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_6_data.ipynb b/notebooks/chapter_1_introduction/tutorial_6_data.ipynb
@@ -655,13 +655,6 @@
     "\n",
     "- **Output**: We saved the simulated data to `.fits` files, the standard format used by astronomers for storing images."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb b/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb
@@ -1150,13 +1150,6 @@
     "- **Model Fitting**: We performed a basic model fit on a simple dataset, adjusting the model parameters to improve the\n",
     "  fit quality.  "
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb b/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb
@@ -312,13 +312,6 @@
     "\n",
     "Even the smallest bit of exposure via a GitHub star can help our project grow!"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb
@@ -1025,13 +1025,6 @@
     "scientific research and data analysis. In the next tutorials, these concepts will be further expanded upon to \n",
     "deepen your understanding and provide more advanced techniques for model fitting and analysis."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb
@@ -574,13 +574,6 @@
     "- How to estimate the run-time of a model-fit before initiating it, and change settings to make it faster or run the\n",
     "  analysis in parallel."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb
@@ -479,13 +479,6 @@
     " components (e.g. a disk, bulge, bar, star-forming knot) and there may even be more than 1 source galaxy! Do you \n",
     " think there is any hope of us navigating a parameter space if the source contributes 20+ parameters by itself?"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb
@@ -814,13 +814,6 @@
     "To wrap up chapter 2, we have a few more tutorials, where we will discuss masking in more detail, the `Result` object\n",
     "and how to make **PyAutoLens** run faster."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb
@@ -858,13 +858,6 @@
     "that does not make assumptions like a centre and can thus reconstruct even more complex, asymmetric and irregular\n",
     "galaxy morphologies."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb
@@ -449,13 +449,6 @@
     " 1.0\" is wise, as it is sufficiently large that even if the detailed structure of the source means we mark the positions\n",
     " incorrectly it will not mean that we remove physically plausible mass models. "
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb
@@ -259,13 +259,6 @@
     "This is because it makes it simple to perform all analyse in a Jupyter notebook, which is the most flexible and \n",
     "versatile way to check results and make figures."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb
@@ -124,13 +124,6 @@
     "\n",
     "_setup_colab.setup(\"howtolens\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb b/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb
@@ -664,13 +664,6 @@
     "Fortunately, we can pass priors in **PyAutoLens** without specifying the specific values. The API for this technique,\n",
     "called prior passing, is the topic of the next tutorial."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb b/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb
@@ -551,13 +551,6 @@
     "\n",
     "And with that, we're done. Chaining priors is a bit of an art form, but one that works really well. "
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb b/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb
@@ -565,13 +565,6 @@
     "always begin by fitting the lens and source simultaneously. This can use linear light profiles of a Multi-Gaussian\n",
     "Expansion. "
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb b/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb
@@ -488,13 +488,6 @@
     "`right_lens`. It still requires caution when writing the pipeline, but goes to show that if you name your galaxies \n",
     "sensibly you should be able to avoid errors, or spot them quickly when you make them."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_5_complex_source.ipynb b/notebooks/chapter_3_search_chaining/tutorial_5_complex_source.ipynb
@@ -484,13 +484,6 @@
     "But fear not, **PyAutoLens** has you covered. In chapter 4, we'll introduce a completely new way to model the source \n",
     "galaxy, which addresses the problem faced here."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb b/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb
@@ -85,13 +85,6 @@
     "\n",
     "_setup_colab.setup(\"howtolens\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb b/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb
@@ -550,13 +550,6 @@
     "\n",
     "Tutorial 2 done, next up, adaptive regularization!"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {

diff --git a/notebooks/chapter_4_pixelizations/tutorial_11_adaptive_regularization.ipynb b/notebooks/chapter_4_pixelizations/tutorial_11_adaptive_regularization.ipynb
@@ -435,13 +435,6 @@
     "solution possible and therefore ensure that our Bayesian evidence has a well defined maximum value. This was not the \n",
     "case for magnification based pixelization's and constant regularization schemes."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {