diff --git a/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb b/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb
index a3ffc9a..a8a9203 100644
--- 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
index c3cf453..ed5359d 100644
--- 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
index 979daf9..101f594 100644
--- 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
index f505281..5477a41 100644
--- 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
index 108c4b7..754a4b0 100644
--- 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
index ba1a670..bf6d4cd 100644
--- 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
index 680684a..4710193 100644
--- 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
index 69dee56..d0e98d4 100644
--- 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
index 5947271..f777e5e 100644
--- 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
index 206ab6c..49c490a 100644
--- 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
index 9635eaf..ebb335d 100644
--- 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
index 57a3c7b..fd5c482 100644
--- 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
index e16247e..8b6f091 100644
--- 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
index 60fdcfb..4af947a 100644
--- 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
index 3dee074..5e188ec 100644
--- 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
index a0119aa..0985b99 100644
--- 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
index 3b9d6b8..dec2e8c 100644
--- 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
index f7440a3..1612c78 100644
--- 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
index bc23985..cafc329 100644
--- 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
index 7b872d0..00e1ab9 100644
--- 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
index e1ba121..01f53e5 100644
--- 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
index fea5e54..be9fe14 100644
--- 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
index 17da152..496fe86 100644
--- 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
index 50eef57..c1acb89 100644
--- 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
index a6ded64..e59c4ce 100644
--- 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": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb b/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb
index b559aef..d6bbb36 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb
@@ -326,13 +326,6 @@
     " 2) The rectangular pixelization`s edges are aligned with the most exterior coordinates of the source-grid. This is \n",
     " intentional, why do you think this is?"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb b/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb
index df9524e..1e9e7cd 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb
@@ -512,13 +512,6 @@
     " galaxies on the pixel-grid. So, how does knowing how each pixel maps to the image actually help us? If you`ve not got \n",
     " any bright ideas, then worry not, that exactly what we're going to cover in the next tutorial."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb b/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
index b8edf48..a399b40 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
@@ -515,13 +515,6 @@
     "`autolens_workspace/*/imaging/log_likelihood_function/inversion.ipynb` which gives a visual step-by-step\n",
     "guide of the process alongside equations and references to literature on the subject."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb b/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb
index eab7252..ae8d885 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb
@@ -487,13 +487,6 @@
     "framework throughout, **PyAutoLens** objectively determines the final lens model following the principles of Bayesian\n",
     "analysis and Occam\u2019s Razor."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb b/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb
index 8decc82..9c35e81 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb
@@ -333,16 +333,8 @@
     "\n",
     "Towards the centre of th elliptical isothermal mass profile, the density begins to rise very sharply, it becomes \n",
     "extremely steep or 'cuspy'. This cuspy behaviour towards its centre can cause extremely large deflection angles to be \n",
-    "calculated:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [
+    "calculated:\n",
     "\n",
-    "# %%\n",
-    "'''\n",
     "Central image pixel can therefore be subjected to 'demagnification', whereby they trace to extremely large values in \n",
     "the source plane! \n",
     "\n",
@@ -363,11 +355,8 @@
     " have had other image-pixels traced within them via image-pixels at even larger radii from the centre of the lens \n",
     " galaxy. However, these image-pixels are at radii above 3.0\", meaning the circular mask removed them from the inversion.\n",
     "\n",
-    "Lets quickly use a large circular mask to confirm that these pixels exist when we don't mask them.\n",
-    "'''"
-   ],
-   "outputs": [],
-   "execution_count": null
+    "Lets quickly use a large circular mask to confirm that these pixels exist when we don't mask them."
+   ]
   },
   {
    "cell_type": "code",
@@ -750,13 +739,6 @@
     "However, as I showed above, if you don't choose a large enough mask things can go wrong and its important you know what \n",
     "borders are, so you can diagnose this potential source of systematics!"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb b/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb
index c659e23..2489d0e 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb
@@ -476,13 +476,6 @@
     " going to impact the source reconstruction negatively and can lead to some pretty nasty systematics. In the next \n",
     " chapter, we'll learn how our adaptive analysis can prevent this residual fitting."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb b/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb
index 73a38c8..0bb996e 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb
@@ -369,13 +369,6 @@
     "In the mean time, you may wish to experiment with using both Delaunay and Delaunay grids to fit \n",
     "lenses which can be easily achieve by changing the input pixelization given to a pipeline."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb b/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
index 8229abc..b7495f3 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
@@ -54,13 +54,6 @@
     "\n",
     "_setup_colab.setup(\"howtolens\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb b/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb
index 1aebd46..bdf8717 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb
@@ -475,13 +475,6 @@
     "\n",
     "The next two tutorials will show **PyAutoLens**'s adapt-model which enables this."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/chapter_optional/tutorial_searches.ipynb b/notebooks/chapter_optional/tutorial_searches.ipynb
index 08ac798..42cda46 100644
--- a/notebooks/chapter_optional/tutorial_searches.ipynb
+++ b/notebooks/chapter_optional/tutorial_searches.ipynb
@@ -477,13 +477,6 @@
     "For the vast majority of lens models in **PyAutoLens**, the default nested sampling search `Nautilus` is recommended,\n",
     "as it is robust, efficient and requires little manual tuning."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/simulator/lens_sersic.ipynb b/notebooks/simulator/lens_sersic.ipynb
index 52986a8..792504f 100644
--- a/notebooks/simulator/lens_sersic.ipynb
+++ b/notebooks/simulator/lens_sersic.ipynb
@@ -369,13 +369,6 @@
    "source": [
     "The dataset can be viewed in the folder `autolens_workspace/imaging/lens_sersic`."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/simulator/lens_x2.ipynb b/notebooks/simulator/lens_x2.ipynb
index 009d3c3..8f5df08 100644
--- a/notebooks/simulator/lens_x2.ipynb
+++ b/notebooks/simulator/lens_x2.ipynb
@@ -352,13 +352,6 @@
    "source": [
     "The dataset can be viewed in the folder `autolens_workspace/imaging/x2_lens_galaxies`."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/simulator/no_lens_light.ipynb b/notebooks/simulator/no_lens_light.ipynb
index cb4471c..6b036f5 100644
--- a/notebooks/simulator/no_lens_light.ipynb
+++ b/notebooks/simulator/no_lens_light.ipynb
@@ -437,13 +437,6 @@
    "source": [
     "The dataset can be viewed in the folder `autolens_workspace/imaging/simple__no_lens_light`."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/simulator/no_lens_light__mass_sis.ipynb b/notebooks/simulator/no_lens_light__mass_sis.ipynb
index 3b3a96c..edb0cfc 100644
--- a/notebooks/simulator/no_lens_light__mass_sis.ipynb
+++ b/notebooks/simulator/no_lens_light__mass_sis.ipynb
@@ -352,13 +352,6 @@
    "source": [
     "The dataset can be viewed in the folder `autolens_workspace/imaging/simple__no_lens_light`."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/notebooks/simulator/source_complex.ipynb b/notebooks/simulator/source_complex.ipynb
index c7aabfc..eb9555c 100644
--- a/notebooks/simulator/source_complex.ipynb
+++ b/notebooks/simulator/source_complex.ipynb
@@ -380,13 +380,6 @@
    "source": [
     "The dataset can be viewed in the folder `autolens_workspace/imaging/source_complex`."
    ]
-  },
-  {
-   "cell_type": "code",
-   "metadata": {},
-   "source": [],
-   "outputs": [],
-   "execution_count": null
   }
  ],
  "metadata": {
diff --git a/scripts/chapter_1_introduction/tutorial_3_more_ray_tracing.py b/scripts/chapter_1_introduction/tutorial_3_more_ray_tracing.py
index c5e2885..7b28149 100644
--- a/scripts/chapter_1_introduction/tutorial_3_more_ray_tracing.py
+++ b/scripts/chapter_1_introduction/tutorial_3_more_ray_tracing.py
@@ -278,10 +278,7 @@
 
 """
 Lets have a quick look at the appearance of our lens galaxy and its satellite.
-"""
-
 
-"""
 And their deflection angles, noting that the satellite does not contribute as much to the deflections.
 """
 
@@ -323,10 +320,7 @@
 
 """
 Lets look at our source galaxies (before lensing)
-"""
-
 
-"""
 __Multi Galaxy Ray Tracing__
 
 Now lets pass our 4 galaxies to a `Tracer`, which means the following will occur:
diff --git a/scripts/chapter_4_pixelizations/tutorial_5_borders.py b/scripts/chapter_4_pixelizations/tutorial_5_borders.py
index 9ea0ec9..67b83bb 100644
--- a/scripts/chapter_4_pixelizations/tutorial_5_borders.py
+++ b/scripts/chapter_4_pixelizations/tutorial_5_borders.py
@@ -194,9 +194,7 @@ def perform_fit_with_source_galaxy_mask_and_border(
 Towards the centre of th elliptical isothermal mass profile, the density begins to rise very sharply, it becomes 
 extremely steep or 'cuspy'. This cuspy behaviour towards its centre can cause extremely large deflection angles to be 
 calculated:
-"""
 
-"""
 Central image pixel can therefore be subjected to 'demagnification', whereby they trace to extremely large values in 
 the source plane!