Updated basic example notebooks

Author: daurer

notebooks/basic_examples/00_the_parameter_tree.ipynb

@@ -323,7 +323,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/01_using_yaml_or_json_config.ipynb

@@ -213,7 +213,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/02_input_output_parameters.ipynb

@@ -57,7 +57,7 @@
    "metadata": {},
    "source": [
     "<div class=\"alert alert-info\" markdown=\"1\">\n",
-    "<strong>Note</strong><br>Live-plotting in Jupyter notebooks using <code>p.io.autoplot</code> works best in conjunction with <code>p.verbose_level = \"interactive\"</code>.\n",
+    "<strong>Note</strong><br>Live-plotting in Jupyter notebooks using <code>p.io.autoplot</code> works best together with <code>p.verbose_level = \"interactive\"</code>.\n",
     "</div>"
    ]
   },
@@ -84,17 +84,7 @@
    "metadata": {},
    "source": [
     "<div class=\"alert alert-warning\" markdown=\"1\">\n",
-    "    <strong>Challenge</strong><br>Modify the <code>p.io.home</code> path in the example below to wherever you would like the PtyPy output to be, run the reconstruction and observe all the new files saved to the path specified as <code>p.io.home</code>. You can use <code>ptypy.utils.plot_recon_from_ptyr</code> to look at the MoonFlower reconstruction at different iterations. \n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "53080c06-2b70-4eaf-9d88-5575c77c13e0",
-   "metadata": {},
-   "source": [
-    "<div class=\"alert alert-success\" markdown=\"1\">\n",
-    "    <strong>Hint</strong><br>You can use shell commands within Jupyter Notebooks to explore the filesystem, i.e. <code>ls /tmp</code> to list all files in /tmp.\n",
+    "    <strong>Challenge</strong><br>Modify the <code>p.io.home</code> path in the example below to wherever you would like the PtyPy output to be, run the reconstruction and observe all the new files saved to the path specified as <code>p.io.home</code>. You can use <code>ptypy.utils.plot_recon_from_ptyr</code> to look at the MoonFlower reconstruction at different iterations based on <code>.ptyr</code> snapshots. \n",
     "</div>"
    ]
   },
@@ -204,7 +194,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/03_scan_models.ipynb

@@ -14,7 +14,19 @@
    "id": "26f5e41d-88c9-4544-a85b-649e29fffbe9",
    "metadata": {},
    "source": [
-    "The scan model is one of the core components that defines a ptychography experiment, it creates different data structures such as [Views](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.View), [Containers](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.Container) and [Storages](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.Storage). It also creates the [PODs](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.POD) which link the containers (and views) of probe, object, exit wave and diffraction data. PtyPy offers a range of different scan models\n",
+    "The scan model is one of the core components that defines a ptychography experiment, it creates different data structures such as [Views](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.View), [Containers](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.Container) and [Storages](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.Storage). It also creates the [PODs](https://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.classes.POD) which link the containers (and views) of probe, object, exit wave and diffraction data. This figure provides an overview of how PtyPy models an ptychographic experiment\n",
+    "\n",
+    "<img src=\"./_assets/ptypy_model.jpg\" alt=\"ptypy-model\" width=\"75%\">\n",
+    "\n",
+    "**The PtyPy model in a nutshell:** (a) Experimental sketch of a ptychographic experiment with optics focused on a sample and diffraction measured by a detector. (b) For each experimental view, PtyPy's **pod** captures all relevant properties from probe/object to exit wave, forward proejctor and diffraction data. (c) Example images for single view. (d) Diagram of the network of pods, each connected to a data view, a probe an object view and an exit wave. (e) Each pod has a container for the probe, object and diffraction - these containers are themselves connected underlying storages."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "751d51d7-f500-4e6e-a37b-2cd1748134c7",
+   "metadata": {},
+   "source": [
+    "PtyPy offers a range of different scan models\n",
     "\n",
     "- The most commonly used scan model is `Full` and should work in most cases, but might not be suitable for large datasets (>10k frames)\n",
     "\n",
@@ -24,7 +36,7 @@
     "\n",
     "- `Vanilla` is a lightweight scan model that can be useful for simple simulations.\n",
     "\n",
-    "All the `Full` - flavoured models share the same set of [parameters](https://ptycho.github.io/ptypy/rst/parameters.html#scan-full), while `Vanilla` has a much smaller sub-set of [parameters](https://ptycho.github.io/ptypy/rst/parameters.html#scan-vanilla).\n"
+    "All the `Full` - flavoured models share the same set of [parameters](https://ptycho.github.io/ptypy/rst/parameters.html#scan-full), while `Vanilla` has a much smaller sub-set of [parameters](https://ptycho.github.io/ptypy/rst/parameters.html#scan-vanilla)."
    ]
   },
   {
@@ -225,7 +237,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/04_choosing_engines.ipynb

@@ -100,7 +100,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/05_projectional_engines.ipynb

@@ -175,7 +175,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/06_stochastic_engines.ipynb

@@ -136,7 +136,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/basic_examples/07_gradient_based_engines.ipynb

@@ -142,7 +142,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,