Merge branch 'main' into timmens

Author: timmens

src/scipy_dev/notebooks/06_scaling-Copy1.ipynb

@@ -31,7 +31,7 @@
    "id": "6ef94deb",
    "metadata": {},
    "source": [
-    "## Get a badly scaled problem from a benchmar set"
+    "## Get a badly scaled problem from a benchmark set"
    ]
   },
   {

src/scipy_dev/notebooks/06_scaling.ipynb

@@ -9,6 +9,8 @@
     "\n",
     "In this exercise you will use automatic differentiation in JAX and estimagic to solve the previous problem.\n",
     "\n",
+    "> Note. Because JAX cannot (yet) be installed on Windows there will be extra exercises for Windows users.\n",
+    "\n",
     "## Resources\n",
     "\n",
     "- https://jax.readthedocs.io/en/latest/jax.numpy.html\n",
@@ -36,7 +38,13 @@
    "source": [
     "## Task 1:  Switch to JAX\n",
     "\n",
-    "- Use the code from exercise 2, task 2, and convert the criterion function and the start parameters to JAX. Look at the [`jax.numpy` documentation](https://jax.readthedocs.io/en/latest/jax.numpy.html) and slides if you have any questions."
+    "- Use the code from exercise 2, task 2, and convert the criterion function and the start parameters to JAX. Look at the [`jax.numpy` documentation](https://jax.readthedocs.io/en/latest/jax.numpy.html) and slides if you have any questions.\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Task 1 (Windows): Copy functions\n",
+    "\n",
+    "- Copy the criterion function and start parameters from exericse 2, task 2, here."
    ]
   },
   {
@@ -55,7 +63,14 @@
     "## Task 2: Gradient\n",
     "\n",
     "- Compute the gradient of the criterion (the whole function). Look at the [`autodiff_cookbook` documentation](https://jax.readthedocs.io/en/latest/notebooks/autodiff_cookbook.html) and slides if you have any questions.\n",
-    "- Measure the runtime of a jitted and unjitted version of the gradient (using `%timeit`.)"
+    "- Measure the runtime of a jitted and unjitted version of the gradient (using `%timeit`.)\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Task 2 (Windows): Gradient\n",
+    "\n",
+    "- Compute the gradient of the criterion (the whole function) analytically\n",
+    "- Implement the analytical gradient"
    ]
   },
   {
@@ -71,7 +86,7 @@
    "id": "85959d9b",
    "metadata": {},
    "source": [
-    "## Task 3: Minimize\n",
+    "## Task 3 (all systems): Minimize\n",
     "\n",
     "- Use estimagic to minimize the criterion\n",
     "    - pass the gradient function you computed above to the minimize call.\n",

src/scipy_dev/notebooks/07_automatic_differentiation.ipynb

@@ -9,6 +9,8 @@
     "\n",
     "In this exercise you will use JAXopt to solve a *batched* version of the first and second exercise.\n",
     "\n",
+    "> Note. You cannot tackle these exercises on Windows.\n",
+    "\n",
     "## Resources\n",
     "\n",
     "- [JAX documentation](https://jax.readthedocs.io/en/latest/notebooks/quickstart.html)\n",

src/scipy_dev/notebooks/08_jaxopt.ipynb

@@ -177,14 +177,6 @@
     "assert_array_almost_equal(b, np.arange(3))\n",
     "assert_array_almost_equal(c, np.eye(2))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "27f71064",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

src/scipy_dev/notebooks/solutions/01_first_optimization_with_scipy_optimize.ipynb

@@ -9,6 +9,8 @@
     "\n",
     "In this exercise you will use automatic differentiation in JAX and estimagic to solve the previous problem.\n",
     "\n",
+    "> Note. Here you will only find the solution for Unix and Linux.\n",
+    "\n",
     "## Resources\n",
     "\n",
     "- https://jax.readthedocs.io/en/latest/jax.numpy.html\n",

src/scipy_dev/notebooks/solutions/07_automatic_differentiation.ipynb

@@ -9,6 +9,8 @@
     "\n",
     "In this exercise you will use JAXopt to solve a *batched* version of the first and second exercise.\n",
     "\n",
+    "> Note. You cannot tackle these exercises on Windows.\n",
+    "\n",
     "## Resources\n",
     "\n",
     "- [JAX documentation](https://jax.readthedocs.io/en/latest/notebooks/quickstart.html)\n",