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gher-uliege · Nov 22, 2024 · 062e71e · 062e71e
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diff --git a/notebooks/3-Analysis/14-cpme-demo.ipynb b/notebooks/3-Analysis/14-cpme-demo.ipynb
@@ -155,13 +155,18 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "source": [
     "### Analysis\n",
     "Analysis parameters have been calibrated in the other notebook [13-processing-parameter-optimization example.ipynb](13-processing-parameter-optimization). \n",
     "\n",
-    "⚠ if the statistical parameters are incorrectly estimated, the error fields are meaningless and only provide an idea of data coverage.\n",
+    "<div class=\"alert alert-block alert-warning\"> \n",
+    " ⚠ If the statistical parameters are incorrectly estimated, the error fields are meaningless and only provide an idea of data coverage.\n",
+    "</div>\n",
     "\n",
     "The analysis parameters are:"
    ]
@@ -173,7 +178,7 @@
    "outputs": [],
    "source": [
     "len = 0.3\n",
-    "epsilon2 = 1.0;"
+    "epsilon2 = 1.4;"
    ]
   },
   {
@@ -224,21 +229,11 @@
    "source": [
     "## Exact error and approximations\n",
     "\n",
-    "Details can be found in the publication:\n",
+    "<div class=\"alert alert-block alert-info\"> \n",
+    "<b>NOTE</b> Details can be found in the publication mentioned at the beginning of the notebook.\n",
+    "</div>\n",
     "\n",
-    "> Approximate and Efficient Methods to Assess Error Fields in Spatial Gridding with Data Interpolating Variational Analysis (DIVA)       \n",
-    "Beckers, Jean-Marie; Barth, Alexander;  Troupin, Charles, Alvera-Azcarate, A.  *Journal of Atmospheric & Oceanic Technology* (2014), **31(2)**, 515-530     \n",
-    "https://orbi.uliege.be/handle/2268/161069      \n",
-    "https://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-13-00130.1"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the 2D case you can try to calculate the exact error expression. This demands the computationally expensive evaluation of `diag(s.P)` accessible via the analysis returned structure `s`. This is only available with `DIVAndrun`.\n",
-    "\n",
-    "We define a function that will be run to plot the error field."
+    "First we define a utility function for plotting."
    ]
   },
   {
@@ -261,14 +256,23 @@
     "end"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exact error by hand\n",
+    "\n",
+    "In the 2D case you can try to calculate the exact error expression. This demands the computationally expensive evaluation of `diag(s.P)` accessible via the analysis returned structure `s`. The latter is only available with `DIVAndrun`."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "exerr, = statevector_unpack(s.sv,diag(s.P),NaN)\n",
-    "ploterr(exerr, figtitle= \"Unscaled error\")"
+    "ploterr(exerr, figtitle= \"Error using P, scaled by global background variance\")"
    ]
   },
   {
@@ -306,7 +310,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Do you see any difference between the exact and clever poor man's error ? \n",
+    "Do you see any difference between the exact and clever poor man's error ? "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Difference between error fields"
    ]
   },
@@ -376,15 +386,12 @@
    "source": [
     "# Conclusion\n",
     "In view of the uncertainties on statistical parameters (L, $\\epsilon^2$), the *clever poor man's error* is generally a sufficient approximation for the error fields.     \n",
-    "This is the one implemented in the `DIVAndgo` high-level analysis function. "
+    "This is the one implemented in the `DIVAndgo` high-level analysis function. \n",
+    "\n",
+    "<div class=\"alert alert-block alert-info\"> \n",
+    "<b>NOTE</b> The next notebook will focus on another function, `DIVAnd_errormap` to evaluate the error field.\n",
+    "</div>"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -419,5 +426,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }