added motivation and prequisits to notebook preambles (fixes #147)

Author: cwehmeyer

notebooks/02-dimension-reduction-and-discretization.ipynb

@@ -8,7 +8,8 @@
     "\n",
     "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons Licence\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" title='This work is licensed under a Creative Commons Attribution 4.0 International License.' align=\"right\"/></a>\n",
     "\n",
-    "In this notebook, we will cover how to perform dimension reduction and discretization of molecular dynamics data.\n",
+    "In this notebook, we will cover how to perform dimension reduction and discretization of molecular dynamics data. We also repeat data loading and visualization tasks from the previous notebook\n",
+    "([01 ➜ 📓](01-data-io-and-featurization.ipynb)).\n",
     "\n",
     "Maintainers: [@cwehmeyer](https://github.com/cwehmeyer), [@marscher](https://github.com/marscher), [@thempel](https://github.com/thempel), [@psolsson](https://github.com/psolsson)\n",
     "\n",

notebooks/03-msm-estimation-and-validation.ipynb

@@ -8,9 +8,13 @@
     "\n",
     "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons Licence\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" title='This work is licensed under a Creative Commons Attribution 4.0 International License.' align=\"right\"/></a>\n",
     "\n",
-    "In this notebook, we will cover how to estimate a Markov state model (MSM) and do model validation.\n",
-    "We recommend to have a look at the literature, if you are new to the concept of Markov state models:\n",
+    "In this notebook, we will cover how to estimate a Markov state model (MSM) and do model validation;\n",
+    "we also show how to save and restore model and estimator objects.\n",
+    "For this notebook, you need to know how to do data loading/visualization\n",
+    "([Notebook 01 ➜ 📓](01-data-io-and-featurization.ipynb))\n",
+    "as well as dimension reduction ([Notebook 02 ➜ 📓](02-dimension-reduction-and-discretization.ipynb)).\n",
     "\n",
+    "We further recommend to have a look at the literature, if you are new to the concept of Markov state models:\n",
     "- <a id=\"ref-1\" href=\"#cite-msm-jhp\">prinz-11</a>\n",
     "- <a id=\"ref-2\" href=\"#cite-msm-book\">bowman-14</a>\n",
     "- <a id=\"ref-3\" href=\"#cite-msm-brooke\">husic-18</a>\n",

notebooks/04-msm-analysis.ipynb

@@ -9,6 +9,10 @@
     "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons Licence\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" title='This work is licensed under a Creative Commons Attribution 4.0 International License.' align=\"right\"/></a>\n",
     "\n",
     "In this notebook, we will cover how to analyze an MSM and how the modeled processes correspond to MSM spectral properties.\n",
+    "We assume that you are familiar with data loading/visualization\n",
+    "([Notebook 01 ➜ 📓](01-data-io-and-featurization.ipynb)),\n",
+    "dimension reduction ([Notebook 02 ➜ 📓](02-dimension-reduction-and-discretization.ipynb)), and\n",
+    "the estimation and validation process ([Notebook 03 ➜ 📓](03-msm-estimation-and-validation.ipynb)).\n",
     "\n",
     "Maintainers: [@cwehmeyer](https://github.com/cwehmeyer), [@marscher](https://github.com/marscher), [@thempel](https://github.com/thempel), [@psolsson](https://github.com/psolsson)\n",
     "\n",

notebooks/05-pcca-tpt.ipynb

@@ -11,13 +11,18 @@
     "In this notebook, we will cover how to use PCCA++ to extract a coarse representation of the MSM.\n",
     "We will further investigate how to use transition path theory (TPT) to follow the pathways of the processes.\n",
     "When we want to analyze pathways, models with fewer states are more often desirable, since these are easier to understand.\n",
-    "PCCA++ allows us to assign the microstates directly to metastable macrostates and TPT uses this group assignment to compute fluxes and pathways. \n",
+    "PCCA++ allows us to assign the microstates directly to metastable macrostates and TPT uses this group assignment to compute fluxes and pathways.\n",
     "\n",
     "Another method to get a model with fewer states are hidden Markov state models (HMM),\n",
     "introduced in [Notebook 07 ➜ 📓](07-hidden-markov-state-models.ipynb).\n",
     "In contrast to computing memberships of microstates to meta stable sets as in PCCA++,\n",
     "in HMMs we directly obtain a model with fewer states.\n",
     "\n",
+    "While we will mostly rely on previously estimated/validated models, it will be helpful to understand the topics\n",
+    "- data loading/visualization ([Notebook 01 ➜ 📓](01-data-io-and-featurization.ipynb))\n",
+    "- dimension reduction ([Notebook 02 ➜ 📓](02-dimension-reduction-and-discretization.ipynb))\n",
+    "- the estimation and validation process ([Notebook 03 ➜ 📓](03-msm-estimation-and-validation.ipynb))\n",
+    "\n",
     "Here you can find literature on the used methods:\n",
     "- <a id=\"ref-1\" href=\"#cite-pcca_plus_plus\">roeblitz-weber-14</a>\n",
     "- <a id=\"ref-2\" href=\"#cite-weinan-tpt\">weinan-06</a>\n",

notebooks/06-expectations-and-observables.ipynb

@@ -9,7 +9,14 @@
     "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons Licence\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" title='This work is licensed under a Creative Commons Attribution 4.0 International License.' align=\"right\"/></a>\n",
     "\n",
     "This notebook covers the calculation of stationary and dynamic expectation values.\n",
-    "These quantities include ensemble averaged observables measurable by experiments, correlation functions, and spectral densities.\n",
+    "These quantities include ensemble averaged observables measurable by experiments,\n",
+    "correlation functions, and spectral densities.\n",
+    "\n",
+    "For this notebook, we assume familiarity with \n",
+    "- data loading/visualization ([Notebook 01 ➜ 📓](01-data-io-and-featurization.ipynb))\n",
+    "- dimension reduction ([Notebook 02 ➜ 📓](02-dimension-reduction-and-discretization.ipynb))\n",
+    "- MSM estimation/validation ([Notebook 03 ➜ 📓](03-msm-estimation-and-validation.ipynb))\n",
+    "- basic analyis techniques ([Notebook 04 ➜ 📓](04-msm-analysis.ipynb) and [Notebook 05 ➜ 📓](05-pcca-tpt.ipynb))\n",
     "\n",
     "Literature:\n",
     "\n",

notebooks/07-hidden-markov-state-models.ipynb

@@ -9,7 +9,13 @@
     "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons Licence\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" title='This work is licensed under a Creative Commons Attribution 4.0 International License.' align=\"right\"/></a>\n",
     "\n",
     "In this notebook, we will learn about hidden Markov state models and how to use them to deal with poor discretization.\n",
-    "We further explain how to obtain a coarse model based on an initial MSM analysis.\n",
+    "We further explain how to obtain a coarse-grained model based on an initial MSM analysis.\n",
+    "\n",
+    "The prequisites for this tutorial are\n",
+    "- data loading/visualization ([Notebook 01 ➜ 📓](01-data-io-and-featurization.ipynb))\n",
+    "- dimension reduction ([Notebook 02 ➜ 📓](02-dimension-reduction-and-discretization.ipynb))\n",
+    "- MSM estimation/validation ([Notebook 03 ➜ 📓](03-msm-estimation-and-validation.ipynb))\n",
+    "- basic analyis techniques ([Notebook 04 ➜ 📓](04-msm-analysis.ipynb) and [Notebook 05 ➜ 📓](05-pcca-tpt.ipynb))\n",
     "\n",
     "Maintainers: [@cwehmeyer](https://github.com/cwehmeyer), [@marscher](https://github.com/marscher), [@thempel](https://github.com/thempel), [@psolsson](https://github.com/psolsson)\n",
     "\n",