[nb00] explain variance cutoff, kinetic map scaling.

fixes #146

Author: marscher

notebooks/00-pentapeptide-showcase.ipynb

@@ -231,7 +231,7 @@
     "\n",
     "### TICA\n",
     "\n",
-    "The goal of the next step is to find a function that maps the usually high-dimensional input space into some lower dimensional space that captures the important dynamics. The recommended way of doing so is a time-lagged independent component analysis (TICA), <a id=\"ref-4\" href=\"#cite-tica2\">molgedey-94</a>, <a id=\"ref-5\" href=\"#cite-tica\">perez-hernandez-13</a>. We perform TICA (with kinetic map scaling) using the lag time obtained from the VAMP-2 score. \n",
+    "The goal of the next step is to find a function that maps the usually high-dimensional input space into some lower dimensional space that captures the important dynamics. The recommended way of doing so is a time-lagged independent component analysis (TICA), <a id=\"ref-4\" href=\"#cite-tica2\">molgedey-94</a>, <a id=\"ref-5\" href=\"#cite-tica\">perez-hernandez-13</a>. We perform TICA (with kinetic map scaling) using the lag time obtained from the VAMP-2 score. The other values are kept at their default parameters, which will use as many dimensions in order to preserve $95\\%$ of the kinetic variance. By kinetic map scaling we ensure that Euclidean distances in the projected space approximate kinetic distances, which is a desirable property for clustering in this space.\n",
     "\n",
     "Please note that the general `PyEMMA` API is consistant for all estimators. By calling the TICA estimator with the data (`tica = pyemma.coordinates.tica(torsions_data)`), the estimation is done and an estimator instance returned (`tica`); this object contains all the information about the specific transformation. For small systems, we can access the transformed data by calling `tica.get_output()`. For large systems, we recommend to pass the `tica` object itself into the subsequent stages, e.g., clustering."
    ]
@@ -1636,7 +1636,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.6"
   },
   "toc": {
    "base_numbering": 1,