From ed2af0cb50945c875f96e48de2b14849ea17c8f5 Mon Sep 17 00:00:00 2001 From: Roger Labbe Date: Thu, 5 Mar 2015 21:50:43 -0800 Subject: [PATCH] Minor fixes. 538.json had some settings that were apparently made obsolete. Somehow a cell in the chapter was set to raw. --- 06_Multivariate_Kalman_Filters.ipynb | 2 +- code/538.json | 2 -- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/06_Multivariate_Kalman_Filters.ipynb b/06_Multivariate_Kalman_Filters.ipynb index e047aac..aff80ff 100644 --- a/06_Multivariate_Kalman_Filters.ipynb +++ b/06_Multivariate_Kalman_Filters.ipynb @@ -266,7 +266,7 @@ ] }, { - "cell_type": "raw", + "cell_type": "markdown", "metadata": {}, "source": [ "The techniques in the last chapter are very powerful, but they only work in one dimension. The gaussians represent a mean and variance that are scalars - real numbers. They provide no way to represent multidimensional data, such as the position of a dog in a field. You may retort that you could use two Kalman filters for that case, one tracks the x coordinate and the other tracks the y coordinate. That does work in some cases, but put that thought aside, because soon you will see some enormous benefits to implementing the multidimensional case.\n", diff --git a/code/538.json b/code/538.json index 98e3f17..a0669c1 100644 --- a/code/538.json +++ b/code/538.json @@ -1,6 +1,5 @@ { "lines.linewidth": 2.0, - "examples.download": true, "patch.linewidth": 0.5, "legend.fancybox": true, "axes.color_cycle": [ @@ -23,7 +22,6 @@ "axes.grid": true, "patch.edgecolor": "#f0f0f0", "axes.titlesize": "x-large", - "svg.embed_char_paths": "path", "examples.directory": "", "figure.facecolor": "#ffffff", "grid.linestyle": "-",