diff --git a/.gitattributes b/.gitattributes
index 237fb3f9b42a2be92bb66e809e51286e04a7b92e..fed42af56db72c93370f2c849ec0c10e126b747b 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -1 +1,2 @@
*.hdf filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..763513e910f7036a1a3cdb21dce8e57da2451891
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+.ipynb_checkpoints
diff --git a/README.md b/README.md
index 57021cb6abc6660ceec9134dd5157a63ea876429..df1fd59f5a0d07c2ad59f645a6e797f18420ab07 100644
--- a/README.md
+++ b/README.md
@@ -32,7 +32,7 @@ Assumptions:
1. On your machine, install the Git LFS extension ([here](https://git-lfs.github.com/) are some instructions).
2. In your local repository clone, configure which types of files you want to track by LFS.
- - For example, to let LFS keep track of HDF files, you can type: `$ git lfs track "*.hdf"`.
+ - For example, to let LFS keep track of [HDF files](https://www.hdfgroup.org/), type: `$ git lfs track "*.hdf"`.
- This will create/change the Git configuration file [`.gitattributes`](.gitattributes).
You should track this configuration change in Git, e.g. by the usual Git commands `$ git add .gitattributes` and `$ git commit -m "start tracking HDF files with LFS"`.
*Note that because the file name `.gitattributes` starts with a dot, it may be hidden from view (on Linux and MacOS, use `$ ls -a` to see it; FIXME: What to do on Windows?).*
diff --git a/example_analyis_script.ipynb b/example_analyis_script.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..568e6eb3e71948ecf337befc2abad7e0c70bbe7d
--- /dev/null
+++ b/example_analyis_script.ipynb
@@ -0,0 +1,19640 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "finite-tract",
+ "metadata": {},
+ "source": [
+ "# Example \"analysis\" script\n",
+ "\n",
+ "This example illustrates the integration of analysis code and data:\n",
+ "\n",
+ "- The script relies on the existence of a data file that is stored via Git LFS.\n",
+ "- The script creates plots that are saved into files that are tracked by Git LFS.\n",
+ "\n",
+ "For illustration, the file size used here is only 1 MB, but could in principle be much larger.\n",
+ "\n",
+ "*(To enable experimentation, you can also generate other data files, see bottom cell.\n",
+ "However, this isn't the point of the illustration.)*"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "id": "documented-reset",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Housekeeping, no output; execute once before other code cells.\n",
+ "%matplotlib inline\n",
+ "%config InlineBackend.figure_formats = ['svg'] # in notebook, save as nice SVG\n",
+ "import numpy # for handling numeric arrays\n",
+ "import h5py # to load/save HDF-5 files\n",
+ "import matplotlib.pyplot as plt # for plotting\n",
+ "\n",
+ "DATA_FILE = 'example_data.hdf' # path to (local) file tracked by Git LFS"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "id": "intimate-fitting",
+ "metadata": {},
+ "outputs": [
+ {
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+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
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+ }
+ ],
+ "source": [
+ "# Main illustration: Create figure based on existing data stored with Git LFS,\n",
+ "# and save figures as SVG files, which are also tracked by Git LFS.\n",
+ "\n",
+ "# The data file contains samples of the standard normal distribution.\n",
+ "with h5py.File(DATA_FILE, 'r') as file_handle:\n",
+ " data = file_handle['stdnormal'][:]\n",
+ "\n",
+ "# plot trace of data samples\n",
+ "plt.figure()\n",
+ "plt.plot(data)\n",
+ "plt.xlabel('Sample numbers')\n",
+ "plt.ylabel('Data values')\n",
+ "plt.title('Example trace plot of data')\n",
+ "plt.savefig(\"plots/plot_example_trace.png\")\n",
+ "\n",
+ "# plot histgram of the data samples\n",
+ "plt.figure()\n",
+ "plt.hist(data, 100)\n",
+ "plt.xlabel('Value')\n",
+ "plt.ylabel('Count')\n",
+ "plt.title('Example histogram of data')\n",
+ "plt.savefig(\"plots/plot_example_histogram.png\")\n",
+ "\n",
+ "# plot cumulative sum of data samples\n",
+ "plt.figure()\n",
+ "plt.plot(numpy.cumsum(data))\n",
+ "plt.ylabel('CumSum of values')\n",
+ "plt.xlabel('Sample numbers')\n",
+ "plt.title('Example plot of cumulative sum')\n",
+ "plt.savefig(\"plots/plot_example_cumsum.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 93,
+ "id": "blocked-prospect",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Wrote data into file \"example_data.hdf\".\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Appendix: Generate data set (for the sake of completeness).\n",
+ "\n",
+ "# Draw samples from the standard normal distribution.\n",
+ "np.random.seed(42)\n",
+ "Num_Data_Points = 150*1000\n",
+ "rand_normal_samples = numpy.random.randn(Num_Data_Points, 1)\n",
+ "\n",
+ "# Save the samples in a HDF-5 file.\n",
+ "with h5py.File(DATA_FILE, 'w') as file_handle:\n",
+ " file_handle.create_dataset('stdnormal', data=rand_normal_samples)\n",
+ "\n",
+ "print('Wrote data into file \"%s\".' % DATA_FILE)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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