diff --git a/workshops/WS2_colormaps.ipynb b/workshops/WS2_colormaps.ipynb
index 41cfc7f..2a54ec4 100644
--- a/workshops/WS2_colormaps.ipynb
+++ b/workshops/WS2_colormaps.ipynb
@@ -2,7 +2,6 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "8ad0822b",
    "metadata": {},
    "source": [
     "# Welcome to the SciViz Workshops\n",
@@ -18,19 +17,17 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b9f7889e",
    "metadata": {},
    "outputs": [],
    "source": [
     "# notebook metadata you can ignore!\n",
     "info = {\"workshop\": \"02\",\n",
     "        \"topic\": [\"colors\", \"colormaps\", \"normalisation\"],\n",
-    "        \"version\" : \"0.0.1\"}"
+    "        \"version\" : \"0.0.2\"}"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "6a4cad29",
    "metadata": {},
    "source": [
     "### How to use this notebook\n",
@@ -45,7 +42,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4385d531",
    "metadata": {},
    "source": [
     "# What is in this Workshop?\n",
@@ -59,7 +55,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "490ea1fe",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,7 +71,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "de61ab7c",
    "metadata": {},
    "source": [
     "# Section 1: Preparing Dummy Data"
@@ -85,7 +79,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "10635f3d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -98,7 +91,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2d6a3701",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -112,7 +104,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "557ad5a0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,7 +116,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "63ec1958",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -139,7 +129,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1a980041",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -158,7 +147,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bf1e794d",
    "metadata": {},
    "source": [
     "# Section 2: Colormaps in Matplotlib\n",
@@ -175,7 +163,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a0146b93",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -194,7 +181,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5e24691",
    "metadata": {
     "pycharm": {
      "name": "#%% md\n"
@@ -207,7 +193,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d8ab4ac2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -219,7 +204,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "83577fd4",
    "metadata": {},
    "source": [
     "And of course, reversed versions of if"
@@ -228,7 +212,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8af79b87",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -242,7 +225,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "577e7850",
    "metadata": {
     "pycharm": {
      "name": "#%% md\n"
@@ -255,7 +237,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e4fe46b5",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -270,7 +251,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "20a08fa7",
    "metadata": {},
    "source": [
     "### Diverging"
@@ -279,7 +259,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b66fefc9",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -294,7 +273,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4d317def",
    "metadata": {},
    "source": [
     "### Cycling"
@@ -303,7 +281,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "04f32d2b",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -316,7 +293,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8fdec44",
    "metadata": {},
    "source": [
     "### Qualitative"
@@ -325,7 +301,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6b55af78",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -339,7 +314,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "05be31ed",
    "metadata": {},
    "source": [
     "### Qualitative from Sequential (or any other type of colormap)"
@@ -348,7 +322,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e04ab5cc",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -362,7 +335,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1fefc3d0",
    "metadata": {},
    "source": [
     "## Colors for line plots\n",
@@ -374,7 +346,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "180de1ee",
    "metadata": {},
    "source": [
     "### Setting the colors explicitly"
@@ -383,7 +354,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "19301803",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -395,7 +365,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9c2ed418",
    "metadata": {
     "pycharm": {
      "name": "#%% md\n"
@@ -408,7 +377,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "06f17d34",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -427,7 +395,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1b82d2dd",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -443,7 +410,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "356e1096",
    "metadata": {
     "pycharm": {
      "name": "#%% md\n"
@@ -456,7 +422,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df149647",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -477,7 +442,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ae6c0f33",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -498,7 +462,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5d0483f6",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -520,7 +483,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "445ab842",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -537,7 +499,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4c1bf526",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -556,9 +517,31 @@
     "        axs.plot(x, y2 + a)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Plotting stacked data with custom sampled colors and cycler\n",
+    "A = np.stack([x, y1, y2]).T\n",
+    "\n",
+    "cs = [plt.get_cmap('viridis')(x) for x in np.linspace(0.1, 0.5, 3)]\n",
+    "\n",
+    "fig, axs = plt.subplots(1, 1, figsize=(8, 6), facecolor='w', edgecolor='k')\n",
+    "\n",
+    "axs.set_prop_cycle(cycler('color', cs) +\n",
+    "                   cycler('linestyle', ['-', '--', ':']))\n",
+    "\n",
+    "axs.plot(x, A)"
+   ]
+  },
   {
    "cell_type": "markdown",
-   "id": "cff1e2ec",
    "metadata": {},
    "source": [
     "## Colors for pseudo-color plots\n"
@@ -567,7 +550,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e96c82c2",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -586,7 +568,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "cf7e3689",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -606,7 +587,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "90955b42",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -626,7 +606,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "37b0ba34",
    "metadata": {},
    "source": [
     "# Section 3: Normalization of Data\n",
@@ -638,7 +617,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b4e69d54",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -660,7 +638,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a8733f76",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -668,7 +645,7 @@
     "fig, axs = plt.subplots(1, 1, figsize=(8, 6), facecolor='w', edgecolor='k')\n",
     "cb = axs.pcolormesh(X, Y, Z,\n",
     "                    shading='auto',\n",
-    "                    cmap=plt.get_cmap('RdBu'))\n",
+    "                    cmap=plt.get_cmap('RdBu_r'))\n",
     "\n",
     "# adding the colorbar\n",
     "cbar = fig.colorbar(cb, ax=axs,\n",
@@ -679,7 +656,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2c208e7e",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -695,7 +671,7 @@
     "cb = axs.pcolormesh(X, Y, Z,\n",
     "                    shading='auto',\n",
     "                    norm=norm,\n",
-    "                    cmap=plt.get_cmap('RdBu'))\n",
+    "                    cmap=plt.get_cmap('RdBu_r'))\n",
     "\n",
     "# adding the colorbar\n",
     "cbar = fig.colorbar(cb, ax=axs,\n",
@@ -706,7 +682,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e3cb63c7",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -720,7 +695,7 @@
     "                    shading='auto',\n",
     "                    vmin=-data_max,\n",
     "                    vmax=data_max,\n",
-    "                    cmap=plt.get_cmap('RdBu'))\n",
+    "                    cmap=plt.get_cmap('RdBu_r'))\n",
     "\n",
     "# adding the colorbar\n",
     "cbar = fig.colorbar(cb, ax=axs,\n",
@@ -731,7 +706,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3116095f",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -746,7 +720,7 @@
     "cb = axs.pcolormesh(X, Y, Z,\n",
     "                    shading='auto',\n",
     "                    norm=norm,\n",
-    "                    cmap=plt.get_cmap('RdBu'))\n",
+    "                    cmap=plt.get_cmap('RdBu_r'))\n",
     "\n",
     "# adding the colorbar\n",
     "cbar = fig.colorbar(cb, ax=axs,\n",
@@ -757,7 +731,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6c9bcccc",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -783,7 +756,7 @@
     "cb = axs.pcolormesh(X, Y, Z,\n",
     "                    shading='auto',\n",
     "                    norm=norm,\n",
-    "                    cmap=plt.get_cmap('RdBu'))\n",
+    "                    cmap=plt.get_cmap('RdBu_r'))\n",
     "\n",
     "# adding the colorbar\n",
     "cbar = fig.colorbar(cb, ax=axs,\n",
@@ -794,7 +767,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4ffec53b",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -803,7 +775,7 @@
    "outputs": [],
    "source": [
     "# we can also specify descrete bounds for the mapping\n",
-    "cmap = plt.get_cmap('RdBu')\n",
+    "cmap = plt.get_cmap('RdBu_r')\n",
     "\n",
     "bounds = [-0.25, -0.1, 0.0, 0.1, 0.25]\n",
     "norm = mpl.colors.BoundaryNorm(bounds, cmap.N, extend='both')\n",
@@ -819,7 +791,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3bbac13e",
    "metadata": {},
    "source": [
     "### Excercises\n",
@@ -840,8 +811,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
-   "id": "50666eea",
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -851,9 +821,7 @@
    "source": [
     "X, Y = np.meshgrid(np.linspace(-5, 5, 100, endpoint=True),\n",
     "                   np.linspace(-5, 5, 100, endpoint=True))\n",
-    "Z = np.sin(X) * np.cos(Y) + 1\n",
-    "\n",
-    "\n"
+    "Z = np.sin(X) * np.cos(Y) + 0.5"
    ]
   }
  ],
@@ -873,9 +841,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}