Fixes course

1_1_matplotlib.ipynb

@@ -26,8 +26,8 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "mpl.rcParams['pdf.fonttype'] = 42\n",
-    "mpl.rcParams['ps.fonttype'] = 42"
+    "mpl.rcParams[\"pdf.fonttype\"] = 42\n",
+    "mpl.rcParams[\"ps.fonttype\"] = 42"
    ]
   },
   {
@@ -105,7 +105,13 @@
     "x = mu + sigma * np.random.randn(10000)\n",
     "fig, ax = plt.subplots(figsize=(5, 2.7), layout=\"constrained\")\n",
     "# the histogram of the data\n",
-    "n, bins, patches = ax.hist(x, 50, density=True, facecolor=\"C0\", alpha=0.75)\n",
+    "n, bins, patches = ax.hist(\n",
+    "    x,\n",
+    "    50,\n",
+    "    density=True,\n",
+    "    facecolor=\"C0\",  # first color in color palette\n",
+    "    alpha=0.75,\n",
+    ")\n",
     "\n",
     "ax.set_xlabel(\"Length [cm]\")\n",
     "ax.set_ylabel(\"Probability\")\n",
@@ -141,7 +147,7 @@
     "Y2 = 1 + np.cos(1 + X / 0.75) / 2\n",
     "Y3 = np.random.uniform(Y1, Y2, len(X))\n",
     "\n",
-    "data = {'X': X, 'red_line': Y1, 'blue_line': Y2, 'circles': Y3}\n",
+    "data = {\"X\": X, \"red_line\": Y1, \"blue_line\": Y2, \"circles\": Y3}\n",
     "data = pd.DataFrame(data)\n",
     "data.head()"
    ]
@@ -175,19 +181,25 @@
     "ax.set_xlim(0, 4)\n",
     "ax.set_ylim(0, 4)\n",
     "\n",
-    "ax.tick_params(which='major', width=1.0, length=10, labelsize=14)\n",
-    "ax.tick_params(which='minor', width=1.0, length=5, labelsize=10,\n",
-    "               labelcolor='0.25')\n",
+    "ax.tick_params(which=\"major\", width=1.0, length=10, labelsize=14)\n",
+    "ax.tick_params(which=\"minor\", width=1.0, length=5, labelsize=10, labelcolor=\"0.25\")\n",
     "\n",
-    "ax.grid(linestyle=\"--\", linewidth=0.5, color='.25', zorder=-10)\n",
+    "ax.grid(linestyle=\"--\", linewidth=0.5, color=\".25\", zorder=-10)\n",
     "\n",
-    "ax.plot(X, Y1, c='C0', lw=2.5, label=\"Blue signal\", zorder=10)\n",
-    "ax.plot(X, Y2, c='C1', lw=2.5, label=\"Orange signal\")\n",
-    "ax.plot(X[::3], Y3[::3], linewidth=0, markersize=9,\n",
-    "        marker='s', markerfacecolor='none', markeredgecolor='C4',\n",
-    "        markeredgewidth=2.5)\n",
+    "ax.plot(X, Y1, c=\"C0\", lw=2.5, label=\"Blue signal\", zorder=10)\n",
+    "ax.plot(X, Y2, c=\"C1\", lw=2.5, label=\"Orange signal\")\n",
+    "ax.plot(\n",
+    "    X[::3],\n",
+    "    Y3[::3],\n",
+    "    linewidth=0,\n",
+    "    markersize=9,\n",
+    "    marker=\"s\",\n",
+    "    markerfacecolor=\"none\",\n",
+    "    markeredgecolor=\"C4\",  # color 5 in color palette\n",
+    "    markeredgewidth=2.5,\n",
+    ")\n",
     "\n",
-    "ax.set_title(\"Anatomy of a figure\", fontsize=20, verticalalignment='bottom')\n",
+    "ax.set_title(\"Anatomy of a figure\", fontsize=20, verticalalignment=\"bottom\")\n",
     "ax.set_xlabel(\"x Axis label\", fontsize=14)\n",
     "ax.set_ylabel(\"y Axis label\", fontsize=14)\n",
     "ax.legend(loc=\"upper right\", fontsize=14)"
@@ -332,7 +344,7 @@
    "outputs": [],
    "source": [
     "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(7.4, 4))\n",
-    "axes = axes.flatten() # in case of more than one dimension (safety snippet for you)\n",
+    "axes = axes.flatten()  # in case of more than one dimension (safety snippet for you)\n",
     "ax = axes[0]\n",
     "n, bins, patches = ax.hist(x, bins=30, alpha=0.7, color=\"C0\")\n",
     "ax = axes[1]\n",

1_1_matplotlib.py

@@ -13,8 +13,8 @@
 import numpy as np
 import pandas as pd
 
-mpl.rcParams['pdf.fonttype'] = 42
-mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams["pdf.fonttype"] = 42
+mpl.rcParams["ps.fonttype"] = 42
 
 # %% [markdown]
 # ## Basic Line Plot
@@ -49,7 +49,13 @@
 x = mu + sigma * np.random.randn(10000)
 fig, ax = plt.subplots(figsize=(5, 2.7), layout="constrained")
 # the histogram of the data
-n, bins, patches = ax.hist(x, 50, density=True, facecolor="C0", alpha=0.75)
+n, bins, patches = ax.hist(
+    x,
+    50,
+    density=True,
+    facecolor="C0",  # first color in color palette
+    alpha=0.75,
+)
 
 ax.set_xlabel("Length [cm]")
 ax.set_ylabel("Probability")
@@ -73,7 +79,7 @@
 Y2 = 1 + np.cos(1 + X / 0.75) / 2
 Y3 = np.random.uniform(Y1, Y2, len(X))
 
-data = {'X': X, 'red_line': Y1, 'blue_line': Y2, 'circles': Y3}
+data = {"X": X, "red_line": Y1, "blue_line": Y2, "circles": Y3}
 data = pd.DataFrame(data)
 data.head()
 
@@ -95,19 +101,25 @@
 ax.set_xlim(0, 4)
 ax.set_ylim(0, 4)
 
-ax.tick_params(which='major', width=1.0, length=10, labelsize=14)
-ax.tick_params(which='minor', width=1.0, length=5, labelsize=10,
-               labelcolor='0.25')
-
-ax.grid(linestyle="--", linewidth=0.5, color='.25', zorder=-10)
-
-ax.plot(X, Y1, c='C0', lw=2.5, label="Blue signal", zorder=10)
-ax.plot(X, Y2, c='C1', lw=2.5, label="Orange signal")
-ax.plot(X[::3], Y3[::3], linewidth=0, markersize=9,
-        marker='s', markerfacecolor='none', markeredgecolor='C4',
-        markeredgewidth=2.5)
-
-ax.set_title("Anatomy of a figure", fontsize=20, verticalalignment='bottom')
+ax.tick_params(which="major", width=1.0, length=10, labelsize=14)
+ax.tick_params(which="minor", width=1.0, length=5, labelsize=10, labelcolor="0.25")
+
+ax.grid(linestyle="--", linewidth=0.5, color=".25", zorder=-10)
+
+ax.plot(X, Y1, c="C0", lw=2.5, label="Blue signal", zorder=10)
+ax.plot(X, Y2, c="C1", lw=2.5, label="Orange signal")
+ax.plot(
+    X[::3],
+    Y3[::3],
+    linewidth=0,
+    markersize=9,
+    marker="s",
+    markerfacecolor="none",
+    markeredgecolor="C4",  # color 5 in color palette
+    markeredgewidth=2.5,
+)
+
+ax.set_title("Anatomy of a figure", fontsize=20, verticalalignment="bottom")
 ax.set_xlabel("x Axis label", fontsize=14)
 ax.set_ylabel("y Axis label", fontsize=14)
 ax.legend(loc="upper right", fontsize=14)
@@ -180,7 +192,7 @@
 
 # %%
 fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(7.4, 4))
-axes = axes.flatten() # in case of more than one dimension (safety snippet for you)
+axes = axes.flatten()  # in case of more than one dimension (safety snippet for you)
 ax = axes[0]
 n, bins, patches = ax.hist(x, bins=30, alpha=0.7, color="C0")
 ax = axes[1]

1_3_seaborn.ipynb

@@ -10,29 +10,18 @@
     "- [website](https://seaborn.pydata.org/)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
-   "source": [
-    "## Recreating the Figure from the sulforaphane Paper"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Recreating the Figure from the sulforaphane Paper\n",
     "Uses the data from [PXD04621](data/README.md) - using simulated data which looks\n",
     "similar to the original data\n",
     "([Marshall et. al. 2023)](https://www.sciencedirect.com/science/article/pii/S1756464623002451)).\n",
-    "![figure_2](https://ars.els-cdn.com/content/image/1-s2.0-S1756464623002451-gr2.jpg)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
+    "- [fake_growth_data.csv](data/growth/fake_growth_data.csv)\n",
+    "\n",
+    "![figure_2](https://ars.els-cdn.com/content/image/1-s2.0-S1756464623002451-gr2.jpg)\n",
+    "\n",
     "Take a look at this picture - do you think it is simple or complicated?\n",
     "It is not trivial to recreate it in Python - but don't worry, we will guide through all steps and tricks on making an (almost) exact copy of that picture in this notebook (at least from our knowledge). Let's get started."
    ]
@@ -63,7 +52,6 @@
     "import matplotlib as mpl\n",
     "import matplotlib.lines as mlines\n",
     "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
     "import pandas as pd\n",
     "import seaborn as sns\n",
     "from matplotlib.ticker import MultipleLocator\n",
@@ -75,15 +63,6 @@
     "IN_COLAB = \"COLAB_GPU\" in os.environ"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "IN_COLAB = True"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

1_3_seaborn.py

@@ -20,15 +20,13 @@
 
 # %% [markdown]
 # ## Recreating the Figure from the sulforaphane Paper
-
-
-# %% [markdown]
 # Uses the data from [PXD04621](data/README.md) - using simulated data which looks
 # similar to the original data
 # ([Marshall et. al. 2023)](https://www.sciencedirect.com/science/article/pii/S1756464623002451)).
+# - [fake_growth_data.csv](data/growth/fake_growth_data.csv)
+#
 # ![figure_2](https://ars.els-cdn.com/content/image/1-s2.0-S1756464623002451-gr2.jpg)
-
-# %% [markdown]
+#
 # Take a look at this picture - do you think it is simple or complicated?
 # It is not trivial to recreate it in Python - but don't worry, we will guide through all steps and tricks on making an (almost) exact copy of that picture in this notebook (at least from our knowledge). Let's get started.
 
@@ -45,7 +43,6 @@
 import matplotlib as mpl
 import matplotlib.lines as mlines
 import matplotlib.pyplot as plt
-import numpy as np
 import pandas as pd
 import seaborn as sns
 from matplotlib.ticker import MultipleLocator
@@ -56,9 +53,6 @@
 
 IN_COLAB = "COLAB_GPU" in os.environ
 
-# %%
-IN_COLAB = True
-
 # %%
 DATA_DIR = Path("data")
 

1_4_matplotlib_config.ipynb

@@ -0,0 +1,84 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "82fc7f4b",
+   "metadata": {
+    "lines_to_next_cell": 0
+   },
+   "source": [
+    "# Matplotlib Configuration\n",
+    "\n",
+    "Matplotlib Runtime Configuration (rc) allows you to customize the default styles and \n",
+    "behaviors of plots. The rcParams dictionary stores these settings,\n",
+    "such as font sizes, line widths,and color schemes.\n",
+    "You can modify rcParams directly in your code to change the appearance of all plots globally.\n",
+    "Example: `mpl.rcParams['lines.linewidth'] = 2.0`\n",
+    "You can also use style sheets or the 'matplotlibrc' file for persistent configuration."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bcf6d84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib\n",
+    "import matplotlib.font_manager\n",
+    "\n",
+    "print(matplotlib.rcParams['font.size'])  # Default font size (usually 'medium')\n",
+    "print(matplotlib.font_manager.font_scalings)  # Shows the scaling factors for each size keyword"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de009889",
+   "metadata": {},
+   "source": [
+    "Find the full list of rcParams you can modify\n",
+    "See the documentation [here] and specifically \n",
+    "[`rcParams`](https://matplotlib.org/stable/api/matplotlib_configuration_api.html#matplotlib.rcParams)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d2460360",
+   "metadata": {
+    "lines_to_next_cell": 2
+   },
+   "outputs": [],
+   "source": [
+    "matplotlib.rcParams['font.size'] = 14  # Set a new default font size"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8d59ddd",
+   "metadata": {},
+   "source": [
+    "See them all below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "55cb182f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "matplotlib.rcParams"
+   ]
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "cell_metadata_filter": "-all",
+   "main_language": "python",
+   "notebook_metadata_filter": "-all"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

1_4_matplotlib_config.py

@@ -0,0 +1,30 @@
+# %% [markdown]
+# # Matplotlib Configuration
+#
+# Matplotlib Runtime Configuration (rc) allows you to customize the default styles and 
+# behaviors of plots. The rcParams dictionary stores these settings,
+# such as font sizes, line widths,and color schemes.
+# You can modify rcParams directly in your code to change the appearance of all plots globally.
+# Example: `mpl.rcParams['lines.linewidth'] = 2.0`
+# You can also use style sheets or the 'matplotlibrc' file for persistent configuration.
+# %%
+import matplotlib
+import matplotlib.font_manager
+
+print(matplotlib.rcParams['font.size'])  # Default font size (usually 'medium')
+print(matplotlib.font_manager.font_scalings)  # Shows the scaling factors for each size keyword
+
+# %% [markdown]
+# Find the full list of rcParams you can modify
+# See the documentation [here] and specifically 
+# [`rcParams`](https://matplotlib.org/stable/api/matplotlib_configuration_api.html#matplotlib.rcParams).
+
+# %%
+matplotlib.rcParams['font.size'] = 14  # Set a new default font size
+
+
+# %% [markdown]
+# See them all below:
+
+# %%
+matplotlib.rcParams

2_plotly.ipynb

@@ -15,10 +15,20 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "845ce912",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "hide-output"
+    ]
+   },
    "outputs": [],
    "source": [
-    "import plotly.express as px"
+    "import os\n",
+    "import plotly.express as px\n",
+    "\n",
+    "IN_COLAB = \"COLAB_GPU\" in os.environ\n",
+    "\n",
+    "if IN_COLAB:\n",
+    "    !pip install kaleido"
    ]
   },
   {