Deploying to gh-pages from @ 93dec5e 🚀

generated/gallery/mg_execution_times/index.html

@@ -613,19 +613,19 @@
 
 
 <h1 id="computation-times">Computation times<a class="headerlink" href="#computation-times" title="Permanent link">&para;</a></h1>
-<p><strong>00:36.628</strong> total execution time for <strong>generated_gallery</strong> files:</p>
+<p><strong>00:51.721</strong> total execution time for <strong>generated_gallery</strong> files:</p>
 <p>+----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_2_2d_examples/">plot_2_2d_examples</a> (docs/examples/plot_2_2d_examples.py)    | 00:13.505 | 0.0 MB |
+| <a href="../plot_2_2d_examples/">plot_2_2d_examples</a> (docs/examples/plot_2_2d_examples.py)    | 00:19.947 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_4_nd_examples/">plot_4_nd_examples</a> (docs/examples/plot_4_nd_examples.py)    | 00:11.310 | 0.0 MB |
+| <a href="../plot_4_nd_examples/">plot_4_nd_examples</a> (docs/examples/plot_4_nd_examples.py)    | 00:15.867 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_3_3d_examples/">plot_3_3d_examples</a> (docs/examples/plot_3_3d_examples.py)    | 00:05.871 | 0.0 MB |
+| <a href="../plot_3_3d_examples/">plot_3_3d_examples</a> (docs/examples/plot_3_3d_examples.py)    | 00:07.542 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_5_mrg_examples/">plot_5_mrg_examples</a> (docs/examples/plot_5_mrg_examples.py) | 00:04.270 | 0.0 MB |
+| <a href="../plot_5_mrg_examples/">plot_5_mrg_examples</a> (docs/examples/plot_5_mrg_examples.py) | 00:06.215 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_1_1d_examples/">plot_1_1d_examples</a> (docs/examples/plot_1_1d_examples.py)    | 00:01.666 | 0.0 MB |
+| <a href="../plot_1_1d_examples/">plot_1_1d_examples</a> (docs/examples/plot_1_1d_examples.py)    | 00:02.143 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+
-| <a href="../plot_functions/">plot_functions</a> (docs/examples/plot_functions.py)                | 00:00.006 | 0.0 MB |
+| <a href="../plot_functions/">plot_functions</a> (docs/examples/plot_functions.py)                | 00:00.007 | 0.0 MB |
 +----------------------------------------------------------------------------------------+-----------+--------+</p>
 
 

generated/gallery/plot_5_mrg_examples.ipynb

@@ -51,7 +51,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "Although it is possible to merge data in any dimension, these examples will\nfocus on merging 2D data. Therefore, we'll use the same\n[`plot_examples_2d`](plot_functions.md#plot_examples_2d) function used for\nthe [2D examples](../plot_2_2d_examples):\n\n"
+        "Although it is possible to merge data in any dimension, these examples will\nfocus on merging 2D data. Therefore, we'll use the same\n[`plot_examples_2d`](plot_functions.md#plot_examples_2d) function used for\nthe [2D examples](plot_2_2d_examples.md):\n\n"
       ]
     },
     {

generated/gallery/plot_5_mrg_examples.py

@@ -23,7 +23,7 @@ def rng(seed):
 # Although it is possible to merge data in any dimension, these examples will
 # focus on merging 2D data. Therefore, we'll use the same
 # [`plot_examples_2d`](plot_functions.md#plot_examples_2d) function used for
-# the [2D examples](../plot_2_2d_examples):
+# the [2D examples](plot_2_2d_examples.md):
 
 from plot_functions import plot_examples_2d
 

generated/gallery/plot_5_mrg_examples.py.md5

@@ -1 +1 @@
-2007d6433257ab7ebd44e4d7fed479cd
+7a370e69cb42b786ee10efd925cb5971

generated/gallery/plot_functions.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import matplotlib.pyplot as plt  # type: ignore\nimport numpy as np\nimport numpy.typing as npt\nimport pandas as pd\nimport seaborn as sns  # type: ignore\n\nfrom pyclugen import Clusters"
+        "import os\nimport warnings\n\nimport matplotlib.pyplot as plt  # type: ignore\nimport numpy as np\nimport numpy.typing as npt\nimport pandas as pd\nimport seaborn as sns  # type: ignore\n\nfrom pyclugen import Clusters\n\n# Hide annoying warnings when building docs in CI\nif os.getenv(\"CI\") != None:\n    warnings.filterwarnings(\"ignore\")"
       ]
     },
     {
@@ -105,7 +105,7 @@
       },
       "outputs": [],
       "source": [
-        "def plot_examples_2d(\n    *ets, pmargin: float = 0.1, ncols: int = 3, clusters_field: str = \"clusters\"\n):\n    \"\"\"Plot the 2D examples given in the ets parameter.\"\"\"\n\n    # Get examples\n    ex = ets[0::2]\n    # Get titles\n    et = ets[1::2]\n\n    df = clusters2df(*ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Set seaborn's dark grid style\n    sns.set_theme(style=\"darkgrid\")\n\n    # Use seaborn to create the plots\n    g = sns.FacetGrid(\n        df,\n        col=\"example\",\n        hue=\"cluster\",\n        xlim=(xmins[0], xmaxs[0]),\n        ylim=(xmins[1], xmaxs[1]),\n        aspect=1,\n        col_wrap=ncols,\n    )\n\n    g.map(sns.scatterplot, \"x0\", \"x1\", s=10)\n\n    # Set the plot titles and x, y labels\n    for ax, t in zip(g.axes, et):\n        ax.set_title(t)\n        ax.set_xlabel(\"x\")\n        ax.set_ylabel(\"y\")"
+        "def plot_examples_2d(\n    *ets, pmargin: float = 0.1, ncols: int = 3, clusters_field: str = \"clusters\"\n):\n    \"\"\"Plot the 2D examples given in the ets parameter.\"\"\"\n\n    # Get examples\n    ex = ets[0::2]\n    # Get titles\n    et = ets[1::2]\n\n    df = clusters2df(*ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Set seaborn's dark grid style\n    sns.set_theme(style=\"darkgrid\")\n\n    # Use seaborn to create the plots\n    g = sns.FacetGrid(\n        df,\n        col=\"example\",\n        hue=\"cluster\",\n        xlim=(xmins.iloc[0], xmaxs.iloc[0]),\n        ylim=(xmins.iloc[1], xmaxs.iloc[1]),\n        aspect=1,\n        col_wrap=ncols,\n    )\n\n    g.map(sns.scatterplot, \"x0\", \"x1\", s=10)\n\n    # Set the plot titles and x, y labels\n    for ax, t in zip(g.axes, et):\n        ax.set_title(t)\n        ax.set_xlabel(\"x\")\n        ax.set_ylabel(\"y\")"
       ]
     },
     {
@@ -123,7 +123,7 @@
       },
       "outputs": [],
       "source": [
-        "def plot_examples_3d(\n    *ets,\n    pmargin: float = 0.1,\n    ncols: int = 3,\n    side=350,\n    clusters_field: str = \"clusters\",\n):\n    \"\"\"Plot the 3D examples given in the ets parameter.\"\"\"\n\n    # Get examples\n    ex = ets[0::2]\n    # Get titles\n    et = ets[1::2]\n\n    # Number of plots and number of rows in combined plot\n    num_plots = len(ex)\n    nrows = max(1, int(np.ceil(num_plots / ncols)))\n    blank_plots = nrows * ncols - num_plots\n\n    df = clusters2df(*ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Reset to default Matplotlib style, to avoid seaborn interference\n    sns.reset_orig()\n\n    # To convert inches to pixels afterwards\n    px = 1 / plt.rcParams[\"figure.dpi\"]  # pixel in inches\n\n    # Use Matplotlib to create the plots\n    _, axs = plt.subplots(\n        nrows,\n        ncols,\n        figsize=(side * px * ncols, side * px * nrows),\n        subplot_kw=dict(projection=\"3d\"),\n    )\n    axs = axs.reshape(-1)\n    for ax, e, t in zip(axs, ex, et):\n        ax.set_title(t, fontsize=10)\n        ax.set_xlim(xmins[0], xmaxs[0])\n        ax.set_ylim(xmins[1], xmaxs[1])\n        ax.set_zlim(xmins[2], xmaxs[2])\n        ax.set_xlabel(\"$x$\", labelpad=-2)\n        ax.set_ylabel(\"$y$\", labelpad=-2)\n        ax.set_zlabel(\"$z$\", labelpad=-2)\n        ax.tick_params(labelsize=8, pad=-2)\n        ax.scatter(\n            e.points[:, 0],\n            e.points[:, 1],\n            e.points[:, 2],\n            c=e.clusters,\n            depthshade=False,\n            edgecolor=\"black\",\n            linewidths=0.2,\n        )\n\n    # Remaining plots are left blank\n    for ax in axs[len(ex) : len(ex) + blank_plots]:\n        ax.set_axis_off()\n        ax.set_facecolor(color=\"white\")\n        ax.patch.set_alpha(0)"
+        "def plot_examples_3d(\n    *ets,\n    pmargin: float = 0.1,\n    ncols: int = 3,\n    side=350,\n    clusters_field: str = \"clusters\",\n):\n    \"\"\"Plot the 3D examples given in the ets parameter.\"\"\"\n\n    # Get examples\n    ex = ets[0::2]\n    # Get titles\n    et = ets[1::2]\n\n    # Number of plots and number of rows in combined plot\n    num_plots = len(ex)\n    nrows = max(1, int(np.ceil(num_plots / ncols)))\n    blank_plots = nrows * ncols - num_plots\n\n    df = clusters2df(*ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Reset to default Matplotlib style, to avoid seaborn interference\n    sns.reset_orig()\n\n    # To convert inches to pixels afterwards\n    px = 1 / plt.rcParams[\"figure.dpi\"]  # pixel in inches\n\n    # Use Matplotlib to create the plots\n    _, axs = plt.subplots(\n        nrows,\n        ncols,\n        figsize=(side * px * ncols, side * px * nrows),\n        subplot_kw=dict(projection=\"3d\"),\n    )\n    axs = axs.reshape(-1)\n    for ax, e, t in zip(axs, ex, et):\n        ax.set_title(t, fontsize=10)\n        ax.set_xlim(xmins.iloc[0], xmaxs.iloc[0])\n        ax.set_ylim(xmins.iloc[1], xmaxs.iloc[1])\n        ax.set_zlim(xmins.iloc[2], xmaxs.iloc[2])\n        ax.set_xlabel(\"$x$\", labelpad=-2)\n        ax.set_ylabel(\"$y$\", labelpad=-2)\n        ax.set_zlabel(\"$z$\", labelpad=-2)\n        ax.tick_params(labelsize=8, pad=-2)\n        ax.scatter(\n            e.points[:, 0],\n            e.points[:, 1],\n            e.points[:, 2],\n            c=e.clusters,\n            depthshade=False,\n            edgecolor=\"black\",\n            linewidths=0.2,\n        )\n\n    # Remaining plots are left blank\n    for ax in axs[len(ex) : len(ex) + blank_plots]:\n        ax.set_axis_off()\n        ax.set_facecolor(color=\"white\")\n        ax.patch.set_alpha(0)"
       ]
     },
     {
@@ -141,7 +141,7 @@
       },
       "outputs": [],
       "source": [
-        "def plot_examples_nd(\n    ex: Clusters, t: str, pmargin: float = 0.1, clusters_field: str = \"clusters\"\n):\n    \"\"\"Plot the nD example given in the ex parameter.\"\"\"\n\n    # How many dimensions?\n    nd = ex.points.shape[1]\n\n    df = clusters2df(ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Set seaborn's dark grid style\n    sns.set_theme(style=\"darkgrid\")\n\n    # Create pairwise plots with nothing on the diagonal\n    g = sns.PairGrid(df.iloc[:, :-1], hue=\"cluster\", palette=\"deep\")\n    g.map_offdiag(sns.scatterplot, s=10)\n    g.figure.suptitle(t, y=1)\n\n    # Decorate plot\n    for i in range(nd):\n        for j in range(nd):\n            if i == j:\n                # Set the x labels in the diagonal plots\n                xycoord = (xmaxs[i] + xmins[i]) / 2\n                g.axes[i, i].text(\n                    xycoord, xycoord, f\"$x{i}$\", fontsize=20, ha=\"center\", va=\"center\"\n                )\n            else:\n                # Set appropriate plot intervals and aspect ratio\n                g.axes[i, j].set_xlim([xmins[j], xmaxs[j]])\n                g.axes[i, j].set_ylim([xmins[i], xmaxs[i]])\n                g.axes[i, j].set_aspect(1)"
+        "def plot_examples_nd(\n    ex: Clusters, t: str, pmargin: float = 0.1, clusters_field: str = \"clusters\"\n):\n    \"\"\"Plot the nD example given in the ex parameter.\"\"\"\n\n    # How many dimensions?\n    nd = ex.points.shape[1]\n\n    df = clusters2df(ex, clusters_field=clusters_field)\n\n    # Get limits in each dimension\n    xmaxs, xmins = get_plot_lims(df, pmargin=pmargin)\n\n    # Set seaborn's dark grid style\n    sns.set_theme(style=\"darkgrid\")\n\n    # Create pairwise plots with nothing on the diagonal\n    g = sns.PairGrid(df.iloc[:, :-1], hue=\"cluster\", palette=\"deep\")\n    g.map_offdiag(sns.scatterplot, s=10)\n    g.figure.suptitle(t, y=1)\n\n    # Decorate plot\n    for i in range(nd):\n        for j in range(nd):\n            if i == j:\n                # Set the x labels in the diagonal plots\n                xycoord = (xmaxs.iloc[i] + xmins.iloc[i]) / 2\n                g.axes[i, i].text(\n                    xycoord, xycoord, f\"$x{i}$\", fontsize=20, ha=\"center\", va=\"center\"\n                )\n            else:\n                # Set appropriate plot intervals and aspect ratio\n                g.axes[i, j].set_xlim([xmins.iloc[j], xmaxs.iloc[j]])\n                g.axes[i, j].set_ylim([xmins.iloc[i], xmaxs.iloc[i]])\n                g.axes[i, j].set_aspect(1)"
       ]
     }
   ],

generated/gallery/plot_functions.py

@@ -6,6 +6,9 @@
 # %%
 # ## Import the required libraries
 
+import os
+import warnings
+
 import matplotlib.pyplot as plt  # type: ignore
 import numpy as np
 import numpy.typing as npt
@@ -14,6 +17,10 @@
 
 from pyclugen import Clusters
 
+# Hide annoying warnings when building docs in CI
+if os.getenv("CI") != None:
+    warnings.filterwarnings("ignore")
+
 # %%
 # ## clusters2df
 
@@ -133,8 +140,8 @@ def plot_examples_2d(
         df,
         col="example",
         hue="cluster",
-        xlim=(xmins[0], xmaxs[0]),
-        ylim=(xmins[1], xmaxs[1]),
+        xlim=(xmins.iloc[0], xmaxs.iloc[0]),
+        ylim=(xmins.iloc[1], xmaxs.iloc[1]),
         aspect=1,
         col_wrap=ncols,
     )
@@ -192,9 +199,9 @@ def plot_examples_3d(
     axs = axs.reshape(-1)
     for ax, e, t in zip(axs, ex, et):
         ax.set_title(t, fontsize=10)
-        ax.set_xlim(xmins[0], xmaxs[0])
-        ax.set_ylim(xmins[1], xmaxs[1])
-        ax.set_zlim(xmins[2], xmaxs[2])
+        ax.set_xlim(xmins.iloc[0], xmaxs.iloc[0])
+        ax.set_ylim(xmins.iloc[1], xmaxs.iloc[1])
+        ax.set_zlim(xmins.iloc[2], xmaxs.iloc[2])
         ax.set_xlabel("$x$", labelpad=-2)
         ax.set_ylabel("$y$", labelpad=-2)
         ax.set_zlabel("$z$", labelpad=-2)
@@ -246,12 +253,12 @@ def plot_examples_nd(
         for j in range(nd):
             if i == j:
                 # Set the x labels in the diagonal plots
-                xycoord = (xmaxs[i] + xmins[i]) / 2
+                xycoord = (xmaxs.iloc[i] + xmins.iloc[i]) / 2
                 g.axes[i, i].text(
                     xycoord, xycoord, f"$x{i}$", fontsize=20, ha="center", va="center"
                 )
             else:
                 # Set appropriate plot intervals and aspect ratio
-                g.axes[i, j].set_xlim([xmins[j], xmaxs[j]])
-                g.axes[i, j].set_ylim([xmins[i], xmaxs[i]])
+                g.axes[i, j].set_xlim([xmins.iloc[j], xmaxs.iloc[j]])
+                g.axes[i, j].set_ylim([xmins.iloc[i], xmaxs.iloc[i]])
                 g.axes[i, j].set_aspect(1)

generated/gallery/plot_functions.py.md5

@@ -1 +1 @@
-d3e68d11254136306e38f7585208145e
+701e8cef4cfc183879b45c1ea33c0780