improved: headings in docs

PhenoAI · Nov 12, 2024 · 001d8c6 · 001d8c6
1 parent e776d8b
commit 001d8c6
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Showing 5 changed files with 37 additions and 6 deletions.
diff --git a/nbs/06_sleep_plots.ipynb b/nbs/06_sleep_plots.ipynb
@@ -303,6 +303,13 @@
     "    "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to plot sleep events and channels"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/nbs/15_timeseries_plots.ipynb b/nbs/15_timeseries_plots.ipynb
@@ -452,7 +452,7 @@
     "\n",
     "\n",
     "def format_xticks(ax: plt.Axes, xticks: Iterable=None, format: str=TIME_FORMAT, **kwargs):\n",
-    "    \"\"\" format datestrings on x axis \"\"\"\n",
+    "    \"\"\" Format datestrings on x axis \"\"\"\n",
     "    if xticks is None:\n",
     "        xticks = ax.get_xticks()\n",
     "    ax.set_xticks(xticks)\n",
@@ -484,6 +484,7 @@
     "        unique (bool): Whether to remove duplicate rows.\n",
     "\n",
     "    Returns:\n",
+    "\n",
     "        pd.DataFrame: The filtered DataFrame\n",
     "    \"\"\"\n",
     "    if participant_id is not None:\n",
@@ -837,6 +838,13 @@
     "    return colors"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to plot time series"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/nbs/16_diet_plots.ipynb b/nbs/16_diet_plots.ipynb
@@ -217,7 +217,7 @@
     "\n",
     "    Returns:\n",
     "\n",
-    "        None: The function creates a lollipop plot with pie charts on the specified or newly created axis.\n",
+    "        plt.Axes: The Matplotlib axis on which the chart was plotted.\n",
     "    \"\"\"\n",
     "    # Prepare the data for plotting\n",
     "    df, grouped_nutrients = prepare_meals(\n",
@@ -514,6 +514,10 @@
     "        alpha (float): The transparency of the bars. Default is 0.7.\n",
     "        ax (Optional[plt.Axes]): The Matplotlib axis on which to plot the lollipop chart. If None, a new axis is created. Default is None.\n",
     "        figsize (Tuple[float, float]): The size of the figure to create. Default is (12, 6).\n",
+    "\n",
+    "    Returns:\n",
+    "\n",
+    "        plt.Axes: The Matplotlib axis on which the chart was plotted.\n",
     "    \"\"\"\n",
     "    diet_log = format_timeseries(\n",
     "        diet_log, participant_id, array_index,\n",
@@ -636,7 +640,7 @@
     "\n",
     "    Returns:\n",
     "\n",
-    "        TimeSeriesFigure: Plot.\n",
+    "        TimeSeriesFigure: The figure object containing the plots.\n",
     "    \"\"\"\n",
     "    g = TimeSeriesFigure(figsize=figsize)\n",
     "\n",
@@ -695,6 +699,13 @@
     "    return g"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to plot diet logs"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/pheno_utils/diet_plots.py b/pheno_utils/diet_plots.py
@@ -179,7 +179,7 @@ def plot_nutrient_lollipop(
 
     Returns:
 
-        None: The function creates a lollipop plot with pie charts on the specified or newly created axis.
+        plt.Axes: The Matplotlib axis on which the chart was plotted.
     """
     # Prepare the data for plotting
     df, grouped_nutrients = prepare_meals(
@@ -470,6 +470,10 @@ def plot_meals_hbars(
         alpha (float): The transparency of the bars. Default is 0.7.
         ax (Optional[plt.Axes]): The Matplotlib axis on which to plot the lollipop chart. If None, a new axis is created. Default is None.
         figsize (Tuple[float, float]): The size of the figure to create. Default is (12, 6).
+
+    Returns:
+
+        plt.Axes: The Matplotlib axis on which the chart was plotted.
     """
     diet_log = format_timeseries(
         diet_log, participant_id, array_index,
@@ -585,7 +589,7 @@ def plot_diet_cgm_sleep(
 
     Returns:
 
-        TimeSeriesFigure: Plot.
+        TimeSeriesFigure: The figure object containing the plots.
     """
     g = TimeSeriesFigure(figsize=figsize)
 

diff --git a/pheno_utils/timeseries_plots.py b/pheno_utils/timeseries_plots.py
@@ -413,7 +413,7 @@ def show(self) -> None:
 
 
 def format_xticks(ax: plt.Axes, xticks: Iterable=None, format: str=TIME_FORMAT, **kwargs):
-    """ format datestrings on x axis """
+    """ Format datestrings on x axis """
     if xticks is None:
         xticks = ax.get_xticks()
     ax.set_xticks(xticks)
@@ -445,6 +445,7 @@ def format_timeseries(
         unique (bool): Whether to remove duplicate rows.
 
     Returns:
+
         pd.DataFrame: The filtered DataFrame
     """
     if participant_id is not None: