From 9d2096be500383de31098ae20265841ce1ab454f Mon Sep 17 00:00:00 2001
From: Raphael Vallat <raphaelvallat9@gmail.com>
Date: Wed, 14 Aug 2019 10:26:34 -0700
Subject: [PATCH] Fixed space/tabs in docstring

---
 html/hypno.html | 35 ++++++++++++++++-------------------
 yasa/hypno.py   | 10 +++++-----
 2 files changed, 21 insertions(+), 24 deletions(-)

diff --git a/html/hypno.html b/html/hypno.html
index 1a504e4..79b9808 100644
--- a/html/hypno.html
+++ b/html/hypno.html
@@ -137,15 +137,15 @@ <h1 class="title">Module <code>yasa.hypno</code></h1>
     Parameters
     ----------
     hypno : array_like
-      The sleep staging (hypnogram) 1D array.
+        The sleep staging (hypnogram) 1D array.
     mapping_dict : dict
-      The mapping dictionnary. Note that this function is
-      essentially a wrapper around `pandas.Series.map`.
+        The mapping dictionnary. Note that this function is
+        essentially a wrapper around `pandas.Series.map`.
 
     Returns
     --------
     hypno : array_like
-      The corresponding integer hypnogram.
+        The corresponding integer hypnogram.
     &#34;&#34;&#34;
     assert isinstance(hypno, (list, np.ndarray, pd.Series)), &#39;Not an array.&#39;
     hypno = pd.Series(np.asarray(hypno, dtype=int))
@@ -265,7 +265,7 @@ <h1 class="title">Module <code>yasa.hypno</code></h1>
     -------
     hypno : array_like
         The hypnogram, upsampled to ``sf_data`` and cropped/padded to
-        ``data.size``.
+        ``max(data.shape)``.
     &#34;&#34;&#34;
     if isinstance(data, mne.io.BaseRaw):
         sf_data = data.info[&#39;sfreq&#39;]
@@ -291,19 +291,16 @@ <h2 class="section-title" id="header-functions">Functions</h2>
 <h2 id="parameters">Parameters</h2>
 <dl>
 <dt><strong><code>hypno</code></strong> :&ensp;<code>array_like</code></dt>
-<dd>&nbsp;</dd>
-<dt>The sleep staging (hypnogram) 1D array.</dt>
+<dd>The sleep staging (hypnogram) 1D array.</dd>
 <dt><strong><code>mapping_dict</code></strong> :&ensp;<code>dict</code></dt>
-<dd>&nbsp;</dd>
+<dd>The mapping dictionnary. Note that this function is
+essentially a wrapper around <code>pandas.Series.map</code>.</dd>
 </dl>
-<p>The mapping dictionnary. Note that this function is
-essentially a wrapper around <code>pandas.Series.map</code>.</p>
 <h2 id="returns">Returns</h2>
 <dl>
 <dt><strong><code>hypno</code></strong> :&ensp;<code>array_like</code></dt>
-<dd>&nbsp;</dd>
-</dl>
-<p>The corresponding integer hypnogram.</p></section>
+<dd>The corresponding integer hypnogram.</dd>
+</dl></section>
 <details class="source">
 <summary>Source code</summary>
 <pre><code class="python">def hypno_int_to_str(hypno, mapping_dict={0: &#39;W&#39;, 1: &#39;N1&#39;, 2: &#39;N2&#39;, 3: &#39;N3&#39;,
@@ -315,15 +312,15 @@ <h2 id="returns">Returns</h2>
     Parameters
     ----------
     hypno : array_like
-      The sleep staging (hypnogram) 1D array.
+        The sleep staging (hypnogram) 1D array.
     mapping_dict : dict
-      The mapping dictionnary. Note that this function is
-      essentially a wrapper around `pandas.Series.map`.
+        The mapping dictionnary. Note that this function is
+        essentially a wrapper around `pandas.Series.map`.
 
     Returns
     --------
     hypno : array_like
-      The corresponding integer hypnogram.
+        The corresponding integer hypnogram.
     &#34;&#34;&#34;
     assert isinstance(hypno, (list, np.ndarray, pd.Series)), &#39;Not an array.&#39;
     hypno = pd.Series(np.asarray(hypno, dtype=int))
@@ -403,7 +400,7 @@ <h2 id="returns">Returns</h2>
 <dl>
 <dt><strong><code>hypno</code></strong> :&ensp;<code>array_like</code></dt>
 <dd>The hypnogram, upsampled to <code>sf_data</code> and cropped/padded to
-<code>data.size</code>.</dd>
+<code>max(data.shape)</code>.</dd>
 </dl></section>
 <details class="source">
 <summary>Source code</summary>
@@ -431,7 +428,7 @@ <h2 id="returns">Returns</h2>
     -------
     hypno : array_like
         The hypnogram, upsampled to ``sf_data`` and cropped/padded to
-        ``data.size``.
+        ``max(data.shape)``.
     &#34;&#34;&#34;
     if isinstance(data, mne.io.BaseRaw):
         sf_data = data.info[&#39;sfreq&#39;]
diff --git a/yasa/hypno.py b/yasa/hypno.py
index 1ae0eca..2a62823 100644
--- a/yasa/hypno.py
+++ b/yasa/hypno.py
@@ -74,15 +74,15 @@ def hypno_int_to_str(hypno, mapping_dict={0: 'W', 1: 'N1', 2: 'N2', 3: 'N3',
     Parameters
     ----------
     hypno : array_like
-      The sleep staging (hypnogram) 1D array.
+        The sleep staging (hypnogram) 1D array.
     mapping_dict : dict
-      The mapping dictionnary. Note that this function is
-      essentially a wrapper around `pandas.Series.map`.
+        The mapping dictionnary. Note that this function is
+        essentially a wrapper around `pandas.Series.map`.
 
     Returns
     --------
     hypno : array_like
-      The corresponding integer hypnogram.
+        The corresponding integer hypnogram.
     """
     assert isinstance(hypno, (list, np.ndarray, pd.Series)), 'Not an array.'
     hypno = pd.Series(np.asarray(hypno, dtype=int))
@@ -202,7 +202,7 @@ def hypno_upsample_to_data(hypno, sf_hypno, data, sf_data=None):
     -------
     hypno : array_like
         The hypnogram, upsampled to ``sf_data`` and cropped/padded to
-        ``data.size``.
+        ``max(data.shape)``.
     """
     if isinstance(data, mne.io.BaseRaw):
         sf_data = data.info['sfreq']