deploy: e790f98

pyapi/grid.cubic.html

@@ -366,13 +366,14 @@
 <dl class="py method">
 <dt class="sig sig-object py" id="grid.cubic.Tensor1DGrids.interpolate">
 <span class="sig-name descname"><span class="pre">interpolate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">points</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">values</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_log</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_x</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_y</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_z</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cubic'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#grid.cubic.Tensor1DGrids.interpolate" title="Permalink to this definition"></a></dt>
-<dd><p>Interpolate function value at a given point.</p>
+<dd><p>Interpolate function and its derivatives on cubic grid.</p>
 <p>Only implemented in three-dimensions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>points</strong> (<em>np.ndarray</em><em>, </em><em>shape</em><em> (</em><em>M</em><em>, </em><em>3</em><em>)</em>) – The 3D Cartesian coordinates of <span class="math notranslate nohighlight">\(M\)</span> points in <span class="math notranslate nohighlight">\(\mathbb{R}^3\)</span> for which
-the interpolant (i.e., the interpolated function) is evaluated.</p></li>
+the interpolant (i.e., the interpolated function) is evaluated. If
+method=”cubic”, then M must be equal to one.</p></li>
 <li><p><strong>values</strong> (<em>np.ndarray</em><em>, </em><em>shape</em><em> (</em><em>N</em><em>,</em><em>)</em>) – Function values at each of the <span class="math notranslate nohighlight">\(N\)</span> grid points.</p></li>
 <li><p><strong>use_log</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, the logarithm of the function values are interpolated.
 Can only be used for interpolating derivatives when the derivative is not a
@@ -838,13 +839,14 @@
 <dl class="py method">
 <dt class="sig sig-object py" id="grid.cubic.UniformGrid.interpolate">
 <span class="sig-name descname"><span class="pre">interpolate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">points</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">values</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_log</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_x</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_y</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nu_z</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cubic'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#grid.cubic.UniformGrid.interpolate" title="Permalink to this definition"></a></dt>
-<dd><p>Interpolate function value at a given point.</p>
+<dd><p>Interpolate function and its derivatives on cubic grid.</p>
 <p>Only implemented in three-dimensions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>points</strong> (<em>np.ndarray</em><em>, </em><em>shape</em><em> (</em><em>M</em><em>, </em><em>3</em><em>)</em>) – The 3D Cartesian coordinates of <span class="math notranslate nohighlight">\(M\)</span> points in <span class="math notranslate nohighlight">\(\mathbb{R}^3\)</span> for which
-the interpolant (i.e., the interpolated function) is evaluated.</p></li>
+the interpolant (i.e., the interpolated function) is evaluated. If
+method=”cubic”, then M must be equal to one.</p></li>
 <li><p><strong>values</strong> (<em>np.ndarray</em><em>, </em><em>shape</em><em> (</em><em>N</em><em>,</em><em>)</em>) – Function values at each of the <span class="math notranslate nohighlight">\(N\)</span> grid points.</p></li>
 <li><p><strong>use_log</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, the logarithm of the function values are interpolated.
 Can only be used for interpolating derivatives when the derivative is not a

pyapi/grid.utils.html

@@ -482,9 +482,9 @@
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p>Value of real spherical harmonics of all orders <span class="math notranslate nohighlight">\(m\)</span>,and degree
-<span class="math notranslate nohighlight">\(l\)</span> spherical harmonics. For each degree, the zeroth order
-is stored, followed by positive orders then negative orders,ordered as:
-<span class="math notranslate nohighlight">\((-l, -l + 1, \cdots -1)\)</span>.</p>
+<span class="math notranslate nohighlight">\(l\)</span> spherical harmonics. For each degree <span class="math notranslate nohighlight">\(l\)</span>,
+the orders <span class="math notranslate nohighlight">\(m\)</span> are in Horton 2 order, i.e.
+<span class="math notranslate nohighlight">\(m=0, 1, -1, 2, -2, \cdots, l, -l\)</span>.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p>ndarray((l_max + 1)**2, N)</p>
@@ -496,6 +496,11 @@
 To obtain specific degrees, e.g. l=2
 &gt;&gt;&gt; desired_degree = 2
 &gt;&gt;&gt; spherical_harmonic[(desired_degree)**2: (desired_degree + 1)**2, :]</p>
+<p class="rubric">Notes</p>
+<ul class="simple">
+<li><p>SciPy spherical harmonics is known (Jan 30, 2024) to give nans when the degree is large,
+for our experience, when l &gt;= 86</p></li>
+</ul>
 </dd></dl>
 
 <dl class="py function">