Doc updates

README.md

@@ -1,4 +1,3 @@
-
 [![](https://img.shields.io/badge/docs-quarto-blue.svg?logo=data:image/png;base64,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)](https://peekxc.github.io/primate/)
 [![build_macos](https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_macos.yml?logo=apple&logoColor=white)](https://github.com/peekxc/primate/actions/workflows/build_macos.yml) 
 [![build_windows](https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_windows.yml?logo=windows&logoColor=white)](https://github.com/peekxc/primate/actions/workflows/build_windows.yml) 

docs/basic/install.html

@@ -350,8 +350,22 @@ <h1 class="title">Installation</h1>
 
 
 <p><code>primate</code> is a standard <a href="https://peps.python.org/pep-0517/">PEP-517</a> package, and thus can be installed via <code>pip</code>:</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>pip install <span class="op">&lt;</span> primate source directory <span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>Currently the package must be built from source via cloning the repository. PYPI support is planned.</p>
+<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>python <span class="op">-</span>m pip install scikit<span class="op">-</span>primate  </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>Assuming your platform is natively supported, no compilation is needed; see <a href="#platform-support">platform support</a> for details.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Like many packages registered on PyPI, the distribution name “<code>scikit-primate</code>” differs from the importable package name “<code>primate</code>” (also see <a href="https://github.com/pypi/support/issues/3471">#3471</a>). Once installed, all exported package modules are available through the <code>primate</code> module.</p>
+</div>
+</div>
+<!-- Currently the package must be built from source via cloning the repository. PYPI support is planned.  -->
 <!-- https://stackoverflow.com/questions/122906s39/quantifiable-metrics-benchmarks-on-the-usage-of-header-only-c-libraries/13593041#13593041 -->
 <section id="platform-support" class="level3">
 <h3 class="anchored" data-anchor-id="platform-support">Platform support</h3>

docs/basic/performance.html

@@ -342,7 +342,7 @@ <h1 class="title">Performance</h1>
 <p><code>primate</code> provides a variety of efficient algorithms for estimating quantities derived from matrix functions. These algorithms are largely implemented in C++ to minimize overhead, and for some computational problems <code>primate</code> can out-perform the standard algorithms for estimating spectral quantities by several orders of magnitude. Nonetheless, there are some performance-related caveats to be aware of.</p>
 <!-- The main  -->
 <!-- To illustrate this, we give an example below using Toeplitz matrices.   -->
-<div id="a4792004" class="cell" data-execution_count="1">
+<div id="edff6716" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> scipy.linalg <span class="im">import</span> toeplitz</span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> primate.trace <span class="im">import</span> hutch </span>
 <span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
@@ -386,7 +386,7 @@ <h1 class="title">Performance</h1>
 <span id="cb1-41"><a href="#cb1-41" aria-hidden="true" tabindex="-1"></a>a, b <span class="op">=</span> lanczos(T, deg<span class="op">=</span><span class="dv">499</span>, orth<span class="op">=</span><span class="dv">150</span>)</span>
 <span id="cb1-42"><a href="#cb1-42" aria-hidden="true" tabindex="-1"></a>np.<span class="bu">sum</span>(np.<span class="bu">abs</span>(eigvalsh_tridiagonal(a,b)))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div id="e2cabf3d" class="cell" data-execution_count="2">
+<div id="43019448" class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> timeit </span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a>timeit.timeit(<span class="kw">lambda</span>: hutch(A, maxiter<span class="op">=</span><span class="dv">20</span>, deg<span class="op">=</span><span class="dv">5</span>, fun<span class="op">=</span><span class="st">"log"</span>, quad<span class="op">=</span><span class="st">"fttr"</span>), number <span class="op">=</span> <span class="dv">1000</span>)</span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>timeit.timeit(<span class="kw">lambda</span>: np.<span class="bu">sum</span>(np.log(np.linalg.eigvalsh(A))), number <span class="op">=</span> <span class="dv">1000</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>

docs/basic/todo.html

@@ -323,7 +323,7 @@
 
 
 
-<div id="690056ed" class="cell" data-execution_count="1">
+<div id="76c9f600" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># a, b = 0.8, 2</span></span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="co"># x = np.random.uniform(low=0, high=10, size=40)</span></span>
 <span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="co"># eps = np.random.normal(loc=0, scale=1.0, size=40)</span></span>

docs/index.html

@@ -322,7 +322,7 @@ <h1 class="title">Package overview</h1>
 </header>
 
 
-<p><a href="https://peekxc.github.io/primate/"><img src="https://img.shields.io/badge/docs-quarto-blue.svg?logo=data:image/png;base64,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.png" class="img-fluid"></a> <!-- [![coverage_badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/peekxc/ef42349965f40edf4232737026690c5f/raw/coverage_info.json)](https://coveralls.io/github/peekxc/simplextree-py)  --> <a href="https://github.com/peekxc/primate/actions/workflows/build_macos.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_macos.yml?logo=apple&amp;logoColor=white" class="img-fluid" alt="build_macos"></a> <a href="https://github.com/peekxc/primate/actions/workflows/build_windows.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_windows.yml?logo=windows&amp;logoColor=white" class="img-fluid" alt="build_windows"></a> <a href="https://github.com/peekxc/primate/actions/workflows/build_linux.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_linux.yml?logo=linux&amp;logoColor=white" class="img-fluid" alt="build_linux"></a> <!-- [![PyPI Version](https://img.shields.io/pypi/v/simplextree)](https://pypi.org/project/simplextree) --> <a href="https://github.com/peekxc/primate/actions"><img src="https://img.shields.io/badge/python-%E2%89%A5%203.8-blue.svg" class="img-fluid" alt="Python versions"></a></p>
+<p><a href="https://peekxc.github.io/primate/"><img src="https://img.shields.io/badge/docs-quarto-blue.svg?logo=data:image/png;base64,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.png" class="img-fluid"></a> <a href="https://github.com/peekxc/primate/actions/workflows/build_macos.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_macos.yml?logo=apple&amp;logoColor=white" class="img-fluid" alt="build_macos"></a> <a href="https://github.com/peekxc/primate/actions/workflows/build_windows.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_windows.yml?logo=windows&amp;logoColor=white" class="img-fluid" alt="build_windows"></a> <a href="https://github.com/peekxc/primate/actions/workflows/build_linux.yml"><img src="https://img.shields.io/github/actions/workflow/status/peekxc/primate/build_linux.yml?logo=linux&amp;logoColor=white" class="img-fluid" alt="build_linux"></a> <a href="https://github.com/peekxc/primate/actions"><img src="https://img.shields.io/badge/python-%E2%89%A5%203.8-blue.svg" class="img-fluid" alt="Python versions"></a> <!-- [![coverage_badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/peekxc/ef42349965f40edf4232737026690c5f/raw/coverage_info.json)](https://coveralls.io/github/peekxc/simplextree-py)  --> <!-- [![PyPI Version](https://img.shields.io/pypi/v/simplextree)](https://pypi.org/project/simplextree) --></p>
 <p><code>primate</code>, short for <strong>Pr</strong>obabalistic <strong>I</strong>mplicit <strong>Ma</strong>trix <strong>T</strong>race <strong>E</strong>stimator, is a Python package that provides estimators of quantities derived from <a href="https://en.wikipedia.org/wiki/Analytic_function_of_a_matrix">matrix functions</a>; that is, matrices parameterized by functions:</p>
 <p><span class="math display"> f(A) \triangleq U f(\Lambda) U^{\intercal}, \quad \quad f : [a,b] \to \mathbb{R}</span></p>
 <p>Estimator approximations are obtained via the <em>Lanczos</em><a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> and <em>stochastic Lanczos quadrature</em><a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a> methods, which are well-suited for sparse or structured operators supporting fast <span class="math inline">v \mapsto Av</span> actions.</p>