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Bears-R-Us · Oct 17, 2024 · 2e1bbf5 · 2e1bbf5
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diff --git a/_modules/arkouda/sparrayclass.html b/_modules/arkouda/sparrayclass.html
@@ -354,7 +354,7 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
 <span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
 
 <span class="kn">import</span> <span class="nn">builtins</span>
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Sequence</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">cast</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Sequence</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">cast</span>
 
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">typeguard</span> <span class="kn">import</span> <span class="n">typechecked</span>
@@ -391,6 +391,8 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
 <span class="sd">        The element type of the array</span>
 <span class="sd">    size : int_scalars</span>
 <span class="sd">        The size of any one dimension of the array (all dimensions are assumed to be equal sized for now)</span>
+<span class="sd">    nnz: int_scalars</span>
+<span class="sd">        The number of non-zero elements in the array</span>
 <span class="sd">    ndim : int_scalars</span>
 <span class="sd">        The rank of the array (currently only rank 2 arrays supported)</span>
 <span class="sd">    shape : Sequence[int]</span>
@@ -426,7 +428,7 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
 
     <span class="k">def</span> <span class="fm">__del__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="k">try</span><span class="p">:</span>
-            <span class="n">logger</span><span class="o">.</span><span class="n">debug</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;deleting pdarray with name </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+            <span class="n">logger</span><span class="o">.</span><span class="n">debug</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;deleting sparray with name </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
             <span class="n">generic_msg</span><span class="p">(</span><span class="n">cmd</span><span class="o">=</span><span class="s2">&quot;delete&quot;</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">})</span>
         <span class="k">except</span> <span class="p">(</span><span class="ne">RuntimeError</span><span class="p">,</span> <span class="ne">AttributeError</span><span class="p">):</span>
             <span class="k">pass</span>
@@ -445,7 +447,7 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span>
         <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">&quot;sparray does not support __getitem__&quot;</span><span class="p">)</span>
 
-    <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>  <span class="c1"># This won&#39;t work out of the box for sparrays need to add this in later</span>
+    <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="kn">from</span> <span class="nn">arkouda.client</span> <span class="kn">import</span> <span class="n">sparrayIterThresh</span>
 
         <span class="k">return</span> <span class="n">generic_msg</span><span class="p">(</span><span class="n">cmd</span><span class="o">=</span><span class="s2">&quot;str&quot;</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;array&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="p">,</span> <span class="s2">&quot;printThresh&quot;</span><span class="p">:</span> <span class="n">sparrayIterThresh</span><span class="p">})</span>
@@ -473,7 +475,7 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="sparray.to_pdarray">
 <a class="viewcode-back" href="../../autoapi/arkouda/sparrayclass/index.html#arkouda.sparray.to_pdarray">[docs]</a>
     <span class="nd">@typechecked</span>
-    <span class="k">def</span> <span class="nf">to_pdarray</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">to_pdarray</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">List</span><span class="p">[</span><span class="n">pdarray</span><span class="p">]:</span>
         <span class="n">dtype</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span>
         <span class="n">dtype_name</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">dtype</span><span class="p">)</span><span class="o">.</span><span class="n">name</span>
         <span class="c1"># check dtype for error</span>
@@ -499,7 +501,7 @@ <h1>Source code for arkouda.sparrayclass</h1><div class="highlight"><pre>
 
         <span class="n">generic_msg</span><span class="p">(</span>
             <span class="n">cmd</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;fill_sparse_vals&lt;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">,2,</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="si">}</span><span class="s2">,</span><span class="si">{</span><span class="n">a</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">,1&gt;&quot;</span><span class="p">,</span>
-            <span class="n">args</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;matrix&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="p">,</span> <span class="s2">&quot;vals&quot;</span><span class="p">:</span> <span class="n">a</span><span class="p">}</span>
+            <span class="n">args</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;matrix&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="p">,</span> <span class="s2">&quot;vals&quot;</span><span class="p">:</span> <span class="n">a</span><span class="p">},</span>
         <span class="p">)</span></div>
 </div>
 

diff --git a/_modules/arkouda/sparsematrix.html b/_modules/arkouda/sparsematrix.html
@@ -353,16 +353,20 @@
           <h1>Source code for arkouda.sparsematrix</h1><div class="highlight"><pre>
 <span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
 
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span><span class="p">,</span> <span class="n">cast</span>
+
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">typeguard</span> <span class="kn">import</span> <span class="n">typechecked</span>
 
 <span class="kn">from</span> <span class="nn">arkouda.client</span> <span class="kn">import</span> <span class="n">generic_msg</span>
+<span class="kn">from</span> <span class="nn">arkouda.dtypes</span> <span class="kn">import</span> <span class="n">dtype</span> <span class="k">as</span> <span class="n">akdtype</span>
+<span class="kn">from</span> <span class="nn">arkouda.dtypes</span> <span class="kn">import</span> <span class="n">int64</span>
 <span class="kn">from</span> <span class="nn">arkouda.logger</span> <span class="kn">import</span> <span class="n">getArkoudaLogger</span>
+<span class="kn">from</span> <span class="nn">arkouda.numpy.dtypes.dtypes</span> <span class="kn">import</span> <span class="n">NumericDTypes</span>
+<span class="kn">from</span> <span class="nn">arkouda.pdarrayclass</span> <span class="kn">import</span> <span class="n">pdarray</span>
 <span class="kn">from</span> <span class="nn">arkouda.sparrayclass</span> <span class="kn">import</span> <span class="n">create_sparray</span><span class="p">,</span> <span class="n">sparray</span>
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span>
-<span class="kn">from</span> <span class="nn">arkouda.dtypes</span> <span class="kn">import</span> <span class="n">int64</span>
-<span class="kn">from</span> <span class="nn">arkouda.dtypes</span> <span class="kn">import</span> <span class="n">dtype</span> <span class="k">as</span> <span class="n">akdtype</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;random_sparse_matrix&quot;</span><span class="p">,</span> <span class="s2">&quot;sparse_matrix_matrix_mult&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;random_sparse_matrix&quot;</span><span class="p">,</span> <span class="s2">&quot;sparse_matrix_matrix_mult&quot;</span><span class="p">,</span> <span class="s2">&quot;create_sparse_matrix&quot;</span><span class="p">]</span>
 
 <span class="n">logger</span> <span class="o">=</span> <span class="n">getArkoudaLogger</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;sparsematrix&quot;</span><span class="p">)</span>
 
@@ -447,6 +451,53 @@ <h1>Source code for arkouda.sparsematrix</h1><div class="highlight"><pre>
 
     <span class="k">return</span> <span class="n">create_sparray</span><span class="p">(</span><span class="n">repMsg</span><span class="p">)</span></div>
 
+
+
+<div class="viewcode-block" id="create_sparse_matrix">
+<a class="viewcode-back" href="../../autoapi/arkouda/sparsematrix/index.html#arkouda.sparsematrix.create_sparse_matrix">[docs]</a>
+<span class="k">def</span> <span class="nf">create_sparse_matrix</span><span class="p">(</span><span class="n">size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">rows</span><span class="p">:</span> <span class="n">pdarray</span><span class="p">,</span> <span class="n">cols</span><span class="p">:</span> <span class="n">pdarray</span><span class="p">,</span> <span class="n">vals</span><span class="p">:</span> <span class="n">pdarray</span><span class="p">,</span> <span class="n">layout</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">sparray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Create a sparse matrix from three pdarrays representing the row indices,</span>
+<span class="sd">    column indices, and values of the non-zero elements of the matrix.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    rows : pdarray</span>
+<span class="sd">        The row indices of the non-zero elements</span>
+<span class="sd">    cols : pdarray</span>
+<span class="sd">        The column indices of the non-zero elements</span>
+<span class="sd">    vals : pdarray</span>
+<span class="sd">        The values of the non-zero elements</span>
+
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    sparray</span>
+<span class="sd">        A sparse matrix with the specified row and column indices and values</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">pdarray</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">cols</span><span class="p">,</span> <span class="n">pdarray</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">vals</span><span class="p">,</span> <span class="n">pdarray</span><span class="p">)):</span>
+        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;rows, cols, and vals must be pdarrays for create_sparse_matrix&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">rows</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">1</span> <span class="ow">and</span> <span class="n">cols</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">1</span> <span class="ow">and</span> <span class="n">vals</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">1</span><span class="p">):</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;rows, cols, and vals must be 1D for create_sparse_matrix&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">rows</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="n">cols</span><span class="o">.</span><span class="n">size</span> <span class="ow">and</span> <span class="n">rows</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="n">vals</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;rows, cols, and vals must have the same size for create_sparse_matrix&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">rows</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="n">int64</span> <span class="ow">and</span> <span class="n">cols</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="n">int64</span><span class="p">):</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;rows and cols must have dtype int64 for create_sparse_matrix&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">layout</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;CSR&quot;</span><span class="p">,</span> <span class="s2">&quot;CSC&quot;</span><span class="p">]:</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;layout must be &#39;CSR&#39; or &#39;CSC&#39;&quot;</span><span class="p">)</span>
+
+    <span class="n">vals_dtype_name</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">vals</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span><span class="o">.</span><span class="n">name</span>
+    <span class="c1"># check dtype for error</span>
+    <span class="k">if</span> <span class="n">vals_dtype_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">NumericDTypes</span><span class="p">:</span>
+        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;unsupported dtype </span><span class="si">{</span><span class="n">vals</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+
+    <span class="n">shape</span> <span class="o">=</span> <span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">size</span><span class="p">)</span>
+    <span class="n">repMsg</span> <span class="o">=</span> <span class="n">generic_msg</span><span class="p">(</span>
+        <span class="n">cmd</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;sparse_matrix_from_pdarrays&lt;</span><span class="si">{</span><span class="n">vals</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">,</span><span class="si">{</span><span class="n">layout</span><span class="si">}</span><span class="s2">&gt;&quot;</span><span class="p">,</span>
+        <span class="n">args</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;rows&quot;</span><span class="p">:</span> <span class="n">rows</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="s2">&quot;cols&quot;</span><span class="p">:</span> <span class="n">cols</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="s2">&quot;vals&quot;</span><span class="p">:</span> <span class="n">vals</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="s2">&quot;shape&quot;</span><span class="p">:</span> <span class="n">shape</span><span class="p">},</span>
+    <span class="p">)</span>
+
+    <span class="k">return</span> <span class="n">create_sparray</span><span class="p">(</span><span class="n">repMsg</span><span class="p">)</span></div>
+
 </pre></div>
         </article>
       </div>

diff --git a/_sources/autoapi/arkouda/index.rst.txt b/_sources/autoapi/arkouda/index.rst.txt
@@ -45837,6 +45837,12 @@ Package Contents
 
       :type: int_scalars
 
+   .. attribute:: nnz
+
+      The number of non-zero elements in the array
+
+      :type: int_scalars
+
    .. attribute:: ndim
 
       The rank of the array (currently only rank 2 arrays supported)
@@ -45889,7 +45895,7 @@ Package Contents
    .. py:attribute:: size
 
 
-   .. py:method:: to_pdarray()
+   .. py:method:: to_pdarray() -> List[arkouda.pdarrayclass.pdarray]
 
 
 .. py:function:: sqrt(pda: pdarray, where: Union[bool, pdarray] = True) -> pdarray

diff --git a/_sources/autoapi/arkouda/sparrayclass/index.rst.txt b/_sources/autoapi/arkouda/sparrayclass/index.rst.txt
@@ -68,6 +68,12 @@ Module Contents
 
       :type: int_scalars
 
+   .. attribute:: nnz
+
+      The number of non-zero elements in the array
+
+      :type: int_scalars
+
    .. attribute:: ndim
 
       The rank of the array (currently only rank 2 arrays supported)
@@ -120,6 +126,6 @@ Module Contents
    .. py:attribute:: size
 
 
-   .. py:method:: to_pdarray()
+   .. py:method:: to_pdarray() -> List[arkouda.pdarrayclass.pdarray]