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4 changes: 2 additions & 2 deletions docs/pynkowski.html
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<p>A Python package to compute Minkowski Functionals and other higher order statistics of input fields, as well as their expected values for different kinds of fields.</p>

<p>The statistics currently supported by this package are:</p>
<p>The <strong>statistics</strong> currently supported by this package are:</p>

<ul>
<li>Minkowski functionals.</li>
Expand Down Expand Up @@ -182,7 +182,7 @@ <h1 id="authors">Authors</h1>
</span><span id="L-2"><a href="#L-2"><span class="linenos"> 2</span></a>
</span><span id="L-3"><a href="#L-3"><span class="linenos"> 3</span></a><span class="sd">A Python package to compute Minkowski Functionals and other higher order statistics of input fields, as well as their expected values for different kinds of fields.</span>
</span><span id="L-4"><a href="#L-4"><span class="linenos"> 4</span></a>
</span><span id="L-5"><a href="#L-5"><span class="linenos"> 5</span></a><span class="sd">The statistics currently supported by this package are:</span>
</span><span id="L-5"><a href="#L-5"><span class="linenos"> 5</span></a><span class="sd">The **statistics** currently supported by this package are:</span>
</span><span id="L-6"><a href="#L-6"><span class="linenos"> 6</span></a>
</span><span id="L-7"><a href="#L-7"><span class="linenos"> 7</span></a><span class="sd">- Minkowski functionals.</span>
</span><span id="L-8"><a href="#L-8"><span class="linenos"> 8</span></a><span class="sd">- Maxima and minima distributions.</span>
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2 changes: 1 addition & 1 deletion docs/pynkowski/__version.html
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<label class="view-source-button" for="mod-__version-view-source"><span>View Source</span></label>

<div class="pdoc-code codehilite"><pre><span></span><span id="L-1"><a href="#L-1"><span class="linenos">1</span></a><span class="n">__version__</span><span class="o">=</span><span class="s1">&#39;1.1.0&#39;</span>
<div class="pdoc-code codehilite"><pre><span></span><span id="L-1"><a href="#L-1"><span class="linenos">1</span></a><span class="n">__version__</span><span class="o">=</span><span class="s1">&#39;1.1.1&#39;</span>
</span><span id="L-2"><a href="#L-2"><span class="linenos">2</span></a>
</span></pre></div>

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30 changes: 15 additions & 15 deletions docs/pynkowski/data/array.html
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Expand Up @@ -142,12 +142,12 @@ <h1 class="modulename">
</span><span id="L-42"><a href="#L-42"><span class="linenos"> 42</span></a> <span class="k">return</span><span class="p">(</span><span class="n">pixels</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span>
</span><span id="L-43"><a href="#L-43"><span class="linenos"> 43</span></a>
</span><span id="L-44"><a href="#L-44"><span class="linenos"> 44</span></a><span class="k">class</span> <span class="nc">DataArray</span><span class="p">(</span><span class="n">DataField</span><span class="p">):</span>
</span><span id="L-45"><a href="#L-45"><span class="linenos"> 45</span></a> <span class="sd">&quot;&quot;&quot;Class for a pixelized Euclidean data cube.</span>
</span><span id="L-45"><a href="#L-45"><span class="linenos"> 45</span></a> <span class="sd">&quot;&quot;&quot;Class for a pixelized Euclidean data array.</span>
</span><span id="L-46"><a href="#L-46"><span class="linenos"> 46</span></a><span class="sd"> </span>
</span><span id="L-47"><a href="#L-47"><span class="linenos"> 47</span></a><span class="sd"> Parameters</span>
</span><span id="L-48"><a href="#L-48"><span class="linenos"> 48</span></a><span class="sd"> ----------</span>
</span><span id="L-49"><a href="#L-49"><span class="linenos"> 49</span></a><span class="sd"> field : np.array</span>
</span><span id="L-50"><a href="#L-50"><span class="linenos"> 50</span></a><span class="sd"> Pixelized field as a 3D array. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see `spacing`).</span>
</span><span id="L-50"><a href="#L-50"><span class="linenos"> 50</span></a><span class="sd"> Pixelized field as an array of arbitrary dimension. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see `spacing`).</span>
</span><span id="L-51"><a href="#L-51"><span class="linenos"> 51</span></a><span class="sd"> The field can have different sizes in each dimension.</span>
</span><span id="L-52"><a href="#L-52"><span class="linenos"> 52</span></a><span class="sd"> </span>
</span><span id="L-53"><a href="#L-53"><span class="linenos"> 53</span></a><span class="sd"> normalise : bool, optional</span>
Expand All @@ -165,13 +165,13 @@ <h1 class="modulename">
</span><span id="L-65"><a href="#L-65"><span class="linenos"> 65</span></a><span class="sd"> Attributes</span>
</span><span id="L-66"><a href="#L-66"><span class="linenos"> 66</span></a><span class="sd"> ----------</span>
</span><span id="L-67"><a href="#L-67"><span class="linenos"> 67</span></a><span class="sd"> field : np.array</span>
</span><span id="L-68"><a href="#L-68"><span class="linenos"> 68</span></a><span class="sd"> Data of the field as a 3D array.</span>
</span><span id="L-68"><a href="#L-68"><span class="linenos"> 68</span></a><span class="sd"> Data of the field as an array.</span>
</span><span id="L-69"><a href="#L-69"><span class="linenos"> 69</span></a><span class="sd"> </span>
</span><span id="L-70"><a href="#L-70"><span class="linenos"> 70</span></a><span class="sd"> dim : int</span>
</span><span id="L-71"><a href="#L-71"><span class="linenos"> 71</span></a><span class="sd"> Dimension of the space where the field is defined. In this case, the space is the 3D space and this is 3.</span>
</span><span id="L-71"><a href="#L-71"><span class="linenos"> 71</span></a><span class="sd"> Dimension of the space where the field is defined. For example, 2 for an image and 3 for a data cube..</span>
</span><span id="L-72"><a href="#L-72"><span class="linenos"> 72</span></a><span class="sd"> </span>
</span><span id="L-73"><a href="#L-73"><span class="linenos"> 73</span></a><span class="sd"> name : str</span>
</span><span id="L-74"><a href="#L-74"><span class="linenos"> 74</span></a><span class="sd"> Name of the field. In this case, &quot;data cube&quot;</span>
</span><span id="L-74"><a href="#L-74"><span class="linenos"> 74</span></a><span class="sd"> Name of the field. In this case, &quot;DataArray&quot;</span>
</span><span id="L-75"><a href="#L-75"><span class="linenos"> 75</span></a><span class="sd"> </span>
</span><span id="L-76"><a href="#L-76"><span class="linenos"> 76</span></a><span class="sd"> first_der : np.array or None</span>
</span><span id="L-77"><a href="#L-77"><span class="linenos"> 77</span></a><span class="sd"> First **covariant** derivatives of the field in an orthonormal basis of the space. Same structure as `field`, and shape `(dim, field.shape)`.</span>
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</div>
<a class="headerlink" href="#DataArray"></a>
<div class="pdoc-code codehilite"><pre><span></span><span id="DataArray-45"><a href="#DataArray-45"><span class="linenos"> 45</span></a><span class="k">class</span> <span class="nc">DataArray</span><span class="p">(</span><span class="n">DataField</span><span class="p">):</span>
</span><span id="DataArray-46"><a href="#DataArray-46"><span class="linenos"> 46</span></a> <span class="sd">&quot;&quot;&quot;Class for a pixelized Euclidean data cube.</span>
</span><span id="DataArray-46"><a href="#DataArray-46"><span class="linenos"> 46</span></a> <span class="sd">&quot;&quot;&quot;Class for a pixelized Euclidean data array.</span>
</span><span id="DataArray-47"><a href="#DataArray-47"><span class="linenos"> 47</span></a><span class="sd"> </span>
</span><span id="DataArray-48"><a href="#DataArray-48"><span class="linenos"> 48</span></a><span class="sd"> Parameters</span>
</span><span id="DataArray-49"><a href="#DataArray-49"><span class="linenos"> 49</span></a><span class="sd"> ----------</span>
</span><span id="DataArray-50"><a href="#DataArray-50"><span class="linenos"> 50</span></a><span class="sd"> field : np.array</span>
</span><span id="DataArray-51"><a href="#DataArray-51"><span class="linenos"> 51</span></a><span class="sd"> Pixelized field as a 3D array. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see `spacing`).</span>
</span><span id="DataArray-51"><a href="#DataArray-51"><span class="linenos"> 51</span></a><span class="sd"> Pixelized field as an array of arbitrary dimension. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see `spacing`).</span>
</span><span id="DataArray-52"><a href="#DataArray-52"><span class="linenos"> 52</span></a><span class="sd"> The field can have different sizes in each dimension.</span>
</span><span id="DataArray-53"><a href="#DataArray-53"><span class="linenos"> 53</span></a><span class="sd"> </span>
</span><span id="DataArray-54"><a href="#DataArray-54"><span class="linenos"> 54</span></a><span class="sd"> normalise : bool, optional</span>
Expand All @@ -308,13 +308,13 @@ <h1 class="modulename">
</span><span id="DataArray-66"><a href="#DataArray-66"><span class="linenos"> 66</span></a><span class="sd"> Attributes</span>
</span><span id="DataArray-67"><a href="#DataArray-67"><span class="linenos"> 67</span></a><span class="sd"> ----------</span>
</span><span id="DataArray-68"><a href="#DataArray-68"><span class="linenos"> 68</span></a><span class="sd"> field : np.array</span>
</span><span id="DataArray-69"><a href="#DataArray-69"><span class="linenos"> 69</span></a><span class="sd"> Data of the field as a 3D array.</span>
</span><span id="DataArray-69"><a href="#DataArray-69"><span class="linenos"> 69</span></a><span class="sd"> Data of the field as an array.</span>
</span><span id="DataArray-70"><a href="#DataArray-70"><span class="linenos"> 70</span></a><span class="sd"> </span>
</span><span id="DataArray-71"><a href="#DataArray-71"><span class="linenos"> 71</span></a><span class="sd"> dim : int</span>
</span><span id="DataArray-72"><a href="#DataArray-72"><span class="linenos"> 72</span></a><span class="sd"> Dimension of the space where the field is defined. In this case, the space is the 3D space and this is 3.</span>
</span><span id="DataArray-72"><a href="#DataArray-72"><span class="linenos"> 72</span></a><span class="sd"> Dimension of the space where the field is defined. For example, 2 for an image and 3 for a data cube..</span>
</span><span id="DataArray-73"><a href="#DataArray-73"><span class="linenos"> 73</span></a><span class="sd"> </span>
</span><span id="DataArray-74"><a href="#DataArray-74"><span class="linenos"> 74</span></a><span class="sd"> name : str</span>
</span><span id="DataArray-75"><a href="#DataArray-75"><span class="linenos"> 75</span></a><span class="sd"> Name of the field. In this case, &quot;data cube&quot;</span>
</span><span id="DataArray-75"><a href="#DataArray-75"><span class="linenos"> 75</span></a><span class="sd"> Name of the field. In this case, &quot;DataArray&quot;</span>
</span><span id="DataArray-76"><a href="#DataArray-76"><span class="linenos"> 76</span></a><span class="sd"> </span>
</span><span id="DataArray-77"><a href="#DataArray-77"><span class="linenos"> 77</span></a><span class="sd"> first_der : np.array or None</span>
</span><span id="DataArray-78"><a href="#DataArray-78"><span class="linenos"> 78</span></a><span class="sd"> First **covariant** derivatives of the field in an orthonormal basis of the space. Same structure as `field`, and shape `(dim, field.shape)`.</span>
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</span></pre></div>


<div class="docstring"><p>Class for a pixelized Euclidean data cube.</p>
<div class="docstring"><p>Class for a pixelized Euclidean data array.</p>

<h6 id="parameters">Parameters</h6>

<ul>
<li><strong>field</strong> (np.array):
Pixelized field as a 3D array. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see <code>spacing</code>).
Pixelized field as an array of arbitrary dimension. All pixels (or voxels) are expected to be the same size. The pixel shape is not necessarily a cube (see <code>spacing</code>).
The field can have different sizes in each dimension.</li>
<li><strong>normalise</strong> (bool, optional):
If <code>True</code>, the map is normalised to have unit variance. Note: the mean of the map is not forced to be 0.
Expand All @@ -433,11 +433,11 @@ <h6 id="attributes">Attributes</h6>

<ul>
<li><strong>field</strong> (np.array):
Data of the field as a 3D array.</li>
Data of the field as an array.</li>
<li><strong>dim</strong> (int):
Dimension of the space where the field is defined. In this case, the space is the 3D space and this is 3.</li>
Dimension of the space where the field is defined. For example, 2 for an image and 3 for a data cube..</li>
<li><strong>name</strong> (str):
Name of the field. In this case, "data cube"</li>
Name of the field. In this case, "DataArray"</li>
<li><strong>first_der</strong> (np.array or None):
First <strong>covariant</strong> derivatives of the field in an orthonormal basis of the space. Same structure as <code>field</code>, and shape <code>(dim, field.shape)</code>.</li>
<li><strong>second_der</strong> (np.array or None):
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