Figures in noise models

docs/_modules/teaspoon/MakeData/DynSysLib/noise_models.html

@@ -165,6 +165,8 @@ <h1>Source code for teaspoon.MakeData.DynSysLib.noise_models</h1><div class="hig
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Generate a noise signal sampled from a Gaussian distribution. </span>
 
+<span class="sd">    .. figure:: ../../../figures/Noise_Models/gaussian_noise.png</span>
+
 <span class="sd">    Parameters:</span>
 <span class="sd">        sigma (Optional[float]): Standard deviation of the normal distribution.</span>
 <span class="sd">        mu (Optional[float]): Mean of the normal distribution. </span>
@@ -187,6 +189,8 @@ <h1>Source code for teaspoon.MakeData.DynSysLib.noise_models</h1><div class="hig
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Generate a noise signal sampled from a uniform distribution.</span>
 
+<span class="sd">    .. figure:: ../../../figures/Noise_Models/uniform_noise.png</span>
+
 <span class="sd">    Parameters:</span>
 <span class="sd">        a (Optional[float]): Uniform distribution lower bound.</span>
 <span class="sd">        b (Optional[float]): Uniform distribution upper bound. </span>
@@ -209,6 +213,8 @@ <h1>Source code for teaspoon.MakeData.DynSysLib.noise_models</h1><div class="hig
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Generate a noise signal sampled from a Rayleigh distribution. </span>
 
+<span class="sd">    .. figure:: ../../../figures/Noise_Models/rayleigh_noise.png</span>
+
 <span class="sd">    Parameters:</span>
 <span class="sd">        sigma (Optional[float]): Rayleigh distribution mode.</span>
 <span class="sd">        L (Optional[int]): amount of time to solve simulation for.</span>
@@ -230,6 +236,8 @@ <h1>Source code for teaspoon.MakeData.DynSysLib.noise_models</h1><div class="hig
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Generate a noise signal sampled from an exponential distribution.</span>
 
+<span class="sd">    .. figure:: ../../../figures/Noise_Models/exponential_noise.png</span>
+
 <span class="sd">    Parameters:</span>
 <span class="sd">        sigma (Optional[float]): Exponential distribution scale.</span>
 <span class="sd">        L (Optional[int]): amount of time to solve simulation for.</span>

docs/modules/MakeData/DynSysLib/noise_models.html

@@ -177,6 +177,9 @@ <h1><span class="section-number">2.1.2.1.6. </span>Noise Models<a class="headerl
 <dt class="sig sig-object py" id="teaspoon.MakeData.DynSysLib.noise_models.exponential_noise">
 <span class="sig-prename descclassname"><span class="pre">teaspoon.MakeData.DynSysLib.noise_models.</span></span><span class="sig-name descname"><span class="pre">exponential_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SampleSize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/teaspoon/MakeData/DynSysLib/noise_models.html#exponential_noise"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#teaspoon.MakeData.DynSysLib.noise_models.exponential_noise" title="Permalink to this definition"></a></dt>
 <dd><p>Generate a noise signal sampled from an exponential distribution.</p>
+<figure class="align-default">
+<img alt="../../../_images/exponential_noise.png" src="../../../_images/exponential_noise.png" />
+</figure>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
@@ -199,6 +202,9 @@ <h1><span class="section-number">2.1.2.1.6. </span>Noise Models<a class="headerl
 <dt class="sig sig-object py" id="teaspoon.MakeData.DynSysLib.noise_models.gaussian_noise">
 <span class="sig-prename descclassname"><span class="pre">teaspoon.MakeData.DynSysLib.noise_models.</span></span><span class="sig-name descname"><span class="pre">gaussian_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mu</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SampleSize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/teaspoon/MakeData/DynSysLib/noise_models.html#gaussian_noise"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#teaspoon.MakeData.DynSysLib.noise_models.gaussian_noise" title="Permalink to this definition"></a></dt>
 <dd><p>Generate a noise signal sampled from a Gaussian distribution.</p>
+<figure class="align-default">
+<img alt="../../../_images/gaussian_noise.png" src="../../../_images/gaussian_noise.png" />
+</figure>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
@@ -222,6 +228,9 @@ <h1><span class="section-number">2.1.2.1.6. </span>Noise Models<a class="headerl
 <dt class="sig sig-object py" id="teaspoon.MakeData.DynSysLib.noise_models.rayleigh_noise">
 <span class="sig-prename descclassname"><span class="pre">teaspoon.MakeData.DynSysLib.noise_models.</span></span><span class="sig-name descname"><span class="pre">rayleigh_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SampleSize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/teaspoon/MakeData/DynSysLib/noise_models.html#rayleigh_noise"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#teaspoon.MakeData.DynSysLib.noise_models.rayleigh_noise" title="Permalink to this definition"></a></dt>
 <dd><p>Generate a noise signal sampled from a Rayleigh distribution.</p>
+<figure class="align-default">
+<img alt="../../../_images/rayleigh_noise.png" src="../../../_images/rayleigh_noise.png" />
+</figure>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
@@ -244,6 +253,9 @@ <h1><span class="section-number">2.1.2.1.6. </span>Noise Models<a class="headerl
 <dt class="sig sig-object py" id="teaspoon.MakeData.DynSysLib.noise_models.uniform_noise">
 <span class="sig-prename descclassname"><span class="pre">teaspoon.MakeData.DynSysLib.noise_models.</span></span><span class="sig-name descname"><span class="pre">uniform_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SampleSize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/teaspoon/MakeData/DynSysLib/noise_models.html#uniform_noise"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#teaspoon.MakeData.DynSysLib.noise_models.uniform_noise" title="Permalink to this definition"></a></dt>
 <dd><p>Generate a noise signal sampled from a uniform distribution.</p>
+<figure class="align-default">
+<img alt="../../../_images/uniform_noise.png" src="../../../_images/uniform_noise.png" />
+</figure>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">

teaspoon/teaspoon/MakeData/DynSysLib/noise_models.py

@@ -23,6 +23,8 @@ def gaussian_noise(sigma=1.0, mu=0.0,
     """
     Generate a noise signal sampled from a Gaussian distribution. 
 
+    .. figure:: ../../../figures/Noise_Models/gaussian_noise.png
+
     Parameters:
         sigma (Optional[float]): Standard deviation of the normal distribution.
         mu (Optional[float]): Mean of the normal distribution. 
@@ -45,6 +47,8 @@ def uniform_noise(a=-1.0, b=1.0,
     """
     Generate a noise signal sampled from a uniform distribution.
 
+    .. figure:: ../../../figures/Noise_Models/uniform_noise.png
+
     Parameters:
         a (Optional[float]): Uniform distribution lower bound.
         b (Optional[float]): Uniform distribution upper bound. 
@@ -67,6 +71,8 @@ def rayleigh_noise(sigma=1.0,
     """
     Generate a noise signal sampled from a Rayleigh distribution. 
 
+    .. figure:: ../../../figures/Noise_Models/rayleigh_noise.png
+
     Parameters:
         sigma (Optional[float]): Rayleigh distribution mode.
         L (Optional[int]): amount of time to solve simulation for.
@@ -88,6 +94,8 @@ def exponential_noise(sigma=1.0,
     """
     Generate a noise signal sampled from an exponential distribution.
 
+    .. figure:: ../../../figures/Noise_Models/exponential_noise.png
+
     Parameters:
         sigma (Optional[float]): Exponential distribution scale.
         L (Optional[int]): amount of time to solve simulation for.