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<h1>Coverage for <b>navipy/arenatools/patterns.py</b> :
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<p id="t1" class="pln"><span class="str">"""</span><span class="strut"> </span></p>
<p id="t2" class="pln"><span class="str">Tools to generate patterns</span><span class="strut"> </span></p>
<p id="t3" class="pln"><span class="str">"""</span><span class="strut"> </span></p>
<p id="t4" class="stm mis"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p>
<p id="t5" class="pln"><span class="strut"> </span></p>
<p id="t6" class="pln"><span class="strut"> </span></p>
<p id="t7" class="stm mis"><span class="key">def</span> <span class="nam">generate_1overf_noise</span><span class="op">(</span><span class="nam">img_size</span><span class="op">,</span> <span class="nam">beta</span><span class="op">,</span> <span class="nam">noise</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
<p id="t8" class="pln"> <span class="str">"""</span><span class="strut"> </span></p>
<p id="t9" class="pln"><span class="str"> Generates the discrete fourier transformation of noise and weights it with weights<0.</span><span class="strut"> </span></p>
<p id="t10" class="pln"><span class="str"> Where the smallest weights are in the middle columns of the returned noise array and the biggest in the outer columns.</span><span class="strut"> </span></p>
<p id="t11" class="pln"><span class="str"> First generates the noise and applies the following formula:</span><span class="strut"> </span></p>
<p id="t12" class="pln"><span class="strut"> </span></p>
<p id="t13" class="pln"><span class="str"> .. math::</span><span class="strut"> </span></p>
<p id="t14" class="pln"><span class="strut"> </span></p>
<p id="t15" class="pln"><span class="str"> DFT(\\frac{1}{f^{\\beta}} * DFT(noise))</span><span class="strut"> </span></p>
<p id="t16" class="pln"><span class="strut"> </span></p>
<p id="t17" class="pln"><span class="str"> The noise must be a 2d array.</span><span class="strut"> </span></p>
<p id="t18" class="pln"><span class="strut"> </span></p>
<p id="t19" class="pln"><span class="str"> :params img_size: size of the output noise dimensions \</span><span class="strut"> </span></p>
<p id="t20" class="pln"><span class="str">(array dimension e.g. (4,4))</span><span class="strut"> </span></p>
<p id="t21" class="pln"><span class="str"> :params beta: used to calculate the weights of the noise, \</span><span class="strut"> </span></p>
<p id="t22" class="pln"><span class="str">the bigger beta the smaller the weights, can have an arbitrary value \</span><span class="strut"> </span></p>
<p id="t23" class="pln"><span class="str">(weights are always between 0 and 1)</span><span class="strut"> </span></p>
<p id="t24" class="pln"><span class="str"> :params noise: array with same size as img_size, that is used as \</span><span class="strut"> </span></p>
<p id="t25" class="pln"><span class="str">the noise (default: random generated noise)</span><span class="strut"> </span></p>
<p id="t26" class="pln"><span class="str"> """</span><span class="strut"> </span></p>
<p id="t27" class="pln"> <span class="com"># Calculate image size -> next biggest power of two,</span><span class="strut"> </span></p>
<p id="t28" class="pln"> <span class="com"># in which the image fits (s>=max(img_size))</span><span class="strut"> </span></p>
<p id="t29" class="stm mis"> <span class="nam">s</span> <span class="op">=</span> <span class="num">2</span><span class="op">**</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">ceil</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log2</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="nam">img_size</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">int</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t30" class="stm mis"> <span class="key">if</span> <span class="nam">noise</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p>
<p id="t31" class="pln"> <span class="com"># generate white noise</span><span class="strut"> </span></p>
<p id="t32" class="stm mis"> <span class="nam">noise</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randn</span><span class="op">(</span><span class="nam">s</span><span class="op">,</span> <span class="nam">s</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t33" class="pln"><span class="strut"> </span></p>
<p id="t34" class="pln"> <span class="com"># calculate filter</span><span class="strut"> </span></p>
<p id="t35" class="stm mis"> <span class="nam">fx</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arange</span><span class="op">(</span><span class="nam">s</span><span class="op">/</span><span class="num">2</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="strut"> </span></p>
<p id="t36" class="pln"> <span class="com"># index from 0-s/2,s/2-0 -> middle highest index</span><span class="strut"> </span></p>
<p id="t37" class="stm mis"> <span class="nam">fx</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">hstack</span><span class="op">(</span><span class="op">[</span><span class="nam">fx</span><span class="op">,</span> <span class="nam">fx</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">:</span><span class="op">:</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t38" class="stm mis"> <span class="nam">fx</span> <span class="op">=</span> <span class="nam">fx</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">newaxis</span><span class="op">]</span><span class="strut"> </span></p>
<p id="t39" class="pln"> <span class="com"># copy first row s times -> fx=[[0..0],[1..],..,[s/2,..s/2],..[0..0]</span><span class="strut"> </span></p>
<p id="t40" class="pln"> <span class="com"># fx is a symmetric matrix</span><span class="strut"> </span></p>
<p id="t41" class="stm mis"> <span class="nam">fx</span> <span class="op">=</span> <span class="nam">fx</span><span class="op">.</span><span class="nam">repeat</span><span class="op">(</span><span class="nam">s</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t42" class="stm mis"> <span class="nam">fy</span> <span class="op">=</span> <span class="nam">fx</span><span class="op">.</span><span class="nam">transpose</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t43" class="pln"><span class="strut"> </span></p>
<p id="t44" class="stm mis"> <span class="nam">f</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">fx</span><span class="op">**</span><span class="num">2</span> <span class="op">+</span> <span class="nam">fy</span><span class="op">**</span><span class="num">2</span><span class="op">)</span> <span class="com"># Euclidian norm</span><span class="strut"> </span></p>
<p id="t45" class="stm mis"> <span class="nam">f</span> <span class="op">=</span> <span class="nam">f</span><span class="op">**</span><span class="op">(</span><span class="op">-</span><span class="nam">beta</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t46" class="pln"> <span class="com"># apply filter in frequency domain</span><span class="strut"> </span></p>
<p id="t47" class="pln"> <span class="com"># calculate disrete furier transformations</span><span class="strut"> </span></p>
<p id="t48" class="stm mis"> <span class="nam">fnoise</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">fft</span><span class="op">.</span><span class="nam">ifft2</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">fft</span><span class="op">.</span><span class="nam">fft2</span><span class="op">(</span><span class="nam">noise</span><span class="op">)</span><span class="op">*</span><span class="nam">f</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t49" class="pln"><span class="strut"> </span></p>
<p id="t50" class="pln"> <span class="com"># trim to image size</span><span class="strut"> </span></p>
<p id="t51" class="stm mis"> <span class="nam">fnoise</span> <span class="op">=</span> <span class="nam">fnoise</span><span class="op">[</span><span class="op">:</span><span class="nam">img_size</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="op">:</span><span class="nam">img_size</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">]</span><span class="strut"> </span></p>
<p id="t52" class="stm mis"> <span class="nam">fnoise</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">real</span><span class="op">(</span><span class="nam">fnoise</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t53" class="stm mis"> <span class="key">return</span> <span class="nam">fnoise</span><span class="strut"> </span></p>
<p id="t54" class="pln"><span class="strut"> </span></p>
<p id="t55" class="pln"><span class="strut"> </span></p>
<p id="t56" class="stm mis"><span class="key">def</span> <span class="nam">gray2red</span><span class="op">(</span><span class="nam">img</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
<p id="t57" class="pln"> <span class="str">""" convert a gray image to a red image (black -> red)</span><span class="strut"> </span></p>
<p id="t58" class="pln"><span class="strut"> </span></p>
<p id="t59" class="pln"><span class="str"> Many bees and flies are not sensitive to red light, and</span><span class="strut"> </span></p>
<p id="t60" class="pln"><span class="str"> can be better observed on red background than on a black one</span><span class="strut"> </span></p>
<p id="t61" class="pln"><span class="str"> due to their dark colour.</span><span class="strut"> </span></p>
<p id="t62" class="pln"><span class="strut"> </span></p>
<p id="t63" class="pln"><span class="str"> :params img: Gray image to be converted into red-white one</span><span class="strut"> </span></p>
<p id="t64" class="pln"><span class="str"> """</span><span class="strut"> </span></p>
<p id="t65" class="stm mis"> <span class="nam">img</span> <span class="op">=</span> <span class="nam">img</span><span class="op">[</span><span class="op">...</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">newaxis</span><span class="op">]</span><span class="strut"> </span></p>
<p id="t66" class="stm mis"> <span class="nam">img</span> <span class="op">=</span> <span class="nam">img</span><span class="op">.</span><span class="nam">repeat</span><span class="op">(</span><span class="num">3</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">2</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t67" class="stm mis"> <span class="nam">maxval</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="nam">img</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t68" class="stm mis"> <span class="nam">img</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">maxval</span><span class="op">-</span><span class="nam">img</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p>
<p id="t69" class="stm mis"> <span class="nam">img</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span> <span class="op">=</span> <span class="nam">maxval</span><span class="op">-</span><span class="nam">img</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p>
<p id="t70" class="stm mis"> <span class="nam">img</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">maxval</span><span class="strut"> </span></p>
<p id="t71" class="stm mis"> <span class="key">return</span> <span class="nam">img</span><span class="strut"> </span></p>
<p id="t72" class="pln"><span class="strut"> </span></p>
<p id="t73" class="pln"><span class="strut"> </span></p>
<p id="t74" class="stm mis"><span class="key">def</span> <span class="nam">norm_img</span><span class="op">(</span><span class="nam">img</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
<p id="t75" class="pln"> <span class="str">""" Normalise an 8bit image between 0 and 255</span><span class="strut"> </span></p>
<p id="t76" class="pln"><span class="strut"> </span></p>
<p id="t77" class="pln"><span class="str"> :params img: Image to be normalised</span><span class="strut"> </span></p>
<p id="t78" class="pln"><span class="str"> """</span><span class="strut"> </span></p>
<p id="t79" class="stm mis"> <span class="nam">img</span> <span class="op">=</span> <span class="nam">img</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">float</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t80" class="stm mis"> <span class="nam">img</span> <span class="op">-=</span> <span class="nam">img</span><span class="op">.</span><span class="nam">min</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t81" class="stm mis"> <span class="nam">img</span> <span class="op">/=</span> <span class="nam">img</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t82" class="stm mis"> <span class="nam">img</span> <span class="op">*=</span> <span class="num">255</span><span class="strut"> </span></p>
<p id="t83" class="stm mis"> <span class="key">return</span> <span class="nam">img</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">uint8</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t84" class="pln"><span class="strut"> </span></p>
<p id="t85" class="pln"><span class="strut"> </span></p>
<p id="t86" class="stm mis"><span class="key">def</span> <span class="nam">rectangular_pattern</span><span class="op">(</span><span class="nam">width</span><span class="op">,</span> <span class="nam">length</span><span class="op">,</span> <span class="nam">beta</span><span class="op">=</span><span class="num">1.4</span><span class="op">,</span> <span class="nam">pixel_per_mm</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
<p id="t87" class="pln"> <span class="str">"""generate a rectangular pattern</span><span class="strut"> </span></p>
<p id="t88" class="pln"><span class="strut"> </span></p>
<p id="t89" class="pln"><span class="str"> :param width: width of the pattern in mm</span><span class="strut"> </span></p>
<p id="t90" class="pln"><span class="str"> :param length: length of the pattern in mm</span><span class="strut"> </span></p>
<p id="t91" class="pln"><span class="str"> :param beta: beta coef for generating a 1/(f^beta) pattern</span><span class="strut"> </span></p>
<p id="t92" class="pln"><span class="str"> :param pixel_per_mm: number of pixel per mm</span><span class="strut"> </span></p>
<p id="t93" class="pln"><span class="str"> :returns: a rectangular random image</span><span class="strut"> </span></p>
<p id="t94" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p>
<p id="t95" class="pln"><span class="str"> """</span><span class="strut"> </span></p>
<p id="t96" class="stm mis"> <span class="nam">corridor</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="nam">width</span><span class="op">,</span> <span class="nam">length</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p>
<p id="t97" class="stm mis"> <span class="nam">corridor_px</span> <span class="op">=</span> <span class="nam">corridor</span><span class="op">*</span><span class="nam">pixel_per_mm</span> <span class="com"># in px</span><span class="strut"> </span></p>
<p id="t98" class="stm mis"> <span class="key">return</span> <span class="nam">generate_1overf_noise</span><span class="op">(</span><span class="nam">corridor_px</span><span class="op">,</span> <span class="nam">beta</span><span class="op">)</span><span class="strut"> </span></p>
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