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form'><form method='get'>
<input type='hidden' name='id' value='af088b88f50d4b1ba0e0688c18d561becefc5bbf'/><select name='h' onchange='this.form.submit();'>
<option value='master'>master</option>
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<tr><td class='sub'>libcamera official repository</td><td class='sub right'>git repository hosting on libcamera.org</td></tr></table>
<table class='tabs'><tr><td>
<a href='/libcamera/libcamera.git/?h=v0.0.3'>summary</a><a href='/libcamera/libcamera.git/refs/?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>refs</a><a href='/libcamera/libcamera.git/log/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3'>log</a><a class='active' href='/libcamera/libcamera.git/tree/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>tree</a><a href='/libcamera/libcamera.git/commit/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>commit</a><a href='/libcamera/libcamera.git/diff/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>diff</a></td><td class='form'><form class='right' method='get' action='/libcamera/libcamera.git/log/utils/raspberrypi/ctt/ctt_awb.py'>
<input type='hidden' name='h' value='v0.0.3'/><input type='hidden' name='id' value='af088b88f50d4b1ba0e0688c18d561becefc5bbf'/><select name='qt'>
<option value='grep'>log msg</option>
<option value='author'>author</option>
<option value='committer'>committer</option>
<option value='range'>range</option>
</select>
<input class='txt' type='search' size='10' name='q' value=''/>
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<div class='path'>path: <a href='/libcamera/libcamera.git/tree/?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>root</a>/<a href='/libcamera/libcamera.git/tree/utils?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>utils</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>raspberrypi</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi/ctt?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>ctt</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>ctt_awb.py</a></div><div class='content'>blob: 3c8cd9027a1ad94246b489ddab9ef4408afa967d (<a href='/libcamera/libcamera.git/plain/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>plain</a>)
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<td class='lines'><pre><code><span class="hl slc"># SPDX-License-Identifier: BSD-2-Clause</span>
<span class="hl slc">#</span>
<span class="hl slc"># Copyright (C) 2019, Raspberry Pi (Trading) Limited</span>
<span class="hl slc">#</span>
<span class="hl slc"># ctt_awb.py - camera tuning tool for AWB</span>
<span class="hl kwa">from</span> ctt_image_load <span class="hl kwa">import</span> <span class="hl opt">*</span>
<span class="hl kwa">import</span> matplotlib<span class="hl opt">.</span>pyplot <span class="hl kwa">as</span> plt
<span class="hl kwa">from</span> bisect <span class="hl kwa">import</span> bisect_left
<span class="hl kwa">from</span> scipy<span class="hl opt">.</span>optimize <span class="hl kwa">import</span> fmin
<span class="hl str">"""</span>
<span class="hl str">obtain piecewise linear approximation for colour curve</span>
<span class="hl str">"""</span>
<span class="hl kwa">def</span> <span class="hl kwd">awb</span><span class="hl opt">(</span>Cam<span class="hl opt">,</span> cal_cr_list<span class="hl opt">,</span> cal_cb_list<span class="hl opt">,</span> plot<span class="hl opt">):</span>
imgs <span class="hl opt">=</span> Cam<span class="hl opt">.</span>imgs
<span class="hl str">"""</span>
<span class="hl str"> condense alsc calibration tables into one dictionary</span>
<span class="hl str"> """</span>
<span class="hl kwa">if</span> cal_cr_list <span class="hl kwa">is None</span><span class="hl opt">:</span>
colour_cals <span class="hl opt">=</span> <span class="hl kwa">None</span>
<span class="hl kwa">else</span><span class="hl opt">:</span>
colour_cals <span class="hl opt">= {}</span>
<span class="hl kwa">for</span> cr<span class="hl opt">,</span> cb <span class="hl kwa">in</span> <span class="hl kwb">zip</span><span class="hl opt">(</span>cal_cr_list<span class="hl opt">,</span> cal_cb_list<span class="hl opt">):</span>
cr_tab <span class="hl opt">=</span> cr<span class="hl opt">[</span><span class="hl str">'table'</span><span class="hl opt">]</span>
cb_tab <span class="hl opt">=</span> cb<span class="hl opt">[</span><span class="hl str">'table'</span><span class="hl opt">]</span>
<span class="hl str">"""</span>
<span class="hl str"> normalise tables so min value is 1</span>
<span class="hl str"> """</span>
cr_tab <span class="hl opt">=</span> cr_tab<span class="hl opt">/</span>np<span class="hl opt">.</span><span class="hl kwb">min</span><span class="hl opt">(</span>cr_tab<span class="hl opt">)</span>
cb_tab <span class="hl opt">=</span> cb_tab<span class="hl opt">/</span>np<span class="hl opt">.</span><span class="hl kwb">min</span><span class="hl opt">(</span>cb_tab<span class="hl opt">)</span>
colour_cals<span class="hl opt">[</span>cr<span class="hl opt">[</span><span class="hl str">'ct'</span><span class="hl opt">]] = [</span>cr_tab<span class="hl opt">,</span> cb_tab<span class="hl opt">]</span>
<span class="hl str">"""</span>
<span class="hl str"> obtain data from greyscale macbeth patches</span>
<span class="hl str"> """</span>
rb_raw <span class="hl opt">= []</span>
rbs_hat <span class="hl opt">= []</span>
<span class="hl kwa">for</span> Img <span class="hl kwa">in</span> imgs<span class="hl opt">:</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Processing '</span><span class="hl opt">+</span>Img<span class="hl opt">.</span>name
<span class="hl str">"""</span>
<span class="hl str"> get greyscale patches with alsc applied if alsc enabled.</span>
<span class="hl str"> Note: if alsc is disabled then colour_cals will be set to None and the</span>
<span class="hl str"> function will just return the greyscale patches</span>
<span class="hl str"> """</span>
r_patchs<span class="hl opt">,</span> b_patchs<span class="hl opt">,</span> g_patchs <span class="hl opt">=</span> <span class="hl kwd">get_alsc_patches</span><span class="hl opt">(</span>Img<span class="hl opt">,</span> colour_cals<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> calculate ratio of r, b to g</span>
<span class="hl str"> """</span>
r_g <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">mean</span><span class="hl opt">(</span>r_patchs<span class="hl opt">/</span>g_patchs<span class="hl opt">)</span>
b_g <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">mean</span><span class="hl opt">(</span>b_patchs<span class="hl opt">/</span>g_patchs<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span> <span class="hl str">r : {:.4f} b : {:.4f}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>r_g<span class="hl opt">,</span> b_g<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> The curve tends to be better behaved in so-called hatspace.</span>
<span class="hl str"> R, B, G represent the individual channels. The colour curve is plotted in</span>
<span class="hl str"> r, b space, where:</span>
<span class="hl str"> r = R/G</span>
<span class="hl str"> b = B/G</span>
<span class="hl str"> This will be referred to as dehatspace... (sorry)</span>
<span class="hl str"> Hatspace is defined as:</span>
<span class="hl str"> r_hat = R/(R+B+G)</span>
<span class="hl str"> b_hat = B/(R+B+G)</span>
<span class="hl str"> To convert from dehatspace to hastpace (hat operation):</span>
<span class="hl str"> r_hat = r/(1+r+b)</span>
<span class="hl str"> b_hat = b/(1+r+b)</span>
<span class="hl str"> To convert from hatspace to dehatspace (dehat operation):</span>
<span class="hl str"> r = r_hat/(1-r_hat-b_hat)</span>
<span class="hl str"> b = b_hat/(1-r_hat-b_hat)</span>
<span class="hl str"> Proof is left as an excercise to the reader...</span>
<span class="hl str"> Throughout the code, r and b are sometimes referred to as r_g and b_g</span>
<span class="hl str"> as a reminder that they are ratios</span>
<span class="hl str"> """</span>
r_g_hat <span class="hl opt">=</span> r_g<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">+</span>r_g<span class="hl opt">+</span>b_g<span class="hl opt">)</span>
b_g_hat <span class="hl opt">=</span> b_g<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">+</span>r_g<span class="hl opt">+</span>b_g<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span> <span class="hl str">r_hat : {:.4f} b_hat : {:.4f}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>r_g_hat<span class="hl opt">,</span> b_g_hat<span class="hl opt">)</span>
rbs_hat<span class="hl opt">.</span><span class="hl kwd">append</span><span class="hl opt">((</span>r_g_hat<span class="hl opt">,</span> b_g_hat<span class="hl opt">,</span> Img<span class="hl opt">.</span>col<span class="hl opt">))</span>
rb_raw<span class="hl opt">.</span><span class="hl kwd">append</span><span class="hl opt">((</span>r_g<span class="hl opt">,</span> b_g<span class="hl opt">))</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">'</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Finished processing images'</span>
<span class="hl str">"""</span>
<span class="hl str"> sort all lits simultaneously by r_hat</span>
<span class="hl str"> """</span>
rbs_zip <span class="hl opt">=</span> <span class="hl kwb">list</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(</span>rbs_hat<span class="hl opt">,</span> rb_raw<span class="hl opt">))</span>
rbs_zip<span class="hl opt">.</span><span class="hl kwd">sort</span><span class="hl opt">(</span>key<span class="hl opt">=</span><span class="hl kwa">lambda</span> x<span class="hl opt">:</span> x<span class="hl opt">[</span><span class="hl num">0</span><span class="hl opt">][</span><span class="hl num">0</span><span class="hl opt">])</span>
rbs_hat<span class="hl opt">,</span> rb_raw <span class="hl opt">=</span> <span class="hl kwb">list</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(*</span>rbs_zip<span class="hl opt">))</span>
<span class="hl str">"""</span>
<span class="hl str"> unzip tuples ready for processing</span>
<span class="hl str"> """</span>
rbs_hat <span class="hl opt">=</span> <span class="hl kwb">list</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(*</span>rbs_hat<span class="hl opt">))</span>
rb_raw <span class="hl opt">=</span> <span class="hl kwb">list</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(*</span>rb_raw<span class="hl opt">))</span>
<span class="hl str">"""</span>
<span class="hl str"> fit quadratic fit to r_g hat and b_g_hat</span>
<span class="hl str"> """</span>
a<span class="hl opt">,</span> b<span class="hl opt">,</span> c <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">polyfit</span><span class="hl opt">(</span>rbs_hat<span class="hl opt">[</span><span class="hl num">0</span><span class="hl opt">],</span> rbs_hat<span class="hl opt">[</span><span class="hl num">1</span><span class="hl opt">],</span> <span class="hl num">2</span><span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Fit quadratic curve in hatspace'</span>
<span class="hl str">"""</span>
<span class="hl str"> the algorithm now approximates the shortest distance from each point to the</span>
<span class="hl str"> curve in dehatspace. Since the fit is done in hatspace, it is easier to</span>
<span class="hl str"> find the actual shortest distance in hatspace and use the projection back</span>
<span class="hl str"> into dehatspace as an overestimate.</span>
<span class="hl str"> The distance will be used for two things:</span>
<span class="hl str"> 1) In the case that colour temperature does not strictly decrease with</span>
<span class="hl str"> increasing r/g, the closest point to the line will be chosen out of an</span>
<span class="hl str"> increasing pair of colours.</span>
<span class="hl str"></span>
<span class="hl str"> 2) To calculate transverse negative an dpositive, the maximum positive</span>
<span class="hl str"> and negative distance from the line are chosen. This benefits from the</span>
<span class="hl str"> overestimate as the transverse pos/neg are upper bound values.</span>
<span class="hl str"> """</span>
<span class="hl str">"""</span>
<span class="hl str"> define fit function</span>
<span class="hl str"> """</span>
<span class="hl kwa">def</span> <span class="hl kwd">f</span><span class="hl opt">(</span>x<span class="hl opt">):</span>
<span class="hl kwa">return</span> a<span class="hl opt">*</span>x<span class="hl opt">**</span><span class="hl num">2</span> <span class="hl opt">+</span> b<span class="hl opt">*</span>x <span class="hl opt">+</span> c
<span class="hl str">"""</span>
<span class="hl str"> iterate over points (R, B are x and y coordinates of points) and calculate</span>
<span class="hl str"> distance to line in dehatspace</span>
<span class="hl str"> """</span>
dists <span class="hl opt">= []</span>
<span class="hl kwa">for</span> i<span class="hl opt">, (</span>R<span class="hl opt">,</span> B<span class="hl opt">)</span> <span class="hl kwa">in</span> <span class="hl kwb">enumerate</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(</span>rbs_hat<span class="hl opt">[</span><span class="hl num">0</span><span class="hl opt">],</span> rbs_hat<span class="hl opt">[</span><span class="hl num">1</span><span class="hl opt">])):</span>
<span class="hl str">"""</span>
<span class="hl str"> define function to minimise as square distance between datapoint and</span>
<span class="hl str"> point on curve. Squaring is monotonic so minimising radius squared is</span>
<span class="hl str"> equivalent to minimising radius</span>
<span class="hl str"> """</span>
<span class="hl kwa">def</span> <span class="hl kwd">f_min</span><span class="hl opt">(</span>x<span class="hl opt">):</span>
y <span class="hl opt">=</span> <span class="hl kwd">f</span><span class="hl opt">(</span>x<span class="hl opt">)</span>
<span class="hl kwa">return</span><span class="hl opt">((</span>x<span class="hl opt">-</span>R<span class="hl opt">)**</span><span class="hl num">2</span><span class="hl opt">+(</span>y<span class="hl opt">-</span>B<span class="hl opt">)**</span><span class="hl num">2</span><span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> perform optimisation with scipy.optmisie.fmin</span>
<span class="hl str"> """</span>
x_hat <span class="hl opt">=</span> <span class="hl kwd">fmin</span><span class="hl opt">(</span>f_min<span class="hl opt">,</span> R<span class="hl opt">,</span> disp<span class="hl opt">=</span><span class="hl num">0</span><span class="hl opt">)[</span><span class="hl num">0</span><span class="hl opt">]</span>
y_hat <span class="hl opt">=</span> <span class="hl kwd">f</span><span class="hl opt">(</span>x_hat<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> dehat</span>
<span class="hl str"> """</span>
x <span class="hl opt">=</span> x_hat<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>x_hat<span class="hl opt">-</span>y_hat<span class="hl opt">)</span>
y <span class="hl opt">=</span> y_hat<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>x_hat<span class="hl opt">-</span>y_hat<span class="hl opt">)</span>
rr <span class="hl opt">=</span> R<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>R<span class="hl opt">-</span>B<span class="hl opt">)</span>
bb <span class="hl opt">=</span> B<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>R<span class="hl opt">-</span>B<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> calculate euclidean distance in dehatspace</span>
<span class="hl str"> """</span>
dist <span class="hl opt">= ((</span>x<span class="hl opt">-</span>rr<span class="hl opt">)**</span><span class="hl num">2</span><span class="hl opt">+(</span>y<span class="hl opt">-</span>bb<span class="hl opt">)**</span><span class="hl num">2</span><span class="hl opt">)**</span><span class="hl num">0.5</span>
<span class="hl str">"""</span>
<span class="hl str"> return negative if point is below the fit curve</span>
<span class="hl str"> """</span>
<span class="hl kwa">if</span> <span class="hl opt">(</span>x<span class="hl opt">+</span>y<span class="hl opt">) > (</span>rr<span class="hl opt">+</span>bb<span class="hl opt">):</span>
dist <span class="hl opt">*= -</span><span class="hl num">1</span>
dists<span class="hl opt">.</span><span class="hl kwd">append</span><span class="hl opt">(</span>dist<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Found closest point on fit line to each point in dehatspace'</span>
<span class="hl str">"""</span>
<span class="hl str"> calculate wiggle factors in awb. 10% added since this is an upper bound</span>
<span class="hl str"> """</span>
transverse_neg <span class="hl opt">= -</span> np<span class="hl opt">.</span><span class="hl kwb">min</span><span class="hl opt">(</span>dists<span class="hl opt">) *</span> <span class="hl num">1.1</span>
transverse_pos <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwb">max</span><span class="hl opt">(</span>dists<span class="hl opt">) *</span> <span class="hl num">1.1</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Transverse pos : {:.5f}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>transverse_pos<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Transverse neg : {:.5f}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>transverse_neg<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> set minimum transverse wiggles to 0.1 .</span>
<span class="hl str"> Wiggle factors dictate how far off of the curve the algorithm searches. 0.1</span>
<span class="hl str"> is a suitable minimum that gives better results for lighting conditions not</span>
<span class="hl str"> within calibration dataset. Anything less will generalise poorly.</span>
<span class="hl str"> """</span>
<span class="hl kwa">if</span> transverse_pos <span class="hl opt"><</span> <span class="hl num">0.01</span><span class="hl opt">:</span>
transverse_pos <span class="hl opt">=</span> <span class="hl num">0.01</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Forced transverse pos to 0.01'</span>
<span class="hl kwa">if</span> transverse_neg <span class="hl opt"><</span> <span class="hl num">0.01</span><span class="hl opt">:</span>
transverse_neg <span class="hl opt">=</span> <span class="hl num">0.01</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Forced transverse neg to 0.01'</span>
<span class="hl str">"""</span>
<span class="hl str"> generate new b_hat values at each r_hat according to fit</span>
<span class="hl str"> """</span>
r_hat_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">array</span><span class="hl opt">(</span>rbs_hat<span class="hl opt">[</span><span class="hl num">0</span><span class="hl opt">])</span>
b_hat_fit <span class="hl opt">=</span> a<span class="hl opt">*</span>r_hat_fit<span class="hl opt">**</span><span class="hl num">2</span> <span class="hl opt">+</span> b<span class="hl opt">*</span>r_hat_fit <span class="hl opt">+</span> c
<span class="hl str">"""</span>
<span class="hl str"> transform from hatspace to dehatspace</span>
<span class="hl str"> """</span>
r_fit <span class="hl opt">=</span> r_hat_fit<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>r_hat_fit<span class="hl opt">-</span>b_hat_fit<span class="hl opt">)</span>
b_fit <span class="hl opt">=</span> b_hat_fit<span class="hl opt">/(</span><span class="hl num">1</span><span class="hl opt">-</span>r_hat_fit<span class="hl opt">-</span>b_hat_fit<span class="hl opt">)</span>
c_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwb">round</span><span class="hl opt">(</span>rbs_hat<span class="hl opt">[</span><span class="hl num">2</span><span class="hl opt">],</span> <span class="hl num">0</span><span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> round to 4dp</span>
<span class="hl str"> """</span>
r_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">where</span><span class="hl opt">((</span><span class="hl num">1000</span><span class="hl opt">*</span>r_fit<span class="hl opt">) %</span> <span class="hl num">1</span> <span class="hl opt"><=</span> <span class="hl num">0.05</span><span class="hl opt">,</span> r_fit<span class="hl opt">+</span><span class="hl num">0.0001</span><span class="hl opt">,</span> r_fit<span class="hl opt">)</span>
r_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">where</span><span class="hl opt">((</span><span class="hl num">1000</span><span class="hl opt">*</span>r_fit<span class="hl opt">) %</span> <span class="hl num">1</span> <span class="hl opt">>=</span> <span class="hl num">0.95</span><span class="hl opt">,</span> r_fit<span class="hl opt">-</span><span class="hl num">0.0001</span><span class="hl opt">,</span> r_fit<span class="hl opt">)</span>
b_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">where</span><span class="hl opt">((</span><span class="hl num">1000</span><span class="hl opt">*</span>b_fit<span class="hl opt">) %</span> <span class="hl num">1</span> <span class="hl opt"><=</span> <span class="hl num">0.05</span><span class="hl opt">,</span> b_fit<span class="hl opt">+</span><span class="hl num">0.0001</span><span class="hl opt">,</span> b_fit<span class="hl opt">)</span>
b_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">where</span><span class="hl opt">((</span><span class="hl num">1000</span><span class="hl opt">*</span>b_fit<span class="hl opt">) %</span> <span class="hl num">1</span> <span class="hl opt">>=</span> <span class="hl num">0.95</span><span class="hl opt">,</span> b_fit<span class="hl opt">-</span><span class="hl num">0.0001</span><span class="hl opt">,</span> b_fit<span class="hl opt">)</span>
r_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwb">round</span><span class="hl opt">(</span>r_fit<span class="hl opt">,</span> <span class="hl num">4</span><span class="hl opt">)</span>
b_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwb">round</span><span class="hl opt">(</span>b_fit<span class="hl opt">,</span> <span class="hl num">4</span><span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> The following code ensures that colour temperature decreases with</span>
<span class="hl str"> increasing r/g</span>
<span class="hl str"> """</span>
<span class="hl str">"""</span>
<span class="hl str"> iterate backwards over list for easier indexing</span>
<span class="hl str"> """</span>
i <span class="hl opt">=</span> <span class="hl kwb">len</span><span class="hl opt">(</span>c_fit<span class="hl opt">) -</span> <span class="hl num">1</span>
<span class="hl kwa">while</span> i <span class="hl opt">></span> <span class="hl num">0</span><span class="hl opt">:</span>
<span class="hl kwa">if</span> c_fit<span class="hl opt">[</span>i<span class="hl opt">] ></span> c_fit<span class="hl opt">[</span>i<span class="hl opt">-</span><span class="hl num">1</span><span class="hl opt">]:</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Colour temperature increase found</span><span class="hl esc">\n</span><span class="hl str">'</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'{} K at r = {} to '</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>c_fit<span class="hl opt">[</span>i<span class="hl opt">-</span><span class="hl num">1</span><span class="hl opt">],</span> r_fit<span class="hl opt">[</span>i<span class="hl opt">-</span><span class="hl num">1</span><span class="hl opt">])</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'{} K at r = {}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>c_fit<span class="hl opt">[</span>i<span class="hl opt">],</span> r_fit<span class="hl opt">[</span>i<span class="hl opt">])</span>
<span class="hl str">"""</span>
<span class="hl str"> if colour temperature increases then discard point furthest from</span>
<span class="hl str"> the transformed fit (dehatspace)</span>
<span class="hl str"> """</span>
error_1 <span class="hl opt">=</span> <span class="hl kwb">abs</span><span class="hl opt">(</span>dists<span class="hl opt">[</span>i<span class="hl opt">-</span><span class="hl num">1</span><span class="hl opt">])</span>
error_2 <span class="hl opt">=</span> <span class="hl kwb">abs</span><span class="hl opt">(</span>dists<span class="hl opt">[</span>i<span class="hl opt">])</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Distances from fit:</span><span class="hl esc">\n</span><span class="hl str">'</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'{} K : {:.5f} , '</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>c_fit<span class="hl opt">[</span>i<span class="hl opt">],</span> error_1<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'{} K : {:.5f}'</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>c_fit<span class="hl opt">[</span>i<span class="hl opt">-</span><span class="hl num">1</span><span class="hl opt">],</span> error_2<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> find bad index</span>
<span class="hl str"> note that in python false = 0 and true = 1</span>
<span class="hl str"> """</span>
bad <span class="hl opt">=</span> i <span class="hl opt">- (</span>error_1 <span class="hl opt"><</span> error_2<span class="hl opt">)</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Point at {} K deleted as '</span><span class="hl opt">.</span><span class="hl kwd">format</span><span class="hl opt">(</span>c_fit<span class="hl opt">[</span>bad<span class="hl opt">])</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'it is furthest from fit'</span>
<span class="hl str">"""</span>
<span class="hl str"> delete bad point</span>
<span class="hl str"> """</span>
r_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">delete</span><span class="hl opt">(</span>r_fit<span class="hl opt">,</span> bad<span class="hl opt">)</span>
b_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">delete</span><span class="hl opt">(</span>b_fit<span class="hl opt">,</span> bad<span class="hl opt">)</span>
c_fit <span class="hl opt">=</span> np<span class="hl opt">.</span><span class="hl kwd">delete</span><span class="hl opt">(</span>c_fit<span class="hl opt">,</span> bad<span class="hl opt">).</span><span class="hl kwd">astype</span><span class="hl opt">(</span>np<span class="hl opt">.</span>uint16<span class="hl opt">)</span>
<span class="hl str">"""</span>
<span class="hl str"> note that if a point has been discarded then the length has decreased</span>
<span class="hl str"> by one, meaning that decreasing the index by one will reassess the kept</span>
<span class="hl str"> point against the next point. It is therefore possible, in theory, for</span>
<span class="hl str"> two adjacent points to be discarded, although probably rare</span>
<span class="hl str"> """</span>
i <span class="hl opt">-=</span> <span class="hl num">1</span>
<span class="hl str">"""</span>
<span class="hl str"> return formatted ct curve, ordered by increasing colour temperature</span>
<span class="hl str"> """</span>
ct_curve <span class="hl opt">=</span> <span class="hl kwb">list</span><span class="hl opt">(</span>np<span class="hl opt">.</span><span class="hl kwd">array</span><span class="hl opt">(</span><span class="hl kwb">list</span><span class="hl opt">(</span><span class="hl kwb">zip</span><span class="hl opt">(</span>b_fit<span class="hl opt">,</span> r_fit<span class="hl opt">,</span> c_fit<span class="hl opt">))).</span><span class="hl kwd">flatten</span><span class="hl opt">())[::-</span><span class="hl num">1</span><span class="hl opt">]</span>
Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">'</span><span class="hl esc">\n</span><span class="hl str">Final CT curve:'</span>