# SPDX-License-Identifier: CC-BY-SA-4.0

@INCLUDE_PATH          = @TOP_BUILDDIR@/Documentation
@INCLUDE               = Doxyfile-common

HIDE_UNDOC_CLASSES     = YES
HIDE_UNDOC_MEMBERS     = YES
HTML_OUTPUT            = api-html
INTERNAL_DOCS          = NO

INPUT                  = "@TOP_SRCDIR@/Documentation" \
                         ${inputs}

EXCLUDE                = @TOP_SRCDIR@/include/libcamera/base/class.h \
                         @TOP_SRCDIR@/include/libcamera/base/object.h \
                         @TOP_SRCDIR@/include/libcamera/base/span.h \
                         @TOP_SRCDIR@/src/libcamera/base/class.cpp \
                         @TOP_SRCDIR@/src/libcamera/base/object.cpp

PREDEFINED            += __DOXYGEN_PUBLIC__
form'><form method='get'>
<input type='hidden' name='id' value='af088b88f50d4b1ba0e0688c18d561becefc5bbf'/><select name='h' onchange='this.form.submit();'>
<option value='master'>master</option>
</select> <input type='submit' value='switch'/></form></td></tr>
<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&amp;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&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>tree</a><a href='/libcamera/libcamera.git/commit/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>commit</a><a href='/libcamera/libcamera.git/diff/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&amp;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=''/>
<input type='submit' value='search'/>
</form>
</td></tr></table>
<div class='path'>path: <a href='/libcamera/libcamera.git/tree/?h=v0.0.3&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>root</a>/<a href='/libcamera/libcamera.git/tree/utils?h=v0.0.3&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>utils</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi?h=v0.0.3&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>raspberrypi</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi/ctt?h=v0.0.3&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>ctt</a>/<a href='/libcamera/libcamera.git/tree/utils/raspberrypi/ctt/ctt_awb.py?h=v0.0.3&amp;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&amp;id=af088b88f50d4b1ba0e0688c18d561becefc5bbf'>plain</a>)
<table summary='blob content' class='blob'>
<tr><td class='linenumbers'><pre><a id='n1' href='#n1'>1</a>
<a id='n2' href='#n2'>2</a>
<a id='n3' href='#n3'>3</a>
<a id='n4' href='#n4'>4</a>
<a id='n5' href='#n5'>5</a>
<a id='n6' href='#n6'>6</a>
<a id='n7' href='#n7'>7</a>
<a id='n8' href='#n8'>8</a>
<a id='n9' href='#n9'>9</a>
<a id='n10' href='#n10'>10</a>
<a id='n11' href='#n11'>11</a>
<a id='n12' href='#n12'>12</a>
<a id='n13' href='#n13'>13</a>
<a id='n14' href='#n14'>14</a>
<a id='n15' href='#n15'>15</a>
<a id='n16' href='#n16'>16</a>
<a id='n17' href='#n17'>17</a>
<a id='n18' href='#n18'>18</a>
<a id='n19' href='#n19'>19</a>
<a id='n20' href='#n20'>20</a>
<a id='n21' href='#n21'>21</a>
<a id='n22' href='#n22'>22</a>
<a id='n23' href='#n23'>23</a>
<a id='n24' href='#n24'>24</a>
<a id='n25' href='#n25'>25</a>
<a id='n26' href='#n26'>26</a>
<a id='n27' href='#n27'>27</a>
<a id='n28' href='#n28'>28</a>
<a id='n29' href='#n29'>29</a>
<a id='n30' href='#n30'>30</a>
<a id='n31' href='#n31'>31</a>
<a id='n32' href='#n32'>32</a>
<a id='n33' href='#n33'>33</a>
<a id='n34' href='#n34'>34</a>
<a id='n35' href='#n35'>35</a>
<a id='n36' href='#n36'>36</a>
<a id='n37' href='#n37'>37</a>
<a id='n38' href='#n38'>38</a>
<a id='n39' href='#n39'>39</a>
<a id='n40' href='#n40'>40</a>
<a id='n41' href='#n41'>41</a>
<a id='n42' href='#n42'>42</a>
<a id='n43' href='#n43'>43</a>
<a id='n44' href='#n44'>44</a>
<a id='n45' href='#n45'>45</a>
<a id='n46' href='#n46'>46</a>
<a id='n47' href='#n47'>47</a>
<a id='n48' href='#n48'>48</a>
<a id='n49' href='#n49'>49</a>
<a id='n50' href='#n50'>50</a>
<a id='n51' href='#n51'>51</a>
<a id='n52' href='#n52'>52</a>
<a id='n53' href='#n53'>53</a>
<a id='n54' href='#n54'>54</a>
<a id='n55' href='#n55'>55</a>
<a id='n56' href='#n56'>56</a>
<a id='n57' href='#n57'>57</a>
<a id='n58' href='#n58'>58</a>
<a id='n59' href='#n59'>59</a>
<a id='n60' href='#n60'>60</a>
<a id='n61' href='#n61'>61</a>
<a id='n62' href='#n62'>62</a>
<a id='n63' href='#n63'>63</a>
<a id='n64' href='#n64'>64</a>
<a id='n65' href='#n65'>65</a>
<a id='n66' href='#n66'>66</a>
<a id='n67' href='#n67'>67</a>
<a id='n68' href='#n68'>68</a>
<a id='n69' href='#n69'>69</a>
<a id='n70' href='#n70'>70</a>
<a id='n71' href='#n71'>71</a>
<a id='n72' href='#n72'>72</a>
<a id='n73' href='#n73'>73</a>
<a id='n74' href='#n74'>74</a>
<a id='n75' href='#n75'>75</a>
<a id='n76' href='#n76'>76</a>
<a id='n77' href='#n77'>77</a>
<a id='n78' href='#n78'>78</a>
<a id='n79' href='#n79'>79</a>
<a id='n80' href='#n80'>80</a>
<a id='n81' href='#n81'>81</a>
<a id='n82' href='#n82'>82</a>
<a id='n83' href='#n83'>83</a>
<a id='n84' href='#n84'>84</a>
<a id='n85' href='#n85'>85</a>
<a id='n86' href='#n86'>86</a>
<a id='n87' href='#n87'>87</a>
<a id='n88' href='#n88'>88</a>
<a id='n89' href='#n89'>89</a>
<a id='n90' href='#n90'>90</a>
<a id='n91' href='#n91'>91</a>
<a id='n92' href='#n92'>92</a>
<a id='n93' href='#n93'>93</a>
<a id='n94' href='#n94'>94</a>
<a id='n95' href='#n95'>95</a>
<a id='n96' href='#n96'>96</a>
<a id='n97' href='#n97'>97</a>
<a id='n98' href='#n98'>98</a>
<a id='n99' href='#n99'>99</a>
<a id='n100' href='#n100'>100</a>
<a id='n101' href='#n101'>101</a>
<a id='n102' href='#n102'>102</a>
<a id='n103' href='#n103'>103</a>
<a id='n104' href='#n104'>104</a>
<a id='n105' href='#n105'>105</a>
<a id='n106' href='#n106'>106</a>
<a id='n107' href='#n107'>107</a>
<a id='n108' href='#n108'>108</a>
<a id='n109' href='#n109'>109</a>
<a id='n110' href='#n110'>110</a>
<a id='n111' href='#n111'>111</a>
<a id='n112' href='#n112'>112</a>
<a id='n113' href='#n113'>113</a>
<a id='n114' href='#n114'>114</a>
<a id='n115' href='#n115'>115</a>
<a id='n116' href='#n116'>116</a>
<a id='n117' href='#n117'>117</a>
<a id='n118' href='#n118'>118</a>
<a id='n119' href='#n119'>119</a>
<a id='n120' href='#n120'>120</a>
<a id='n121' href='#n121'>121</a>
<a id='n122' href='#n122'>122</a>
<a id='n123' href='#n123'>123</a>
<a id='n124' href='#n124'>124</a>
<a id='n125' href='#n125'>125</a>
<a id='n126' href='#n126'>126</a>
<a id='n127' href='#n127'>127</a>
<a id='n128' href='#n128'>128</a>
<a id='n129' href='#n129'>129</a>
<a id='n130' href='#n130'>130</a>
<a id='n131' href='#n131'>131</a>
<a id='n132' href='#n132'>132</a>
<a id='n133' href='#n133'>133</a>
<a id='n134' href='#n134'>134</a>
<a id='n135' href='#n135'>135</a>
<a id='n136' href='#n136'>136</a>
<a id='n137' href='#n137'>137</a>
<a id='n138' href='#n138'>138</a>
<a id='n139' href='#n139'>139</a>
<a id='n140' href='#n140'>140</a>
<a id='n141' href='#n141'>141</a>
<a id='n142' href='#n142'>142</a>
<a id='n143' href='#n143'>143</a>
<a id='n144' href='#n144'>144</a>
<a id='n145' href='#n145'>145</a>
<a id='n146' href='#n146'>146</a>
<a id='n147' href='#n147'>147</a>
<a id='n148' href='#n148'>148</a>
<a id='n149' href='#n149'>149</a>
<a id='n150' href='#n150'>150</a>
<a id='n151' href='#n151'>151</a>
<a id='n152' href='#n152'>152</a>
<a id='n153' href='#n153'>153</a>
<a id='n154' href='#n154'>154</a>
<a id='n155' href='#n155'>155</a>
<a id='n156' href='#n156'>156</a>
<a id='n157' href='#n157'>157</a>
<a id='n158' href='#n158'>158</a>
<a id='n159' href='#n159'>159</a>
<a id='n160' href='#n160'>160</a>
<a id='n161' href='#n161'>161</a>
<a id='n162' href='#n162'>162</a>
<a id='n163' href='#n163'>163</a>
<a id='n164' href='#n164'>164</a>
<a id='n165' href='#n165'>165</a>
<a id='n166' href='#n166'>166</a>
<a id='n167' href='#n167'>167</a>
<a id='n168' href='#n168'>168</a>
<a id='n169' href='#n169'>169</a>
<a id='n170' href='#n170'>170</a>
<a id='n171' href='#n171'>171</a>
<a id='n172' href='#n172'>172</a>
<a id='n173' href='#n173'>173</a>
<a id='n174' href='#n174'>174</a>
<a id='n175' href='#n175'>175</a>
<a id='n176' href='#n176'>176</a>
<a id='n177' href='#n177'>177</a>
<a id='n178' href='#n178'>178</a>
<a id='n179' href='#n179'>179</a>
<a id='n180' href='#n180'>180</a>
<a id='n181' href='#n181'>181</a>
<a id='n182' href='#n182'>182</a>
<a id='n183' href='#n183'>183</a>
<a id='n184' href='#n184'>184</a>
<a id='n185' href='#n185'>185</a>
<a id='n186' href='#n186'>186</a>
<a id='n187' href='#n187'>187</a>
<a id='n188' href='#n188'>188</a>
<a id='n189' href='#n189'>189</a>
<a id='n190' href='#n190'>190</a>
<a id='n191' href='#n191'>191</a>
<a id='n192' href='#n192'>192</a>
<a id='n193' href='#n193'>193</a>
<a id='n194' href='#n194'>194</a>
<a id='n195' href='#n195'>195</a>
<a id='n196' href='#n196'>196</a>
<a id='n197' href='#n197'>197</a>
<a id='n198' href='#n198'>198</a>
<a id='n199' href='#n199'>199</a>
<a id='n200' href='#n200'>200</a>
<a id='n201' href='#n201'>201</a>
<a id='n202' href='#n202'>202</a>
<a id='n203' href='#n203'>203</a>
<a id='n204' href='#n204'>204</a>
<a id='n205' href='#n205'>205</a>
<a id='n206' href='#n206'>206</a>
<a id='n207' href='#n207'>207</a>
<a id='n208' href='#n208'>208</a>
<a id='n209' href='#n209'>209</a>
<a id='n210' href='#n210'>210</a>
<a id='n211' href='#n211'>211</a>
<a id='n212' href='#n212'>212</a>
<a id='n213' href='#n213'>213</a>
<a id='n214' href='#n214'>214</a>
<a id='n215' href='#n215'>215</a>
<a id='n216' href='#n216'>216</a>
<a id='n217' href='#n217'>217</a>
<a id='n218' href='#n218'>218</a>
<a id='n219' href='#n219'>219</a>
<a id='n220' href='#n220'>220</a>
<a id='n221' href='#n221'>221</a>
<a id='n222' href='#n222'>222</a>
<a id='n223' href='#n223'>223</a>
<a id='n224' href='#n224'>224</a>
<a id='n225' href='#n225'>225</a>
<a id='n226' href='#n226'>226</a>
<a id='n227' href='#n227'>227</a>
<a id='n228' href='#n228'>228</a>
<a id='n229' href='#n229'>229</a>
<a id='n230' href='#n230'>230</a>
<a id='n231' href='#n231'>231</a>
<a id='n232' href='#n232'>232</a>
<a id='n233' href='#n233'>233</a>
<a id='n234' href='#n234'>234</a>
<a id='n235' href='#n235'>235</a>
<a id='n236' href='#n236'>236</a>
<a id='n237' href='#n237'>237</a>
<a id='n238' href='#n238'>238</a>
<a id='n239' href='#n239'>239</a>
<a id='n240' href='#n240'>240</a>
<a id='n241' href='#n241'>241</a>
<a id='n242' href='#n242'>242</a>
<a id='n243' href='#n243'>243</a>
<a id='n244' href='#n244'>244</a>
<a id='n245' href='#n245'>245</a>
<a id='n246' href='#n246'>246</a>
<a id='n247' href='#n247'>247</a>
<a id='n248' href='#n248'>248</a>
<a id='n249' href='#n249'>249</a>
<a id='n250' href='#n250'>250</a>
<a id='n251' href='#n251'>251</a>
<a id='n252' href='#n252'>252</a>
<a id='n253' href='#n253'>253</a>
<a id='n254' href='#n254'>254</a>
<a id='n255' href='#n255'>255</a>
<a id='n256' href='#n256'>256</a>
<a id='n257' href='#n257'>257</a>
<a id='n258' href='#n258'>258</a>
<a id='n259' href='#n259'>259</a>
<a id='n260' href='#n260'>260</a>
<a id='n261' href='#n261'>261</a>
<a id='n262' href='#n262'>262</a>
<a id='n263' href='#n263'>263</a>
<a id='n264' href='#n264'>264</a>
<a id='n265' href='#n265'>265</a>
<a id='n266' href='#n266'>266</a>
<a id='n267' href='#n267'>267</a>
<a id='n268' href='#n268'>268</a>
<a id='n269' href='#n269'>269</a>
<a id='n270' href='#n270'>270</a>
<a id='n271' href='#n271'>271</a>
<a id='n272' href='#n272'>272</a>
<a id='n273' href='#n273'>273</a>
<a id='n274' href='#n274'>274</a>
<a id='n275' href='#n275'>275</a>
<a id='n276' href='#n276'>276</a>
<a id='n277' href='#n277'>277</a>
<a id='n278' href='#n278'>278</a>
<a id='n279' href='#n279'>279</a>
<a id='n280' href='#n280'>280</a>
<a id='n281' href='#n281'>281</a>
<a id='n282' href='#n282'>282</a>
<a id='n283' href='#n283'>283</a>
<a id='n284' href='#n284'>284</a>
<a id='n285' href='#n285'>285</a>
<a id='n286' href='#n286'>286</a>
<a id='n287' href='#n287'>287</a>
<a id='n288' href='#n288'>288</a>
<a id='n289' href='#n289'>289</a>
<a id='n290' href='#n290'>290</a>
<a id='n291' href='#n291'>291</a>
<a id='n292' href='#n292'>292</a>
<a id='n293' href='#n293'>293</a>
<a id='n294' href='#n294'>294</a>
<a id='n295' href='#n295'>295</a>
<a id='n296' href='#n296'>296</a>
<a id='n297' href='#n297'>297</a>
<a id='n298' href='#n298'>298</a>
<a id='n299' href='#n299'>299</a>
<a id='n300' href='#n300'>300</a>
<a id='n301' href='#n301'>301</a>
<a id='n302' href='#n302'>302</a>
<a id='n303' href='#n303'>303</a>
<a id='n304' href='#n304'>304</a>
<a id='n305' href='#n305'>305</a>
<a id='n306' href='#n306'>306</a>
<a id='n307' href='#n307'>307</a>
<a id='n308' href='#n308'>308</a>
<a id='n309' href='#n309'>309</a>
<a id='n310' href='#n310'>310</a>
<a id='n311' href='#n311'>311</a>
<a id='n312' href='#n312'>312</a>
<a id='n313' href='#n313'>313</a>
<a id='n314' href='#n314'>314</a>
<a id='n315' href='#n315'>315</a>
<a id='n316' href='#n316'>316</a>
<a id='n317' href='#n317'>317</a>
<a id='n318' href='#n318'>318</a>
<a id='n319' href='#n319'>319</a>
<a id='n320' href='#n320'>320</a>
<a id='n321' href='#n321'>321</a>
<a id='n322' href='#n322'>322</a>
<a id='n323' href='#n323'>323</a>
<a id='n324' href='#n324'>324</a>
<a id='n325' href='#n325'>325</a>
<a id='n326' href='#n326'>326</a>
<a id='n327' href='#n327'>327</a>
<a id='n328' href='#n328'>328</a>
<a id='n329' href='#n329'>329</a>
<a id='n330' href='#n330'>330</a>
<a id='n331' href='#n331'>331</a>
<a id='n332' href='#n332'>332</a>
<a id='n333' href='#n333'>333</a>
<a id='n334' href='#n334'>334</a>
<a id='n335' href='#n335'>335</a>
<a id='n336' href='#n336'>336</a>
<a id='n337' href='#n337'>337</a>
<a id='n338' href='#n338'>338</a>
<a id='n339' href='#n339'>339</a>
<a id='n340' href='#n340'>340</a>
<a id='n341' href='#n341'>341</a>
<a id='n342' href='#n342'>342</a>
<a id='n343' href='#n343'>343</a>
<a id='n344' href='#n344'>344</a>
<a id='n345' href='#n345'>345</a>
<a id='n346' href='#n346'>346</a>
<a id='n347' href='#n347'>347</a>
<a id='n348' href='#n348'>348</a>
<a id='n349' href='#n349'>349</a>
<a id='n350' href='#n350'>350</a>
<a id='n351' href='#n351'>351</a>
<a id='n352' href='#n352'>352</a>
<a id='n353' href='#n353'>353</a>
<a id='n354' href='#n354'>354</a>
<a id='n355' href='#n355'>355</a>
<a id='n356' href='#n356'>356</a>
<a id='n357' href='#n357'>357</a>
<a id='n358' href='#n358'>358</a>
<a id='n359' href='#n359'>359</a>
<a id='n360' href='#n360'>360</a>
<a id='n361' href='#n361'>361</a>
<a id='n362' href='#n362'>362</a>
<a id='n363' href='#n363'>363</a>
<a id='n364' href='#n364'>364</a>
<a id='n365' href='#n365'>365</a>
<a id='n366' href='#n366'>366</a>
<a id='n367' href='#n367'>367</a>
<a id='n368' href='#n368'>368</a>
<a id='n369' href='#n369'>369</a>
<a id='n370' href='#n370'>370</a>
<a id='n371' href='#n371'>371</a>
<a id='n372' href='#n372'>372</a>
<a id='n373' href='#n373'>373</a>
<a id='n374' href='#n374'>374</a>
<a id='n375' href='#n375'>375</a>
<a id='n376' href='#n376'>376</a>
</pre></td>
<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">&quot;&quot;&quot;</span>
<span class="hl str">obtain piecewise linear approximation for colour curve</span>
<span class="hl str">&quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">    condense alsc calibration tables into one dictionary</span>
<span class="hl str">    &quot;&quot;&quot;</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">&apos;table&apos;</span><span class="hl opt">]</span>
            cb_tab <span class="hl opt">=</span> cb<span class="hl opt">[</span><span class="hl str">&apos;table&apos;</span><span class="hl opt">]</span>
            <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">            normalise tables so min value is 1</span>
<span class="hl str">            &quot;&quot;&quot;</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">&apos;ct&apos;</span><span class="hl opt">]] = [</span>cr_tab<span class="hl opt">,</span> cb_tab<span class="hl opt">]</span>
    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    obtain data from greyscale macbeth patches</span>
<span class="hl str">    &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Processing &apos;</span><span class="hl opt">+</span>Img<span class="hl opt">.</span>name
        <span class="hl str">&quot;&quot;&quot;</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">        &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">        calculate ratio of r, b to g</span>
<span class="hl str">        &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span>       <span class="hl str">r : {:.4f}       b : {:.4f}&apos;</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">&quot;&quot;&quot;</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">        &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span>   <span class="hl str">r_hat : {:.4f}   b_hat : {:.4f}&apos;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">&apos;</span>

    Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">&apos;</span><span class="hl esc">\n</span><span class="hl str">Finished processing images&apos;</span>
    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    sort all lits simultaneously by r_hat</span>
<span class="hl str">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">    unzip tuples ready for processing</span>
<span class="hl str">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">    fit quadratic fit to r_g hat and b_g_hat</span>
<span class="hl str">    &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Fit quadratic curve in hatspace&apos;</span>
    <span class="hl str">&quot;&quot;&quot;</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">    &quot;&quot;&quot;</span>
    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    define fit function</span>
<span class="hl str">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</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">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</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">        &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">        perform optimisation with scipy.optmisie.fmin</span>
<span class="hl str">        &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">        dehat</span>
<span class="hl str">        &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">        calculate euclidean distance in dehatspace</span>
<span class="hl str">        &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">        return negative if point is below the fit curve</span>
<span class="hl str">        &quot;&quot;&quot;</span>
        <span class="hl kwa">if</span> <span class="hl opt">(</span>x<span class="hl opt">+</span>y<span class="hl opt">) &gt; (</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Found closest point on fit line to each point in dehatspace&apos;</span>
    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    calculate wiggle factors in awb. 10% added since this is an upper bound</span>
<span class="hl str">    &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Transverse pos : {:.5f}&apos;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Transverse neg : {:.5f}&apos;</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">&quot;&quot;&quot;</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">    &quot;&quot;&quot;</span>
    <span class="hl kwa">if</span> transverse_pos <span class="hl opt">&lt;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Forced transverse pos to 0.01&apos;</span>
    <span class="hl kwa">if</span> transverse_neg <span class="hl opt">&lt;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Forced transverse neg to 0.01&apos;</span>

    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    generate new b_hat values at each r_hat according to fit</span>
<span class="hl str">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">    transform from hatspace to dehatspace</span>
<span class="hl str">    &quot;&quot;&quot;</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">&quot;&quot;&quot;</span>
<span class="hl str">    round to 4dp</span>
<span class="hl str">    &quot;&quot;&quot;</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">&lt;=</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">&gt;=</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">&lt;=</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">&gt;=</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">&quot;&quot;&quot;</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">    &quot;&quot;&quot;</span>
    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    iterate backwards over list for easier indexing</span>
<span class="hl str">    &quot;&quot;&quot;</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">&gt;</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">] &gt;</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">&apos;</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">&apos;</span>
            Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">&apos;{} K at r = {} to &apos;</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">&apos;{} K at r = {}&apos;</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">&quot;&quot;&quot;</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">            &quot;&quot;&quot;</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">&apos;</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">&apos;</span>
            Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">&apos;{} K : {:.5f} , &apos;</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">&apos;{} K : {:.5f}&apos;</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">&quot;&quot;&quot;</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">            &quot;&quot;&quot;</span>
            bad <span class="hl opt">=</span> i <span class="hl opt">- (</span>error_1 <span class="hl opt">&lt;</span> error_2<span class="hl opt">)</span>
            Cam<span class="hl opt">.</span>log <span class="hl opt">+=</span> <span class="hl str">&apos;</span><span class="hl esc">\n</span><span class="hl str">Point at {} K deleted as &apos;</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">&apos;it is furthest from fit&apos;</span>
            <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">            delete bad point</span>
<span class="hl str">            &quot;&quot;&quot;</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">&quot;&quot;&quot;</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">        &quot;&quot;&quot;</span>
        i <span class="hl opt">-=</span> <span class="hl num">1</span>

    <span class="hl str">&quot;&quot;&quot;</span>
<span class="hl str">    return formatted ct curve, ordered by increasing colour temperature</span>
<span class="hl str">    &quot;&quot;&quot;</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">&apos;</span><span class="hl esc">\n</span><span class="hl str">Final CT curve:&apos;</span>