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https://github.com/csharpee/Map-Projections.git
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5e01e339b9
I tidied up the documentation on the BFGS stuff and updated my maps and defaults to be informed by the new optimizations.
45 lines
3.3 KiB
Plaintext
45 lines
3.3 KiB
Plaintext
We got the best Tobler Hyperelliptical projections using:
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t0=30.506558786136164; t1=0.3975383525206906; t2=3.997720064276123; (2.5245792765063137E-4, 0.49042998348577777)
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t0=30.53431423862674; t1=0.4062974245671901; t2=3.951968307864351; (2.3634131999763095E-4, 0.490413331660892)
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t0=30.534996054570122; t1=0.40982217940437315; t2=3.9388293231446183; (2.3084286442176676E-4, 0.49040541967506746)
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t0=30.526861993190156; t1=0.41289331825953984; t2=3.948490584936325; (2.2823612925236138E-4, 0.4903943344342276)
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t0=30.171506742208667; t1=0.5447325922534694; t2=3.3045726206106174; (7.472092115181078E-5, 0.4905648364049878)
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t0=30.472407744588843; t1=0.4624100943196009; t2=3.7058554158579327; (1.6026863026488797E-4, 0.4903554923556594)
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t0=30.772855981645655; t1=0.3505145046575816; t2=4.142699303717857; (2.0497084855872877E-4, 0.4905873681746431)
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t0=30.597300348860273; t1=0.34295825057460816; t2=4.058216809727585; (2.1112594263567147E-4, 0.49068831665768275)
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t0=0.0; t1=1.0; t2=1.0; (2.3111608934529733E-8, 0.6137565646410882)
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We got the best Winkel Tripel projections using:
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t0=17.957933140628256; (0.25932019508548493, 0.36444804618226867)
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t0=19.578229322577233; (0.2586497441950308, 0.3644980527902062)
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t0=21.663672947605303; (0.2576915304376235, 0.36472868044150314)
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t0=24.552760247498448; (0.2561800301642924, 0.36543738102508005)
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t0=28.935732586336282; (0.2534534735464852, 0.367639315334747)
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t0=36.48524369490269; (0.2473866667743297, 0.3758665329854081)
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t0=89.64383463941283; (0.07078405279816037, 0.8459966547063894)
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t0=90.20684487459667; (0.06743617153928232, 0.8587166159021128)
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t0=90.31210519110017; (0.06728093742152608, 0.8611571986133976)
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We got the best TetraPower projections using:
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t0=0.7251510971705017; t1=0.8799415807400688; t2=0.8572850133622626; (0.422750395775632, 0.13826331216471252)
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t0=0.7442516235907949; t1=0.9031123519136701; t2=0.8650260337289639; (0.41666407130907396, 0.13643981232990932)
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t0=0.7995356266967016; t1=0.877198483919957; t2=0.8775689219350017; (0.4061846891910591, 0.13545117616364158)
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t0=0.843813906814002; t1=0.9055863648561882; t2=0.9068219650428548; (0.39168587855607145, 0.13590934103565014)
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t0=1.0887347058906243; t1=1.1906232589287455; t2=1.0068156358843527; (0.3136201572259122, 0.20723377252523384)
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t0=1.8578831572159344; t1=1.3230427148676347; t2=1.3541168911984933; (0.09659313794029525, 0.5053885132535845)
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t0=1.8609065719598639; t1=1.2417845624360808; t2=1.4437856176727957; (0.07501424763978838, 0.5451384929588722)
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t0=1.8892521212625646; t1=1.1793474367429049; t2=1.5043789437785882; (0.06455989310517463, 0.5775973717174138)
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t0=1.9077945281918272; t1=1.1571046889875514; t2=1.5308152214270465; (0.062421585098500404, 0.5926588448712382)
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We got the best AuthaPower projections using:
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t0=0.5500000000000003; (0.41312749977668417, 0.08828966383834298)
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t0=0.5500000000000003; (0.41312749977668417, 0.08828966383834298)
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t0=0.5500000000000003; (0.41312749977668417, 0.08828966383834298)
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t0=0.5750000000000003; (0.3876223544028035, 0.0968718822112939)
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t0=0.6000000000000003; (0.3621275092593102, 0.1161981251407432)
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t0=0.9250000000000006; (0.04143197931427, 0.5374514903103988)
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t0=0.9500000000000006; (0.030342030927343812, 0.5653681878864117)
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t0=0.9500000000000006; (0.030342030927343812, 0.5653681878864117)
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t0=0.9500000000000006; (0.030342030927343812, 0.5653681878864117)
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