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Merge branch 'dev-patch' into dev-minor
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CHANGELOG.md

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- Change: Large rewrite of the `image_texture` class. Now handles image loading too. (#434)
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# v3.0.3 (in progress)
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### _In One Weekend_
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- Fix: Correct typo in "What's next?" list to rejoin split paragraph on "Lights." Adjust numbering
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in rest of list.
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# v3.0.2 (2020-04-11)
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books/RayTracingInOneWeekend.html

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You now have a cool ray tracer! What next?
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1. Lights. You can do this explicitly, by sending shadow rays to lights. Or it can be done
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implicitly by making some objects emit light,
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1. Lights. You can do this explicitly, by sending shadow rays to lights, or it can be done
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implicitly by making some objects emit light, biasing scattered rays toward them, and then
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downweighting those rays to cancel out the bias. Both work. I am in the minority in favoring
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the latter approach.
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2. Biasing scattered rays toward them, and then downweighting those rays to cancel out the bias.
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Both work. I am in the minority in favoring the latter approach.
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3. Triangles. Most cool models are in triangle form. The model I/O is the worst and almost
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2. Triangles. Most cool models are in triangle form. The model I/O is the worst and almost
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everybody tries to get somebody else’s code to do this.
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4. Surface textures. This lets you paste images on like wall paper. Pretty easy and a good thing
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3. Surface textures. This lets you paste images on like wall paper. Pretty easy and a good thing
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to do.
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5. Solid textures. Ken Perlin has his code online. Andrew Kensler has some very cool info at his
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4. Solid textures. Ken Perlin has his code online. Andrew Kensler has some very cool info at his
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blog.
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6. Volumes and media. Cool stuff and will challenge your software architecture. I favor making
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5. Volumes and media. Cool stuff and will challenge your software architecture. I favor making
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volumes have the hittable interface and probabilistically have intersections based on density.
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Your rendering code doesn’t even have to know it has volumes with that method.
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7. Parallelism. Run $N$ copies of your code on $N$ cores with different random seeds. Average the
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6. Parallelism. Run $N$ copies of your code on $N$ cores with different random seeds. Average the
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$N$ runs. This averaging can also be done hierarchically where $N/2$ pairs can be averaged to
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get $N/4$ images, and pairs of those can be averaged. That method of parallelism should extend
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well into the thousands of cores with very little coding.

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