Remove internal and unsupported features
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@ -113,24 +113,3 @@ The `mean(distribution)` function gives the mean (expected value) of a distribut
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The `sample(distribution)` samples a given distribution:
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The `sample(distribution)` samples a given distribution:
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<SquiggleEditor initialSquiggleString="sample(normal(0, 10))" />
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<SquiggleEditor initialSquiggleString="sample(normal(0, 10))" />
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### Exponential Scaling
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The `scaleExp(distribution, factor)` function scales a distribution's PDF exponentially
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in the y axis.
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<SquiggleEditor initialSquiggleString="scaleExp(normal(10, 10), 10)" />
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### Multiply Scaling
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The `scaleMultiply(distribution, factor)` function scales a distribution's PDF by multiplication
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in the y axis.
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<SquiggleEditor initialSquiggleString="scaleMultiply(normal(10, 10), 2)" />
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### Log scaling
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The `scaleLog(distribution, factor)` function scales a distribution's PDF by the log
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function in the y axis
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<SquiggleEditor initialSquiggleString="scaleLog(normal(10, 10), 2)" />
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@ -35,17 +35,3 @@ Squiggle supports functions, including the rendering of functions:
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ozzie_estimate
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ozzie_estimate
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`} />
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`} />
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## Squiggle units
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Squiggle supports using suffixes at the end of numbers to refer to units:
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<SquiggleEditor initialSquiggleString={`
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us_economy_2018 = (10.5 to 10.9)T
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growth_rate = 1.08 to 1.2
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us_economy(t) = us_economy_2018 * (growth_rate^t)
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us_population_2019 = 320M to 330M
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us_population_growth_rate = 1.01 to 1.1
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us_population(t) = us_population_2019 * (us_population_growth_rate^t)
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gdp_per_person(t) = us_economy(t)/us_population(t)
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gdp_per_person`} />
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