forked from kscience/kmath
Ignore print test
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@ -1,6 +1,5 @@
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package space.kscience.kmath.tensors.core
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package space.kscience.kmath.tensors.core
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.nd.as1D
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import space.kscience.kmath.nd.as1D
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import space.kscience.kmath.samplers.GaussianSampler
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import space.kscience.kmath.samplers.GaussianSampler
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import space.kscience.kmath.stat.RandomGenerator
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import space.kscience.kmath.stat.RandomGenerator
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@ -72,7 +71,7 @@ internal inline fun format(value: Double, digits: Int = 4): String {
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val lead = value / ten.pow(order)
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val lead = value / ten.pow(order)
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val leadDisplay = round(lead*ten.pow(digits)) / ten.pow(digits)
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val leadDisplay = round(lead*ten.pow(digits)) / ten.pow(digits)
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val orderDisplay = if(order == 0) "" else if(order > 0) "E+$order" else "E$order"
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val orderDisplay = if(order == 0) "" else if(order > 0) "E+$order" else "E$order"
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val valueDisplay = "${leadDisplay}$orderDisplay"
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val valueDisplay = "$leadDisplay$orderDisplay"
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val res = if(value < 0.0) valueDisplay else " $valueDisplay"
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val res = if(value < 0.0) valueDisplay else " $valueDisplay"
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val fLength = digits + 6
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val fLength = digits + 6
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val endSpace = " ".repeat(fLength - res.length)
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val endSpace = " ".repeat(fLength - res.length)
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@ -1,8 +1,10 @@
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package space.kscience.kmath.tensors.core
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package space.kscience.kmath.tensors.core
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import kotlinx.coroutines.InternalCoroutinesApi
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import space.kscience.kmath.nd.as1D
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import space.kscience.kmath.nd.as1D
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import space.kscience.kmath.nd.as2D
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import space.kscience.kmath.nd.as2D
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import space.kscience.kmath.structures.toDoubleArray
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import space.kscience.kmath.structures.toDoubleArray
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import kotlin.test.Ignore
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import kotlin.test.Test
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import kotlin.test.Test
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import kotlin.test.assertEquals
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import kotlin.test.assertEquals
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import kotlin.test.assertTrue
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import kotlin.test.assertTrue
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@ -47,7 +49,7 @@ class TestDoubleTensor {
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}
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}
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}
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}
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@Test
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@Test @Ignore
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fun toStringTest() = DoubleTensorAlgebra {
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fun toStringTest() = DoubleTensorAlgebra {
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val tensor = randNormal(intArrayOf(2,3))
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val tensor = randNormal(intArrayOf(2,3))
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println(tensor)
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println(tensor)
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