{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Kotlin-numpy library demo\n",
"\n",
"Follow the project repository: https://github.com/Kotlin/kotlin-numpy"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%use numpy(0.1.4)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating Arrays"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"val a = array(arrayOf(1L, 2L, 3L))\n",
"val b = array<Double>(listOf(listOf(1.5f, 2f, 3f), listOf(4f, 5f, 6f)))\n",
"val c = array<Double>(\n",
" listOf(\n",
" listOf(listOf(1.5f, 2f, 3f), listOf(4f, 5f, 6f)),\n",
" listOf(listOf(3f, 2f, 1f), listOf(4f, 5f, 6f))\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Initial Placeholders"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1.4012985e-45 0.0000000e+00]\n",
" [2.0743408e+01 4.5909340e-41]\n",
" [2.0743408e+01 4.5909340e-41]]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"zeros<Int>(3, 4) // Create an array of zeros\n",
"ones<Short>(2, 3, 4) // Create an array of ones\n",
"val d = arange<Long>(10, 25, 5) // Create an array of evenly spaced values (step value)\n",
"\n",
"linspace<Float>(0, 2, 9) // Create an array of evenly spaced values (number of samples)\n",
"\n",
"val e = full(intArrayOf(2, 2), 7L) // Create a constant array\n",
"val f = eye<Double>(2) // Create a 2x2 identity matrix\n",
"Random.random(2, 2) // Create an array with random values\n",
"empty<Float>(3, 2) // Create an empty array"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## I/0"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"// a.toFile(\"my_array\")\n",
"// fromfile<Long>(\"my_array\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Inspecting Your Array"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1 2 3]\n",
" [4 5 6]]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a.shape // Array domensions\n",
"b.ndim // Number of array dimensions\n",
"e.size // Number of array elements\n",
"b.dtype // Dara type of array elements\n",
"b.dtype.name // Name of data type\n",
"b.asType<Double, Int>() // Convert an array to a different type"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Array Mathematics"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Arithmetic Operations"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Subtraction:\n",
"[[-0.5 0. 0. ]\n",
" [-3. -3. -3. ]]\n",
"Addition:\n",
"[[2.5 4. 6. ]\n",
" [5. 7. 9. ]]\n",
"Division:\n",
"[[0.66666667 1. 1. ]\n",
" [0.25 0.4 0.5 ]]\n",
"Multiplication:\n",
"[[ 1.5 4. 9. ]\n",
" [ 4. 10. 18. ]]\n"
]
},
{
"data": {
"text/plain": [
"[[7. 7.]\n",
" [7. 7.]]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"val g = a - b\n",
"println(\"Subtraction:\")\n",
"println(a - b) // Subraction\n",
"\n",
"println(\"Addition:\")\n",
"println(b + a) // Addition\n",
"\n",
"println(\"Division:\")\n",
"println(a / b) // Division\n",
"\n",
"println(\"Multiplication:\")\n",
"println(a * b) // Multiplication\n",
"\n",
"exp(b) // Exponentiation\n",
"sqrt(b) // Square root\n",
"sin(a) // Sin\n",
"cos(b) // Cos\n",
"log(a) // natural logarithm\n",
"e.dot(f) // Dot product"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Comparison"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Element-wise comparison\n",
"[[[ True True True]\n",
" [ True True True]]\n",
"\n",
" [[False True False]\n",
" [ True True True]]]\n",
"Element-wise comparison\n",
"[ True False False]\n",
"Array comparison\n",
"false\n"
]
}
],
"source": [
"println(\"Element-wise comparison\")\n",
"println(c eq b)\n",
"\n",
"println(\"Element-wise comparison\")\n",
"println(a lt 2)\n",
"\n",
"println(\"Array comparison\")\n",
"println(a == b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Aggregate Functions"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4.08248290463863"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a.sum() // Array sum\n",
"a.min() // Array minimum value\n",
"b.max(0) // Maximum value of an array row\n",
"b.cumSum(1) // Cumulative sum of the lements\n",
"a.mean() // Mean\n",
"median(b) // Median\n",
"corrcoef<Long, Long>(a) // Correlation coefficient\n",
"std(d) // Standard deviation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Copying arrays"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"var h = a.view<Long, Long>()\n",
"copy(a)\n",
"h = copy(a)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sorting Arrays"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"a.sort()\n",
"c.sort(axis = 0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Subsetting, Slicing, Indexing, Iterating"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Subsetting"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\r\n",
"6.0\r\n"
]
}
],
"source": [
"println(a[2]) // Select the element at the 2nd index\n",
"println(b[1, 2]) // Select the element at row 1 column 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Slicing"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1 2]\r\n",
"[2. 5.]\r\n",
"[[1.5 2. 3. ]]\r\n",
"[[3. 2. 3.]\n",
" [4. 5. 6.]]\r\n",
"[3 2 1]\r\n"
]
}
],
"source": [
"println(a[0..2]) // Select items at index 0 and 1\n",
"println(b[0..2, 1]) // Select items at rows 0 and 1 in column 1\n",
"\n",
"println(b[None..1]) // Select all items at row 0\n",
"\n",
"println(c[1, None..None, None..None]) // Same as [1, ...] or [1, :, :] in Python\n",
"println(a[None..None..-1]) // Reversed array a"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Boolean Indexing"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1]"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a[a lt 2] // Select elements from a less than 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Fancy indexing"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[4. 2. 6. 1.5]\r\n",
"[[4. 5. 6. 4. ]\n",
" [1.5 2. 3. 1.5]\n",
" [4. 5. 6. 4. ]\n",
" [1.5 2. 3. 1.5]]\r\n"
]
}
],
"source": [
"println(b[arrayOf(1, 0, 1, 0), arrayOf(0, 1, 2, 0)]) // Select elements (1,0), (0,1), (1,2) and (0, 0)\n",
"\n",
"println(b[arrayOf(1, 0, 1, 0)][None..None, arrayOf(0, 1, 2, 0)]) // Select a subset of the matrix's rows and columns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Iterating"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 2 3 \r\n",
"[1.5 2. 3. ]\r\n",
"[4. 5. 6.]\r\n"
]
}
],
"source": [
"// Flat array iteration\n",
"for (element in a.flatIter()) {\n",
" print(\"$element \")\n",
"}\n",
"println()\n",
"\n",
"// Iteration along the axes of the array\n",
"for (ax in b) {\n",
" println(ax)\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Array Manipulation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Transposing Array"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1.5 2. 3. ]\n",
" [4. 5. 6. ]]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"val i = transpose(b) // Permute array dimensions\n",
"i.t"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Changing Array Shape"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[-0.5 0. ]\n",
" [ 0. -3. ]\n",
" [-3. -3. ]]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.ravel() // Flatten the array\n",
"g.reshape(3, -2) // Reshape, but don't chenge data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Adding/Removing Elements"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1 3]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"h.resize(2, 6) // Change to new array with shape (2,6)\n",
"append(h.view(), g) // Append items to an array\n",
"insert(a, 1, array(arrayOf(5L))) // Insert items in an array\n",
"delete(a, 1) // Delete items from an array"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Combining Arrays"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 1 2 3 10 15 20]\n",
"[[1. 2. 3. ]\n",
" [1.5 2. 3. ]\n",
" [4. 5. 6. ]]\n",
"[[7. 7. 1. 0.]\n",
" [7. 7. 0. 1.]]\n",
"[[ 1 10]\n",
" [ 2 15]\n",
" [ 3 20]]\n"
]
}
],
"source": [
"println(concatenate(a, d, axis = 0)) // Concatenate arrays\n",
"\n",
"println(vstack(a.view(), b)) // Stack arrays vertically\n",
"\n",
"println(hstack(e.view(), f)) // Stack arrays horizontally\n",
"\n",
"println(columnStack(a, d)) // Create stacked column-wise arrays"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Splitting Arrays"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1], [2], [3]]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"hsplit(a, 3) // Split the array horizontally at the 3rd index"
]
}
],
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"display_name": "Kotlin",
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