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‎.ipynb_checkpoints/Untitled-checkpoint.ipynb‎

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎.ipynb_checkpoints/trig funcs-checkpoint.ipynb‎

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎Untitled.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "b199e8fd",
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"metadata": {},
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"source": [
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"# BINARY SEARCH"
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]
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},
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{
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"cell_type": "markdown",
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"id": "df14691f",
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"metadata": {},
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"source": [
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"### Alice has some cards with numbers written on them . she arranges the cards in decreasing order and lays them out face down in a sequence on a table . she challenges Bob to pick out the card containing a given number by turning over a s few cards as possible. write a function to help Bob locate the card."
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]
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},
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{
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"cell_type": "markdown",
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"id": "ee8d6a0e",
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"metadata": {},
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"source": [
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"####inputs\n",
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"cards: a list of numbers sorted in decreasing order eg [12, 11, 10, 6, 4, 3, 2]\n",
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"query: a number whose position in the array will be determined"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1d46a3ce",
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"metadata": {},
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"source": [
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"####output\n",
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"position: the position of the query in the list cards"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d51d9758",
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"metadata": {},
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"outputs": [],
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"source": [
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"def locate_card(cards, query):\n",
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" pass"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎trig funcs.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "90a55051",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0.0000000e+00 1.0000000e+00 1.2246468e-16]\n",
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"[ 1.000000e+00 6.123234e-17 -1.000000e+00]\n",
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"[ 0.00000000e+00 1.63312394e+16 -1.22464680e-16]\n"
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]
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}
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],
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"source": [
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"#trigonometric functions\n",
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"#array of angles\n",
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"import numpy as np\n",
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"theta = np.linspace(0, np.pi, 3)\n",
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"print(np.sin(theta))\n",
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"print(np.cos(theta))\n",
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"print(np.tan(theta))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "f71d4ef4",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[-1.57079633 0. 1.57079633]\n",
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"[3.14159265 1.57079633 0. ]\n",
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"[-0.78539816 0. 0.78539816]\n"
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]
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}
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],
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"source": [
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"#inverse trigonometry\n",
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"x = [-1, 0, 1]\n",
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"print(np.arcsin(x))\n",
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"print(np.arccos(x))\n",
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"print(np.arctan(x))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "f179e021",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[ 2.71828183 7.3890561 20.08553692]\n",
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"[2. 4. 8.]\n",
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"[ 3 9 27]\n"
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]
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}
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],
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"source": [
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"#exponentials\n",
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"x = [1, 2, 3]\n",
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"print(np.exp(x))\n",
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"print(np.exp2(x))\n",
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"print(np.power(3, x))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "3780ac89",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0. 0.69314718 1.38629436 2.30258509]\n",
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"[0. 1. 2. 3.32192809]\n",
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"[0. 0.30103 0.60205999 1. ]\n"
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]
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}
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],
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"source": [
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"#logarithms\n",
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"x = [1, 2, 4, 10]\n",
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"print(np.log(x))\n",
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"print(np.log2(x))\n",
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"print(np.log10(x))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "516d9e69",
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"metadata": {},
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'scipy'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"Input \u001b[1;32mIn [9]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m#special ufuncs\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m special\n\u001b[0;32m 3\u001b[0m x \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m5\u001b[39m, \u001b[38;5;241m10\u001b[39m]\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(special\u001b[38;5;241m.\u001b[39mgamma(x))\n",
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"\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'scipy'"
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]
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}
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],
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"source": [
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"#special ufuncs\n",
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"from scipy import special\n",
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"x = [1, 5, 10]\n",
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"print(special.gamma(x))\n",
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"print(special.gammaln(x))\n",
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"print(special.beta(x, 2))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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