"pull requests open"
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# urgh\n",
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"\n",
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"import\n"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np, matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"get to work\n",
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"\n",
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"## linspace, function.\n",
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"\n",
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"linspace is just linear spaces that is dense enough so it looks pleasant\n"
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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": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"x = np.linspace(-5, 5, 20) # they use arange more so look into that\n",
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"\n",
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"y = x + 1\n",
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"y2 = -x + 2"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## plot\n",
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"\n",
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"im discovering all of this as i type. deadass never used plot in my life\n"
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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": 16,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Text(0.5, 1.0, 'cant be arsed')"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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truncated
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"%matplotlib inline\n",
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"\n",
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"plt.plot(x, y)\n",
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"\n",
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"plt.plot(x, y2)\n",
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"\n",
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"plt.title(\"cant be arsed\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## hmm\n",
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"\n",
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"why\n"
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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",
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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": "3.12.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@@ -0,0 +1,8 @@
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# i try to do stuff
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remember all given code is from the internet made by probably also a learning person!
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implement your own code. or leave it to the lib maintainers. they know what up.
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(explanation for why some functions given by tutor is pure ass. They are from the internet. not reliable.
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use whatever built in. Yes there is one built in.)
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@@ -0,0 +1,23 @@
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# quit this shit rn
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import sympy
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from sympy.abc import k, n, i
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import sympy.algebras
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import sympy.vector
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# 5
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f = 1 / k + 1 / (1 - k)
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pinf = sympy.oo
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f_s = sympy.summation(f, (i, 0, n))
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print(f_s)
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f_2 = 1 / (n**2)
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f_inf = sympy.summation(f_2, (n, 1, pinf))
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print(f_inf)
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