From 5b2516d475d44014d97a1b26626caa498dbe0b90 Mon Sep 17 00:00:00 2001 From: Justin Vermillion Date: Tue, 8 Dec 2020 19:20:39 -0700 Subject: [PATCH 1/3] fix space issue --- setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.py b/setup.py index df21e753..64ff8280 100644 --- a/setup.py +++ b/setup.py @@ -1,5 +1,6 @@ from distutils.core import setup + def readme(): try: with open('README.rst') as f: From 70bae4e72ba7d4a22d789c4544373773128a1431 Mon Sep 17 00:00:00 2001 From: Justin Vermillion Date: Wed, 9 Dec 2020 13:40:45 -0700 Subject: [PATCH 2/3] Worked through Chapter 3 --- notebooks/chap01.ipynb | 349 ++++++++++++++-- notebooks/chap02.ipynb | 652 +++++++++++++++++++++++++----- notebooks/chap03.ipynb | 406 ++++++++++++++++--- notebooks/chap04.ipynb | 316 +++++++++++++-- notebooks/chap05.ipynb | 694 +++++++++++++++++++++++++++++--- notebooks/figs/chap02-fig01.pdf | Bin 0 -> 13915 bytes notebooks/figs/chap02-fig02.pdf | Bin 0 -> 14827 bytes notebooks/figs/chap02-fig03.pdf | Bin 0 -> 14414 bytes notebooks/figs/chap02-fig04.pdf | Bin 0 -> 18309 bytes notebooks/figs/chap05-fig01.pdf | Bin 0 -> 16200 bytes notebooks/figs/chap05-fig02.pdf | Bin 0 -> 18024 bytes notebooks/figs/chap05-fig03.pdf | Bin 0 -> 18154 bytes 12 files changed, 2120 insertions(+), 297 deletions(-) create mode 100644 notebooks/figs/chap02-fig01.pdf create mode 100644 notebooks/figs/chap02-fig02.pdf create mode 100644 notebooks/figs/chap02-fig03.pdf create mode 100644 notebooks/figs/chap02-fig04.pdf create mode 100644 notebooks/figs/chap05-fig01.pdf create mode 100644 notebooks/figs/chap05-fig02.pdf create mode 100644 notebooks/figs/chap05-fig03.pdf diff --git a/notebooks/chap01.ipynb b/notebooks/chap01.ipynb index 4d73a4a0..86431ef6 100644 --- a/notebooks/chap01.ipynb +++ b/notebooks/chap01.ipynb @@ -136,7 +136,15 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Python 3.7.7\n" + ] + } + ], "source": [ "!python --version" ] @@ -145,7 +153,15 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "6.1.4\n" + ] + } + ], "source": [ "!jupyter-notebook --version" ] @@ -195,7 +211,20 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "meter", + "text/latex": "$\\mathrm{meter}$" + }, + "metadata": {}, + "execution_count": 6 + } + ], "source": [ "meter = UNITS.meter" ] @@ -204,7 +233,20 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "second", + "text/latex": "$\\mathrm{second}$" + }, + "metadata": {}, + "execution_count": 7 + } + ], "source": [ "second = UNITS.second" ] @@ -234,7 +276,20 @@ "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "9.8 " + ], + "text/html": "9.8 meter/second2", + "text/latex": "$9.8\\ \\frac{\\mathrm{meter}}{\\mathrm{second}^{2}}$" + }, + "metadata": {}, + "execution_count": 8 + } + ], "source": [ "a = 9.8 * meter / second**2" ] @@ -250,7 +305,20 @@ "cell_type": "code", "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "4 " + ], + "text/html": "4 second", + "text/latex": "$4\\ \\mathrm{second}$" + }, + "metadata": {}, + "execution_count": 9 + } + ], "source": [ "t = 4 * second" ] @@ -266,7 +334,20 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "78.4 " + ], + "text/html": "78.4 meter", + "text/latex": "$78.4\\ \\mathrm{meter}$" + }, + "metadata": {}, + "execution_count": 10 + } + ], "source": [ "a * t**2 / 2" ] @@ -282,9 +363,23 @@ "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "39.2 " + ], + "text/html": "39.2 meter/second", + "text/latex": "$39.2\\ \\frac{\\mathrm{meter}}{\\mathrm{second}}$" + }, + "metadata": {}, + "execution_count": 11 + } + ], + "source": [ + "# Solution goes here\n", + "v = a * t" ] }, { @@ -296,11 +391,27 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "error", + "ename": "DimensionalityError", + "evalue": "Cannot convert from 'meter / second ** 2' ([length] / [time] ** 2) to 'second' ([time])", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mDimensionalityError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Solution goes here\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/.pyenv/versions/anaconda3-2020.02/lib/python3.7/site-packages/pint/quantity.py\u001b[0m in \u001b[0;36m__add__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 1077\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_timedelta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1078\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_add_sub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1080\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1081\u001b[0m \u001b[0m__radd__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m__add__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/.pyenv/versions/anaconda3-2020.02/lib/python3.7/site-packages/pint/quantity.py\u001b[0m in \u001b[0;36mwrapped\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mother\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 114\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 115\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 116\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 117\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/.pyenv/versions/anaconda3-2020.02/lib/python3.7/site-packages/pint/quantity.py\u001b[0m in \u001b[0;36m_add_sub\u001b[0;34m(self, other, op)\u001b[0m\n\u001b[1;32m 988\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdimensionality\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdimensionality\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 989\u001b[0m raise DimensionalityError(\n\u001b[0;32m--> 990\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_units\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_units\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdimensionality\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 991\u001b[0m )\n\u001b[1;32m 992\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mDimensionalityError\u001b[0m: Cannot convert from 'meter / second ** 2' ([length] / [time] ** 2) to 'second' ([time])" + ] + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "a + t" ] }, { @@ -331,9 +442,22 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "381 " + ], + "text/html": "381 meter", + "text/latex": "$381\\ \\mathrm{meter}$" + }, + "metadata": {}, + "execution_count": 14 + } + ], "source": [ "h = 381 * meter" ] @@ -351,9 +475,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "8.817885349720552 " + ], + "text/html": "8.817885349720552 second", + "text/latex": "$8.817885349720552\\ \\mathrm{second}$" + }, + "metadata": {}, + "execution_count": 15 + } + ], "source": [ "t = sqrt(2 * h / a)" ] @@ -369,9 +506,22 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "86.41527642726142 " + ], + "text/html": "86.41527642726142 meter/second", + "text/latex": "$86.41527642726142\\ \\frac{\\mathrm{meter}}{\\mathrm{second}}$" + }, + "metadata": {}, + "execution_count": 16 + } + ], "source": [ "v = a * t" ] @@ -385,9 +535,22 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "hour", + "text/latex": "$\\mathrm{hour}$" + }, + "metadata": {}, + "execution_count": 17 + } + ], "source": [ "mile = UNITS.mile\n", "hour = UNITS.hour" @@ -395,9 +558,22 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "193.30546802805432 " + ], + "text/html": "193.30546802805432 mile/hour", + "text/latex": "$193.30546802805432\\ \\frac{\\mathrm{mile}}{\\mathrm{hour}}$" + }, + "metadata": {}, + "execution_count": 18 + } + ], "source": [ "v.to(mile/hour)" ] @@ -415,20 +591,49 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "10 " + ], + "text/html": "10 foot", + "text/latex": "$10\\ \\mathrm{foot}$" + }, + "metadata": {}, + "execution_count": 19 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "foot = UNITS.foot\n", + "pole = 10 * foot" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "384.048 " + ], + "text/html": "384.048 meter", + "text/latex": "$384.048\\ \\mathrm{meter}$" + }, + "metadata": {}, + "execution_count": 20 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "h + pole" ] }, { @@ -450,43 +655,99 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "18 " + ], + "text/html": "18 meter/second", + "text/latex": "$18\\ \\frac{\\mathrm{meter}}{\\mathrm{second}}$" + }, + "metadata": {}, + "execution_count": 21 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "v = 18 * (meter/second)" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1.8367346938775508 " + ], + "text/html": "1.8367346938775508 second", + "text/latex": "$1.8367346938775508\\ \\mathrm{second}$" + }, + "metadata": {}, + "execution_count": 22 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "t = v / a" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "16.530612244897956 " + ], + "text/html": "16.530612244897956 meter", + "text/latex": "$16.530612244897956\\ \\mathrm{meter}$" + }, + "metadata": {}, + "execution_count": 23 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "d = a*t**2/2" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0.9183673469387753 " + ], + "text/html": "0.9183673469387753 second", + "text/latex": "$0.9183673469387753\\ \\mathrm{second}$" + }, + "metadata": {}, + "execution_count": 24 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "t = d / v" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -530,9 +791,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/chap02.ipynb b/notebooks/chap02.ipynb index 192035b5..40ae94d9 100644 --- a/notebooks/chap02.ipynb +++ b/notebooks/chap02.ipynb @@ -29,7 +29,7 @@ "from modsim import *\n", "\n", "# set the random number generator\n", - "np.random.seed(7)\n", + "np.random.seed()\n", "\n", "# If this cell runs successfully, it produces no output." ] @@ -54,7 +54,21 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin10
wellesley2
\n
" + }, + "metadata": {}, + "execution_count": 2 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)" ] @@ -70,7 +84,18 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "10" + ] + }, + "metadata": {}, + "execution_count": 3 + } + ], "source": [ "bikeshare.olin" ] @@ -81,7 +106,18 @@ "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "2" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "bikeshare.wellesley" ] @@ -131,7 +167,21 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin9
wellesley2
\n
" + }, + "metadata": {}, + "execution_count": 6 + } + ], "source": [ "bikeshare" ] @@ -147,7 +197,21 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 3\n", + "dtype: int64" + ], + "text/html": "
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values
olin9
wellesley3
\n
" + }, + "metadata": {}, + "execution_count": 7 + } + ], "source": [ "bikeshare.wellesley += 1\n", "bikeshare" @@ -184,7 +248,21 @@ "cell_type": "code", "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 8\n", + "wellesley 4\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin8
wellesley4
\n
" + }, + "metadata": {}, + "execution_count": 9 + } + ], "source": [ "bike_to_wellesley()\n", "bikeshare" @@ -202,7 +280,18 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 10 + } + ], "source": [ "bike_to_wellesley" ] @@ -227,16 +316,35 @@ "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def bike_to_olin():\n", + " bikeshare.olin += 1\n", + " bikeshare.wellesley -= 1" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 3\n", + "dtype: int64" + ], + "text/html": "
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wellesley3
\n
" + }, + "metadata": {}, + "execution_count": 12 + } + ], + "source": [ + "# Solution goes here\n", + "bike_to_olin()\n", + "bikeshare" ] }, { @@ -259,7 +367,15 @@ "cell_type": "code", "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function flip in module modsim.modsim:\n\nflip(p=0.5)\n Flips a coin with the given probability.\n \n p: float 0-1\n \n returns: boolean (True or False)\n\n" + ] + } + ], "source": [ "help(flip)" ] @@ -273,9 +389,20 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "False" + ] + }, + "metadata": {}, + "execution_count": 18 + } + ], "source": [ "flip(0.7)" ] @@ -289,9 +416,17 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "heads\n" + ] + } + ], "source": [ "if flip(0.7):\n", " print('heads')" @@ -306,9 +441,17 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "heads\n" + ] + } + ], "source": [ "if flip(0.7):\n", " print('heads')\n", @@ -327,9 +470,23 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
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values
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\n
" + }, + "metadata": {}, + "execution_count": 21 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)" ] @@ -343,9 +500,30 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Moving a bike to Wellesley\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 3\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 22 + } + ], "source": [ "if flip(0.5):\n", " bike_to_wellesley()\n", @@ -363,9 +541,23 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 3\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 23 + } + ], "source": [ "if flip(0.4):\n", " bike_to_olin()\n", @@ -383,7 +575,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -406,9 +598,30 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Moving a bike to Wellesley\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 9\n", + "wellesley 3\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 40 + } + ], "source": [ "step()\n", "bikeshare" @@ -427,11 +640,12 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "def step(p1, p2):\n", + " print(p1, p2)\n", " if flip(p1):\n", " bike_to_wellesley()\n", " print('Moving a bike to Wellesley')\n", @@ -450,9 +664,23 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 8\n", + "wellesley 4\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 44 + } + ], "source": [ "step(0.5, 0.4)\n", "bikeshare" @@ -467,11 +695,20 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 46, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "0.3 0.2\n" + ] + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "step(0.3, 0.2)" ] }, { @@ -490,7 +727,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ @@ -511,9 +748,23 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 48 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)" ] @@ -527,9 +778,23 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 6\n", + "wellesley 6\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 49 + } + ], "source": [ "for i in range(4):\n", " bike_to_wellesley()\n", @@ -546,9 +811,23 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 6\n", + "wellesley 6\n", + "dtype: int64" + ], + "text/html": "
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\n
" + }, + "metadata": {}, + "execution_count": 50 + } + ], "source": [ "for i in range(4):\n", " step(0.3, 0.2)\n", @@ -565,9 +844,23 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 1\n", + "wellesley 11\n", + "dtype: int64" + ], + "text/html": "
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\n
" + }, + "metadata": {}, + "execution_count": 51 + } + ], "source": [ "for i in range(60):\n", " step(0.3, 0.2)\n", @@ -597,9 +890,21 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "TimeSeries([], dtype: float64)" + ], + "text/html": "
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values
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" + }, + "metadata": {}, + "execution_count": 52 + } + ], "source": [ "results = TimeSeries()" ] @@ -613,9 +918,22 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0 1\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 53 + } + ], "source": [ "results[0] = bikeshare.olin\n", "results" @@ -632,9 +950,23 @@ }, { "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 54 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)" ] @@ -648,7 +980,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 55, "metadata": {}, "outputs": [], "source": [ @@ -666,9 +998,31 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0 10\n", + "1 10\n", + "2 10\n", + "3 11\n", + "4 12\n", + "5 11\n", + "6 12\n", + "7 11\n", + "8 11\n", + "9 11\n", + "dtype: int64" + ], + "text/html": "
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" + }, + "metadata": {}, + "execution_count": 56 + } + ], "source": [ "results" ] @@ -682,18 +1036,48 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "10.9" + ] + }, + "metadata": {}, + "execution_count": 57 + } + ], "source": [ "results.mean()" ] }, { "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "count 10.000000\n", + "mean 10.900000\n", + "std 0.737865\n", + "min 10.000000\n", + "25% 10.250000\n", + "50% 11.000000\n", + "75% 11.000000\n", + "max 12.000000\n", + "dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 58 + } + ], "source": [ "results.describe()" ] @@ -716,9 +1100,26 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [], + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap02-fig01.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "plot(results, label='Olin')\n", "\n", @@ -738,9 +1139,17 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function decorate in module modsim.modsim:\n\ndecorate(**options)\n Decorate the current axes.\n \n Call decorate with keyword arguments like\n \n decorate(title='Title',\n xlabel='x',\n ylabel='y')\n \n The keyword arguments can be any of the axis properties\n \n https://matplotlib.org/api/axes_api.html\n \n In addition, you can use `legend=False` to suppress the legend.\n \n And you can use `loc` to indicate the location of the legend\n (the default value is 'best')\n\n" + ] + } + ], "source": [ "help(decorate)" ] @@ -754,9 +1163,17 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function savefig in module modsim.modsim:\n\nsavefig(filename, **options)\n Save the current figure.\n \n Keyword arguments are passed along to plt.savefig\n \n https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html\n \n filename: string\n\n" + ] + } + ], "source": [ "help(savefig)" ] @@ -795,20 +1212,57 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 68, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "bikeshare = State(olin=10, wellesley=2)\n", + "\n", + "def run_simulation(p1, p2, num_steps):\n", + " oresults = TimeSeries()\n", + " wresults = TimeSeries()\n", + " oresults[0], wresults[0] = bikeshare.olin, bikeshare.wellesley\n", + " \n", + " for i in range(num_steps):\n", + " step(p1, p2)\n", + " oresults[i], wresults[i] = bikeshare.olin, bikeshare.wellesley\n", + " \n", + " plot(oresults, label='Olin')\n", + " plot(wresults, label='Wellesley')\n", + "\n", + " decorate(title='Olin-Wellesley Bikeshare',\n", + " xlabel='Time step (min)', \n", + " ylabel='Number of bikes')\n", + "\n", + " savefig('figs/chap02-fig04.pdf')" ] }, { "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap02-fig04.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Solution goes here\n", + "run_simulation(0.4, 0.2, 600)" ] }, { @@ -858,9 +1312,17 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function decorate in module modsim.modsim:\n\ndecorate(**options)\n Decorate the current axes.\n \n Call decorate with keyword arguments like\n \n decorate(title='Title',\n xlabel='x',\n ylabel='y')\n \n The keyword arguments can be any of the axis properties\n \n https://matplotlib.org/api/axes_api.html\n \n In addition, you can use `legend=False` to suppress the legend.\n \n And you can use `loc` to indicate the location of the legend\n (the default value is 'best')\n\n" + ] + } + ], "source": [ "help(decorate)" ] @@ -878,9 +1340,17 @@ }, { "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [], + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "def flip(p=0.5):\n \"\"\"Flips a coin with the given probability.\n\n p: float 0-1\n\n returns: boolean (True or False)\n \"\"\"\n return np.random.random() < p\n\n" + ] + } + ], "source": [ "source_code(flip)" ] @@ -909,9 +1379,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/chap03.ipynb b/notebooks/chap03.ipynb index 82a9d53a..7b103818 100644 --- a/notebooks/chap03.ipynb +++ b/notebooks/chap03.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +29,7 @@ "from modsim import *\n", "\n", "# set the random number generator\n", - "np.random.seed(7)" + "np.random.seed()" ] }, { @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -96,7 +96,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -125,18 +125,46 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)\n", "run_simulation(bikeshare, 0.4, 0.2, 60)\n", @@ -227,7 +295,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -261,9 +329,21 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2)\n", "run_simulation(bikeshare, 0.4, 0.2, 60)\n", @@ -290,9 +370,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "5" + ] + }, + "metadata": {}, + "execution_count": 16 + } + ], "source": [ "x = 5" ] @@ -306,9 +397,20 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "execution_count": 17 + } + ], "source": [ "x == 5" ] @@ -322,9 +424,17 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "yes, x is 5\n" + ] + } + ], "source": [ "if x == 5:\n", " print('yes, x is 5')" @@ -339,7 +449,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -382,9 +492,25 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "olin_empty 0\n", + "wellesley_empty 0\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin10
wellesley2
olin_empty0
wellesley_empty0
\n
" + }, + "metadata": {}, + "execution_count": 20 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2, \n", " olin_empty=0, wellesley_empty=0)" @@ -399,7 +525,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -435,9 +561,21 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ "run_simulation(bikeshare, 0.4, 0.2, 60)\n", "decorate_bikeshare()" @@ -452,18 +590,40 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0" + ] + }, + "metadata": {}, + "execution_count": 23 + } + ], "source": [ "bikeshare.olin_empty" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1" + ] + }, + "metadata": {}, + "execution_count": 24 + } + ], "source": [ "bikeshare.wellesley_empty" ] @@ -485,9 +645,26 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "olin_empty 0\n", + "wellesley_empty 0\n", + "clock 0\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin10
wellesley2
olin_empty0
wellesley_empty0
clock0
\n
" + }, + "metadata": {}, + "execution_count": 25 + } + ], "source": [ "bikeshare = State(olin=10, wellesley=2, \n", " olin_empty=0, wellesley_empty=0,\n", @@ -496,29 +673,68 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def step(state, p1, p2):\n", + " \"\"\"Simulate one minute of time.\n", + " \n", + " state: bikeshare State object\n", + " p1: probability of an Olin->Wellesley customer arrival\n", + " p2: probability of a Wellesley->Olin customer arrival\n", + " \"\"\"\n", + " state.clock += 1\n", + "\n", + " if flip(p1):\n", + " bike_to_wellesley(state)\n", + " \n", + " if flip(p2):\n", + " bike_to_olin(state)" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 30, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "run_simulation(bikeshare, 0.3, 0.2, 60)" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "60" + ] + }, + "metadata": {}, + "execution_count": 31 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "bikeshare.clock" ] }, { @@ -536,39 +752,111 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 2\n", + "wellesley 10\n", + "olin_empty 0\n", + "wellesley_empty 0\n", + "clock 0\n", + "t_first_empty -1\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin2
wellesley10
olin_empty0
wellesley_empty0
clock0
t_first_empty-1
\n
" + }, + "metadata": {}, + "execution_count": 43 + } + ], + "source": [ + "# Solution goes here\n", + "bikeshare = State(\n", + " olin=2, \n", + " wellesley=10, \n", + " olin_empty=0, \n", + " wellesley_empty=0, \n", + " clock=0, \n", + " t_first_empty=-1,\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 44, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def step(state, p1, p2):\n", + " \"\"\"Simulate one minute of time.\n", + " \n", + " state: bikeshare State object\n", + " p1: probability of an Olin->Wellesley customer arrival\n", + " p2: probability of a Wellesley->Olin customer arrival\n", + " \"\"\"\n", + " state.clock += 1\n", + " \n", + " if flip(p1):\n", + " bike_to_wellesley(state)\n", + " \n", + " if flip(p2):\n", + " bike_to_olin(state)\n", + " \n", + " if (state.wellesley_empty or state.olin_empty) and state.t_first_empty == -1:\n", + " state.t_first_empty = state.clock" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 45, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "run_simulation(bikeshare, 0.4, 0.2, 60)" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 46, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "12 0 11\n" + ] + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "print(bikeshare.olin_empty, bikeshare.wellesley_empty, bikeshare.t_first_empty)" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "# Solution goes here" - ] + "source": [] } ], "metadata": { @@ -587,9 +875,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/chap04.ipynb b/notebooks/chap04.ipynb index 1945f357..24e620e7 100644 --- a/notebooks/chap04.ipynb +++ b/notebooks/chap04.ipynb @@ -64,7 +64,18 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "8" + ] + }, + "metadata": {}, + "execution_count": 3 + } + ], "source": [ "y = add_five(3)" ] @@ -80,7 +91,18 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "10" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "add_five(5)" ] @@ -98,7 +120,18 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "10" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ], "source": [ "add_five(3)\n", "add_five(5)" @@ -115,7 +148,15 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "8 10\n" + ] + } + ], "source": [ "y1 = add_five(3)\n", "y2 = add_five(5)\n", @@ -138,16 +179,33 @@ "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def make_state() -> State:\n", + " return State(olin=10, wellesley=2)\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 10\n", + "wellesley 2\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin10
wellesley2
\n
" + }, + "metadata": {}, + "execution_count": 8 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "init = make_state()" ] }, { @@ -252,7 +310,23 @@ "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "olin 0\n", + "wellesley 12\n", + "olin_empty 4\n", + "wellesley_empty 0\n", + "dtype: int64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
olin0
wellesley12
olin_empty4
wellesley_empty0
\n
" + }, + "metadata": {}, + "execution_count": 11 + } + ], "source": [ "state = run_simulation(0.4, 0.2, 60)" ] @@ -268,7 +342,18 @@ "cell_type": "code", "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "4" + ] + }, + "metadata": {}, + "execution_count": 12 + } + ], "source": [ "state.olin_empty" ] @@ -284,7 +369,18 @@ "cell_type": "code", "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0" + ] + }, + "metadata": {}, + "execution_count": 13 + } + ], "source": [ "state = run_simulation(0.2, 0.2, 60)\n", "state.olin_empty" @@ -301,7 +397,18 @@ "cell_type": "code", "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "15" + ] + }, + "metadata": {}, + "execution_count": 14 + } + ], "source": [ "state = run_simulation(0.6, 0.2, 60)\n", "state.olin_empty" @@ -325,7 +432,18 @@ "cell_type": "code", "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([0. , 0.25, 0.5 , 0.75, 1. ])" + ] + }, + "metadata": {}, + "execution_count": 15 + } + ], "source": [ "p1_array = linspace(0, 1, 5)" ] @@ -341,7 +459,15 @@ "cell_type": "code", "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "0.0\n0.25\n0.5\n0.75\n1.0\n" + ] + } + ], "source": [ "for p1 in p1_array:\n", " print(p1)" @@ -360,7 +486,15 @@ "cell_type": "code", "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function linspace in module modsim.modsim:\n\nlinspace(start, stop, num=50, **options)\n Returns an array of evenly-spaced values in the interval [start, stop].\n \n start: first value\n stop: last value\n num: number of values\n \n Also accepts the same keyword arguments as np.linspace. See\n https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html\n \n returns: array or Quantity\n\n" + ] + } + ], "source": [ "help(linspace)" ] @@ -384,9 +518,21 @@ "cell_type": "code", "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])" + ] + }, + "metadata": {}, + "execution_count": 18 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "array = linspace(1, 10, num=10)" ] }, { @@ -400,7 +546,15 @@ "cell_type": "code", "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Help on function linrange in module modsim.modsim:\n\nlinrange(start=0, stop=None, step=1, endpoint=False, **options)\n Returns an array of evenly-spaced values in an interval.\n \n By default, the last value in the array is `stop-step`\n (at least approximately).\n If you provide the keyword argument `endpoint=True`,\n the last value in the array is `stop`.\n \n This function works best if the space between start and stop\n is divisible by step; otherwise the results might be surprising.\n \n start: first value\n stop: last value\n step: space between values\n \n returns: NumPy array\n\n" + ] + } + ], "source": [ "help(linrange)" ] @@ -416,9 +570,21 @@ "cell_type": "code", "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([1, 3, 5, 7, 9])" + ] + }, + "metadata": {}, + "execution_count": 20 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "r = linrange(1, 11, 2)" ] }, { @@ -439,7 +605,18 @@ "cell_type": "code", "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])" + ] + }, + "metadata": {}, + "execution_count": 21 + } + ], "source": [ "p2 = 0.2\n", "num_steps = 60\n", @@ -457,7 +634,15 @@ "cell_type": "code", "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "0.0 0\n0.1 0\n0.2 0\n0.30000000000000004 4\n0.4 3\n0.5 6\n0.6000000000000001 12\n0.7000000000000001 19\n0.8 25\n0.9 33\n1.0 36\n" + ] + } + ], "source": [ "for p1 in p1_array:\n", " state = run_simulation(p1, p2, num_steps)\n", @@ -496,7 +681,17 @@ "cell_type": "code", "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "plot(sweep, label='Olin')\n", "\n", @@ -518,20 +713,43 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def sweep_p1(p1_array) -> SweepSeries:\n", + " sweep = SweepSeries()\n", + "\n", + " for p1 in p1_array:\n", + " state = run_simulation(p1, p2, num_steps)\n", + " sweep[p1] = state.olin_empty\n", + " \n", + " return sweep" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Solution goes here\n", + "plot(sweep_p1(p1_array), label='Olin')\n", + "\n", + "decorate(title='Olin-Wellesley Bikeshare',\n", + " xlabel='Arrival rate at Olin (p1 in customers/min)', \n", + " ylabel='Number of unhappy customers')" ] }, { @@ -543,20 +761,44 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def sweep_p2(p2_array) -> SweepSeries:\n", + " sweep = SweepSeries()\n", + "\n", + " for p2 in p2_array:\n", + " state = run_simulation(p1, p2, num_steps)\n", + " sweep[p2] = state.olin_empty\n", + " \n", + " return sweep" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Solution goes here\n", + "p1 = 0.5\n", + "p2_array = linspace(0, 1, 11)\n", + "plot(sweep_p2(p2_array), label=\"Olin\")\n", + "decorate(title='Olin-Wellesley Bikeshare',\n", + " xlabel='Arrival rate at Wellesley (p2 in customers/min)', \n", + " ylabel='Number of unhappy customers')" ] }, { @@ -593,7 +835,7 @@ "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here " ] }, { @@ -659,9 +901,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/chap05.ipynb b/notebooks/chap05.ipynb index d624e63e..70f4f848 100644 --- a/notebooks/chap05.ipynb +++ b/notebooks/chap05.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -58,9 +58,20 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "6" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "filename = 'data/World_population_estimates.html'\n", "tables = read_html(filename, header=0, index_col=0, decimal='M')\n", @@ -78,11 +89,69 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " United States Census Bureau (2017)[28] \\\n", + "Year \n", + "1950 2557628654 \n", + "1951 2594939877 \n", + "1952 2636772306 \n", + "1953 2682053389 \n", + "1954 2730228104 \n", + "\n", + " Population Reference Bureau (1973–2016)[15] \\\n", + "Year \n", + "1950 2.516000e+09 \n", + "1951 NaN \n", + "1952 NaN \n", + "1953 NaN \n", + "1954 NaN \n", + "\n", + " United Nations Department of Economic and Social Affairs (2015)[16] \\\n", + "Year \n", + "1950 2.525149e+09 \n", + "1951 2.572851e+09 \n", + "1952 2.619292e+09 \n", + "1953 2.665865e+09 \n", + "1954 2.713172e+09 \n", + "\n", + " Maddison (2008)[17] HYDE (2007)[24] Tanton (1994)[18] \\\n", + "Year \n", + "1950 2.544000e+09 2.527960e+09 2.400000e+09 \n", + "1951 2.571663e+09 NaN NaN \n", + "1952 2.617949e+09 NaN NaN \n", + "1953 2.665959e+09 NaN NaN \n", + "1954 2.716927e+09 NaN NaN \n", + "\n", + " Biraben (1980)[19] McEvedy & Jones (1978)[20] Thomlinson (1975)[21] \\\n", + "Year \n", + "1950 2.527000e+09 2.500000e+09 2.400000e+09 \n", + "1951 NaN NaN NaN \n", + "1952 NaN NaN NaN \n", + "1953 NaN NaN NaN \n", + "1954 NaN NaN NaN \n", + "\n", + " Durand (1974)[22] Clark (1967)[23] \n", + "Year \n", + "1950 NaN 2.486000e+09 \n", + "1951 NaN NaN \n", + "1952 NaN NaN \n", + "1953 NaN NaN \n", + "1954 NaN NaN " + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
United States Census Bureau (2017)[28]Population Reference Bureau (1973–2016)[15]United Nations Department of Economic and Social Affairs (2015)[16]Maddison (2008)[17]HYDE (2007)[24]Tanton (1994)[18]Biraben (1980)[19]McEvedy & Jones (1978)[20]Thomlinson (1975)[21]Durand (1974)[22]Clark (1967)[23]
Year
195025576286542.516000e+092.525149e+092.544000e+092.527960e+092.400000e+092.527000e+092.500000e+092.400000e+09NaN2.486000e+09
19512594939877NaN2.572851e+092.571663e+09NaNNaNNaNNaNNaNNaNNaN
19522636772306NaN2.619292e+092.617949e+09NaNNaNNaNNaNNaNNaNNaN
19532682053389NaN2.665865e+092.665959e+09NaNNaNNaNNaNNaNNaNNaN
19542730228104NaN2.713172e+092.716927e+09NaNNaNNaNNaNNaNNaNNaN
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" + }, + "metadata": {}, + "execution_count": 5 + } + ], "source": [ "table2 = tables[2]\n", "table2.head()" @@ -97,9 +166,67 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " United States Census Bureau (2017)[28] \\\n", + "Year \n", + "2012 7013871313 \n", + "2013 7092128094 \n", + "2014 7169968185 \n", + "2015 7247892788 \n", + "2016 7325996709 \n", + "\n", + " Population Reference Bureau (1973–2016)[15] \\\n", + "Year \n", + "2012 7.057075e+09 \n", + "2013 7.136796e+09 \n", + "2014 7.238184e+09 \n", + "2015 7.336435e+09 \n", + "2016 7.418152e+09 \n", + "\n", + " United Nations Department of Economic and Social Affairs (2015)[16] \\\n", + "Year \n", + "2012 7.080072e+09 \n", + "2013 7.162119e+09 \n", + "2014 7.243784e+09 \n", + "2015 7.349472e+09 \n", + "2016 NaN \n", + "\n", + " Maddison (2008)[17] HYDE (2007)[24] Tanton (1994)[18] \\\n", + "Year \n", + "2012 NaN NaN NaN \n", + "2013 NaN NaN NaN \n", + "2014 NaN NaN NaN \n", + "2015 NaN NaN NaN \n", + "2016 NaN NaN NaN \n", + "\n", + " Biraben (1980)[19] McEvedy & Jones (1978)[20] Thomlinson (1975)[21] \\\n", + "Year \n", + "2012 NaN NaN NaN \n", + "2013 NaN NaN NaN \n", + "2014 NaN NaN NaN \n", + "2015 NaN NaN NaN \n", + "2016 NaN NaN NaN \n", + "\n", + " Durand (1974)[22] Clark (1967)[23] \n", + "Year \n", + "2012 NaN NaN \n", + "2013 NaN NaN \n", + "2014 NaN NaN \n", + "2015 NaN NaN \n", + "2016 NaN NaN " + ], + "text/html": "
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United States Census Bureau (2017)[28]Population Reference Bureau (1973–2016)[15]United Nations Department of Economic and Social Affairs (2015)[16]Maddison (2008)[17]HYDE (2007)[24]Tanton (1994)[18]Biraben (1980)[19]McEvedy & Jones (1978)[20]Thomlinson (1975)[21]Durand (1974)[22]Clark (1967)[23]
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censusprbunmaddisonhydetantonbirabenmjthomlinsondurandclark
Year
195025576286542.516000e+092.525149e+092.544000e+092.527960e+092.400000e+092.527000e+092.500000e+092.400000e+09NaN2.486000e+09
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" + }, + "metadata": {}, + "execution_count": 8 + } + ], "source": [ "table2.head()" ] @@ -160,9 +321,26 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2557628654\n", + "1951 2594939877\n", + "1952 2636772306\n", + "1953 2682053389\n", + "1954 2730228104\n", + "Name: census, dtype: int64" + ] + }, + "metadata": {}, + "execution_count": 9 + } + ], "source": [ "census = table2.census\n", "census.head()" @@ -170,9 +348,26 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "2012 7013871313\n", + "2013 7092128094\n", + "2014 7169968185\n", + "2015 7247892788\n", + "2016 7325996709\n", + "Name: census, dtype: int64" + ] + }, + "metadata": {}, + "execution_count": 10 + } + ], "source": [ "census.tail()" ] @@ -195,9 +390,26 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.525149\n", + "1951 2.572851\n", + "1952 2.619292\n", + "1953 2.665865\n", + "1954 2.713172\n", + "Name: un, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 11 + } + ], "source": [ "un = table2.un / 1e9\n", "un.head()" @@ -205,9 +417,26 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.557629\n", + "1951 2.594940\n", + "1952 2.636772\n", + "1953 2.682053\n", + "1954 2.730228\n", + "Name: census, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 12 + } + ], "source": [ "census = table2.census / 1e9\n", "census.head()" @@ -222,11 +451,30 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap05-fig01.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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p1QgrmfyS702aNKFx48akpaUxffr000q+n6levXo88sgjPPbYY0RE+DdlicfjYe3atTz++ONMmDCB8PBwv/br3bs3U6dOZcqUKdx6663ExMRw4MABZs6cWVBufvbs2QwZMoQaNWqctu8VV1zBm2++ye23315QHVgIUTRPTibJSz4oGKH3xRuv0/yKv9C8fgxAhSiHUdaKS1Dd/L2/5NtunlJqfqlEVYn5U/K9KKNHj2bZsmWsXLnynNts376dxMREAOx2O7Vr1+bWW2/luuuuO227+++/H5vt7Kn2v/76axISEvjoo4945ZVXGD58OFlZWURHRzNkyBDuuecekpOT+e6773j33XfP2n/48OFMmTKFb775huHDh/v5f0SIqidz9waOffka7vTjYLWzt0ZvZm6pifp8C1Pv7ml2eAGjRCXffYUG7YCl8HKtdWYpx3XmeRsgJd+FEBWcO/sUKd+9S8bGpQAE1WxM/PC78EbX5t2FW7imfzOiI4NNjrJ8FVfy3a9RfEqpbhj3o1qfY5PAr3wlhBAmyz28i4yNS/FY7KxydOWaG+8u6DmZcEXRXfxVmb/DzF8CTmDcZ/LviU8hhBB48nKwOowRuiEN2xLZZyzP/5DHlqQgGm07Tvc2Nc9zhKrL3wTVBuOe1OayDEYIISoLr9fLqa0/k7z4HWIvv5+Qui2w2azE9biCG2smk5XjolOLGuc/UBXmb4LaCtQCJEEJIcR5uDJSOf7NW2TqVQB899HHuLuN46p+TQFo1UieFfSHvwnqFeAtpdQrwA4gt/BKrfWi0g5MCCEqGq/XS8bGpaQseQ9P9ikszhBOtbqCd5bYaLD+AJf3aYLNajn/gQTgf4Ka6ftvUfPYeJFBEkKIKs6Vnsyxha+S9ccmAEIaJxI/dAL2qHgm1T5Il5YJkpxKyK8EpbWuvNPlCiFEKbDY7OQk/UGONYRPT3XmlgG3YI8yHpC/tF1tk6OrmEo0m7lSqj/QCmOqo63AEq312RPLCSFEFZB7bD+OmAQsNge2sChqXD2Jt78/zvrfT7D7YDo14/ybwUUUzd/noBKA+UAHYA/Gg7r1gW1KqQFa66NlFaAQQgQaryuP1J/mkvbzPBydLie40xXER4cQUq8lN12Vw9XDXNSMCzM7zArP3667lwEXxpO+zbTWTYEGQArwYhnFJoQQASd7/zYOvP0AaSvmgsfN0hVbefV/GwrKsUeFB0lyKiX+dvENAfpqrQ/mL9BaH1JKPQB8WyaRCSFEAPHkZJLy/Yekr/sG8OKIqUVQ31v4etYhOoQ4yHV5CHLIeLHS5G+CysYYrXcmGcEnhKj0XCeOcfC9R3BnpOC1WKnW/Uqie16N1e5k2qTmxFSx+fPKi79dfIuBF5VSBY89+16/AHxTFoEJIUSgsEXG4YipRZK1BlPThvFbVC+sdieAJKcy5O8V1EPAUmCvUmqvb1l9YBNwQ1kEJoQQZvF6PWRsWEJIgzY4ohOwWCzUuPJBNm88jmPFH3KPqZz4+xxUklKqLca9qJZAFrBVa/1dWQYnhBDlLff4AY4vep3s/VvJimlKeo976N62FrbQCAZ2Dad/l/rYbfJoaHkoruR7aH6dJ6VUfq3xpb5/FF5e1vWghBCirHldeaT9Mo/Unz4FtwtPUASz9yXwx5GNtG0aT1iIA6vVghWZDaK8FHcFlaGUqul7xukkRQ+SsCADJYQQFVz2/m0cW/QaeccPABDRrj/V+o4laM5WxreuSWhwieY0EKWkuP/r/TCec8p/7X/pXSGEqCDcp05w+KOn8LpyOWGLpv4VdxGj2gPw6M1dzQ2uijtngtJaLyv0+odyiUYIIcpB/kO1FosFW1gU1S69miW/7OTDw00ZtcPBeGVygAIo/h7UHH8PorW+pnTCEUKIsuVKP87xr98irGUPQlv2xGa1EN3jKro0TidjzX6uGyjZKVAU18V3qtyiEEKIMub1uElf+xUpyz7Gm5vN0T92smJrBHeOTgSgXkIkN49oZXKUorDiuvhuLs9AhBCirOQk7eb4otfJObzLWNCgIy9sakTWiYNcP6QF0RHysG0gKq6L704/j+HVWr9WSvEIIUSp8eTlkPrjJ5xYtRC8HmwRscQNuY2wZp25ufl+WjSMleQUwIrr4nvIz2N4Ab8SlFKqpm/bvhjz+72ptX7cz/MIIUTJWCxkbl+L1+tlRU4Luoy+k7BmtQDo07GuycGJ8ymui69hGZxvAbAOqAHUBJYppbZqrT8qg3MJIaog18k0LDY7tpBwrHYn8SPvZtHPe5i7MovgvRm0aGZ2hMJfxXXxXQZ8q7XO870+F6/W+qvznUgp1RVoBPTQWucBfyil+mBMmySEEBclf/68lKUf4GzSFe8l46gdH05w7WYMu7wxqmMarRrFmh2mKIHiuvgWAgnAUd/rc/F3JomOwGbgSaXUeIwuvula6xf8C1UIIYpWeP48gM2bdvCl/oUX7u+Pw24lyGGT5FQBFdfFZy3q9UWIAXoCyzCupJoDXyulDksXnxDiQnhdeaT9PI/Un43582xhUUT2u5lPv8imWkgwGZm5Ug6jAivRBFNKqcZAKyAHYzbzfSXYPQdI11o/6Xu/USn1NnAlIAlKCFEintwsDs58uGD+vLB2/YnrfxO2kHCeqZtFbFQwVqtM7FqR+XVlpJSKVkotBnYAczAGO/yhlPpQKRXh57m2AaFKKWehZTIDoxDiglidIQTVakqGPYb/pg/mx5AB2ELCAYiPDpHkVAn423X3BlANaK+1DtZaBwNdgRbAq34e41vgGPCCUsqplGoD3AJ8XLKQhRBV1altK8k+oAvexw36C54RT5IaWo861f39riwqCn+vYIZhjL7blL9Aa71WKTUBWAKMO98BtNbZSqnewCvAYYxBElO11p+WPGwhRFXiykjh+Ddvk6lX4YlMYG+XB+jftRHWoFASW4by5iMJBDmk6k9l42+CSsIY5HCmECDN35NprXdjJDshhDivgqHjS97Hk5MJjmA+S6rH6s9+o2XjGgWl1yU5VU7FPQfVstDb14GZSqlJwErADbQFXgL+WZYBCiGqpryUwxxb9BrZe7cAENqkI3FDbydo0X5GRgYRGyWj8yq74q6gfsN4xqnwncaP+bNwYf7y14G3Sj80IURV5XW7OPThk7jTj5NjCyWi73hqdOmHxWLhnmtjsVhkAERVUFyCKoupjoQQ4rwsNjsxfW5gw/dLmbavJS1/C2NyVyMpSXKqOopLUA6t9c6SHEwp1VRrveMiYxJCVDFet4u0X+ZjsTuo1m0UABFtetOmQTfazN3A+OFSp6kqKi5BfaCU2gD8V2u9tbiDKKXaA3cBbTCGnwshhF9yj+7l6Bevkpu0G6/Vzsc7o/nrmJ5YLBaqRQTx6M3yJ6WqKi5B9QDuBX5QSqUCXwNbgOMY95/igXZAbyAWeA6YUKbRCiEqDa/HbUxTtPx/4HFhjYzjrWOd2LQ+lY4djtClZYLZIQqTFTcXnwf4j1JqOnA9cBkwEqNUhgdj6Pk64FlgrtZaZiUXQvgl9+g+31WTUeE2InEQsf1vYuCWZC7JzKVT8xomRygCwXmfg9Ja5wDv+v4JIcRFS/5uJrlJuzhliySr0400GtAPgD4d6pgcmQgkpTFLuRBCnJfX6y14HTd0Aml1LuWpY8N4Y5Ubt9tjYmQiUMlkrUKIMuX1ekhfs4isvVuoftVDWK1WHNEJJN70N0Z+tZXB3Rpgs8l3ZXE2+akQQpSZvBNHOfzhkyR/O5PM7at5/vlZnMzMBYznmW66rCU1YkJNjlIEKklQQohS5/V6ydj0PQfevJ/svVuwhkbxTehwlh+J4puVe80OT1QQfnfxKaXsQAPAwenTH6G1/r10wxJCVFTuzHSOLXqdTL0KgFDVlfihExiVaaPBzuMM6Vbf5AhFReFXglJKDQfewXjeKT855c/T5wVkKmEhBADp678lU68iz+Jka42hjLrqRiwWC7XCoFZ8uNnhiQrE3yuoZ4AfgaeA9LILRwhR0VXrNorUpCSmrI7m5MlIemXkEBMpM4+LkvM3QTUBrtVabyvLYIQQFU9O0m6Sl7xP7Mi/ERRRDYvNTqOrJjK+0QGa1YuW5CQumL+DJFZjzLMnhBCAMXw8beUCDs78O9l7NjPvvy+xZXdywfpeiXVIiA0zMUJR0fl7BTUPeFMp1QfYAeQWXqm1nl7KcQkhApgrPZmjX7xC9p7NAByK68qc7Y3Zs2I3rRrFmhydqCz8TVD3YZR2v6yIdV5AEpQQVcQpvZpjX07Dk3USW1gU8cMnUrdBIn9ZuYch3RuYHZ6oRPxKUFprKV4ohCD3+AGOzJ0KeNlrq0+38Y8SUs24Yhp+aSNzgxOVTkmegwoGxgCtMO5dbQVma63TyiY0IUSgccbVIbzb5Xy+6gifH2vMpL3ZXFrN7KhEZeXvc1DNgMVAGLAe4/mnG4AnlFK9Slp5VwhRMXi9XjI2LMEeU5Ogui2xWS1U7z+WXk1TaZuRQ5dWUrNJlB1/r6BexkhMY7TWmQBKqVDgPeA/wIiyCU8IYRZPbhbHv3qTk7/9yClrBNsS72f0kLYANKsXbXJ0oirwd5h5L+Cx/OQE4Hv9FEZFXSFEJZJzZA8H35nEyd9+xGtz8ll6Wz7/5RBZOS6zQxNViL9XUKlAtSKWVwPySisYIYS58rv0khfPwOvKxRFfjxpXPsAlu9zc1bw6IUFSoUeUn5I8B/WaUmqc1no9gFKqAzAN+KysghNClK/kxe+QvnYRAFbVi9qj/orVEcTAOJMDE1WSv118jwJHgHVKqSylVBawBuOh3fvLKjghRPkKbdQel8XJrJM9+CTzEqyOILNDElWYv89BpQMDlVKtMIaZZwFbZfSeEBVf7vEDOOPqABDatCO1/voq9X5O4tqByuTIRFV3zgSllGoJbNNae3yvwZg14jffa2f+cqkHJUTF48nLMbr0Ni5lecIYbho/CqvVQnhMLOOHy3RFwnzFXUH9BiQAR32vC9d/yif1oISogPJSDnHk0xfIPboHl9fGnh1/8MOvB+jXqa7ZoQlRoLgE1RA4Vui1EKISOLVtJUcXTsObk4k9OoG09uNpfiqS3om1zQ5NiNOcM0FprfcWevsEcK/WOqPwNkqpaOBt4KqyCU8IUVq8bhfJ388ifdUXAIQ170b8sDupFxxGB5NjE6Ioxd2Dagfkf6UaB3yrlDpxxmatgcH+nkwp9RfgDSCn0OKJWuv3/D2GEOLCuE+d4MT6pXi8Fr7K7cyYAXdhDQ4xOywhzqm4Lr4oYGGh9x8Wsc1JYGoJztcBeEFr/XAJ9hFClAJ7ZCw1r3qAT3/cS6tW7aXSrQh4xXXx/YjvOSml1B9AZ6318Ys8X0eMef2EEGXM6/WQsnwuv+/LoPWoMURHBBPaqB03NmpndmhC+OWi60EppWpprQ+d7xhKKRvQFrhRKfUikIlx/2qK1tpb7M5CiBJxnzrB0c9fJmv3Rmp4rbz9UV0emjDI7LCEKJGSlNt4DmjJn0PKLUAQUN3P48QDazFmQL8SaAEsANKRirxClJrsA9s48tkLuDNSsARH8Lm7D4P6JpodlhAl5u9cfK8BMb7//gt4DGgE3Arc5s8BtNZJnD7z+Qal1CsYIwAlQQlxkbxeD8dXzCd9+cdYvB6C6ihqXPEA94fHYLVazA5PiBLzdy6+bsAErfWLwEZgpdb6TuD/MAoXnpdSqpVS6qkzFjuBbH+DFUKcW/IPH5Px44dYvB4yGval1th/YI+MleQkKix/E5QFSPK93gbk9xfMB78foUgDHlBK3aaUsiqlOgL3ADP93F8IUYxqHQeTGxLH585hxPQfh8UmpTFExeZvgtqIcd8IYAt/dtXVxkhe56W1PgiMBCZg3Hf6FPin1nqu39EKIQp4PW7+WPENW3YZE77YI+Nodu80Jt43nro1IkyOToiL5+9XrCeBBUqpPGAW8JhS6gegObDI35NprZcCnUoYoxDiDK6MFPbOeRFL0lZWuLtQ94H7iAxzYrXZ/f7WKUSg8+tnWWv9DdAM+Mo3pPwSYDXwH/wcJCGEKB2ntq/hwFv3Y0naSpYlhMi6TbDb5D6TqHz87qTWWu8r9Po3YFKZRCSEKJI7N5tNH08n6sBPAIQ0akfCkIm0ipbSGKJyKm4uvjWcXlrjnLTWXUotIiHEWVwZKfz+xqNE5RzFg5W4ATcS1WU4Fot06InKq7grqIXFrBNClCNbWBThUZEcP5KDp9ftNOnazeyQhChzxc3Fd+YzS0KIcnRw7z627E5lUN92WKw26l33MLVtToJCw8wOTYhy4e9UR8XOWK61lvtRQpSi4xt+JHXha+S54tjW4EmaN4zFHhHt/01jISoBf3/eOxexX0MgGvikVCMSogpzZ58iefEMTm5eRqgFoiNDqFnNYXZYQpjC39nM+xa1XCn1EuAqzYCEqIrcHi9L5n9F472fYclMxWJ3Et1/HA07DsZikSHkomq62B6D/2LMUP5gKcQiRJXk9XpZ9+5/aHLYGD7urNmE6qPuwRlb+zx7ClG5XWyCGgS4SyMQIaoqi8VCg/rVOXHYSm6rYTQceSMWq+38OwpRyfk7SKKoZ6KigCbAs6UdlBCV3b6DyXz//VrGXD8Qu81KfJ9rqdamJ87q9c0OTYiA4e8V1JnPRHmBXGCN1npJ6YYkROWWuV9z5P2ptPXk8NX3CYwY0A6LzSHJSYgz+DtIQp6JEuIieVy5pP44mxMrPycWDxlBsfRsHmV2WEIELL/vQSmlbgTuBFpj3HfaCPxHaz2/bEITonJwe7x8u3Ap9XfNJSjzKFisRHW/nAa9rsVqd5odnhABy997UPcC/wbewBi5ZwW6Ah8qpe7QWr9fdiEKUbFtX/QRTTZ9htUC1uhaJIy6m+DazcwOS4iA5+8V1APAbVrrDwst+1AptQ54HJAEJcQ5NGjVhoMb55PVbAAtrrhZrpqE8JO/Caoa8GsRy38BapZaNEJUAsePJfP1p18y6JqrqR4TSkjDtjS4azr2qHizQxOiQvF3rv53gKeVUqH5C5RSdowHdGeWRWBCVESndqzlyDsPcknyAhb876uC5ZKchCg5f6+gGgKDgQNKqQ0Y0xu1BmoAm5RSq/M3lNpQoirKPpHMiaXvcer3nwgBUpw1GTWwrdlhCVGh+ZugfuXsLr6fSjkWISqclPQsvv3wY9qmLiHIm43FEURMnxto2GmozAYhxEWS56CEuAg56xbSOeVLAKx1WlN71EQc1aqbHJUQlUNJnoMaCjwCtMK4d7UNeElrLeU2RJWyLymdujUisFgsVO8yiN2blhLa9QpqdR0oM48LUYr8GiShlLoJmA9sBu4CJmJ0+c1USo0ps+iECDDz53zF2teeYPmvewGjFHuTu1+ldrdBkpyEKGX+XkH9Hbhfaz2t0LIPlVKbgIeBD4veTYjKwZ2VQcrSWbTd8R04Yf+2H6DjeAC51yREGfE3QdUHvi5i+XfAf0ovHCECy+4DaZza8iMRv8/Dk5kOVjvWdpfRc9D1ZocmRKXnb4LaAfQHdp2xfACwr1QjEiJA6E1b2PPZNJo6juABguu1Im7o7Tjj6pgdmhBVgr8JagrwjlKqFbDSt6w7cBvGBLJCVDoJniM4HEfItYUSP3AcMR36y30mIcqRv8PMP1JKWYC/YSSlLGArMFprfWatKCEqpO37UlmwaBV/vakfEaFOItv1xX0qjajEgdhCI8wOT4gqx+9h5r6JYmUwhKiUXBmp7Jv9HCNydvLlV2Fcd1VPLBYLMT2uNDs0IaqskjwH1Qu4gz/rQW0AXtFaryub0IQoW263h5xcF3m/fUfKso9plJuJ2+pgUFPpxhMiEPhbD+o6YBbwBfARxvNTXYCflVKXa62/Km5/IQLNzgNpfPzRNwyzLqdazmEAQpt0JHbwrTIThBABwt8rqH8AD2itXy68UCl1P8YACklQokKx7/yR63P/h9XixRoRS/ygWwhVXWQQhBABxN9yG7UpOgl9ATQpvXCEKBt5LjertyQVvK/VugMWu52wTsOoN+Flwpp3leQkRIDxN0HNA+4pYvmNwIKSnFApVU0ptU8pNb4k+wlxodxuD5NfXMjqj95k6+5kAJxxdWhw9xvUGPwXrEEhJkcohCiKv118J4FblVIDgJ8x6kF1ABKBxUqpOfkbaq2vOc+xXse4IhOizHk9bjLWLuIv7k+whebi2rcaGg0FjHn0hBCBy98EFQR87HttARwYE8duLsnJlFLjgMiS7idESeS5PMz7YSeto9KJ3PgJuUf+wAaEqO7Ed+xqdnhCCD/5+6DuzRd7IqVUQ+AJ4BKKntdPiFLx9Y9bObnsY5zB28jFiz0yjtghtxHWtJPZoQkhSsDv56AuhlLKhjFM/UGtdZJSqjxOK6oQr9dbMMihu3Mb6cFb8VqsRHUdQXTPa7E6g02OUAhRUuWSoIDHAa21/qyczieqCI/Hy+JVe/lh7V7+eUdPHHYrMd1G4D62l2rdryAooaHZIQohLpC/o/gu1nXA1UqpNKVUGtAGmK6Uml5O5xeVVF6eiz3fz+fy1Jn8vG4nAFa7kxpX3C/JSYgKrlyuoLTWzQu/V0ptwCgX/255nF9ULtm5LmxWK57kfRxf9DqDvDvABrHWnUAzs8MTQpSScyYoX5l3v2it3y+dcIQo3uZdx5n+yRrG1tpBzaQV4HFjC48hbvAthDXvZnZ4QohSVNwV1AtnvI8BPMAhIBeoC9gwihmWKEFprduXZHsh8lmStjPePZv4QxmAhciOQ4jpcwPW4DCzQxNClLJzJiitdXz+a6XUROBK4Cat9UHfsjhgJvBrWQcpqi6v18uew+k0rGU8VNu4dgSHbRk44usSP+xOgmtLl54QlZW/gySeAO7NT04AWuvjwMMUPQWSEBctN8/NI9NX8Mqrczl8/BQAIQ3aUGP0w9S55XlJTkJUciUZxVeziGWNgexSikWI06UncXn2Z9wVtojk7ZsKFoc164zFVl5PSAghzOLvb/lM4D2l1D+A9RjTHXUFHgVeKpvQRFWk96YQGWIlWC8m9adPiXe7sIRE0DBOEpIQVY2/v/V/B7Iwuvpq+JYdBqZqrZ8vi8BE1fPDuv0s+N8ibqy2hmruVADC2/Yjtv9N2EIjTI5OCFHe/J2LzwM8CTzpGxyRfw9KiFLTIm8L9SIWgxvsMbWIv2wCIfVbmx2WEMIkxT0HdVlxOxaeT09rvagUYxJVRPKJLJas2c/o/k2xWCzEtelO1qq5RHUYRLXuV2CxO8wOUQhhouKuoBb6eQwvxvNQQvjN7fYw9dUvaJu9jmXV7qBPpwbYwqKod+c0rI4gs8MTQgSA4p6DKhjhp5RqrrXeVj4hicrOk5fDiZ8/43bLPCzBbpzpa4AGAJKchBAF/B0k8YNSarjWem2ZRiMqrawcFx99s43WwUnU3DkPV2oSFiC8fX9iuw8xOzwhRADyN0GlANXKMA5Rya1Zu42otTOJD9qDC4yZIIZOILhuC7NDE0IEKH8T1PfAQqXUUmAXxpDzAlrrSaUdmKj48lweHHajp7h9+DGOB+3Ba3MS22s0UV1HYLHJIAghxLn5m6BaAr8AIcCZ4369pRqRqPDcbg9zl+5g+apt/Pv+oUSEOolo2wdXyiEiEgfiqFbd7BCFEBWAv89B9S3rQETl4c05SfiGj5nIVtatrkOfPh2xWCzE9B1jdmhCiArE7/ljlFJtgElAK4w5/LYCr2itfy6j2EQFcvj4KUKCrFh3/UzK97NokZuO12qlY0y62aEJISoovxKUUmoo8DnwLTAXYy6+S4BlSqlhWuvFZReiCHRL1+7j07lLuTl+PTHZBwAIrteKuCG34oyvZ3J0QoiKyt8rqGeAp7XWTxVeqJR6DPgnIAmqCmt0cj33hS/Emu3FGlaN2AHjCG/VE4vFYnZoQogKzN9yGy2AD4tY/gnQpvTCERXB738kM/tbXfC+VuuOWB0OIjsPo95f/0tE616SnIQQF83fK6h9QCKw84zlHYGjpRqRCGgnTubwzluf0da2G930QVSDWJxxdah/9xvYQiPNDk8IUYn4m6CmAa8rpeoAK33LumPUg5paFoGJwOFye7DbrOSlJpG99APuDDN+BKJPaoxbkUhyEkKUOn+Hmf9XKRWBURcqzrf4EPCE1vrVsgpOmG/lb4d5f8E67lEHcO78HtwuLHYn1bpfQZTqaHZ4QohKrLhyG0OA5VrrUwBa62eAZ5RS1YEsrXVGOcUoTHRy0/f81bMQp84BILxtH2J634A9MtbkyIQQlV1xV1BfAi6l1FpgKbAE+EVrLfecKrHUjGxS03NoVDsKgPZ1HKT/kUNQnRbEDbqZoJqNTY5QCFFVFJeg4oAeGPeaLgXuA6xKqZUYCWspsEpr7S7zKEW52L4vlRlvfkaNMDf3TLoVu81KTLcRhNSoR2izLjIyTwhRroqrB5WKUbRwIYBSygZ0wEhY3YG/AHFKqeVa62HlEKsoQzlH9hD+80dMCFlHNqFkpI0mOjYaqzOYMNXV7PCEEFWQ31Mdaa3dSqkDwGGMoeX7gOpAozKKTZSxQ8dP8s03KxkSvJGsbcaMVRZHMDW7jyAqIsTk6IQQVV2xCUopFQ70AQYAA4HmwH6M8hszgBu01ofKOEZRBtzZmfz69r/p6dJkWbxYbA4iOg4m+pIrsYVFmR2eEEIUO4pvOdAFSAV+AF4Glmqtz3xYV1QQHo8Xt8eLw27FGhSMCs+AExacrfuS0Pda7JFx5z+IEEKUk+KuoHoAB4B3MAZE/KK1ziuXqESp271tJ1s+/4BsNYjRo3pgsVipd+U9WEPCcUQnmB2eEEKcpbgE1Qija68/cAcQppRagTHcfCnwq9ZaihUGuLzUJNJ++gzvpu9p5fWw/jc3ecO647BbCarVxOzwhBDinIobxbcHeNv3D6VUO6AfRsJ6HMhTSv0ALNFaTy/zSEWJ7Nu2jZSfPiPyyHrwerBYrJyq3ZmBg64vKMMuhBCBrCSj+DYCG5VSL2NMEnszcCNwOSAJKoAkLZ9P7rIPiLQAFivhbfsQ3eMqHDG1zA5NCCH8dt4E5ZsgtivQzfffDoAL+Bl4GmMAhTDR0ZRMNv6+jwE9FBaLhehm7clY/jH7otrTauQY4utK0UAhRMVT3Ci+TzESUk0gA/gJ+AJ4EFh3ITNIKKWGA/8CGmI8SzVVa/3GBcQtAK/Xw8nta/l9zkxww97GU2hQM5KgGg1o+Le3aRoaYXaIQghxwYq7ggoCXsK4QvpVa+25mBMppWpilIu/Qmv9lVKqA/CTUmqN1vrXizl2VeF2e/huzX7WbzvEHYk5pK+aT96x/dSzQo49GO+pVMAoe2GX5CSEqOCKGyQxvDRPpLU+rJSK11pnKKWsQCxGV6HMil4Mr9f75xx47lz2LZnLQPcGkg9mAmCLiKVat5FEtO+P1SmzPwghKg+/B0mUBl9yCgVO+M49RWu9ozxjqCjcbg9zl+5g+YaDPH9vL4KddiweN31t67CSgy22DjHdRxHeuicWm8PscIUQotSVa4LyyQbCgLbAIqXUDq31DBPiCGg2m5Wdm3+nU/oaVm1sQO/OjbAGh1F90HhsETGENumAxSLDxYUQlVe5JyjfvaxcYK1S6k1gFMa8flXapp3HmL9sF/dc0x7ncc2JlV9wfdZ6CIZY207y5+SN7DDI3ECFEKKclFuCUkr1Bl7UWheuEx4EpJVXDIFswfcadq9m/1sfEJaVBIDF7iSiXT9CG7Y1OTohhCh/5XkFtQGorZS6H2Pi2a7ALcAV5RhDQMhzuflh3QHaNIkjITYMgOutX2MN3wpZYAurRmSnoUR2GIxNRuMJIaqocktQWusTSqnLgP8CT2CU7bhVa72svGIIFDMX/s6vP69lX2ITbrm+JwA1OvXjxOosoroMI7xVTyx2GfgghKjaynsU368Y5eOrlJT0bHLz3NSoFsQpvYqBx79gQNQOTnp6A0aCCm/Tm/C2faWsuhBC+Jgxiq9K+WnTIV7/cDlX1z5Ee+/vuE+mAGAJCqVO7T/rL1msNrNCFEKIgCQJqpS5PV5OnMwhJjIYgEYn1/N4xFzsGR7cgCOuDpEdhxLRpjfWIHmwVgghzkUSVCn649AJnpu5glrhHh67dwQAMQ0UWVYvoU06E9l5KCEN2ko3nhBC+EES1EXKynEREmQn59BOgtct5m7vMpJOxpN+ajCRYU6CajWh3t1vYY+INjtUIYSoUCRBXaDUjGxenvUL1VM3MbLGAXKTdgMQZIFm9aIJd/5ZbFiSkxBClJwkqBI4mZVHeIgx/Nt5fAfXJb+O0+IiNwmsIeFEtOlDROJAnHF1TI5UCCEqPklQfsjOcTH17R/IOrKfpx6/CafDRnDNRjjsVhwJzanWaTBhzbthtTvNDlUIISoNSVBF8Hq9HDh6kjrVw8j6YxMZG5dyfdovZDmc7N43jOaNq2MLDqP+Xa9hD69mdrhCCFEpSYI6g8vt4dHnFtDw1GaGxB/Ek3EcABsWYhoqEqr/+b9MkpMQQpSdKp+gjqRksmnHMQZ2rQ+AJ/kAE9yzIBg8GWCvVp2Itv2IaNcXe2TceY4mhBCitFTpBOVyuZnyn7nUdB+iVeO7qBUXjiO+Lra4+gTXqEdk+/4E128ldZeEEMIEVSZBZee6+GDRVnbsT+OZWxLJ/H0FGRu+467gPwBwpR2FuHAsFgv1bntOph4SQgiTVZkE5bRb2b/pVzq4fmPff6djcecCxvDw8Na9qVY9qmBbSU5CCGG+KpOgvNmnGOdYhMXmAjcEN2hDZPsBhKmuUtpCCCECUJVJULbQCKI6DMLqDCKiXX8cMTXNDkkIIUQxqkyCAogbfIvZIQghhPCTDE8TQggRkCRBCSGECEiSoIQQQgQkSVBCCCECkiQoIYQQAUkSlBBCiIAkCUoIIURAqijPQdkAkpKSzI5DCCFEKSr0d/2sOeYqSoKqCTBmzBiz4xBCCFE2agK7Ci+oKAlqDdATOAy4TY5FCCFE6bFhJKc1Z66weL3e8g9HCCGEOA8ZJCGEECIgSYISQggRkCRBCSGECEiSoIQQQgQkSVBCCCECkiQoIYQQAUkSlBBCiIAkCUoIIURAqigzSZyTUqoLsFBrXd33Ph54GRgM5ADvAE9ord2+9e8D1wCuQodpq7XerZSqB8wAugFHgbu11ovKrTFcUHsu8a1vARwCHtFaz/WtM7U9JWmLUup1YOwZhwgDHtVa/8vstsAFfTY3A48BccA24AGt9QrfuorYnruB+4BY4GdgotZ6t5ntUUoNBJ4FmvrO+5zW+g2llBN4FbgaY/aZF7XW/y603zXAvzBmMFgGjNdaHzWzLRfTnkL73wf01lpfXmiZ6T9rF6rCXkEppSxKqVuBxYCz0Kr3gOoYf7BbA12AfxRa3wG4XGsdXujfbt+6T4BNGL+AtwGfKKUalXFTgAtrj1KqJvAlxg9uBDARmOX7gQST2nMhbdFa/7XwZwI8BPzua5tpbbnQ9iil2gIvAqOAasAsYL5SKv93rqK15xrgGeBmX8yfA98qpYJ9+5Z7e5RSdYFPgacx/h9fD/xbKTUYeApQQGOgMzBOKXWTb7+WGH+wx/vi3eGLP59ZvzcX1B7fvuFKqeeAF4o4tGk/axerwiYojA/sDowPEwClVCgwBLhPa31Ua50CPA7c5vulDAGaAxvOPJhSqhnQCZistc7VWi/F+CW8pcxbYihxe4CbgB+11u9prb1a628x/qikmtyeC2kLhbZtDEwFbtBap1fQz6Ypf/5+WTC+9Wb59q2I7bkKeEtrvUxr7dJavwbkAv1NbE8D4COt9TyttUdrvQb4AegBjAOe0Vqnaq33AM8DE3z7jQW+0Fqv0FpnA38Heiilmpr82Vxoe8D4otoQeKPwAQPgZ+2iVOQE9brWuiOwttCy/PacKrTMDcRjfCNpj9G195ZS6phS6lel1HDfdi2BfVrrwvtuA9qUQexFuZD2dAT2KKU+UUodV0qtBxK01hmY254LaUthL2D8Mdzoe18RP5tvgN+AzRh/yKcA12qtPVTM9ljPWJe/vhkmtUdrvVxr/df890qpGIxJpddjdN39fo54WhZep7XOBPb71pv22VxEewCu11pfDRw547Bm/6xdlAqboLTWh4pYdhKj22KqUipGKRULTPatDsHoBluO8Q2yFkaXxRylVDsgHMg845CZQGjZtOCs2C+kPTEYl+yzMH6A/w3M812BmNaeC2wLAEqp1sBAjD/o+SriZxMMaIx+/zDg/zC6+BKomO35FLhdKdVJKeVQSt2G0RsRgsntAVBKRWFcGawC1hWKoah4iovX9LZAidtT5GfqExDtuVAVNkEV40aMb6xbMW5+zvctT9NaL9ZaD9Rar9Va52mtPwWWAiMxvh2GnHGsUOBk+YR9TudsD8aN7K+11gt97ZkD/AoMJTDbU1xb8v0FmK+1LvxNMBDbAsW350kgSWu9Smudo7WeDuwBRlMB26O1/gTjC9AnGFcbrYFvgVRMbo+vG2slxtXD1UCGb1XhmArHU1y8pn82F9Ce4pjenotRGRNUTWCC1rqG1ro1cBDYqrXOVEqNUEqNO2N7J5CNcflcz3efKl9zTr+sNsM524NxqR59xvb5IzMDsT3FtSXfKE6/YQ2B2RYovj11gaAztncBeVTA9vgG5HyhtW6itU4A7sdIUuswsT1KqV4YVxnzgau11tla61QgCWNQQVHx/F54ne/+Wz3fclM/mwtsT3EC9WfNLxV+mHkRXgR+U0o9iPFDN4U/R4LZgJeVUlsxfrGuBS4BbtVa71NKbQSeUUr93bd8FNC9vBtwhuLa8z5wl1JqLPARxrfztsA1Wuv9Adie4tqSP8y5EfBT4Z201joA2wLFt2chRnfZHIxCbGOAVsCXAfrZQPHt6Q88oZTqCaRjdP8dAtZorb1mtMfXlb0Q41GEV85Y/YEv3k0Y3VwPYgyhB+N3ZYVSqg/wC8aV4Xqt9XbfcU35bC6iPecUwL87fqmMCeo24C0gBaOr5RVf9wpa6/lKqUeBj4EEjCuQ4Vrrfb59rwLexHhW4Dhwi9b6t/IN/yzFtWejUuoyjD8k04F9wJVa6/2+fQOtPedsi08DIMc3guxMgdYWKP6zect3H+EjjOegfgcuC+DPBor/fD7EuLG+EaPXYQkwUmudX/HUjPZMxLiv/G+lVOFngqZhJNAXgC0YPUVvAq8DaK03K6X+4ntfG+OKZXSh/c36bC6oPX4IxJ81v0hFXSGEEAGpMt6DEkIIUQlIghJCCBGQJEEJIYQISJKghBBCBCRJUEIIIQKSJCghhBABSRKUEGXEN4nvMd+kn2eue1QpdVIp1cCE0ISoECRBCVF2/obxMPxpheWUUg2BRzFmDNhT/mEJUTFIghKijGitkzBqDd2qlOpaaNUrGDXJzpzORghRiMwkIUQZ8hX7+wljeqDOGDPnzwESMWYFfwFjxmovxsz69+aXTlBKNfWt74UxI/UO4BGt9ee+9V6MooO3Y0wm2kH7yrMLURnIFZQQZcg3V93tGJP43oxRCfVprfXvGPOjKWAw0BsjSX2jlLL7EtsXGKUWumEU29wMzFRKFS7TPgboB4yT5CQqG7mCEqIcKKWeBR7AqLXUEaMcxy6gjtb6oG+bIIzJPK/HuJq6E3gnf/JcpVR+Fdx6vhnRvcDftdbPlnd7hCgPcgUlRPl4CmPAxD+11nkYpbgBtG8030kgGaP6rvLVlHoNuEop9YZS6nuMpAVG2Zh8u8onfCHKX2UstyFEwNFaZymlALJ8i+wYxQsTMbr2CktRSoVhlIHIAuZhlP8+CfxwxrZZCFFJSYISwhxbAQcQprXeAOBLSrMw6nvFAk2BKK11tm/9Nb59LeUerRAmkAQlhAl8lU4/B95XSk0EjgHPYAyI2IZRltsJXKuU+gHoALzk2/3MUvJCVEpyD0oI84zDGPQwH6MsfBQwUGudprVeifEw77MY1XgnY5T5TsUYZCFEpSej+IQQQgQkuYISQggRkCRBCSGECEiSoIQQQgQkSVBCCCECkiQoIYQQAUkSlBBCiIAkCUoIIURAkgQlhBAiIP0/XSvDGt+pQyoAAAAASUVORK5CYII=\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ "plot(census, ':', label='US Census')\n", "plot(un, '--', label='UN DESA')\n", @@ -248,9 +496,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1.3821293828998855" + ] + }, + "metadata": {}, + "execution_count": 14 + } + ], "source": [ "max(abs(census - un) / un) * 100" ] @@ -269,44 +528,140 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 0.032480\n", + "1951 0.022089\n", + "1952 0.017480\n", + "1953 0.016188\n", + "1954 0.017056\n", + " ... \n", + "2012 -0.066201\n", + "2013 -0.069991\n", + "2014 -0.073816\n", + "2015 -0.101579\n", + "2016 NaN\n", + "Length: 67, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 15 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "census - un" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 0.032480\n", + "1951 0.022089\n", + "1952 0.017480\n", + "1953 0.016188\n", + "1954 0.017056\n", + " ... \n", + "2012 0.066201\n", + "2013 0.069991\n", + "2014 0.073816\n", + "2015 0.101579\n", + "2016 NaN\n", + "Length: 67, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 16 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "abs(census - un)" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 0.012862\n", + "1951 0.008585\n", + "1952 0.006674\n", + "1953 0.006072\n", + "1954 0.006286\n", + " ... \n", + "2012 0.009350\n", + "2013 0.009772\n", + "2014 0.010190\n", + "2015 0.013821\n", + "2016 NaN\n", + "Length: 67, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 17 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "abs(census - un) / un" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 1.286247\n", + "1951 0.858540\n", + "1952 0.667365\n", + "1953 0.607232\n", + "1954 0.628640\n", + " ... \n", + "2012 0.935034\n", + "2013 0.977243\n", + "2014 1.019023\n", + "2015 1.382129\n", + "2016 NaN\n", + "Length: 67, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 18 + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "abs(census - un) / un * 100" ] }, { @@ -332,9 +687,20 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "2.557628654" + ] + }, + "metadata": {}, + "execution_count": 19 + } + ], "source": [ "census[1950]" ] @@ -348,9 +714,20 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "7.325996709" + ] + }, + "metadata": {}, + "execution_count": 20 + } + ], "source": [ "census[2016]" ] @@ -364,27 +741,60 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1950" + ] + }, + "metadata": {}, + "execution_count": 21 + } + ], "source": [ "t_0 = get_first_label(census)" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "2016" + ] + }, + "metadata": {}, + "execution_count": 22 + } + ], "source": [ "t_end = get_last_label(census)" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "66" + ] + }, + "metadata": {}, + "execution_count": 23 + } + ], "source": [ "elapsed_time = t_end - t_0" ] @@ -398,18 +808,40 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "2.557628654" + ] + }, + "metadata": {}, + "execution_count": 24 + } + ], "source": [ "p_0 = get_first_value(census)" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "7.325996709" + ] + }, + "metadata": {}, + "execution_count": 25 + } + ], "source": [ "p_end = get_last_value(census)" ] @@ -423,18 +855,40 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "4.768368055" + ] + }, + "metadata": {}, + "execution_count": 26 + } + ], "source": [ "total_growth = p_end - p_0" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0.07224800083333333" + ] + }, + "metadata": {}, + "execution_count": 27 + } + ], "source": [ "annual_growth = total_growth / elapsed_time" ] @@ -455,9 +909,21 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "TimeSeries([], dtype: float64)" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n
values
\n
" + }, + "metadata": {}, + "execution_count": 28 + } + ], "source": [ "results = TimeSeries()" ] @@ -471,9 +937,22 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1950 2.557629\n", + "dtype: float64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n
values
19502.557629
\n
" + }, + "metadata": {}, + "execution_count": 29 + } + ], "source": [ "results[t_0] = census[t_0]\n", "results" @@ -488,7 +967,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -505,9 +984,28 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap05-fig02.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ "plot(census, ':', label='US Census')\n", "plot(un, '--', label='UN DESA')\n", @@ -546,18 +1044,82 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 48, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "1970 46 3.712697742 7.325996709 0.07854997754347826\nSaving figure to file figs/chap05-fig03.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "t_0 = 1970\n", + "elapsed_time = t_end - t_0\n", + "p_0 = census[t_0]\n", + "annual_growth = (p_end - p_0) / elapsed_time\n", + "\n", + "print(t_0, elapsed_time, p_0, p_end, annual_growth)\n", + "\n", + "results = TimeSeries()\n", + "t_0 = get_first_label(census)\n", + "results[t_0] = census[t_0]\n", + "for t in linrange(t_0, t_end):\n", + " results[t+1] = results[t] + annual_growth - 0.01\n", + "\n", + "plot(census, ':', label='US Census')\n", + "plot(un, '--', label='UN DESA')\n", + "plot(results, color='gray', label='model')\n", + "\n", + "decorate(xlabel='Year', \n", + " ylabel='World population (billion)',\n", + " title='Constant growth')\n", + "\n", + "savefig('figs/chap05-fig03.pdf')" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1960 3.043002\n", + "1961 3.083967\n", + "1962 3.140093\n", + "1963 3.209828\n", + "1964 3.281201\n", + "1965 3.350426\n", + "1966 3.420678\n", + "1967 3.490334\n", + "1968 3.562314\n", + "1969 3.637159\n", + "1970 3.712698\n", + "Name: census, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 32 + } + ], "source": [ "census.loc[1960:1970]" ] @@ -586,9 +1148,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/figs/chap02-fig01.pdf b/notebooks/figs/chap02-fig01.pdf new file mode 100644 index 0000000000000000000000000000000000000000..4e2a9cf6f23ca40beaf094e79ae2dfb769366903 GIT binary patch literal 13915 zcmb_@2{cvT7jPlNLm@+Cc*t11`8|Zp^E?;I!!ysGIh8RXV;M?h7D*9>D1^);MWjiC zWJ;)r@7{-gk@f$qZ+*|Y?z#J%v&VDK-uvEt1@x3u#1P_Wh``MeXh{tO0fj@|t(_p! 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| 229 ++++++++++++++++++++++--- notebooks/chap07.ipynb | 293 ++++++++++++++++++++++++++------ notebooks/figs/chap06-fig01.pdf | Bin 0 -> 17505 bytes notebooks/figs/chap07-fig01.pdf | Bin 0 -> 17948 bytes notebooks/figs/chap07-fig02.pdf | Bin 0 -> 17948 bytes 5 files changed, 454 insertions(+), 68 deletions(-) create mode 100644 notebooks/figs/chap06-fig01.pdf create mode 100644 notebooks/figs/chap07-fig01.pdf create mode 100644 notebooks/figs/chap07-fig02.pdf diff --git a/notebooks/chap06.ipynb b/notebooks/chap06.ipynb index aee7cc16..0e8e3a9a 100644 --- a/notebooks/chap06.ipynb +++ b/notebooks/chap06.ipynb @@ -57,7 +57,24 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.525149\n", + "1951 2.572851\n", + "1952 2.619292\n", + "1953 2.665865\n", + "1954 2.713172\n", + "Name: un, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 3 + } + ], "source": [ "un = table2.un / 1e9\n", "un.head()" @@ -67,7 +84,24 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.557629\n", + "1951 2.594940\n", + "1952 2.636772\n", + "1953 2.682053\n", + "1954 2.730228\n", + "Name: census, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "census = table2.census / 1e9\n", "census.head()" @@ -77,7 +111,18 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0.07224800083333333" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ], "source": [ "t_0 = get_first_label(census)\n", "t_end = get_last_label(census)\n", @@ -108,7 +153,23 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "t_0 1950.000000\n", + "t_end 2016.000000\n", + "p_0 2.557629\n", + "annual_growth 0.072248\n", + "dtype: float64" + ], + "text/html": "

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t_end2016.000000
p_02.557629
annual_growth0.072248
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" + }, + "metadata": {}, + "execution_count": 6 + } + ], "source": [ "system = System(t_0=t_0, \n", " t_end=t_end,\n", @@ -186,7 +247,17 @@ "cell_type": "code", "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "results = run_simulation1(system)\n", "plot_results(census, un, results, 'Constant growth model')" @@ -258,7 +329,24 @@ "cell_type": "code", "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap06-fig01.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "results = run_simulation2(system)\n", "plot_results(census, un, results, 'Proportional model')\n", @@ -317,7 +405,18 @@ "cell_type": "code", "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 14 + } + ], "source": [ "update_func1" ] @@ -333,7 +432,18 @@ "cell_type": "code", "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "function" + ] + }, + "metadata": {}, + "execution_count": 15 + } + ], "source": [ "type(update_func1)" ] @@ -379,7 +489,24 @@ "cell_type": "code", "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "t_0 1950.000000\n", + "t_end 2016.000000\n", + "p_0 2.557629\n", + "birth_rate 0.027000\n", + "death_rate 0.010000\n", + "dtype: float64" + ], + "text/html": "
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t_end2016.000000
p_02.557629
birth_rate0.027000
death_rate0.010000
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" + }, + "metadata": {}, + "execution_count": 17 + } + ], "source": [ "t_0 = get_first_label(census)\n", "t_end = get_last_label(census)\n", @@ -396,7 +523,17 @@ "cell_type": "code", "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "results = run_simulation(system, update_func1)\n", "plot_results(census, un, results, 'Proportional model, factored')" @@ -460,7 +597,17 @@ "cell_type": "code", "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "system.alpha = system.birth_rate - system.death_rate\n", "\n", @@ -484,23 +631,67 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 38, "metadata": { "scrolled": false }, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "system = System(t_0=t_0, \n", + " t_end=t_end,\n", + " p_0=p_0,\n", + " birth_rate1=0.027,\n", + " death_rate1=0.01,\n", + " birth_rate2=0.023,\n", + " death_rate2=0.007)\n", + "\n", + "def update_func3(pop, t, system):\n", + " \"\"\"Compute the population next year.\n", + " \n", + " pop: current population\n", + " t: current year\n", + " system: system object containing parameters of the model\n", + " \n", + " returns: population next year\n", + " \"\"\"\n", + " if t < 1980:\n", + " net_growth = system.alpha1 * pop\n", + " else:\n", + " net_growth = system.alpha2 * pop\n", + " return pop + net_growth" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Solution goes here\n", + "system.alpha1 = system.birth_rate1 - system.death_rate1\n", + "system.alpha2 = system.birth_rate2 - system.death_rate2\n", + "\n", + "results = run_simulation(system, update_func3)\n", + "plot_results(census, un, results, 'Proportional model, combined birth and death')" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "# Solution goes here" - ] + "source": [] } ], "metadata": { @@ -519,9 +710,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/chap07.ipynb b/notebooks/chap07.ipynb index fb1ed01b..c4e25e95 100644 --- a/notebooks/chap07.ipynb +++ b/notebooks/chap07.ipynb @@ -56,7 +56,24 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.525149\n", + "1951 2.572851\n", + "1952 2.619292\n", + "1953 2.665865\n", + "1954 2.713172\n", + "Name: un, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 3 + } + ], "source": [ "un = table2.un / 1e9\n", "un.head()" @@ -66,7 +83,24 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1950 2.557629\n", + "1951 2.594940\n", + "1952 2.636772\n", + "1953 2.682053\n", + "1954 2.730228\n", + "Name: census, dtype: float64" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "census = table2.census / 1e9\n", "census.head()" @@ -160,9 +194,26 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "t_0 1950.000000\n", + "t_end 2016.000000\n", + "p_0 2.557629\n", + "alpha 0.024300\n", + "beta -0.001700\n", + "dtype: float64" + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
values
t_01950.000000
t_end2016.000000
p_02.557629
alpha0.024300
beta-0.001700
\n
" + }, + "metadata": {}, + "execution_count": 24 + } + ], "source": [ "t_0 = get_first_label(census)\n", "t_end = get_last_label(census)\n", @@ -171,8 +222,8 @@ "system = System(t_0=t_0, \n", " t_end=t_end,\n", " p_0=p_0,\n", - " alpha=0.025,\n", - " beta=-0.0018)" + " alpha=0.0243,\n", + " beta=-0.0017)" ] }, { @@ -184,9 +235,26 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap07-fig01.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "results = run_simulation(system, update_func_quad)\n", "plot_results(census, un, results, 'Quadratic model')\n", @@ -211,7 +279,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -229,9 +297,26 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap07-fig02.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], "source": [ "sns.set_style('whitegrid')\n", "\n", @@ -262,9 +347,20 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "14.294117647058824" + ] + }, + "metadata": {}, + "execution_count": 28 + } + ], "source": [ "-system.alpha / system.beta" ] @@ -301,9 +397,17 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "13.88888888888889\n" + ] + } + ], "source": [ "def carrying_capacity(system):\n", " K = -system.alpha / system.beta\n", @@ -325,9 +429,17 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "13.88888888888889\n" + ] + } + ], "source": [ "def carrying_capacity():\n", " K = -sys1.alpha / sys1.beta\n", @@ -349,9 +461,17 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "13.88888888888889\n" + ] + } + ], "source": [ "def carrying_capacity(system):\n", " system = System(alpha=0.025, beta=-0.0018)\n", @@ -377,9 +497,17 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "None\n" + ] + } + ], "source": [ "def carrying_capacity(system):\n", " K = -system.alpha / system.beta\n", @@ -400,9 +528,20 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "13.88888888888889" + ] + }, + "metadata": {}, + "execution_count": 33 + } + ], "source": [ "def carrying_capacity(system):\n", " K = -system.alpha / system.beta\n", @@ -427,9 +566,17 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "13.88888888888889\n" + ] + } + ], "source": [ "print(carrying_capacity(sys1))" ] @@ -443,9 +590,20 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "27.77777777777778" + ] + }, + "metadata": {}, + "execution_count": 35 + } + ], "source": [ "total = carrying_capacity(sys1) + carrying_capacity(sys2)\n", "total" @@ -466,29 +624,66 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "sys3 = system = System(t_0=t_0, \n", + " t_end=t_end,\n", + " p_0=p_0,\n", + " r=0.0243,\n", + " K=-0.0243/-0.0017,\n", + " )" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ - "# Solution goes here" + "# Solution goes here\n", + "def update_func_quad2(pop, t, system):\n", + " \"\"\"Compute the population next year with a quadratic model.\n", + " \n", + " pop: current population\n", + " t: current year\n", + " system: system object containing parameters of the model\n", + " \n", + " returns: population next year\n", + " \"\"\"\n", + " net_growth = system.r * pop * (1 - (pop / system.K))\n", + " return pop + net_growth" ] }, { "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "# Solution goes here" + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving figure to file figs/chap07-fig02.pdf\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "# Solution goes here\n", + "results = run_simulation(sys3, update_func_quad2)\n", + "plot_results(census, un, results, 'Quadratic model')\n", + "savefig('figs/chap07-fig02.pdf')" ] }, { @@ -515,9 +710,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7-final" } }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/notebooks/figs/chap06-fig01.pdf b/notebooks/figs/chap06-fig01.pdf new file mode 100644 index 0000000000000000000000000000000000000000..84f481e6bd24186918e8fea7118d8a2dedbc5a51 GIT binary patch literal 17505 zcmb`v1z42N6F9EY2TFtV0a7Adz#S>w-HlR5C~%Z?NT<@Jgmeii2#5+wOQV3&C?O&( z0wN&4_fS7yLI1x$&;R-JJg@KG?9S}$%~#4?xn<5$)y*bOGQ?1FWDNfnP#D z3CO#kZ#aQ5!<5zrLu63yc9tkDd7x|HmyV0MqpOp-3(C>b>-Wfiwg)0xhXw}4?YG3VP_F13E|!1@F*5p3gczy*AwLW|zxkE3vj;>3hRE3i zGL%7CqOAattDqch+-$)xjApbjh^}rfD02spXGTG~YNBa1Y1sC*zAZsCeZFIfv5^$G 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