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@@ -46,6 +46,9 @@
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],
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"source": [
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"# Data science imports\n",
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+ "import cufflinks\n",
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+ "import plotly.graph_objs as go\n",
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+ "import plotly.plotly as py\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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@@ -53,9 +56,6 @@
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"from IPython.core.interactiveshell import InteractiveShell\n",
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"InteractiveShell.ast_node_interactivity = 'all'\n",
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"\n",
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- "import plotly.plotly as py\n",
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- "import plotly.graph_objs as go\n",
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- "import cufflinks\n",
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"cufflinks.go_offline()"
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]
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},
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@@ -82,8 +82,8 @@
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"outputs": [],
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"source": [
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"def calculate_multipliers(ci):\n",
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- " z = (1-ci)/2\n",
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- " return z/(1-z), (1-z)/z"
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+ " z = (1 - ci) / 2\n",
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+ " return z / (1 - z), (1 - z) / z"
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]
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},
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{
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@@ -146,7 +146,7 @@
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"source": [
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"def calculate_lifetime(t_current, ci):\n",
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" low, high = calculate_multipliers(ci)\n",
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- " return t_current*low, t_current*high"
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+ " return t_current * low, t_current * high"
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]
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},
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{
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@@ -226,7 +226,9 @@
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" low, high = calculate_lifetime(t_current, ci)\n",
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" now = datetime.now()\n",
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" try:\n",
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- " print(f'Estimated lifetime from {(now + timedelta(days=low*365)).date()} ({low:,.2f} years) to {(now + timedelta(days=high*365)).date()} ({high:,.0f} years).')\n",
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+ " print(\n",
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+ " f'Estimated lifetime from {(now + timedelta(days=low*365)).date()} ({low:,.2f} years) to {(now + timedelta(days=high*365)).date()} ({high:,.0f} years).'\n",
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+ " )\n",
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" except:\n",
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" print(f'Estimated lifetime in years: {low:,.2f} to {high:,.0f}.')"
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]
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@@ -303,7 +305,7 @@
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}
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],
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"source": [
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- "print_lifetime(2018-2012, 0.95)"
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+ "print_lifetime(2018 - 2012, 0.95)"
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]
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},
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{
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@@ -325,7 +327,7 @@
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}
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],
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"source": [
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- "print_lifetime(2018-2012, 0.5)"
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+ "print_lifetime(2018 - 2012, 0.5)"
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]
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},
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{
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@@ -356,7 +358,7 @@
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}
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],
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"source": [
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- "print_lifetime(2018-1000, 0.95)"
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+ "print_lifetime(2018 - 1000, 0.95)"
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]
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},
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{
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@@ -389,7 +391,7 @@
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}
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],
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"source": [
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- "print_lifetime(2018-868, 0.95)"
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+ "print_lifetime(2018 - 868, 0.95)"
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]
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},
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{
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@@ -420,7 +422,7 @@
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}
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],
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"source": [
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- "print_lifetime(2018-1220, 0.95)"
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+ "print_lifetime(2018 - 1220, 0.95)"
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]
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},
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{
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@@ -2538,18 +2540,34 @@
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],
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"source": [
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"df = pd.DataFrame({'x': x, 'y': y})\n",
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- "df.iplot(x='x', y='y', layout=dict(xaxis=dict(type='log', tickfont=dict(size=16),\n",
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- " titlefont=dict(size=18),\n",
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- " title=r'$\\frac{t_{future}}{t_{currrent}}$'),\n",
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- " yaxis=dict(title='probability'), title = 'PDF',\n",
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- " shapes=[dict(type='line',\n",
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- " x0 = 39, x1= 39, \n",
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- " y0 = 0, y1=1,\n",
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- " line=dict(color='black', dash='dash')),\n",
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- " dict(type='line',\n",
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- " x0 = 1/39, x1= 1/39, \n",
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- " y0 = 0, y1=1, name='39',\n",
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- " line=dict(color='black', dash='dash'))]))"
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+ "df.iplot(\n",
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+ " x='x',\n",
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+ " y='y',\n",
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+ " layout=dict(\n",
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+ " xaxis=dict(\n",
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+ " type='log',\n",
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+ " tickfont=dict(size=16),\n",
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+ " titlefont=dict(size=18),\n",
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+ " title=r'$\\frac{t_{future}}{t_{currrent}}$'),\n",
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+ " yaxis=dict(title='probability'),\n",
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+ " title='PDF',\n",
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+ " shapes=[\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=39,\n",
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+ " x1=39,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " line=dict(color='black', dash='dash')),\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=1 / 39,\n",
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+ " x1=1 / 39,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " name='39',\n",
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+ " line=dict(color='black', dash='dash'))\n",
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+ " ]))"
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]
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},
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{
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@@ -4653,20 +4671,38 @@
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"source": [
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"t_c = 6\n",
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"df = pd.DataFrame({'x': x * t_c, 'y': y})\n",
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- "annotations = [dict(x=np.log10(39*t_c), y = 0.5, text = '95% upper limit'),\n",
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- " dict(x=np.log10(1/39*t_c), y = 0.5, text = '95% lower limit')]\n",
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- "df.iplot(x='x', y='y', layout=dict(annotations=annotations,\n",
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- " xaxis=dict(type='log', tickfont=dict(size=16),\n",
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- " title=r'$t_{future} \\text{ (years)}$'),\n",
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- " yaxis=dict(title='probability'), title = 'PDF for Lifetime of Data Science',\n",
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- " shapes=[dict(type='line',\n",
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- " x0 = 39 * t_c, x1= 39*t_c, \n",
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- " y0 = 0, y1=1,\n",
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- " line=dict(color='black', dash='dash')),\n",
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- " dict(type='line',\n",
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- " x0 = (1/39)*t_c, x1= (1/39)*t_c, \n",
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- " y0 = 0, y1=1, name='39',\n",
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- " line=dict(color='black', dash='dash'))]))"
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+ "annotations = [\n",
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+ " dict(x=np.log10(39 * t_c), y=0.5, text='95% upper limit'),\n",
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+ " dict(x=np.log10(1 / 39 * t_c), y=0.5, text='95% lower limit')\n",
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+ "]\n",
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+ "df.iplot(\n",
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+ " x='x',\n",
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+ " y='y',\n",
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+ " layout=dict(\n",
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+ " annotations=annotations,\n",
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+ " xaxis=dict(\n",
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+ " type='log',\n",
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+ " tickfont=dict(size=16),\n",
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+ " title=r'$t_{future} \\text{ (years)}$'),\n",
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+ " yaxis=dict(title='probability'),\n",
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+ " title='PDF for Lifetime of Data Science',\n",
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+ " shapes=[\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=39 * t_c,\n",
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+ " x1=39 * t_c,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " line=dict(color='black', dash='dash')),\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=(1 / 39) * t_c,\n",
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+ " x1=(1 / 39) * t_c,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " name='39',\n",
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+ " line=dict(color='black', dash='dash'))\n",
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+ " ]))"
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]
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},
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{
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@@ -6770,20 +6806,38 @@
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"source": [
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"t_c = 200000\n",
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"df = pd.DataFrame({'x': x * t_c, 'y': y})\n",
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- "annotations = [dict(x=np.log10(39*t_c), y = 0.5, text = '95% upper limit'),\n",
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- " dict(x=np.log10(1/39*t_c), y = 0.5, text = '95% lower limit')]\n",
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- "df.iplot(x='x', y='y', layout=dict(annotations=annotations,\n",
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- " xaxis=dict(type='log', tickfont=dict(size=16),\n",
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- " title=r'$t_{future} \\text{ (years)}$'),\n",
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- " yaxis=dict(title='probability'), title = 'PDF for Lifetime of Human Species',\n",
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- " shapes=[dict(type='line',\n",
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- " x0 = 39 * t_c, x1= 39*t_c, \n",
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- " y0 = 0, y1=1,\n",
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- " line=dict(color='black', dash='dash')),\n",
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- " dict(type='line',\n",
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- " x0 = (1/39)*t_c, x1= (1/39)*t_c, \n",
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- " y0 = 0, y1=1, name='39',\n",
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- " line=dict(color='black', dash='dash'))]))"
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+ "annotations = [\n",
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+ " dict(x=np.log10(39 * t_c), y=0.5, text='95% upper limit'),\n",
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+ " dict(x=np.log10(1 / 39 * t_c), y=0.5, text='95% lower limit')\n",
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+ "]\n",
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+ "df.iplot(\n",
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+ " x='x',\n",
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+ " y='y',\n",
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+ " layout=dict(\n",
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+ " annotations=annotations,\n",
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+ " xaxis=dict(\n",
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+ " type='log',\n",
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+ " tickfont=dict(size=16),\n",
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+ " title=r'$t_{future} \\text{ (years)}$'),\n",
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+ " yaxis=dict(title='probability'),\n",
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+ " title='PDF for Lifetime of Human Species',\n",
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+ " shapes=[\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=39 * t_c,\n",
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+ " x1=39 * t_c,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " line=dict(color='black', dash='dash')),\n",
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+ " dict(\n",
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+ " type='line',\n",
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+ " x0=(1 / 39) * t_c,\n",
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+ " x1=(1 / 39) * t_c,\n",
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+ " y0=0,\n",
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+ " y1=1,\n",
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+ " name='39',\n",
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+ " line=dict(color='black', dash='dash'))\n",
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+ " ]))"
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]
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},
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{
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WillKoehrsen