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week 45

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mhjensen
2020-11-02 16:26:03 +01:00
parent cbb7ca21cc
commit e9f83107f5
7 changed files with 62 additions and 6 deletions
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doc/pub/week45/html/._week45-bs005.html
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@@ -197,7 +197,16 @@ MathJax.Hub.Config({
<p>
<!-- code=python (!bc pycod) typeset with pygments style "default" -->
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span>heads_proba <span style="color: #666666">=</span> <span style="color: #666666">0.51</span>
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span><span style="color: #408080; font-style: italic"># Common imports</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib.pyplot</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">plt</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">matplotlib.colors</span> <span style="color: #008000; font-weight: bold">import</span> ListedColormap
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;axes.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">14</span>
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;xtick.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">12</span>
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;ytick.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">12</span>
heads_proba <span style="color: #666666">=</span> <span style="color: #666666">0.51</span>
coin_tosses <span style="color: #666666">=</span> (np<span style="color: #666666">.</span>random<span style="color: #666666">.</span>rand(<span style="color: #666666">10000</span>, <span style="color: #666666">10</span>) <span style="color: #666666">&lt;</span> heads_proba)<span style="color: #666666">.</span>astype(np<span style="color: #666666">.</span>int32)
cumulative_heads_ratio <span style="color: #666666">=</span> np<span style="color: #666666">.</span>cumsum(coin_tosses, axis<span style="color: #666666">=0</span>) <span style="color: #666666">/</span> np<span style="color: #666666">.</span>arange(<span style="color: #666666">1</span>, <span style="color: #666666">10001</span>)<span style="color: #666666">.</span>reshape(<span style="color: #666666">-1</span>, <span style="color: #666666">1</span>)
plt<span style="color: #666666">.</span>figure(figsize<span style="color: #666666">=</span>(<span style="color: #666666">8</span>,<span style="color: #666666">3.5</span>))
doc/pub/week45/html/week45-reveal.html
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@@ -230,7 +230,16 @@ The example here shows how we can implement the coin tossing case, clealry demos
<p>
<!-- code=python (!bc pycod) typeset with pygments style "perldoc" -->
<div class="highlight" style="background: #eeeedd"><pre style="font-size: 80%; line-height: 125%"><span></span>heads_proba = <span style="color: #B452CD">0.51</span>
<div class="highlight" style="background: #eeeedd"><pre style="font-size: 80%; line-height: 125%"><span></span><span style="color: #228B22"># Common imports</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">matplotlib</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">matplotlib.pyplot</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">plt</span>
<span style="color: #8B008B; font-weight: bold">from</span> <span style="color: #008b45; text-decoration: underline">matplotlib.colors</span> <span style="color: #8B008B; font-weight: bold">import</span> ListedColormap
plt.rcParams[<span style="color: #CD5555">&#39;axes.labelsize&#39;</span>] = <span style="color: #B452CD">14</span>
plt.rcParams[<span style="color: #CD5555">&#39;xtick.labelsize&#39;</span>] = <span style="color: #B452CD">12</span>
plt.rcParams[<span style="color: #CD5555">&#39;ytick.labelsize&#39;</span>] = <span style="color: #B452CD">12</span>
heads_proba = <span style="color: #B452CD">0.51</span>
coin_tosses = (np.random.rand(<span style="color: #B452CD">10000</span>, <span style="color: #B452CD">10</span>) &lt; heads_proba).astype(np.int32)
cumulative_heads_ratio = np.cumsum(coin_tosses, axis=<span style="color: #B452CD">0</span>) / np.arange(<span style="color: #B452CD">1</span>, <span style="color: #B452CD">10001</span>).reshape(-<span style="color: #B452CD">1</span>, <span style="color: #B452CD">1</span>)
plt.figure(figsize=(<span style="color: #B452CD">8</span>,<span style="color: #B452CD">3.5</span>))
doc/pub/week45/html/week45-solarized.html
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@@ -219,7 +219,16 @@ The example here shows how we can implement the coin tossing case, clealry demos
<p>
<!-- code=python (!bc pycod) typeset with pygments style "perldoc" -->
<div class="highlight" style="background: #eeeedd"><pre style="line-height: 125%"><span></span>heads_proba = <span style="color: #B452CD">0.51</span>
<div class="highlight" style="background: #eeeedd"><pre style="line-height: 125%"><span></span><span style="color: #228B22"># Common imports</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">matplotlib</span>
<span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">matplotlib.pyplot</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">plt</span>
<span style="color: #8B008B; font-weight: bold">from</span> <span style="color: #008b45; text-decoration: underline">matplotlib.colors</span> <span style="color: #8B008B; font-weight: bold">import</span> ListedColormap
plt.rcParams[<span style="color: #CD5555">&#39;axes.labelsize&#39;</span>] = <span style="color: #B452CD">14</span>
plt.rcParams[<span style="color: #CD5555">&#39;xtick.labelsize&#39;</span>] = <span style="color: #B452CD">12</span>
plt.rcParams[<span style="color: #CD5555">&#39;ytick.labelsize&#39;</span>] = <span style="color: #B452CD">12</span>
heads_proba = <span style="color: #B452CD">0.51</span>
coin_tosses = (np.random.rand(<span style="color: #B452CD">10000</span>, <span style="color: #B452CD">10</span>) &lt; heads_proba).astype(np.int32)
cumulative_heads_ratio = np.cumsum(coin_tosses, axis=<span style="color: #B452CD">0</span>) / np.arange(<span style="color: #B452CD">1</span>, <span style="color: #B452CD">10001</span>).reshape(-<span style="color: #B452CD">1</span>, <span style="color: #B452CD">1</span>)
plt.figure(figsize=(<span style="color: #B452CD">8</span>,<span style="color: #B452CD">3.5</span>))
doc/pub/week45/html/week45.html
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@@ -224,7 +224,16 @@ The example here shows how we can implement the coin tossing case, clealry demos
<p>
<!-- code=python (!bc pycod) typeset with pygments style "default" -->
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span>heads_proba <span style="color: #666666">=</span> <span style="color: #666666">0.51</span>
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span><span style="color: #408080; font-style: italic"># Common imports</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib.pyplot</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">plt</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">matplotlib.colors</span> <span style="color: #008000; font-weight: bold">import</span> ListedColormap
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;axes.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">14</span>
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;xtick.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">12</span>
plt<span style="color: #666666">.</span>rcParams[<span style="color: #BA2121">&#39;ytick.labelsize&#39;</span>] <span style="color: #666666">=</span> <span style="color: #666666">12</span>
heads_proba <span style="color: #666666">=</span> <span style="color: #666666">0.51</span>
coin_tosses <span style="color: #666666">=</span> (np<span style="color: #666666">.</span>random<span style="color: #666666">.</span>rand(<span style="color: #666666">10000</span>, <span style="color: #666666">10</span>) <span style="color: #666666">&lt;</span> heads_proba)<span style="color: #666666">.</span>astype(np<span style="color: #666666">.</span>int32)
cumulative_heads_ratio <span style="color: #666666">=</span> np<span style="color: #666666">.</span>cumsum(coin_tosses, axis<span style="color: #666666">=0</span>) <span style="color: #666666">/</span> np<span style="color: #666666">.</span>arange(<span style="color: #666666">1</span>, <span style="color: #666666">10001</span>)<span style="color: #666666">.</span>reshape(<span style="color: #666666">-1</span>, <span style="color: #666666">1</span>)
plt<span style="color: #666666">.</span>figure(figsize<span style="color: #666666">=</span>(<span style="color: #666666">8</span>,<span style="color: #666666">3.5</span>))
doc/pub/week45/ipynb/ipynb-week45-src.tar.gz
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doc/pub/week45/ipynb/week45.ipynb
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@@ -73,6 +73,17 @@
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"# Common imports\n",
"import numpy as np\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.colors import ListedColormap\n",
"plt.rcParams['axes.labelsize'] = 14\n",
"plt.rcParams['xtick.labelsize'] = 12\n",
"plt.rcParams['ytick.labelsize'] = 12\n",
"\n",
"heads_proba = 0.51\n",
"coin_tosses = (np.random.rand(10000, 10) < heads_proba).astype(np.int32)\n",
"cumulative_heads_ratio = np.cumsum(coin_tosses, axis=0) / np.arange(1, 10001).reshape(-1, 1)\n",
@@ -316,8 +327,6 @@
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from sklearn.model_selection import train_test_split \n",
doc/src/week45/week45.do.txt
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@@ -55,6 +55,15 @@ The example here shows how we can implement the coin tossing case, clealry demos
!split
===== Simple Voting Example, head or tail =====
!bc pycod
# Common imports
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12
heads_proba = 0.51
coin_tosses = (np.random.rand(10000, 10) < heads_proba).astype(np.int32)
cumulative_heads_ratio = np.cumsum(coin_tosses, axis=0) / np.arange(1, 10001).reshape(-1, 1)
@@ -995,3 +1004,5 @@ plt.show()