2016-08-22 23:03:41 +01:00
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:- [library(python)].
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main :-
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Plt = matplotlib.pyplot,
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:= import( Plt ),
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:= (
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2016-08-25 18:10:33 +01:00
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Plt.figure(figsize=(10,2.5)),
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2016-08-22 23:03:41 +01:00
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Plt.plot([1,2,3,4]),
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Plt.ylabel(`some numbers`),
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Plt.show()
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).
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2016-08-25 07:26:11 +01:00
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2016-08-25 18:10:33 +01:00
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main2 :-
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:= ( import( numpy),
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import( matplotlib.mlab),
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import( matplotlib.pyplot) ),
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NP = numpy,
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Mlab = matplotlib.mlab,
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Plt = matplotlib.pyplot,
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% example data
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mu := 100, % mean of distribution,
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sigma := 15, % standard deviation of distribution,
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x := mu + sigma * NP.random.randn(10000),
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num_bins := 50,
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% the histogram of the data
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(n, bins, patches) := Plt.hist(x, num_bins, normed=1, facecolor= `green`, alpha=0.5),
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% add a `best fit` line
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y := Mlab.normpdf(bins, mu, sigma),
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:= (Plt.plot(bins, y, `r--`),
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Plt.xlabel(`Smarts`),
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Plt.ylabel(`Probability`),
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Plt.title(`Histogram of IQ: $\\mu=100$, $\\sigma=15$`),
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% Tweak spacing to prevent clipping of ylabel,
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Plt.subplots_adjust(left=0.15),
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Plt.show()).
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