Heatmap samt Erzeugerskript hinzugefügt.
Sie wird aus mathplotlib mit seaborn generiert.
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#!/usr/bin/env python
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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import seaborn as sns
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f = open("faust.txt", "r")
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str = f.read()
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LAYOUT = ["xvlcwkhgfqß","uiaeosnrtdy","üöäpzbm,.j"]
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#LAYOUT = ["qwertzuiopü","asdfghjklöö","yxcvbnm;:-"]
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# we create two vertically offset data points for each key
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# to visually vertically stretch the result
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d = {}
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for i in range(len(LAYOUT[0])):
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x = LAYOUT[0][i]
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X = x.upper()
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d[x] = [(73+i*36), (62-10),0]
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d[X] = [(73+i*36), (62+0),0]
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for i in range(len(LAYOUT[1])):
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x = LAYOUT[1][i]
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X = x.upper()
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d[x] = [(84+i*36), (98-10),0]
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d[X] = [(84+i*36), (98+0),0]
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for i in range(len(LAYOUT[2])):
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x = LAYOUT[2][i]
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X = x.upper()
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d[x] = [(101+i*36), (134-10),0]
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d[X] = [(101+i*36), (134+0),0]
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for x in str:
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x = x.lower()
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X = x.upper()
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if x in d.keys():
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d[x][2] += 1
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d[X][2] += 1
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df = pd.DataFrame.from_dict(d, orient="index", columns=["x","y","z"])
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fig = plt.figure(figsize=(5.35, 1.83), dpi=100)
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ax= fig.add_axes([0,0,1,1])
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img = mpimg.imread("neo.png")
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sns.kdeplot(data=df, x="x",y="y",weights="z",
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cmap='rainbow', fill=True, alpha=1,
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bw_adjust=0.5, thresh=0,
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cut=800, clip=((0,535),(0,183)),
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levels=1000)
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ax.imshow(img, alpha=0.4, zorder=5)
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ax.axes.get_xaxis().set_visible(False)
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ax.axes.get_yaxis().set_visible(False)
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ax.set_frame_on(False)
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ax.axis('off')
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plt.savefig('heatmap.png')
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