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#!/usr/bin/env python3
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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# %%
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dfs = {
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i: pd.read_csv(f"top_actors_{i:02d}_c.txt", sep='\t', usecols=[1], names=["actor"])
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for i in [5] + list(range(10, 71, 10))}
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sets = {i: set(df["actor"]) for i, df in dfs.items()}
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diff = []
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for i in sets.keys():
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diff.append([len(sets[i]) - len(sets[i] & sets[j]) for j in sets.keys()])
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diff = np.array(diff, dtype=float)
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diff /= len(next(iter(sets.values())))
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plt.matshow(diff)
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for (i, j), z in np.ndenumerate(diff):
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plt.gca().text(j, i, f'{z:0.2f}', ha='center', va='center')
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plt.gca().set_xticks(np.linspace(0.0, len(sets) - 1, len(sets)))
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plt.gca().set_yticks(np.linspace(0.0, len(sets) - 1, len(sets)))
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plt.gca().set_xticklabels([f"{i:d}" for i in sets.keys()])
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plt.gca().set_yticklabels([f"{i:d}" for i in sets.keys()])
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plt.ylabel("\nMIN_ACTORS value")
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plt.xlabel("\nMIN_ACTORS value")
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cb = plt.colorbar()
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cb.set_label("\npercentace of difference in results varing MIN_MOVIES")
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plt.show()
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# %% 3 + 3
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