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import itertools |
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from collections.abc import Iterable |
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from typing import Optional |
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5
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import more_itertools |
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import networkx as nx |
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from matplotlib import pyplot |
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9
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10
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def sliding_window_visibility_graph(series: Iterable[float], window_size: Optional[int] = None): |
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if window_size: |
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yield from itertools.chain( |
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visibility_graph(subseries) for subseries in more_itertools.sliding_window(series, window_size)) |
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else: |
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yield visibility_graph(series) |
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def obstruction_predicate(n1, t1, n2, t2): |
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slope = (t2 - t1) / (n2 - n1) |
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constant = t2 - slope * n2 |
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def is_obstruction(n, t): |
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return t >= constant + slope * n |
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return is_obstruction |
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def visibility_graph(series: Iterable[float]): |
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graph = nx.Graph() |
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# Check all combinations of nodes n series |
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for s1, s2 in itertools.combinations(enumerate(series), 2): |
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n1, t1 = s1 |
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n2, t2 = s2 |
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if n2 == n1 + 1: |
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graph.add_node(n1, value=t1) |
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graph.add_node(n2, value=t2) |
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graph.add_edge(n1, n2) |
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else: |
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is_obstruction = obstruction_predicate(n1, t1, n2, t2) |
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obstructed = any(is_obstruction(n, t) for n, t in enumerate(series) if n1 < n < n2) |
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if not obstructed: |
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graph.add_edge(n1, n2) |
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return graph |
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49
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if __name__ == '__main__': |
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series_list = [ |
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# range(10), |
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# [2, 1, 3, 2, 1, 3, 2, 1, 3, 2, 1, 3, 4], |
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[-(x ** 3) for x in range(-10, 11)], |
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# [2, 1, 3, 4, 2, 1, 4, 3, 1, 1, 3, 4, 2, 4, 1, 3], |
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# random.sample(range(1000), 500) |
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] |
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58
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for s in series_list: |
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g = visibility_graph(s) |
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print(g) |
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62
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pos = [[x, 0] for x in range(len(s))] |
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labels = nx.get_node_attributes(g, 'value') |
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nx.draw_networkx_nodes(g, pos) |
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nx.draw_networkx_labels(g, pos, labels=labels) |
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nx.draw_networkx_edges(g, pos, arrows=True, connectionstyle='arc3,rad=-1.57079632679') |
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pyplot.show() |
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erivlis /
graphinate
