69 lines
1.6 KiB
Python
69 lines
1.6 KiB
Python
from pathlib import Path
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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import scipy
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from glob import glob
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import sys
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def read_xy(path: str):
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df = pd.read_csv(path, skipinitialspace=True)
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df['N'] = df.index + 1
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df['r'] = (df.x ** 2 + df.y ** 2) ** 0.5
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df['cr'] = df.r.cummax()
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df['fd'] = np.log(df.N) / np.log(df.cr)
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return df
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def read_all(load_dir: str):
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paths = glob(f'{load_dir}/*.csv')
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return [read_xy(path) for path in paths]
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def stick_prob_from_load_dir(load_dir: str):
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return float(Path(load_dir).name)
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def read_sp_dir(load_dir: str):
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return stick_prob_from_load_dir(load_dir), read_all(load_dir)
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def read_sp_full(probabilities_dir: str):
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a = [read_sp_dir(load_dir) for load_dir in glob(f'{probabilities_dir}/*')]
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b = [fd_of_dfs(dfs) for (p, dfs) in a]
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ps = [p for (p, dfs) in a]
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means, stds = list(zip(*b))
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c = pd.DataFrame(zip(ps, means, stds), columns=['p', 'fd_mean', 'fd_std'])
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c.sort_values(by='p', inplace=True)
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return c
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def convergent_tail_index(series, tol):
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diffs = np.abs(np.ediff1d(series))
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for i in range(0, len(diffs)):
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if np.max(diffs[i:]) <= tol:
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return i
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# No convergence found
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return None
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def mean_of_tail(series, tol=0.05):
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tail_index = convergent_tail_index(series, tol)
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return np.mean(series[tail_index:])
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def fd_of_dfs(dfs):
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fds = [mean_of_tail(df.fd, 0.001) for df in dfs]
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fds_clean = [f for f in fds if f < np.inf]
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return np.mean(fds_clean), np.std(fds_clean)
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print(sys.argv)
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np.seterr(divide='ignore')
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argv_ = sys.argv[1]
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print(read_sp_full(argv_))
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