97 lines
3.2 KiB
Python
97 lines
3.2 KiB
Python
import numpy as np
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import os
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from IPython import embed
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def load_chirp_spikes(dataset):
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spikes_file = os.path.join(dataset, "chirpspikess1.dat")
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if not os.path.exists(spikes_file):
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print("found no chirps!")
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return {}
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with open(spikes_file, 'r') as f:
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lines = f.readlines()
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spikes = {}
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for l in lines:
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l = l.strip()
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if "index" in l and "chirp" not in l:
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index = int(l.split(":")[-1])
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if "deltaf" in l and "true" not in l:
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df = l.split(":")[-1]
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if "contrast" in l and "true" not in l:
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contrast = l.split(":")[-1]
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if "chirpsize" in l:
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cs = l.split(":")[-1]
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if "#Key" in l:
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spikes[(index, df, contrast, cs)] = {}
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if "chirp index" in l:
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ci = int(l.split(":")[-1])
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if "beat phase" in l:
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phase = float(l.split(":")[-1])
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spikes[(index, df, contrast, cs)][(ci, phase)] = []
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if len(l.strip()) != 0 and "#" not in l:
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spikes[(index, df, contrast, cs)][(ci, phase)].append(float(l))
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return spikes
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def load_chirp_eod(dataset):
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eod_file = os.path.join(dataset, "chirpeodampls.dat")
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if not os.path.exists(eod_file):
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print("found no chirpeodampls.dat!")
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return {}
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with open(eod_file, 'r') as f:
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lines = f.readlines()
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chirp_eod = {}
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for l in lines:
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l = l.strip()
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if "index" in l and "chirp" not in l:
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index = int(l.split(":")[-1])
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if "deltaf" in l and "true" not in l:
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df = l.split(":")[-1]
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if "contrast" in l and "true" not in l:
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contrast = l.split(":")[-1]
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if "chirpsize" in l:
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cs = l.split(":")[-1]
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if "#Key" in l:
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chirp_eod[(index, df, contrast, cs)] = ([], [])
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if len(l.strip()) != 0 and "#" not in l:
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time = float(l.split()[0])
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ampl = float(l.split()[1])
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chirp_eod[(index, df, contrast, cs)][0].append(time)
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chirp_eod[(index, df, contrast, cs)][1].append(ampl)
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return chirp_eod
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def load_chirp_times(dataset):
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chirp_times_file = os.path.join(dataset, "chirpss.dat")
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if not os.path.exists(chirp_times_file):
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print("found no chirpss.dat!")
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return {}
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with open(chirp_times_file, 'r') as f:
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lines = f.readlines()
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chirp_times = {}
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for l in lines:
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l = l.strip()
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if "index" in l and "chirp" not in l:
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index = int(l.split(":")[-1])
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if "deltaf" in l and "true" not in l:
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df = l.split(":")[-1]
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if "contrast" in l and "true" not in l:
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contrast = l.split(":")[-1]
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if "chirpsize" in l:
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cs = l.split(":")[-1]
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if "#Key" in l:
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chirp_times[(index, df, contrast, cs)] = []
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if len(l.strip()) != 0 and "#" not in l:
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chirp_times[(index, df, contrast, cs)].append(float(l.split()[1]))
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return chirp_times
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if __name__ == "__main__":
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data_dir = "../data"
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dataset = "2018-11-09-ad-invivo-1"
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spikes = load_chirp_spikes(os.path.join(data_dir, dataset))
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chirp_times = load_chirp_times(os.path.join(data_dir, dataset))
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chirp_eod = load_chirp_eod(os.path.join(data_dir, dataset))
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embed()
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