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generate_sequences.py
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generate_sequences.py
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import numpy as np
def check_sequence(sequence, n_row):
"""Checks the sequence
Parameters
----------
sequence : list of ints
n_row : int
Returns
-------
boolean
"""
if n_row <= 1:
raise ValueError("n_row must be >= 2")
trials = np.unique(sequence)
for trial in trials:
start, end = None, None
for i, x in enumerate(sequence):
if x == trial and start is None:
start = i
if x != trial and start is not None and end is None:
end = i-1
if start is not None and end is not None:
if end-start+1 > n_row:
return False
else:
start, end = None, None
return True
def check_trial_prior(sequence, trial, n_prior):
"""Checks the correct number of prior trials of the same type
Parameters
----------
sequence : list of ints
trial : int
n_prior : int
Returns
-------
boolean
"""
trials = np.unique(sequence)
counts = {trial: 0 for trial in trials}
for i, x in enumerate(sequence):
if x == trial:
counts[sequence[i-1]] += 1
return not any(trial_val > n_prior for trial_val in counts.values())
def check_prior(sequence, n_prior):
"""Checks the prior trials
Parameters
----------
sequence : list of ints
n_prior : int
Returns
-------
boolean
"""
trials = np.unique(sequence)
return all(check_trial_prior(sequence, trial, n_prior) for trial in trials)
def find_sequence(trial_types, n_row, n_prior, n_sequences):
"""Finds sequences that have fewer than x of the same
trial type or reward outcome in a row.
Parameters
----------
trial_types : list of ints
n_row : int
Number of same trial types allowed in a row.
n_prior : int
Number of trial type
n_sequences : int
Number of trials in a sequence
Returns
-------
sequences : list of lists
"""
sequences = []
while len(sequences) < n_sequences:
np.random.shuffle(trial_types)
sequence = trial_types.copy()
outcome_sequence = [x % 2 for x in sequence]
if not check_sequence(sequence, n_row):
continue
if not check_sequence(outcome_sequence, n_row):
continue
if not check_prior(sequence, n_prior):
continue
sequences.append(sequence)
return sequences
def find_iti(iti_lengths, n_row, n_sequences):
"""Finds sequences that have fewer than x of the same iti type in a row.
Parameters
----------
iti_lengths : list of strs
n_row : int
Number of same trial types allowed in a row.
n_sequences : int
Number of trials in a sequence
Returns
-------
sequences : list of lists
"""
sequences = []
while len(sequences) < n_sequences:
np.random.shuffle(iti_lengths)
sequence = iti_lengths.copy()
if not check_sequence(sequence, n_row):
continue
sequences.append('[%s]' % '", '.join(map(str, sequence)))
return sequences
# feature_lengths = [150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270]
# trial_types = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
# 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
# feature_lengths = [150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 150, 180, 210, 240, 270,
# 180, 210, 240]
# trial_types = [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2,
# 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4]
feature_lengths = [150, 180, 210, 240, 270,
150, 180, 210, 240, 270,
150, 180, 210, 240, 270,
150, 180, 210, 240, 270,
150, 180, 210, 240, 270,
180, 210, 240]
# trial_types = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
# 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4]
# trial_types = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
# 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
trial_types = [3, 3, 3, 3, 3, 3, 3,
4, 4, 4, 4, 4, 4, 4]
# trial_types = [1, 1, 1, 1, 1, 1, 1,
# 2, 2, 2, 2, 2, 2, 2]
sequences = find_sequence(trial_types, n_row=4, n_prior=10, n_sequences=20)
print('Sequence length is:', len(sequences[0]))
print(sequences)
feature_sequences = find_iti(feature_lengths, n_row=3, n_sequences=20)
print(feature_sequences)