def update_output(self, t, out_ind):
# Figure out what the motor output is and write it to file
if out_ind >= 0 and out_ind < len(self.num_out_list):
out_str = self.num_out_list[out_ind]
else:
out_str = self.null_output
logger.write(out_str)
logger.flush()
if self.in_learning_phase(t):
# Denote learning phase reward
logger.write('|')
logger.flush()
# In learning phase. Evaluate output and choose reward
if out_ind >= 0 and out_ind < (len(self.num_out_list) - 1):
t_ind = min(self.get_t_ind(t),
len(self.task_phase_seq_list) - 1)
rewards = self.task_phase_seq_list[t_ind][1]
if out_ind >= 0 and out_ind < self.num_learn_actions:
reward_chance = rewards[out_ind]
else:
reward_chance = 0
rewarded = str(int(np.random.random() < reward_chance))
self.stim_seq_list[self.get_t_ind(t) + 1] = \
self.num_map[rewarded]
elif (self.get_t_ind(t) + 1) < len(self.stim_seq_list):
self.stim_seq_list[self.get_t_ind(t) + 1] = self.num_map['0']
else:
pass
def update_output(self, t, out_ind):
# Figure out what the motor output is and write it to file
if out_ind >= 0 and out_ind < len(self.num_out_list):
out_str = self.num_out_list[out_ind]
else:
out_str = self.null_output
logger.write(out_str)
logger.flush()
if self.in_learning_phase(t):
# Denote learning phase reward
logger.write('|')
logger.flush()
# In learning phase. Evaluate output and choose reward
if out_ind >= 0 and out_ind < (len(self.num_out_list) - 1):
t_ind = min(self.get_t_ind(t),
len(self.task_phase_seq_list) - 1)
rewards = self.task_phase_seq_list[t_ind][1]
if out_ind >= 0 and out_ind < self.num_learn_actions:
reward_chance = rewards[out_ind]
else:
reward_chance = 0
rewarded = str(int(np.random.random() < reward_chance))
self.stim_seq_list[self.get_t_ind(t) + 1] = \
self.num_map[rewarded]
elif (self.get_t_ind(t) + 1) < len(self.stim_seq_list):
self.stim_seq_list[self.get_t_ind(t) + 1] = self.num_map['0']
else:
pass
def write_header(self):
# Write spaun configurator options
logger.write('# Spaun Configuration Options:\n')
logger.write('# ----------------------------\n')
for param_name in sorted(self.__dict__.keys()):
param_value = getattr(self, param_name)
if not callable(param_value):
logger.write('# - %s = %s\n' % (param_name, param_value))
logger.write('#\n')
def write_header(self):
# Write spaun configurator options
logger.write('# Spaun Configuration Options:\n')
logger.write('# ----------------------------\n')
for param_name in sorted(self.__dict__.keys()):
param_value = getattr(self, param_name)
if not callable(param_value):
logger.write('# - %s = %s\n' % (param_name, param_value))
logger.write('#\n')
def write_header(self):
logger.write('# Spaun Vocabulary Options:\n')
logger.write('# -------------------------\n')
for param_name in sorted(self.__dict__.keys()):
param_value = getattr(self, param_name)
if not callable(param_value) and not isinstance(param_value, list)\
and not isinstance(param_value, Vocabulary) \
and not isinstance(param_value, SemanticPointer) \
and not isinstance(param_value, np.ndarray):
logger.write('# - %s = %s\n' % (param_name, param_value))
logger.write('\n')
def get_stimulus(self, t):
t_ind = self.get_t_ind(t)
t_ind_float = self.get_t_ind_float(t)
if t <= 0:
return None
if t_ind != self.prev_t_ind:
# Write the stimulus to file
if t_ind < len(self.stim_seq_list):
stim_char = self.stim_seq_list[t_ind]
if (stim_char == '.'):
# logger.write('_')
logger.write('') # Ignore the . blank character
elif stim_char == 'A' and self.prev_t_ind >= 0:
logger.write('\nA')
elif isinstance(stim_char, int):
logger.write('<%s>' % stim_char)
elif stim_char in self.num_rev_map:
logger.write('%s' % self.num_rev_map[stim_char])
elif stim_char in self.sym_rev_map:
logger.write('%s' % self.sym_rev_map[stim_char])
elif stim_char is not None:
logger.write('%s' % str(stim_char))
# Done all the stuff needed for new t_ind. Store new t_ind
self.prev_t_ind = t_ind
if (self.present_blanks and t_ind != int(round(t_ind_float))) or \
t_ind >= len(self.stim_seq_list) or \
self.stim_seq_list[t_ind] == '.':
return None
else:
return self.stim_seq_list[t_ind]
def write_header(self):
logger.write('# Spaun Experiment Options:\n')
logger.write('# -------------------------\n')
for param_name in sorted(self.__dict__.keys()):
param_value = getattr(self, param_name)
if not callable(param_value):
if (isinstance(param_value, list) and len(param_value) > 20) \
or (isinstance(param_value, np.ndarray) and
param_value.shape[0] > 20):
param_value = str(param_value[:20])[:-1] + '...'
logger.write('# - %s = %s\n' % (param_name, param_value))
logger.write('# ------\n')
logger.write('# Simulation time: %0.2fs' % self.get_est_simtime())
logger.write('#\n')
def write_header(self):
logger.write('# Spaun Experiment Options:\n')
logger.write('# -------------------------\n')
for param_name in sorted(self.__dict__.keys()):
param_value = getattr(self, param_name)
if not callable(param_value):
if (isinstance(param_value, list) and len(param_value) > 20) \
or (isinstance(param_value, np.ndarray) and
param_value.shape[0] > 20):
param_value = str(param_value[:20])[:-1] + '...'
logger.write('# - %s = %s\n' % (param_name, param_value))
logger.write('# ------\n')
logger.write('# Simulation time: %0.2fs' % self.get_est_simtime())
logger.write('#\n')
def get_stimulus(self, t):
t_ind = self.get_t_ind(t)
t_ind_float = self.get_t_ind_float(t)
if t <= 0:
return None
if t_ind != self.prev_t_ind:
# Write the stimulus to file
if t_ind < len(self.stim_seq_list):
stim_char = self.stim_seq_list[t_ind]
if (stim_char == '.'):
# logger.write('_')
logger.write('') # Ignore the . blank character
elif stim_char == 'A' and self.prev_t_ind >= 0:
logger.write('\nA')
elif isinstance(stim_char, int):
logger.write('<%s>' % stim_char)
elif stim_char in self.num_rev_map:
logger.write('%s' % self.num_rev_map[stim_char])
elif stim_char in self.sym_rev_map:
logger.write('%s' % self.sym_rev_map[stim_char])
elif stim_char is not None:
logger.write('%s' % str(stim_char))
# Done all the stuff needed for new t_ind. Store new t_ind
self.prev_t_ind = t_ind
if (self.present_blanks and t_ind != int(round(t_ind_float))) or \
t_ind >= len(self.stim_seq_list) or \
self.stim_seq_list[t_ind] == '.':
return None
else:
return self.stim_seq_list[t_ind]
