plot.xticks()
plot.yticks()

plot.text(FIX + 50, 0.05, r'ongoing stimulus',
          ha='left', va='center', fontsize=6.5, color='k')
plot.arrow(780, 0.05, 210, 0, width=0.003, head_width=0.07, head_length=25,
           length_includes_head=True, fc='k', ec='k')

#-----------------------------------------------------------------------------------------
# Psychometric curves
#-----------------------------------------------------------------------------------------

# Variable stimulus
plot = plots['C']
rdm.psychometric_function(varstim_trialsfile, plot, ms=5)

# Reaction time
plot = plots['D']
rdm.psychometric_function(rt_trialsfile, plot, threshold=True, ms=5)

#-----------------------------------------------------------------------------------------
# Proportion correct as a function of stimulus duration
#-----------------------------------------------------------------------------------------

plot = plots['E']
rdm.plot_stimulus_duration(varstim_trialsfile, plot, ms=4.5)

#-----------------------------------------------------------------------------------------
# Reaction time
#-----------------------------------------------------------------------------------------
plot.ylabel(r'Percent choice 1', labelpad=4)
plot.text_upper_center('No Dale\'s principle', **textprop)

plot = plots['Bpsy']
plot.text_upper_center('Dale, dense initial connectivity', **textprop)

plot = plots['Cpsy']
plot.text_upper_center('Dale, constrained connectivity', **textprop)

#=========================================================================================
# Psychometric curves
#=========================================================================================

# No Dale
plot = plots['Apsy']
rdm.psychometric_function(nodale_trialsfile, plot, ms=5)

# Dale, dense
plot = plots['Bpsy']
rdm.psychometric_function(dense_trialsfile, plot, ms=5)

# Dale, fixed
plot = plots['Cpsy']
rdm.psychometric_function(fixed_trialsfile, plot, ms=5)

#=========================================================================================
# Connection matrices
#=========================================================================================

for rnn, sortbyfile, s, dprimefile in zip([rnn_nodale, rnn_dense, rnn_fixed],
                                          [sortby_nodale, sortby_dense, sortby_fixed],
Beispiel #3
0
plot.ylabel(r'Percent choice 1', labelpad=4)
plot.text_upper_center('No Dale\'s principle', **textprop)

plot = plots['Bpsy']
plot.text_upper_center('Dale, dense initial connectivity', **textprop)

plot = plots['Cpsy']
plot.text_upper_center('Dale, constrained connectivity', **textprop)

#=========================================================================================
# Psychometric curves
#=========================================================================================

# No Dale
plot = plots['Apsy']
rdm.psychometric_function(nodale_trialsfile, plot, ms=5)

# Dale, dense
plot = plots['Bpsy']
rdm.psychometric_function(dense_trialsfile, plot, ms=5)

# Dale, fixed
plot = plots['Cpsy']
rdm.psychometric_function(fixed_trialsfile, plot, ms=5)

#=========================================================================================
# Connection matrices
#=========================================================================================

for rnn, sortbyfile, s, dprimefile in zip(
    [rnn_nodale, rnn_dense, rnn_fixed],
Beispiel #4
0
           210,
           0,
           width=0.003,
           head_width=0.07,
           head_length=25,
           length_includes_head=True,
           fc='k',
           ec='k')

#-----------------------------------------------------------------------------------------
# Psychometric curves
#-----------------------------------------------------------------------------------------

# Variable stimulus
plot = plots['C']
rdm.psychometric_function(varstim_trialsfile, plot, ms=5)

# Reaction time
plot = plots['D']
rdm.psychometric_function(rt_trialsfile, plot, threshold=True, ms=5)

#-----------------------------------------------------------------------------------------
# Proportion correct as a function of stimulus duration
#-----------------------------------------------------------------------------------------

plot = plots['E']
rdm.plot_stimulus_duration(varstim_trialsfile, plot, ms=4.5)

#-----------------------------------------------------------------------------------------
# Reaction time
#-----------------------------------------------------------------------------------------