Example #1
0
'''
# Plasticity, started IN-phase
# Rate
fnamer = 'Learned_group_synchrony_plas_r.dat'
titr = 'Plasticity run - started IN phase'
xlabr = eval("r'Time (100 $\mu$s)'")
ylabr = 'Rate (Hz)'
# Weight
fnamew = 'Learned_group_synchrony_plas_w.dat'
xlabw = 'Time (10 ms)'
ylabw = 'Synaptic weight'
#Plot
plt.figure()
ax1=plt.subplot(2,1,1) #Rates over init-IN plasticity run
plot_tools.linep(fnamer, titr, xlabr, ylabr)
ax2=plt.subplot(2,1,2) #Weights over init-IN plasticity run
plot_tools.linep(fnamew, ' ', xlabw, ylabw, 0, None, None, None, [0, 0.31])

'''

# After IN plasticity
fnameINa = 'Learned_Synchrony_postIN_pdvpd.dat'
titINa = 'After plasticity run, initIN,\n X-Oxc EI=0.3, IE= -0.5, II=0'
xlabINa = eval("r'$\Delta\Phi_0 $ (Initial Phase diff)'")
ylabINa = eval("r'$\langle \Delta\Phi_{SS} \\rangle$ (Avg. Steady-state Phase diff)'")
xranINa = [0, 2*math.pi]
yranINa = None
xlimsINa = None
ylimsINa = [-0.1, math.pi+0.1]
smooth_w = 0
Example #2
0
# Plotter for 1.1

import sys
import os

path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../graphing/"))
if path not in sys.path:
    sys.path.insert(1, path)
import plot_tools
import matplotlib.pyplot as plt
import numpy as np

fname = "single_PING_group.dat"
tit = "Single PING Oscillator"
xlab = eval("r'Time ($100 \mu$s)'")
ylab = "Rate (Hz)"
s = 0
xran = None
yran = None
xlims = [5000, 8000]


plt.figure()
lines = plot_tools.linep(fname, tit, xlab, ylab, s, xran, yran, xlims)
plt.setp(lines[0], color="g")
plt.setp(lines[1], color="r")
plt.legend(("Excitatory", "Inhibitory"))
plt.show()
Example #3
0
# Plasticity, started IN-phase
print "plotting fig 2 of 3..."
# Rate
fname_rI = "rateSTDP_tester_rI.dat"
tit_rI = "Plasticity run - started IN phase"
xlab_rI = " "
ylab_rI = "Rate (Hz)"
# Weight
fname_wI = "rateSTDP_tester_wI.dat"
tit_wI = " "
xlab_wI = eval("r'Time (100 $\mu$s)'")
ylab_wI = "Synaptic Weight"
# Plot
plt.figure()
ax1 = plt.subplot(2, 1, 1)  # Rates over init-IN plasticity run
pt.linep(fname_rI, tit_rI, xlab_rI, ylab_rI)
ax2 = plt.subplot(2, 1, 2)  # Weights over init-IN plasticity run
pt.linep(fname_wI, tit_wI, xlab_wI, ylab_wI)


# Plasticity, started OUT-of-phase
print "plotting fig 3 of 3..."
# Rate
fname_rO = "rateSTDP_tester_rO.dat"
tit_rO = "Plasticity run - started OUT of phase"
xlab_rO = " "
ylab_rO = "Rate (Hz)"
# Weight
fname_wO = "rateSTDP_tester_wO.dat"
tit_wO = " "
xlab_wO = eval("r'Time (100 $\mu$s)'")
Example #4
0
# Plotter for 1.1

import sys
import os
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../graphing/'))
if path not in sys.path:
    sys.path.insert(1,path)
import plot_tools
import matplotlib.pyplot as plt

fname = 'pingRateN_tester_iIN_ssIN.dat'
tit = eval("r'Two coupled PING Oscillator, $\Delta\Psi_0=0$, $\Delta\Psi_{SS}=0$'")
xlab = eval("r'Time ($100 \mu$s'")
ylab = 'Rate (Hz)'
plt.figure()
plot_tools.linep(fname,tit,xlab,ylab)

#I IN, SS OUT
fname = 'pingRateN_tester_iIN_ssOUT.dat'
tit = eval("r'Two coupled PING Oscillator, $\Delta\Psi_0=0$, $\Delta\Psi_{SS}=\pi$'")
xlab = eval("r'Time ($100 \mu$s'")
ylab = 'Rate (Hz)'
plt.figure()
plot_tools.linep(fname,tit,xlab,ylab)

#I OUT, SS IN 
fname = 'pingRateN_tester_iOUT_ssIN.dat'
tit = eval("r'Two coupled PING Oscillator, $\Delta\Psi_0=\pi$, $\Delta\Psi_{SS}=0$'")
xlab = eval("r'Time ($100 \mu$s'")
ylab = 'Rate (Hz)'
plt.figure()
Example #5
0
import matplotlib.pyplot as plt



# Before plasticity
fname = 'Learned_Synchrony_pre_pdvpd.dat'
tit = 'Steady-state Phase Difference as a function of Initial Phase Difference\n before plasticity, X-Oxc EE=0.2, EI=0.3, IE= -0.5, II=0'
xlab = eval("r'$\Delta\Phi_0 $ (Initial Phase diff)'")
ylab = eval("r'$\langle \Delta\Phi_{SS} \\rangle$ (Avg. Steady-state Phase diff)'")
xran = [0, 2*math.pi]
smooth = 0
yran = None
xlims = None
ylims = [-0.1, math.pi+0.1]
plt.figure()
plot_tools.linep(fname, tit, xlab, ylab, smooth, xran, yran, xlims, ylims)


# Plasticity, started IN-phase
# Rate
fnameINr = 'Learned_Synchrony_plas_IN_r.dat'
titINr = 'Plasticity run - started IN phase'
xlabINr = eval("r'Time (100 $\mu$s)'")
ylabINr = 'Rate (Hz)'
# Weight
fnameINw = 'Learned_Synchrony_plas_IN_w.dat'
xlabINw = eval("r'Time (ms)'")
ylabINw = 'Synaptic weight'
#Plot
plt.figure()
#ax1=plt.subplot(2,1,1) #Rates over init-IN plasticity run