def target_perturbations(self):
d=mallet2008()
out={}
ll=[d['all']['activation']['control']['rate'],
d['STN']['activation']['control']['rate'],
d['TI']['activation']['lesioned']['rate'],
d['TA']['activation']['lesioned']['rate'],
d['STN']['activation']['lesioned']['rate'],
d['all']['slow_wave']['control']['rate'],
d['STN']['slow_wave']['control']['rate'],
d['TI']['slow_wave']['lesioned']['rate'],
d['TA']['slow_wave']['lesioned']['rate'],
d['STN']['slow_wave']['lesioned']['rate']]
d={'node':{'GP':{'rate':ll[0]},
'ST':{'rate':ll[1]}}}
out['beta_control']=d
d={'node':{'GI':{'rate':ll[2]},
'GA':{'rate':ll[3]},
'ST':{'rate':ll[4]}}}
out['beta_lesion']=d
d={'node':{'GP':{'rate':ll[5]},
'ST':{'rate':ll[6]}}}
out['sw_control']=d
d={'node':{'GI':{'rate':ll[7]},
'GA':{'rate':ll[8]},
'ST':{'rate':ll[9]}}}
out['sw_lesion']=d
return out
def target_perturbations():
d=mallet2008()
out={}
ll=[d['all']['activation']['control']['rate'],
d['STN']['activation']['control']['rate'],
d['TI']['activation']['lesioned']['rate'],
d['TA']['activation']['lesioned']['rate'],
d['STN']['activation']['lesioned']['rate'],
d['all']['slow_wave']['control']['rate'],
d['STN']['slow_wave']['control']['rate'],
d['TI']['slow_wave']['lesioned']['rate'],
d['TA']['slow_wave']['lesioned']['rate'],
d['STN']['slow_wave']['lesioned']['rate']]
d={'node':{'GI':{'rate':ll[0]},
'GA':{'rate':ll[3]},
'ST':{'rate':ll[1]}}}
out['beta_control']=d
d={'node':{'GI':{'rate':ll[2]},
'GA':{'rate':ll[3]},
'ST':{'rate':ll[4]}}}
out['beta_lesion']=d
d={'node':{'GI':{'rate':ll[5]},
'ST':{'rate':ll[6]}}}
out['sw_control']=d
d={'node':{'GI':{'rate':ll[7]},
'GA':{'rate':ll[8]},
'ST':{'rate':ll[9]}}}
out['sw_lesion']=d
for d in out.values():
for model in d['node'].keys():
d['node'][model+'p']=d['node'][model].copy()
return out
save(sd, d)
elif from_disk==2:
keys_iterator=[]
for key in ['mean_rates', 'xlabels', 'ylabels']:
keys_iterator+=[['beta', 'Net_0', key],
['beta', 'Net_1', key],
['sw', 'Net_0', key],
['sw', 'Net_1', key],
]
d = sd.load_dic(**{'keys_iterator':keys_iterator})
# d=sd.load_dic(*filt)
pp(d)
from scripts_inhibition.base_oscillation import mallet2008
exp=mallet2008()
pp(exp)
translation={'all':'GP',
'STN':'ST',
'TI':'GI',
'TA':'GA',
'activation':'beta',
'slow_wave':'sw',
'control':'Net_0',
'lesioned':'Net_1'}
exp=process_exp(exp, translation)
fitting(d, exp)
def target_perturbations():
d = mallet2008()
out = {}
ll = [
d['all']['activation']['control']['rate'],
d['STN']['activation']['control']['rate'],
d['TI']['activation']['lesioned']['rate'],
d['TA']['activation']['lesioned']['rate'],
d['STN']['activation']['lesioned']['rate'],
d['all']['slow_wave']['control']['rate'],
d['STN']['slow_wave']['control']['rate'],
d['TI']['slow_wave']['lesioned']['rate'],
d['TA']['slow_wave']['lesioned']['rate'],
d['STN']['slow_wave']['lesioned']['rate']
]
d = {
'node': {
'GI': {
'rate': ll[0]
},
'GA': {
'rate': ll[3]
},
'ST': {
'rate': ll[1]
}
}
}
out['beta_control'] = d
d = {
'node': {
'GI': {
'rate': ll[2]
},
'GA': {
'rate': ll[3]
},
'ST': {
'rate': ll[4]
}
}
}
out['beta_lesion'] = d
d = {'node': {'GI': {'rate': ll[5]}, 'ST': {'rate': ll[6]}}}
out['sw_control'] = d
d = {
'node': {
'GI': {
'rate': ll[7]
},
'GA': {
'rate': ll[8]
},
'ST': {
'rate': ll[9]
}
}
}
out['sw_lesion'] = d
for d in out.values():
for model in d['node'].keys():
d['node'][model + 'p'] = d['node'][model].copy()
return out