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