def load_dic(self, *filt, **kw):
d = {}
if kw.get('keys_iterator'):
for keys in kw['keys_iterator']:
print keys
storage = misc.dict_recursive_get(self, keys)
val = storage.load_data()
d = misc.dict_recursive_add(d, keys, val)
return d
for keys, storage in misc.dict_iter(self):
if filt == ():
pass
else:
a = False
i = 0
for key in keys:
if key not in filt and i not in kw.get('star', []):
a = True
i += 1
if key == 'mean_rates':
pass
if i == len(keys):
break
if a:
continue
val = storage.load_data()
d = misc.dict_recursive_add(d, keys, val)
return d
def generate_plot_data(d,
models,
attrs,
exclude=['all', 'striatum', 'GP-ST-SN', 'Normal']):
out = {}
labels = []
keys = d.keys()
for k in sorted(keys):
if k in exclude:
continue
labels.append(k)
for model in models:
l = []
for attr in attrs:
l.append([])
for k in sorted(keys):
if k in exclude:
continue
l[-1].append(misc.dict_recursive_get(d, [k, model, attr]))
lsum = [[a] * len(l[0]) for a in numpy.sum(l, axis=1)]
obj = Data_bar(**{
'y': numpy.array(l) #/numpy.array(lsum)
})
out = misc.dict_recursive_add(out, [model], obj)
return out, labels
def generate_plot_data(d, models, attrs, exclude=['all',
'striatum',
'GP-ST-SN',
'Normal']):
out={}
labels=[]
keys=d.keys()
for k in sorted(keys):
if k in exclude:
continue
labels.append(k)
for model in models:
l=[]
for attr in attrs:
l.append([])
for k in sorted(keys):
if k in exclude:
continue
l[-1].append(misc.dict_recursive_get(d, [k, model, attr]))
lsum=[[a]*len(l[0]) for a in numpy.sum(l, axis=1)]
obj=Data_bar(**{'y':numpy.array(l)#/numpy.array(lsum)
})
out=misc.dict_recursive_add(out, [model], obj)
return out, labels
def load_dic(self, *filt, **kw):
d={}
if kw.get('keys_iterator'):
for keys in kw['keys_iterator']:
print keys
storage=misc.dict_recursive_get(self, keys)
val=storage.load_data()
d=misc.dict_recursive_add(d, keys, val)
return d
for keys, storage in misc.dict_iter(self):
if filt==():
pass
else:
a=False
i=0
for key in keys:
if key not in filt and i not in kw.get('star', []):
a=True
i+=1
if key=='mean_rates':
pass
if i==len(keys):
break
if a:
continue
val=storage.load_data()
d=misc.dict_recursive_add(d, keys, val)
return d
def save_dic(self, d, **k):
print 'Saving ' + self.file_name
for keys, data in misc.dict_iter(d):
if not misc.dict_haskey(self.dic, keys):
self.add_storage(keys)
s = misc.dict_recursive_get(self.dic, keys)
s.save_data('-'.join(keys), data, **k)
self.save()
def save_dic(self, d, **k):
print 'Saving '+self.file_name
for keys, data in misc.dict_iter(d):
if not misc.dict_haskey(self.dic, keys):
self.add_storage(keys)
s=misc.dict_recursive_get(self.dic, keys)
s.save_data('-'.join(keys), data, **k)
self.save()
def compute_performance(d, nets, models, attrs):
results={}
for run in d.keys():
for model in models:
for attr in attrs:
keys1=[run, 'Net_0', model, attr]
keys2=[run, 'Net_1', model, attr]
keys3=[run, model, attr]
v1=misc.dict_recursive_get(d, keys1)
v2=misc.dict_recursive_get(d, keys2)
v=(v1-v2)/v1
v[numpy.isnan(v)]=0
v=numpy.mean((v)**2)
results=misc.dict_recursive_add(results, keys3, v)
d0={}
for run in results.keys():
for model in models:
for attr in attrs:
keys0=['Normal', model, attr]
v1=misc.dict_recursive_get(results, keys0)
d0=misc.dict_recursive_add(d0, keys0, v1)
for run in results.keys():
for model in models:
for attr in attrs:
keys0=['Normal', model, attr]
keys3=[run, model, attr]
v0=misc.dict_recursive_get(d0, keys0)
v1=misc.dict_recursive_get(results, keys3)
results=misc.dict_recursive_add(results, keys3, v1/v0)
return results
def test_save(self):
self.sd = Storage_dic(self.file_name)
for keys, val in misc.dict_iter(self.data):
#Add storage objects
self.sd.add_storage(keys)
s = misc.dict_recursive_get(self.sd, keys)
key = '-'.join(keys)
s.save_data(key, val)
self.sd.save()
self.assertTrue(os.path.isfile(self.file_name + '.pkl'))
self.assertTrue(os.path.isdir(self.file_name + '/'))
def test_save(self):
self.sd=Storage_dic(self.file_name)
for keys, val in misc.dict_iter(self.data):
#Add storage objects
self.sd.add_storage(keys)
s=misc.dict_recursive_get(self.sd, keys)
key='-'.join(keys)
s.save_data(key,val)
self.sd.save()
self.assertTrue(os.path.isfile(self.file_name+'.pkl'))
self.assertTrue(os.path.isdir(self.file_name+'/'))
def compute_performance(d, nets, models, attrs):
results = {}
for run in d.keys():
for model in models:
for attr in attrs:
keys1 = [run, 'Net_0', model, attr]
keys2 = [run, 'Net_1', model, attr]
keys3 = [run, model, attr]
v1 = misc.dict_recursive_get(d, keys1)
v2 = misc.dict_recursive_get(d, keys2)
v = (v1 - v2) / v1
v[numpy.isnan(v)] = 0
v = numpy.mean((v)**2)
results = misc.dict_recursive_add(results, keys3, v)
d0 = {}
for run in results.keys():
for model in models:
for attr in attrs:
keys0 = ['Normal', model, attr]
v1 = misc.dict_recursive_get(results, keys0)
d0 = misc.dict_recursive_add(d0, keys0, v1)
for run in results.keys():
for model in models:
for attr in attrs:
keys0 = ['Normal', model, attr]
keys3 = [run, model, attr]
v0 = misc.dict_recursive_get(d0, keys0)
v1 = misc.dict_recursive_get(results, keys3)
results = misc.dict_recursive_add(results, keys3, v1 / v0)
return results