def load_params(simID, path):
"""
Load saved simulation parameters
Parameters
----------
simID : string
simulation ID
path : string
the base directory
Returns
--------
all information about the given simulation: class instance
"""
from utils.utils import update_path
params = pickle.load(open(path + '/Log/metadata_' + simID + '.pkl', "rb"))
params.data_dir = update_path(path, params.data_dir)
params.data_dir = "/".join(params.data_dir.split(os.sep)[:9]) + '/'
params.path = update_path(path, params.path)
return params
def __init__(self, simID, nn=0, effect=None, cond='30'):
self.simID = simID
self.params = pickle.load(
open(path + '/Log/metadata_' + simID + '.pkl', "rb"))
self.params.data_dir = update_path(path, self.params.data_dir)
self.params.path = update_path(path, self.params.path)
self.nn = nn
self.cond = cond
if effect:
self.params.effect = effect
#fig=[plt.subplots(1,1) for i in range(len(params.noise))]
IDs = ['10-13_15:40:44', '10-13_15:40:51']
#IDs=['10-13_18:13:22','10-13_18:13:14','10-13_18:41:30','10-13_19:23:53']
#labels=['Related lures','Unrelated lures']
labels = ['1', '2', '3', '4']
colors = ['r', 'g', 'b', 'orange']
markers = ['-', '-', '-', '-']
#fits=['Rn:0','Rn:0','Rn:0','Rn:0']
fits = ['Full', 'Rn:0', 'Full', 'Full']
fig, ax = plt.subplots(1, 1)
m = -1
o = 0
nn = 0
for index, simID in enumerate(IDs):
params = pickle.load(open(path1 + '/Log/metadata_' + simID + '.pkl', "rb"))
params.data_dir = update_path(path1, params.data_dir)
params.data_dir = "/".join(params.data_dir.split(os.sep)[:9]) + '/'
params.path = update_path(path1, params.path)
mat = matlab(params)
data, conds = mat.load_dpsd(fit=fits[index])
ax.plot(data[o][m]['fa'][0][nn],
data[o][m]['hits'][0][nn],
'o',
color=colors[index],
alpha=0.6)
# ax.plot(data[o][0]['fa'][nn][0],data[o][0]['hits'][nn][0],'ro')
ax.plot(data[o][m]['roc_fa'][m][:, nn],
data[o][m]['roc_hit'][0][:, nn],
'b',
color=colors[index],
linestyle=markers[index],
import numpy as np
import matplotlib.pyplot as plt
#path=os.path.abspath(os.path.join(os.getcwd(), os.pardir))
#sys.path.insert(0,path)
path = os.path.abspath(os.path.join(os.getcwd(), os.pardir))
os.chdir(path)
path1 = os.path.abspath(os.path.join(path, os.pardir))
m = -1 # which hippocampal system to access
from utils import utils
from utils.utils import update_path
from analysis.plot_utils import set_aspect
simID = '07-05_17:39:39'
params = pickle.load(open(path1 + '/Log/metadata_' + simID + '.pkl', "rb"))
params.data_dir = update_path(path1, params.data_dir, separator='Data')
params.data_dir = "/".join(params.data_dir.split(os.sep)[:9]) + '/'
params.path = update_path(path1, params.path)
# don't change these
o = params.offset[-1] # offset level to access
n = params.noise[0] # noise level to access
data_weak = [
pd.read_pickle(params.data_dir + 'weak/' + str(params.N_t) + '-' +
str(params.pat_sep[ii]) + '.pkl') for ii in [0, m]
]
data_strong = [
pd.read_pickle(params.data_dir + 'strong/' + str(params.N_t) + '-' +
str(params.pat_sep[ii]) + '.pkl') for ii in [0, m]
]
