def __init__(self, numero_entradas_rams, tamanho_entrada,
numero_discriminadores):
self.retina = retina.Retina(tamanho_entrada)
self.discriminadores = []
self.numero_discriminadores = numero_discriminadores
for i in range(0, numero_discriminadores):
self.discriminadores.append(
discriminador.Discriminador(numero_entradas_rams,
tamanho_entrada))
self.classificacao_discriminadores = [0] * numero_discriminadores
def __init__(self, numero_entradas_rams, tamanho_entrada, score_minimo,
intervalo_crescimento):
self.retina = retina.Retina(tamanho_entrada)
self.discriminadores = []
self.numero_discriminadores = 0
self.numero_entradas_rams = numero_entradas_rams
self.tamanho_entrada = tamanho_entrada
self.score_minimo = score_minimo
self.intervalo_crescimento = intervalo_crescimento
self.classificacao_discriminadores = []
self.clusters = []
def __init__(self, numero_entradas_rams, tamanho_entrada, numero_discriminadores, score_minimo, intervalo_crescimento):
self.retina = retina.Retina(tamanho_entrada)
self.discriminadores = []
self.numero_discriminadores = numero_discriminadores
self.numero_entradas_rams = numero_entradas_rams
self.tamanho_entrada = tamanho_entrada
self.score_minimo = score_minimo
self.intervalo_crescimento = intervalo_crescimento
for i in range(0, numero_discriminadores):
self.discriminadores.append(discriminador_cluswisard.DiscriminadorCluswisard(numero_entradas_rams, tamanho_entrada, i))
self.classificacao_discriminadores = [0]*numero_discriminadores
def init_ipy(debug=False, nb_dir=None, api_url=None):
# get config
for c in filter(lambda x: not x.startswith('_'), config.__dict__.keys()):
setattr(Ipy, c, getattr(config, c))
# set pathing
if nb_dir and os.path.isdir(nb_dir):
Ipy.NB_DIR = nb_dir
else:
Ipy.NB_DIR = os.getcwd()
Ipy.LIB_DIR = Ipy.NB_DIR + '/lib'
Ipy.TMP_DIR = Ipy.NB_DIR + '/tmp'
Ipy.CCH_DIR = Ipy.NB_DIR + '/cache'
Ipy.IMG_DIR = Ipy.NB_DIR + '/images'
for d in (Ipy.LIB_DIR, Ipy.TMP_DIR, Ipy.IMG_DIR):
if not os.path.isdir(d):
os.mkdir(d)
# set api
if api_url is not None:
Ipy.API_URL = api_url
# set graphing tools
Ipy.FL_PLOT = flotplot.FlotPlot()
Ipy.RETINA = retina.Retina()
Ipy.DEBUG = debug
# load matR and extras
ro.r('suppressMessages(library(matR))')
ro.r('suppressMessages(library(gplots))')
ro.r('suppressMessages(library(scatterplot3d))')
# add tab completion from a dir - bit of a hack
# skip names with hyphen '-' in them, its an operator and not valid name syntax :(
# these are for kbase command line scripts, no .pl
names = map(lambda x: os.path.basename(x), glob.glob(Ipy.KBASE_BIN + '/*'))
names = filter(
lambda x: (not x.endswith('.pl')) and (not x.endswith('.py')), names)
Ipy.KBASE_CMDS = "\n".join(names)
names = filter(lambda x: '-' not in x, names)
add_tab_completion(names)
# echo
if Ipy.DEBUG:
for k in filter(lambda x: not x.startswith('_'), Ipy.__dict__.keys()):
print k, getattr(Ipy, k)
liquid.matrix_programmable_exc_inh[
use_retina_projections] = np.random.choice(
[0, 1], size=np.sum(use_retina_projections))
liquid.matrix_programmable_w[use_retina_projections] = np.random.choice(
[0, 1, 2, 3], size=np.sum(use_retina_projections))
liquid.program_config()
###### configure retina
inputpop = pyNCS.Population('', '')
inputpop.populate_by_id(nsetup, 'mn256r1', 'excitatory',
np.linspace(0, 255, 256))
syncpop = pyNCS.Population("", "")
syncpop.populate_by_id(nsetup, 'mn256r1', 'excitatory', [nsync])
#reset multiplexer
chip.configurator._set_multiplexer(0)
retina = ret.Retina(inputpop)
retina._init_fpga_mapper()
retina.map_retina_sync(syncpop,
ncol_retina=ncol_retina_sync,
neu_sync=nsync) ### neuron 255 is our sync neuron
rr, pre, post = retina.map_retina_random_connectivity(
inputpop, c=0.3, syntype='virtual_exc', ncol_sync=ncol_retina_sync)
rr, pre, post = retina.map_retina_random_connectivity(
inputpop, c=0.1, syntype='virtual_inh', ncol_sync=ncol_retina_sync)
import RetinaInputs as ri
win = ri.RetinaInputs(nsetup)
#win.run(300)
chip.load_parameters('biases/biases_reservoir_retina.biases')
p = ParameterSpace({
'noise_std':
ParameterRange(list(10.**(numpy.linspace(-.50, 1., N_exp_noise))))
})
name = sys.argv[0].split('.')[
0] # name of the current script withpout the '.py' part
results = shelve.open('results/mat-' + name)
try:
CRF = results['CRF']
except:
# this is not mandatory but just a "easy_install progressbar" away
# else remove all corresponding lines in this code...
import progressbar # see http://projects.scipy.org/pipermail/scipy-dev/2008-January/008200.html
import retina as model
retina = model.Retina(N)
retina.params['snr'] = 0 # no input
# calculates the dimension of the parameter space
results_dim, results_label = p.parameter_space_dimension_labels()
# creates results array with size of parameter space dimension
CRF = numpy.empty(results_dim)
pbar = progressbar.ProgressBar(widgets=[
name, " ",
progressbar.Percentage(), ' ',
progressbar.Bar(), ' ',
progressbar.ETA()
],
maxval=numpy.prod(results_dim))