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src/n/e/NeuroTools-0.2.0/examples/single_neuron/simple_single_neuron.py   NeuroTools(Download)
from NeuroTools.signals import load_spikelist
# using parameters utility
from NeuroTools.parameters import ParameterSet
from pyNN.utility import Timer
 
    def __init__(self,N=100):
        # simulator specific
        simulation_params = ParameterSet({'dt'        : 0.1,# discretization step in simulations (ms)
                    'simtime'   : 40000*0.1,      # float; (ms)
                    'syn_delay' : 1.0,         # float; (ms)
                    'kernelseed' : 4321097,       # array with one element per thread
                    'connectseed' : 12345789  # seed for random generator(s) used during simulation
                    })
        # these may change
        self.params = ParameterSet({'simulation': simulation_params,

src/n/e/NeuroTools-0.2.0/examples/parameters/validation/simple_validation.py   NeuroTools(Download)
import NeuroTools.parameters.validators
import NeuroTools.parameters as ntp
 
schema = ntp.ParameterSchema("./data/conf_schema1.yaml")
p1 = ntp.ParameterSet("./data/conf1.yaml")
p2 = ntp.ParameterSet("./data/conf2.yaml")

src/n/e/NeuroTools-0.2.0/examples/parameters/parameter_to_latex.py   NeuroTools(Download)
from NeuroTools.parameters import ParameterSet
from NeuroTools.parameters import ParameterRange
from NeuroTools.parameters import ParameterTable
 
 
 
p = ParameterSet({})
""")
p.a = 23
p.b = ParameterSet({})
p.b.s = ParameterRange([1,2,3])
p.b.w = ParameterTable("""

src/n/e/NeuroTools-0.2.0/examples/parameter_search/parameter_search_example.py   NeuroTools(Download)
    rates = numpy.linspace(start = 10., stop = 100.,  num = 5)
    weights = numpy.linspace(start = 0.1,  stop = 1.0, num = 5)
    from NeuroTools.parameters import ParameterSet, ParameterSpace, ParameterRange
    params = ParameterSpace(ParameterSet({'rate':ParameterRange(rates), 
                                          'weight': ParameterRange(weights)}))

src/n/e/NeuroTools-0.2.0/examples/retina/retina.py   NeuroTools(Download)
import os, tempfile
import numpy
from NeuroTools.parameters import ParameterSet
 
 
        params['amplitude'] = amplitude
 
        self.params =  ParameterSet(params)
            #self.params.save('file://' + os.getcwd() + '/retina.param')
 

src/p/y/PyNN-HEAD/examples/iaf_sfa_relref/mcb.py   PyNN(Download)
### Neurons ###
 
params = NeuroTools.parameters.ParameterSet('standard_neurons.yaml')
myModel = sim.IF_cond_exp_gsfa_grr
popE = sim.Population((1,),myModel,params.excitatory,label='popE')

src/p/y/PyNN-HEAD/examples/iaf_sfa_relref/iaf_sfa_network_STATIC.py   PyNN(Download)
localPath = "./standard_neurons.yaml"
import NeuroTools.parameters
params = NeuroTools.parameters.ParameterSet(localPath)
 
## Effectively zero the refractory period ##

src/p/y/PyNN-HEAD/examples/iaf_sfa_relref/iaf_sfa_network_INH_GAMMA.py   PyNN(Download)
localPath = "./standard_neurons.yaml"
import NeuroTools.parameters
params = NeuroTools.parameters.ParameterSet(localPath)
 
## Effectively zero the refractory period ##

src/p/y/PyNN-HEAD/examples/iaf_sfa_relref/backend_comparison.py   PyNN(Download)
    sim.setup(timestep=dt, min_delay=dt, max_delay=30.0, debug=True, quit_on_end=False)
 
    params = NeuroTools.parameters.ParameterSet('standard_neurons.yaml')
    myModel = sim.IF_cond_exp_gsfa_grr
    popE = sim.Population((1,),myModel,params.excitatory,label='popE')

src/n/e/NeuroTools-0.2.0/src/parameters/validators.py   NeuroTools(Download)
 
import yaml
from NeuroTools.parameters import ParameterSet
import NeuroTools.parameters
 
class ParameterSchema(ParameterSet):
    """
    A sub-class of ParameterSet against which other ParameterSets can be validated against.
 
    Presenlty, it is more or less a ParameterSet, with all leafs(values) which are not explicitly
        if not isinstance(ps, ParameterSet):
            # create ParameterSet, but allowing SchemaBase derived objects
            ps = ParameterSet(ps,update_namespace=schema_checkers_namespace)
 
        # convert each element 

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