Ejemplo n.º 1
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def test_proto_and_arky_fit(npz1, npz2, fit_num):
    create_npz_param(npz1, model='gp', neuron_type='proto', fitnum=fit_num)
    create_npz_param(npz2,
                     model='gp',
                     neuron_type='arky',
                     fitnum=fit_num,
                     cond_file='param_cond_proto144_proto_10.py')
Ejemplo n.º 2
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def persist_cond_param(object_type, model, neuron_type, **kwargs):
    if object_type == "fit":
        pass
    elif object_type == "npz":
        npz_file = kwargs.get('npz_file') if kwargs.get('npz_file') else raise ValueError('npz_file needed!!!')
        create_npz_param(npz_file, model, neuron_type, store_param_path=kwargs.get('store_param_path'),
                             fitnum=kwargs.get('fitnum'), cond_file= kwargs.get('cond_file'))
    else:
        raise ValueError("Object_type must be 'fit' or 'npz' with valid parameters!")
Ejemplo n.º 3
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def test_proto_and_arky(npz1, npz2):
    create_npz_param(npz1, model='gp', neuron_type='proto')
    create_npz_param(npz2,
                     model='gp',
                     neuron_type='arky',
                     cond_file='param_cond_proto144_proto_1954.py')
Ejemplo n.º 4
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def test_proto_only(npz1):
    create_npz_param(npz1, model='gp', neuron_type='proto')
Ejemplo n.º 5
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def test_proto_and_arky(fit_num):
        npz1 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitFgp-proto-proto144.npz"
	npz2 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitgp-arky-arky120F.npz"
	create_npz_param(npz1, model='gp', neuron_type='proto', fitnum = fit_num)
        create_npz_param(npz2, model='gp', neuron_type='arky', cond_file= 'param_cond_proto144_proto_1954.py')
Ejemplo n.º 6
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def test_proto_only():
	npz1 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitFgp-proto-proto144.npz"
	create_npz_param(npz1, model='gp', neuron_type='proto')
Ejemplo n.º 7
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#!/usr/bin/env python3


import logging
from ajustador.helpers.loggingsystem import getlogger
from ajustador.helpers.save_param.create_npz_param import create_npz_param

logger = getlogger(__name__)
logger.setLevel(logging.INFO)

npz1 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitFgp-proto-proto144.npz"
npz2 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitd1d2-D1-D1_010612_pas3.npz"
npz3 = "/home/ram/neural_prj/prof_resources/parameters_fit_to_param_cond/fitgp-arky-arky120F.npz"
store_param_path = "/home/ram/neural_prj/outputs/parameter_sets"

### Test run ###
create_npz_param(npz2, model='d1d2', neuron_type='D1')
create_npz_param(npz1, model='gp', neuron_type='proto')
create_npz_param(npz2, model='d1d2', neuron_type='D1', store_param_path=store_param_path)
create_npz_param(npz1, model='gp', neuron_type='proto', fitnum=10, store_param_path=store_param_path)
create_npz_param(npz3, model='gp', neuron_type='arky', cond_file= 'param_cond_proto_1954.py')
create_npz_param(npz3, model='gp', neuron_type='arky',fitnum = 20, cond_file= 'param_cond_proto_1954_arky_1585.py')
create_npz_param(npz1, model='gp', neuron_type='proto',fitnum = 55, cond_file= 'param_cond_proto_1954_arky_1585.py')