def load_parameters(filename, global_only=True, verbose=False, net_id=0):
"""
Loads the global parameters of a network (flag ``population`` for neurons, ``projection`` for synapses) from a JSON file.
*Parameters:*
* **filename:** path to the JSON file.
* **global_only:** True if only global parameters (flags ``population`` and ``projection``) should be loaded, the other values are ignored. (default: True)
* **verbose**: True if the old and new values of the parameters should be printed (default: False).
* **net_id:** ID of the network (default: 0, the global network).
*Returns:*
* a dictionary of additional parameters not related to populations or projections (keyword ``network`` in the JSON file).
It is advised to generate the JSON file first with ``save_parameters()`` and later edit it manually.
A strong restriction is that population/projection names cannot change between saving and loading.
By default, they take names such as ``pop0`` or ``proj2``, we advise setting explicitly a name in their constructor for readability.
If you add a parameter name to the JSON file but it does not exist in te neuron/synapse, it will be silently skipped.
Enable ``verbose=True`` to see which parameters are effectively changed.
If you set ``global_only`` to True, you will be able to set values for non-global parameters (e.g. synapse-specific), but a single value will be loaded for all.
The JSON file cannot contain arrays.
If you want to save/load the value of variables after a simulation, please refer to ``save()`` or ``load()``.
"""
import json
with open('network.json', 'r') as rfile:
desc = json.load(rfile)
if verbose:
Global._print('Loading parameters from file', filename)
Global._print('-'*40)
# Populations
try:
populations = desc['populations']
except:
populations = {}
if verbose:
Global._print('load_parameters(): no population parameters.')
for name, parameters in populations.items():
# Get the population
for pop in Global._network[net_id]['populations']:
if pop.name == name:
population = pop
break
else:
Global._warning('The population', name, 'defined in the file', filename, 'does not exist in the current network.')
if verbose:
Global._print('Population', name)
# Set the parameters
for name, val in parameters.items():
# Check that the variable indeed exists
if not name in population.parameters:
Global._print(' ', name, 'is not a global parameter of', population.name, ', skipping.')
continue
if global_only and not name in population.neuron_type.description['global']:
Global._print(' ', name, 'is not a global parameter of', population.name, ', skipping.')
continue
if verbose:
Global._print(' ', name, ':', population.get(name), '->', val)
population.set({name: float(val)})
# Projections
try:
projections = desc['projections']
except:
projections = {}
if verbose:
Global._print('load_parameters(): no projection parameters.')
for name, parameters in projections.items():
# Get the projection
for proj in Global._network[net_id]['projections']:
if proj.name == name:
projection = proj
break
else:
Global._warning('The projection', name, 'defined in the file', filename, 'does not exist in the current network.')
if verbose:
Global._print('Projection', name)
# Set the parameters
for name, val in parameters.items():
# Check that the variable indeed exists
if not name in projection.parameters:
Global._print(' ', name, 'is not a global parameter of', population.name, ', skipping.')
continue
if global_only and not name in projection.synapse_type.description['global']:
Global._print(' ', name, 'is not a global parameter of', population.name, ', skipping.')
continue
if verbose:
Global._print(' ', name, ':', projection.get(name), '->', val)
projection.set({name: float(val)})
# Constants
try:
constants = desc['constants']
except:
constants = {}
if verbose:
Global._print('load_parameters(): no constants.')
for name, value in constants.items():
if name in Global.list_constants(): # modify it
Global.get_constant(name).value = value
else: # create it
_ = Global.Constant(name, value)
# Global user-defined parameters
try:
network_parameters = {}
for name, val in desc['network'].items():
network_parameters[name] = float(val)
except:
network_parameters = {}
return network_parameters
def extract_boundsflags(constraint, equation="", extra_values={}):
# Process the flags if any
bounds, flags = extract_flags(constraint)
# Get the type of the variable (float/int/bool)
if 'int' in flags:
ctype = 'int'
elif 'bool' in flags:
ctype = 'bool'
else:
ctype = Global.config['precision']
# Get the init value if declared
if 'init' in bounds.keys(): # Variables: explicitely set in init=xx
init = bounds['init']
if ctype == 'bool':
if init in ['false', 'False', '0']:
init = False
elif init in ['true', 'True', '1']:
init = True
elif init in Global.list_constants():
init = Global.get_constant(init)
elif ctype == 'int':
init = int(init)
else:
init = float(init)
elif '=' in equation: # Parameters: the value is in the equation
init = equation.split('=')[1].strip()
# Boolean
if init in ['false', 'False']:
init = False
ctype = 'bool'
elif init in ['true', 'True']:
init = True
ctype = 'bool'
# Constants
elif init in Global.list_constants():
init = Global.get_constant(init)
# Extra-args (obsolete)
elif init.strip().startswith("'"):
var = init.replace("'", "")
init = extra_values[var]
# Integers
elif ctype == 'int':
try:
init = eval('int(' + init + ')')
except:
Global._print(equation)
Global._error('The value of the parameter is not an integer.')
# Floats
else:
try:
init = eval('float(' + init + ')')
except:
Global._print(equation)
Global._error('The value of the parameter is not a float.')
else: # Default = 0 according to ctype
if ctype == 'bool':
init = False
elif ctype == 'int':
init = 0
elif ctype == 'double' or ctype == 'float':
init = 0.0
return bounds, flags, ctype, init
def load_parameters(filename, global_only=True, verbose=False, net_id=0):
"""
Loads the global parameters of a network (flag ``population`` for neurons, ``projection`` for synapses) from a JSON file.
It is advised to generate the JSON file first with ``save_parameters()`` and later edit it manually.
A strong restriction is that population/projection names cannot change between saving and loading.
By default, they take names such as ``pop0`` or ``proj2``, we advise setting explicitly a name in their constructor for readability.
If you add a parameter name to the JSON file but it does not exist in te neuron/synapse, it will be silently skipped.
Enable ``verbose=True`` to see which parameters are effectively changed.
If you set ``global_only`` to True, you will be able to set values for non-global parameters (e.g. synapse-specific), but a single value will be loaded for all.
The JSON file cannot contain arrays.
If you want to save/load the value of variables after a simulation, please refer to ``save()`` or ``load()``.
:param filename: path to the JSON file.
:param global_only: True if only global parameters (flags ``population`` and ``projection``) should be loaded, the other values are ignored. (default: True)
:param verbose: True if the old and new values of the parameters should be printed (default: False).
:param net_id: ID of the network (default: 0, the global network).
:return: a dictionary of additional parameters not related to populations or projections (keyword ``network`` in the JSON file).
"""
import json
with open(filename, 'r') as rfile:
desc = json.load(rfile)
if verbose:
Global._print('Loading parameters from file', filename)
Global._print('-' * 40)
# Populations
try:
populations = desc['populations']
except:
populations = {}
if verbose:
Global._print('load_parameters(): no population parameters.')
for name, parameters in populations.items():
# Get the population
for pop in Global._network[net_id]['populations']:
if pop.name == name:
population = pop
break
else:
Global._warning('The population', name, 'defined in the file',
filename, 'does not exist in the current network.')
if verbose:
Global._print('Population', name)
# Set the parameters
for name, val in parameters.items():
# Check that the variable indeed exists
if not name in population.parameters:
Global._print(' ', name, 'is not a global parameter of',
population.name, ', skipping.')
continue
if global_only and not name in population.neuron_type.description[
'global']:
Global._print(' ', name, 'is not a global parameter of',
population.name, ', skipping.')
continue
if verbose:
Global._print(' ', name, ':', population.get(name), '->', val)
population.set({name: float(val)})
# Projections
try:
projections = desc['projections']
except:
projections = {}
if verbose:
Global._print('load_parameters(): no projection parameters.')
for name, parameters in projections.items():
# Get the projection
for proj in Global._network[net_id]['projections']:
if proj.name == name:
projection = proj
break
else:
Global._warning('The projection', name, 'defined in the file',
filename, 'does not exist in the current network.')
if verbose:
Global._print('Projection', name)
# Set the parameters
for name, val in parameters.items():
# Check that the variable indeed exists
if not name in projection.parameters:
Global._print(' ', name, 'is not a global parameter of',
population.name, ', skipping.')
continue
if global_only and not name in projection.synapse_type.description[
'global']:
Global._print(' ', name, 'is not a global parameter of',
population.name, ', skipping.')
continue
if verbose:
Global._print(' ', name, ':', projection.get(name), '->', val)
projection.set({name: float(val)})
# Constants
try:
constants = desc['constants']
except:
constants = {}
if verbose:
Global._print('load_parameters(): no constants.')
for name, value in constants.items():
if name in Global.list_constants(): # modify it
Global.get_constant(name).value = value
else: # create it
_ = Global.Constant(name, value)
# Global user-defined parameters
try:
network_parameters = {}
for name, val in desc['network'].items():
network_parameters[name] = float(val)
except:
network_parameters = {}
return network_parameters
def extract_boundsflags(constraint, equation ="", extra_values={}):
# Process the flags if any
bounds, flags = extract_flags(constraint)
# Get the type of the variable (float/int/bool)
if 'int' in flags:
ctype = 'int'
elif 'bool' in flags:
ctype = 'bool'
else:
ctype = Global.config['precision']
# Get the init value if declared
if 'init' in bounds.keys(): # Variables: explicitely set in init=xx
init = bounds['init']
if ctype == 'bool':
if init in ['false', 'False', '0']:
init = False
elif init in ['true', 'True', '1']:
init = True
elif init in Global.list_constants():
init = Global.get_constant(init)
elif ctype == 'int':
init = int(init)
else:
init = float(init)
elif '=' in equation: # Parameters: the value is in the equation
init = equation.split('=')[1].strip()
# Boolean
if init in ['false', 'False']:
init = False
ctype = 'bool'
elif init in ['true', 'True']:
init = True
ctype = 'bool'
# Constants
elif init in Global.list_constants():
init = Global.get_constant(init)
# Extra-args (obsolete)
elif init.strip().startswith("'"):
var = init.replace("'","")
init = extra_values[var]
# Integers
elif ctype == 'int':
try:
init = eval('int(' + init + ')')
except:
Global._print(equation)
Global._error('The value of the parameter is not an integer.')
# Floats
else:
try:
init = eval('float(' + init + ')')
except:
Global._print(equation)
Global._error('The value of the parameter is not a float.')
else: # Default = 0 according to ctype
if ctype == 'bool':
init = False
elif ctype == 'int':
init = 0
elif ctype == 'double' or ctype == 'float':
init = 0.0
return bounds, flags, ctype, init
