def _generate_projections(net_id, gather_subprojections):
txt = ""
proj_tpl = """
%(pre)s & %(post)s & %(target)s & %(synapse)s &
%(description)s \\\\ \\hline
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name and proj.target == existing_proj.target : # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
for proj in projections:
# Find a name for the synapse
if proj.synapse_type.name in Synapse._default_names.values(): # name not set
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type)
else:
synapse_name = proj.synapse_type.name
txt += proj_tpl % { 'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / '),
'synapse': synapse_name,
'description': proj.connector_description}
return connectivity_template % {'projections_description': txt}
def _generate_projections(net_id, gather_subprojections):
txt = ""
proj_tpl = """
%(pre)s & %(post)s & %(target)s & %(synapse)s &
%(description)s \\\\ \\hline
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name and proj.target == existing_proj.target : # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
for proj in projections:
# Find a name for the synapse
if proj.synapse_type.name in Synapse._default_names.values(): # name not set
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type)
else:
synapse_name = proj.synapse_type.name
txt += proj_tpl % { 'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / '),
'synapse': synapse_name,
'description': proj.connector_description}
return connectivity_template % {'projections_description': txt}
def _generate_projection_parameters(net_id, gather_subprojections):
txt = ""
proj_tpl = """
%(name)s & $%(param)s$ & %(value)s \\\\ \\hline
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name and proj.target == existing_proj.target: # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
first = True
for rk, proj in enumerate(projections):
parameters = ""
for idx, param in enumerate(proj.parameters):
if param == 'w':
continue
if idx == 0:
proj_name = "%(pre)s $\\rightarrow$ %(post)s with target %(target)s" % {
'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / ')
}
else:
proj_name = ""
val = proj.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.min(val)) + ", " + str(np.max(val)) + "]$"
parameters += proj_tpl % {
'name': proj_name,
'param': LatexParser._latexify_name(param, []),
'value': val
}
if parameters != "":
txt += projparameters_template % {
'parameters':
parameters,
'firstprojection':
"\hdr{3}{H}{Projection parameters}\\\\ \\hline"
if first else ""
}
first = False
return txt
def _generate_projection_parameters(net_id, gather_subprojections):
txt = ""
proj_tpl = """
%(name)s & $%(param)s$ & %(value)s \\\\ \\hline
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name and proj.target == existing_proj.target : # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
first = True
for rk, proj in enumerate(projections):
parameters = ""
for idx, param in enumerate(proj.parameters):
if param == 'w':
continue
if idx == 0:
proj_name = "%(pre)s $\\rightarrow$ %(post)s with target %(target)s" % {
'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / ')}
else:
proj_name = ""
val = proj.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.min(val)) + ", " + str(np.max(val)) + "]$"
parameters += proj_tpl % {'name': proj_name, 'param': LatexParser._latexify_name(param, []), 'value': val}
if parameters != "":
txt += projparameters_template % {'parameters': parameters, 'firstprojection': "\hdr{3}{H}{Projection parameters}\\\\ \\hline" if first else ""}
first = False
return txt
def _generate_summary(net_id):
txt = """
# Structure of the network
"""
# General information
backend = 'default'
if Global.config['paradigm'] == 'cuda':
backend = "CUDA"
elif Global.config['paradigm'] == "openmp" and Global.config['num_threads'] > 1:
backend = "OpenMP"
txt +="""
* ANNarchy %(version)s using the %(backend)s backend.
* Numerical step size: %(dt)s ms.
""" % {'version': ANNarchy.__release__, 'backend': backend, 'dt': Global.config['dt']}
# Populations
if len(Global._network[net_id]['populations']) > 0:
headers = ["Population", "Size", "Neuron type"]
populations = []
for pop in Global._network[net_id]['populations']:
# Find a name for the neuron
neuron_name = "Neuron " + str(pop.neuron_type._rk_neurons_type) if pop.neuron_type.name in Neuron._default_names.values() \
else pop.neuron_type.name
populations.append([
pop.name,
pop.geometry if len(pop.geometry)>1 else pop.size,
neuron_name])
txt += """
## Populations
"""
txt += _make_table(headers, populations)
# Projections
if len(Global._network[net_id]['projections']) > 0 :
headers = ["Source", "Destination", "Target", "Synapse type", "Pattern"]
projections = []
for proj in Global._network[net_id]['projections']:
# Find a name for the synapse
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type) if proj.synapse_type.name in Synapse._default_names.values() \
else proj.synapse_type.name
projections.append([
proj.pre.name,
proj.post.name,
LatexParser._format_list(proj.target, ' / '),
synapse_name,
proj.connector_description
])
txt += """
## Projections
"""
txt += _make_table(headers, projections)
# Monitors
if len(Global._network[net_id]['monitors']) > 0:
headers = ["Object", "Variables", "Period"]
monitors = []
for monitor in Global._network[net_id]['monitors']:
monitors.append([
monitor.object.name + (" (subset)" if isinstance(monitor.object, PopulationView) else ""),
LatexParser._format_list(monitor.variables, ', '),
monitor.period
])
txt += """
## Monitors
"""
txt += _make_table(headers, monitors)
# Functions
if len(Global._objects['functions']) > 0 :
txt += """## Functions
"""
for name, func in Global._objects['functions']:
txt += LatexParser._process_functions(func, begin="$$", end="$$\n\n")
return txt
def _generate_parameters(net_id, gather_subprojections):
txt = """
# Parameters
"""
# Constants
if len(Global._objects['constants']) > 0:
txt += """
## Constants
"""
constants_list = [
["$" + LatexParser._latexify_name(constant.name, []) + "$", constant.value]
for constant in Global._objects['constants']]
constants_headers = ["Name", "Value"]
txt += _make_table(constants_headers, constants_list)
# Population parameters
txt += """
## Population parameters
"""
parameters_list = []
for rk, pop in enumerate(Global._network[net_id]['populations']):
neuron_name = "Neuron " + str(pop.neuron_type._rk_neurons_type) if pop.neuron_type.name in Neuron._default_names.values() \
else pop.neuron_type.name
for idx, param in enumerate(pop.parameters):
val = pop.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.array(val).min()) + ", " + str(np.array(val).max()) + "]$"
parameters_list.append(
[ LatexParser.pop_name(pop.name) if idx==0 else "",
neuron_name if idx==0 else "",
"$" + LatexParser._latexify_name(param, []) + "$",
val ] )
population_headers = ["Population", "Neuron type", "Name", "Value"]
txt += _make_table(population_headers, parameters_list)
# Projection parameters
txt += """
## Projection parameters
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name \
and proj.target == existing_proj.target : # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
parameters_list = []
for rk, proj in enumerate(projections):
for idx, param in enumerate(proj.parameters):
if param == 'w':
continue
if idx == 0:
proj_name = "%(pre)s $\\rightarrow$ %(post)s with target %(target)s" % {
'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / ')}
else:
proj_name = ""
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type) if proj.synapse_type.name in Synapse._default_names.values() \
else proj.synapse_type.name
val = proj.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.array(val).min()) + ", " + str(np.array(val).max()) + "]$"
parameters_list.append(
[ proj_name,
synapse_name if idx == 0 else "",
"$" + LatexParser._latexify_name(param, []) + "$",
val ] )
projection_headers = ["Projection", "Synapse type", "Name", "Value"]
txt += _make_table(projection_headers, parameters_list)
return txt
def _generate_summary(net_id):
txt = """
# Structure of the network
"""
# General information
backend = 'default'
if Global.config['paradigm'] == 'cuda':
backend = "CUDA"
elif Global.config['paradigm'] == "openmp" and Global.config['num_threads'] > 1:
backend = "OpenMP"
txt +="""
* ANNarchy %(version)s using the %(backend)s backend.
* Numerical step size: %(dt)s ms.
""" % {'version': ANNarchy.__release__, 'backend': backend, 'dt': Global.config['dt']}
# Populations
if len(Global._network[net_id]['populations']) > 0:
headers = ["Population", "Size", "Neuron type"]
populations = []
for pop in Global._network[net_id]['populations']:
# Find a name for the neuron
neuron_name = "Neuron " + str(pop.neuron_type._rk_neurons_type) if pop.neuron_type.name in Neuron._default_names.values() \
else pop.neuron_type.name
populations.append([
pop.name,
pop.geometry if len(pop.geometry)>1 else pop.size,
neuron_name])
txt += """
## Populations
"""
txt += _make_table(headers, populations)
# Projections
if len(Global._network[net_id]['projections']) > 0 :
headers = ["Source", "Destination", "Target", "Synapse type", "Pattern"]
projections = []
for proj in Global._network[net_id]['projections']:
# Find a name for the synapse
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type) if proj.synapse_type.name in Synapse._default_names.values() \
else proj.synapse_type.name
projections.append([
proj.pre.name,
proj.post.name,
LatexParser._format_list(proj.target, ' / '),
synapse_name,
proj.connector_description
])
txt += """
## Projections
"""
txt += _make_table(headers, projections)
# Monitors
if len(Global._network[net_id]['monitors']) > 0:
headers = ["Object", "Variables", "Period"]
monitors = []
for monitor in Global._network[net_id]['monitors']:
monitors.append([
monitor.object.name + (" (subset)" if isinstance(monitor.object, PopulationView) else ""),
LatexParser._format_list(monitor.variables, ', '),
monitor.period
])
txt += """
## Monitors
"""
txt += _make_table(headers, monitors)
# Functions
if len(Global._objects['functions']) > 0 :
txt += """## Functions
"""
for name, func in Global._objects['functions']:
txt += LatexParser._process_functions(func, begin="$$", end="$$\n\n")
return txt
def _generate_parameters(net_id, gather_subprojections):
txt = """
# Parameters
"""
# Constants
if len(Global._objects['constants']) > 0:
txt += """
## Constants
"""
constants_list = [
["$" + LatexParser._latexify_name(constant.name, []) + "$", constant.value]
for constant in Global._objects['constants']]
constants_headers = ["Name", "Value"]
txt += _make_table(constants_headers, constants_list)
# Population parameters
txt += """
## Population parameters
"""
parameters_list = []
for rk, pop in enumerate(Global._network[net_id]['populations']):
neuron_name = "Neuron " + str(pop.neuron_type._rk_neurons_type) if pop.neuron_type.name in Neuron._default_names.values() \
else pop.neuron_type.name
for idx, param in enumerate(pop.parameters):
val = pop.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.array(val).min()) + ", " + str(np.array(val).max()) + "]$"
parameters_list.append(
[ LatexParser.pop_name(pop.name) if idx==0 else "",
neuron_name if idx==0 else "",
"$" + LatexParser._latexify_name(param, []) + "$",
val ] )
population_headers = ["Population", "Neuron type", "Name", "Value"]
txt += _make_table(population_headers, parameters_list)
# Projection parameters
txt += """
## Projection parameters
"""
if gather_subprojections:
projections = []
for proj in Global._network[net_id]['projections']:
for existing_proj in projections:
if proj.pre.name == existing_proj.pre.name and proj.post.name == existing_proj.post.name \
and proj.target == existing_proj.target : # TODO
break
else:
projections.append(proj)
else:
projections = Global._network[net_id]['projections']
parameters_list = []
for rk, proj in enumerate(projections):
for idx, param in enumerate(proj.parameters):
if param == 'w':
continue
if idx == 0:
proj_name = "%(pre)s $\\rightarrow$ %(post)s with target %(target)s" % {
'pre': LatexParser.pop_name(proj.pre.name),
'post': LatexParser.pop_name(proj.post.name),
'target': LatexParser._format_list(proj.target, ' / ')}
else:
proj_name = ""
synapse_name = "Synapse " + str(proj.synapse_type._rk_synapses_type) if proj.synapse_type.name in Synapse._default_names.values() \
else proj.synapse_type.name
val = proj.init[param]
if isinstance(val, (list, np.ndarray)):
val = "$[" + str(np.array(val).min()) + ", " + str(np.array(val).max()) + "]$"
parameters_list.append(
[ proj_name,
synapse_name if idx == 0 else "",
"$" + LatexParser._latexify_name(param, []) + "$",
val ] )
projection_headers = ["Projection", "Synapse type", "Name", "Value"]
txt += _make_table(projection_headers, parameters_list)
return txt