def allocate_sync_ensembles(self, tolerance = 0.01, indexes = None):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each
synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.
@param[in] indexes (list): List of real object indexes and it should be equal to amount of oscillators (in case of 'None' - indexes are in range [0; amount_oscillators]).
@return (list) Grours (lists) of indexes of synchronous oscillators.
For example [ [index_osc1, index_osc3], [index_osc2], [index_osc4, index_osc5] ].
"""
if (self._ccore_sync_dynamic_pointer is not None):
ensembles = wrapper.sync_dynamic_allocate_sync_ensembles(self._ccore_sync_dynamic_pointer, tolerance);
if (indexes is not None):
for ensemble in ensembles:
for index in range(len(ensemble)):
ensemble[index] = indexes[ ensemble[index] ];
return ensembles;
if ( (self._dynamic is None) or (len(self._dynamic) == 0) ):
return [];
number_oscillators = len(self._dynamic[0]);
last_state = self._dynamic[len(self._dynamic) - 1];
clusters = [];
if (number_oscillators > 0):
clusters.append([0]);
for i in range(1, number_oscillators, 1):
cluster_allocated = False;
for cluster in clusters:
for neuron_index in cluster:
last_state_shifted = abs(last_state[i] - 2 * pi);
if ( ( (last_state[i] < (last_state[neuron_index] + tolerance)) and (last_state[i] > (last_state[neuron_index] - tolerance)) ) or
( (last_state_shifted < (last_state[neuron_index] + tolerance)) and (last_state_shifted > (last_state[neuron_index] - tolerance)) ) ):
cluster_allocated = True;
real_index = i;
if (indexes is not None):
real_index = indexes[i];
cluster.append(real_index);
break;
if (cluster_allocated == True):
break;
if (cluster_allocated == False):
clusters.append([i]);
return clusters;
def allocate_sync_ensembles(self, tolerance = 0.01):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each
synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.
@return (list) Grours (lists) of indexes of synchronous oscillators.
For example [ [index_osc1, index_osc3], [index_osc2], [index_osc4, index_osc5] ].
"""
if (self._ccore_sync_dynamic_pointer is not None):
return wrapper.sync_dynamic_allocate_sync_ensembles(self._ccore_sync_dynamic_pointer, tolerance);
number_oscillators = len(self._dynamic[0]);
last_state = self._dynamic[len(self._dynamic) - 1];
clusters = [];
if (number_oscillators > 0):
clusters.append([0]);
for i in range(1, number_oscillators, 1):
cluster_allocated = False;
for cluster in clusters:
for neuron_index in cluster:
last_state_shifted = abs(last_state[i] - 2 * pi);
if ( ( (last_state[i] < (last_state[neuron_index] + tolerance)) and (last_state[i] > (last_state[neuron_index] - tolerance)) ) or
( (last_state_shifted < (last_state[neuron_index] + tolerance)) and (last_state_shifted > (last_state[neuron_index] - tolerance)) ) ):
cluster_allocated = True;
cluster.append(i);
break;
if (cluster_allocated == True):
break;
if (cluster_allocated == False):
clusters.append([i]);
return clusters;
def allocate_sync_ensembles(self,
tolerance=0.01,
indexes=None,
iteration=None):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.
@param[in] indexes (list): List of real object indexes and it should be equal to amount of oscillators (in case of 'None' - indexes are in range [0; amount_oscillators]).
@param[in] iteration (uint): Iteration of simulation that should be used for allocation.
@return (list) Grours (lists) of indexes of synchronous oscillators.
For example [ [index_osc1, index_osc3], [index_osc2], [index_osc4, index_osc5] ].
"""
if (self._ccore_sync_dynamic_pointer is not None):
ensembles = wrapper.sync_dynamic_allocate_sync_ensembles(
self._ccore_sync_dynamic_pointer, tolerance, iteration)
if (indexes is not None):
for ensemble in ensembles:
for index in range(len(ensemble)):
ensemble[index] = indexes[ensemble[index]]
return ensembles
if ((self._dynamic is None) or (len(self._dynamic) == 0)):
return []
number_oscillators = len(self._dynamic[0])
last_state = None
if (iteration is None):
last_state = self._dynamic[len(self._dynamic) - 1]
else:
last_state = self._dynamic[iteration]
clusters = []
if (number_oscillators > 0):
clusters.append([0])
for i in range(1, number_oscillators, 1):
cluster_allocated = False
for cluster in clusters:
for neuron_index in cluster:
last_state_shifted = abs(last_state[i] - 2 * pi)
if (((last_state[i] <
(last_state[neuron_index] + tolerance)) and
(last_state[i] >
(last_state[neuron_index] - tolerance)))
or ((last_state_shifted <
(last_state[neuron_index] + tolerance)) and
(last_state_shifted >
(last_state[neuron_index] - tolerance)))):
cluster_allocated = True
real_index = i
if (indexes is not None):
real_index = indexes[i]
cluster.append(real_index)
break
if (cluster_allocated == True):
break
if (cluster_allocated == False):
clusters.append([i])
return clusters
