Remove more nmllite

Author: pgleeson

modelspec/utils.py

@@ -35,37 +35,6 @@ def load_yaml(filename):
     return data
 
 
-def load_network_json(filename):
-    """
-    Load a NeuroMLlite network JSON file
-    """
-
-    data = load_json(filename)
-
-    print_v("Loaded network specification from %s" % filename)
-
-    net = Network()
-    net = _parse_element(data, net)
-
-    return net
-
-
-def load_simulation_json(filename):
-    """
-    Load a NeuroMLlite simulation JSON file
-    """
-
-    with open(filename, "r") as f:
-
-        data = json.load(f, object_hook=ascii_encode_dict)
-
-    print_v("Loaded simulation specification from %s" % filename)
-
-    sim = Simulation()
-    sim = _parse_element(data, sim)
-
-    return sim
-
 
 def save_to_json_file(info_dict, filename, indent=4):
 
@@ -326,34 +295,9 @@ def evaluate(expr, parameters={}, rng=None, array_format=FORMAT_NUMPY, verbose=F
             return expr
 
 
-def get_pops_vs_cell_indices_seg_ids(recordSpec, network):
-
-    pvc = {}
-    if recordSpec is not None:
-        for p in recordSpec:
-            indices = recordSpec[p]
-            if p == "all":
-                for pop in network.populations:
-                    cell_indices_seg_ids = _generate_cell_indices_seg_ids(
-                        pop.id, indices, network
-                    )
-                    pvc[pop.id] = cell_indices_seg_ids
-
-            else:
-                # pop = network.get_child(p, 'populations')
-                cell_indices_seg_ids = _generate_cell_indices_seg_ids(
-                    p, indices, network
-                )
-                pvc[p] = cell_indices_seg_ids
-
-    return pvc
-
-
 """
     Translates a string like '3', '[0,2]' to a list
 """
-
-
 def parse_list_like(list_str):
 
     if isinstance(list_str, int):
@@ -376,176 +320,3 @@ def parse_list_like(list_str):
         if "[" in list_str:
             l = eval(list_str)
             return l
-
-
-def _generate_cell_indices_seg_ids(pop_id, indices_segids, network):
-
-    a = {}
-    pop = network.get_child(pop_id, "populations")
-
-    if not isinstance(indices_segids, str) or not ":" in indices_segids:
-        seg_ids = None
-        indices = indices_segids
-    else:
-        indices = indices_segids.split(":")[0]
-        seg_id_info = indices_segids.split(":")[1]
-        l = parse_list_like(seg_id_info)
-        print_v("Parsed %s as %s" % (seg_id_info, l))
-        seg_ids = l
-
-    if indices == "*":
-        size = evaluate(pop.size, network.parameters)
-        for index in range(size):
-            a[index] = seg_ids
-    else:
-        l = parse_list_like(indices)
-        print_v("Parsed %s (full: %s) as %s" % (indices, indices_segids, l))
-        for index in l:
-            a[index] = seg_ids
-    return a
-
-
-def is_spiking_input_population(population, network):
-
-    cell = network.get_child(population.component, "cells")
-
-    return is_spiking_input_cell(cell)
-
-
-def is_spiking_input_cell(cell):
-    if cell.pynn_cell:
-        if cell.pynn_cell == "SpikeSourcePoisson":
-            return True
-        else:
-            return False
-
-
-def is_spiking_input_nml_cell(component_obj):
-    if component_obj.__class__.__name__ == "SpikeSourcePoisson":
-        return True
-    else:
-        return False
-
-
-def create_new_model(
-    reference,
-    duration,
-    dt=0.025,  # ms
-    temperature=6.3,  # degC
-    default_region=None,
-    parameters=None,
-    cell_for_default_population=None,
-    color_for_default_population="0.8 0 0",
-    input_for_default_population=None,
-    synapses=[],
-    simulation_seed=12345,
-    network_filename=None,
-    simulation_filename=None,
-):
-
-    ################################################################################
-    ###   Build a new network
-
-    net = Network(id=reference)
-    net.notes = "A network model: %s" % reference
-    net.temperature = temperature  # degC
-    if parameters:
-        net.parameters = parameters
-
-    ################################################################################
-    ###   Add some regions
-
-    if default_region:
-        if type(default_region) == str:
-            r1 = RectangularRegion(
-                id=default_region, x=0, y=0, z=0, width=1000, height=100, depth=1000
-            )
-            net.regions.append(r1)
-            default_region = r1
-        else:
-            net.regions.append(default_region)
-
-    ################################################################################
-    ###   Add some cells
-
-    if cell_for_default_population:
-        net.cells.append(cell_for_default_population)
-
-    ################################################################################
-    ###   Add some synapses
-
-    for s in synapses:
-        net.synapses.append(s)
-
-    ################################################################################
-    ###   Add some populations
-
-    if cell_for_default_population:
-        pop = Population(
-            id="pop_%s" % cell_for_default_population.id,
-            size=1,
-            component=cell_for_default_population.id,
-            properties={"color": color_for_default_population},
-        )
-
-        if default_region:
-            pop.region = default_region
-
-            pop.random_layout = RandomLayout(region=default_region.id)
-
-        net.populations.append(pop)
-
-    ################################################################################
-    ###   Add a projection
-
-    """
-    net.projections.append(Projection(id='proj0',
-                                      presynaptic=p0.id,
-                                      postsynaptic=p1.id,
-                                      synapse='ampa'))
-
-    net.projections[0].random_connectivity=RandomConnectivity(probability=0.5)"""
-
-    ################################################################################
-    ###   Add some inputs
-
-    if input_for_default_population:
-
-        net.input_sources.append(input_for_default_population)
-
-        net.inputs.append(
-            Input(
-                id="Stim_%s" % input_for_default_population.id,
-                input_source=input_for_default_population.id,
-                population=pop.id,
-                percentage=100,
-            )
-        )
-
-    ################################################################################
-    ###   Save to JSON format
-
-    net.id = reference
-
-    print(net.to_json())
-    if network_filename == None:
-        network_filename = "%s.json" % net.id
-    new_file = net.to_json_file(network_filename)
-
-    ################################################################################
-    ###   Build Simulation object & save as JSON
-
-    sim = Simulation(
-        id="Sim_%s" % reference,
-        network=new_file,
-        duration=duration,
-        dt=dt,
-        seed=simulation_seed,
-        recordTraces={"all": "*"},
-    )
-
-    if simulation_filename == None:
-        simulation_filename = "%s.json" % sim.id
-    sim.to_json_file(simulation_filename)
-
-    return sim, net