fix voltage_timeseries for single neurons

Neuroblox · Oct 4, 2024 · a0afb02 · a0afb02
1 parent 0f1fb20
commit a0afb02
Showing 1 changed file with 27 additions and 8 deletions.
diff --git a/src/blox/blox_utilities.jl b/src/blox/blox_utilities.jl
@@ -487,6 +487,18 @@ function mean_firing_rate(spikes::SparseMatrixCSC, sol; trim_transient = 0,
     return t, rₘ
 end
 
+function state_timeseries(blox, sol::SciMLBase.AbstractSolution, state::String; ts=nothing)
+
+    namespaced_name = namespaced_nameof(blox)
+    state_name = Symbol(namespaced_name, "₊$(state)")
+
+    if isnothing(ts)
+        return sol[state_name]
+    else
+        return Array(sol(ts, idxs = state_name))
+    end
+end
+
 function state_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}},
                           sol::SciMLBase.AbstractSolution, state::String; ts=nothing)
 
@@ -502,36 +514,43 @@ function state_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeur
     return s
 end
 
-function meanfield_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}}, sol::SciMLBase.AbstractSolution,
-                              state::String; ts=nothing)
+function meanfield_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}},
+                              sol::SciMLBase.AbstractSolution, state::String; ts=nothing)
 
     s = state_timeseries(cb, sol, state; ts)
 
     return vec(mapslices(nanmean, s; dims = 2))
 end
 
-function voltage_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractBlox}}, sol::SciMLBase.AbstractSolution; ts=nothing)
+voltage_timeseries(blox, sol::SciMLBase.AbstractSolution; ts=nothing) = 
+    state_timeseries(blox, sol, "V"; ts)
+
+function voltage_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractBlox}},
+                            sol::SciMLBase.AbstractSolution; ts=nothing)
     return state_timeseries(cb, sol, "V"; ts)
 end
 
-function meanfield_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}}, sol::SciMLBase.AbstractSolution; ts=nothing)
+function meanfield_timeseries(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}},
+                              sol::SciMLBase.AbstractSolution; ts=nothing)
     V = voltage_timeseries(cb, sol; ts)
     replace_refractory!(V, cb, sol)
 
     return vec(mapslices(nanmean, V; dims = 2))
 end
 
-function powerspectrum(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}}, sol::SciMLBase.AbstractSolution, state::String;
-                       sampling_rate=nothing, method=periodogram, window=nothing)
+function powerspectrum(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}},
+                       sol::SciMLBase.AbstractSolution, state::String; sampling_rate=nothing,
+                       method=periodogram, window=nothing)
 
     t_sampled, sampling_freq = get_sampling_info(sol; sampling_rate=sampling_rate)
     s = meanfield_timeseries(cb, sol, state; ts = t_sampled)
 
     return method(s, fs=sampling_freq, window=window)
 end
 
-function powerspectrum(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}}, sol::SciMLBase.AbstractSolution;
-                       sampling_rate=nothing, method=periodogram, window=nothing)
+function powerspectrum(cb::Union{CompositeBlox, AbstractVector{<:AbstractNeuronBlox}},
+                       sol::SciMLBase.AbstractSolution; sampling_rate=nothing,
+                       method=periodogram, window=nothing)
 
     t_sampled, sampling_freq = get_sampling_info(sol; sampling_rate=sampling_rate)
     V = voltage_timeseries(cb, sol; ts = t_sampled)