Dashboard — CLI Simulation Monitor

Text-based dashboard for monitoring spiking network simulations in the terminal. Displays per-neuron firing rates with trend indicators and bar charts. Designed for quick visual feedback during development — not a replacement for proper analysis tools.

SCDashboard

Maintains a rolling history (last 20 timesteps) of firing rates per neuron. On each update(), prints a formatted table with:

• Neuron index
• Current firing rate
• Trend indicator: / UP (rate increasing), \ DWN (decreasing), - STY (stable, ±0.01)
• Bar chart (rate × 20 characters)

Parameter	Meaning
n_neurons	Number of neurons to monitor

Methods:

• update(firing_rates, step) — Record rates and render dashboard
• History is auto-truncated to 20 entries per neuron

Usage

from sc_neurocore.dashboard.text_dashboard import SCDashboard
import numpy as np

dash = SCDashboard(n_neurons=4)
for step in range(100):
    rates = np.random.rand(4).tolist()
    dash.update(rates, step=step)

Output:

--- SC DASHBOARD | Step 42 ---
Neuron   | Rate     | Trend (Last 5)
----------------------------------------
#0       | 0.731    | / UP ||||||||||||||
#1       | 0.245    | \ DWN |||||
#2       | 0.500    | - STY ||||||||||
#3       | 0.892    | / UP ||||||||||||||||||
----------------------------------------

sc_neurocore.dashboard.text_dashboard

SCDashboard

Simple CLI Dashboard for monitoring SC simulation.

Source code in src/sc_neurocore/dashboard/text_dashboard.py

class SCDashboard:
    """
    Simple CLI Dashboard for monitoring SC simulation.
    """

    def __init__(self, n_neurons: int):
        self.n_neurons = n_neurons
        self.history: list[list[float]] = [[] for _ in range(n_neurons)]

    def update(self, firing_rates: list[float], step: int) -> None:
        # Update history
        for i, rate in enumerate(firing_rates):
            self.history[i].append(rate)
            if len(self.history[i]) > 20:  # Keep last 20
                self.history[i].pop(0)

        self._render(step)

    def _render(self, step: int) -> None:
        # ANSI Escape codes for clearing screen/cursor might not work well in all notebook/CLI envs
        # We will just print a frame separator.

        print(f"\n--- SC DASHBOARD | Step {step} ---")
        print(f"{'Neuron':<8} | {'Rate':<8} | {'Trend (Last 5)'}")
        print("-" * 40)

        for i in range(self.n_neurons):
            rate = self.history[i][-1]

            # Simple sparkline-like trend
            trend = ""
            if len(self.history[i]) >= 2:
                diff = rate - self.history[i][-2]
                if diff > 0.01:
                    trend = "/ UP"
                elif diff < -0.01:
                    trend = "\\ DWN"
                else:
                    trend = "- STY"

            # Bar chart
            bar_len = int(rate * 20)
            bar = "|" * bar_len

            print(f"#{i:<7} | {rate:.3f}    | {trend} {bar}")

        print("-" * 40)