Basic Usage

This example demonstrates the fundamental operations of DataLab-Kernel.

Creating a Workspace

from datalab_kernel import Workspace, Plotter
from sigima import create_signal, create_image
import numpy as np

# Create workspace (auto-detects DataLab)
workspace = Workspace()
plotter = Plotter(workspace)

print(f"Operating mode: {workspace.mode}")

Working with Signals

# Create time-domain signal
t = np.linspace(0, 1, 1000)
freq = 5  # Hz
signal = np.sin(2 * np.pi * freq * t) + 0.2 * np.random.randn(len(t))

# Create signal object with metadata
sig = create_signal(
    "Noisy Sine Wave",
    t, signal,
    units=("s", "V"),
    labels=("Time", "Amplitude"),
)

# Add to workspace
workspace.add("sine_wave", sig)

# Visualize
plotter.plot("sine_wave")

Working with Images

# Create 2D Gaussian
size = 128
x = np.linspace(-3, 3, size)
y = np.linspace(-3, 3, size)
X, Y = np.meshgrid(x, y)
gaussian = np.exp(-(X**2 + Y**2) / 2)

# Add some noise
noisy_gaussian = gaussian + 0.1 * np.random.randn(size, size)

# Create image object
img = create_image(
    "Noisy Gaussian",
    noisy_gaussian.astype(np.float32),
    units=("mm", "mm", "a.u."),
    labels=("X", "Y", "Intensity"),
)

# Add and visualize
workspace.add("gaussian", img)
plotter.plot("gaussian")

Workspace Operations

# List all objects
print("Objects:", workspace.list())

# Check existence
print("Has 'sine_wave':", workspace.exists("sine_wave"))
print("Has 'unknown':", workspace.exists("unknown"))

# Object count
print("Count:", len(workspace))

# Iteration
for name in workspace:
    print(f"  - {name}")

# Retrieve object
retrieved = workspace.get("sine_wave")
print("Retrieved signal title:", retrieved.title)

# Rename
workspace.rename("gaussian", "gaussian_2d")
print("After rename:", workspace.list())

# Remove
workspace.remove("gaussian_2d")
print("After remove:", workspace.list())

Containment Check

# Using 'in' operator
if "sine_wave" in workspace:
    print("Signal exists!")

if "nonexistent" not in workspace:
    print("Object not found")