import numpy as np

# -----------------------------
# HDGL Channel (Dynamic Flip-Chip)
# -----------------------------
class HDGLChannel:
    def __init__(self, id):
        self.id = id
        self.pages = []
        self.tension = 0.0

    def assign_page(self, page_data: bytes):
        self.pages.append(bytearray(page_data))
        self.update_tension(len(page_data))

    def operate(self):
        for i, page in enumerate(self.pages):
            arr = np.frombuffer(page, dtype=np.uint8).copy()
            arr = ((arr.astype(np.uint16) + 1) % 256).astype(np.uint8)
            self.pages[i] = bytearray(arr)
        self.update_tension(sum(len(p) for p in self.pages))

    def update_tension(self, size):
        # Analog superposition propagation
        self.tension = 0.7 * self.tension + 0.3 * (size / 4096.0)

    def swap_out_pages(self):
        # Simulate dynamic page swap to free tension
        if len(self.pages) > 4:
            removed = self.pages[:len(self.pages)//2]
            self.pages = self.pages[len(self.pages)//2:]
            self.update_tension(sum(len(p) for p in self.pages))
            return removed
        return []

# -----------------------------
# HDGL Lattice (Dynamic Expansion)
# -----------------------------
class HDGLLattice:
    def __init__(self, initial_channels=32, max_channels=64):
        self.channels = [HDGLChannel(i) for i in range(initial_channels)]
        self.max_channels = max_channels
        self.next_id = initial_channels

    def select_channel(self):
        tensions = np.array([ch.tension for ch in self.channels])
        min_idx = np.argmin(tensions)
        return self.channels[min_idx]

    def map_page(self, page_data: bytes):
        ch = self.select_channel()
        if ch.tension > 2.0 and len(self.channels) < self.max_channels:
            # Auto-expand lattice with new channel
            new_ch = HDGLChannel(self.next_id)
            self.next_id += 1
            self.channels.append(new_ch)
            new_ch.assign_page(page_data)
        else:
            ch.assign_page(page_data)

    def harmonic_fusion(self):
        tensions = np.array([ch.tension for ch in self.channels])
        fused = (tensions + np.roll(tensions, 1) + np.roll(tensions, -1)) / 3
        for i, ch in enumerate(self.channels):
            ch.tension = fused[i]

    def operate_all(self):
        swapped_pages = []
        for ch in self.channels:
            ch.operate()
            swapped_pages.extend(ch.swap_out_pages())
        self.harmonic_fusion()
        # Remap swapped-out pages dynamically
        for page in swapped_pages:
            self.map_page(page)

# -----------------------------
# Synthetic Pages
# -----------------------------
def generate_synthetic_pages(num_pages=128, page_size=4096):
    return [bytes(np.random.randint(0, 256, page_size, dtype=np.uint8)) for _ in range(num_pages)]

def generate_all_device_pages():
    devices = {
        "kernel": 64,
        "initramfs": 128,
        "CPU": 32,
        "GPU": 32,
        "RAM": 64,
        "swap": 16,
        "network": 8
    }
    pages = []
    for dev, count in devices.items():
        pages.extend(generate_synthetic_pages(num_pages=count))
    return pages

# -----------------------------
# Main Execution
# -----------------------------
if __name__ == "__main__":
    lattice = HDGLLattice(initial_channels=32, max_channels=64)

    all_pages = generate_all_device_pages()
    for page in all_pages:
        lattice.map_page(page)

    # Operate lattice for multiple cycles to simulate live OS activity
    for cycle in range(5):
        lattice.operate_all()
        print(f"Cycle {cycle}: {len(lattice.channels)} channels active")
        for ch in lattice.channels:
            print(f"  Channel {ch.id}: {len(ch.pages)} pages, tension {ch.tension:.4f}")
