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# Copyright (c) 2026 Zymatica. All rights reserved.
import sys
class SparseTransition:
def __init__(self, key=0, sym=0, count=0):
self.key = key
self.sym = sym
self.count = count
class RadicalPredictor:
def __init__(self, alpha=1, weight=128):
self.alpha = alpha
self.weight = weight
self.trans_rc = []
self.trans_rf = []
self.trans_ra = []
self.prev_rc = 0
self.prev_rf = 0
self.prev_ra = 0
def observe(self, rc, rf, ra):
w = self.weight
key_rc = self.prev_rc
found = False
for entry in self.trans_rc:
if entry.key == key_rc and entry.sym == rc:
entry.count += w
found = True
break
if not found and len(self.trans_rc) < 256:
self.trans_rc.append(SparseTransition(key_rc, rc, w))
key_rf = (rc << 8) | self.prev_rf
found = False
for entry in self.trans_rf:
if entry.key == key_rf and entry.sym == rf:
entry.count += w
found = True
break
if not found and len(self.trans_rf) < 256:
self.trans_rf.append(SparseTransition(key_rf, rf, w))
key_ra = (rc << 16) | (rf << 8) | self.prev_ra
found = False
for entry in self.trans_ra:
if entry.key == key_ra and entry.sym == ra:
entry.count += w
found = True
break
if not found and len(self.trans_ra) < 256:
self.trans_ra.append(SparseTransition(key_ra, ra, w))
self.prev_rc = rc
self.prev_rf = rf
self.prev_ra = ra
def get_cum_freqs_rc(self, prev_rc):
freqs = [self.alpha] * 256
for entry in self.trans_rc:
if entry.key == prev_rc:
freqs[entry.sym] += entry.count
cum_freqs = [0] * 257
for i in range(256):
cum_freqs[i+1] = cum_freqs[i] + freqs[i]
return cum_freqs
def get_cum_freqs_rf(self, curr_rc, prev_rf):
freqs = [self.alpha] * 256
key = (curr_rc << 8) | prev_rf
for entry in self.trans_rf:
if entry.key == key:
freqs[entry.sym] += entry.count
cum_freqs = [0] * 257
for i in range(256):
cum_freqs[i+1] = cum_freqs[i] + freqs[i]
return cum_freqs
def get_cum_freqs_ra(self, curr_rc, curr_rf, prev_ra):
freqs = [self.alpha] * 256
key = (curr_rc << 16) | (curr_rf << 8) | prev_ra
for entry in self.trans_ra:
if entry.key == key:
freqs[entry.sym] += entry.count
cum_freqs = [0] * 257
for i in range(256):
cum_freqs[i+1] = cum_freqs[i] + freqs[i]
return cum_freqs
class BitWriter:
def __init__(self):
self.buffer = bytearray()
self.bit_index = 0
def write_bit(self, bit):
byte_pos = self.bit_index // 8
bit_pos = 7 - (self.bit_index % 8)
if byte_pos >= len(self.buffer):
self.buffer.append(0)
if bit:
self.buffer[byte_pos] |= (1 << bit_pos)
else:
self.buffer[byte_pos] &= ~(1 << bit_pos)
self.bit_index += 1
def write_bit_helper(self, underflow_bits, bit):
self.write_bit(bit)
while underflow_bits[0] > 0:
self.write_bit(1 - bit)
underflow_bits[0] -= 1
class BitReader:
def __init__(self, data):
self.data = data
self.bit_index = 0
self.total_bits = len(data) * 8
def read_bit(self):
if self.bit_index >= self.total_bits:
return 0
byte_pos = self.bit_index // 8
bit_pos = 7 - (self.bit_index % 8)
bit = (self.data[byte_pos] >> bit_pos) & 1
self.bit_index += 1
return bit
def encode(concepts, alpha, weight):
pred = RadicalPredictor(alpha, weight)
w = BitWriter()
low = 0
high = 0xFFFFFFFF
underflow_bits = [0]
for c in concepts:
rc = (c[0] << 4) | c[1]
rf = (c[2] << 4) | c[3]
ra = (c[4] << 4) | c[5]
symbols = [rc, rf, ra]
prev_rc = pred.prev_rc
prev_rf = pred.prev_rf
prev_ra = pred.prev_ra
for step in range(3):
if step == 0:
cum_freqs = pred.get_cum_freqs_rc(prev_rc)
elif step == 1:
cum_freqs = pred.get_cum_freqs_rf(symbols[0], prev_rf)
else:
cum_freqs = pred.get_cum_freqs_ra(symbols[0], symbols[1], prev_ra)
sym = symbols[step]
total = cum_freqs[256]
cum_low = cum_freqs[sym]
cum_high = cum_freqs[sym + 1]
range_width = high - low + 1
high = low + (range_width * cum_high) // total - 1
low = low + (range_width * cum_low) // total
while True:
if high < 0x80000000:
w.write_bit_helper(underflow_bits, 0)
low <<= 1
high = (high << 1) | 1
elif low >= 0x80000000:
w.write_bit_helper(underflow_bits, 1)
low = (low - 0x80000000) << 1
high = ((high - 0x80000000) << 1) | 1
elif low >= 0x40000000 and high < 0xC0000000:
underflow_bits[0] += 1
low = (low - 0x40000000) << 1
high = ((high - 0x40000000) << 1) | 1
else:
break
low &= 0xFFFFFFFF
high &= 0xFFFFFFFF
pred.observe(rc, rf, ra)
underflow_bits[0] += 1
if low < 0x40000000:
w.write_bit_helper(underflow_bits, 0)
else:
w.write_bit_helper(underflow_bits, 1)
return w.buffer, w.bit_index
def decode(encoded_bytes, num_concepts, alpha, weight):
pred = RadicalPredictor(alpha, weight)
r = BitReader(encoded_bytes)
value = 0
for _ in range(32):
value = (value << 1) | r.read_bit()
low = 0
high = 0xFFFFFFFF
decoded_concepts = []
for _ in range(num_concepts):
prev_rc = pred.prev_rc
prev_rf = pred.prev_rf
prev_ra = pred.prev_ra
symbols = [0, 0, 0]
for step in range(3):
if step == 0:
cum_freqs = pred.get_cum_freqs_rc(prev_rc)
elif step == 1:
cum_freqs = pred.get_cum_freqs_rf(symbols[0], prev_rf)
else:
cum_freqs = pred.get_cum_freqs_ra(symbols[0], symbols[1], prev_ra)
total = cum_freqs[256]
range_width = high - low + 1
scaled_val = ((value - low + 1) * total - 1) // range_width
sym = 0
l_idx, r_idx = 0, 255
while l_idx <= r_idx:
m_idx = (l_idx + r_idx) // 2
if cum_freqs[m_idx] <= scaled_val < cum_freqs[m_idx + 1]:
sym = m_idx
break
elif scaled_val >= cum_freqs[m_idx + 1]:
l_idx = m_idx + 1
else:
r_idx = m_idx - 1
symbols[step] = sym
cum_low = cum_freqs[sym]
cum_high = cum_freqs[sym + 1]
high = low + (range_width * cum_high) // total - 1
low = low + (range_width * cum_low) // total
while True:
if high < 0x80000000:
low <<= 1
high = (high << 1) | 1
value = (value << 1) | r.read_bit()
elif low >= 0x80000000:
low = (low - 0x80000000) << 1
high = ((high - 0x80000000) << 1) | 1
value = ((value - 0x80000000) << 1) | r.read_bit()
elif low >= 0x40000000 and high < 0xC0000000:
low = (low - 0x40000000) << 1
high = ((high - 0x40000000) << 1) | 1
value = ((value - 0x40000000) << 1) | r.read_bit()
else:
break
low &= 0xFFFFFFFF
high &= 0xFFFFFFFF
value &= 0xFFFFFFFF
decoded_concepts.append([
(symbols[0] >> 4) & 0xF,
symbols[0] & 0xF,
(symbols[1] >> 4) & 0xF,
symbols[1] & 0xF,
(symbols[2] >> 4) & 0xF,
symbols[2] & 0xF
])
pred.observe(symbols[0], symbols[1], symbols[2])
return decoded_concepts
def main():
print("======================================================================")
print("ZYMATICA | zymatica-inference-engine-python")
print("======================================================================\n")
inputs = [
[1, 2, 3, 4, 5, 6],
[8, 0, 15, 1, 0, 15],
[0, 0, 0, 0, 0, 0],
[15, 15, 15, 15, 15, 15],
[4, 5, 6, 7, 8, 9]
]
buf, bits = encode(inputs, 1, 128)
print(f"Encoded Bits: {bits}, Bytes: {len(buf)}")
print("Hex:", " ".join(f"{b:02X}" for b in buf))
import time
start_time = time.perf_counter()
runs = 100000
match = True
for r in range(runs):
decoded = decode(buf, 5, 1, 128)
if r == 0:
match = decoded == inputs
end_time = time.perf_counter()
elapsed_ms = (end_time - start_time) * 1000.0
print(f"Decoded matches inputs: {match}")
if not match:
print("ERROR: mismatch!")
sys.exit(1)
print(f"[INTERNAL_MATH] {elapsed_ms:.4f} ms")
print("\n[VERIFICATION] Multi-Language runtime FFI structures validated.")
if __name__ == '__main__':
main()
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