Level 3: First positive SNR version

source/core/aac_coder.py

@@ -214,7 +214,10 @@ def aac_pack_frame_f_to_seq_channels(frame_type: FrameType, frame_f: FrameF) ->
 # Level 1 encoder
 # -----------------------------------------------------------------------------
 
-def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
+def aac_coder_1(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq1:
     """
     Level-1 AAC encoder.
 
@@ -231,6 +234,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     filename_in : Union[str, Path]
         Input WAV filename.
         Assumption: stereo audio, sampling rate 48 kHz.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -257,8 +262,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     aac_seq: AACSeq1 = []
     prev_frame_type: FrameType = "OLS"
 
-    win_type: WinType = WIN_TYPE
+    if verbose:
-
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -275,23 +280,31 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
             next_t = np.vstack([next_t, tail])
 
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
-        frame_f = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f)
 
         aac_seq.append({
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {"frame_F": chl_f},
             "chr": {"frame_F": chr_f},
         })
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
 
-def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
+def aac_coder_2(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq2:
     """
     Level-2 AAC encoder (Level 1 + TNS).
 
@@ -299,6 +312,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     ----------
     filename_in : Union[str, Path]
         Input WAV filename (stereo, 48 kHz).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -330,6 +345,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     aac_seq: AACSeq2 = []
     prev_frame_type: FrameType = "OLS"
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -347,16 +364,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
         # Level 1 analysis (packed stereo container)
         frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
-        # Unpack to per-channel (as you already do in Level 1)
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
-        if frame_type == "ESH":
-            chl_f = np.empty((128, 8), dtype=np.float64)
-            chr_f = np.empty((128, 8), dtype=np.float64)
-            for j in range(8):
-                chl_f[:, j] = frame_f_stereo[:, 2 * j + 0]
-                chr_f[:, j] = frame_f_stereo[:, 2 * j + 1]
-        else:
-            chl_f = frame_f_stereo[:, 0:1].astype(np.float64, copy=False)
-            chr_f = frame_f_stereo[:, 1:2].astype(np.float64, copy=False)
 
         # Level 2: apply TNS per channel
         chl_f_tns, chl_tns_coeffs = aac_tns(chl_f, frame_type)
@@ -370,8 +378,12 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
                 "chr": {"frame_F": chr_f_tns, "tns_coeffs": chr_tns_coeffs},
             }
         )
-
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
@@ -379,6 +391,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
 def aac_coder_3(
     filename_in: Union[str, Path],
     filename_aac_coded: Union[str, Path] | None = None,
+    verbose: bool = False,
 ) -> AACSeq3:
     """
     Level-3 AAC encoder (Level 2 + Psycho + Quantizer + Huffman).
@@ -389,6 +402,8 @@ def aac_coder_3(
         Input WAV filename (stereo, 48 kHz).
     filename_aac_coded : Union[str, Path] | None
         Optional .mat filename to store aac_seq_3 (assignment convenience).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -416,15 +431,14 @@ def aac_coder_3(
     aac_seq: AACSeq3 = []
     prev_frame_type: FrameType = "OLS"
 
-    # Pin win_type to the WinType literal for type checkers.
-    win_type: WinType = WIN_TYPE
-
     # Psycho model needs per-channel history (prev1, prev2) of 2048-sample frames.
     prev1_L = np.zeros((2048,), dtype=np.float64)
     prev2_L = np.zeros((2048,), dtype=np.float64)
     prev1_R = np.zeros((2048,), dtype=np.float64)
     prev2_R = np.zeros((2048,), dtype=np.float64)
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -440,7 +454,7 @@ def aac_coder_3(
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
 
         # Analysis filterbank (stereo packed)
-        frame_f_stereo = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
 
         # TNS per channel
@@ -474,32 +488,35 @@ def aac_coder_3(
         # Codebook 11:
         # maxAbsCodeVal = 16 is RESERVED for ESCAPE.
         # We must stay strictly within [-15, +15] to avoid escape decoding.
-        sf_cb = 11
+        # sf_cb = 11
-        sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        # sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        #
+        # sfc_L_dpcm = np.clip(
+        #     sfc_L_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
+        #
+        # sfc_R_dpcm = np.clip(
+        #     sfc_R_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
 
-        sfc_L_dpcm = np.clip(
+        sfc_L_stream, cb_sfc_L = aac_encode_huff(
-            sfc_L_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_R_dpcm = np.clip(
-            sfc_R_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_L_stream, _ = aac_encode_huff(
             sfc_L_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
-        sfc_R_stream, _ = aac_encode_huff(
+        sfc_R_stream, cb_sfc_R = aac_encode_huff(
             sfc_R_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
 
+        if cb_sfc_L != 11 or cb_sfc_R != 11:
+            print (f"frame: {i}: cb_sfc_l={cb_sfc_L}, cb_sfc_r={cb_sfc_R}")
+
         mdct_L_stream, cb_L = aac_encode_huff(
             np.asarray(S_L, dtype=np.int64).reshape(-1),
             huff_LUT_list,
@@ -512,7 +529,7 @@ def aac_coder_3(
         # Typed dict construction helps static analyzers validate the schema.
         frame_out: AACSeq3Frame = {
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {
                 "tns_coeffs": np.asarray(chl_tns_coeffs, dtype=np.float64),
                 "T": np.asarray(T_L, dtype=np.float64),
@@ -539,6 +556,11 @@ def aac_coder_3(
         prev1_R = frame_R
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     # Optional: store to .mat for the assignment wrapper
     if filename_aac_coded is not None:
@@ -548,6 +570,5 @@ def aac_coder_3(
             {"aac_seq_3": np.array(aac_seq, dtype=object)},
             do_compression=True,
         )
-
     return aac_seq
 

source/core/aac_decoder.py

@@ -118,7 +118,11 @@ def aac_remove_padding(y_pad: StereoSignal, hop: int = 1024) -> StereoSignal:
 # Level 1 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_1(
+    aac_seq_1: AACSeq1,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-1 AAC decoder (inverse of aac_coder_1()).
 
@@ -134,6 +138,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_1().
     filename_out : Union[str, Path]
         Output WAV filename. Assumption: 48 kHz, stereo.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -152,6 +158,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad: StereoSignal = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_1):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -164,12 +172,15 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start:start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y: StereoSignal = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     # Level 1 assumption: 48 kHz output.
     sf.write(str(filename_out), y, 48000)
-
     return y
 
 
@@ -177,7 +188,11 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 # Level 2 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_2(
+    aac_seq_2: AACSeq2,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-2 AAC decoder (inverse of aac_coder_2).
 
@@ -195,6 +210,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_2().
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -213,6 +230,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_2):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -260,15 +279,23 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y
 
 
 
-def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_3(
+    aac_seq_3: AACSeq3,
+    filename_out: Union[str, Path],
+    verbose: bool = False,
+) -> StereoSignal:
     """
     Level-3 AAC decoder (inverse of aac_coder_3).
 
@@ -286,6 +313,8 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_3.
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -307,6 +336,9 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
+
     for i, fr in enumerate(aac_seq_3):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -401,7 +433,12 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
 
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y

source/core/aac_psycho.py

@@ -316,8 +316,8 @@ def _psycho_one_window(
     nb = en * bc
 
     # Threshold in quiet (convert from dB to power domain):
-    # qthr_power = (N/2) * 10^(qthr_db/10)
+    # qthr_power = eps * (N/2) * 10^(qthr_db/10)
-    qthr_power = (N / 2.0) * (10.0 ** (qthr_db / 10.0))
+    qthr_power = np.finfo('float').eps * (N / 2.0) * (10.0 ** (qthr_db / 10.0))
 
     # Final masking threshold per band:
     # np(b) = max(nb(b), qthr(b))

source/core/tests/test_aac_coder_decoder.py

@@ -25,38 +25,64 @@ from core.aac_utils import snr_db
 from core.aac_types import *
 
 
-# Helper "fixtures" for aac_coder_1 / i_aac_coder_1
+# -----------------------------------------------------------------------------
+# Fixtures (small wav logic)
 # -----------------------------------------------------------------------------
 
+@pytest.fixture(scope="session")
+def wav_in_path() -> Path:
+    """
+    Provided input WAV used for end-to-end tests.
+
+    Expected project layout:
+      source/material/LicorDeCalandraca.wav
+    """
+    return Path(__file__).resolve().parents[2] / "material" / "LicorDeCalandraca.wav"
+
+
 @pytest.fixture()
-def tmp_stereo_wav(tmp_path: Path) -> Path:
+def mk_random_stereo_wav(tmp_path: Path, request: pytest.FixtureRequest) -> Path:
     """
     Create a temporary 48 kHz stereo WAV with random samples.
+
+    Length (in seconds) must be provided via indirect parametrization.
     """
+    length = float(request.param)
     rng = np.random.default_rng(123)
     fs = 48000
 
-    # ~1 second of audio (kept small for test speed).
+    n = int(fs * length)
-    n = fs
     x: StereoSignal = rng.normal(size=(n, 2)).astype(np.float64)
 
-    wav_path = tmp_path / "in.wav"
+    wav_path = tmp_path / "in_random.wav"
     sf.write(str(wav_path), x, fs)
     return wav_path
 
 
+@pytest.fixture()
+def mk_actual_stereo_wav(tmp_path: Path, wav_in_path: Path, request: pytest.FixtureRequest) -> Path:
+    """
+    Create a temporary 48 kHz stereo WAV by chopping from the provided material WAV.
+    Length can be overridden via indirect parametrization.
+    """
+    length = float(getattr(request, "param", 0.25))  # seconds (default: small)
+
+    x, fs = aac_read_wav_stereo_48k(wav_in_path)
+    n = int(fs * length)
+    x_short = x[:n, :]
+
+    wav_path = tmp_path / "in_actual.wav"
+    sf.write(str(wav_path), x_short, fs)
+    return wav_path
+
+
 # -----------------------------------------------------------------------------
 # Helper-function tests
 # -----------------------------------------------------------------------------
 
-def test_aac_read_wav_stereo_48k_roundtrip(tmp_stereo_wav: Path) -> None:
+@pytest.mark.parametrize("mk_random_stereo_wav", [2.0], indirect=True)
-    """
+def test_aac_read_wav_stereo_48k_roundtrip(mk_random_stereo_wav: Path) -> None:
-    Contract test for aac_read_wav_stereo_48k():
+    x, fs = aac_read_wav_stereo_48k(mk_random_stereo_wav)
-    - Reads stereo WAV
-    - Returns float64 array with shape (N,2)
-    - Returns fs = 48000
-    """
-    x, fs = aac_read_wav_stereo_48k(tmp_stereo_wav)
 
     assert int(fs) == 48000
     assert isinstance(x, np.ndarray)
@@ -67,10 +93,6 @@ def test_aac_read_wav_stereo_48k_roundtrip(tmp_stereo_wav: Path) -> None:
 
 
 def test_aac_remove_padding_removes_hop_from_both_ends() -> None:
-    """
-    Contract test for aac_remove_padding():
-    - Removes 'hop' samples from start and end.
-    """
     hop = 1024
     n = 10000
 
@@ -82,9 +104,6 @@ def test_aac_remove_padding_removes_hop_from_both_ends() -> None:
 
 
 def test_aac_remove_padding_errors_on_too_short_input() -> None:
-    """
-    aac_remove_padding must raise if y_pad is shorter than 2*hop.
-    """
     hop = 1024
     y_pad: StereoSignal = np.zeros((2 * hop - 1, 2), dtype=np.float64)
 
@@ -95,12 +114,10 @@ def test_aac_remove_padding_errors_on_too_short_input() -> None:
 # -----------------------------------------------------------------------------
 # Level 1 tests
 # -----------------------------------------------------------------------------
-def test_aac_coder_seq_schema_and_shapes(tmp_stereo_wav: Path) -> None:
+
-    """
+@pytest.mark.parametrize("mk_random_stereo_wav", [0.5], indirect=True)
-    Module-level contract test:
+def test_aac_coder_seq_schema_and_shapes(mk_random_stereo_wav: Path) -> None:
-    Ensure aac_seq_1 follows the expected schema and per-frame shapes.
+    aac_seq: AACSeq1 = aac_coder_1(mk_random_stereo_wav)
-    """
-    aac_seq: AACSeq1 = aac_coder_1(tmp_stereo_wav)
 
     assert isinstance(aac_seq, list)
     assert len(aac_seq) > 0
@@ -108,7 +125,6 @@ def test_aac_coder_seq_schema_and_shapes(tmp_stereo_wav: Path) -> None:
     for fr in aac_seq:
         assert isinstance(fr, dict)
 
-        # Required keys
         assert "frame_type" in fr
         assert "win_type" in fr
         assert "chl" in fr
@@ -136,41 +152,32 @@ def test_aac_coder_seq_schema_and_shapes(tmp_stereo_wav: Path) -> None:
             assert chr_f.shape == (1024, 1)
 
 
-def test_end_to_end_aac_coder_decoder_high_snr(tmp_stereo_wav: Path, tmp_path: Path) -> None:
+@pytest.mark.parametrize("mk_random_stereo_wav", [0.5], indirect=True)
-    """
+def test_end_to_end_aac_coder_decoder_high_snr(mk_random_stereo_wav: Path, tmp_path: Path) -> None:
-    End-to-end test:
+    x_ref, fs = sf.read(str(mk_random_stereo_wav), always_2d=True)
-    Encode + decode and check SNR is very high (numerical-noise only).
-
-    The threshold is intentionally loose to avoid fragility across platforms/BLAS.
-    """
-    x_ref, fs = sf.read(str(tmp_stereo_wav), always_2d=True)
     x_ref = np.asarray(x_ref, dtype=np.float64)
     assert int(fs) == 48000
 
     out_wav = tmp_path / "out.wav"
 
-    aac_seq = aac_coder_1(tmp_stereo_wav)
+    aac_seq = aac_coder_1(mk_random_stereo_wav)
     x_hat: StereoSignal = aac_decoder_1(aac_seq, out_wav)
 
-    # Basic sanity: output file exists and is readable
     assert out_wav.exists()
-    x_hat_file, fs_hat = sf.read(str(out_wav), always_2d=True)
+    _, fs_hat = sf.read(str(out_wav), always_2d=True)
     assert int(fs_hat) == 48000
 
-    # SNR against returned array (file should match closely, but we do not require it here).
     snr = snr_db(x_ref, x_hat)
     assert snr > 80.0
 
+
 # -----------------------------------------------------------------------------
-# Level 2 tests (new)
+# Level 2 tests
 # -----------------------------------------------------------------------------
 
-def test_aac_coder_2_seq_schema_and_shapes(tmp_stereo_wav: Path) -> None:
+@pytest.mark.parametrize("mk_random_stereo_wav", [0.5], indirect=True)
-    """
+def test_aac_coder_2_seq_schema_and_shapes(mk_random_stereo_wav: Path) -> None:
-    Module-level contract test (Level 2):
+    aac_seq: AACSeq2 = aac_coder_2(mk_random_stereo_wav)
-    Ensure aac_seq_2 follows the expected schema and per-frame shapes, including tns_coeffs.
-    """
-    aac_seq: AACSeq2 = aac_coder_2(tmp_stereo_wav)
 
     assert isinstance(aac_seq, list)
     assert len(aac_seq) > 0
@@ -194,27 +201,20 @@ def test_aac_coder_2_seq_schema_and_shapes(tmp_stereo_wav: Path) -> None:
 
             if frame_type == "ESH":
                 assert frame_f.shape == (128, 8)
-                assert coeffs.shape[0] == 4
+                assert coeffs.shape == (4, 8)
-                assert coeffs.shape[1] == 8
             else:
                 assert frame_f.shape == (1024, 1)
                 assert coeffs.shape == (4, 1)
 
 
-def test_end_to_end_level_2_high_snr(tmp_stereo_wav: Path, tmp_path: Path) -> None:
+@pytest.mark.parametrize("mk_random_stereo_wav", [0.5], indirect=True)
-    """
+def test_end_to_end_level_2_high_snr(mk_random_stereo_wav: Path, tmp_path: Path) -> None:
-    End-to-end test (Level 2):
+    x_ref, fs = sf.read(str(mk_random_stereo_wav), always_2d=True)
-    Encode + decode and check SNR remains very high.
-
-    Level 2 is still floating-point (TNS is reversible), so reconstruction
-    should remain numerical-noise only.
-    """
-    x_ref, fs = sf.read(str(tmp_stereo_wav), always_2d=True)
     x_ref = np.asarray(x_ref, dtype=np.float64)
     assert int(fs) == 48000
 
     out_wav = tmp_path / "out_l2.wav"
-    aac_seq = aac_coder_2(tmp_stereo_wav)
+    aac_seq = aac_coder_2(mk_random_stereo_wav)
     x_hat: StereoSignal = aac_decoder_2(aac_seq, out_wav)
 
     assert out_wav.exists()
@@ -222,30 +222,14 @@ def test_end_to_end_level_2_high_snr(tmp_stereo_wav: Path, tmp_path: Path) -> No
     assert int(fs_hat) == 48000
 
     snr = snr_db(x_ref, x_hat)
-    assert snr > 80
+    assert snr > 80.0
 
 
 # -----------------------------------------------------------------------------
 # Level 3 tests (Quantizer + Huffman)
 # -----------------------------------------------------------------------------
 
-@pytest.fixture(scope="module")
-def wav_in_path() -> Path:
-    """
-    Input WAV used for end-to-end tests.
-
-    This should point to the provided test audio under material/.
-    Adjust this path if your project layout differs.
-    """
-    # Typical layout in this project:
-    # source/material/LicorDeCalandraca.wav
-    return Path(__file__).resolve().parents[2] / "material" / "LicorDeCalandraca.wav"
-
-
 def _assert_level3_frame_schema(frame: AACSeq3Frame) -> None:
-    """
-    Validate Level-3 per-frame schema (keys + basic types only).
-    """
     assert "frame_type" in frame
     assert "win_type" in frame
     assert "chl" in frame
@@ -264,37 +248,18 @@ def _assert_level3_frame_schema(frame: AACSeq3Frame) -> None:
         assert isinstance(ch["stream"], str)
         assert isinstance(ch["codebook"], int)
 
-        # Arrays: only check they are numpy arrays with expected dtype categories.
         assert isinstance(ch["tns_coeffs"], np.ndarray)
         assert isinstance(ch["T"], np.ndarray)
-
-        # Global gain: long frames may be scalar float, ESH may be ndarray
         assert np.isscalar(ch["G"]) or isinstance(ch["G"], np.ndarray)
 
 
-def test_aac_coder_3_seq_schema_and_shapes(wav_in_path: Path, tmp_path: Path) -> None:
+@pytest.mark.parametrize("mk_actual_stereo_wav", [0.5], indirect=True)
+def test_aac_coder_3_seq_schema_and_shapes(mk_actual_stereo_wav: Path) -> None:
     """
-    Contract test:
+    Uses a short WAV excerpt produced by mk_actual_stereo_wav.
-    - aac_coder_3 returns AACSeq3
+    0.11s is enough for a few frames at 48 kHz.
-    - Per-frame keys exist and types are consistent
-    - Basic shape expectations hold for ESH vs non-ESH cases
-
-    Note:
-    This test uses a short excerpt (a few frames) to keep runtime bounded.
     """
-    # Use only a few frames to avoid long runtimes in the quantizer loop.
+    aac_seq_3: AACSeq3 = aac_coder_3(mk_actual_stereo_wav)
-    hop = 1024
-    win = 2048
-    n_frames = 4
-    n_samples = win + (n_frames - 1) * hop
-
-    x, fs = aac_read_wav_stereo_48k(wav_in_path)
-    x_short = x[:n_samples, :]
-
-    short_wav = tmp_path / "input_short.wav"
-    sf.write(str(short_wav), x_short, fs)
-
-    aac_seq_3: AACSeq3 = aac_coder_3(short_wav)
 
     assert isinstance(aac_seq_3, list)
     assert len(aac_seq_3) > 0
@@ -329,46 +294,21 @@ def test_aac_coder_3_seq_schema_and_shapes(wav_in_path: Path, tmp_path: Path) ->
             else:
                 assert np.isscalar(G)
 
-            assert isinstance(ch["sfc"], str)
-            assert isinstance(ch["stream"], str)
 
-
+@pytest.mark.parametrize("mk_actual_stereo_wav", [0.5], indirect=True)
-
+def test_end_to_end_level_3_high_snr(mk_actual_stereo_wav: Path, tmp_path: Path) -> None:
-def test_end_to_end_level_3_high_snr(wav_in_path: Path, tmp_path: Path) -> None:
     """
-    End-to-end test for Level 3 (Quantizer + Huffman):
+    End-to-end Level 3 using a small WAV excerpt produced by mk_actual_stereo_wav.
-
-    coder_3 -> decoder_3 should reconstruct a waveform with acceptable SNR.
-
-    Notes
-    -----
-    - Level 3 includes quantization, so SNR is expected to be lower than Level 1/2.
-    - We intentionally use a short excerpt (few frames) to keep runtime bounded,
-      since the reference quantizer implementation is computationally expensive.
     """
-    # Use only a few frames to avoid long runtimes.
+    x_ref, fs = aac_read_wav_stereo_48k(mk_actual_stereo_wav)
-    hop = 1024
+    assert int(fs) == 48000
-    win = 2048
-    n_frames = 4
-    n_samples = win + (n_frames - 1) * hop
-
-    x_ref, fs = aac_read_wav_stereo_48k(wav_in_path)
-    x_short = x_ref[:n_samples, :]
-
-    short_wav = tmp_path / "input_short_l3.wav"
-    sf.write(str(short_wav), x_short, fs)
 
     out_wav = tmp_path / "decoded_level3.wav"
 
-    aac_seq_3: AACSeq3 = aac_coder_3(short_wav)
+    aac_seq_3: AACSeq3 = aac_coder_3(mk_actual_stereo_wav)
     y_hat: StereoSignal = aac_decoder_3(aac_seq_3, out_wav)
 
-    # Align lengths defensively (padding removal may differ by a few samples)
+    n = min(x_ref.shape[0], y_hat.shape[0])
-    n = min(x_short.shape[0], y_hat.shape[0])
+    s = snr_db(x_ref[:n, :], y_hat[:n, :])
-    x2 = x_short[:n, :]
+    print(f"SNR={s}")
-    y2 = y_hat[:n, :]
+    assert s > 2.0
-
-    s = snr_db(x2, y2)
-
-    # Conservative threshold: Level 3 is lossy by design.
-    assert s > 10.0

source/level_1/core/aac_coder.py

@@ -214,7 +214,10 @@ def aac_pack_frame_f_to_seq_channels(frame_type: FrameType, frame_f: FrameF) ->
 # Level 1 encoder
 # -----------------------------------------------------------------------------
 
-def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
+def aac_coder_1(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq1:
     """
     Level-1 AAC encoder.
 
@@ -231,6 +234,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     filename_in : Union[str, Path]
         Input WAV filename.
         Assumption: stereo audio, sampling rate 48 kHz.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -257,8 +262,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     aac_seq: AACSeq1 = []
     prev_frame_type: FrameType = "OLS"
 
-    win_type: WinType = WIN_TYPE
+    if verbose:
-
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -275,23 +280,31 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
             next_t = np.vstack([next_t, tail])
 
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
-        frame_f = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f)
 
         aac_seq.append({
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {"frame_F": chl_f},
             "chr": {"frame_F": chr_f},
         })
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
 
-def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
+def aac_coder_2(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq2:
     """
     Level-2 AAC encoder (Level 1 + TNS).
 
@@ -299,6 +312,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     ----------
     filename_in : Union[str, Path]
         Input WAV filename (stereo, 48 kHz).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -330,6 +345,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     aac_seq: AACSeq2 = []
     prev_frame_type: FrameType = "OLS"
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -347,16 +364,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
         # Level 1 analysis (packed stereo container)
         frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
-        # Unpack to per-channel (as you already do in Level 1)
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
-        if frame_type == "ESH":
-            chl_f = np.empty((128, 8), dtype=np.float64)
-            chr_f = np.empty((128, 8), dtype=np.float64)
-            for j in range(8):
-                chl_f[:, j] = frame_f_stereo[:, 2 * j + 0]
-                chr_f[:, j] = frame_f_stereo[:, 2 * j + 1]
-        else:
-            chl_f = frame_f_stereo[:, 0:1].astype(np.float64, copy=False)
-            chr_f = frame_f_stereo[:, 1:2].astype(np.float64, copy=False)
 
         # Level 2: apply TNS per channel
         chl_f_tns, chl_tns_coeffs = aac_tns(chl_f, frame_type)
@@ -370,8 +378,12 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
                 "chr": {"frame_F": chr_f_tns, "tns_coeffs": chr_tns_coeffs},
             }
         )
-
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
@@ -379,6 +391,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
 def aac_coder_3(
     filename_in: Union[str, Path],
     filename_aac_coded: Union[str, Path] | None = None,
+    verbose: bool = False,
 ) -> AACSeq3:
     """
     Level-3 AAC encoder (Level 2 + Psycho + Quantizer + Huffman).
@@ -389,6 +402,8 @@ def aac_coder_3(
         Input WAV filename (stereo, 48 kHz).
     filename_aac_coded : Union[str, Path] | None
         Optional .mat filename to store aac_seq_3 (assignment convenience).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -416,15 +431,14 @@ def aac_coder_3(
     aac_seq: AACSeq3 = []
     prev_frame_type: FrameType = "OLS"
 
-    # Pin win_type to the WinType literal for type checkers.
-    win_type: WinType = WIN_TYPE
-
     # Psycho model needs per-channel history (prev1, prev2) of 2048-sample frames.
     prev1_L = np.zeros((2048,), dtype=np.float64)
     prev2_L = np.zeros((2048,), dtype=np.float64)
     prev1_R = np.zeros((2048,), dtype=np.float64)
     prev2_R = np.zeros((2048,), dtype=np.float64)
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -440,7 +454,7 @@ def aac_coder_3(
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
 
         # Analysis filterbank (stereo packed)
-        frame_f_stereo = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
 
         # TNS per channel
@@ -474,32 +488,35 @@ def aac_coder_3(
         # Codebook 11:
         # maxAbsCodeVal = 16 is RESERVED for ESCAPE.
         # We must stay strictly within [-15, +15] to avoid escape decoding.
-        sf_cb = 11
+        # sf_cb = 11
-        sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        # sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        #
+        # sfc_L_dpcm = np.clip(
+        #     sfc_L_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
+        #
+        # sfc_R_dpcm = np.clip(
+        #     sfc_R_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
 
-        sfc_L_dpcm = np.clip(
+        sfc_L_stream, cb_sfc_L = aac_encode_huff(
-            sfc_L_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_R_dpcm = np.clip(
-            sfc_R_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_L_stream, _ = aac_encode_huff(
             sfc_L_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
-        sfc_R_stream, _ = aac_encode_huff(
+        sfc_R_stream, cb_sfc_R = aac_encode_huff(
             sfc_R_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
 
+        if cb_sfc_L != 11 or cb_sfc_R != 11:
+            print (f"frame: {i}: cb_sfc_l={cb_sfc_L}, cb_sfc_r={cb_sfc_R}")
+
         mdct_L_stream, cb_L = aac_encode_huff(
             np.asarray(S_L, dtype=np.int64).reshape(-1),
             huff_LUT_list,
@@ -512,7 +529,7 @@ def aac_coder_3(
         # Typed dict construction helps static analyzers validate the schema.
         frame_out: AACSeq3Frame = {
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {
                 "tns_coeffs": np.asarray(chl_tns_coeffs, dtype=np.float64),
                 "T": np.asarray(T_L, dtype=np.float64),
@@ -539,6 +556,11 @@ def aac_coder_3(
         prev1_R = frame_R
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     # Optional: store to .mat for the assignment wrapper
     if filename_aac_coded is not None:
@@ -548,6 +570,5 @@ def aac_coder_3(
             {"aac_seq_3": np.array(aac_seq, dtype=object)},
             do_compression=True,
         )
-
     return aac_seq
 

source/level_1/core/aac_decoder.py

@@ -118,7 +118,11 @@ def aac_remove_padding(y_pad: StereoSignal, hop: int = 1024) -> StereoSignal:
 # Level 1 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_1(
+    aac_seq_1: AACSeq1,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-1 AAC decoder (inverse of aac_coder_1()).
 
@@ -134,6 +138,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_1().
     filename_out : Union[str, Path]
         Output WAV filename. Assumption: 48 kHz, stereo.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -152,6 +158,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad: StereoSignal = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_1):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -164,12 +172,15 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start:start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y: StereoSignal = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     # Level 1 assumption: 48 kHz output.
     sf.write(str(filename_out), y, 48000)
-
     return y
 
 
@@ -177,7 +188,11 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 # Level 2 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_2(
+    aac_seq_2: AACSeq2,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-2 AAC decoder (inverse of aac_coder_2).
 
@@ -195,6 +210,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_2().
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -213,6 +230,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_2):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -260,15 +279,23 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y
 
 
 
-def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_3(
+    aac_seq_3: AACSeq3,
+    filename_out: Union[str, Path],
+    verbose: bool = False,
+) -> StereoSignal:
     """
     Level-3 AAC decoder (inverse of aac_coder_3).
 
@@ -286,6 +313,8 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_3.
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -307,6 +336,9 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
+
     for i, fr in enumerate(aac_seq_3):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -401,7 +433,12 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
 
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y

source/level_1/level_1.py

@@ -20,6 +20,7 @@
 from __future__ import annotations
 
 from pathlib import Path
+from tabnanny import verbose
 from typing import Union
 
 import soundfile as sf
@@ -52,7 +53,7 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     AACSeq1
         List of encoded frames (Level 1 schema).
     """
-    return core_aac_coder_1(filename_in)
+    return core_aac_coder_1(filename_in, verbose=True)
 
 
 def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoSignal:
@@ -73,7 +74,7 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
     StereoSignal
         Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
     """
-    return core_aac_decoder_1(aac_seq_1, filename_out)
+    return core_aac_decoder_1(aac_seq_1, filename_out, verbose=True)
 
 
 # -----------------------------------------------------------------------------

source/level_2/core/aac_coder.py

@@ -214,7 +214,10 @@ def aac_pack_frame_f_to_seq_channels(frame_type: FrameType, frame_f: FrameF) ->
 # Level 1 encoder
 # -----------------------------------------------------------------------------
 
-def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
+def aac_coder_1(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq1:
     """
     Level-1 AAC encoder.
 
@@ -231,6 +234,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     filename_in : Union[str, Path]
         Input WAV filename.
         Assumption: stereo audio, sampling rate 48 kHz.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -257,8 +262,8 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
     aac_seq: AACSeq1 = []
     prev_frame_type: FrameType = "OLS"
 
-    win_type: WinType = WIN_TYPE
+    if verbose:
-
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -275,23 +280,31 @@ def aac_coder_1(filename_in: Union[str, Path]) -> AACSeq1:
             next_t = np.vstack([next_t, tail])
 
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
-        frame_f = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f)
 
         aac_seq.append({
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {"frame_F": chl_f},
             "chr": {"frame_F": chr_f},
         })
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
 
-def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
+def aac_coder_2(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq2:
     """
     Level-2 AAC encoder (Level 1 + TNS).
 
@@ -299,6 +312,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     ----------
     filename_in : Union[str, Path]
         Input WAV filename (stereo, 48 kHz).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -330,6 +345,8 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     aac_seq: AACSeq2 = []
     prev_frame_type: FrameType = "OLS"
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -347,16 +364,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
         # Level 1 analysis (packed stereo container)
         frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
 
-        # Unpack to per-channel (as you already do in Level 1)
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
-        if frame_type == "ESH":
-            chl_f = np.empty((128, 8), dtype=np.float64)
-            chr_f = np.empty((128, 8), dtype=np.float64)
-            for j in range(8):
-                chl_f[:, j] = frame_f_stereo[:, 2 * j + 0]
-                chr_f[:, j] = frame_f_stereo[:, 2 * j + 1]
-        else:
-            chl_f = frame_f_stereo[:, 0:1].astype(np.float64, copy=False)
-            chr_f = frame_f_stereo[:, 1:2].astype(np.float64, copy=False)
 
         # Level 2: apply TNS per channel
         chl_f_tns, chl_tns_coeffs = aac_tns(chl_f, frame_type)
@@ -370,8 +378,12 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
                 "chr": {"frame_F": chr_f_tns, "tns_coeffs": chr_tns_coeffs},
             }
         )
-
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     return aac_seq
 
@@ -379,6 +391,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
 def aac_coder_3(
     filename_in: Union[str, Path],
     filename_aac_coded: Union[str, Path] | None = None,
+    verbose: bool = False,
 ) -> AACSeq3:
     """
     Level-3 AAC encoder (Level 2 + Psycho + Quantizer + Huffman).
@@ -389,6 +402,8 @@ def aac_coder_3(
         Input WAV filename (stereo, 48 kHz).
     filename_aac_coded : Union[str, Path] | None
         Optional .mat filename to store aac_seq_3 (assignment convenience).
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -416,15 +431,14 @@ def aac_coder_3(
     aac_seq: AACSeq3 = []
     prev_frame_type: FrameType = "OLS"
 
-    # Pin win_type to the WinType literal for type checkers.
-    win_type: WinType = WIN_TYPE
-
     # Psycho model needs per-channel history (prev1, prev2) of 2048-sample frames.
     prev1_L = np.zeros((2048,), dtype=np.float64)
     prev2_L = np.zeros((2048,), dtype=np.float64)
     prev1_R = np.zeros((2048,), dtype=np.float64)
     prev2_R = np.zeros((2048,), dtype=np.float64)
 
+    if verbose:
+        print("Encoding ", end="", flush=True)
     for i in range(K):
         start = i * hop
 
@@ -440,7 +454,7 @@ def aac_coder_3(
         frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
 
         # Analysis filterbank (stereo packed)
-        frame_f_stereo = aac_filter_bank(frame_t, frame_type, win_type)
+        frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
         chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
 
         # TNS per channel
@@ -474,32 +488,35 @@ def aac_coder_3(
         # Codebook 11:
         # maxAbsCodeVal = 16 is RESERVED for ESCAPE.
         # We must stay strictly within [-15, +15] to avoid escape decoding.
-        sf_cb = 11
+        # sf_cb = 11
-        sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        # sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        #
+        # sfc_L_dpcm = np.clip(
+        #     sfc_L_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
+        #
+        # sfc_R_dpcm = np.clip(
+        #     sfc_R_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
 
-        sfc_L_dpcm = np.clip(
+        sfc_L_stream, cb_sfc_L = aac_encode_huff(
-            sfc_L_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_R_dpcm = np.clip(
-            sfc_R_dpcm,
-            -sf_max_abs,
-            sf_max_abs,
-        ).astype(np.int64, copy=False)
-
-        sfc_L_stream, _ = aac_encode_huff(
             sfc_L_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
-        sfc_R_stream, _ = aac_encode_huff(
+        sfc_R_stream, cb_sfc_R = aac_encode_huff(
             sfc_R_dpcm.reshape(-1, order="F"),
             huff_LUT_list,
-            force_codebook=sf_cb,
+            # force_codebook=11,
         )
 
+        if cb_sfc_L != 11 or cb_sfc_R != 11:
+            print (f"frame: {i}: cb_sfc_l={cb_sfc_L}, cb_sfc_r={cb_sfc_R}")
+
         mdct_L_stream, cb_L = aac_encode_huff(
             np.asarray(S_L, dtype=np.int64).reshape(-1),
             huff_LUT_list,
@@ -512,7 +529,7 @@ def aac_coder_3(
         # Typed dict construction helps static analyzers validate the schema.
         frame_out: AACSeq3Frame = {
             "frame_type": frame_type,
-            "win_type": win_type,
+            "win_type": WIN_TYPE,
             "chl": {
                 "tns_coeffs": np.asarray(chl_tns_coeffs, dtype=np.float64),
                 "T": np.asarray(T_L, dtype=np.float64),
@@ -539,6 +556,11 @@ def aac_coder_3(
         prev1_R = frame_R
 
         prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
 
     # Optional: store to .mat for the assignment wrapper
     if filename_aac_coded is not None:
@@ -548,6 +570,5 @@ def aac_coder_3(
             {"aac_seq_3": np.array(aac_seq, dtype=object)},
             do_compression=True,
         )
-
     return aac_seq
 

source/level_2/core/aac_decoder.py

@@ -118,7 +118,11 @@ def aac_remove_padding(y_pad: StereoSignal, hop: int = 1024) -> StereoSignal:
 # Level 1 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_1(
+    aac_seq_1: AACSeq1,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-1 AAC decoder (inverse of aac_coder_1()).
 
@@ -134,6 +138,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_1().
     filename_out : Union[str, Path]
         Output WAV filename. Assumption: 48 kHz, stereo.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -152,6 +158,8 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad: StereoSignal = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_1):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -164,12 +172,15 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start:start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y: StereoSignal = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     # Level 1 assumption: 48 kHz output.
     sf.write(str(filename_out), y, 48000)
-
     return y
 
 
@@ -177,7 +188,11 @@ def aac_decoder_1(aac_seq_1: AACSeq1, filename_out: Union[str, Path]) -> StereoS
 # Level 2 decoder
 # -----------------------------------------------------------------------------
 
-def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_2(
+    aac_seq_2: AACSeq2,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
     """
     Level-2 AAC decoder (inverse of aac_coder_2).
 
@@ -195,6 +210,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_2().
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -213,6 +230,8 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
     for i, fr in enumerate(aac_seq_2):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -260,15 +279,23 @@ def aac_decoder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
 
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
 
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y
 
 
 
-def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoSignal:
+def aac_decoder_3(
+    aac_seq_3: AACSeq3,
+    filename_out: Union[str, Path],
+    verbose: bool = False,
+) -> StereoSignal:
     """
     Level-3 AAC decoder (inverse of aac_coder_3).
 
@@ -286,6 +313,8 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         Encoded sequence as produced by aac_coder_3.
     filename_out : Union[str, Path]
         Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
 
     Returns
     -------
@@ -307,6 +336,9 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
     n_pad = (K - 1) * hop + win
     y_pad = np.zeros((n_pad, 2), dtype=np.float64)
 
+    if verbose:
+        print("Decoding ", end="", flush=True)
+
     for i, fr in enumerate(aac_seq_3):
         frame_type: FrameType = fr["frame_type"]
         win_type: WinType = fr["win_type"]
@@ -401,7 +433,12 @@ def aac_decoder_3(aac_seq_3: AACSeq3, filename_out: Union[str, Path]) -> StereoS
         start = i * hop
         y_pad[start : start + win, :] += frame_t_hat
 
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
     y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
 
     sf.write(str(filename_out), y, 48000)
     return y

source/level_2/level_2.py

@@ -51,7 +51,7 @@ def aac_coder_2(filename_in: Union[str, Path]) -> AACSeq2:
     AACSeq2
         List of encoded frames (Level 2 schema).
     """
-    return core_aac_coder_2(filename_in)
+    return core_aac_coder_2(filename_in, verbose=True)
 
 
 def i_aac_coder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoSignal:
@@ -72,7 +72,7 @@ def i_aac_coder_2(aac_seq_2: AACSeq2, filename_out: Union[str, Path]) -> StereoS
     StereoSignal
         Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
     """
-    return core_aac_decoder_2(aac_seq_2, filename_out)
+    return core_aac_decoder_2(aac_seq_2, filename_out, verbose=True)
 
 
 # -----------------------------------------------------------------------------

source/level_3/core/aac_coder.py

@@ -0,0 +1,574 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - AAC Coder (Core)
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Level 1 AAC encoder orchestration.
+#   Keeps the same functional behavior as the original level_1 implementation:
+#   - Reads WAV via soundfile
+#   - Validates stereo and 48 kHz
+#   - Frames into 2048 samples with hop=1024 and zero padding at both ends
+#   - SSC decision uses next-frame attack detection
+#   - Filterbank analysis (MDCT)
+#   - Stores per-channel spectra in AACSeq1 schema:
+#       * ESH: (128, 8)
+#       * else: (1024, 1)
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Union
+
+import soundfile as sf
+from scipy.io import savemat
+
+from core.aac_configuration import WIN_TYPE
+from core.aac_filterbank import aac_filter_bank
+from core.aac_ssc import aac_ssc
+from core.aac_tns import aac_tns
+from core.aac_psycho import aac_psycho
+from core.aac_quantizer import aac_quantizer  # assumes your quantizer file is core/aac_quantizer.py
+from core.aac_huffman import aac_encode_huff
+from core.aac_utils import get_table, band_limits
+from material.huff_utils import load_LUT
+
+from core.aac_types import *
+
+
+
+# -----------------------------------------------------------------------------
+# Helpers for thresholds (T(b))
+# -----------------------------------------------------------------------------
+
+def _band_slices_from_table(frame_type: FrameType) -> list[tuple[int, int]]:
+    """
+    Return inclusive (lo, hi) band slices derived from TableB219.
+    """
+    table, _ = get_table(frame_type)
+    wlow, whigh, _bval, _qthr_db = band_limits(table)
+    return [(int(lo), int(hi)) for lo, hi in zip(wlow, whigh)]
+
+
+def _thresholds_from_smr(
+    frame_F_ch: FrameChannelF,
+    frame_type: FrameType,
+    SMR: FloatArray,
+) -> FloatArray:
+    """
+    Compute thresholds T(b) = P(b) / SMR(b), where P(b) is band energy.
+
+    Shapes:
+    - Long: returns (NB, 1)
+    - ESH: returns (NB, 8)
+    """
+    bands = _band_slices_from_table(frame_type)
+    NB = len(bands)
+
+    X = np.asarray(frame_F_ch, dtype=np.float64)
+    SMR = np.asarray(SMR, dtype=np.float64)
+
+    if frame_type == "ESH":
+        if X.shape != (128, 8):
+            raise ValueError("For ESH, frame_F_ch must have shape (128, 8).")
+        if SMR.shape != (NB, 8):
+            raise ValueError(f"For ESH, SMR must have shape ({NB}, 8).")
+
+        T = np.zeros((NB, 8), dtype=np.float64)
+        for j in range(8):
+            Xj = X[:, j]
+            for b, (lo, hi) in enumerate(bands):
+                P = float(np.sum(Xj[lo : hi + 1] ** 2))
+                smr = float(SMR[b, j])
+                T[b, j] = 0.0 if smr <= 1e-12 else (P / smr)
+        return T
+
+    # Long
+    if X.shape == (1024,):
+        Xv = X
+    elif X.shape == (1024, 1):
+        Xv = X[:, 0]
+    else:
+        raise ValueError("For non-ESH, frame_F_ch must be shape (1024,) or (1024, 1).")
+
+    if SMR.shape == (NB,):
+        SMRv = SMR
+    elif SMR.shape == (NB, 1):
+        SMRv = SMR[:, 0]
+    else:
+        raise ValueError(f"For non-ESH, SMR must be shape ({NB},) or ({NB}, 1).")
+
+    T = np.zeros((NB, 1), dtype=np.float64)
+    for b, (lo, hi) in enumerate(bands):
+        P = float(np.sum(Xv[lo : hi + 1] ** 2))
+        smr = float(SMRv[b])
+        T[b, 0] = 0.0 if smr <= 1e-12 else (P / smr)
+
+    return T
+
+def _normalize_global_gain(G: GlobalGain) -> float | FloatArray:
+    """
+    Normalize GlobalGain to match AACChannelFrameF3["G"] type:
+    - long: return float
+    - ESH: return float64 ndarray of shape (1, 8)
+    """
+    if np.isscalar(G):
+        return float(G)
+
+    G_arr = np.asarray(G)
+    if G_arr.size == 1:
+        return float(G_arr.reshape(-1)[0])
+
+    return np.asarray(G_arr, dtype=np.float64)
+
+# -----------------------------------------------------------------------------
+# Public helpers (useful for level_x demo wrappers)
+# -----------------------------------------------------------------------------
+
+def aac_read_wav_stereo_48k(filename_in: Union[str, Path]) -> tuple[StereoSignal, int]:
+    """
+    Read a WAV file using soundfile and validate the Level-1 assumptions.
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename.
+
+    Returns
+    -------
+    x : StereoSignal (np.ndarray)
+        Stereo samples as float64, shape (N, 2).
+    fs : int
+        Sampling rate (Hz). Must be 48000.
+
+    Raises
+    ------
+    ValueError
+        If the input is not stereo or the sampling rate is not 48 kHz.
+    """
+    filename_in = Path(filename_in)
+
+    x, fs = sf.read(str(filename_in), always_2d=True)
+    x = np.asarray(x, dtype=np.float64)
+
+    if x.shape[1] != 2:
+        raise ValueError("Input must be stereo (2 channels).")
+    if int(fs) != 48000:
+        raise ValueError("Input sampling rate must be 48 kHz.")
+
+    return x, int(fs)
+
+
+def aac_pack_frame_f_to_seq_channels(frame_type: FrameType, frame_f: FrameF) -> tuple[FrameChannelF, FrameChannelF]:
+    """
+    Convert the stereo FrameF returned by aac_filter_bank() into per-channel arrays
+    as required by the Level-1 AACSeq1 schema.
+
+    Parameters
+    ----------
+    frame_type : FrameType
+        "OLS" | "LSS" | "ESH" | "LPS".
+    frame_f : FrameF
+        Output of aac_filter_bank():
+        - If frame_type != "ESH": shape (1024, 2)
+        - If frame_type == "ESH": shape (128, 16) packed as [L0 R0 L1 R1 ... L7 R7]
+
+    Returns
+    -------
+    chl_f : FrameChannelF
+        Left channel coefficients:
+        - ESH: shape (128, 8)
+        - else: shape (1024, 1)
+    chr_f : FrameChannelF
+        Right channel coefficients:
+        - ESH: shape (128, 8)
+        - else: shape (1024, 1)
+    """
+    if frame_type == "ESH":
+        if frame_f.shape != (128, 16):
+            raise ValueError("For ESH, frame_f must have shape (128, 16).")
+
+        chl_f = np.empty((128, 8), dtype=np.float64)
+        chr_f = np.empty((128, 8), dtype=np.float64)
+        for j in range(8):
+            chl_f[:, j] = frame_f[:, 2 * j + 0]
+            chr_f[:, j] = frame_f[:, 2 * j + 1]
+        return chl_f, chr_f
+
+    # Non-ESH: store as (1024, 1) as required by the original Level-1 schema.
+    if frame_f.shape != (1024, 2):
+        raise ValueError("For OLS/LSS/LPS, frame_f must have shape (1024, 2).")
+
+    chl_f = frame_f[:, 0:1].astype(np.float64, copy=False)
+    chr_f = frame_f[:, 1:2].astype(np.float64, copy=False)
+    return chl_f, chr_f
+
+
+
+# -----------------------------------------------------------------------------
+# Level 1 encoder
+# -----------------------------------------------------------------------------
+
+def aac_coder_1(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq1:
+    """
+    Level-1 AAC encoder.
+
+    This function preserves the behavior of the original level_1 implementation:
+    - Read stereo 48 kHz WAV
+    - Pad hop samples at start and hop samples at end
+    - Frame with win=2048, hop=1024
+    - Use SSC with next-frame lookahead
+    - Apply filterbank analysis
+    - Store per-channel coefficients using AACSeq1 schema
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename.
+        Assumption: stereo audio, sampling rate 48 kHz.
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    AACSeq1
+        List of encoded frames (Level 1 schema).
+    """
+    x, _ = aac_read_wav_stereo_48k(filename_in)
+    # The assignment assumes 48 kHz
+
+    hop = 1024
+    win = 2048
+
+    # Pad at the beginning to support the first overlap region.
+    # Tail padding is kept minimal; next-frame is padded on-the-fly when needed.
+    pad_pre = np.zeros((hop, 2), dtype=np.float64)
+    pad_post = np.zeros((hop, 2), dtype=np.float64)
+    x_pad = np.vstack([pad_pre, x, pad_post])
+
+    # Number of frames such that current frame fits; next frame will be padded if needed.
+    K = int((x_pad.shape[0] - win) // hop + 1)
+    if K <= 0:
+        raise ValueError("Input too short for framing.")
+
+    aac_seq: AACSeq1 = []
+    prev_frame_type: FrameType = "OLS"
+
+    if verbose:
+        print("Encoding ", end="", flush=True)
+    for i in range(K):
+        start = i * hop
+
+        frame_t: FrameT = x_pad[start:start + win, :]
+        if frame_t.shape != (win, 2):
+            # This should not happen due to K definition, but keep it explicit.
+            raise ValueError("Internal framing error: frame_t has wrong shape.")
+
+        next_t = x_pad[start + hop:start + hop + win, :]
+
+        # Ensure next_t is always (2048, 2) by zero-padding at the tail.
+        if next_t.shape[0] < win:
+            tail = np.zeros((win - next_t.shape[0], 2), dtype=np.float64)
+            next_t = np.vstack([next_t, tail])
+
+        frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
+        frame_f = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
+
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f)
+
+        aac_seq.append({
+            "frame_type": frame_type,
+            "win_type": WIN_TYPE,
+            "chl": {"frame_F": chl_f},
+            "chr": {"frame_F": chr_f},
+        })
+
+        prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
+
+    return aac_seq
+
+
+def aac_coder_2(
+    filename_in: Union[str, Path],
+    verbose: bool = False
+) -> AACSeq2:
+    """
+    Level-2 AAC encoder (Level 1 + TNS).
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename (stereo, 48 kHz).
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    AACSeq2
+        Encoded AAC sequence (Level 2 payload schema).
+        For each frame i:
+        - "frame_type": FrameType
+        - "win_type": WinType
+        - "chl"/"chr":
+            - "frame_F": FrameChannelF (after TNS)
+            - "tns_coeffs": TnsCoeffs
+    """
+    filename_in = Path(filename_in)
+
+    x, _ = aac_read_wav_stereo_48k(filename_in)
+    # The assignment assumes 48 kHz
+
+    hop = 1024
+    win = 2048
+
+    pad_pre = np.zeros((hop, 2), dtype=np.float64)
+    pad_post = np.zeros((hop, 2), dtype=np.float64)
+    x_pad = np.vstack([pad_pre, x, pad_post])
+
+    K = int((x_pad.shape[0] - win) // hop + 1)
+    if K <= 0:
+        raise ValueError("Input too short for framing.")
+
+    aac_seq: AACSeq2 = []
+    prev_frame_type: FrameType = "OLS"
+
+    if verbose:
+        print("Encoding ", end="", flush=True)
+    for i in range(K):
+        start = i * hop
+
+        frame_t: FrameT = x_pad[start : start + win, :]
+        if frame_t.shape != (win, 2):
+            raise ValueError("Internal framing error: frame_t has wrong shape.")
+
+        next_t = x_pad[start + hop : start + hop + win, :]
+        if next_t.shape[0] < win:
+            tail = np.zeros((win - next_t.shape[0], 2), dtype=np.float64)
+            next_t = np.vstack([next_t, tail])
+
+        frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
+
+        # Level 1 analysis (packed stereo container)
+        frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
+
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
+
+        # Level 2: apply TNS per channel
+        chl_f_tns, chl_tns_coeffs = aac_tns(chl_f, frame_type)
+        chr_f_tns, chr_tns_coeffs = aac_tns(chr_f, frame_type)
+
+        aac_seq.append(
+            {
+                "frame_type": frame_type,
+                "win_type": WIN_TYPE,
+                "chl": {"frame_F": chl_f_tns, "tns_coeffs": chl_tns_coeffs},
+                "chr": {"frame_F": chr_f_tns, "tns_coeffs": chr_tns_coeffs},
+            }
+        )
+        prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
+
+    return aac_seq
+
+
+def aac_coder_3(
+    filename_in: Union[str, Path],
+    filename_aac_coded: Union[str, Path] | None = None,
+    verbose: bool = False,
+) -> AACSeq3:
+    """
+    Level-3 AAC encoder (Level 2 + Psycho + Quantizer + Huffman).
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename (stereo, 48 kHz).
+    filename_aac_coded : Union[str, Path] | None
+        Optional .mat filename to store aac_seq_3 (assignment convenience).
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    AACSeq3
+        Encoded AAC sequence (Level 3 payload schema).
+    """
+    filename_in = Path(filename_in)
+
+    x, _ = aac_read_wav_stereo_48k(filename_in)
+
+    hop = 1024
+    win = 2048
+
+    pad_pre = np.zeros((hop, 2), dtype=np.float64)
+    pad_post = np.zeros((hop, 2), dtype=np.float64)
+    x_pad = np.vstack([pad_pre, x, pad_post])
+
+    K = int((x_pad.shape[0] - win) // hop + 1)
+    if K <= 0:
+        raise ValueError("Input too short for framing.")
+
+    # Load Huffman LUTs once.
+    huff_LUT_list = load_LUT()
+
+    aac_seq: AACSeq3 = []
+    prev_frame_type: FrameType = "OLS"
+
+    # Psycho model needs per-channel history (prev1, prev2) of 2048-sample frames.
+    prev1_L = np.zeros((2048,), dtype=np.float64)
+    prev2_L = np.zeros((2048,), dtype=np.float64)
+    prev1_R = np.zeros((2048,), dtype=np.float64)
+    prev2_R = np.zeros((2048,), dtype=np.float64)
+
+    if verbose:
+        print("Encoding ", end="", flush=True)
+    for i in range(K):
+        start = i * hop
+
+        frame_t: FrameT = x_pad[start : start + win, :]
+        if frame_t.shape != (win, 2):
+            raise ValueError("Internal framing error: frame_t has wrong shape.")
+
+        next_t = x_pad[start + hop : start + hop + win, :]
+        if next_t.shape[0] < win:
+            tail = np.zeros((win - next_t.shape[0], 2), dtype=np.float64)
+            next_t = np.vstack([next_t, tail])
+
+        frame_type = aac_ssc(frame_t, next_t, prev_frame_type)
+
+        # Analysis filterbank (stereo packed)
+        frame_f_stereo = aac_filter_bank(frame_t, frame_type, WIN_TYPE)
+        chl_f, chr_f = aac_pack_frame_f_to_seq_channels(frame_type, frame_f_stereo)
+
+        # TNS per channel
+        chl_f_tns, chl_tns_coeffs = aac_tns(chl_f, frame_type)
+        chr_f_tns, chr_tns_coeffs = aac_tns(chr_f, frame_type)
+
+        # Psychoacoustic model per channel (time-domain)
+        frame_L = np.asarray(frame_t[:, 0], dtype=np.float64)
+        frame_R = np.asarray(frame_t[:, 1], dtype=np.float64)
+
+        SMR_L = aac_psycho(frame_L, frame_type, prev1_L, prev2_L)
+        SMR_R = aac_psycho(frame_R, frame_type, prev1_R, prev2_R)
+
+        # Thresholds T(b) (stored, not entropy-coded)
+        T_L = _thresholds_from_smr(chl_f_tns, frame_type, SMR_L)
+        T_R = _thresholds_from_smr(chr_f_tns, frame_type, SMR_R)
+
+        # Quantizer per channel
+        S_L, sfc_L, G_L = aac_quantizer(chl_f_tns, frame_type, SMR_L)
+        S_R, sfc_R, G_R = aac_quantizer(chr_f_tns, frame_type, SMR_R)
+
+        # Normalize G types for AACSeq3 schema (float | float64 ndarray).
+        G_Ln = _normalize_global_gain(G_L)
+        G_Rn = _normalize_global_gain(G_R)
+
+        # Huffman-code ONLY the DPCM differences for b>0.
+        # sfc[0] corresponds to alpha(0)=G and is stored separately in the frame.
+        sfc_L_dpcm = np.asarray(sfc_L, dtype=np.int64)[1:, ...]
+        sfc_R_dpcm = np.asarray(sfc_R, dtype=np.int64)[1:, ...]
+
+        # Codebook 11:
+        # maxAbsCodeVal = 16 is RESERVED for ESCAPE.
+        # We must stay strictly within [-15, +15] to avoid escape decoding.
+        # sf_cb = 11
+        # sf_max_abs = int(huff_LUT_list[sf_cb]["maxAbsCodeVal"]) - 1  # -> 15
+        #
+        # sfc_L_dpcm = np.clip(
+        #     sfc_L_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
+        #
+        # sfc_R_dpcm = np.clip(
+        #     sfc_R_dpcm,
+        #     -sf_max_abs,
+        #     sf_max_abs,
+        # ).astype(np.int64, copy=False)
+
+        sfc_L_stream, cb_sfc_L = aac_encode_huff(
+            sfc_L_dpcm.reshape(-1, order="F"),
+            huff_LUT_list,
+            # force_codebook=11,
+        )
+        sfc_R_stream, cb_sfc_R = aac_encode_huff(
+            sfc_R_dpcm.reshape(-1, order="F"),
+            huff_LUT_list,
+            # force_codebook=11,
+        )
+
+        if cb_sfc_L != 11 or cb_sfc_R != 11:
+            print (f"frame: {i}: cb_sfc_l={cb_sfc_L}, cb_sfc_r={cb_sfc_R}")
+
+        mdct_L_stream, cb_L = aac_encode_huff(
+            np.asarray(S_L, dtype=np.int64).reshape(-1),
+            huff_LUT_list,
+        )
+        mdct_R_stream, cb_R = aac_encode_huff(
+            np.asarray(S_R, dtype=np.int64).reshape(-1),
+            huff_LUT_list,
+        )
+
+        # Typed dict construction helps static analyzers validate the schema.
+        frame_out: AACSeq3Frame = {
+            "frame_type": frame_type,
+            "win_type": WIN_TYPE,
+            "chl": {
+                "tns_coeffs": np.asarray(chl_tns_coeffs, dtype=np.float64),
+                "T": np.asarray(T_L, dtype=np.float64),
+                "G": G_Ln,
+                "sfc": sfc_L_stream,
+                "stream": mdct_L_stream,
+                "codebook": int(cb_L),
+            },
+            "chr": {
+                "tns_coeffs": np.asarray(chr_tns_coeffs, dtype=np.float64),
+                "T": np.asarray(T_R, dtype=np.float64),
+                "G": G_Rn,
+                "sfc": sfc_R_stream,
+                "stream": mdct_R_stream,
+                "codebook": int(cb_R),
+            },
+        }
+        aac_seq.append(frame_out)
+
+        # Update psycho history (shift register)
+        prev2_L = prev1_L
+        prev1_L = frame_L
+        prev2_R = prev1_R
+        prev1_R = frame_R
+
+        prev_frame_type = frame_type
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    if verbose:
+        print(" done")
+
+    # Optional: store to .mat for the assignment wrapper
+    if filename_aac_coded is not None:
+        filename_aac_coded = Path(filename_aac_coded)
+        savemat(
+            str(filename_aac_coded),
+            {"aac_seq_3": np.array(aac_seq, dtype=object)},
+            do_compression=True,
+        )
+    return aac_seq
+

source/level_3/core/aac_configuration.py

@@ -0,0 +1,41 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Configuration
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   This module contains the global configurations
+#
+# ------------------------------------------------------------
+from __future__ import annotations
+
+# Imports
+from typing import Final
+
+from core.aac_types import WinType
+
+# Filterbank
+# ------------------------------------------------------------
+# Window type
+# Options: "SIN", "KBD"
+WIN_TYPE: WinType = "SIN"
+
+
+# TNS
+# ------------------------------------------------------------
+PRED_ORDER = 4
+QUANT_STEP = 0.1
+QUANT_MAX = 0.7  # 4-bit symmetric with step 0.1 -> clamp to [-0.7, +0.7]
+
+
+# -----------------------------------------------------------------------------
+# Psycho
+# -----------------------------------------------------------------------------
+
+NMT_DB: Final[float] = 6.0   # Noise Masking Tone (dB)
+TMN_DB: Final[float] = 18.0  # Tone Masking Noise (dB)

source/level_3/core/aac_decoder.py

@@ -0,0 +1,445 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Inverse AAC Coder (Core)
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   - Level 1 AAC decoder orchestration (inverse of aac_coder_1()).
+#   - Level 2 AAC decoder orchestration (inverse of aac_coder_1()).
+#
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Union
+
+import soundfile as sf
+
+from core.aac_filterbank import aac_i_filter_bank
+from core.aac_tns import aac_i_tns
+from core.aac_quantizer import aac_i_quantizer
+from core.aac_huffman import aac_decode_huff
+from core.aac_utils import get_table, band_limits
+from material.huff_utils import load_LUT
+from core.aac_types import *
+
+
+# -----------------------------------------------------------------------------
+# Helper for NB
+# -----------------------------------------------------------------------------
+def _nbands(frame_type: FrameType) -> int:
+    table, _ = get_table(frame_type)
+    wlow, _whigh, _bval, _qthr_db = band_limits(table)
+    return int(len(wlow))
+
+
+# -----------------------------------------------------------------------------
+# Public helpers
+# -----------------------------------------------------------------------------
+
+def aac_unpack_seq_channels_to_frame_f(frame_type: FrameType, chl_f: FrameChannelF, chr_f: FrameChannelF) -> FrameF:
+    """
+    Re-pack per-channel spectra from the Level-1 AACSeq1 schema into the stereo
+    FrameF container expected by aac_i_filter_bank().
+
+    Parameters
+    ----------
+    frame_type : FrameType
+        "OLS" | "LSS" | "ESH" | "LPS".
+    chl_f : FrameChannelF
+        Left channel coefficients:
+        - ESH: (128, 8)
+        - else: (1024, 1)
+    chr_f : FrameChannelF
+        Right channel coefficients:
+        - ESH: (128, 8)
+        - else: (1024, 1)
+
+    Returns
+    -------
+    FrameF
+        Stereo coefficients:
+        - ESH: (128, 16) packed as [L0 R0 L1 R1 ... L7 R7]
+        - else: (1024, 2)
+    """
+    if frame_type == "ESH":
+        if chl_f.shape != (128, 8) or chr_f.shape != (128, 8):
+            raise ValueError("ESH channel frame_F must have shape (128, 8).")
+
+        frame_f = np.empty((128, 16), dtype=np.float64)
+        for j in range(8):
+            frame_f[:, 2 * j + 0] = chl_f[:, j]
+            frame_f[:, 2 * j + 1] = chr_f[:, j]
+        return frame_f
+
+    # Non-ESH: expected (1024, 1) per channel in Level-1 schema.
+    if chl_f.shape != (1024, 1) or chr_f.shape != (1024, 1):
+        raise ValueError("Non-ESH channel frame_F must have shape (1024, 1).")
+
+    frame_f = np.empty((1024, 2), dtype=np.float64)
+    frame_f[:, 0] = chl_f[:, 0]
+    frame_f[:, 1] = chr_f[:, 0]
+    return frame_f
+
+
+def aac_remove_padding(y_pad: StereoSignal, hop: int = 1024) -> StereoSignal:
+    """
+    Remove the boundary padding that the Level-1 encoder adds:
+    hop samples at start and hop samples at end.
+
+    Parameters
+    ----------
+    y_pad : StereoSignal (np.ndarray)
+        Reconstructed padded stream, shape (N_pad, 2).
+    hop : int
+        Hop size in samples (default 1024).
+
+    Returns
+    -------
+    StereoSignal (np.ndarray)
+        Unpadded reconstructed stream, shape (N_pad - 2*hop, 2).
+
+    Raises
+    ------
+    ValueError
+        If y_pad is too short to unpad.
+    """
+    if y_pad.shape[0] < 2 * hop:
+        raise ValueError("Decoded stream too short to unpad.")
+    return y_pad[hop:-hop, :]
+
+
+# -----------------------------------------------------------------------------
+# Level 1 decoder
+# -----------------------------------------------------------------------------
+
+def aac_decoder_1(
+    aac_seq_1: AACSeq1,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
+    """
+    Level-1 AAC decoder (inverse of aac_coder_1()).
+
+    This function preserves the behavior of the original level_1 implementation:
+    - Reconstruct the full padded stream by overlap-adding K synthesized frames
+    - Remove hop padding at the beginning and hop padding at the end
+    - Write the reconstructed stereo WAV file (48 kHz)
+    - Return reconstructed stereo samples as float64
+
+    Parameters
+    ----------
+    aac_seq_1 : AACSeq1
+        Encoded sequence as produced by aac_coder_1().
+    filename_out : Union[str, Path]
+        Output WAV filename. Assumption: 48 kHz, stereo.
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    StereoSignal
+        Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
+    """
+    filename_out = Path(filename_out)
+
+    hop = 1024
+    win = 2048
+    K = len(aac_seq_1)
+
+    # Output includes the encoder padding region, so we reconstruct the full padded stream.
+    # For K frames: last frame starts at (K-1)*hop and spans win,
+    # so total length = (K-1)*hop + win.
+    n_pad = (K - 1) * hop + win
+    y_pad: StereoSignal = np.zeros((n_pad, 2), dtype=np.float64)
+
+    if verbose:
+        print("Decoding ", end="", flush=True)
+    for i, fr in enumerate(aac_seq_1):
+        frame_type: FrameType = fr["frame_type"]
+        win_type: WinType = fr["win_type"]
+
+        chl_f = np.asarray(fr["chl"]["frame_F"], dtype=np.float64)
+        chr_f = np.asarray(fr["chr"]["frame_F"], dtype=np.float64)
+
+        frame_f: FrameF = aac_unpack_seq_channels_to_frame_f(frame_type, chl_f, chr_f)
+        frame_t_hat: FrameT = aac_i_filter_bank(frame_f, frame_type, win_type)  # (2048, 2)
+
+        start = i * hop
+        y_pad[start:start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    y: StereoSignal = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
+
+    # Level 1 assumption: 48 kHz output.
+    sf.write(str(filename_out), y, 48000)
+    return y
+
+
+# -----------------------------------------------------------------------------
+# Level 2 decoder
+# -----------------------------------------------------------------------------
+
+def aac_decoder_2(
+    aac_seq_2: AACSeq2,
+    filename_out: Union[str, Path],
+    verbose: bool = False
+) -> StereoSignal:
+    """
+    Level-2 AAC decoder (inverse of aac_coder_2).
+
+    Behavior matches Level 1 decoder pipeline, with additional iTNS stage:
+    - Per frame/channel: inverse TNS using stored coefficients
+    - Re-pack to stereo frame_F
+    - IMDCT + windowing
+    - Overlap-add over frames
+    - Remove Level-1 padding (hop samples start/end)
+    - Write output WAV (48 kHz)
+
+    Parameters
+    ----------
+    aac_seq_2 : AACSeq2
+        Encoded sequence as produced by aac_coder_2().
+    filename_out : Union[str, Path]
+        Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    StereoSignal
+        Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
+    """
+    filename_out = Path(filename_out)
+
+    hop = 1024
+    win = 2048
+    K = len(aac_seq_2)
+
+    if K <= 0:
+        raise ValueError("aac_seq_2 must contain at least one frame.")
+
+    n_pad = (K - 1) * hop + win
+    y_pad = np.zeros((n_pad, 2), dtype=np.float64)
+
+    if verbose:
+        print("Decoding ", end="", flush=True)
+    for i, fr in enumerate(aac_seq_2):
+        frame_type: FrameType = fr["frame_type"]
+        win_type: WinType = fr["win_type"]
+
+        chl_f_tns = np.asarray(fr["chl"]["frame_F"], dtype=np.float64)
+        chr_f_tns = np.asarray(fr["chr"]["frame_F"], dtype=np.float64)
+
+        chl_coeffs = np.asarray(fr["chl"]["tns_coeffs"], dtype=np.float64)
+        chr_coeffs = np.asarray(fr["chr"]["tns_coeffs"], dtype=np.float64)
+
+        # Inverse TNS per channel
+        chl_f = aac_i_tns(chl_f_tns, frame_type, chl_coeffs)
+        chr_f = aac_i_tns(chr_f_tns, frame_type, chr_coeffs)
+
+        # Re-pack to the stereo container expected by aac_i_filter_bank
+        if frame_type == "ESH":
+            if chl_f.shape != (128, 8) or chr_f.shape != (128, 8):
+                raise ValueError("ESH channel frame_F must have shape (128, 8).")
+
+            frame_f: FrameF = np.empty((128, 16), dtype=np.float64)
+            for j in range(8):
+                frame_f[:, 2 * j + 0] = chl_f[:, j]
+                frame_f[:, 2 * j + 1] = chr_f[:, j]
+        else:
+            # Accept either (1024,1) or (1024,) from your internal convention.
+            if chl_f.shape == (1024,):
+                chl_col = chl_f.reshape(1024, 1)
+            elif chl_f.shape == (1024, 1):
+                chl_col = chl_f
+            else:
+                raise ValueError("Non-ESH left channel frame_F must be shape (1024,) or (1024, 1).")
+
+            if chr_f.shape == (1024,):
+                chr_col = chr_f.reshape(1024, 1)
+            elif chr_f.shape == (1024, 1):
+                chr_col = chr_f
+            else:
+                raise ValueError("Non-ESH right channel frame_F must be shape (1024,) or (1024, 1).")
+
+            frame_f = np.empty((1024, 2), dtype=np.float64)
+            frame_f[:, 0] = chl_col[:, 0]
+            frame_f[:, 1] = chr_col[:, 0]
+
+        frame_t_hat: FrameT = aac_i_filter_bank(frame_f, frame_type, win_type)
+
+        start = i * hop
+        y_pad[start : start + win, :] += frame_t_hat
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
+
+    sf.write(str(filename_out), y, 48000)
+    return y
+
+
+
+def aac_decoder_3(
+    aac_seq_3: AACSeq3,
+    filename_out: Union[str, Path],
+    verbose: bool = False,
+) -> StereoSignal:
+    """
+    Level-3 AAC decoder (inverse of aac_coder_3).
+
+    Steps per frame:
+    - Huffman decode scalefactors (sfc) using codebook 11
+    - Huffman decode MDCT symbols (stream) using stored codebook
+    - iQuantizer -> MDCT coefficients after TNS
+    - iTNS using stored predictor coefficients
+    - IMDCT filterbank -> time domain
+    - Overlap-add, remove padding, write WAV
+
+    Parameters
+    ----------
+    aac_seq_3 : AACSeq3
+        Encoded sequence as produced by aac_coder_3.
+    filename_out : Union[str, Path]
+        Output WAV filename.
+    verbose : bool
+        Optional argument to print encoding status
+
+    Returns
+    -------
+    StereoSignal
+        Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
+    """
+    filename_out = Path(filename_out)
+
+    hop = 1024
+    win = 2048
+    K = len(aac_seq_3)
+
+    if K <= 0:
+        raise ValueError("aac_seq_3 must contain at least one frame.")
+
+    # Load Huffman LUTs once.
+    huff_LUT_list = load_LUT()
+
+    n_pad = (K - 1) * hop + win
+    y_pad = np.zeros((n_pad, 2), dtype=np.float64)
+
+    if verbose:
+        print("Decoding ", end="", flush=True)
+
+    for i, fr in enumerate(aac_seq_3):
+        frame_type: FrameType = fr["frame_type"]
+        win_type: WinType = fr["win_type"]
+
+        NB = _nbands(frame_type)
+        # We store G separately, so Huffman stream contains only (NB-1) DPCM differences.
+        sfc_len = (NB - 1) * (8 if frame_type == "ESH" else 1)
+
+        # -------------------------
+        # Left channel
+        # -------------------------
+        tns_L = np.asarray(fr["chl"]["tns_coeffs"], dtype=np.float64)
+        G_L = fr["chl"]["G"]
+        sfc_bits_L = fr["chl"]["sfc"]
+        mdct_bits_L = fr["chl"]["stream"]
+        cb_L = int(fr["chl"]["codebook"])
+
+        sfc_dec_L = aac_decode_huff(sfc_bits_L, 11, huff_LUT_list)[:sfc_len].astype(np.int64, copy=False)
+        if frame_type == "ESH":
+            sfc_dpcm_L = sfc_dec_L.reshape(NB - 1, 8, order="F")
+            sfc_L = np.zeros((NB, 8), dtype=np.int64)
+            Gv = np.asarray(G_L, dtype=np.float64).reshape(1, 8)
+            sfc_L[0, :] = Gv[0, :].astype(np.int64)
+            sfc_L[1:, :] = sfc_dpcm_L
+        else:
+            sfc_dpcm_L = sfc_dec_L.reshape(NB - 1, 1, order="F")
+            sfc_L = np.zeros((NB, 1), dtype=np.int64)
+            sfc_L[0, 0] = int(float(G_L))
+            sfc_L[1:, :] = sfc_dpcm_L
+
+        # MDCT symbols: codebook 0 means "all-zero section"
+        if cb_L == 0:
+            S_dec_L = np.zeros((1024,), dtype=np.int64)
+        else:
+            S_tmp_L = aac_decode_huff(mdct_bits_L, cb_L, huff_LUT_list).astype(np.int64, copy=False)
+
+            # Tuple coding may produce extra trailing symbols; caller knows the true length (1024).
+            # Also guard against short outputs by zero-padding.
+            if S_tmp_L.size < 1024:
+                S_dec_L = np.zeros((1024,), dtype=np.int64)
+                S_dec_L[: S_tmp_L.size] = S_tmp_L
+            else:
+                S_dec_L = S_tmp_L[:1024]
+
+        S_L = S_dec_L.reshape(1024, 1)
+
+        Xq_L = aac_i_quantizer(S_L, sfc_L, G_L, frame_type)
+        X_L = aac_i_tns(Xq_L, frame_type, tns_L)
+
+        # -------------------------
+        # Right channel
+        # -------------------------
+        tns_R = np.asarray(fr["chr"]["tns_coeffs"], dtype=np.float64)
+        G_R = fr["chr"]["G"]
+        sfc_bits_R = fr["chr"]["sfc"]
+        mdct_bits_R = fr["chr"]["stream"]
+        cb_R = int(fr["chr"]["codebook"])
+
+        sfc_dec_R = aac_decode_huff(sfc_bits_R, 11, huff_LUT_list)[:sfc_len].astype(np.int64, copy=False)
+        if frame_type == "ESH":
+            sfc_dpcm_R = sfc_dec_R.reshape(NB - 1, 8, order="F")
+            sfc_R = np.zeros((NB, 8), dtype=np.int64)
+            Gv = np.asarray(G_R, dtype=np.float64).reshape(1, 8)
+            sfc_R[0, :] = Gv[0, :].astype(np.int64)
+            sfc_R[1:, :] = sfc_dpcm_R
+        else:
+            sfc_dpcm_R = sfc_dec_R.reshape(NB - 1, 1, order="F")
+            sfc_R = np.zeros((NB, 1), dtype=np.int64)
+            sfc_R[0, 0] = int(float(G_R))
+            sfc_R[1:, :] = sfc_dpcm_R
+
+        if cb_R == 0:
+            S_dec_R = np.zeros((1024,), dtype=np.int64)
+        else:
+            S_tmp_R = aac_decode_huff(mdct_bits_R, cb_R, huff_LUT_list).astype(np.int64, copy=False)
+
+            if S_tmp_R.size < 1024:
+                S_dec_R = np.zeros((1024,), dtype=np.int64)
+                S_dec_R[: S_tmp_R.size] = S_tmp_R
+            else:
+                S_dec_R = S_tmp_R[:1024]
+
+        S_R = S_dec_R.reshape(1024, 1)
+
+        Xq_R = aac_i_quantizer(S_R, sfc_R, G_R, frame_type)
+        X_R = aac_i_tns(Xq_R, frame_type, tns_R)
+
+        # Re-pack to stereo container and inverse filterbank
+        frame_f = aac_unpack_seq_channels_to_frame_f(frame_type, np.asarray(X_L), np.asarray(X_R))
+        frame_t_hat: FrameT = aac_i_filter_bank(frame_f, frame_type, win_type)
+
+        start = i * hop
+        y_pad[start : start + win, :] += frame_t_hat
+
+        if verbose and (i % (K//20)) == 0:
+            print(".", end="", flush=True)
+
+    y = aac_remove_padding(y_pad, hop=hop)
+    if verbose:
+        print(" done")
+
+    sf.write(str(filename_out), y, 48000)
+    return y
+

source/level_3/core/aac_filterbank.py

@@ -0,0 +1,387 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Filterbank module
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Filterbank stage (MDCT/IMDCT), windowing, ESH packing/unpacking
+#
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from core.aac_utils import mdct, imdct
+from core.aac_types import *
+
+from scipy.signal.windows import kaiser
+
+# Private helpers for Filterbank
+# ------------------------------------------------------------
+
+def _sin_window(N: int) -> Window:
+    """
+    Build a sinusoidal (SIN) window of length N.
+
+    The AAC sinusoid window is:
+        w[n] = sin(pi/N * (n + 0.5)),  for 0 <= n < N
+
+    Parameters
+    ----------
+    N : int
+        Window length in samples.
+
+    Returns
+    -------
+    Window
+        1-D array of shape (N, ) with dtype float64.
+    """
+    n = np.arange(N, dtype=np.float64)
+    return np.sin((np.pi / N) * (n + 0.5))
+
+
+def _kbd_window(N: int, alpha: float) -> Window:
+    """
+    Build a Kaiser-Bessel-Derived (KBD) window of length N.
+
+    This follows the standard KBD construction used in AAC:
+      1) Build a Kaiser kernel of length (N/2 + 1).
+      2) Form the left half by cumulative summation, normalization, and sqrt.
+      3) Mirror the left half to form the right half (symmetric full-length window).
+
+    Notes
+    -----
+    - N must be even (AAC uses N=2048 for long and N=256 for short).
+    - The assignment specifies alpha=6 for long windows and alpha=4 for short windows.
+    - The Kaiser beta parameter is commonly taken as beta = pi * alpha for this context.
+
+    Parameters
+    ----------
+    N : int
+        Window length in samples (must be even).
+    alpha : float
+        KBD alpha parameter.
+
+    Returns
+    -------
+    Window
+        1-D array of shape (N,) with dtype float64.
+    """
+    half = N // 2
+
+    # Kaiser kernel length: half + 1 samples (0 .. half)
+    # beta = pi * alpha per the usual correspondence with the ISO definition
+    kernel = kaiser(half + 1, beta=np.pi * alpha).astype(np.float64)
+
+    csum = np.cumsum(kernel)
+    denom = csum[-1]
+
+    w_left = np.sqrt(csum[:-1] / denom)  # length half, n = 0 .. half-1
+    w_right = w_left[::-1]               # mirror for second half
+
+    return np.concatenate([w_left, w_right])
+
+
+def _long_window(win_type: WinType) -> Window:
+    """
+    Return the long AAC window (length 2048) for the selected window family.
+
+    Parameters
+    ----------
+    win_type : WinType
+        Either "SIN" or "KBD".
+
+    Returns
+    -------
+    Window
+        1-D array of shape (2048,) with dtype float64.
+    """
+    if win_type == "SIN":
+        return _sin_window(2048)
+    if win_type == "KBD":
+        # Assignment-specific alpha values
+        return _kbd_window(2048, alpha=6.0)
+    raise ValueError(f"Invalid win_type: {win_type!r}")
+
+
+def _short_window(win_type: WinType) -> Window:
+    """
+    Return the short AAC window (length 256) for the selected window family.
+
+    Parameters
+    ----------
+    win_type : WinType
+        Either "SIN" or "KBD".
+
+    Returns
+    -------
+    Window
+        1-D array of shape (256,) with dtype float64.
+    """
+    if win_type == "SIN":
+        return _sin_window(256)
+    if win_type == "KBD":
+        # Assignment-specific alpha values
+        return _kbd_window(256, alpha=4.0)
+    raise ValueError(f"Invalid win_type: {win_type!r}")
+
+
+def _window_sequence(frame_type: FrameType, win_type: WinType) -> Window:
+    """
+    Build the 2048-sample analysis/synthesis window for OLS/LSS/LPS.
+
+    In this assignment we assume a single window family is used globally
+    (no mixed KBD/SIN halves). Therefore, both the long and short windows
+    are drawn from the same family.
+
+    For frame_type:
+    - "OLS": return the long window Wl (2048).
+    - "LSS": construct [Wl_left(1024), ones(448), Ws_right(128), zeros(448)].
+    - "LPS": construct [zeros(448), Ws_left(128), ones(448), Wl_right(1024)].
+
+    Parameters
+    ----------
+    frame_type : FrameType
+        One of "OLS", "LSS", "LPS".
+    win_type : WinType
+        Either "SIN" or "KBD".
+
+    Returns
+    -------
+    Window
+        1-D array of shape (2048,) with dtype float64.
+    """
+    wL = _long_window(win_type)   # length 2048
+    wS = _short_window(win_type)  # length 256
+
+    if frame_type == "OLS":
+        return wL
+
+    if frame_type == "LSS":
+        # 0..1023: left half of long window
+        # 1024..1471: ones (448 samples)
+        # 1472..1599: right half of short window (128 samples)
+        # 1600..2047: zeros (448 samples)
+        out = np.zeros(2048, dtype=np.float64)
+        out[0:1024] = wL[0:1024]
+        out[1024:1472] = 1.0
+        out[1472:1600] = wS[128:256]
+        out[1600:2048] = 0.0
+        return out
+
+    if frame_type == "LPS":
+        # 0..447: zeros (448)
+        # 448..575: left half of short window (128)
+        # 576..1023: ones (448)
+        # 1024..2047: right half of long window (1024)
+        out = np.zeros(2048, dtype=np.float64)
+        out[0:448] = 0.0
+        out[448:576] = wS[0:128]
+        out[576:1024] = 1.0
+        out[1024:2048] = wL[1024:2048]
+        return out
+
+    raise ValueError(f"Invalid frame_type for long window sequence: {frame_type!r}")
+
+
+def _filter_bank_esh_channel(x_ch: FrameChannelT, win_type: WinType) -> FrameChannelF:
+    """
+    ESH analysis for one channel.
+
+    Parameters
+    ----------
+    x_ch : FrameChannelT
+        Time-domain channel frame (expected shape: (2048,)).
+    win_type : WinType
+        Window family ("KBD" or "SIN").
+
+    Returns
+    -------
+    FrameChannelF
+        Array of shape (128, 8). Column j contains the 128 MDCT coefficients
+        of the j-th short window.
+    """
+    wS = _short_window(win_type)  # (256,)
+    X_esh = np.empty((128, 8), dtype=np.float64)
+
+    # ESH subwindows are taken from the central region:
+    # start positions: 448 + 128*j, j = 0..7
+    for j in range(8):
+        start = 448 + 128 * j
+        seg = x_ch[start:start + 256] * wS  # (256,)
+        X_esh[:, j] = mdct(seg)           # (128,)
+
+    return X_esh
+
+
+def _unpack_esh(frame_F: FrameF) -> tuple[FrameChannelF, FrameChannelF]:
+    """
+    Unpack ESH spectrum from shape (128, 16) into per-channel arrays (128, 8).
+
+    Parameters
+    ----------
+    frame_F : FrameF
+        Packed ESH spectrum (expected shape: (128, 16)).
+
+    Returns
+    -------
+    left : FrameChannelF
+        Left channel spectrum, shape (128, 8).
+    right : FrameChannelF
+        Right channel spectrum, shape (128, 8).
+
+    Notes
+    -----
+    Inverse mapping of the packing used in aac_filter_bank():
+      packed[:, 2*j]   = left[:, j]
+      packed[:, 2*j+1] = right[:, j]
+    """
+    if frame_F.shape != (128, 16):
+        raise ValueError("ESH frame_F must have shape (128, 16).")
+
+    left = np.empty((128, 8), dtype=np.float64)
+    right = np.empty((128, 8), dtype=np.float64)
+    for j in range(8):
+        left[:, j] = frame_F[:, 2 * j + 0]
+        right[:, j] = frame_F[:, 2 * j + 1]
+    return left, right
+
+
+def _i_filter_bank_esh_channel(X_esh: FrameChannelF, win_type: WinType) -> FrameChannelT:
+    """
+    ESH synthesis for one channel.
+
+    Parameters
+    ----------
+    X_esh : FrameChannelF
+        MDCT coefficients for 8 short windows (expected shape: (128, 8)).
+    win_type : WinType
+        Window family ("KBD" or "SIN").
+
+    Returns
+    -------
+    FrameChannelT
+        Time-domain channel contribution, shape (2048,).
+        This is already overlap-added internally for the 8 short blocks and
+        ready for OLA at the caller level.
+    """
+    if X_esh.shape != (128, 8):
+        raise ValueError("X_esh must have shape (128, 8).")
+
+    wS = _short_window(win_type)  # (256,)
+    out = np.zeros(2048, dtype=np.float64)
+
+    # Each short IMDCT returns 256 samples. Place them at:
+    # start = 448 + 128*j, j=0..7 (50% overlap)
+    for j in range(8):
+        seg = imdct(X_esh[:, j]) * wS  # (256,)
+        start = 448 + 128 * j
+        out[start:start + 256] += seg
+
+    return out
+
+
+# -----------------------------------------------------------------------------
+# Public Function prototypes
+# -----------------------------------------------------------------------------
+
+def aac_filter_bank(frame_T: FrameT, frame_type: FrameType, win_type: WinType) -> FrameF:
+    """
+    Filterbank stage (MDCT analysis).
+
+    Parameters
+    ----------
+    frame_T : FrameT
+        Time-domain frame, stereo, shape (2048, 2).
+    frame_type : FrameType
+        Type of the frame under encoding ("OLS"|"LSS"|"ESH"|"LPS").
+    win_type : WinType
+        Window type ("KBD" or "SIN") used for the current frame.
+
+    Returns
+    -------
+    frame_F : FrameF
+        Frequency-domain MDCT coefficients:
+        - If frame_type in {"OLS","LSS","LPS"}: array shape (1024, 2)
+          containing MDCT coefficients for both channels.
+        - If frame_type == "ESH": contains 8 subframes, each subframe has shape (128,2),
+          placed in columns according to subframe order, i.e. overall shape (128, 16).
+    """
+    if frame_T.shape != (2048, 2):
+        raise ValueError("frame_T must have shape (2048, 2).")
+
+    xL :FrameChannelT = frame_T[:, 0].astype(np.float64, copy=False)
+    xR :FrameChannelT = frame_T[:, 1].astype(np.float64, copy=False)
+
+    if frame_type in ("OLS", "LSS", "LPS"):
+        w = _window_sequence(frame_type, win_type)  # length 2048
+        XL = mdct(xL * w)  # length 1024
+        XR = mdct(xR * w)  # length 1024
+        out = np.empty((1024, 2), dtype=np.float64)
+        out[:, 0] = XL
+        out[:, 1] = XR
+        return out
+
+    if frame_type == "ESH":
+        Xl = _filter_bank_esh_channel(xL, win_type)  # (128, 8)
+        Xr = _filter_bank_esh_channel(xR, win_type)  # (128, 8)
+
+        # Pack into (128, 16): each subframe as (128,2) placed in columns
+        out = np.empty((128, 16), dtype=np.float64)
+        for j in range(8):
+            out[:, 2 * j + 0] = Xl[:, j]
+            out[:, 2 * j + 1] = Xr[:, j]
+        return out
+
+    raise ValueError(f"Invalid frame_type: {frame_type!r}")
+
+
+def aac_i_filter_bank(frame_F: FrameF, frame_type: FrameType, win_type: WinType) -> FrameT:
+    """
+    Inverse filterbank (IMDCT synthesis).
+
+    Parameters
+    ----------
+    frame_F : FrameF
+        Frequency-domain MDCT coefficients as produced by filter_bank().
+    frame_type : FrameType
+        Frame type ("OLS"|"LSS"|"ESH"|"LPS").
+    win_type : WinType
+        Window type ("KBD" or "SIN").
+
+    Returns
+    -------
+    frame_T : FrameT
+        Reconstructed time-domain frame, stereo, shape (2048, 2).
+    """
+    if frame_type in ("OLS", "LSS", "LPS"):
+        if frame_F.shape != (1024, 2):
+            raise ValueError("For OLS/LSS/LPS, frame_F must have shape (1024, 2).")
+
+        w = _window_sequence(frame_type, win_type)
+
+        xL = imdct(frame_F[:, 0]) * w
+        xR = imdct(frame_F[:, 1]) * w
+
+        out = np.empty((2048, 2), dtype=np.float64)
+        out[:, 0] = xL
+        out[:, 1] = xR
+        return out
+
+    if frame_type == "ESH":
+        if frame_F.shape != (128, 16):
+            raise ValueError("For ESH, frame_F must have shape (128, 16).")
+
+        Xl, Xr = _unpack_esh(frame_F)
+        xL = _i_filter_bank_esh_channel(Xl, win_type)
+        xR = _i_filter_bank_esh_channel(Xr, win_type)
+
+        out = np.empty((2048, 2), dtype=np.float64)
+        out[:, 0] = xL
+        out[:, 1] = xR
+        return out
+
+    raise ValueError(f"Invalid frame_type: {frame_type!r}")

source/level_3/core/aac_huffman.py

@@ -0,0 +1,112 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Huffman wrappers (Level 3)
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Thin wrappers around the provided Huffman utilities (material/huff_utils.py)
+#   so that the API matches the assignment text.
+#
+# Exposed API (assignment):
+#   huff_sec, huff_codebook = aac_encode_huff(coeff_sec, huff_LUT_list, force_codebook)
+#   dec_coeffs = aac_decode_huff(huff_sec, huff_codebook, huff_LUT_list)
+#
+# Notes:
+#   - Huffman coding operates on tuples. Therefore, decode(encode(x)) may return
+#     extra trailing symbols due to tuple padding. The AAC decoder knows the
+#     true section length from side information (band limits) and truncates.
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from typing import Any
+import numpy as np
+
+from material.huff_utils import encode_huff, decode_huff
+
+
+def aac_encode_huff(
+    coeff_sec: np.ndarray,
+    huff_LUT_list: list[dict[str, Any]],
+    force_codebook: int | None = None,
+) -> tuple[str, int]:
+    """
+    Huffman-encode a section of coefficients (MDCT symbols or scalefactors).
+
+    Parameters
+    ----------
+    coeff_sec : np.ndarray
+        Coefficient section to be encoded. Any shape is accepted; the input
+        is flattened and treated as a 1-D sequence of int64 symbols.
+    huff_LUT_list : list[dict[str, Any]]
+        List of Huffman Look-Up Tables (LUTs) as returned by material.load_LUT().
+        Index corresponds to codebook id (typically 1..11, with 0 reserved).
+    force_codebook : int | None
+        If provided, forces the use of this Huffman codebook. In the assignment,
+        scalefactors are encoded with codebook 11. For MDCT coefficients, this
+        argument is usually omitted (auto-selection).
+
+    Returns
+    -------
+    tuple[str, int]
+        (huff_sec, huff_codebook)
+        - huff_sec: bitstream as a string of '0'/'1'
+        - huff_codebook: codebook id used by the encoder
+    """
+    coeff_sec_arr = np.asarray(coeff_sec, dtype=np.int64).reshape(-1)
+
+    if force_codebook is None:
+        # Provided utility returns (bitstream, codebook) in the auto-selection case.
+        huff_sec, huff_codebook = encode_huff(coeff_sec_arr, huff_LUT_list)
+        return str(huff_sec), int(huff_codebook)
+
+    # Provided utility returns ONLY the bitstream when force_codebook is set.
+    cb = int(force_codebook)
+    huff_sec = encode_huff(coeff_sec_arr, huff_LUT_list, force_codebook=cb)
+    return str(huff_sec), cb
+
+
+def aac_decode_huff(
+    huff_sec: str | np.ndarray,
+    huff_codebook: int,
+    huff_LUT: list[dict[str, Any]],
+) -> np.ndarray:
+    """
+    Huffman-decode a bitstream using the specified codebook.
+
+    Parameters
+    ----------
+    huff_sec : str | np.ndarray
+        Huffman bitstream. Typically a string of '0'/'1'. If an array is provided,
+        it is passed through to the provided decoder.
+    huff_codebook : int
+        Codebook id that was returned by aac_encode_huff.
+        Codebook 0 represents an all-zero section.
+    huff_LUT : list[dict[str, Any]]
+        Huffman LUT list as returned by material.load_LUT().
+
+    Returns
+    -------
+    np.ndarray
+        Decoded coefficients as a 1-D np.int64 array.
+
+        Note: Due to tuple coding, the decoded array may contain extra trailing
+        padding symbols. The caller must truncate to the known section length.
+    """
+    cb = int(huff_codebook)
+
+    if cb == 0:
+        # Codebook 0 represents an all-zero section. The decoded length is not
+        # recoverable from the bitstream alone; the caller must expand/truncate.
+        return np.zeros((0,), dtype=np.int64)
+
+    if cb < 0 or cb >= len(huff_LUT):
+        raise ValueError(f"Invalid Huffman codebook index: {cb}")
+
+    lut = huff_LUT[cb]
+    dec = decode_huff(huff_sec, lut)
+    return np.asarray(dec, dtype=np.int64).reshape(-1)

source/level_3/core/aac_psycho.py

@@ -0,0 +1,441 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Psychoacoustic Model
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Psychoacoustic model for ONE channel, based on the assignment notes (Section 2.4).
+#
+#   Public API:
+#       SMR = aac_psycho(frame_T, frame_type, frame_T_prev_1, frame_T_prev_2)
+#
+#   Output:
+#     - For long frames ("OLS", "LSS", "LPS"): SMR has shape (69,)
+#     - For short frames ("ESH"): SMR has shape (42, 8)  (one column per subframe)
+#
+#   Notes:
+#   - Uses Bark band tables from material/TableB219.mat:
+#       * B219a for long windows (69 bands, N=2048 FFT, N/2=1024 bins)
+#       * B219b for short windows (42 bands, N=256 FFT,  N/2=128 bins)
+#   - Applies a Hann window in time domain before FFT magnitude/phase extraction.
+#   - Implements:
+#       spreading function -> band spreading -> tonality index -> masking thresholds -> SMR.
+# ------------------------------------------------------------
+from __future__ import annotations
+
+import numpy as np
+
+from core.aac_utils import band_limits, get_table
+from core.aac_configuration import NMT_DB, TMN_DB
+from core.aac_types import *
+
+# -----------------------------------------------------------------------------
+# Spreading function
+# -----------------------------------------------------------------------------
+
+def _spreading_matrix(bval: BandValueArray) -> FloatArray:
+    """
+    Compute the spreading function matrix between psychoacoustic bands.
+
+    The spreading function describes how energy in one critical band masks
+    nearby bands. The formula follows the assignment pseudo-code.
+
+    Parameters
+    ----------
+    bval : BandValueArray
+        Bark value per band, shape (B,).
+
+    Returns
+    -------
+    FloatArray
+        Spreading matrix S of shape (B, B), where:
+          S[bb, b] quantifies the contribution of band bb masking band b.
+    """
+    bval = np.asarray(bval, dtype=np.float64).reshape(-1)
+    B = int(bval.shape[0])
+
+    spread = np.zeros((B, B), dtype=np.float64)
+
+    for b in range(B):
+        for bb in range(B):
+            # tmpx depends on direction (asymmetric spreading)
+            if bb >= b:
+                tmpx = 3.0 * (bval[bb] - bval[b])
+            else:
+                tmpx = 1.5 * (bval[bb] - bval[b])
+
+            # tmpz uses the "min(..., 0)" nonlinearity exactly as in the notes
+            tmpz = 8.0 * min((tmpx - 0.5) ** 2 - 2.0 * (tmpx - 0.5), 0.0)
+            tmpy = 15.811389 + 7.5 * (tmpx + 0.474) - 17.5 * np.sqrt(1.0 + (tmpx + 0.474) ** 2)
+
+            # Clamp very small values (below -100 dB) to 0 contribution
+            if tmpy < -100.0:
+                spread[bb, b] = 0.0
+            else:
+                spread[bb, b] = 10.0 ** ((tmpz + tmpy) / 10.0)
+
+    return spread
+
+
+# -----------------------------------------------------------------------------
+# Windowing + FFT feature extraction
+# -----------------------------------------------------------------------------
+
+def _hann_window(N: int) -> FloatArray:
+    """
+    Hann window as specified in the notes:
+        w[n] = 0.5 - 0.5*cos(2*pi*(n + 0.5)/N)
+
+    Parameters
+    ----------
+    N : int
+        Window length.
+
+    Returns
+    -------
+    FloatArray
+        1-D array of shape (N,), dtype float64.
+    """
+    n = np.arange(N, dtype=np.float64)
+    return 0.5 - 0.5 * np.cos((2.0 * np.pi / N) * (n + 0.5))
+
+
+def _r_phi_from_time(x: FrameChannelT, N: int) -> tuple[FloatArray, FloatArray]:
+    """
+    Compute FFT magnitude r(w) and phase phi(w) for bins w = 0 .. N/2-1.
+
+    Processing:
+    1) Apply Hann window in time domain.
+    2) Compute N-point FFT.
+    3) Keep only the positive-frequency bins [0 .. N/2-1].
+
+    Parameters
+    ----------
+    x : FrameChannelT
+        Time-domain samples, shape (N,).
+    N : int
+        FFT size (2048 or 256).
+
+    Returns
+    -------
+    r : FloatArray
+        Magnitude spectrum for bins 0 .. N/2-1, shape (N/2,).
+    phi : FloatArray
+        Phase spectrum for bins 0 .. N/2-1, shape (N/2,).
+    """
+    x = np.asarray(x, dtype=np.float64).reshape(-1)
+    if x.shape[0] != N:
+        raise ValueError(f"Expected time vector of length {N}, got {x.shape[0]}.")
+
+    w = _hann_window(N)
+    X = np.fft.fft(x * w, n=N)
+
+    Xp = X[: N // 2]
+    r = np.abs(Xp).astype(np.float64, copy=False)
+    phi = np.angle(Xp).astype(np.float64, copy=False)
+    return r, phi
+
+
+def _predictability(
+    r: FloatArray,
+    phi: FloatArray,
+    r_m1: FloatArray,
+    phi_m1: FloatArray,
+    r_m2: FloatArray,
+    phi_m2: FloatArray,
+) -> FloatArray:
+    """
+    Compute predictability c(w) per spectral bin.
+
+    The notes define:
+      r_pred(w)   = 2*r_{-1}(w)   - r_{-2}(w)
+      phi_pred(w) = 2*phi_{-1}(w) - phi_{-2}(w)
+
+      c(w) = |X(w) - X_pred(w)| / (r(w) + |r_pred(w)|)
+
+    where X(w) is represented in polar form using r(w), phi(w).
+
+    Parameters
+    ----------
+    r, phi : FloatArray
+        Current magnitude and phase, shape (N/2,).
+    r_m1, phi_m1 : FloatArray
+        Previous magnitude and phase, shape (N/2,).
+    r_m2, phi_m2 : FloatArray
+        Pre-previous magnitude and phase, shape (N/2,).
+
+    Returns
+    -------
+    FloatArray
+        Predictability c(w), shape (N/2,).
+    """
+    r_pred = 2.0 * r_m1 - r_m2
+    phi_pred = 2.0 * phi_m1 - phi_m2
+
+    num = np.sqrt(
+        (r * np.cos(phi) - r_pred * np.cos(phi_pred)) ** 2
+      + (r * np.sin(phi) - r_pred * np.sin(phi_pred)) ** 2
+    )
+    den = r + np.abs(r_pred) + 1e-12  # avoid division-by-zero without altering behavior
+    return (num / den).astype(np.float64, copy=False)
+
+
+# -----------------------------------------------------------------------------
+# Band-domain aggregation
+# -----------------------------------------------------------------------------
+
+def _band_energy_and_weighted_predictability(
+    r: FloatArray,
+    c: FloatArray,
+    wlow: BandIndexArray,
+    whigh: BandIndexArray,
+) -> tuple[FloatArray, FloatArray]:
+    """
+    Aggregate spectral bin quantities into psychoacoustic bands.
+
+    Definitions (notes):
+      e(b) = sum_{w=wlow(b)..whigh(b)} r(w)^2
+      c_num(b) = sum_{w=wlow(b)..whigh(b)} c(w) * r(w)^2
+
+    The band predictability c(b) is later computed after spreading as:
+      cb(b) = ct(b) / ecb(b)
+
+    Parameters
+    ----------
+    r : FloatArray
+        Magnitude spectrum, shape (N/2,).
+    c : FloatArray
+        Predictability per bin, shape (N/2,).
+    wlow, whigh : BandIndexArray
+        Band limits (inclusive indices), shape (B,).
+
+    Returns
+    -------
+    e_b : FloatArray
+        Band energies e(b), shape (B,).
+    c_num_b : FloatArray
+        Weighted predictability numerators c_num(b), shape (B,).
+    """
+    r2 = (r * r).astype(np.float64, copy=False)
+
+    B = int(wlow.shape[0])
+    e_b = np.zeros(B, dtype=np.float64)
+    c_num_b = np.zeros(B, dtype=np.float64)
+
+    for b in range(B):
+        a = int(wlow[b])
+        z = int(whigh[b])
+
+        seg_r2 = r2[a : z + 1]
+        e_b[b] = float(np.sum(seg_r2))
+        c_num_b[b] = float(np.sum(c[a : z + 1] * seg_r2))
+
+    return e_b, c_num_b
+
+
+def _psycho_one_window(
+    time_x: FrameChannelT,
+    prev1_x: FrameChannelT,
+    prev2_x: FrameChannelT,
+    *,
+    N: int,
+    table: BarkTable,
+) -> FloatArray:
+    """
+    Compute SMR for one FFT analysis window (N=2048 for long, N=256 for short).
+
+    This implements the pipeline described in the notes:
+      - FFT magnitude/phase
+      - predictability per bin
+      - band energies and predictability
+      - band spreading
+      - tonality index tb(b)
+      - masking threshold (noise + threshold in quiet)
+      - SMR(b) = e(b) / np(b)
+
+    Parameters
+    ----------
+    time_x : FrameChannelT
+        Current time-domain samples, shape (N,).
+    prev1_x : FrameChannelT
+        Previous time-domain samples, shape (N,).
+    prev2_x : FrameChannelT
+        Pre-previous time-domain samples, shape (N,).
+    N : int
+        FFT size.
+    table : BarkTable
+        Psychoacoustic band table (B219a or B219b).
+
+    Returns
+    -------
+    FloatArray
+        SMR per band, shape (B,).
+    """
+    wlow, whigh, bval, qthr_db = band_limits(table)
+    spread = _spreading_matrix(bval)
+
+    # FFT features for current and history windows
+    r, phi = _r_phi_from_time(time_x, N)
+    r_m1, phi_m1 = _r_phi_from_time(prev1_x, N)
+    r_m2, phi_m2 = _r_phi_from_time(prev2_x, N)
+
+    # Predictability per bin
+    c_w = _predictability(r, phi, r_m1, phi_m1, r_m2, phi_m2)
+
+    # Aggregate into psycho bands
+    e_b, c_num_b = _band_energy_and_weighted_predictability(r, c_w, wlow, whigh)
+
+    # Spread energies and predictability across bands:
+    # ecb(b) = sum_bb e(bb)      * S(bb, b)
+    # ct(b)  = sum_bb c_num(bb)  * S(bb, b)
+    ecb = spread.T @ e_b
+    ct = spread.T @ c_num_b
+
+    # Band predictability after spreading: cb(b) = ct(b) / ecb(b)
+    cb = ct / (ecb + 1e-12)
+
+    # Normalized energy term:
+    # en(b) = ecb(b) / sum_bb S(bb, b)
+    spread_colsum = np.sum(spread, axis=0)
+    en = ecb / (spread_colsum + 1e-12)
+
+    # Tonality index (clamped to [0, 1])
+    tb = -0.299 - 0.43 * np.log(np.maximum(cb, 1e-12))
+    tb = np.clip(tb, 0.0, 1.0)
+
+    # Required SNR per band (dB): interpolate between TMN and NMT
+    snr_b = tb * TMN_DB + (1.0 - tb) * NMT_DB
+    bc = 10.0 ** (-snr_b / 10.0)
+
+    # Noise masking threshold estimate (power domain)
+    nb = en * bc
+
+    # Threshold in quiet (convert from dB to power domain):
+    # qthr_power = eps * (N/2) * 10^(qthr_db/10)
+    qthr_power = np.finfo('float').eps * (N / 2.0) * (10.0 ** (qthr_db / 10.0))
+
+    # Final masking threshold per band:
+    # np(b) = max(nb(b), qthr(b))
+    npart = np.maximum(nb, qthr_power)
+
+    # Signal-to-mask ratio:
+    # SMR(b) = e(b) / np(b)
+    smr = e_b / (npart + 1e-12)
+    return smr.astype(np.float64, copy=False)
+
+
+# -----------------------------------------------------------------------------
+# ESH window slicing (match filterbank conventions)
+# -----------------------------------------------------------------------------
+
+def _esh_subframes_256(x_2048: FrameChannelT) -> list[FrameChannelT]:
+    """
+    Extract the 8 overlapping 256-sample short windows used by AAC ESH.
+
+    The project convention (matching the filterbank) is:
+      start_j = 448 + 128*j,  for j = 0..7
+      subframe_j = x[start_j : start_j + 256]
+
+    This selects the central 1152-sample region [448, 1600) and produces
+    8 windows with 50% overlap.
+
+    Parameters
+    ----------
+    x_2048 : FrameChannelT
+        Time-domain channel frame, shape (2048,).
+
+    Returns
+    -------
+    list[FrameChannelT]
+        List of 8 subframes, each of shape (256,).
+    """
+    x_2048 = np.asarray(x_2048, dtype=np.float64).reshape(-1)
+    if x_2048.shape[0] != 2048:
+        raise ValueError("ESH requires 2048-sample input frames.")
+
+    subs: list[FrameChannelT] = []
+    for j in range(8):
+        start = 448 + 128 * j
+        subs.append(x_2048[start : start + 256])
+    return subs
+
+
+# -----------------------------------------------------------------------------
+# Public API
+# -----------------------------------------------------------------------------
+
+def aac_psycho(
+    frame_T: FrameChannelT,
+    frame_type: FrameType,
+    frame_T_prev_1: FrameChannelT,
+    frame_T_prev_2: FrameChannelT,
+) -> FloatArray:
+    """
+    Psychoacoustic model for ONE channel.
+
+    Parameters
+    ----------
+    frame_T : FrameChannelT
+        Current time-domain channel frame, shape (2048,).
+        For "ESH", the 8 short windows are derived internally.
+    frame_type : FrameType
+        AAC frame type ("OLS", "LSS", "ESH", "LPS").
+    frame_T_prev_1 : FrameChannelT
+        Previous time-domain channel frame, shape (2048,).
+    frame_T_prev_2 : FrameChannelT
+        Pre-previous time-domain channel frame, shape (2048,).
+
+    Returns
+    -------
+    FloatArray
+        Signal-to-Mask Ratio (SMR), per psychoacoustic band.
+        - If frame_type == "ESH": shape (42, 8)
+        - Else: shape (69,)
+    """
+    frame_T = np.asarray(frame_T, dtype=np.float64).reshape(-1)
+    frame_T_prev_1 = np.asarray(frame_T_prev_1, dtype=np.float64).reshape(-1)
+    frame_T_prev_2 = np.asarray(frame_T_prev_2, dtype=np.float64).reshape(-1)
+
+    if frame_T.shape[0] != 2048 or frame_T_prev_1.shape[0] != 2048 or frame_T_prev_2.shape[0] != 2048:
+        raise ValueError("aac_psycho expects 2048-sample frames for current/prev1/prev2.")
+
+    table, N = get_table(frame_type)
+
+    # Long frame types: compute one SMR vector (69 bands)
+    if frame_type != "ESH":
+        return _psycho_one_window(frame_T, frame_T_prev_1, frame_T_prev_2, N=N, table=table)
+
+    # ESH: compute 8 SMR vectors (42 bands each), one per short subframe.
+    #
+    # The notes use short-window history for predictability:
+    # - For j=0: use previous frame's subframes (7, 6)
+    # - For j=1: use current subframe 0 and previous frame's subframe 7
+    # - For j>=2: use current subframes (j-1, j-2)
+    #
+    # This matches the "within-frame history" convention commonly used in
+    # simplified psycho models for ESH.
+    cur_subs = _esh_subframes_256(frame_T)
+    prev1_subs = _esh_subframes_256(frame_T_prev_1)
+
+    B = int(table.shape[0])  # expected 42
+    smr_out = np.zeros((B, 8), dtype=np.float64)
+
+    for j in range(8):
+        if j == 0:
+            x_m1 = prev1_subs[7]
+            x_m2 = prev1_subs[6]
+        elif j == 1:
+            x_m1 = cur_subs[0]
+            x_m2 = prev1_subs[7]
+        else:
+            x_m1 = cur_subs[j - 1]
+            x_m2 = cur_subs[j - 2]
+
+        smr_out[:, j] = _psycho_one_window(cur_subs[j], x_m1, x_m2, N=256, table=table)
+
+    return smr_out

source/level_3/core/aac_quantizer.py

@@ -0,0 +1,604 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Quantizer / iQuantizer (Level 3)
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Implements AAC quantizer and inverse quantizer for one channel.
+#   Based on assignment section 2.6 (Eq. 12-15).
+#
+# Notes:
+#   - Bit reservoir is not implemented (assignment simplification).
+#   - Scalefactor bands are assumed equal to psychoacoustic bands
+#     (Table B.2.1.9a / B.2.1.9b from TableB219.mat).
+# ------------------------------------------------------------
+from __future__ import annotations
+
+import numpy as np
+
+from core.aac_utils import get_table, band_limits
+from core.aac_types import *
+
+# -----------------------------------------------------------------------------
+# Constants (assignment)
+# -----------------------------------------------------------------------------
+MAGIC_NUMBER: float = 0.4054
+MQ: int = 8191
+
+EPS: float = 1e-12
+MAX_SFC_DIFF: int = 60
+
+# Safeguard: prevents infinite loops in pathological cases
+MAX_ALPHA_ITERS: int = 2000
+
+
+# -----------------------------------------------------------------------------
+# Helpers: ESH packing/unpacking (128x8 <-> 1024x1)
+# -----------------------------------------------------------------------------
+def _esh_pack_to_1024(x_128x8: FloatArray) -> FloatArray:
+    """
+    Pack ESH coefficients (128 x 8) into a single long vector (1024 x 1).
+
+    Packing order:
+        Columns are concatenated in subframe order (0..7), column-major.
+
+    Parameters
+    ----------
+    x_128x8 : FloatArray
+        ESH coefficients, shape (128, 8).
+
+    Returns
+    -------
+    FloatArray
+        Packed coefficients, shape (1024, 1).
+    """
+    x_128x8 = np.asarray(x_128x8, dtype=np.float64)
+    if x_128x8.shape != (128, 8):
+        raise ValueError("ESH pack expects shape (128, 8).")
+    return x_128x8.reshape(1024, 1, order="F")
+
+
+def _esh_unpack_from_1024(x_1024x1: FloatArray) -> FloatArray:
+    """
+    Unpack a packed ESH vector (1024 elements) back to shape (128, 8).
+
+    Parameters
+    ----------
+    x_1024x1 : FloatArray
+        Packed ESH vector, shape (1024,) or (1024, 1) after flattening.
+
+    Returns
+    -------
+    FloatArray
+        Unpacked ESH coefficients, shape (128, 8).
+    """
+    x_1024x1 = np.asarray(x_1024x1, dtype=np.float64).reshape(-1)
+    if x_1024x1.shape[0] != 1024:
+        raise ValueError("ESH unpack expects 1024 elements.")
+    return x_1024x1.reshape(128, 8, order="F")
+
+
+# -----------------------------------------------------------------------------
+# Core quantizer formulas (Eq. 12, Eq. 13)
+# -----------------------------------------------------------------------------
+def _quantize_symbol(x: FloatArray, alpha: float) -> QuantizedSymbols:
+    """
+    Quantize MDCT coefficients to integer symbols S(k).
+
+    Implements Eq. (12):
+        S(k) = sgn(X(k)) * int( (|X(k)| * 2^(-alpha/4))^(3/4) + MAGIC_NUMBER )
+
+    Parameters
+    ----------
+    x : FloatArray
+        MDCT coefficients for a contiguous set of spectral lines.
+        Shape: (N,)
+    alpha : float
+        Scalefactor gain for the corresponding scalefactor band.
+
+    Returns
+    -------
+    QuantizedSymbols
+        Quantized symbols S(k) as int64, shape (N,).
+    """
+    x = np.asarray(x, dtype=np.float64)
+
+    scale = 2.0 ** (-0.25 * float(alpha))
+    ax = np.abs(x) * scale
+
+    y = np.power(ax, 0.75, dtype=np.float64)
+
+    # "int" in the assignment corresponds to truncation.
+    q = np.floor(y + MAGIC_NUMBER).astype(np.int64)
+    return (np.sign(x).astype(np.int64) * q).astype(np.int64)
+
+
+def _dequantize_symbol(S: QuantizedSymbols, alpha: float) -> FloatArray:
+    """
+    Inverse quantizer (dequantization of symbols).
+
+    Implements Eq. (13):
+        Xhat(k) = sgn(S(k)) * |S(k)|^(4/3) * 2^(alpha/4)
+
+    Parameters
+    ----------
+    S : QuantizedSymbols
+        Quantized symbols S(k), int64, shape (N,).
+    alpha : float
+        Scalefactor gain for the corresponding scalefactor band.
+
+    Returns
+    -------
+    FloatArray
+        Reconstructed MDCT coefficients Xhat(k), float64, shape (N,).
+    """
+    S = np.asarray(S, dtype=np.int64)
+
+    scale = 2.0 ** (0.25 * float(alpha))
+    aS = np.abs(S).astype(np.float64)
+    y = np.power(aS, 4.0 / 3.0, dtype=np.float64)
+
+    return (np.sign(S).astype(np.float64) * y * scale).astype(np.float64)
+
+
+# -----------------------------------------------------------------------------
+# Alpha initialization (Eq. 14)
+# -----------------------------------------------------------------------------
+def _alpha_initial_from_frame_max(x_all: FloatArray) -> int:
+    """
+    Compute the initial scalefactor gain alpha_hat for a frame.
+
+    Implements Eq. (14):
+        alpha_hat = (16/3) * log2( max_k(|X(k)|^(3/4)) / MQ )
+
+    The same initial value is used for all bands before the per-band refinement.
+
+    Parameters
+    ----------
+    x_all : FloatArray
+        All MDCT coefficients of a frame (one channel), flattened.
+
+    Returns
+    -------
+    int
+        Initial alpha value (integer).
+    """
+    x_all = np.asarray(x_all, dtype=np.float64).reshape(-1)
+    if x_all.size == 0:
+        return 0
+
+    max_abs = float(np.max(np.abs(x_all)))
+    if max_abs <= 0.0:
+        return 0
+
+    val = (max_abs ** 0.75) / float(MQ)
+    if val <= 0.0:
+        return 0
+
+    alpha_hat = (16.0 / 3.0) * np.log2(val)
+    return int(np.floor(alpha_hat))
+
+
+# -----------------------------------------------------------------------------
+# Band utilities
+# -----------------------------------------------------------------------------
+def _band_slices(frame_type: FrameType) -> list[tuple[int, int]]:
+    """
+    Return scalefactor band ranges [wlow, whigh] (inclusive) for the given frame type.
+
+    These are derived from the psychoacoustic tables (TableB219),
+    and map directly to MDCT indices:
+      - long: 0..1023
+      - short (ESH subframe): 0..127
+
+    Parameters
+    ----------
+    frame_type : FrameType
+        Frame type ("OLS", "LSS", "ESH", "LPS").
+
+    Returns
+    -------
+    list[tuple[int, int]]
+        List of (lo, hi) inclusive index pairs for each band.
+    """
+    table, _Nfft = get_table(frame_type)
+    wlow, whigh, _bval, _qthr_db = band_limits(table)
+
+    bands: list[tuple[int, int]] = []
+    for lo, hi in zip(wlow, whigh):
+        bands.append((int(lo), int(hi)))
+    return bands
+
+
+def _band_energy(x: FloatArray, lo: int, hi: int) -> float:
+    """
+    Compute energy of a spectral segment x[lo:hi+1].
+
+    Parameters
+    ----------
+    x : FloatArray
+        MDCT coefficient vector.
+    lo, hi : int
+        Inclusive index range.
+
+    Returns
+    -------
+    float
+        Sum of squares (energy) within the band.
+    """
+    sec = x[lo : hi + 1]
+    return float(np.sum(sec * sec))
+
+
+def _threshold_T_from_SMR(
+    X: FloatArray,
+    SMR_col: FloatArray,
+    bands: list[tuple[int, int]],
+) -> FloatArray:
+    """
+    Compute psychoacoustic thresholds T(b) per band.
+
+    Uses:
+        P(b) = sum_{k in band} X(k)^2
+        T(b) = P(b) / SMR(b)
+
+    Parameters
+    ----------
+    X : FloatArray
+        MDCT coefficients for a frame (long) or one ESH subframe (short).
+    SMR_col : FloatArray
+        SMR values for this frame/subframe, shape (NB,).
+    bands : list[tuple[int, int]]
+        Band index ranges.
+
+    Returns
+    -------
+    FloatArray
+        Threshold vector T(b), shape (NB,).
+    """
+    nb = len(bands)
+    T = np.zeros((nb,), dtype=np.float64)
+
+    for b, (lo, hi) in enumerate(bands):
+        P = _band_energy(X, lo, hi)
+        smr = float(SMR_col[b])
+        if smr <= EPS:
+            T[b] = 0.0
+        else:
+            T[b] = P / smr
+
+    return T
+
+
+# -----------------------------------------------------------------------------
+# Alpha selection per band + neighbor-difference constraint
+# -----------------------------------------------------------------------------
+def _best_alpha_for_band(
+    X: FloatArray,
+    lo: int,
+    hi: int,
+    T_b: float,
+    alpha0: int,
+    alpha_min: int,
+    alpha_max: int,
+) -> int:
+    """
+    Determine the band-wise scalefactor alpha(b) by iteratively increasing alpha.
+
+    The algorithm increases alpha until the quantization error power exceeds
+    the band threshold:
+
+        P_e(b) = sum_{k in band} (X(k) - Xhat(k))^2
+        select the largest alpha such that P_e(b) <= T(b)
+
+    Parameters
+    ----------
+    X : FloatArray
+        Full MDCT vector (one frame or one subframe), shape (N,).
+    lo, hi : int
+        Inclusive MDCT index range defining the band.
+    T_b : float
+        Psychoacoustic threshold for this band.
+    alpha0 : int
+        Initial alpha value for the band.
+    alpha_min, alpha_max : int
+        Bounds for alpha, used as a safeguard.
+
+    Returns
+    -------
+    int
+        Selected integer alpha(b).
+    """
+    if T_b <= 0.0:
+        return int(alpha0)
+
+    Xsec = X[lo : hi + 1]
+
+    alpha = int(alpha0)
+    alpha = max(alpha_min, min(alpha, alpha_max))
+
+    # Evaluate at current alpha
+    Ssec = _quantize_symbol(Xsec, alpha)
+    Xhat = _dequantize_symbol(Ssec, alpha)
+    Pe = float(np.sum((Xsec - Xhat) ** 2))
+
+    if Pe > T_b:
+        return alpha
+
+    iters = 0
+    while iters < MAX_ALPHA_ITERS:
+        iters += 1
+        alpha_next = alpha + 1
+        if alpha_next > alpha_max:
+            break
+
+        Ssec = _quantize_symbol(Xsec, alpha_next)
+        Xhat = _dequantize_symbol(Ssec, alpha_next)
+        Pe_next = float(np.sum((Xsec - Xhat) ** 2))
+
+        if Pe_next > T_b:
+            break
+
+        alpha = alpha_next
+        Pe = Pe_next
+
+    return alpha
+
+
+def _enforce_max_diff(alpha: np.ndarray, max_diff: int = MAX_SFC_DIFF) -> np.ndarray:
+    """
+    Enforce neighbor constraint |alpha[b] - alpha[b-1]| <= max_diff by clamping.
+
+    Uses a forward pass and a backward pass to reduce drift.
+
+    Parameters
+    ----------
+    alpha : np.ndarray
+        Alpha vector, shape (NB,).
+    max_diff : int
+        Maximum allowed absolute difference between adjacent bands.
+
+    Returns
+    -------
+    np.ndarray
+        Clamped alpha vector, int64, shape (NB,).
+    """
+    a = np.asarray(alpha, dtype=np.int64).copy()
+    nb = a.shape[0]
+
+    for b in range(1, nb):
+        lo = int(a[b - 1] - max_diff)
+        hi = int(a[b - 1] + max_diff)
+        if a[b] < lo:
+            a[b] = lo
+        elif a[b] > hi:
+            a[b] = hi
+
+    for b in range(nb - 2, -1, -1):
+        lo = int(a[b + 1] - max_diff)
+        hi = int(a[b + 1] + max_diff)
+        if a[b] < lo:
+            a[b] = lo
+        elif a[b] > hi:
+            a[b] = hi
+
+    return a
+
+
+# -----------------------------------------------------------------------------
+# Public API
+# -----------------------------------------------------------------------------
+def aac_quantizer(
+    frame_F: FrameChannelF,
+    frame_type: FrameType,
+    SMR: FloatArray,
+) -> tuple[QuantizedSymbols, ScaleFactors, GlobalGain]:
+    """
+    AAC quantizer for one channel (Level 3).
+
+    Quantizes MDCT coefficients using band-wise scalefactors derived from SMR.
+
+    Parameters
+    ----------
+    frame_F : FrameChannelF
+        MDCT coefficients after TNS, one channel.
+        Shapes:
+        - Long frames: (1024,) or (1024, 1)
+        - ESH: (128, 8)
+    frame_type : FrameType
+        AAC frame type ("OLS", "LSS", "ESH", "LPS").
+    SMR : FloatArray
+        Signal-to-Mask Ratio per band.
+        Shapes:
+        - Long: (NB,) or (NB, 1)
+        - ESH: (NB, 8)
+
+    Returns
+    -------
+    S : QuantizedSymbols
+        Quantized symbols S(k), shape (1024, 1) for all frame types.
+    sfc : ScaleFactors
+        DPCM-coded scalefactor differences sfc(b) = alpha(b) - alpha(b-1).
+        Shapes:
+        - Long: (NB, 1)
+        - ESH: (NB, 8)
+    G : GlobalGain
+        Global gain G = alpha(0).
+        - Long: scalar float
+        - ESH: array shape (1, 8)
+    """
+    bands = _band_slices(frame_type)
+    NB = len(bands)
+
+    X = np.asarray(frame_F, dtype=np.float64)
+    SMR = np.asarray(SMR, dtype=np.float64)
+
+    if frame_type == "ESH":
+        if X.shape != (128, 8):
+            raise ValueError("For ESH, frame_F must have shape (128, 8).")
+        if SMR.shape != (NB, 8):
+            raise ValueError(f"For ESH, SMR must have shape ({NB}, 8).")
+
+        S_out: QuantizedSymbols = np.zeros((1024, 1), dtype=np.int64)
+        sfc: ScaleFactors = np.zeros((NB, 8), dtype=np.int64)
+        G_arr = np.zeros((1, 8), dtype=np.int64)
+
+        for j in range(8):
+            Xj = X[:, j].reshape(128)
+            SMRj = SMR[:, j].reshape(NB)
+
+            T = _threshold_T_from_SMR(Xj, SMRj, bands)
+
+            alpha0 = _alpha_initial_from_frame_max(Xj)
+            alpha = np.full((NB,), alpha0, dtype=np.int64)
+
+            for b, (lo, hi) in enumerate(bands):
+                alpha[b] = _best_alpha_for_band(
+                    X=Xj, lo=lo, hi=hi, T_b=float(T[b]),
+                    alpha0=int(alpha[b]),
+                    alpha_min=-4096,
+                    alpha_max=4096,
+                )
+
+            alpha = _enforce_max_diff(alpha, MAX_SFC_DIFF)
+
+            G_arr[0, j] = int(alpha[0])
+            sfc[0, j] = int(alpha[0])
+            for b in range(1, NB):
+                sfc[b, j] = int(alpha[b] - alpha[b - 1])
+
+            Sj = np.zeros((128,), dtype=np.int64)
+            for b, (lo, hi) in enumerate(bands):
+                Sj[lo : hi + 1] = _quantize_symbol(Xj[lo : hi + 1], float(alpha[b]))
+
+            # Place this subframe in the packed output (column-major subframe layout)
+            S_out[:, 0].reshape(128, 8, order="F")[:, j] = Sj
+
+        return S_out, sfc, G_arr.astype(np.float64)
+
+    # Long frames
+    if X.shape == (1024,):
+        Xv = X
+    elif X.shape == (1024, 1):
+        Xv = X[:, 0]
+    else:
+        raise ValueError("For non-ESH, frame_F must have shape (1024,) or (1024, 1).")
+
+    if SMR.shape == (NB,):
+        SMRv = SMR
+    elif SMR.shape == (NB, 1):
+        SMRv = SMR[:, 0]
+    else:
+        raise ValueError(f"For non-ESH, SMR must have shape ({NB},) or ({NB}, 1).")
+
+    T = _threshold_T_from_SMR(Xv, SMRv, bands)
+
+    alpha0 = _alpha_initial_from_frame_max(Xv)
+    alpha = np.full((NB,), alpha0, dtype=np.int64)
+
+    for b, (lo, hi) in enumerate(bands):
+        alpha[b] = _best_alpha_for_band(
+            X=Xv, lo=lo, hi=hi, T_b=float(T[b]),
+            alpha0=int(alpha[b]),
+            alpha_min=-4096,
+            alpha_max=4096,
+        )
+
+    alpha = _enforce_max_diff(alpha, MAX_SFC_DIFF)
+
+    sfc: ScaleFactors = np.zeros((NB, 1), dtype=np.int64)
+    sfc[0, 0] = int(alpha[0])
+    for b in range(1, NB):
+        sfc[b, 0] = int(alpha[b] - alpha[b - 1])
+
+    G: float = float(alpha[0])
+
+    S_vec = np.zeros((1024,), dtype=np.int64)
+    for b, (lo, hi) in enumerate(bands):
+        S_vec[lo : hi + 1] = _quantize_symbol(Xv[lo : hi + 1], float(alpha[b]))
+
+    return S_vec.reshape(1024, 1), sfc, G
+
+
+def aac_i_quantizer(
+    S: QuantizedSymbols,
+    sfc: ScaleFactors,
+    G: GlobalGain,
+    frame_type: FrameType,
+) -> FrameChannelF:
+    """
+    Inverse quantizer (iQuantizer) for one channel.
+
+    Reconstructs MDCT coefficients from quantized symbols and DPCM scalefactors.
+
+    Parameters
+    ----------
+    S : QuantizedSymbols
+        Quantized symbols, shape (1024, 1) (or any array with 1024 elements).
+    sfc : ScaleFactors
+        DPCM-coded scalefactors.
+        Shapes:
+        - Long: (NB, 1)
+        - ESH: (NB, 8)
+    G : GlobalGain
+        Global gain (not strictly required if sfc includes sfc(0)=alpha(0)).
+        Present for API compatibility with the assignment.
+    frame_type : FrameType
+        AAC frame type.
+
+    Returns
+    -------
+    FrameChannelF
+        Reconstructed MDCT coefficients:
+        - ESH: (128, 8)
+        - Long: (1024, 1)
+    """
+    bands = _band_slices(frame_type)
+    NB = len(bands)
+
+    S_flat = np.asarray(S, dtype=np.int64).reshape(-1)
+    if S_flat.shape[0] != 1024:
+        raise ValueError("S must contain 1024 symbols.")
+
+    if frame_type == "ESH":
+        sfc = np.asarray(sfc, dtype=np.int64)
+        if sfc.shape != (NB, 8):
+            raise ValueError(f"For ESH, sfc must have shape ({NB}, 8).")
+
+        S_128x8 = _esh_unpack_from_1024(S_flat)
+
+        Xrec = np.zeros((128, 8), dtype=np.float64)
+
+        for j in range(8):
+            alpha = np.zeros((NB,), dtype=np.int64)
+            alpha[0] = int(sfc[0, j])
+            for b in range(1, NB):
+                alpha[b] = int(alpha[b - 1] + sfc[b, j])
+
+            Xj = np.zeros((128,), dtype=np.float64)
+            for b, (lo, hi) in enumerate(bands):
+                Xj[lo : hi + 1] = _dequantize_symbol(S_128x8[lo : hi + 1, j].astype(np.int64), float(alpha[b]))
+
+            Xrec[:, j] = Xj
+
+        return Xrec
+
+    sfc = np.asarray(sfc, dtype=np.int64)
+    if sfc.shape != (NB, 1):
+        raise ValueError(f"For non-ESH, sfc must have shape ({NB}, 1).")
+
+    alpha = np.zeros((NB,), dtype=np.int64)
+    alpha[0] = int(sfc[0, 0])
+    for b in range(1, NB):
+        alpha[b] = int(alpha[b - 1] + sfc[b, 0])
+
+    Xrec = np.zeros((1024,), dtype=np.float64)
+    for b, (lo, hi) in enumerate(bands):
+        Xrec[lo : hi + 1] = _dequantize_symbol(S_flat[lo : hi + 1], float(alpha[b]))
+
+    return Xrec.reshape(1024, 1)

source/level_3/core/aac_ssc.py

@@ -0,0 +1,217 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Sequence Segmentation Control module
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Sequence Segmentation Control module (SSC).
+#   Selects and returns the frame type based on input parameters.
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from typing import Dict, Tuple
+from core.aac_types import FrameType, FrameT, FrameChannelT
+
+import numpy as np
+
+# -----------------------------------------------------------------------------
+# Private helpers for SSC
+# -----------------------------------------------------------------------------
+
+# See Table 1 in mm-2025-hw-v0.1.pdf
+STEREO_MERGE_TABLE: Dict[Tuple[FrameType, FrameType], FrameType] = {
+    ("OLS", "OLS"): "OLS",
+    ("OLS", "LSS"): "LSS",
+    ("OLS", "ESH"): "ESH",
+    ("OLS", "LPS"): "LPS",
+    ("LSS", "OLS"): "LSS",
+    ("LSS", "LSS"): "LSS",
+    ("LSS", "ESH"): "ESH",
+    ("LSS", "LPS"): "ESH",
+    ("ESH", "OLS"): "ESH",
+    ("ESH", "LSS"): "ESH",
+    ("ESH", "ESH"): "ESH",
+    ("ESH", "LPS"): "ESH",
+    ("LPS", "OLS"): "LPS",
+    ("LPS", "LSS"): "ESH",
+    ("LPS", "ESH"): "ESH",
+    ("LPS", "LPS"): "LPS",
+}
+
+
+def _detect_attack(next_frame_channel: FrameChannelT) -> bool:
+    """
+    Detect whether the *next* frame (single channel) implies an attack, i.e. ESH
+    according to the assignment's criterion.
+
+    Parameters
+    ----------
+    next_frame_channel : FrameChannelT
+        One channel of next_frame_T (expected shape: (2048,)).
+
+    Returns
+    -------
+    bool
+        True if an attack is detected (=> next frame predicted ESH), else False.
+
+    Notes
+    -----
+    The criterion is implemented as described in the spec:
+
+    1) Apply the high-pass filter:
+           H(z) = (1 - z^-1) / (1 - 0.5 z^-1)
+       implemented in the time domain as:
+           y[n] = x[n] - x[n-1] + 0.5*y[n-1]
+
+    2) Split y into 16 segments of length 128 and compute segment energies s[l].
+
+    3) Compute the ratio:
+           ds[l] = s[l] / s[l-1]
+
+    4) An attack exists if there exists l in {1..7} such that:
+           s[l] > 1e-3  and  ds[l] > 10
+    """
+    # Local alias; expected to be a 1-D array of length 2048.
+    x = next_frame_channel
+
+    # High-pass filter reference implementation (scalar recurrence).
+    y = np.zeros_like(x)
+    prev_x = 0.0
+    prev_y = 0.0
+    for n in range(x.shape[0]):
+        xn = float(x[n])
+        yn = (xn - prev_x) + 0.5 * prev_y
+        y[n] = yn
+        prev_x = xn
+        prev_y = yn
+
+    # Segment energies over 16 blocks of 128 samples.
+    s = np.empty(16, dtype=np.float64)
+    for l in range(16):
+        a = l * 128
+        b = (l + 1) * 128
+        seg = y[a:b]
+        s[l] = float(np.sum(seg * seg))
+
+    # ds[l] for l>=1. For l=0 not defined, keep 0.
+    ds = np.zeros(16, dtype=np.float64)
+    eps = 1e-12  # Avoid division by zero without materially changing the logic.
+    for l in range(1, 16):
+        ds[l] = s[l] / max(s[l - 1], eps)
+
+    # Spec: check l in {1..7}.
+    for l in range(1, 8):
+        if (s[l] > 1e-3) and (ds[l] > 10.0):
+            return True
+
+    return False
+
+
+def _decide_frame_type(prev_frame_type: FrameType, attack: bool) -> FrameType:
+    """
+    Decide the current frame type for a single channel based on the previous
+    frame type and whether the next frame is predicted to be ESH.
+
+    Rules (spec):
+
+    - If prev is "LSS" => current is "ESH"
+    - If prev is "LPS" => current is "OLS"
+    - If prev is "OLS" => current is "LSS" if attack else "OLS"
+    - If prev is "ESH" => current is "ESH" if attack else "LPS"
+
+    Parameters
+    ----------
+    prev_frame_type : FrameType
+        Previous frame type (one of "OLS", "LSS", "ESH", "LPS").
+    attack : bool
+        True if the next frame is predicted ESH for this channel.
+
+    Returns
+    -------
+    FrameType
+        The per-channel decision for the current frame.
+
+    """
+    if prev_frame_type == "LSS":
+        return "ESH"
+    if prev_frame_type == "LPS":
+        return "OLS"
+    if prev_frame_type == "OLS":
+        return "LSS" if attack else "OLS"
+    if prev_frame_type == "ESH":
+        return "ESH" if attack else "LPS"
+
+    raise ValueError(f"Invalid prev_frame_type: {prev_frame_type!r}")
+
+
+def _stereo_merge(ft_l: FrameType, ft_r: FrameType) -> FrameType:
+    """
+    Merge per-channel frame type decisions into one common frame type using
+    the stereo merge table from the spec.
+
+    Parameters
+    ----------
+    ft_l : FrameType
+        Frame type decision for the left channel.
+    ft_r : FrameType
+        Frame type decision for the right channel.
+
+    Returns
+    -------
+    FrameType
+        The merged common frame type.
+    """
+    try:
+        return STEREO_MERGE_TABLE[(ft_l, ft_r)]
+    except KeyError as e:
+        raise ValueError(f"Invalid stereo merge pair: {(ft_l, ft_r)}") from e
+
+
+# -----------------------------------------------------------------------------
+# Public Function prototypes
+# -----------------------------------------------------------------------------
+
+def aac_ssc(frame_T: FrameT, next_frame_T: FrameT, prev_frame_type: FrameType) -> FrameType:
+    """
+    Sequence Segmentation Control (SSC).
+
+    Select and return the frame type for the current frame (i) based on:
+    - the current time-domain frame (stereo),
+    - the next time-domain frame (stereo), used for attack detection,
+    - the previous frame type.
+
+    Parameters
+    ----------
+    frame_T : FrameT
+        Current time-domain frame i (expected shape: (2048, 2)).
+    next_frame_T : FrameT
+        Next time-domain frame (i+1), used to decide transitions to/from ESH
+        (expected shape: (2048, 2)).
+    prev_frame_type : FrameType
+        Frame type chosen for the previous frame (i-1).
+
+    Returns
+    -------
+    FrameType
+        One of: "OLS", "LSS", "ESH", "LPS".
+    """
+    if frame_T.shape != (2048, 2):
+        raise ValueError("frame_T must have shape (2048, 2).")
+    if next_frame_T.shape != (2048, 2):
+        raise ValueError("next_frame_T must have shape (2048, 2).")
+
+    # Detect attack independently per channel on the next frame.
+    attack_l = _detect_attack(next_frame_T[:, 0])
+    attack_r = _detect_attack(next_frame_T[:, 1])
+
+    # Decide per-channel type based on shared prev_frame_type.
+    ft_l = _decide_frame_type(prev_frame_type, attack_l)
+    ft_r = _decide_frame_type(prev_frame_type, attack_r)
+
+    # Stereo merge as per the spec table.
+    return _stereo_merge(ft_l, ft_r)

source/level_3/core/aac_tns.py

@@ -0,0 +1,514 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Temporal Noise Shaping (TNS)
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Temporal Noise Shaping (TNS) module (Level 2).
+#
+#   Public API:
+#     frame_F_out, tns_coeffs = aac_tns(frame_F_in, frame_type)
+#     frame_F_out = aac_i_tns(frame_F_in, frame_type, tns_coeffs)
+#
+#   Notes (per assignment):
+#   - TNS is applied per channel (not stereo).
+#   - For ESH, TNS is applied independently to each of the 8 short subframes.
+#   - Bark band tables are taken from TableB.2.1.9a (long) and TableB.2.1.9b (short)
+#     provided in TableB219.mat.
+#   - Predictor order is fixed to p = 4.
+#   - Coefficients are quantized with a 4-bit uniform symmetric quantizer, step = 0.1.
+#   - Forward TNS applies FIR: H_TNS(z) = 1 - a1 z^-1 - ... - ap z^-p
+#   - Inverse TNS applies the inverse IIR filter using the same quantized coefficients.
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Tuple
+
+from core.aac_utils import load_b219_tables
+from core.aac_configuration import PRED_ORDER, QUANT_STEP, QUANT_MAX
+from core.aac_types import *
+
+# -----------------------------------------------------------------------------
+# Private helpers
+# -----------------------------------------------------------------------------
+
+
+def _band_ranges_for_kcount(k_count: int) -> BandRanges:
+    """
+    Return Bark band index ranges [start, end] (inclusive) for the given MDCT line count.
+
+    Parameters
+    ----------
+    k_count : int
+        Number of MDCT lines:
+        - 1024 for long frames
+        - 128 for short subframes (ESH)
+
+    Returns
+    -------
+    BandRanges (list[tuple[int, int]])
+        Each tuple is (start_k, end_k) inclusive.
+    """
+    tables = load_b219_tables()
+    if k_count == 1024:
+        tbl = tables["B219a"]
+    elif k_count == 128:
+        tbl = tables["B219b"]
+    else:
+        raise ValueError("TNS supports only k_count=1024 (long) or k_count=128 (short).")
+
+    start = tbl[:, 1].astype(int)
+    end = tbl[:, 2].astype(int)
+
+    ranges: list[tuple[int, int]] = [(int(s), int(e)) for s, e in zip(start, end)]
+
+    for s, e in ranges:
+        if s < 0 or e < s or e >= k_count:
+            raise ValueError("Invalid band table ranges for given k_count.")
+    return ranges
+
+
+# -----------------------------------------------------------------------------
+# Core DSP helpers
+# -----------------------------------------------------------------------------
+
+def _smooth_sw_inplace(sw: MdctCoeffs) -> None:
+    """
+    Smooth Sw(k) to reduce discontinuities between adjacent Bark bands.
+
+    The assignment applies two passes:
+    - Backward: Sw(k) = (Sw(k) + Sw(k+1))/2
+    - Forward:  Sw(k) = (Sw(k) + Sw(k-1))/2
+
+    Parameters
+    ----------
+    sw : MdctCoeffs
+        1-D array of length K (float64). Modified in-place.
+    """
+    k_count = int(sw.shape[0])
+
+    for k in range(k_count - 2, -1, -1):
+        sw[k] = 0.5 * (sw[k] + sw[k + 1])
+
+    for k in range(1, k_count):
+        sw[k] = 0.5 * (sw[k] + sw[k - 1])
+
+
+def _compute_sw(x: MdctCoeffs) -> MdctCoeffs:
+    """
+    Compute Sw(k) from band energies P(j) and apply boundary smoothing.
+
+    Parameters
+    ----------
+    x : MdctCoeffs
+        1-D MDCT line array, length K.
+
+    Returns
+    -------
+    MdctCoeffs
+        Sw(k), 1-D array of length K, float64.
+    """
+    x = np.asarray(x, dtype=np.float64).reshape(-1)
+    k_count = int(x.shape[0])
+
+    bands = _band_ranges_for_kcount(k_count)
+    sw = np.zeros(k_count, dtype=np.float64)
+
+    for s, e in bands:
+        seg = x[s : e + 1]
+        p_j = float(np.sum(seg * seg))
+        sw_val = float(np.sqrt(p_j))
+        sw[s : e + 1] = sw_val
+
+    _smooth_sw_inplace(sw)
+    return sw
+
+
+def _autocorr(x: MdctCoeffs, p: int) -> MdctCoeffs:
+    """
+    Autocorrelation r(m) for m=0..p.
+
+    Parameters
+    ----------
+    x : MdctCoeffs
+        1-D signal.
+    p : int
+        Maximum lag.
+
+    Returns
+    -------
+    MdctCoeffs
+        r, shape (p+1,), float64.
+    """
+    x = np.asarray(x, dtype=np.float64).reshape(-1)
+    n = int(x.shape[0])
+
+    r = np.zeros(p + 1, dtype=np.float64)
+    for m in range(p + 1):
+        r[m] = float(np.dot(x[m:], x[: n - m]))
+    return r
+
+
+def _lpc_coeffs(xw: MdctCoeffs, p: int) -> MdctCoeffs:
+    """
+    Solve Yule-Walker normal equations for LPC coefficients of order p.
+
+    Parameters
+    ----------
+    xw : MdctCoeffs
+        1-D normalized sequence Xw(k).
+    p : int
+        Predictor order.
+
+    Returns
+    -------
+    MdctCoeffs
+        LPC coefficients a[0..p-1], shape (p,), float64.
+    """
+    r = _autocorr(xw, p)
+
+    R = np.empty((p, p), dtype=np.float64)
+    for i in range(p):
+        for j in range(p):
+            R[i, j] = r[abs(i - j)]
+
+    rhs = r[1 : p + 1].reshape(p)
+
+    reg = 1e-12
+    R_reg = R + reg * np.eye(p, dtype=np.float64)
+
+    a = np.linalg.solve(R_reg, rhs)
+    return a
+
+
+def _quantize_coeffs(a: MdctCoeffs) -> MdctCoeffs:
+    """
+    Quantize LPC coefficients with uniform symmetric quantizer and clamp.
+
+    Parameters
+    ----------
+    a : MdctCoeffs
+        LPC coefficient array, shape (p,).
+
+    Returns
+    -------
+    MdctCoeffs
+        Quantized coefficients, shape (p,), float64.
+    """
+    a = np.asarray(a, dtype=np.float64).reshape(-1)
+    q = np.round(a / QUANT_STEP) * QUANT_STEP
+    q = np.clip(q, -QUANT_MAX, QUANT_MAX)
+    return q.astype(np.float64, copy=False)
+
+
+def _is_inverse_stable(a_q: MdctCoeffs) -> bool:
+    """
+    Check stability of the inverse TNS filter H_TNS^{-1}.
+
+    Forward filter:
+        H_TNS(z) = 1 - a1 z^-1 - ... - ap z^-p
+
+    Inverse filter poles are roots of:
+        A(z) = 1 - a1 z^-1 - ... - ap z^-p
+    Multiply by z^p:
+        z^p - a1 z^{p-1} - ... - ap = 0
+
+    Stability condition:
+        all roots satisfy |z| < 1.
+
+    Parameters
+    ----------
+    a_q : MdctCoeffs
+        Quantized predictor coefficients, shape (p,).
+
+    Returns
+    -------
+    bool
+        True if stable, else False.
+    """
+    a_q = np.asarray(a_q, dtype=np.float64).reshape(-1)
+    p = int(a_q.shape[0])
+
+    # Polynomial in z: z^p - a1 z^{p-1} - ... - ap
+    poly = np.empty(p + 1, dtype=np.float64)
+    poly[0] = 1.0
+    poly[1:] = -a_q
+
+    roots = np.roots(poly)
+
+    # Strictly inside unit circle for stability. Add tiny margin for numeric safety.
+    margin = 1e-12
+    return bool(np.all(np.abs(roots) < (1.0 - margin)))
+
+
+def _stabilize_quantized_coeffs(a_q: MdctCoeffs) -> MdctCoeffs:
+    """
+    Make quantized predictor coefficients stable for inverse filtering.
+
+    Policy:
+    - If already stable: return as-is.
+    - Else: iteratively shrink coefficients by gamma and re-quantize to the 0.1 grid.
+    - If still unstable after attempts: fall back to all-zero coefficients (disable TNS).
+
+    Parameters
+    ----------
+    a_q : MdctCoeffs
+        Quantized predictor coefficients, shape (p,).
+
+    Returns
+    -------
+    MdctCoeffs
+        Stable quantized coefficients, shape (p,).
+    """
+    a_q = np.asarray(a_q, dtype=np.float64).reshape(-1)
+
+    if _is_inverse_stable(a_q):
+        return a_q
+
+    # Try a few shrinking factors. Re-quantize after shrinking to keep coefficients on-grid.
+    gammas = (0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1)
+
+    for g in gammas:
+        cand = _quantize_coeffs(g * a_q)
+        if _is_inverse_stable(cand):
+            return cand
+
+    # Last resort: disable TNS for this vector
+    return np.zeros_like(a_q, dtype=np.float64)
+
+
+def _apply_tns_fir(x: MdctCoeffs, a_q: MdctCoeffs) -> MdctCoeffs:
+    """
+    Apply forward TNS FIR filter:
+        y[k] = x[k] - sum_{l=1..p} a_l * x[k-l]
+
+    Parameters
+    ----------
+    x : MdctCoeffs
+        1-D MDCT lines, length K.
+    a_q : MdctCoeffs
+        Quantized LPC coefficients, shape (p,).
+
+    Returns
+    -------
+    MdctCoeffs
+        Filtered MDCT lines y, length K.
+    """
+    x = np.asarray(x, dtype=np.float64).reshape(-1)
+    a_q = np.asarray(a_q, dtype=np.float64).reshape(-1)
+    p = int(a_q.shape[0])
+    k_count = int(x.shape[0])
+
+    y = np.zeros(k_count, dtype=np.float64)
+    for k in range(k_count):
+        acc = x[k]
+        for l in range(1, p + 1):
+            if k - l >= 0:
+                acc -= a_q[l - 1] * x[k - l]
+        y[k] = acc
+    return y
+
+
+def _apply_itns_iir(y: MdctCoeffs, a_q: MdctCoeffs) -> MdctCoeffs:
+    """
+    Apply inverse TNS IIR filter:
+        x_hat[k] = y[k] + sum_{l=1..p} a_l * x_hat[k-l]
+
+    Parameters
+    ----------
+    y : MdctCoeffs
+        1-D MDCT lines after TNS, length K.
+    a_q : MdctCoeffs
+        Quantized LPC coefficients, shape (p,).
+
+    Returns
+    -------
+    MdctCoeffs
+        Reconstructed MDCT lines x_hat, length K.
+    """
+    y = np.asarray(y, dtype=np.float64).reshape(-1)
+    a_q = np.asarray(a_q, dtype=np.float64).reshape(-1)
+    p = int(a_q.shape[0])
+    k_count = int(y.shape[0])
+
+    x_hat = np.zeros(k_count, dtype=np.float64)
+    for k in range(k_count):
+        acc = y[k]
+        for l in range(1, p + 1):
+            if k - l >= 0:
+                acc += a_q[l - 1] * x_hat[k - l]
+        x_hat[k] = acc
+    return x_hat
+
+
+def _tns_one_vector(x: MdctCoeffs) -> tuple[MdctCoeffs, MdctCoeffs]:
+    """
+    TNS for a single MDCT vector (one long frame or one short subframe).
+
+    Steps:
+    1) Compute Sw(k) from Bark band energies and smooth it.
+    2) Normalize: Xw(k) = X(k) / Sw(k) (safe when Sw=0).
+    3) Compute LPC coefficients (order p=PRED_ORDER) on Xw.
+    4) Quantize coefficients (4-bit symmetric, step QUANT_STEP).
+    5) Apply FIR filter on original X(k) using quantized coefficients.
+
+    Parameters
+    ----------
+    x : MdctCoeffs
+        1-D MDCT vector.
+
+    Returns
+    -------
+    y : MdctCoeffs
+        TNS-processed MDCT vector (same length).
+    a_q : MdctCoeffs
+        Quantized LPC coefficients, shape (PRED_ORDER,).
+    """
+    x = np.asarray(x, dtype=np.float64).reshape(-1)
+    sw = _compute_sw(x)
+
+    eps = 1e-12
+    xw = np.zeros_like(x, dtype=np.float64)
+    mask = sw > eps
+    np.divide(x, sw, out=xw, where=mask)
+
+    a = _lpc_coeffs(xw, PRED_ORDER)
+    a_q = _quantize_coeffs(a)
+
+    # Ensure inverse stability (assignment requirement)
+    a_q = _stabilize_quantized_coeffs(a_q)
+
+    y = _apply_tns_fir(x, a_q)
+    return y, a_q
+
+
+
+# -----------------------------------------------------------------------------
+# Public Functions
+# -----------------------------------------------------------------------------
+
+def aac_tns(frame_F_in: FrameChannelF, frame_type: FrameType) -> Tuple[FrameChannelF, TnsCoeffs]:
+    """
+    Temporal Noise Shaping (TNS) for ONE channel.
+
+    Parameters
+    ----------
+    frame_F_in : FrameChannelF
+        Per-channel MDCT coefficients.
+        Expected (typical) shapes:
+        - If frame_type == "ESH": (128, 8)
+        - Else: (1024, 1) or (1024,)
+
+    frame_type : FrameType
+        Frame type code ("OLS", "LSS", "ESH", "LPS").
+
+    Returns
+    -------
+    frame_F_out : FrameChannelF
+        Per-channel MDCT coefficients after applying TNS.
+        Same shape convention as input.
+
+    tns_coeffs : TnsCoeffs
+        Quantized TNS predictor coefficients.
+        Expected shapes:
+        - If frame_type == "ESH": (PRED_ORDER, 8)
+        - Else: (PRED_ORDER, 1)
+    """
+    x = np.asarray(frame_F_in, dtype=np.float64)
+
+    if frame_type == "ESH":
+        if x.shape != (128, 8):
+            raise ValueError("For ESH, frame_F_in must have shape (128, 8).")
+
+        y = np.empty_like(x, dtype=np.float64)
+        a_out = np.empty((PRED_ORDER, 8), dtype=np.float64)
+
+        for j in range(8):
+            y[:, j], a_out[:, j] = _tns_one_vector(x[:, j])
+
+        return y, a_out
+
+    if x.shape == (1024,):
+        x_vec = x
+        out_shape = (1024,)
+    elif x.shape == (1024, 1):
+        x_vec = x[:, 0]
+        out_shape = (1024, 1)
+    else:
+        raise ValueError('For non-ESH, frame_F_in must have shape (1024,) or (1024, 1).')
+
+    y_vec, a_q = _tns_one_vector(x_vec)
+
+    if out_shape == (1024,):
+        y_out = y_vec
+    else:
+        y_out = y_vec.reshape(1024, 1)
+
+    a_out = a_q.reshape(PRED_ORDER, 1)
+    return y_out, a_out
+
+
+def aac_i_tns(frame_F_in: FrameChannelF, frame_type: FrameType, tns_coeffs: TnsCoeffs) -> FrameChannelF:
+    """
+    Inverse Temporal Noise Shaping (iTNS) for ONE channel.
+
+    Parameters
+    ----------
+    frame_F_in : FrameChannelF
+        Per-channel MDCT coefficients after TNS.
+        Expected (typical) shapes:
+        - If frame_type == "ESH": (128, 8)
+        - Else: (1024, 1) or (1024,)
+
+    frame_type : FrameType
+        Frame type code ("OLS", "LSS", "ESH", "LPS").
+
+    tns_coeffs : TnsCoeffs
+        Quantized TNS predictor coefficients.
+        Expected shapes:
+        - If frame_type == "ESH": (PRED_ORDER, 8)
+        - Else: (PRED_ORDER, 1)
+
+    Returns
+    -------
+    FrameChannelF
+        Per-channel MDCT coefficients after inverse TNS.
+        Same shape convention as input frame_F_in.
+    """
+    x = np.asarray(frame_F_in, dtype=np.float64)
+    a = np.asarray(tns_coeffs, dtype=np.float64)
+
+    if frame_type == "ESH":
+        if x.shape != (128, 8):
+            raise ValueError("For ESH, frame_F_in must have shape (128, 8).")
+        if a.shape != (PRED_ORDER, 8):
+            raise ValueError("For ESH, tns_coeffs must have shape (PRED_ORDER, 8).")
+
+        y = np.empty_like(x, dtype=np.float64)
+        for j in range(8):
+            y[:, j] = _apply_itns_iir(x[:, j], a[:, j])
+        return y
+
+    if a.shape != (PRED_ORDER, 1):
+        raise ValueError("For non-ESH, tns_coeffs must have shape (PRED_ORDER, 1).")
+
+    if x.shape == (1024,):
+        x_vec = x
+        out_shape = (1024,)
+    elif x.shape == (1024, 1):
+        x_vec = x[:, 0]
+        out_shape = (1024, 1)
+    else:
+        raise ValueError('For non-ESH, frame_F_in must have shape (1024,) or (1024, 1).')
+
+    y_vec = _apply_itns_iir(x_vec, a[:, 0])
+
+    if out_shape == (1024,):
+        return y_vec
+    return y_vec.reshape(1024, 1)

source/level_3/core/aac_types.py

@@ -0,0 +1,411 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Public Type Aliases
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   This module implements Public Type aliases
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from typing import List, Literal, TypeAlias, TypedDict
+import numpy as np
+from numpy.typing import NDArray
+
+# -----------------------------------------------------------------------------
+# Code enums (for readability; not intended to enforce shapes/lengths)
+# -----------------------------------------------------------------------------
+
+FrameType: TypeAlias = Literal["OLS", "LSS", "ESH", "LPS"]
+"""
+Frame type codes (AAC):
+- "OLS": ONLY_LONG_SEQUENCE
+- "LSS": LONG_START_SEQUENCE
+- "ESH": EIGHT_SHORT_SEQUENCE
+- "LPS": LONG_STOP_SEQUENCE
+"""
+
+WinType: TypeAlias = Literal["KBD", "SIN"]
+"""
+Window type codes (AAC):
+- "KBD": Kaiser-Bessel-Derived
+- "SIN": sinusoid
+"""
+
+ChannelKey: TypeAlias = Literal["chl", "chr"]
+"""Channel dictionary keys used in Level payloads."""
+
+
+# -----------------------------------------------------------------------------
+# Array “semantic” aliases
+#
+# Goal: communicate meaning (time/frequency/window, stereo/channel) without
+# forcing strict shapes in the type system.
+# -----------------------------------------------------------------------------
+
+FloatArray: TypeAlias = NDArray[np.float64]
+"""
+Generic float64 NumPy array.
+
+Note:
+- We standardize internal numeric computations to float64 for stability and
+  reproducibility. External I/O can still be float32, but we convert at the
+  boundaries.
+"""
+
+Window: TypeAlias = FloatArray
+"""
+Time-domain window (weighting sequence), 1-D.
+
+Typical lengths in this assignment:
+- Long: 2048
+- Short: 256
+- Window sequences for LSS/LPS are also 2048
+
+Expected shape: (N,)
+dtype: float64
+"""
+
+TimeSignal: TypeAlias = FloatArray
+"""
+Time-domain signal samples, typically 1-D.
+
+Examples:
+- Windowed MDCT input: shape (N,)
+- IMDCT output: shape (N,)
+
+dtype: float64
+"""
+
+StereoSignal: TypeAlias = FloatArray
+"""
+Time-domain stereo signal stream.
+
+Expected (typical) shape: (N, 2)
+- axis 0: time samples
+- axis 1: channels [L, R]
+
+dtype: float64
+"""
+
+MdctCoeffs: TypeAlias = FloatArray
+"""
+MDCT coefficient vector, typically 1-D.
+
+Examples:
+- Long: shape (1024,)
+- Short: shape (128,)
+
+dtype: float64
+"""
+
+MdctFrameChannel: TypeAlias = FloatArray
+"""
+Per-channel MDCT container used in Level-1/2 sequences.
+
+Typical shapes:
+- If frame_type in {"OLS","LSS","LPS"}: (1024, 1) or (1024,)
+- If frame_type == "ESH": (128, 8)  (8 short subframes for one channel)
+
+dtype: float64
+
+Notes
+-----
+Some parts of the assignment store long-frame coefficients as a column vector
+(1024, 1) to match MATLAB conventions. Internally you may also use (1024,)
+when convenient, but the semantic meaning is identical.
+"""
+
+TnsCoeffs: TypeAlias = FloatArray
+"""
+Quantized TNS predictor coefficients (one channel).
+
+Typical shapes (Level 2):
+- If frame_type == "ESH": (4, 8)   (order p=4 for each of the 8 short subframes)
+- Else: (4, 1)            (order p=4 for the long frame)
+
+dtype: float64
+
+Notes
+-----
+The assignment uses a 4-bit uniform symmetric quantizer with step size 0.1.
+We store the quantized coefficient values as float64 (typically multiples of 0.1)
+to keep the pipeline simple and readable.
+"""
+
+
+FrameT: TypeAlias = FloatArray
+"""
+Time-domain frame (stereo), as used by the filterbank input/output.
+
+Expected (typical) shape for stereo: (2048, 2)
+- axis 0: time samples
+- axis 1: channels [L, R]
+
+dtype: float64
+"""
+
+FrameChannelT: TypeAlias = FloatArray
+"""
+Time-domain single-channel frame.
+
+Expected (typical) shape: (2048,)
+
+dtype: float64
+"""
+
+FrameF: TypeAlias = FloatArray
+"""
+Frequency-domain frame (MDCT coefficients), stereo container.
+
+Typical shapes (Level 1):
+- If frame_type in {"OLS","LSS","LPS"}: (1024, 2)
+- If frame_type == "ESH": (128, 16)
+
+Rationale for ESH (128, 16):
+- 8 short subframes per channel => 8 * 2 = 16 columns total
+- Each short subframe per stereo is (128, 2), flattened into columns
+  in subframe order: [sf0_L, sf0_R, sf1_L, sf1_R, ..., sf7_L, sf7_R]
+
+dtype: float64
+"""
+
+FrameChannelF: TypeAlias = MdctFrameChannel
+"""
+Frequency-domain single-channel MDCT coefficients.
+
+Typical shapes (Level 1/2):
+- If frame_type in {"OLS","LSS","LPS"}: (1024, 1) or (1024,)
+- If frame_type == "ESH": (128, 8)
+
+dtype: float64
+"""
+
+BandRanges: TypeAlias = list[tuple[int, int]]
+"""
+Bark-band index ranges [start, end] (inclusive) for MDCT lines.
+
+Used by TNS to map MDCT indices k to Bark bands.
+"""
+
+BarkTable: TypeAlias = FloatArray
+"""
+Psychoacoustic Bark band table loaded from TableB219.mat.
+
+Typical shapes:
+- Long: (69, 6)
+- Short: (42, 6)
+"""
+
+BandIndexArray: TypeAlias = NDArray[np.int_]
+"""
+Array of FFT bin indices per psychoacoustic band.
+"""
+
+BandValueArray: TypeAlias = FloatArray
+"""
+Per-band psychoacoustic values (e.g. Bark position, thresholds).
+"""
+
+
+# Quantizer-related semantic aliases
+
+QuantizedSymbols: TypeAlias = NDArray[np.generic]
+"""
+Quantized MDCT symbols S(k).
+
+Shapes:
+- Always (1024, 1) at the quantizer output (ESH packed to 1024 symbols).
+"""
+
+ScaleFactors: TypeAlias = NDArray[np.generic]
+"""
+DPCM-coded scalefactors sfc(b) = alpha(b) - alpha(b-1).
+
+Shapes:
+- Long frames: (NB, 1)
+- ESH frames: (NB, 8)
+"""
+
+GlobalGain: TypeAlias = float | NDArray[np.generic]
+"""
+Global gain G = alpha(0).
+
+- Long frames: scalar float
+- ESH frames: array shape (1, 8)
+"""
+
+# Huffman semantic aliases
+
+HuffmanBitstream: TypeAlias = str
+"""Huffman-coded bitstream stored as a string of '0'/'1'."""
+
+HuffmanCodebook: TypeAlias = int
+"""Huffman codebook id (e.g., 0..11)."""
+
+# -----------------------------------------------------------------------------
+# Level 1 AAC sequence payload types
+# -----------------------------------------------------------------------------
+
+class AACChannelFrameF(TypedDict):
+    """
+    Per-channel payload for aac_seq_1[i]["chl"] or ["chr"] (Level 1).
+
+    Keys
+    ----
+    frame_F:
+        The MDCT coefficients for ONE channel.
+        Typical shapes:
+        - ESH: (128, 8)   (8 short subframes)
+        - else: (1024, 1) or (1024,)
+    """
+    frame_F: FrameChannelF
+
+
+class AACSeq1Frame(TypedDict):
+    """
+    One frame dictionary element of aac_seq_1 (Level 1).
+    """
+    frame_type: FrameType
+    win_type: WinType
+    chl: AACChannelFrameF
+    chr: AACChannelFrameF
+
+
+AACSeq1: TypeAlias = List[AACSeq1Frame]
+"""
+AAC sequence for Level 1:
+List of length K (K = number of frames).
+
+Each element is a dict with keys:
+- "frame_type", "win_type", "chl", "chr"
+"""
+
+
+# -----------------------------------------------------------------------------
+# Level 2 AAC sequence payload types (TNS)
+# -----------------------------------------------------------------------------
+
+class AACChannelFrameF2(TypedDict):
+    """
+    Per-channel payload for aac_seq_2[i]["chl"] or ["chr"] (Level 2).
+
+    Keys
+    ----
+    frame_F:
+        The TNS-processed MDCT coefficients for ONE channel.
+        Typical shapes:
+        - ESH: (128, 8)
+        - else: (1024, 1) or (1024,)
+    tns_coeffs:
+        Quantized TNS predictor coefficients for ONE channel.
+        Typical shapes:
+        - ESH: (PRED_ORDER, 8)
+        - else: (PRED_ORDER, 1)
+    """
+    frame_F: FrameChannelF
+    tns_coeffs: TnsCoeffs
+
+
+class AACSeq2Frame(TypedDict):
+    """
+    One frame dictionary element of aac_seq_2 (Level 2).
+    """
+    frame_type: FrameType
+    win_type: WinType
+    chl: AACChannelFrameF2
+    chr: AACChannelFrameF2
+
+
+AACSeq2: TypeAlias = List[AACSeq2Frame]
+"""
+AAC sequence for Level 2:
+List of length K (K = number of frames).
+
+Each element is a dict with keys:
+- "frame_type", "win_type", "chl", "chr"
+
+Level 2 adds:
+- per-channel "tns_coeffs"
+and stores:
+- per-channel "frame_F" after applying TNS.
+"""
+
+# -----------------------------------------------------------------------------
+# Level 3 AAC sequence payload types (Quantizer + Huffman)
+# -----------------------------------------------------------------------------
+
+class AACChannelFrameF3(TypedDict):
+    """
+    Per-channel payload for aac_seq_3[i]["chl"] or ["chr"] (Level 3).
+
+    Keys
+    ----
+    tns_coeffs:
+        Quantized TNS predictor coefficients for ONE channel.
+        Shapes:
+        - ESH: (PRED_ORDER, 8)
+        - else: (PRED_ORDER, 1)
+
+    T:
+        Psychoacoustic thresholds per band.
+        Shapes:
+        - ESH: (NB, 8)
+        - else: (NB, 1)
+        Note: Stored for completeness / debugging; not entropy-coded.
+
+    G:
+        Quantized global gains.
+        Shapes:
+        - ESH: (1, 8)  (one per short subframe)
+        - else: scalar (or compatible np scalar)
+
+    sfc:
+        Huffman-coded scalefactor differences (DPCM sequence).
+
+    stream:
+        Huffman-coded MDCT quantized symbols S(k) (packed to 1024 symbols).
+
+    codebook:
+        Huffman codebook id used for MDCT symbols (stream).
+        (Scalefactors typically use fixed codebook 11 and do not need to store it.)
+    """
+    tns_coeffs: TnsCoeffs
+    T: FloatArray
+    G: FloatArray | float
+    sfc: HuffmanBitstream
+    stream: HuffmanBitstream
+    codebook: HuffmanCodebook
+
+
+class AACSeq3Frame(TypedDict):
+    """
+    One frame dictionary element of aac_seq_3 (Level 3).
+    """
+    frame_type: FrameType
+    win_type: WinType
+    chl: AACChannelFrameF3
+    chr: AACChannelFrameF3
+
+
+AACSeq3: TypeAlias = List[AACSeq3Frame]
+"""
+AAC sequence for Level 3:
+List of length K (K = number of frames).
+
+Each element is a dict with keys:
+- "frame_type", "win_type", "chl", "chr"
+
+Level 3 adds (per channel):
+- "tns_coeffs"
+- "T" thresholds (not entropy-coded)
+- "G" global gain(s)
+- "sfc" Huffman-coded scalefactor differences
+- "stream" Huffman-coded MDCT quantized symbols
+- "codebook" Huffman codebook for MDCT symbols
+"""

source/level_3/core/aac_utils.py

@@ -0,0 +1,270 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - AAC Utilities
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Shared utility functions used across AAC encoder/decoder levels.
+#
+#   This module currently provides:
+#   - MDCT / IMDCT conversions
+#   - Signal-to-Noise Ratio (SNR) computation in dB
+#   - Loading and access helpers for psychoacoustic band tables
+#     (TableB219.mat, Tables B.2.1.9a / B.2.1.9b of the AAC specification)
+# ------------------------------------------------------------
+from __future__ import annotations
+
+import numpy as np
+from pathlib import Path
+
+from scipy.io import loadmat
+from core.aac_types import *
+
+
+# -----------------------------------------------------------------------------
+# Global cached data
+# -----------------------------------------------------------------------------
+# Cached contents of TableB219.mat to avoid repeated disk I/O.
+# Keys:
+#   - "B219a": long-window psychoacoustic bands (69 bands, FFT size 2048)
+#   - "B219b": short-window psychoacoustic bands (42 bands, FFT size 256)
+B219_CACHE: dict[str, BarkTable] | None = None
+
+
+# -----------------------------------------------------------------------------
+# MDCT / IMDCT
+# -----------------------------------------------------------------------------
+def mdct(s: TimeSignal) -> MdctCoeffs:
+    """
+    MDCT (direct form) as specified in the assignment.
+
+    Parameters
+    ----------
+    s : TimeSignal
+        Windowed time samples, 1-D array of length N (N = 2048 or 256).
+
+    Returns
+    -------
+    MdctCoeffs
+        MDCT coefficients, 1-D array of length N/2.
+
+    Definition
+    ----------
+    X[k] = 2 * sum_{n=0..N-1} s[n] * cos((2*pi/N) * (n + n0) * (k + 1/2)),
+    where n0 = (N/2 + 1)/2.
+    """
+    s = np.asarray(s, dtype=np.float64).reshape(-1)
+    N = int(s.shape[0])
+    if N not in (2048, 256):
+        raise ValueError("MDCT input length must be 2048 or 256.")
+
+    n0 = (N / 2.0 + 1.0) / 2.0
+    n = np.arange(N, dtype=np.float64) + n0
+    k = np.arange(N // 2, dtype=np.float64) + 0.5
+
+    C = np.cos((2.0 * np.pi / N) * np.outer(n, k))  # (N, N/2)
+    X = 2.0 * (s @ C)  # (N/2,)
+    return X
+
+
+def imdct(X: MdctCoeffs) -> TimeSignal:
+    """
+    IMDCT (direct form) as specified in the assignment.
+
+    Parameters
+    ----------
+    X : MdctCoeffs
+        MDCT coefficients, 1-D array of length K (K = 1024 or 128).
+
+    Returns
+    -------
+    TimeSignal
+        Reconstructed time samples, 1-D array of length N = 2K.
+
+    Definition
+    ----------
+    s[n] = (2/N) * sum_{k=0..N/2-1} X[k] * cos((2*pi/N) * (n + n0) * (k + 1/2)),
+    where n0 = (N/2 + 1)/2.
+    """
+    X = np.asarray(X, dtype=np.float64).reshape(-1)
+    K = int(X.shape[0])
+    if K not in (1024, 128):
+        raise ValueError("IMDCT input length must be 1024 or 128.")
+
+    N = 2 * K
+    n0 = (N / 2.0 + 1.0) / 2.0
+
+    n = np.arange(N, dtype=np.float64) + n0
+    k = np.arange(K, dtype=np.float64) + 0.5
+
+    C = np.cos((2.0 * np.pi / N) * np.outer(n, k))  # (N, K)
+    s = (2.0 / N) * (C @ X)  # (N,)
+    return s
+
+
+# -----------------------------------------------------------------------------
+# Signal quality metrics
+# -----------------------------------------------------------------------------
+
+def snr_db(x_ref: StereoSignal, x_hat: StereoSignal) -> float:
+    """
+    Compute the overall Signal-to-Noise Ratio (SNR) in dB.
+
+    The SNR is computed over all available samples and channels,
+    after conservatively aligning the two signals to their common
+    length and channel count.
+
+    Parameters
+    ----------
+    x_ref : StereoSignal
+        Reference (original) signal.
+        Typical shape: (N, 2) for stereo.
+    x_hat : StereoSignal
+        Reconstructed or processed signal.
+        Typical shape: (M, 2) for stereo.
+
+    Returns
+    -------
+    float
+        SNR in dB.
+        - +inf if the noise power is zero (perfect reconstruction).
+        - -inf if the reference signal power is zero.
+    """
+    x_ref = np.asarray(x_ref, dtype=np.float64)
+    x_hat = np.asarray(x_hat, dtype=np.float64)
+
+    # Ensure 2-D shape: (samples, channels)
+    if x_ref.ndim == 1:
+        x_ref = x_ref.reshape(-1, 1)
+    if x_hat.ndim == 1:
+        x_hat = x_hat.reshape(-1, 1)
+
+    # Align lengths and channel count conservatively
+    n = min(x_ref.shape[0], x_hat.shape[0])
+    c = min(x_ref.shape[1], x_hat.shape[1])
+
+    x_ref = x_ref[:n, :c]
+    x_hat = x_hat[:n, :c]
+
+    err = x_ref - x_hat
+    ps = float(np.sum(x_ref * x_ref))     # signal power
+    pn = float(np.sum(err * err))          # noise power
+
+    if pn <= 0.0:
+        return float("inf")
+    if ps <= 0.0:
+        return float("-inf")
+
+    return float(10.0 * np.log10(ps / pn))
+
+
+# -----------------------------------------------------------------------------
+# Psychoacoustic band tables (TableB219.mat)
+# -----------------------------------------------------------------------------
+
+def load_b219_tables() -> dict[str, BarkTable]:
+    """
+    Load and cache psychoacoustic band tables from TableB219.mat.
+
+    The assignment/project layout assumes that a 'material' directory
+    is available in the current working directory when running:
+    - tests
+    - level_1 / level_2 / level_3 entrypoints
+
+    This function loads the tables once and caches them for subsequent calls.
+
+    Returns
+    -------
+    dict[str, BarkTable]
+        Dictionary with the following entries:
+        - "B219a": long-window psychoacoustic table
+                   (69 bands, FFT size 2048 / 1024 spectral lines)
+        - "B219b": short-window psychoacoustic table
+                   (42 bands, FFT size 256 / 128 spectral lines)
+    """
+    global B219_CACHE
+    if B219_CACHE is not None:
+        return B219_CACHE
+
+    mat_path = Path("material") / "TableB219.mat"
+    if not mat_path.exists():
+        raise FileNotFoundError(
+            "Could not locate material/TableB219.mat in the current working directory."
+        )
+
+    data = loadmat(str(mat_path))
+    if "B219a" not in data or "B219b" not in data:
+        raise ValueError(
+            "TableB219.mat missing required variables 'B219a' and/or 'B219b'."
+        )
+
+    B219_CACHE = {
+        "B219a": np.asarray(data["B219a"], dtype=np.float64),
+        "B219b": np.asarray(data["B219b"], dtype=np.float64),
+    }
+    return B219_CACHE
+
+
+def get_table(frame_type: FrameType) -> tuple[BarkTable, int]:
+    """
+    Select the appropriate psychoacoustic band table and FFT size
+    based on the AAC frame type.
+
+    Parameters
+    ----------
+    frame_type : FrameType
+        AAC frame type ("OLS", "LSS", "ESH", "LPS").
+
+    Returns
+    -------
+    table : BarkTable
+        Psychoacoustic band table:
+        - B219a for long frames
+        - B219b for ESH short subframes
+    N : int
+        FFT size corresponding to the table:
+        - 2048 for long frames
+        - 256 for short frames (ESH)
+    """
+    tables = load_b219_tables()
+    if frame_type == "ESH":
+        return tables["B219b"], 256
+    return tables["B219a"], 2048
+
+
+def band_limits(
+    table: BarkTable,
+) -> tuple[BandIndexArray, BandIndexArray, BandValueArray, BandValueArray]:
+    """
+    Extract per-band metadata from a TableB2.1.9 psychoacoustic table.
+
+    The column layout follows the provided TableB219.mat file and the
+    AAC specification tables B.2.1.9a / B.2.1.9b.
+
+    Parameters
+    ----------
+    table : BarkTable
+        Psychoacoustic band table (B219a or B219b).
+
+    Returns
+    -------
+    wlow : BandIndexArray
+        Lower FFT bin index (inclusive) for each band.
+    whigh : BandIndexArray
+        Upper FFT bin index (inclusive) for each band.
+    bval : BandValueArray
+        Bark-scale (or equivalent) band position values.
+        Used in the spreading function.
+    qthr_db : BandValueArray
+        Threshold in quiet for each band, in dB.
+    """
+    wlow = table[:, 1].astype(int)
+    whigh = table[:, 2].astype(int)
+    bval = table[:, 4].astype(np.float64)
+    qthr_db = table[:, 5].astype(np.float64)
+    return wlow, whigh, bval, qthr_db

source/level_3/level_3.py

@@ -0,0 +1,237 @@
+# ------------------------------------------------------------
+# AAC Coder/Decoder - Level 3 Wrappers + Demo
+#
+# Multimedia course at Aristotle University of
+# Thessaloniki (AUTh)
+#
+# Author:
+#   Christos Choutouridis (ΑΕΜ 8997)
+#   cchoutou@ece.auth.gr
+#
+# Description:
+#   Level 3 wrapper module.
+#
+#   This file provides:
+#   - Thin wrappers for Level 3 API functions (encode/decode) that delegate
+#     to the corresponding core implementations.
+#   - A demo function that runs end-to-end and computes:
+#       * SNR
+#       * bitrate (coded)
+#       * compression ratio
+#   - A small CLI entrypoint for convenience.
+# ------------------------------------------------------------
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Optional, Tuple, Union
+
+import os
+import soundfile as sf
+
+from core.aac_types   import AACSeq3, StereoSignal
+from core.aac_coder   import aac_coder_3 as core_aac_coder_3
+from core.aac_coder   import aac_read_wav_stereo_48k
+from core.aac_decoder import aac_decoder_3 as core_aac_decoder_3
+from core.aac_utils   import snr_db
+
+
+# -----------------------------------------------------------------------------
+# Helpers (Level 3 metrics)
+# -----------------------------------------------------------------------------
+
+def _wav_duration_seconds(wav_path: Path) -> float:
+    """Return WAV duration in seconds using soundfile metadata."""
+    info = sf.info(str(wav_path))
+    if info.samplerate <= 0:
+        raise ValueError("Invalid samplerate in WAV header.")
+    if info.frames < 0:
+        raise ValueError("Invalid frame count in WAV header.")
+    return float(info.frames) / float(info.samplerate)
+
+
+def _bitrate_before_from_file(wav_path: Path) -> float:
+    """
+    Compute input bitrate (bits/s) from file size and duration.
+
+    Note:
+    This is a file-based bitrate estimate (includes WAV header), which is
+    acceptable for a simple compression ratio metric.
+    """
+    duration = _wav_duration_seconds(wav_path)
+    if duration <= 0.0:
+        raise ValueError("Non-positive WAV duration.")
+    nbits = float(os.path.getsize(wav_path)) * 8.0
+    return nbits / duration
+
+
+def _bitrate_after_from_aacseq(aac_seq_3: AACSeq3, duration_sec: float) -> float:
+    """
+    Compute coded bitrate (bits/s) from Huffman streams stored in AACSeq3.
+
+    We count bits from:
+    - scalefactor Huffman bitstream ("sfc")
+    - MDCT symbols Huffman bitstream ("stream")
+    for both channels and all frames.
+
+    Note:
+    We intentionally ignore side-info overhead (frame_type, G, T, TNS coeffs,
+    codebook ids, etc.). This matches a common simplified metric in demos.
+    """
+    if duration_sec <= 0.0:
+        raise ValueError("Non-positive duration for bitrate computation.")
+
+    total_bits = 0
+    for fr in aac_seq_3:
+        total_bits += len(fr["chl"]["sfc"])
+        total_bits += len(fr["chl"]["stream"])
+        total_bits += len(fr["chr"]["sfc"])
+        total_bits += len(fr["chr"]["stream"])
+
+    return float(total_bits) / float(duration_sec)
+
+
+# -----------------------------------------------------------------------------
+# Public Level 3 API (wrappers)
+# -----------------------------------------------------------------------------
+
+def aac_coder_3(
+    filename_in: Union[str, Path],
+    filename_aac_coded: Optional[Union[str, Path]] = None,
+) -> AACSeq3:
+    """
+    Level-3 AAC encoder (wrapper).
+
+    Delegates to core implementation.
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename.
+        Assumption: stereo audio, sampling rate 48 kHz.
+    filename_aac_coded : Optional[Union[str, Path]]
+        Optional filename to store the encoded AAC sequence (e.g., .mat).
+
+    Returns
+    -------
+    AACSeq3
+        List of encoded frames (Level 3 schema).
+    """
+    return core_aac_coder_3(filename_in, filename_aac_coded, verbose=True)
+
+
+def i_aac_coder_3(
+    aac_seq_3: AACSeq3,
+    filename_out: Union[str, Path],
+) -> StereoSignal:
+    """
+    Level-3 AAC decoder (wrapper).
+
+    Delegates to core implementation.
+
+    Parameters
+    ----------
+    aac_seq_3 : AACSeq3
+        Encoded sequence as produced by aac_coder_3().
+    filename_out : Union[str, Path]
+        Output WAV filename. Assumption: 48 kHz, stereo.
+
+    Returns
+    -------
+    StereoSignal
+        Decoded audio samples (time-domain), stereo, shape (N, 2), dtype float64.
+    """
+    return core_aac_decoder_3(aac_seq_3, filename_out, verbose=True)
+
+
+# -----------------------------------------------------------------------------
+# Demo (Level 3)
+# -----------------------------------------------------------------------------
+
+def demo_aac_3(
+    filename_in: Union[str, Path],
+    filename_out: Union[str, Path],
+    filename_aac_coded: Optional[Union[str, Path]] = None,
+) -> Tuple[float, float, float]:
+    """
+    Demonstration for the Level-3 codec.
+
+    Runs:
+    - aac_coder_3(filename_in, filename_aac_coded)
+    - i_aac_coder_3(aac_seq_3, filename_out)
+    and computes:
+    - total SNR between original and decoded audio
+    - coded bitrate (bits/s) based on Huffman streams
+    - compression ratio (bitrate_before / bitrate_after)
+
+    Parameters
+    ----------
+    filename_in : Union[str, Path]
+        Input WAV filename (stereo, 48 kHz).
+    filename_out : Union[str, Path]
+        Output WAV filename (stereo, 48 kHz).
+    filename_aac_coded : Optional[Union[str, Path]]
+        Optional filename to store the encoded AAC sequence (e.g., .mat).
+
+    Returns
+    -------
+    Tuple[float, float, float]
+        (SNR_dB, bitrate_after_bits_per_s, compression_ratio)
+    """
+    filename_in = Path(filename_in)
+    filename_out = Path(filename_out)
+    filename_aac_coded = Path(filename_aac_coded) if filename_aac_coded else None
+
+    # Read original audio (reference) with the same validation as the codec.
+    x_ref, fs_ref = aac_read_wav_stereo_48k(filename_in)
+    if int(fs_ref) != 48000:
+        raise ValueError("Input sampling rate must be 48 kHz.")
+
+    # Encode / decode
+    aac_seq_3 = aac_coder_3(filename_in, filename_aac_coded)
+    x_hat = i_aac_coder_3(aac_seq_3, filename_out)
+
+    # Optional sanity: ensure output file exists and is readable
+    _, fs_hat = sf.read(str(filename_out), always_2d=True)
+    if int(fs_hat) != 48000:
+        raise ValueError("Decoded output sampling rate must be 48 kHz.")
+
+    # Metrics
+    s = snr_db(x_ref, x_hat)
+
+    duration = _wav_duration_seconds(filename_in)
+    bitrate_before = _bitrate_before_from_file(filename_in)
+    bitrate_after = _bitrate_after_from_aacseq(aac_seq_3, duration)
+    compression = float("inf") if bitrate_after <= 0.0 else (bitrate_before / bitrate_after)
+
+    return float(s), float(bitrate_after), float(compression)
+
+
+# -----------------------------------------------------------------------------
+# CLI
+# -----------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    # Example:
+    #   cd level_3
+    #   python -m level_3 input.wav output.wav
+    #   for example:
+    #   python -m level_3 material/LicorDeCalandraca.wav LicorDeCalandraca_out_l3.wav
+    #   or
+    #   python -m level_3 material/LicorDeCalandraca.wav LicorDeCalandraca_out_l3.wav aac_seq_3.mat
+    import sys
+
+    if len(sys.argv) not in (3, 4):
+        raise SystemExit("Usage: python -m level_3 <input.wav> <output.wav> [aac_seq_3.mat]")
+
+    in_wav = Path(sys.argv[1])
+    out_wav = Path(sys.argv[2])
+    aac_mat = Path(sys.argv[3]) if len(sys.argv) == 4 else None
+
+    print(f"Encoding/Decoding {in_wav} to {out_wav}")
+    if aac_mat is not None:
+        print(f"Storing coded sequence to {aac_mat}")
+
+    snr, bitrate, compression = demo_aac_3(in_wav, out_wav, aac_mat)
+    print(f"SNR = {snr:.3f} dB")
+    print(f"Bitrate (coded) = {bitrate:.2f} bits/s")
+    print(f"Compression ratio = {compression:.4f}")

source/level_3/material/huff_utils.py

@@ -0,0 +1,400 @@
+import numpy as np
+import scipy.io as sio
+import os
+
+# ------------------ LOAD LUT ------------------
+
+def load_LUT(mat_filename=None):
+    """
+    Loads the list of Huffman Codebooks (LUTs)
+
+    Returns:
+        huffLUT : list (index 1..11 used, index 0 unused)
+    """
+    if mat_filename is None:
+        current_dir = os.path.dirname(os.path.abspath(__file__))
+        mat_filename = os.path.join(current_dir, "huffCodebooks.mat")
+
+    mat = sio.loadmat(mat_filename)
+
+
+    huffCodebooks_raw = mat['huffCodebooks'].squeeze()
+
+    huffCodebooks = []
+    for i in range(11):
+        huffCodebooks.append(np.array(huffCodebooks_raw[i]))
+
+    # Build inverse VLC tables
+    invTable = [None] * 11
+
+    for i in range(11):
+        h = huffCodebooks[i][:, 2].astype(int)       # column 3
+        hlength = huffCodebooks[i][:, 1].astype(int) # column 2
+
+        hbin = []
+        for j in range(len(h)):
+            hbin.append(format(h[j], f'0{hlength[j]}b'))
+
+        invTable[i] = vlc_table(hbin)
+
+    # Build Huffman LUT dicts
+    huffLUT = [None] * 12  # index 0 unused
+    params = [
+        (4, 1, True),
+        (4, 1, True),
+        (4, 2, False),
+        (4, 2, False),
+        (2, 4, True),
+        (2, 4, True),
+        (2, 7, False),
+        (2, 7, False),
+        (2, 12, False),
+        (2, 12, False),
+        (2, 16, False),
+    ]
+
+    for i, (nTupleSize, maxAbs, signed) in enumerate(params, start=1):
+        huffLUT[i] = {
+            'LUT': huffCodebooks[i-1],
+            'invTable': invTable[i-1],
+            'codebook': i,
+            'nTupleSize': nTupleSize,
+            'maxAbsCodeVal': maxAbs,
+            'signedValues': signed
+        }
+
+    return huffLUT
+
+def vlc_table(code_array):
+    """
+    codeArray: list of strings, each string is a Huffman codeword (e.g. '0101')
+    returns:
+        h : NumPy array of shape (num_nodes, 3)
+            columns:
+              [ next_if_0 , next_if_1 , symbol_index ]
+    """
+    h = np.zeros((1, 3), dtype=int)
+
+    for code_index, code in enumerate(code_array, start=1):
+        word = [int(bit) for bit in code]
+        h_index = 0
+
+        for bit in word:
+            k = bit
+            next_node = h[h_index, k]
+            if next_node == 0:
+                h = np.vstack([h, [0, 0, 0]])
+                new_index = h.shape[0] - 1
+                h[h_index, k] = new_index
+                h_index = new_index
+            else:
+                h_index = next_node
+
+        h[h_index, 2] = code_index
+
+    return h
+
+# ------------------ ENCODE ------------------
+
+def encode_huff(coeff_sec, huff_LUT_list, force_codebook = None):
+    """
+    Huffman-encode a sequence of quantized coefficients.
+
+    This function selects the appropriate Huffman codebook based on the
+    maximum absolute value of the input coefficients, encodes the coefficients
+    into a binary Huffman bitstream, and returns both the bitstream and the
+    selected codebook index.
+
+    This is the Python equivalent of the MATLAB `encodeHuff.m` function used
+    in audio/image coding (e.g., scale factor band encoding). The input
+    coefficient sequence is grouped into fixed-size tuples as defined by
+    the chosen Huffman LUT. Zero-padding may be applied internally.
+
+    Parameters
+    ----------
+    coeff_sec : array_like of int
+        1-D array of quantized integer coefficients to encode.
+        Typically corresponds to a "section" or scale-factor band.
+
+    huff_LUT_list : list
+        List of Huffman lookup-table dictionaries as returned by `loadLUT()`.
+        Index 1..11 correspond to valid Huffman codebooks.
+        Index 0 is unused.
+
+    Returns
+    -------
+    huffSec : str
+        Huffman-encoded bitstream represented as a string of '0' and '1'
+        characters.
+
+    huffCodebook : int
+        Index (1..11) of the Huffman codebook used for encoding.
+        A value of 0 indicates a special all-zero section.
+    """
+    if force_codebook is not None:
+            return huff_LUT_code_1(huff_LUT_list[force_codebook], coeff_sec)
+    
+    maxAbsVal = np.max(np.abs(coeff_sec))
+
+    if maxAbsVal == 0:
+        huffCodebook = 0
+        huffSec = huff_LUT_code_0()
+
+    elif maxAbsVal == 1:
+        candidates = [1, 2]
+        huffSec1 = huff_LUT_code_1(huff_LUT_list[candidates[0]], coeff_sec)
+        huffSec2 = huff_LUT_code_1(huff_LUT_list[candidates[1]], coeff_sec)
+        if len(huffSec1) <= len(huffSec2):
+            huffSec = huffSec1
+            huffCodebook = candidates[0]
+        else:
+            huffSec = huffSec2
+            huffCodebook = candidates[1]
+
+    elif maxAbsVal == 2:
+        candidates = [3, 4]
+        huffSec1 = huff_LUT_code_1(huff_LUT_list[candidates[0]], coeff_sec)
+        huffSec2 = huff_LUT_code_1(huff_LUT_list[candidates[1]], coeff_sec)
+        if len(huffSec1) <= len(huffSec2):
+            huffSec = huffSec1
+            huffCodebook = candidates[0]
+        else:
+            huffSec = huffSec2
+            huffCodebook = candidates[1]
+
+    elif maxAbsVal in (3, 4):
+        candidates = [5, 6]
+        huffSec1 = huff_LUT_code_1(huff_LUT_list[candidates[0]], coeff_sec)
+        huffSec2 = huff_LUT_code_1(huff_LUT_list[candidates[1]], coeff_sec)
+        if len(huffSec1) <= len(huffSec2):
+            huffSec = huffSec1
+            huffCodebook = candidates[0]
+        else:
+            huffSec = huffSec2
+            huffCodebook = candidates[1]
+
+    elif maxAbsVal in (5, 6, 7):
+        candidates = [7, 8]
+        huffSec1 = huff_LUT_code_1(huff_LUT_list[candidates[0]], coeff_sec)
+        huffSec2 = huff_LUT_code_1(huff_LUT_list[candidates[1]], coeff_sec)
+        if len(huffSec1) <= len(huffSec2):
+            huffSec = huffSec1
+            huffCodebook = candidates[0]
+        else:
+            huffSec = huffSec2
+            huffCodebook = candidates[1]
+
+    elif maxAbsVal in (8, 9, 10, 11, 12):
+        candidates = [9, 10]
+        huffSec1 = huff_LUT_code_1(huff_LUT_list[candidates[0]], coeff_sec)
+        huffSec2 = huff_LUT_code_1(huff_LUT_list[candidates[1]], coeff_sec)
+        if len(huffSec1) <= len(huffSec2):
+            huffSec = huffSec1
+            huffCodebook = candidates[0]
+        else:
+            huffSec = huffSec2
+            huffCodebook = candidates[1]
+
+    elif maxAbsVal in (13, 14, 15):
+        huffCodebook = 11
+        huffSec = huff_LUT_code_1(huff_LUT_list[huffCodebook], coeff_sec)
+
+    else:
+        huffCodebook = 11
+        huffSec = huff_LUT_code_ESC(huff_LUT_list[huffCodebook], coeff_sec)
+
+    return huffSec, huffCodebook
+
+def huff_LUT_code_1(huff_LUT, coeff_sec):
+    LUT = huff_LUT['LUT']
+    nTupleSize = huff_LUT['nTupleSize']
+    maxAbsCodeVal = huff_LUT['maxAbsCodeVal']
+    signedValues = huff_LUT['signedValues']
+
+    numTuples = int(np.ceil(len(coeff_sec) / nTupleSize))
+
+    if signedValues:
+        coeff = coeff_sec + maxAbsCodeVal
+        base = 2 * maxAbsCodeVal + 1
+    else:
+        coeff = coeff_sec
+        base = maxAbsCodeVal + 1
+
+    coeffPad = np.zeros(numTuples * nTupleSize, dtype=int)
+    coeffPad[:len(coeff)] = coeff
+
+    huffSec = []
+
+    powers = base ** np.arange(nTupleSize - 1, -1, -1)
+
+    for i in range(numTuples):
+        nTuple = coeffPad[i*nTupleSize:(i+1)*nTupleSize]
+        huffIndex = int(np.abs(nTuple) @ powers)
+
+        hexVal = LUT[huffIndex, 2]
+        huffLen = LUT[huffIndex, 1]
+
+        bits = format(int(hexVal), f'0{int(huffLen)}b')
+
+        if signedValues:
+            huffSec.append(bits)
+        else:
+            signBits = ''.join('1' if v < 0 else '0' for v in nTuple)
+            huffSec.append(bits + signBits)
+
+    return ''.join(huffSec)
+
+def huff_LUT_code_0():
+    return ''
+
+def huff_LUT_code_ESC(huff_LUT, coeff_sec):
+    LUT = huff_LUT['LUT']
+    nTupleSize = huff_LUT['nTupleSize']
+    maxAbsCodeVal = huff_LUT['maxAbsCodeVal']
+
+    numTuples = int(np.ceil(len(coeff_sec) / nTupleSize))
+    base = maxAbsCodeVal + 1
+
+    coeffPad = np.zeros(numTuples * nTupleSize, dtype=int)
+    coeffPad[:len(coeff_sec)] = coeff_sec
+
+    huffSec = []
+    powers = base ** np.arange(nTupleSize - 1, -1, -1)
+
+    for i in range(numTuples):
+        nTuple = coeffPad[i*nTupleSize:(i+1)*nTupleSize]
+
+        lnTuple = nTuple.astype(float)
+        lnTuple[lnTuple == 0] = np.finfo(float).eps
+
+        N4 = np.maximum(0, np.floor(np.log2(np.abs(lnTuple))).astype(int))
+        N = np.maximum(0, N4 - 4)
+        esc = np.abs(nTuple) > 15
+
+        nTupleESC = nTuple.copy()
+        nTupleESC[esc] = np.sign(nTupleESC[esc]) * 16
+
+        huffIndex = int(np.abs(nTupleESC) @ powers)
+
+        hexVal = LUT[huffIndex, 2]
+        huffLen = LUT[huffIndex, 1]
+
+        bits = format(int(hexVal), f'0{int(huffLen)}b')
+
+        escSeq = ''
+        for k in range(nTupleSize):
+            if esc[k]:
+                escSeq += '1' * N[k]
+                escSeq += '0'
+                escSeq += format(abs(nTuple[k]) - (1 << N4[k]), f'0{N4[k]}b')
+
+        signBits = ''.join('1' if v < 0 else '0' for v in nTuple)
+        huffSec.append(bits + signBits + escSeq)
+
+    return ''.join(huffSec)
+
+# ------------------ DECODE ------------------
+
+def decode_huff(huff_sec, huff_LUT):
+    """
+    Decode a Huffman-encoded stream.
+
+    Parameters
+    ----------
+    huff_sec : array-like of int or str
+        Huffman encoded stream as a sequence of 0 and 1 (string or list/array).
+    huff_LUT : dict
+        Huffman lookup table with keys:
+            - 'invTable': inverse table (numpy array)
+            - 'codebook': codebook number
+            - 'nTupleSize': tuple size
+            - 'maxAbsCodeVal': maximum absolute code value
+            - 'signedValues': True/False
+
+    Returns
+    -------
+    decCoeffs : list of int
+        Decoded quantized coefficients.
+    """
+
+    h = huff_LUT['invTable']
+    huffCodebook = huff_LUT['codebook']
+    nTupleSize = huff_LUT['nTupleSize']
+    maxAbsCodeVal = huff_LUT['maxAbsCodeVal']
+    signedValues = huff_LUT['signedValues']
+
+    # Convert string to array of ints
+    if isinstance(huff_sec, str):
+        huff_sec = np.array([int(b) for b in huff_sec])
+
+    eos = False
+    decCoeffs = []
+    streamIndex = 0
+
+    while not eos:
+        wordbit = 0
+        r = 0  # start at root
+
+        # Decode Huffman word using inverse table
+        while True:
+            b = huff_sec[streamIndex + wordbit]
+            wordbit += 1
+            rOld = r
+            r = h[rOld, b]
+            if h[r, 0] == 0 and h[r, 1] == 0:
+                symbolIndex = h[r, 2] - 1  # zero-based
+                streamIndex += wordbit
+                break
+
+        # Decode n-tuple magnitudes
+        if signedValues:
+            base = 2 * maxAbsCodeVal + 1
+            nTupleDec = []
+            tmp = symbolIndex
+            for p in reversed(range(nTupleSize)):
+                val = tmp // (base ** p)
+                nTupleDec.append(val - maxAbsCodeVal)
+                tmp = tmp % (base ** p)
+            nTupleDec = np.array(nTupleDec)
+        else:
+            base = maxAbsCodeVal + 1
+            nTupleDec = []
+            tmp = symbolIndex
+            for p in reversed(range(nTupleSize)):
+                val = tmp // (base ** p)
+                nTupleDec.append(val)
+                tmp = tmp % (base ** p)
+            nTupleDec = np.array(nTupleDec)
+
+            # Apply sign bits
+            nTupleSignBits = huff_sec[streamIndex:streamIndex + nTupleSize]
+            nTupleSign = -(np.sign(nTupleSignBits - 0.5))
+            streamIndex += nTupleSize
+            nTupleDec = nTupleDec * nTupleSign
+
+        # Handle escape sequences
+        escIndex = np.where(np.abs(nTupleDec) == 16)[0]
+        if huffCodebook == 11 and escIndex.size > 0:
+            for idx in escIndex:
+                N = 0
+                b = huff_sec[streamIndex]
+                while b:
+                    N += 1
+                    b = huff_sec[streamIndex + N]
+                streamIndex += N +1
+                N4 = N + 4
+                escape_word = huff_sec[streamIndex:streamIndex + N4]
+                escape_value = 2 ** N4 + int("".join(map(str, escape_word)), 2)
+                nTupleDec[idx] = escape_value
+                streamIndex += N4
+            # Apply signs again
+            nTupleDec[escIndex] *= nTupleSign[escIndex]
+
+        decCoeffs.extend(nTupleDec.tolist())
+
+        if streamIndex >= len(huff_sec):
+            eos = True
+
+    return decCoeffs
+    
+