taut.js: fxNames update

assets/disk0/tvdos/bin/taut.js

@@ -116,17 +116,17 @@ P:"UNIMPLEMENTED", // IT: panning slide. Use PanEff instead
 Q:"Retrigger    ",
 R:"Tremolo      ",
 S:"Special      ",
-S0:"UNIMPLEMENTED", // PT: Set audio filter.
+S0:"UNIMPLEMENTED", // PT: Set audio filter
 S1:"Gliss. ctrl  ",
 S2:"Sample tune  ",
 S3:"Vibrato LFO  ",
 S4:"Tremolo LFO  ",
 S5:"Panbrello LFO",
-S6:"UNIMPLEMENTED", // IT: Fine pattern delay.
-S7:"UNIMPLEMENTED", // IT: misc. functions
-S8:"Channel pan  ", // Taud: 8-bit channel panning.
-S9:"UNIMPLEMENTED", // IT: Sound control.
-SA:"UNIMPLEMENTED", // SC3: Stereo control. IT: Sample offset high twobyte.
+S6:"Fine delay   ",
+S7:"Note action  ",
+S8:"Channel pan  ", // Taud: 8-bit channel panning
+S9:"UNIMPLEMENTED", // IT: Sound control
+SA:"UNIMPLEMENTED", // SC3: Stereo control. IT: Sample offset high twobyte (not applicable because Taud has 64k limit)
 SB:"Pattern loop ",
 SC:"Note cut     ",
 SD:"Note delay   ",
@@ -135,10 +135,10 @@ SF:"Funk it      ",
 T:"Tempo        ",
 U:"Fine vibrato ",
 V:"Global volume",
-W:"UNIMPLEMENTED", // IT: Global volume slide.
-X:"UNIMPLEMENTED", // IT: 8-bit channel panning. Use PanEff or S80xx instead
+W:"G.Vol Slide  ",
+X:"UNIMPLEMENTED", // IT: 8-bit channel panning. Use S80xx instead
 Y:"Panbrello    ",
-Z:"UNIMPLEMENTED", // IT: MIDI macro.
+Z:"UNIMPLEMENTED", // IT: MIDI macro
 }
 const panFxNames = {
 0:"Set to",

it2taud.py

@@ -52,7 +52,7 @@ from taud_common import (
     EFF_K, EFF_L, EFF_M, EFF_N, EFF_O, EFF_P, EFF_Q, EFF_R, EFF_S, EFF_T,
     EFF_U, EFF_V, EFF_W, EFF_X, EFF_Y, EFF_Z,
     J_SEMI_TABLE,
-    d_arg_to_col, resample_linear, encode_cue, deduplicate_patterns,
+    d_arg_to_col, resample_linear, rescale_offset_effects, encode_cue, deduplicate_patterns,
     normalise_sample, encode_song_entry,
 )
 
@@ -1314,7 +1314,7 @@ def build_sample_inst_bin_it(samples_or_proxy: list,
 
         vprint(f"  instrument[{taud_idx}] '{s.name}' ptr:{ptr} c5spd:{s.c5_speed}")
 
-    return bytes(sample_bin) + bytes(inst_bin), offsets
+    return bytes(sample_bin) + bytes(inst_bin), offsets, ratio
 
 
 # ── Pattern builder ───────────────────────────────────────────────────────────
@@ -1682,7 +1682,7 @@ def assemble_taud(h: ITHeader, samples: list, instruments: list,
                 'dct':        inst.dct,
                 'dca':        inst.dca,
             }
-        sampleinst_raw, _ = build_sample_inst_bin_it(proxy, instr_data_by_slot)
+        sampleinst_raw, _, sample_ratio = build_sample_inst_bin_it(proxy, instr_data_by_slot)
     else:
         # Samples referenced directly; proxy is samples list (0-based, slot 0 unused)
         proxy = [None] + list(samples)
@@ -1691,7 +1691,7 @@ def assemble_taud(h: ITHeader, samples: list, instruments: list,
             for i, s in enumerate(samples)
             if s is not None
         }
-        sampleinst_raw, _ = build_sample_inst_bin_it(proxy)
+        sampleinst_raw, _, sample_ratio = build_sample_inst_bin_it(proxy)
 
     assert len(sampleinst_raw) == SAMPLEINST_SIZE
 
@@ -1723,8 +1723,11 @@ def assemble_taud(h: ITHeader, samples: list, instruments: list,
             pat_bin += build_pattern_it(cg, ch, default_pans[vi], inst_vols,
                                           amiga_mode=not h.linear_slides)
 
+    # Rescale TOP_O sample-offset args if samples were globally downsampled.
+    pat_bin = rescale_offset_effects(bytes(pat_bin), sample_ratio)
+
     orig_count   = len(taud_cue_list) * C
-    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(bytes(pat_bin), orig_count)
+    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(pat_bin, orig_count)
     vprint(f"  patterns: {orig_count} → {num_taud_pats} unique "
            f"({orig_count - num_taud_pats} deduplicated)")
 

mod2taud.py

@@ -39,7 +39,7 @@ from taud_common import (
     TOP_J, TOP_K, TOP_L, TOP_O, TOP_Q, TOP_R, TOP_S, TOP_T, TOP_U, TOP_V, TOP_Y,
     SEL_SET, SEL_UP, SEL_DOWN, SEL_FINE,
     J_SEMI_TABLE,
-    d_arg_to_col, resample_linear, encode_cue, deduplicate_patterns,
+    d_arg_to_col, resample_linear, rescale_offset_effects, encode_cue, deduplicate_patterns,
     encode_song_entry,
 )
 
@@ -546,7 +546,7 @@ def build_sample_inst_bin(samples: list) -> tuple:
         vprint(f"  instrument[{taud_idx}] '{s.name}' ptr={ptr} c2spd={s.c2spd} "
                f"vol={s.volume} loop=({ls},{le},{'on' if loop_mode else 'off'})")
 
-    return bytes(sample_bin) + bytes(inst_bin), offsets
+    return bytes(sample_bin) + bytes(inst_bin), offsets, ratio
 
 
 # ── Pattern build ────────────────────────────────────────────────────────────
@@ -704,7 +704,7 @@ def assemble_taud(mod: dict) -> bytes:
     relocate_late_note_delays(patterns, order_list, n_channels, init_speed)
 
     vprint("  building sample/instrument bin…")
-    sampleinst_raw, _offsets = build_sample_inst_bin(samples)
+    sampleinst_raw, _offsets, sample_ratio = build_sample_inst_bin(samples)
     assert len(sampleinst_raw) == SAMPLEINST_SIZE
 
     compressed = gzip.compress(sampleinst_raw, compresslevel=9, mtime=0)
@@ -742,9 +742,12 @@ def assemble_taud(mod: dict) -> bytes:
             pat_bin += build_pattern(grid, ch, default_pan, inst_vols)
     assert len(pat_bin) == n_patterns * n_channels * PATTERN_BYTES
 
+    # Rescale TOP_O sample-offset args if samples were globally downsampled.
+    pat_bin = rescale_offset_effects(bytes(pat_bin), sample_ratio)
+
     vprint("  deduplicating patterns…")
     orig_count = n_patterns * n_channels
-    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(bytes(pat_bin), orig_count)
+    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(pat_bin, orig_count)
     vprint(f"  patterns: {orig_count} → {num_taud_pats} unique "
            f"({orig_count - num_taud_pats} deduplicated)")
 

s3m2taud.py

@@ -43,7 +43,7 @@ from taud_common import (
     EFF_K, EFF_L, EFF_M, EFF_N, EFF_O, EFF_P, EFF_Q, EFF_R, EFF_S, EFF_T,
     EFF_U, EFF_V, EFF_W, EFF_X, EFF_Y, EFF_Z,
     J_SEMI_TABLE,
-    d_arg_to_col, resample_linear, encode_cue, deduplicate_patterns,
+    d_arg_to_col, resample_linear, rescale_offset_effects, encode_cue, deduplicate_patterns,
     normalise_sample, encode_song_entry,
 )
 
@@ -528,7 +528,7 @@ def build_sample_inst_bin(instruments: list) -> tuple:
         if inst.c2spd > 65535:
             vprint(f"  warning: sampling rate of '{inst.name}' exceeds 65535 (got '{inst.c2spd}')")
 
-    return bytes(sample_bin) + bytes(inst_bin), offsets
+    return bytes(sample_bin) + bytes(inst_bin), offsets, ratio
 
 
 def _default_channel_pan(ch_setting: int) -> int:
@@ -740,7 +740,7 @@ def assemble_taud(h: S3MHeader, instruments: list, patterns: list) -> bytes:
 
     # Build sample+instrument bin
     vprint("  building sample/instrument bin…")
-    sampleinst_raw, _offsets = build_sample_inst_bin(instruments)
+    sampleinst_raw, _offsets, sample_ratio = build_sample_inst_bin(instruments)
     assert len(sampleinst_raw) == SAMPLEINST_SIZE
 
     # Compress
@@ -787,10 +787,13 @@ def assemble_taud(h: S3MHeader, instruments: list, patterns: list) -> bytes:
                                       inst_vols, amiga_mode=not h.linear_slides)
     assert len(pat_bin) == num_taud_pats * PATTERN_BYTES
 
+    # Rescale TOP_O sample-offset args if samples were globally downsampled.
+    pat_bin = rescale_offset_effects(bytes(pat_bin), sample_ratio)
+
     # Deduplicate identical patterns
     vprint("  deduplicating patterns…")
     orig_count = num_taud_pats
-    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(bytes(pat_bin), orig_count)
+    pat_bin, pat_remap, num_taud_pats = deduplicate_patterns(pat_bin, orig_count)
     vprint(f"  patterns: {orig_count} → {num_taud_pats} unique ({orig_count - num_taud_pats} deduplicated)")
 
     # Cue sheet (using remapped pattern indices)

taud_common.py

@@ -131,6 +131,27 @@ def resample_linear(data: bytes, ratio: float) -> bytes:
     return bytes(out)
 
 
+def rescale_offset_effects(pat_bin: bytes, ratio: float) -> bytes:
+    """Scale TOP_O sample-offset args in raw pattern bytes by `ratio`.
+
+    Each row is 8 bytes; byte 5 is the effect opcode, bytes 6-7 are the
+    little-endian 16-bit arg (= byte offset into the sample). When the
+    sample bin overflows and every sample is downsampled globally, the
+    offset commands must shrink the same amount or O-jumps land past
+    the new end of sample.
+    """
+    if ratio == 1.0 or not pat_bin:
+        return pat_bin
+    out = bytearray(pat_bin)
+    for i in range(0, len(out) - 7, 8):
+        if out[i + 5] == TOP_O:
+            arg = out[i + 6] | (out[i + 7] << 8)
+            arg = max(0, min(0xFFFF, int(arg * ratio + 0.5)))
+            out[i + 6] = arg & 0xFF
+            out[i + 7] = (arg >> 8) & 0xFF
+    return bytes(out)
+
+
 def encode_cue(patterns12: list, instruction: int) -> bytearray:
     """Encode a 32-byte cue entry for up to 20 voices with 12-bit pattern numbers."""
     pats = list(patterns12) + [0xFFF] * NUM_VOICES