compressionkit E2A2 codec, redistributed from danjacobellis/E2A2 with the author's permission
adce33d | {"spec": "e2a2 stream layout v1 over [GGDLPC v1: unified coder (one learned causal FIR predictor per channel with arithmetic-mean fallback; one stateless pooled statistic: mean of the causal template abs differences and the last 16 coded abs residuals in scan order; two per-channel affine laws -> analytic folded GGD conditionals on the tau=2^(1/4) scale grid; canonical Huffman tables under the derived quotient split, <= 63 windowed hi values + escape at any bit depth; derived zero-run mode with elementary Golomb codes and exclusion tables, always available); inputs in [-N, N], N <= 65536; one call = one byte-padded bitstream, channel prefixes are literal bit prefixes]: two_stream = global[first scale group, whole plane, one pad] + per-macroregion detail streams (scale groups >= 1, coarse-to-fine, channel-major, one pad per region); all_detail = NO global stream, every channel per macroregion, each region decodable from its own bytes alone; one GGDLPC channel record per latent channel (global index); op-point streams are literal bit-prefixes", "version": 5, "stream_mode": "all_detail", "rank": 1, "macroregion": 256, "N": 31, "scale_groups": [[256, 0, 4], [128, 4, 12], [64, 12, 20], [32, 20, 32], [16, 32, 40]], "channels": [{"channel": 0, "mu": 0.005923485846630173, "a": 0.0, "b": 0.41763605700970285, "u": 0.37854465872652554, "v": 0.0, "wq": [0, 0], "bq": 0, "n_samples": 26376192}, {"channel": 1, "mu": -0.004251485582149235, "a": 0.0, "b": 0.3614046764239063, "u": 0.36139967115668514, "v": 0.0, "wq": [0, 0], "bq": 0, "n_samples": 26376192}, {"channel": 2, "mu": 0.009092745457721874, "a": 0.0, "b": 0.377503156607408, "u": 0.3775546601975996, "v": 0.0, "wq": [0, 0], "bq": 0, "n_samples": 26376192}, {"channel": 3, "mu": 0.014506832525331935, "a": 0.0, "b": 0.3992776171112435, "u": 0.3977903279776543, "v": 0.0, "wq": [0, 0], "bq": 0, "n_samples": 26376192}, {"channel": 4, "mu": 0.00038544229584012735, "a": 0.8871017254983561, "b": 0.40476366783415385, "u": 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"danjacobellis/librispeech:train[:45792]", "seed": 0, "ggdlpc_fit": {"N": 31, "rank": 1, "K_beta": 8, "order1": 2, "dense": true, "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "passes": ["predictor moments", "dense h(S, r) histogram"]}}, {"channels": [4, 12], "ps": 128, "stream": "detail", "slicing": "tile f=2", "rank": 1, "stream_mode": "all_detail", "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "ggdlpc_fit": {"N": 31, "rank": 1, "K_beta": 8, "order1": 2, "dense": true, "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "passes": ["predictor moments", "dense h(S, r) histogram"]}}, {"channels": [12, 20], "ps": 64, "stream": "detail", "slicing": "tile f=4", "rank": 1, "stream_mode": "all_detail", "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "ggdlpc_fit": {"N": 31, "rank": 1, "K_beta": 8, "order1": 2, "dense": true, "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "passes": ["predictor moments", "dense h(S, r) histogram"]}}, {"channels": [20, 32], "ps": 32, "stream": "detail", "slicing": "tile f=8", "rank": 1, "stream_mode": "all_detail", "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "ggdlpc_fit": {"N": 31, "rank": 1, "K_beta": 8, "order1": 2, "dense": true, "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "passes": ["predictor moments", "dense h(S, r) histogram"]}}, {"channels": [32, 40], "ps": 16, "stream": "detail", "slicing": "tile f=16", "rank": 1, "stream_mode": "all_detail", "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "ggdlpc_fit": {"N": 31, "rank": 1, "K_beta": 8, "order1": 2, "dense": true, "dataset": "danjacobellis/librispeech:train[:45792]", "seed": 0, "passes": ["predictor moments", "dense h(S, r) histogram"]}}]} |