Studio 2.2.11: preset matrices and automatic PA datasets

README.md

@@ -37,11 +37,11 @@ OpenDPD is a PyTorch framework for power amplifier (PA) modeling and digital pre
 ## What's new
 
 <!-- --8<-- [start:studio-features] -->
-**OpenDPD 2.2.10** improves Studio security and reliability: bounded uploads, faster built-in dataset browsing, safer worker startup, and hardened publishing and hosted services. Signal Analyzer supports real or complex CSV signals and connects directly to Signal Generator and Virtual PA.
+**OpenDPD 2.2.11** makes signal generation easier: 1,186 compact matrix presets, multi-preset datasets, optional ideal input filtering, automatic Virtual PA dataset creation, and CSV/ZIP downloads with a standalone PA replay script. Signal Analyzer accepts real or complex CSV signals.
 
-**Signal Generator → PA Library → PA training → DPD training/testing.** Generate a PA input, simulate its output with one of nine Virtual PAs, or use existing input/output data. Standard presets remain uncoded engineering stimuli; Wi-Fi 8 is experimental.
+**Signal Generator → PA Library → PA training → DPD training/testing.** Generate a PA input, simulate its output with one of nine Virtual PAs, or use existing input/output data. Standard presets are uncoded engineering stimuli; each capture keeps its own sample rate and length.
 
-[2.2.10 release notes](https://lab-emi.github.io/OpenDPD/releases/release-notes-2.2.10/) · [Signal Generator](https://lab-emi.github.io/OpenDPD/guides/signal-generator/) · [Signal Analyzer](https://lab-emi.github.io/OpenDPD/guides/signal-analyzer/). During the hosted trial, **2 hours of inactivity clears that IP’s temporary workspaces**; the top bar shows the expiry time.
+[2.2.11 release notes](https://lab-emi.github.io/OpenDPD/releases/release-notes-2.2.11/) · [Signal Generator](https://lab-emi.github.io/OpenDPD/guides/signal-generator/) · [Signal Analyzer](https://lab-emi.github.io/OpenDPD/guides/signal-analyzer/). During the hosted trial, **2 hours of inactivity clears that IP’s temporary workspaces**; the top bar shows the expiry time.
 <!-- --8<-- [end:studio-features] -->
 
 [Feature history](docs/whats-new.md) · [Verified platform status](docs/releases/support-matrix.md)
@@ -70,7 +70,7 @@ powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | ie
 mkdir opendpd-lab
 cd opendpd-lab
 uv venv --python 3.12
-uv pip install --python .venv "opendpd==2.2.10" --torch-backend=auto
+uv pip install --python .venv "opendpd==2.2.11" --torch-backend=auto
 uv run --no-project --python .venv opendpd gui
 ```
 
@@ -108,7 +108,7 @@ uv run --no-project --python .venv opendpd gui
 
 [PA Library guide](docs/guides/virtual-pa-library.md) · [Reading signal-chain PSD plots](docs/guides/signal-chain-spectra.md)
 
-![Studio 2.2.10: Signal Analyzer with independent spectrum and spectrogram](pics/studio-signal-analyzer.png)
+![Studio 2.2.11: compact waveform presets grouped by bandwidth, QAM and OFDMA channels](pics/studio-signal-generator.png)
 
 ## Choose your next step
 

docs/architecture/public-studio.md

@@ -403,3 +403,12 @@ The GPU service retains rootful Podman on this installation, with an explicit ca
 The guest installer moves an existing `OPENDPD_GPU_TOKEN` value into `/etc/opendpd-web-gpu.token`, readable only by root and the worker group, and stores only `OPENDPD_GPU_TOKEN_FILE` in the environment file. New installations should use the file setting directly. Keep public dataset publication disabled unless a separately reviewed submission identity and approval process are configured.
 
 The VM administrator has passwordless sudo solely inside the isolated disposable VM; the host administrator's SSH key is root-readable only. Provision the baseline from a reviewed clean image with no user captures, credentials or histories. The production installer refuses to replace an existing VM disk.
+
+
+## Multi-preset generation in 2.2.11
+
+`POST /signal-generator/batches` accepts up to 16 distinct presets and four million total samples. `POST /pa-library/datasets` validates all sources before registering any datasets, simulates each at its own sample rate, and saves a collection. Captures use ordinary versioned dataset storage so existing training/evaluation operates on one selected capture with truthful frequency metadata. The first capture is the parent; other captures refer to its ID. The parent manifest records membership, sample counts and independent sample rates. Failed registration removes only datasets created by that operation.
+
+The two new mutations have explicit public allowlist entries, schema validation, per-IP rates, shared numeric admission and aggregate disk estimates. Custom-dataset capability gating also covers the one-step endpoint. Authenticated `GET /datasets/{id}/download` returns a CSV or collection ZIP and shares heavy-read admission. `collection=false` selects a single capture/version. Export reads verify file membership and hashes; generated replay source is frozen and hash checked, never evaluated by the server. Response completion removes temporary export files. No user-supplied executable code is accepted.
+
+Deploy the same reviewed 2.2.11 commit to the API, GPU agent/container and static site after draining pending jobs. Retain source/image rollback copies; a server restart expires temporary sessions. Validate multi-preset generation, dataset navigation, authenticated ZIP download and a CUDA training/testing job after deployment.