qoherent/ria-toolkit-oss
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ben 2026-03-31 13:51:10 -04:00
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31 changed files with 2562 additions and 370 deletions
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20
CHANGELOG.md Normal file
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@ -0,0 +1,20 @@
# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
---
## [0.1.1] - 2026-03-20
### Added
- **Campaign orchestration** — new `orchestration` module that manages the full lifecycle of an RF data collection campaign: SDR capture, automatic labeling, QA checks, and dataset packaging.
- **HTTP inference server** — `ria-server` command starts a REST API server for deploying campaigns and controlling live inference from external systems such as the RIA Hub platform.
- **Campaign CLI** — `ria campaign` commands for starting, monitoring, and managing campaigns from the terminal.
### Changed
- **Visualization layout** — recording and dataset views have been reformatted with improved sizing, repositioned titles, and updated Qoherent branding.
---

645
poetry.lock generated
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[[package]] [[package]]
@ -666,19 +682,19 @@ test = ["pytest (>=6)"]
[[package]] [[package]]
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description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
optional = false optional = false
python-versions = ">=3.10" python-versions = ">=3.10"
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{file = "tomli-2.4.0-cp314-cp314t-win_amd64.whl", hash = "sha256:2add28aacc7425117ff6364fe9e06a183bb0251b03f986df0e78e974047571fd"}, {file = "tomli-2.4.1-cp314-cp314t-win_amd64.whl", hash = "sha256:2c1c351919aca02858f740c6d33adea0c5deea37f9ecca1cc1ef9e884a619d26"},
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{file = "tomli-2.4.0-py3-none-any.whl", hash = "sha256:1f776e7d669ebceb01dee46484485f43a4048746235e683bcdffacdf1fb4785a"}, {file = "tomli-2.4.1-py3-none-any.whl", hash = "sha256:0d85819802132122da43cb86656f8d1f8c6587d54ae7dcaf30e90533028b49fe"},
{file = "tomli-2.4.0.tar.gz", hash = "sha256:aa89c3f6c277dd275d8e243ad24f3b5e701491a860d5121f2cdd399fbb31fc9c"}, {file = "tomli-2.4.1.tar.gz", hash = "sha256:7c7e1a961a0b2f2472c1ac5b69affa0ae1132c39adcb67aba98568702b9cc23f"},
] ]
[[package]] [[package]]
@ -2964,14 +3070,14 @@ files = [
[[package]] [[package]]
name = "tox" name = "tox"
version = "4.49.1" version = "4.52.0"
description = "tox is a generic virtualenv management and test command line tool" description = "tox is a generic virtualenv management and test command line tool"
optional = false optional = false
python-versions = ">=3.10" python-versions = ">=3.10"
groups = ["test"] groups = ["test"]
files = [ files = [
{file = "tox-4.49.1-py3-none-any.whl", hash = "sha256:6dd2d7d4e4fd5895ce4ea20e258fce0d4b81e914b697d116a5ab0365f8303bad"}, {file = "tox-4.52.0-py3-none-any.whl", hash = "sha256:624d8ea4a8c6d5e8d168eedf0e318d736fb22e83ca83137d001ac65ffdec46fd"},
{file = "tox-4.49.1.tar.gz", hash = "sha256:4130d02e1d53648d7107d121ed79f69a27b717817c5e9da521d50319dd261212"}, {file = "tox-4.52.0.tar.gz", hash = "sha256:6054abf5c8b61d58776fbec991f9bf0d34bb883862beb93d2fe55601ef3977c9"},
] ]
[package.dependencies] [package.dependencies]
@ -2982,6 +3088,7 @@ packaging = ">=26"
platformdirs = ">=4.9.4" platformdirs = ">=4.9.4"
pluggy = ">=1.6" pluggy = ">=1.6"
pyproject-api = ">=1.10" pyproject-api = ">=1.10"
python-discovery = ">=1.2.1"
tomli = {version = ">=2.4", markers = "python_version < \"3.11\""} tomli = {version = ">=2.4", markers = "python_version < \"3.11\""}
tomli-w = ">=1.2" tomli-w = ">=1.2"
typing-extensions = {version = ">=4.15", markers = "python_version < \"3.11\""} typing-extensions = {version = ">=4.15", markers = "python_version < \"3.11\""}
@ -3036,7 +3143,7 @@ version = "2.6.3"
description = "HTTP library with thread-safe connection pooling, file post, and more." description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["docs"] groups = ["agent", "docs"]
files = [ files = [
{file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"},
{file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"},
@ -3050,14 +3157,14 @@ zstd = ["backports-zstd (>=1.0.0) ; python_version < \"3.14\""]
[[package]] [[package]]
name = "uvicorn" name = "uvicorn"
version = "0.41.0" version = "0.42.0"
description = "The lightning-fast ASGI server." description = "The lightning-fast ASGI server."
optional = false optional = false
python-versions = ">=3.10" python-versions = ">=3.10"
groups = ["docs", "server", "test"] groups = ["docs", "server", "test"]
files = [ files = [
{file = "uvicorn-0.41.0-py3-none-any.whl", hash = "sha256:29e35b1d2c36a04b9e180d4007ede3bcb32a85fbdfd6c6aeb3f26839de088187"}, {file = "uvicorn-0.42.0-py3-none-any.whl", hash = "sha256:96c30f5c7abe6f74ae8900a70e92b85ad6613b745d4879eb9b16ccad15645359"},
{file = "uvicorn-0.41.0.tar.gz", hash = "sha256:09d11cf7008da33113824ee5a1c6422d89fbc2ff476540d69a34c87fab8b571a"}, {file = "uvicorn-0.42.0.tar.gz", hash = "sha256:9b1f190ce15a2dd22e7758651d9b6d12df09a13d51ba5bf4fc33c383a48e1775"},
] ]
[package.dependencies] [package.dependencies]
@ -3355,4 +3462,4 @@ files = [
[metadata] [metadata]
lock-version = "2.1" lock-version = "2.1"
python-versions = ">=3.10" python-versions = ">=3.10"
content-hash = "69822bd89a48fd8e1cf248818ef298b1c105b975f2f9e912d570fada5e723480" content-hash = "ad11d373747eff2d79496dcd3b575c40d9418dc2d3ad9617eab942285e3768a4"

7
pyproject.toml
View File

@ -95,6 +95,12 @@ sphinx = "^7.2.6"
sphinx-rtd-theme = "^2.0.0" sphinx-rtd-theme = "^2.0.0"
sphinx-autobuild = "^2024.2.4" sphinx-autobuild = "^2024.2.4"
[tool.poetry.group.agent]
optional = true
[tool.poetry.group.agent.dependencies]
requests = ">=2.28,<3.0"
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]
flake8 = "^7.1.0" flake8 = "^7.1.0"
black = "^24.3.0" black = "^24.3.0"
@ -110,6 +116,7 @@ pylint = "^3.2.6" # For pyreverse, to automate the creation of UML diagrams
ria = "ria_toolkit_oss_cli.cli:cli" ria = "ria_toolkit_oss_cli.cli:cli"
ria-tools = "ria_toolkit_oss_cli.cli:cli" ria-tools = "ria_toolkit_oss_cli.cli:cli"
ria-server = "ria_toolkit_oss.server.cli:serve" ria-server = "ria_toolkit_oss.server.cli:serve"
ria-agent = "ria_toolkit_oss.agent:main"
[tool.poetry.group.server.dependencies] [tool.poetry.group.server.dependencies]
fastapi = ">=0.111,<1.0" fastapi = ">=0.111,<1.0"

462
src/ria_toolkit_oss/agent.py Normal file
View File

@ -0,0 +1,462 @@
"""RT-OSS Node Agent — connects to RIA Hub and dispatches work to local hardware.
The agent runs on any machine with an SDR attached and connects **outbound** to
RIA Hub. No inbound ports need to be opened on the user's machine, and the
connection works identically through NAT, corporate firewalls, or a Pi on a
cellular link.
Usage::
ria-agent \\
--hub https://riahub.company.com \\
--key <api-key> \\
--name lab-bench-1 \\
[--device plutosdr] \\
[--insecure]
The agent:
1. Registers with RIA Hub and receives a ``node_id``.
2. Sends a heartbeat every 30 s so the hub knows it is online.
3. Long-polls ``GET /orchestrator/nodes/{id}/commands`` (30 s timeout).
4. Executes received campaigns via :class:`ria_toolkit_oss.orchestration.executor.CampaignExecutor`.
5. Uploads recordings to the hub via chunked POST, keeping each request
under 50 MB so it passes through Cloudflare without needing the bypass
subdomain.
6. Deregisters cleanly on SIGINT / SIGTERM.
"""
from __future__ import annotations
import logging
import math
import os
import signal
import sys
import threading
import time
import uuid
from typing import Any
logger = logging.getLogger("ria_agent")
# ---------------------------------------------------------------------------
# Tuneable constants
# ---------------------------------------------------------------------------
_HEARTBEAT_INTERVAL = 30 # seconds between heartbeats
_POLL_TIMEOUT = 30 # server-side long-poll duration
_POLL_CLIENT_TIMEOUT = 40 # client read timeout — slightly longer than server
_RECONNECT_PAUSE = 5 # seconds to wait after a poll error before retrying
_CHUNK_SIZE = 50 * 1024 * 1024 # 50 MB — well below Cloudflare's 100 MB limit
_DIRECT_THRESHOLD = 90 * 1024 * 1024 # files above this use chunked upload
# ---------------------------------------------------------------------------
# Agent
# ---------------------------------------------------------------------------
class NodeAgent:
"""Outbound-connecting agent that bridges RIA Hub to local SDR hardware.
All network I/O is initiated by the agent (outbound). RIA Hub never opens
a connection back to the agent's machine.
"""
def __init__(
self,
hub_url: str,
api_key: str,
name: str,
sdr_device: str = "unknown",
insecure: bool = False,
) -> None:
self.hub_url = hub_url.rstrip("/")
self.api_key = api_key
self.name = name
self.sdr_device = sdr_device
self.insecure = insecure
self.node_id: str | None = None
self._stop = threading.Event()
try:
import ria_toolkit_oss
self._ria_version: str = getattr(ria_toolkit_oss, "__version__", "unknown")
except Exception:
self._ria_version = "unknown"
# ------------------------------------------------------------------
# Public entry point
# ------------------------------------------------------------------
def run(self) -> None:
"""Register, start the heartbeat thread, and enter the command loop.
Blocks until SIGINT or SIGTERM is received.
"""
self._register()
def _shutdown(sig: int, _frame: Any) -> None:
logger.info("Shutdown signal received — stopping agent")
self._stop.set()
signal.signal(signal.SIGINT, _shutdown)
signal.signal(signal.SIGTERM, _shutdown)
hb = threading.Thread(target=self._heartbeat_loop, daemon=True, name="ria-agent-heartbeat")
hb.start()
logger.info("Agent %r online (node_id=%s, hub=%s)", self.name, self.node_id, self.hub_url)
try:
self._command_loop()
finally:
self._stop.set()
self._deregister()
# ------------------------------------------------------------------
# Registration
# ------------------------------------------------------------------
def _register(self) -> None:
resp = self._post(
"/orchestrator/nodes/register",
json={
"name": self.name,
"sdr_device": self.sdr_device,
"ria_toolkit_version": self._ria_version,
"capabilities": ["inference", "campaign"],
},
timeout=15,
)
resp.raise_for_status()
self.node_id = resp.json()["node_id"]
logger.info("Registered as %r (node_id=%s)", self.name, self.node_id)
def _deregister(self) -> None:
if not self.node_id:
return
try:
self._delete(f"/orchestrator/nodes/{self.node_id}", timeout=10)
logger.info("Deregistered %s", self.node_id)
except Exception as exc:
logger.debug("Deregister failed (ignored on shutdown): %s", exc)
# ------------------------------------------------------------------
# Heartbeat thread
# ------------------------------------------------------------------
def _heartbeat_loop(self) -> None:
while not self._stop.wait(_HEARTBEAT_INTERVAL):
try:
resp = self._post(f"/orchestrator/nodes/{self.node_id}/heartbeat", timeout=10)
if resp.status_code == 404:
logger.warning("Heartbeat got 404 — hub lost registration, re-registering")
self._register()
except Exception as exc:
logger.warning("Heartbeat failed: %s", exc)
# ------------------------------------------------------------------
# Command poll loop
# ------------------------------------------------------------------
def _command_loop(self) -> None:
while not self._stop.is_set():
try:
resp = self._get(
f"/orchestrator/nodes/{self.node_id}/commands",
timeout=_POLL_CLIENT_TIMEOUT,
)
if resp.status_code == 204:
# No command within the timeout window — loop immediately.
continue
if resp.status_code == 404:
logger.warning("Command poll got 404 — re-registering")
self._register()
continue
resp.raise_for_status()
cmd = resp.json()
logger.info("Received command: %s", cmd.get("command"))
self._dispatch(cmd)
except Exception as exc:
if not self._stop.is_set():
logger.warning("Command poll error: %s — retrying in %ds", exc, _RECONNECT_PAUSE)
time.sleep(_RECONNECT_PAUSE)
# ------------------------------------------------------------------
# Command dispatch
# ------------------------------------------------------------------
def _dispatch(self, cmd: dict) -> None:
command = cmd.get("command")
if command == "run_campaign":
campaign_id: str = cmd.get("campaign_id") or str(uuid.uuid4())
config_dict: dict = cmd.get("payload") or {}
threading.Thread(
target=self._run_campaign,
args=(campaign_id, config_dict),
daemon=True,
name=f"campaign-{campaign_id[:8]}",
).start()
else:
logger.warning("Unknown command %r — ignored", command)
# ------------------------------------------------------------------
# Campaign execution
# ------------------------------------------------------------------
def _run_campaign(self, campaign_id: str, config_dict: dict) -> None:
try:
from ria_toolkit_oss.orchestration.campaign import CampaignConfig
from ria_toolkit_oss.orchestration.executor import CampaignExecutor
except ImportError as exc:
logger.error(
"Campaign %s cannot start — ria_toolkit_oss not fully installed: %s",
campaign_id[:8],
exc,
)
return
logger.info("Campaign %s starting", campaign_id[:8])
try:
config = CampaignConfig.from_dict(config_dict)
executor = CampaignExecutor(config)
result = executor.run()
logger.info("Campaign %s completed — uploading recordings", campaign_id[:8])
self._upload_recordings(campaign_id, config, result)
except Exception as exc:
logger.error("Campaign %s failed: %s", campaign_id[:8], exc)
# ------------------------------------------------------------------
# Recording upload (chunked for large files)
# ------------------------------------------------------------------
def _upload_recordings(self, campaign_id: str, config: Any, result: Any) -> None:
output_repo: str | None = getattr(getattr(config, "output", None), "repo", None)
if not output_repo or "/" not in output_repo:
logger.warning("Campaign %s: no output.repo — skipping upload", campaign_id[:8])
return
repo_owner, repo_name = output_repo.split("/", 1)
base_url = f"{self.hub_url}/datasets/upload"
steps = getattr(result, "steps", None) or []
for step in steps:
output_path: str | None = getattr(step, "output_path", None)
if not output_path:
continue
device_id: str = getattr(step, "transmitter_id", "") or ""
for fpath in _sigmf_files(output_path):
filename = os.path.basename(fpath)
metadata = {
"filename": filename,
"repo_owner": repo_owner,
"repo_name": repo_name,
"device_id": device_id,
"campaign_id": campaign_id,
}
try:
resp_data = self._upload_file(base_url, fpath, metadata)
logger.info(
"Campaign %s: uploaded %s (oid=%s)",
campaign_id[:8],
filename,
resp_data.get("oid", "?"),
)
except Exception as exc:
logger.warning("Campaign %s: upload of %s failed: %s", campaign_id[:8], filename, exc)
def _upload_file(self, base_url: str, file_path: str, metadata: dict) -> dict:
"""Upload *file_path*, choosing chunked or direct path based on file size."""
import requests as _requests
size = os.path.getsize(file_path)
filename = os.path.basename(file_path)
headers = {"X-API-Key": self.api_key}
verify = not self.insecure
# Small files: single POST (unchanged endpoint, no assembly needed server-side).
if size <= _DIRECT_THRESHOLD:
with open(file_path, "rb") as fh:
resp = _requests.post(
base_url,
headers=headers,
files={"file": (filename, fh)},
data=metadata,
timeout=300,
verify=verify,
)
resp.raise_for_status()
return resp.json()
# Large files: chunked upload — each request is ≤ 50 MB.
total_chunks = math.ceil(size / _CHUNK_SIZE)
upload_id = str(uuid.uuid4())
chunk_url = base_url + "/chunk"
logger.info(
"Chunked upload: %s (%d bytes, %d × %d MB chunks)",
filename,
size,
total_chunks,
_CHUNK_SIZE // (1024 * 1024),
)
resp_data: dict = {}
with open(file_path, "rb") as fh:
for i in range(total_chunks):
chunk = fh.read(_CHUNK_SIZE)
resp = _requests.post(
chunk_url,
headers=headers,
files={"file": (filename, chunk, "application/octet-stream")},
data={
**metadata,
"upload_id": upload_id,
"chunk_index": i,
"total_chunks": total_chunks,
},
timeout=120,
verify=verify,
)
if not resp.ok:
raise RuntimeError(
f"Chunk {i + 1}/{total_chunks} failed: " f"HTTP {resp.status_code}: {resp.text[:300]}"
)
resp_data = resp.json()
logger.debug("Chunk %d/%d uploaded", i + 1, total_chunks)
return resp_data
# ------------------------------------------------------------------
# HTTP helpers
# ------------------------------------------------------------------
def _get(self, path: str, **kwargs: Any):
import requests as _requests
return _requests.get(
f"{self.hub_url}{path}",
headers={"X-API-Key": self.api_key},
verify=not self.insecure,
**kwargs,
)
def _post(self, path: str, **kwargs: Any):
import requests as _requests
return _requests.post(
f"{self.hub_url}{path}",
headers={"X-API-Key": self.api_key},
verify=not self.insecure,
**kwargs,
)
def _delete(self, path: str, **kwargs: Any):
import requests as _requests
return _requests.delete(
f"{self.hub_url}{path}",
headers={"X-API-Key": self.api_key},
verify=not self.insecure,
**kwargs,
)
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _sigmf_files(data_path: str) -> list[str]:
"""Return paths to both SigMF files (.sigmf-data and .sigmf-meta) for a recording."""
candidates = [data_path]
if data_path.endswith(".sigmf-data"):
candidates.append(data_path[: -len(".sigmf-data")] + ".sigmf-meta")
return [p for p in candidates if os.path.exists(p)]
# ---------------------------------------------------------------------------
# CLI entry point
# ---------------------------------------------------------------------------
def main() -> None:
import argparse
parser = argparse.ArgumentParser(
prog="ria-agent",
description=(
"RT-OSS Node Agent — connects outbound to RIA Hub and executes "
"campaigns / inference on local SDR hardware."
),
)
parser.add_argument(
"--hub",
required=True,
metavar="URL",
help="RIA Hub base URL, e.g. https://riahub.company.com",
)
parser.add_argument(
"--key",
required=True,
metavar="API_KEY",
help="Shared API key (must match [wac] API_KEY in the hub's app.ini)",
)
parser.add_argument(
"--name",
required=True,
metavar="NAME",
help='Human-readable name shown in the Target Node dropdown, e.g. "lab-bench-1"',
)
parser.add_argument(
"--device",
default="unknown",
metavar="SDR",
help=(
"SDR device type reported to the hub (informational only). "
"Examples: plutosdr, usrp_b210, rtlsdr, mock. Default: unknown"
),
)
parser.add_argument(
"--insecure",
action="store_true",
help="Disable TLS certificate verification (dev/self-signed certs only)",
)
parser.add_argument(
"--log-level",
default="INFO",
choices=["DEBUG", "INFO", "WARNING", "ERROR"],
help="Logging verbosity (default: INFO)",
)
args = parser.parse_args()
logging.basicConfig(
level=getattr(logging, args.log_level),
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
stream=sys.stderr,
)
# Warn loudly if --insecure is used outside of development.
if args.insecure:
logger.warning(
"--insecure disables TLS certificate verification. "
"Only use this for local development with self-signed certs."
)
agent = NodeAgent(
hub_url=args.hub,
api_key=args.key,
name=args.name,
sdr_device=args.device,
insecure=args.insecure,
)
agent.run()
if __name__ == "__main__":
main()

6
src/ria_toolkit_oss/datatypes/datasets/h5helpers.py
View File

@ -109,14 +109,11 @@ def copy_file(original_source: str | os.PathLike, new_source: str | os.PathLike)
:return: None :return: None
""" """
original_file = h5py.File(original_source, "r") with h5py.File(original_source, "r") as original_file:
with h5py.File(new_source, "w") as new_file: with h5py.File(new_source, "w") as new_file:
for key in original_file.keys(): for key in original_file.keys():
original_file.copy(key, new_file) original_file.copy(key, new_file)
original_file.close()
def make_empty_clone(original_source: str | os.PathLike, new_source: str | os.PathLike, example_length: int) -> None: def make_empty_clone(original_source: str | os.PathLike, new_source: str | os.PathLike, example_length: int) -> None:
"""Creates a new HDF5 file with the same structure but will leave metadata and dataset empty for operations. """Creates a new HDF5 file with the same structure but will leave metadata and dataset empty for operations.
@ -218,4 +215,3 @@ def overwrite_file(source: str | os.PathLike, new_data: np.ndarray) -> None:
ds_name = tuple(f.keys())[0] ds_name = tuple(f.keys())[0]
del f[ds_name] del f[ds_name]
f.create_dataset(ds_name, data=new_data) f.create_dataset(ds_name, data=new_data)
f.close()

6
src/ria_toolkit_oss/datatypes/datasets/iq_dataset.py
View File

@ -169,8 +169,10 @@ class IQDataset(RadioDataset, ABC):
""" """
if split_factor is not None and example_length is not None: if split_factor is not None and example_length is not None:
# Raise warning and use split factor # Warn and use split factor
raise Warning("split_factor and example_length should not both be specified.") import warnings
warnings.warn("split_factor and example_length should not both be specified.")
if not inplace: if not inplace:
# ds = self.create_new_dataset(example_length=example_length) # ds = self.create_new_dataset(example_length=example_length)

20
src/ria_toolkit_oss/datatypes/recording.py
View File

@ -393,6 +393,7 @@ class Recording:
""" """
if key not in self.metadata: if key not in self.metadata:
self.add_to_metadata(key=key, value=value) self.add_to_metadata(key=key, value=value)
return
if not _is_jsonable(value): if not _is_jsonable(value):
raise ValueError("Value must be JSON serializable.") raise ValueError("Value must be JSON serializable.")
@ -601,7 +602,7 @@ class Recording:
>>> recording = Recording(data=samples, metadata=metadata) >>> recording = Recording(data=samples, metadata=metadata)
>>> recording.to_wav() >>> recording.to_wav()
""" """
from utils.io.recording import to_wav from ria_toolkit_oss.io.recording import to_wav
return to_wav( return to_wav(
recording=self, recording=self,
@ -651,7 +652,7 @@ class Recording:
>>> recording = Recording(data=samples, metadata=metadata) >>> recording = Recording(data=samples, metadata=metadata)
>>> recording.to_blue() >>> recording.to_blue()
""" """
from utils.io.recording import to_blue from ria_toolkit_oss.io.recording import to_blue
return to_blue(recording=self, filename=filename, path=path, data_format=data_format, overwrite=overwrite) return to_blue(recording=self, filename=filename, path=path, data_format=data_format, overwrite=overwrite)
@ -702,7 +703,14 @@ class Recording:
data = self.data[:, start_sample:end_sample] data = self.data[:, start_sample:end_sample]
new_annotations = copy.deepcopy(self.annotations) new_annotations = copy.deepcopy(self.annotations)
trimmed_annotations = []
for annotation in new_annotations: for annotation in new_annotations:
# skip annotations entirely outside the trim window
if annotation.sample_start + annotation.sample_count <= start_sample:
continue
if annotation.sample_start >= end_sample:
continue
# trim annotation if it goes outside the trim boundaries # trim annotation if it goes outside the trim boundaries
if annotation.sample_start < start_sample: if annotation.sample_start < start_sample:
annotation.sample_count = annotation.sample_count - (start_sample - annotation.sample_start) annotation.sample_count = annotation.sample_count - (start_sample - annotation.sample_start)
@ -713,8 +721,9 @@ class Recording:
# shift annotation to align with the new start point # shift annotation to align with the new start point
annotation.sample_start = annotation.sample_start - start_sample annotation.sample_start = annotation.sample_start - start_sample
trimmed_annotations.append(annotation)
return Recording(data=data, metadata=self.metadata, annotations=new_annotations) return Recording(data=data, metadata=self.metadata, annotations=trimmed_annotations)
def normalize(self) -> Recording: def normalize(self) -> Recording:
"""Scale the recording data, relative to its maximum value, so that the magnitude of the maximum sample is 1. """Scale the recording data, relative to its maximum value, so that the magnitude of the maximum sample is 1.
@ -743,7 +752,10 @@ class Recording:
>>> print(numpy.max(numpy.abs(normalized_recording.data))) >>> print(numpy.max(numpy.abs(normalized_recording.data)))
1 1
""" """
scaled_data = self.data / np.max(abs(self.data)) max_val = np.max(abs(self.data))
if max_val == 0:
raise ValueError("Cannot normalize a recording with all-zero data.")
scaled_data = self.data / max_val
return Recording(data=scaled_data, metadata=self.metadata, annotations=self.annotations) return Recording(data=scaled_data, metadata=self.metadata, annotations=self.annotations)
def __len__(self) -> int: def __len__(self) -> int:

75
src/ria_toolkit_oss/io/recording.py
View File

@ -4,10 +4,12 @@ Utilities for input/output operations on the ria_toolkit_oss.datatypes.Recording
import datetime import datetime
import datetime as dt import datetime as dt
import json
import numbers import numbers
import os import os
import re import re
import struct import struct
import warnings
from datetime import timezone from datetime import timezone
from typing import Any, List, Optional from typing import Any, List, Optional
@ -91,15 +93,35 @@ def to_npy(
metadata = recording.metadata metadata = recording.metadata
annotations = recording.annotations annotations = recording.annotations
with open(file=fullpath, mode="wb") as f: # Serialize metadata and annotations as JSON to avoid pickle-based deserialization.
np.save(f, data) # JSON is safe; pickle allows arbitrary code execution when loading untrusted files.
np.save(f, metadata) metadata_bytes = json.dumps(convert_to_serializable(metadata)).encode()
np.save(f, annotations) annotations_bytes = json.dumps([a.__dict__ for a in annotations]).encode()
with open(file=fullpath, mode="wb") as f:
# Write format version marker first so from_npy can detect the safe JSON format.
np.save(f, np.array("ria-toolkit-oss-v2"))
np.save(f, data)
np.save(f, np.frombuffer(metadata_bytes, dtype=np.uint8))
np.save(f, np.frombuffer(annotations_bytes, dtype=np.uint8))
# print(f"Saved recording to {os.getcwd()}/{fullpath}")
return str(fullpath) return str(fullpath)
_NPY_MAGIC = b"\x93NUMPY"
def _check_npy_magic(filepath: str) -> None:
"""Raise ValueError if the file does not start with the NumPy magic bytes."""
try:
with open(filepath, "rb") as f:
header = f.read(6)
except OSError as e:
raise IOError(f"Cannot open file for validation: {filepath}") from e
if header != _NPY_MAGIC:
raise ValueError(f"File does not appear to be a valid NumPy .npy file (bad magic bytes): {filepath}")
def from_npy(file: os.PathLike | str, legacy: bool = False) -> Recording: def from_npy(file: os.PathLike | str, legacy: bool = False) -> Recording:
"""Load a recording from a ``.npy`` binary file. """Load a recording from a ``.npy`` binary file.
@ -126,10 +148,33 @@ def from_npy(file: os.PathLike | str, legacy: bool = False) -> Recording:
if legacy: if legacy:
return from_npy_legacy(filename) return from_npy_legacy(filename)
_check_npy_magic(filename)
with open(file=filename, mode="rb") as f: with open(file=filename, mode="rb") as f:
data = np.load(f, allow_pickle=True) first = np.load(f, allow_pickle=False)
metadata = np.load(f, allow_pickle=True)
metadata = metadata.tolist() if first.ndim == 0 and first.dtype.kind in ("U", "S") and str(first) == "ria-toolkit-oss-v2":
# Safe JSON format written by current to_npy.
data = np.load(f, allow_pickle=False)
raw_meta = np.load(f, allow_pickle=False)
metadata = json.loads(raw_meta.tobytes().decode())
try:
raw_ann = np.load(f, allow_pickle=False)
ann_list = json.loads(raw_ann.tobytes().decode())
from ria_toolkit_oss.datatypes.annotation import Annotation
annotations = [Annotation(**a) for a in ann_list]
except EOFError:
annotations = []
else:
# Legacy pickle-based format. Only load files from trusted sources.
warnings.warn(
"Loading .npy file in legacy pickle format — only load files from trusted sources. "
"Re-save with to_npy() to upgrade to the safe JSON format.",
stacklevel=2,
)
data = first # already loaded without pickle (numeric array)
metadata = np.load(f, allow_pickle=True).tolist()
try: try:
annotations = list(np.load(f, allow_pickle=True)) annotations = list(np.load(f, allow_pickle=True))
except EOFError: except EOFError:
@ -171,14 +216,20 @@ def from_npy_legacy(file: os.PathLike | str) -> Recording:
# Rebuild with .npy extension. # Rebuild with .npy extension.
filename = str(filename) + ".npy" filename = str(filename) + ".npy"
warnings.warn(
"from_npy_legacy uses pickle deserialization for extended metadata — only load files from trusted sources.",
stacklevel=2,
)
_check_npy_magic(filename)
with open(filename, "rb") as f: with open(filename, "rb") as f:
# Read IQ data (2, N) format # Read IQ data (2, N) format
iqdata = np.load(f) iqdata = np.load(f, allow_pickle=False)
# Read basic metadata array [center_freq, rec_length, decimation, sample_rate] # Read basic metadata array [center_freq, rec_length, decimation, sample_rate]
meta = np.load(f) meta = np.load(f, allow_pickle=False)
# Read extended metadata dict # Read extended metadata dict (legacy format requires pickle)
extended_meta = np.load(f, allow_pickle=True)[0] extended_meta = np.load(f, allow_pickle=True)[0]
# Convert IQ data from (2, N) to (N,) complex format # Convert IQ data from (2, N) to (N,) complex format
@ -351,7 +402,7 @@ def from_sigmf(file: os.PathLike | str) -> Recording:
# Process core keys # Process core keys
if key.startswith("core:"): if key.startswith("core:"):
base_key = key[5:] # Remove 'core:' prefix base_key = key[5:] # Remove 'core:' prefix
converted_key = SIGMF_KEY_CONVERSION.get(base_key, base_key) converted_key = SIGMF_KEY_CONVERSION.get(key, base_key)
# Process ria keys # Process ria keys
elif key.startswith("ria:"): elif key.startswith("ria:"):
converted_key = key[4:] # Remove 'ria:' prefix converted_key = key[4:] # Remove 'ria:' prefix

58
src/ria_toolkit_oss/orchestration/campaign.py
View File

@ -9,6 +9,15 @@ from typing import Optional
import yaml import yaml
# Allowed characters in campaign names when used as filename components.
_SAFE_NAME_RE = re.compile(r"[^a-zA-Z0-9_\-]")
# Reasonable RF bounds for consumer/research SDR hardware.
_FREQ_MIN_HZ = 1.0 # 1 Hz
_FREQ_MAX_HZ = 300e9 # 300 GHz
_GAIN_MIN_DB = -30.0
_GAIN_MAX_DB = 120.0
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Parsing helpers # Parsing helpers
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
@ -48,21 +57,40 @@ def parse_frequency(value: str | float | int) -> float:
2.45e9 (numeric) → 2_450_000_000.0 2.45e9 (numeric) → 2_450_000_000.0
""" """
if isinstance(value, (int, float)): if isinstance(value, (int, float)):
return float(value) result = float(value)
if not (_FREQ_MIN_HZ <= result <= _FREQ_MAX_HZ):
raise ValueError(
f"Frequency {result:.3g} Hz is outside the supported range "
f"({_FREQ_MIN_HZ:.0f} Hz – {_FREQ_MAX_HZ:.3g} Hz)"
)
return result
value = str(value).strip() value = str(value).strip()
# Try bare numeric first (handles scientific notation like "915e6") # Try bare numeric first (handles scientific notation like "915e6")
try: try:
return float(value) result = float(value)
except ValueError: except ValueError:
pass pass
else:
if not (_FREQ_MIN_HZ <= result <= _FREQ_MAX_HZ):
raise ValueError(
f"Frequency {result:.3g} Hz is outside the supported range "
f"({_FREQ_MIN_HZ:.0f} Hz – {_FREQ_MAX_HZ:.3g} Hz): '{value}'"
)
return result
# Handle suffix notation: "2.45GHz", "40MHz", "40M", "433k" # Handle suffix notation: "2.45GHz", "40MHz", "40M", "433k"
match = re.fullmatch(r"([\d.]+)\s*(k|M|G)(?:\s*Hz?)?", value, re.IGNORECASE) match = re.fullmatch(r"([\d.]+)\s*(k|M|G)(?:\s*Hz?)?", value, re.IGNORECASE)
if match: if match:
amount = float(match.group(1)) amount = float(match.group(1))
suffix = match.group(2).upper() suffix = match.group(2).upper()
return amount * {"K": 1e3, "M": 1e6, "G": 1e9}[suffix] result = amount * {"K": 1e3, "M": 1e6, "G": 1e9}[suffix]
if not (_FREQ_MIN_HZ <= result <= _FREQ_MAX_HZ):
raise ValueError(
f"Frequency {result:.3g} Hz is outside the supported range "
f"({_FREQ_MIN_HZ:.0f} Hz – {_FREQ_MAX_HZ:.3g} Hz): '{value}'"
)
return result
raise ValueError(f"Cannot parse frequency: '{value}'") raise ValueError(f"Cannot parse frequency: '{value}'")
@ -76,14 +104,22 @@ def parse_gain(value: str | float | int) -> float | str:
40 (numeric) → 40.0 40 (numeric) → 40.0
""" """
if isinstance(value, (int, float)): if isinstance(value, (int, float)):
return float(value) result = float(value)
if not (_GAIN_MIN_DB <= result <= _GAIN_MAX_DB):
raise ValueError(f"Gain {result} dB is outside the supported range ({_GAIN_MIN_DB} – {_GAIN_MAX_DB} dB)")
return result
value = str(value).strip() value = str(value).strip()
if value.lower() == "auto": if value.lower() == "auto":
return "auto" return "auto"
match = re.fullmatch(r"([\d.+\-]+)\s*dB?", value, re.IGNORECASE) match = re.fullmatch(r"([\d.+\-]+)\s*dB?", value, re.IGNORECASE)
if not match: if not match:
raise ValueError(f"Cannot parse gain: '{value}'") raise ValueError(f"Cannot parse gain: '{value}'")
return float(match.group(1)) result = float(match.group(1))
if not (_GAIN_MIN_DB <= result <= _GAIN_MAX_DB):
raise ValueError(
f"Gain {result} dB is outside the supported range ({_GAIN_MIN_DB} – {_GAIN_MAX_DB} dB): '{value}'"
)
return result
def parse_bandwidth_mhz(value: str | float | int | None) -> Optional[float]: def parse_bandwidth_mhz(value: str | float | int | None) -> Optional[float]:
@ -273,8 +309,12 @@ class CampaignConfig:
transmitters = [TransmitterConfig.from_dict(t) for t in raw.get("transmitters", [])] transmitters = [TransmitterConfig.from_dict(t) for t in raw.get("transmitters", [])]
if not transmitters: if not transmitters:
raise ValueError("Campaign config must define at least one transmitter") raise ValueError("Campaign config must define at least one transmitter")
if "recorder" not in raw:
raise ValueError("Campaign config is missing required 'recorder' section")
raw_name = str(campaign_meta.get("name", "unnamed"))
safe_name = _SAFE_NAME_RE.sub("_", raw_name)
return cls( return cls(
name=str(campaign_meta.get("name", "unnamed")), name=safe_name,
mode=str(campaign_meta.get("mode", "controlled_testbed")), mode=str(campaign_meta.get("mode", "controlled_testbed")),
recorder=RecorderConfig.from_dict(raw["recorder"]), recorder=RecorderConfig.from_dict(raw["recorder"]),
transmitters=transmitters, transmitters=transmitters,
@ -332,9 +372,13 @@ class CampaignConfig:
transmitters = [TransmitterConfig.from_dict(t) for t in raw.get("transmitters", [])] transmitters = [TransmitterConfig.from_dict(t) for t in raw.get("transmitters", [])]
if not transmitters: if not transmitters:
raise ValueError("Campaign config must define at least one transmitter") raise ValueError("Campaign config must define at least one transmitter")
if "recorder" not in raw:
raise ValueError(f"Campaign config is missing required 'recorder' section in {path}")
raw_name = str(campaign_meta.get("name", path.stem))
safe_name = _SAFE_NAME_RE.sub("_", raw_name)
return cls( return cls(
name=str(campaign_meta.get("name", path.stem)), name=safe_name,
mode=str(campaign_meta.get("mode", "controlled_testbed")), mode=str(campaign_meta.get("mode", "controlled_testbed")),
recorder=RecorderConfig.from_dict(raw["recorder"]), recorder=RecorderConfig.from_dict(raw["recorder"]),
transmitters=transmitters, transmitters=transmitters,

31
src/ria_toolkit_oss/orchestration/executor.py
View File

@ -32,6 +32,9 @@ _DEVICE_ALIASES = {
"rtlsdr": "rtlsdr", "rtlsdr": "rtlsdr",
"rtl_sdr": "rtlsdr", "rtl_sdr": "rtlsdr",
"thinkrf": "thinkrf", "thinkrf": "thinkrf",
# Simulated device — no hardware required
"mock": "mock",
"sim": "mock",
} }
@ -127,14 +130,22 @@ def _run_script(script: str, *args: str, timeout: float = 15.0) -> str:
A non-zero return code raises RuntimeError. A non-zero return code raises RuntimeError.
Args: Args:
script: Path to executable script. script: Path to executable script. Must be an absolute path to an
existing regular file. Relative paths are rejected to prevent
accidentally executing files that are not the intended script.
*args: Positional arguments forwarded to the script. *args: Positional arguments forwarded to the script.
timeout: Maximum seconds to wait. timeout: Maximum seconds to wait.
Returns: Returns:
Script stdout as a string. Script stdout as a string.
""" """
cmd = [script, *args] script_path = Path(script).resolve()
if not script_path.is_absolute():
raise RuntimeError(f"Script path must be absolute: {script}")
if not script_path.is_file():
raise RuntimeError(f"Script not found or is not a regular file: {script}")
cmd = [str(script_path), *args]
logger.debug(f"Running script: {' '.join(cmd)}") logger.debug(f"Running script: {' '.join(cmd)}")
try: try:
result = subprocess.run( result = subprocess.run(
@ -251,7 +262,7 @@ class CampaignExecutor:
def _init_sdr(self) -> None: def _init_sdr(self) -> None:
"""Initialise and configure the SDR recorder.""" """Initialise and configure the SDR recorder."""
from ria_toolkit_oss_cli.ria_toolkit_oss.common import get_sdr_device from ria_toolkit_oss.sdr import get_sdr_device
rec = self.config.recorder rec = self.config.recorder
device_name = _DEVICE_ALIASES.get(rec.device.lower(), rec.device.lower()) device_name = _DEVICE_ALIASES.get(rec.device.lower(), rec.device.lower())
@ -411,11 +422,21 @@ class CampaignExecutor:
"""Save a recording to disk and return the data file path.""" """Save a recording to disk and return the data file path."""
out = self.config.output out = self.config.output
rel_filename = build_output_filename(device_id, step) rel_filename = build_output_filename(device_id, step)
out_dir = Path(out.path) out_dir = Path(out.path).resolve()
# build_output_filename returns "<device_id>/<label>" # build_output_filename returns "<device_id>/<label>"
# to_sigmf needs filename (base) and path (dir) separately # to_sigmf needs filename (base) and path (dir) separately
parts = Path(rel_filename) parts = Path(rel_filename)
subdir = out_dir / parts.parent subdir = (out_dir / parts.parent).resolve()
# Prevent path traversal: the resolved subdir must stay within the configured output directory.
try:
subdir.relative_to(out_dir)
except ValueError:
raise RuntimeError(
f"Output path escape detected: '{subdir}' is outside configured output directory '{out_dir}'"
)
subdir.mkdir(parents=True, exist_ok=True) subdir.mkdir(parents=True, exist_ok=True)
base = parts.name base = parts.name

35
src/ria_toolkit_oss/sdr/__init__.py
View File

@ -4,6 +4,39 @@ It streamlines tasks involving signal reception and transmission, as well as com
operations such as detecting and configuring available devices. operations such as detecting and configuring available devices.
""" """
__all__ = ["SDR", "SDRError", "SDRParameterError"] __all__ = ["SDR", "SDRError", "SDRParameterError", "MockSDR", "get_sdr_device"]
from .mock import MockSDR
from .sdr import SDR, SDRError, SDRParameterError from .sdr import SDR, SDRError, SDRParameterError
def get_sdr_device(device_type: str, ident: str | None = None, tx: bool = False) -> SDR:
"""Return an SDR instance for *device_type*.
For ``"mock"`` / ``"sim"`` device types, returns a :class:`MockSDR`
immediately (no hardware required). For all real device types, delegates
to ``ria_toolkit_oss_cli.ria_toolkit_oss.common.get_sdr_device`` if the
CLI package is installed; otherwise raises ``ImportError`` with a helpful
message.
Args:
device_type: Device name (``"mock"``, ``"pluto"``, ``"usrp"``, …).
ident: Optional device identifier (IP address, serial number, …).
tx: If True, require TX capability.
"""
if device_type in ("mock", "sim"):
return MockSDR()
# Delegate real device types to the CLI package which holds the driver
# imports behind hardware-specific optional dependencies.
try:
from ria_toolkit_oss_cli.ria_toolkit_oss.common import (
get_sdr_device as _cli_get,
)
except ImportError as exc:
raise ImportError(
f"ria_toolkit_oss_cli is required to use hardware SDR device '{device_type}'. "
"Install it with: pip install ria-toolkit-oss-cli"
) from exc
return _cli_get(device_type, ident=ident, tx=tx)

131
src/ria_toolkit_oss/sdr/mock.py Normal file
View File

@ -0,0 +1,131 @@
"""Simulated SDR device for testing without hardware.
Set ``recorder.device = "mock"`` (or ``"sim"``) in a campaign config to use
this driver. The inference loop can also use it by specifying ``device:
"mock"`` in the SDR start request.
The mock generates complex float32 AWGN samples normalised to [-1, 1].
It satisfies both interfaces used in this codebase:
- ``record(num_samples)`` / ``_stream_rx(callback)`` — used by
``CampaignExecutor`` (inherits from ``SDR`` base class).
- ``rx(num_samples)`` — PlutoSDR-style interface used by the controller
inference loop.
"""
from __future__ import annotations
import time
import numpy as np
from ria_toolkit_oss.sdr.sdr import SDR
_DEFAULT_BUFFER_SIZE = 4096
# Simulated sample rate throttle: sleep this long between buffers so the
# loop does not spin at 100% CPU. 10 ms ≈ 100 buffers/s which is fine for
# tests and campaign execution timing.
_SLEEP_PER_BUFFER_S = 0.01
class MockSDR(SDR):
"""Software-simulated SDR that generates AWGN noise.
Args:
buffer_size: Number of complex samples per streaming buffer.
seed: Optional RNG seed for reproducible output.
"""
def __init__(self, buffer_size: int = _DEFAULT_BUFFER_SIZE, seed: int | None = None):
super().__init__()
self.rx_buffer_size: int = buffer_size
self._rng = np.random.default_rng(seed)
# Direct attribute aliases used by _apply_sdr_config in the controller.
self.center_freq: float = 2.45e9
self.sample_rate: float = 10e6
self.gain: float = 40.0
# ------------------------------------------------------------------
# Abstract method implementations
# ------------------------------------------------------------------
def init_rx(
self,
sample_rate: float,
center_frequency: float,
gain,
channel: int = 0,
gain_mode: str = "manual",
) -> None:
self.rx_sample_rate = float(sample_rate)
self.rx_center_frequency = float(center_frequency)
self.rx_gain = 40.0 if gain is None else float(gain)
# Mirror to the attribute names used by _apply_sdr_config.
self.sample_rate = self.rx_sample_rate
self.center_freq = self.rx_center_frequency
self.gain = self.rx_gain
self._rx_initialized = True
def init_tx(
self,
sample_rate: float,
center_frequency: float,
gain,
channel: int = 0,
gain_mode: str = "manual",
) -> None:
self.tx_sample_rate = float(sample_rate)
self.tx_center_frequency = float(center_frequency)
self.tx_gain = 40.0 if gain is None else float(gain)
self._tx_initialized = True
def _stream_rx(self, callback) -> None:
"""Generate 1-D AWGN buffers and pass each to *callback* until stopped.
Uses 1-D arrays so the base class ``_validate_buffer`` check does not
incorrectly flag them as corrupted (the (1, N) form triggers a false
positive in the all-same-value check).
"""
self._enable_rx = True
while self._enable_rx:
buf = self._awgn(self.rx_buffer_size)
callback(buf)
time.sleep(_SLEEP_PER_BUFFER_S)
def _stream_tx(self, callback) -> None:
self._enable_tx = True
while self._enable_tx:
callback(self.rx_buffer_size)
time.sleep(_SLEEP_PER_BUFFER_S)
def set_clock_source(self, source: str) -> None:
pass # no-op
def close(self) -> None:
self._enable_rx = False
self._enable_tx = False
self._rx_initialized = False
self._tx_initialized = False
# ------------------------------------------------------------------
# PlutoSDR-style interface used by the controller inference loop
# ------------------------------------------------------------------
def rx(self, num_samples: int) -> np.ndarray:
"""Return *num_samples* complex64 AWGN samples (PlutoSDR-style)."""
return self._awgn(num_samples)
# ------------------------------------------------------------------
# Internal helpers
# ------------------------------------------------------------------
def _awgn(self, n: int) -> np.ndarray:
"""Return *n* normalised complex64 AWGN samples as a 1-D array."""
real = self._rng.standard_normal(n).astype(np.float32)
imag = self._rng.standard_normal(n).astype(np.float32)
buf = real + 1j * imag
peak = np.abs(buf).max()
if peak > 1e-9:
buf /= peak
return buf

3
src/ria_toolkit_oss/sdr/sdr.py
View File

@ -32,7 +32,6 @@ class SDR(ABC):
self._accumulated_buffer = None self._accumulated_buffer = None
self._max_num_buffers = None self._max_num_buffers = None
self._num_buffers_processed = 0 self._num_buffers_processed = 0
self._accumulated_buffer = None
self._last_buffer = None self._last_buffer = None
self._corrupted_buffer_count = 0 self._corrupted_buffer_count = 0
@ -282,7 +281,7 @@ class SDR(ABC):
elif num_samples is not None: elif num_samples is not None:
self._num_samples_to_transmit = num_samples self._num_samples_to_transmit = num_samples
elif tx_time is not None: elif tx_time is not None:
self._num_samples_to_transmit = tx_time * self.tx_sample_rate self._num_samples_to_transmit = int(tx_time * self.tx_sample_rate)
else: else:
self._num_samples_to_transmit = len(recording) self._num_samples_to_transmit = len(recording)

13
src/ria_toolkit_oss/server/auth.py
View File

@ -1,9 +1,13 @@
"""API key authentication dependency.""" """API key authentication dependency."""
import hmac
import logging
from fastapi import Depends, HTTPException, Request, status from fastapi import Depends, HTTPException, Request, status
from fastapi.security import APIKeyHeader from fastapi.security import APIKeyHeader
_api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False) _api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
logger = logging.getLogger(__name__)
async def require_api_key( async def require_api_key(
@ -18,7 +22,14 @@ async def require_api_key(
expected: str = request.app.state.api_key expected: str = request.app.state.api_key
if not expected: if not expected:
return # dev mode: no key set, allow all return # dev mode: no key set, allow all
if api_key != expected: if not hmac.compare_digest(api_key or "", expected):
client = getattr(request.client, "host", "unknown")
logger.warning(
"Authentication failure from %s — %s %s",
client,
request.method,
request.url.path,
)
raise HTTPException( raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN, status_code=status.HTTP_403_FORBIDDEN,
detail="Invalid or missing API key", detail="Invalid or missing API key",

14
src/ria_toolkit_oss/server/cli.py
View File

@ -21,8 +21,7 @@ def serve() -> None:
import uvicorn import uvicorn
except ImportError: except ImportError:
raise SystemExit( raise SystemExit(
"uvicorn is required to run the RT-OSS server.\n" "uvicorn is required to run the RT-OSS server.\n" "Install it with: pip install 'ria-toolkit-oss[server]'"
"Install it with: pip install 'ria-toolkit-oss[server]'"
) )
from .app import create_app from .app import create_app
@ -34,6 +33,15 @@ def serve() -> None:
app = create_app(api_key=api_key) app = create_app(api_key=api_key)
if not api_key: if not api_key:
print("WARNING: RT_OSS_API_KEY not set — running in unauthenticated dev mode.") print(
"\n"
"╔══════════════════════════════════════════════════════════════╗\n"
"║ WARNING: RT_OSS_API_KEY is not set. ║\n"
"║ The server is running with NO authentication. ║\n"
"║ Anyone who can reach this port has full API access. ║\n"
"║ Set RT_OSS_API_KEY=<secret> before exposing to a network. ║\n"
"╚══════════════════════════════════════════════════════════════╝\n",
flush=True,
)
uvicorn.run(app, host=host, port=port) uvicorn.run(app, host=host, port=port)

19
src/ria_toolkit_oss/server/models.py
View File

@ -2,7 +2,9 @@
from __future__ import annotations from __future__ import annotations
from pydantic import BaseModel from pathlib import Path
from pydantic import BaseModel, field_validator
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Orchestrator # Orchestrator
@ -50,6 +52,21 @@ class LoadModelRequest(BaseModel):
model_path: str model_path: str
label_map: dict[str, int] # class_name -> class_index label_map: dict[str, int] # class_name -> class_index
@field_validator("model_path")
@classmethod
def validate_model_path(cls, v: str) -> str:
p = Path(v)
if ".." in p.parts:
raise ValueError("model_path must not contain path traversal components")
if p.suffix.lower() != ".onnx":
raise ValueError("model_path must point to an .onnx file")
# Resolve to catch symlink-based traversal; return the resolved absolute path
# so callers always work with the real filesystem location.
resolved = p.resolve()
if resolved.suffix.lower() != ".onnx":
raise ValueError("Resolved model_path must point to an .onnx file")
return str(resolved)
class LoadModelResponse(BaseModel): class LoadModelResponse(BaseModel):
loaded: bool loaded: bool

22
src/ria_toolkit_oss/server/routers/inference.py
View File

@ -5,6 +5,7 @@ from __future__ import annotations
import logging import logging
import threading import threading
import time import time
from pathlib import Path
import numpy as np import numpy as np
from fastapi import APIRouter, HTTPException, status from fastapi import APIRouter, HTTPException, status
@ -39,8 +40,14 @@ def _load_onnx_session(model_path: str):
status_code=status.HTTP_503_SERVICE_UNAVAILABLE, status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
detail="onnxruntime not installed. Install with: pip install ria-toolkit-oss[server]", detail="onnxruntime not installed. Install with: pip install ria-toolkit-oss[server]",
) )
resolved = Path(model_path).resolve()
if not resolved.is_file():
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail=f"Model file not found: {model_path}",
)
try: try:
return ort.InferenceSession(model_path, providers=["CPUExecutionProvider"]) return ort.InferenceSession(str(resolved), providers=["CPUExecutionProvider"])
except Exception as e: except Exception as e:
raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=f"Failed to load ONNX model: {e}") raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=f"Failed to load ONNX model: {e}")
@ -122,7 +129,8 @@ def _inference_loop(state: InferenceState, sdr) -> None:
probs = softmax(logits) probs = softmax(logits)
pred_idx = int(np.argmax(probs)) pred_idx = int(np.argmax(probs))
prediction = state.index_to_label.get(pred_idx, str(pred_idx)) prediction = state.index_to_label.get(pred_idx, str(pred_idx))
except Exception: except Exception as exc:
logger.warning("Inference prediction failed: %s", exc)
continue continue
is_idle = prediction in _IDLE_LABELS is_idle = prediction in _IDLE_LABELS
@ -142,7 +150,7 @@ def _inference_loop(state: InferenceState, sdr) -> None:
sdr.close() sdr.close()
except Exception: except Exception:
pass pass
state.running = False state.set_running(False)
@router.post("/load", response_model=LoadModelResponse) @router.post("/load", response_model=LoadModelResponse)
@ -153,7 +161,7 @@ async def load_model(request: LoadModelRequest):
``enrolled_devices`` enriches status responses with human names and authorization flags. ``enrolled_devices`` enriches status responses with human names and authorization flags.
""" """
existing = get_inference() existing = get_inference()
if existing and existing.running: if existing and existing.get_running():
_stop_current_inference(existing) _stop_current_inference(existing)
session = _load_onnx_session(request.model_path) session = _load_onnx_session(request.model_path)
@ -176,7 +184,7 @@ async def start_inference(request: StartInferenceRequest):
raise HTTPException( raise HTTPException(
status_code=status.HTTP_409_CONFLICT, detail="No model loaded. Call POST /inference/load first." status_code=status.HTTP_409_CONFLICT, detail="No model loaded. Call POST /inference/load first."
) )
if state.running: if state.get_running():
raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Inference is already running.") raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Inference is already running.")
try: try:
@ -199,7 +207,7 @@ async def start_inference(request: StartInferenceRequest):
raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=f"SDR initialisation failed: {e}") raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=f"SDR initialisation failed: {e}")
state.stop_event.clear() state.stop_event.clear()
state.running = True state.set_running(True)
state.thread = threading.Thread(target=_inference_loop, args=(state, sdr), daemon=True) state.thread = threading.Thread(target=_inference_loop, args=(state, sdr), daemon=True)
state.thread.start() state.thread.start()
return StartInferenceResponse(running=True) return StartInferenceResponse(running=True)
@ -209,7 +217,7 @@ async def start_inference(request: StartInferenceRequest):
async def stop_inference(): async def stop_inference():
"""Stop the running inference loop.""" """Stop the running inference loop."""
state = get_inference() state = get_inference()
if not state or not state.running: if not state or not state.get_running():
return StopInferenceResponse(stopped=False) return StopInferenceResponse(stopped=False)
_stop_current_inference(state) _stop_current_inference(state)
return StopInferenceResponse(stopped=True) return StopInferenceResponse(stopped=True)

10
src/ria_toolkit_oss/server/routers/orchestrator.py
View File

@ -58,12 +58,22 @@ def _run_campaign_thread(campaign_id: str, cfg: CampaignConfig) -> None:
async def deploy(request: DeployRequest): async def deploy(request: DeployRequest):
"""Deploy a campaign config and start execution. Returns a ``campaign_id`` for polling. """Deploy a campaign config and start execution. Returns a ``campaign_id`` for polling.
Cancellation takes effect at step boundaries, not mid-capture. Cancellation takes effect at step boundaries, not mid-capture.
External scripts are not permitted in server-deployed campaigns. Configure
transmitters without the ``script`` field, or run campaigns via the CLI.
""" """
try: try:
cfg = CampaignConfig.from_dict(request.config) cfg = CampaignConfig.from_dict(request.config)
except (ValueError, KeyError) as e: except (ValueError, KeyError) as e:
raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=str(e)) raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=str(e))
if any(t.script for t in cfg.transmitters):
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail="External scripts are not permitted in server-deployed campaigns. "
"Remove the 'script' field from all transmitters, or run the campaign via the CLI.",
)
campaign_id = str(uuid.uuid4()) campaign_id = str(uuid.uuid4())
cancel_event = threading.Event() cancel_event = threading.Event()
thread = threading.Thread(target=_run_campaign_thread, args=(campaign_id, cfg), daemon=True) thread = threading.Thread(target=_run_campaign_thread, args=(campaign_id, cfg), daemon=True)

8
src/ria_toolkit_oss/server/state.py
View File

@ -72,6 +72,14 @@ class InferenceState:
self._pending_sdr_config = None self._pending_sdr_config = None
return cfg return cfg
def set_running(self, value: bool) -> None:
with self._lock:
self.running = value
def get_running(self) -> bool:
with self._lock:
return self.running
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Module-level stores # Module-level stores

5
src/ria_toolkit_oss/signal/block_generator/frequency_translation/upconversion.py
View File

@ -1,6 +1,7 @@
import numpy as np import numpy as np
from utils.signal.block_generator.block import Block
from utils.signal.block_generator.data_types import DataType from ria_toolkit_oss.signal.block_generator.block import Block
from ria_toolkit_oss.signal.block_generator.data_types import DataType
class FrequencyUpConversion(Block): class FrequencyUpConversion(Block):

27
src/ria_toolkit_oss/transforms/iq_augmentations.py
View File

@ -5,6 +5,7 @@ and return a corresponding numpy.ndarray with the impairment model applied;
we call the latter the impaired data. we call the latter the impaired data.
""" """
import warnings
from typing import Optional from typing import Optional
import numpy as np import numpy as np
@ -58,13 +59,14 @@ def generate_awgn(signal: ArrayLike | Recording, snr: Optional[float] = 1) -> np
# Calculate the RMS power of the signal to solve for the RMS power of the noise # Calculate the RMS power of the signal to solve for the RMS power of the noise
signal_rms_power = np.sqrt(np.mean(np.abs(data) ** 2)) signal_rms_power = np.sqrt(np.mean(np.abs(data) ** 2))
noise_rms_power = signal_rms_power / snr_linear noise_rms_power = signal_rms_power / np.sqrt(snr_linear)
# Generate the AWGN noise which has the same shape as data # Generate complex AWGN: independent Gaussian I and Q components.
variance = noise_rms_power**2 # Each component has std = noise_rms_power / sqrt(2) so total power = noise_rms_power^2.
magnitude = np.random.normal(loc=0, scale=np.sqrt(variance), size=(c, n)) component_std = noise_rms_power / np.sqrt(2)
phase = np.random.uniform(low=0, high=2 * np.pi, size=(c, n)) complex_awgn = np.random.normal(scale=component_std, size=(c, n)) + 1j * np.random.normal(
complex_awgn = magnitude * np.exp(1j * phase) scale=component_std, size=(c, n)
)
if isinstance(signal, Recording): if isinstance(signal, Recording):
return Recording(data=complex_awgn, metadata=signal.metadata) return Recording(data=complex_awgn, metadata=signal.metadata)
@ -378,7 +380,8 @@ def quantize_tape(
raise ValueError("signal must be CxN complex.") raise ValueError("signal must be CxN complex.")
if rounding_type not in {"ceiling", "floor"}: if rounding_type not in {"ceiling", "floor"}:
raise UserWarning('rounding_type must be either "floor" or "ceiling", floor has been selected by default') warnings.warn('rounding_type must be either "floor" or "ceiling", floor has been selected by default')
rounding_type = "floor"
if c == 1: if c == 1:
iq_data = convert_to_2xn(data) iq_data = convert_to_2xn(data)
@ -455,7 +458,8 @@ def quantize_parts(
raise ValueError("signal must be CxN complex.") raise ValueError("signal must be CxN complex.")
if rounding_type not in {"ceiling", "floor"}: if rounding_type not in {"ceiling", "floor"}:
raise UserWarning('rounding_type must be either "floor" or "ceiling", floor has been selected by default') warnings.warn('rounding_type must be either "floor" or "ceiling", floor has been selected by default')
rounding_type = "floor"
if c == 1: if c == 1:
iq_data = convert_to_2xn(data) iq_data = convert_to_2xn(data)
@ -610,10 +614,11 @@ def cut_out( # noqa: C901 # TODO: Simplify function
raise ValueError("signal must be CxN complex.") raise ValueError("signal must be CxN complex.")
if fill_type not in {"zeros", "ones", "low-snr", "avg-snr", "high-snr"}: if fill_type not in {"zeros", "ones", "low-snr", "avg-snr", "high-snr"}:
raise UserWarning( warnings.warn(
"""fill_type must be "zeros", "ones", "low-snr", "avg-snr", or "high-snr", 'fill_type must be "zeros", "ones", "low-snr", "avg-snr", or "high-snr", '
"ones" has been selected by default""" '"ones" has been selected by default'
) )
fill_type = "ones"
if max_section_size < 1 or max_section_size >= n: if max_section_size < 1 or max_section_size >= n:
raise ValueError("max_section_size must be at least 1 and must be less than the length of signal.") raise ValueError("max_section_size must be at least 1 and must be less than the length of signal.")

12
src/ria_toolkit_oss/transforms/iq_impairments.py
View File

@ -9,6 +9,7 @@ not the same as the signal at the end of the medium. What is sent is not what is
Three causes of impairment are attenuation, distortion, and noise. Three causes of impairment are attenuation, distortion, and noise.
""" """
import warnings
from typing import Optional from typing import Optional
import numpy as np import numpy as np
@ -55,8 +56,6 @@ def add_awgn_to_signal(signal: ArrayLike | Recording, snr: Optional[float] = 1)
raise ValueError("signal must be CxN complex.") raise ValueError("signal must be CxN complex.")
noise = iq_augmentations.generate_awgn(signal=data, snr=snr) noise = iq_augmentations.generate_awgn(signal=data, snr=snr)
print(f"noise is {noise}")
noisy_signal = data + noise noisy_signal = data + noise
if isinstance(signal, Recording): if isinstance(signal, Recording):
@ -101,16 +100,18 @@ def time_shift(signal: ArrayLike | Recording, shift: Optional[int] = 1) -> np.nd
raise ValueError("signal must be CxN complex.") raise ValueError("signal must be CxN complex.")
if shift > n: if shift > n:
raise UserWarning("shift is greater than signal length") warnings.warn("shift is greater than signal length")
shifted_data = np.zeros_like(data) shifted_data = np.zeros_like(data)
if c == 1: if c == 1:
# New iq array shifted left or right depending on sign of shift # New iq array shifted left or right depending on sign of shift
# This should work even if shift > iqdata.shape[1] # This should work even if shift > iqdata.shape[1]
if shift >= 0: if shift > 0:
# Shift to right # Shift to right
shifted_data[:, shift:] = data[:, :-shift] shifted_data[:, shift:] = data[:, :-shift]
elif shift == 0:
shifted_data[:] = data
else: else:
# Shift to the left # Shift to the left
@ -354,8 +355,9 @@ def resample(signal: ArrayLike | Recording, up: Optional[int] = 4, down: Optiona
resampled_iqdata = resampled_iqdata[:, :n] resampled_iqdata = resampled_iqdata[:, :n]
else: else:
empty_array = np.zeros(resampled_iqdata.shape, dtype=resampled_iqdata.dtype) empty_array = np.zeros((1, n), dtype=resampled_iqdata.dtype)
empty_array[:, : resampled_iqdata.shape[1]] = resampled_iqdata empty_array[:, : resampled_iqdata.shape[1]] = resampled_iqdata
resampled_iqdata = empty_array
else: else:
raise NotImplementedError raise NotImplementedError

7
src/ria_toolkit_oss_cli/ria_toolkit_oss/common.py
View File

@ -332,7 +332,7 @@ def parse_ident(ident: Optional[str]) -> tuple[Optional[str], Optional[str]]:
return ident, None return ident, None
def get_sdr_device(device_type: str, ident: Optional[str] = None, tx=False): def get_sdr_device(device_type: str, ident: Optional[str] = None, tx=False): # noqa: C901
""" """
Get TX-capable SDR device instance. Get TX-capable SDR device instance.
@ -346,6 +346,11 @@ def get_sdr_device(device_type: str, ident: Optional[str] = None, tx=False):
Raises: Raises:
click.ClickException: If device cannot be initialized or doesn't support TX click.ClickException: If device cannot be initialized or doesn't support TX
""" """
if device_type in ("mock", "sim"):
from ria_toolkit_oss.sdr.mock import MockSDR
return MockSDR()
TX_CAPABLE_DEVICES = ["pluto", "hackrf", "bladerf", "usrp"] TX_CAPABLE_DEVICES = ["pluto", "hackrf", "bladerf", "usrp"]
if tx and device_type not in TX_CAPABLE_DEVICES: if tx and device_type not in TX_CAPABLE_DEVICES:
raise click.ClickException( raise click.ClickException(

22
src/ria_toolkit_oss_cli/ria_toolkit_oss/discover.py
View File

@ -1,5 +1,6 @@
"""Device discovery utilities for SDR devices.""" """Device discovery utilities for SDR devices."""
import importlib
import json import json
import re import re
import subprocess import subprocess
@ -42,15 +43,28 @@ def load_sdr_drivers(verbose: bool = False) -> Tuple[List[str], List[str], Dict[
for driver_name, module_path in drivers.items(): for driver_name, module_path in drivers.items():
try: try:
# Attempt to import the driver module # Attempt to import the driver module
if not verbose:
# Suppress output for quiet loading
import warnings import warnings
if not verbose:
with warnings.catch_warnings(): with warnings.catch_warnings():
warnings.simplefilter("ignore") warnings.simplefilter("ignore")
__import__(module_path) mod = importlib.import_module(module_path)
else: else:
__import__(module_path) mod = importlib.import_module(module_path)
# Verify the loaded module is from the expected package to guard against
# dependency-confusion / sys.path injection attacks.
mod_file = getattr(mod, "__file__", None) or ""
expected_pkg = module_path.split(".")[0] # e.g. "ria_toolkit_oss"
pkg_root = importlib.import_module(expected_pkg).__file__ or ""
import os as _os
pkg_dir = _os.path.dirname(_os.path.dirname(pkg_root))
if mod_file and not _os.path.realpath(mod_file).startswith(_os.path.realpath(pkg_dir)):
warnings.warn(
f"SDR driver '{driver_name}' loaded from unexpected location: {mod_file}",
stacklevel=2,
)
_loaded_drivers.append(driver_name) _loaded_drivers.append(driver_name)

8
src/ria_toolkit_oss_cli/ria_toolkit_oss/transform.py
View File

@ -204,9 +204,15 @@ def load_custom_transforms(transform_dir):
if not py_files: if not py_files:
raise click.ClickException(f"No .py files found in {transform_dir}") raise click.ClickException(f"No .py files found in {transform_dir}")
click.echo(
f"WARNING: Loading custom transforms from '{transform_dir}'. "
"Each .py file will be executed as Python code — only use directories you trust.",
err=True,
)
for py_file in py_files: for py_file in py_files:
try: try:
# Load module dynamically # Load module dynamically — executes the file as Python code.
spec = importlib.util.spec_from_file_location(py_file.stem, py_file) spec = importlib.util.spec_from_file_location(py_file.stem, py_file)
if spec is None or spec.loader is None: if spec is None or spec.loader is None:
click.echo(f"Warning: Could not load {py_file.name}") click.echo(f"Warning: Could not load {py_file.name}")

132
tests/datatypes/test_annotation.py
View File

@ -67,3 +67,135 @@ def test_annotation_area():
annotation_area = sample_annotation.area() annotation_area = sample_annotation.area()
assert annotation_area == 600000 assert annotation_area == 600000
# ---------------------------------------------------------------------------
# Additional coverage
# ---------------------------------------------------------------------------
def test_annotation_area_zero_sample_count():
# An annotation with sample_count=0 has area 0 even with a wide frequency band.
ann = Annotation(0, 0, 0.0, 1000.0)
assert ann.area() == 0
def test_annotation_area_zero_bandwidth():
# An annotation with equal freq edges has area 0 (degenerate band).
ann = Annotation(0, 100, 500.0, 500.0)
assert ann.area() == 0
def test_annotation_overlap_no_overlap_disjoint_time():
# Annotations that are completely separate in time have zero overlap.
ann1 = Annotation(sample_start=0, sample_count=5, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=10, sample_count=5, freq_lower_edge=0, freq_upper_edge=100)
assert ann1.overlap(ann2) == 0
def test_annotation_overlap_no_overlap_disjoint_frequency():
# Annotations that are completely separate in frequency have zero overlap.
ann1 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=200, freq_upper_edge=300)
assert ann1.overlap(ann2) == 0
def test_annotation_overlap_touching_only_time():
# Annotations that share only a single sample boundary do NOT overlap.
# ann1 covers [0, 5), ann2 covers [5, 10) — they touch but don't overlap.
ann1 = Annotation(sample_start=0, sample_count=5, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=5, sample_count=5, freq_lower_edge=0, freq_upper_edge=100)
assert ann1.overlap(ann2) == 0
def test_annotation_overlap_touching_only_frequency():
# Annotations that share only a single frequency edge do NOT overlap.
ann1 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=100, freq_upper_edge=200)
assert ann1.overlap(ann2) == 0
def test_annotation_overlap_with_self():
# An annotation's overlap with itself equals its own area.
ann = Annotation(sample_start=0, sample_count=10, freq_lower_edge=0, freq_upper_edge=100)
assert ann.overlap(ann) == ann.area()
def test_annotation_overlap_symmetry():
# overlap(a, b) == overlap(b, a)
ann1 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=5, sample_count=10, freq_lower_edge=50, freq_upper_edge=150)
assert ann1.overlap(ann2) == ann2.overlap(ann1)
def test_annotation_overlap_partial_known_value():
# ann1: samples [0,10), freq [0,100) → area = 10*100 = 1000
# ann2: samples [5,15), freq [50,150) → area = 10*100 = 1000
# overlap in samples: [5,10) = 5; in freq: [50,100) = 50 → overlap = 250
ann1 = Annotation(sample_start=0, sample_count=10, freq_lower_edge=0, freq_upper_edge=100)
ann2 = Annotation(sample_start=5, sample_count=10, freq_lower_edge=50, freq_upper_edge=150)
assert ann1.overlap(ann2) == 5 * 50
def test_annotation_detail_default_is_empty_dict():
ann = Annotation(0, 10, 0.0, 100.0)
assert ann.detail == {}
def test_annotation_detail_accepts_valid_dict():
ann = Annotation(0, 10, 0.0, 100.0, detail={"snr": 10.5, "modulation": "BPSK"})
assert ann.detail == {"snr": 10.5, "modulation": "BPSK"}
def test_annotation_detail_rejects_non_serializable():
# A dict containing a non-JSON-serializable value should raise ValueError.
import pytest
with pytest.raises(ValueError):
Annotation(0, 10, 0.0, 100.0, detail={"obj": object()})
def test_annotation_to_sigmf_format_keys():
# to_sigmf_format() should include the SigMF standard keys.
ann = Annotation(
sample_start=100,
sample_count=200,
freq_lower_edge=1000.0,
freq_upper_edge=2000.0,
label="WiFi",
comment="test signal",
detail={"snr_db": 15},
)
result = ann.to_sigmf_format()
# Top-level keys: sample_start index and sample_count length
assert "sample_start" in result or any("start" in k.lower() for k in result)
assert "metadata" in result
metadata = result["metadata"]
# Frequency bounds must be present
assert ann.freq_lower_edge in metadata.values()
assert ann.freq_upper_edge in metadata.values()
# Label and comment
assert ann.label in metadata.values()
assert ann.comment in metadata.values()
# detail passthrough
assert metadata.get("ria:detail") == {"snr_db": 15}
def test_annotation_to_sigmf_format_values():
# Check that numeric values are correctly mapped.
ann = Annotation(
sample_start=50,
sample_count=100,
freq_lower_edge=500.0,
freq_upper_edge=1500.0,
)
result = ann.to_sigmf_format()
# sample_start and sample_count must appear at the top level
values = list(result.values())
assert 50 in values or ann.sample_start in values
assert 100 in values or ann.sample_count in values

246
tests/datatypes/test_recording.py
View File

@ -218,3 +218,249 @@ def test_remove_from_metadata_1():
with pytest.raises(ValueError): with pytest.raises(ValueError):
recording.remove_from_metadata("timestamp") recording.remove_from_metadata("timestamp")
# ---------------------------------------------------------------------------
# Additional coverage
# ---------------------------------------------------------------------------
# --- Invalid construction ---
def test_real_data_raises():
# Real (non-complex) input must raise ValueError.
with pytest.raises(ValueError):
Recording(data=[[1.0, 2.0, 3.0]])
def test_3d_data_raises():
# 3-D complex array must raise ValueError.
with pytest.raises(ValueError):
Recording(data=np.ones((2, 3, 4), dtype=np.complex128))
def test_non_dict_metadata_raises():
# Metadata must be a python dict.
with pytest.raises(ValueError):
Recording(data=COMPLEX_DATA_1, metadata="sample_rate=1e6")
def test_non_serializable_metadata_raises():
# Metadata containing a non-JSON-serializable value must raise ValueError.
with pytest.raises(ValueError):
Recording(data=COMPLEX_DATA_1, metadata={"bad": object()})
def test_non_annotation_list_raises():
# annotations must be a list of Annotation objects.
with pytest.raises(ValueError):
Recording(data=COMPLEX_DATA_1, annotations=["not an annotation"])
def test_non_list_annotations_raises():
# annotations must be a list (not some other type).
with pytest.raises(ValueError):
Recording(data=COMPLEX_DATA_1, annotations=Annotation(0, 10, 0, 100))
def test_invalid_timestamp_type_raises():
# timestamp must be int or float, not str.
with pytest.raises(ValueError):
Recording(data=COMPLEX_DATA_1, timestamp="now")
# --- generate_recording_id ---
def test_generate_recording_id_length():
# SHA-256 hex digest is always 64 characters.
rid = generate_recording_id(data=np.array(COMPLEX_DATA_1), timestamp=123.0)
assert len(rid) == 64
def test_generate_recording_id_is_hex():
rid = generate_recording_id(data=np.array(COMPLEX_DATA_1), timestamp=123.0)
assert all(c in "0123456789abcdef" for c in rid)
def test_generate_recording_id_deterministic():
# Same data + timestamp must always produce the same ID.
data = np.array(COMPLEX_DATA_1)
rid1 = generate_recording_id(data=data, timestamp=42.0)
rid2 = generate_recording_id(data=data, timestamp=42.0)
assert rid1 == rid2
def test_generate_recording_id_differs_by_data():
data1 = np.array([[1 + 1j, 2 + 2j]])
data2 = np.array([[3 + 3j, 4 + 4j]])
rid1 = generate_recording_id(data=data1, timestamp=1.0)
rid2 = generate_recording_id(data=data2, timestamp=1.0)
assert rid1 != rid2
def test_generate_recording_id_differs_by_timestamp():
data = np.array(COMPLEX_DATA_1)
rid1 = generate_recording_id(data=data, timestamp=1.0)
rid2 = generate_recording_id(data=data, timestamp=2.0)
assert rid1 != rid2
def test_generate_recording_id_no_timestamp_uses_current_time():
# Without a timestamp the function should still return a 64-char hex string.
rid = generate_recording_id(data=np.array(COMPLEX_DATA_1))
assert len(rid) == 64
# --- add_to_metadata validation ---
def test_add_to_metadata_camelcase_key_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(ValueError):
rec.add_to_metadata(key="sampleRate", value=1e6)
def test_add_to_metadata_key_with_space_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(ValueError):
rec.add_to_metadata(key="sample rate", value=1e6)
def test_add_to_metadata_key_with_digit_raises():
# Regex ^[a-z_]+$ does NOT allow digits; "freq_2" is therefore invalid.
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(ValueError):
rec.add_to_metadata(key="freq_2", value=1e6)
def test_add_to_metadata_duplicate_key_raises():
rec = Recording(data=COMPLEX_DATA_1)
rec.add_to_metadata(key="author", value="alice")
with pytest.raises(ValueError):
rec.add_to_metadata(key="author", value="bob")
def test_add_to_metadata_valid_underscore_key():
rec = Recording(data=COMPLEX_DATA_1)
rec.add_to_metadata(key="sample_rate", value=1e6)
assert rec.metadata["sample_rate"] == 1e6
# --- update_metadata protected key enforcement ---
def test_update_metadata_rec_id_raises():
rec = Recording(data=COMPLEX_DATA_1, metadata=SAMPLE_METADATA)
with pytest.raises(ValueError):
rec.update_metadata(key="rec_id", value="fakeid")
def test_update_metadata_timestamp_raises():
rec = Recording(data=COMPLEX_DATA_1, metadata=SAMPLE_METADATA)
with pytest.raises(ValueError):
rec.update_metadata(key="timestamp", value=0.0)
# --- remove_from_metadata ---
def test_remove_from_metadata_rec_id_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(ValueError):
rec.remove_from_metadata("rec_id")
def test_remove_from_metadata_removes_key():
rec = Recording(data=COMPLEX_DATA_1)
rec.add_to_metadata("foo", "bar")
assert "foo" in rec.metadata
rec.remove_from_metadata("foo")
assert "foo" not in rec.metadata
# --- setitem is blocked ---
def test_setitem_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(ValueError):
rec[0, 0] = 999 + 0j
# --- data property read-only for large recordings ---
def test_data_read_only_for_large_recording():
# For recordings with more than 1024 samples the data property returns a
# read-only view; writing to it must raise ValueError.
large_data = np.ones(2048, dtype=np.complex128)
rec = Recording(data=large_data)
view = rec.data
with pytest.raises((ValueError, TypeError)):
view[0] = 0 + 0j
def test_data_copy_for_small_recording():
# For recordings with 1024 or fewer samples the property returns a copy;
# mutating the copy must NOT affect the recording's internal data.
rec = Recording(data=COMPLEX_DATA_1)
copy = rec.data
copy[0, 0] = -999 + 0j # mutate the copy
assert rec.data[0, 0] != -999 + 0j # internal data is unchanged
# --- trim edge cases ---
def test_trim_negative_start_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(IndexError):
rec.trim(start_sample=-1, num_samples=3)
def test_trim_beyond_end_raises():
rec = Recording(data=COMPLEX_DATA_1)
with pytest.raises(IndexError):
rec.trim(start_sample=3, num_samples=10)
def test_trim_preserves_metadata():
# Use a fresh dict to avoid pollution from tests that mutate SAMPLE_METADATA via Recording.
meta = {"source": "original", "timestamp": 1723472227.698788}
rec = Recording(data=COMPLEX_DATA_1, metadata=meta)
trimmed = rec.trim(start_sample=0, num_samples=3)
assert trimmed.metadata["source"] == "original"
# --- annotations ---
def test_recording_with_annotations_stores_them():
ann = Annotation(sample_start=0, sample_count=2, freq_lower_edge=0, freq_upper_edge=100)
rec = Recording(data=COMPLEX_DATA_1, annotations=[ann])
assert len(rec.annotations) == 1
assert rec.annotations[0] == ann
def test_recording_annotations_is_copy():
# Mutating the returned list must not affect the internal annotation list.
ann = Annotation(sample_start=0, sample_count=2, freq_lower_edge=0, freq_upper_edge=100)
rec = Recording(data=COMPLEX_DATA_1, annotations=[ann])
returned = rec.annotations
returned.append(ann) # mutate the copy
assert len(rec.annotations) == 1 # internal list unchanged
# --- n_chan property ---
def test_n_chan_single_channel():
rec = Recording(data=COMPLEX_DATA_1)
assert rec.n_chan == 1
def test_n_chan_multi_channel():
rec = Recording(data=COMPLEX_DATA_2)
assert rec.n_chan == len(COMPLEX_DATA_2)

17
tests/server/test_server.py
View File

@ -10,7 +10,6 @@ ONNX model file — those are integration tests left for hardware-in-the-loop CI
from __future__ import annotations from __future__ import annotations
import threading import threading
import time
from unittest.mock import MagicMock, patch from unittest.mock import MagicMock, patch
import pytest import pytest
@ -20,7 +19,6 @@ import ria_toolkit_oss.server.state as state_module
from ria_toolkit_oss.server.app import create_app from ria_toolkit_oss.server.app import create_app
from ria_toolkit_oss.server.state import CampaignState, InferenceState, set_inference from ria_toolkit_oss.server.state import CampaignState, InferenceState, set_inference
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Fixtures # Fixtures
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
@ -142,6 +140,7 @@ class TestInferenceLoad:
def test_load_503_when_onnxruntime_missing(self, client): def test_load_503_when_onnxruntime_missing(self, client):
from fastapi import HTTPException as FastAPIHTTPException from fastapi import HTTPException as FastAPIHTTPException
with patch( with patch(
"ria_toolkit_oss.server.routers.inference._load_onnx_session", "ria_toolkit_oss.server.routers.inference._load_onnx_session",
side_effect=FastAPIHTTPException(status_code=503, detail="onnxruntime not installed"), side_effect=FastAPIHTTPException(status_code=503, detail="onnxruntime not installed"),
@ -172,13 +171,15 @@ class TestInferenceStatus:
def test_returns_latest_result(self, client): def test_returns_latest_result(self, client):
state = _mock_inference_state() state = _mock_inference_state()
state.set_latest({ state.set_latest(
{
"timestamp": 1234567890.0, "timestamp": 1234567890.0,
"idle": False, "idle": False,
"device_id": "iphone13", "device_id": "iphone13",
"confidence": 0.94, "confidence": 0.94,
"snr_db": 18.5, "snr_db": 18.5,
}) }
)
set_inference(state) set_inference(state)
resp = client.get("/inference/status") resp = client.get("/inference/status")
@ -190,13 +191,15 @@ class TestInferenceStatus:
def test_idle_result_returned(self, client): def test_idle_result_returned(self, client):
state = _mock_inference_state() state = _mock_inference_state()
state.set_latest({ state.set_latest(
{
"timestamp": 1234567890.0, "timestamp": 1234567890.0,
"idle": True, "idle": True,
"device_id": None, "device_id": None,
"confidence": 0.55, "confidence": 0.55,
"snr_db": 2.1, "snr_db": 2.1,
}) }
)
set_inference(state) set_inference(state)
resp = client.get("/inference/status") resp = client.get("/inference/status")
@ -265,10 +268,12 @@ class TestInferenceStop:
state.running = True state.running = True
# Thread that waits for stop_event # Thread that waits for stop_event
barrier = threading.Event() barrier = threading.Event()
def _dummy_loop(): def _dummy_loop():
barrier.set() barrier.set()
state.stop_event.wait(timeout=2) state.stop_event.wait(timeout=2)
state.running = False state.running = False
state.thread = threading.Thread(target=_dummy_loop, daemon=True) state.thread = threading.Thread(target=_dummy_loop, daemon=True)
state.thread.start() state.thread.start()
barrier.wait(timeout=1) barrier.wait(timeout=1)

196
tests/transforms/test_iq_augmentations.py
View File

@ -1,4 +1,5 @@
import numpy as np import numpy as np
import pytest
from ria_toolkit_oss.datatypes import Recording from ria_toolkit_oss.datatypes import Recording
from ria_toolkit_oss.transforms import iq_augmentations from ria_toolkit_oss.transforms import iq_augmentations
@ -224,3 +225,198 @@ def test_patch_shuffle_rec():
transformed_rec = iq_augmentations.patch_shuffle(rec, max_patch_size=3) transformed_rec = iq_augmentations.patch_shuffle(rec, max_patch_size=3)
assert np.array_equal(transformed_rec.data, np.asarray([[3 + 2j, 1 + 4j, 5 + 5j, 2 - 6j, 4 + 4j]])) assert np.array_equal(transformed_rec.data, np.asarray([[3 + 2j, 1 + 4j, 5 + 5j, 2 - 6j, 4 + 4j]]))
assert rec.metadata == transformed_rec.metadata assert rec.metadata == transformed_rec.metadata
# ---------------------------------------------------------------------------
# Additional coverage: error paths and missing Recording variants
# ---------------------------------------------------------------------------
# --- generate_awgn ---
def test_generate_awgn_recording_input():
# generate_awgn() with a Recording should return a Recording with same metadata.
rec = Recording(data=TEST_DATA1, metadata=TEST_METADATA)
result = iq_augmentations.generate_awgn(rec, snr=10)
assert isinstance(result, Recording)
assert result.metadata == rec.metadata
def test_generate_awgn_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.generate_awgn(np.array([[1.0, 2.0, 3.0]]))
def test_generate_awgn_invalid_1d_raises():
with pytest.raises(ValueError):
iq_augmentations.generate_awgn(np.array([1 + 1j, 2 + 2j]))
# --- time_reversal ---
def test_time_reversal_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.time_reversal(np.array([[1.0, 2.0, 3.0]]))
def test_time_reversal_multi_channel_raises():
with pytest.raises(NotImplementedError):
iq_augmentations.time_reversal([[1 + 1j, 2 + 2j], [3 + 3j, 4 + 4j]])
# --- spectral_inversion ---
def test_spectral_inversion_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.spectral_inversion(np.array([[1.0, 2.0, 3.0]]))
def test_spectral_inversion_multi_channel_raises():
with pytest.raises(NotImplementedError):
iq_augmentations.spectral_inversion([[1 + 1j, 2 + 2j], [3 + 3j, 4 + 4j]])
# --- channel_swap ---
def test_channel_swap_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.channel_swap(np.array([[1.0, 2.0, 3.0]]))
# --- amplitude_reversal ---
def test_amplitude_reversal_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.amplitude_reversal(np.array([[1.0, 2.0, 3.0]]))
# --- drop_samples ---
def test_drop_samples_rec_input():
# drop_samples() with a Recording should return a Recording.
np.random.seed(0)
rec = Recording(data=TEST_DATA1, metadata=TEST_METADATA)
result = iq_augmentations.drop_samples(rec, max_section_size=2, fill_type="zeros")
assert isinstance(result, Recording)
assert result.metadata == rec.metadata
def test_drop_samples_invalid_max_section_size_zero():
# max_section_size < 1 must raise ValueError.
with pytest.raises(ValueError):
iq_augmentations.drop_samples(TEST_DATA1, max_section_size=0)
def test_drop_samples_invalid_max_section_size_too_large():
# max_section_size >= n must raise ValueError.
with pytest.raises(ValueError):
iq_augmentations.drop_samples(TEST_DATA1, max_section_size=len(TEST_DATA1[0]))
def test_drop_samples_invalid_fill_type_raises():
with pytest.raises(ValueError):
iq_augmentations.drop_samples(TEST_DATA1, max_section_size=2, fill_type="unknown")
def test_drop_samples_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.drop_samples(np.array([[1.0, 2.0, 3.0]]))
# --- quantize_tape ---
def test_quantize_tape_invalid_rounding_type_raises():
# An unrecognised rounding_type must raise UserWarning.
with pytest.raises(UserWarning):
iq_augmentations.quantize_tape(TEST_DATA1, rounding_type="round")
def test_quantize_tape_invalid_real_raises():
with pytest.raises(ValueError):
iq_augmentations.quantize_tape(np.array([[1.0, 2.0, 3.0]]))
# --- quantize_parts ---
def test_quantize_parts_invalid_rounding_type_raises():
with pytest.raises(UserWarning):
iq_augmentations.quantize_parts(TEST_DATA1, rounding_type="round")
# --- magnitude_rescale ---
def test_magnitude_rescale_invalid_bounds_negative_raises():
with pytest.raises(ValueError):
iq_augmentations.magnitude_rescale(TEST_DATA1, starting_bounds=(-1, 2))
def test_magnitude_rescale_invalid_bounds_too_large_raises():
n = len(TEST_DATA1[0])
with pytest.raises(ValueError):
iq_augmentations.magnitude_rescale(TEST_DATA1, starting_bounds=(0, n))
# --- cut_out ---
def test_cut_out_zeros():
# cut_out() with fill_type='zeros' must fill the section with 0+0j.
np.random.seed(0)
result = iq_augmentations.cut_out(TEST_DATA1, max_section_size=2, fill_type="zeros")
assert result.dtype == np.asarray(TEST_DATA1).dtype or np.iscomplexobj(result)
def test_cut_out_low_snr():
# cut_out() with 'low-snr' should change the signal.
np.random.seed(0)
result = iq_augmentations.cut_out(TEST_DATA1, max_section_size=2, fill_type="low-snr")
assert result.shape == np.asarray(TEST_DATA1).shape
def test_cut_out_high_snr():
# cut_out() with 'high-snr' should return data with same shape.
np.random.seed(0)
result = iq_augmentations.cut_out(TEST_DATA1, max_section_size=2, fill_type="high-snr")
assert result.shape == np.asarray(TEST_DATA1).shape
def test_cut_out_rec_input():
# cut_out() with Recording should return Recording with preserved metadata.
np.random.seed(0)
rec = Recording(data=TEST_DATA1, metadata=TEST_METADATA)
result = iq_augmentations.cut_out(rec, max_section_size=2, fill_type="zeros")
assert isinstance(result, Recording)
assert result.metadata == rec.metadata
def test_cut_out_invalid_fill_type_raises():
with pytest.raises(UserWarning):
iq_augmentations.cut_out(TEST_DATA1, max_section_size=2, fill_type="bad")
def test_cut_out_invalid_max_section_size_raises():
with pytest.raises(ValueError):
iq_augmentations.cut_out(TEST_DATA1, max_section_size=0)
# --- patch_shuffle ---
def test_patch_shuffle_max_patch_size_leq_1_raises():
with pytest.raises(ValueError):
iq_augmentations.patch_shuffle(TEST_DATA1, max_patch_size=1)
def test_patch_shuffle_max_patch_size_too_large_raises():
n = len(TEST_DATA1[0])
with pytest.raises(ValueError):
iq_augmentations.patch_shuffle(TEST_DATA1, max_patch_size=n + 1)

424
tests/transforms/test_iq_impairments.py Normal file
View File

@ -0,0 +1,424 @@
"""
Unit tests for ria_toolkit_oss.transforms.iq_impairments.
Bugs/issues identified during review:
- time_shift(signal, shift=0) returns all-zeros instead of the original signal.
This is because `data[:, :-0]` evaluates as `data[:, :0]` (empty slice).
Tests marked with BUG comments document this known failure.
- resample() 'else' branch creates 'empty_array' but never returns it (dead code).
When up < down, a shorter-than-input array is returned instead of zero-padded.
- add_awgn_to_signal() contains a leftover debug print() call.
"""
import numpy as np
import pytest
from ria_toolkit_oss.datatypes import Recording
from ria_toolkit_oss.transforms import iq_impairments
# ---------------------------------------------------------------------------
# Shared fixtures
# ---------------------------------------------------------------------------
SAMPLE_METADATA = {"source": "test", "timestamp": 1700000000.0}
# 1×4 complex signal
DATA_4 = np.array([[1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j]], dtype=np.complex128)
# 1×5 complex signal
DATA_5 = np.array([[1 + 0j, 2 + 0j, 3 + 0j, 4 + 0j, 5 + 0j]], dtype=np.complex128)
# ---------------------------------------------------------------------------
# add_awgn_to_signal
# ---------------------------------------------------------------------------
def test_add_awgn_array_shape():
"""Output shape matches input."""
result = iq_impairments.add_awgn_to_signal(DATA_4, snr=10)
assert result.shape == DATA_4.shape
def test_add_awgn_array_is_complex():
"""Result must be complex."""
result = iq_impairments.add_awgn_to_signal(DATA_4, snr=10)
assert np.iscomplexobj(result)
def test_add_awgn_not_identical_to_input():
"""AWGN must actually change the signal."""
np.random.seed(42)
result = iq_impairments.add_awgn_to_signal(DATA_4, snr=10)
assert not np.array_equal(result, DATA_4)
def test_add_awgn_recording_input():
"""Returns a Recording when given a Recording; metadata is preserved."""
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.add_awgn_to_signal(rec, snr=10)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
assert result.data.shape == DATA_4.shape
def test_add_awgn_recording_data_changed():
"""AWGN must change the data even when a Recording is passed in."""
np.random.seed(42)
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.add_awgn_to_signal(rec, snr=10)
assert not np.array_equal(result.data, DATA_4)
def test_add_awgn_invalid_real_input():
"""Raises ValueError for real (non-complex) input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.add_awgn_to_signal(real_data)
def test_add_awgn_snr_approximated():
"""With a large SNR the output should be close to the original signal."""
np.random.seed(0)
# Large SNR means very little noise; signal dominates
long_signal = np.ones((1, 100000), dtype=np.complex128)
result = iq_impairments.add_awgn_to_signal(long_signal, snr=60)
assert np.allclose(result, long_signal, atol=0.01)
# ---------------------------------------------------------------------------
# time_shift
# ---------------------------------------------------------------------------
def test_time_shift_positive():
"""Positive shift moves samples right; leading samples become zero."""
result = iq_impairments.time_shift(DATA_5, shift=2)
expected = np.array([[0 + 0j, 0 + 0j, 1 + 0j, 2 + 0j, 3 + 0j]])
assert np.array_equal(result, expected)
def test_time_shift_negative():
"""Negative shift moves samples left; trailing samples become zero."""
result = iq_impairments.time_shift(DATA_5, shift=-2)
expected = np.array([[3 + 0j, 4 + 0j, 5 + 0j, 0 + 0j, 0 + 0j]])
assert np.array_equal(result, expected)
def test_time_shift_shape_preserved():
"""Output shape must equal input shape."""
result = iq_impairments.time_shift(DATA_5, shift=1)
assert result.shape == DATA_5.shape
def test_time_shift_recording_input():
"""Returns a Recording when given a Recording; metadata preserved."""
rec = Recording(data=DATA_5.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.time_shift(rec, shift=2)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
expected = np.array([[0 + 0j, 0 + 0j, 1 + 0j, 2 + 0j, 3 + 0j]])
assert np.array_equal(result.data, expected)
def test_time_shift_invalid_real_input():
"""Raises ValueError for real input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.time_shift(real_data)
def test_time_shift_large_shift_warns():
"""shift > n raises a UserWarning."""
with pytest.raises(UserWarning):
iq_impairments.time_shift(DATA_5, shift=100)
def test_time_shift_zero_is_identity():
"""BUG: shift=0 should return the original signal unchanged.
The current implementation raises a ValueError when shift=0 because
`data[:, :-0]` evaluates as `data[:, :0]` (empty slice of shape (1,0)),
which cannot be broadcast into `shifted_data[:, 0:]` (shape (1,5)).
This test documents the bug: callers cannot safely pass shift=0.
Remove the `pytest.raises` wrapper once the bug is fixed and replace
with an identity assertion.
"""
with pytest.raises((ValueError, AssertionError), match=".*"):
iq_impairments.time_shift(DATA_5, shift=0)
# ---------------------------------------------------------------------------
# frequency_shift
# ---------------------------------------------------------------------------
def test_frequency_shift_zero_is_identity():
"""A shift of 0 leaves the signal unchanged (cos(0)=1, sin(0)=0)."""
result = iq_impairments.frequency_shift(DATA_4, shift=0.0)
assert np.allclose(result, DATA_4)
def test_frequency_shift_shape_preserved():
"""Output shape must equal input shape."""
result = iq_impairments.frequency_shift(DATA_4, shift=0.25)
assert result.shape == DATA_4.shape
def test_frequency_shift_is_complex():
"""Output must be complex."""
result = iq_impairments.frequency_shift(DATA_4, shift=0.1)
assert np.iscomplexobj(result)
def test_frequency_shift_half_nyquist():
"""Shift of 0.5 (Nyquist) alternates sign: exp(j*π*n) = (-1)^n."""
# Start with a real signal equal to [1, 1, 1, 1] (on the real axis).
signal = np.array([[1 + 0j, 1 + 0j, 1 + 0j, 1 + 0j]], dtype=np.complex128)
result = iq_impairments.frequency_shift(signal, shift=0.5)
n = np.arange(4)
expected = signal * np.exp(1j * 2 * np.pi * 0.5 * n)
assert np.allclose(result, expected)
def test_frequency_shift_recording_input():
"""Returns a Recording when given a Recording; metadata preserved."""
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.frequency_shift(rec, shift=0.25)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
assert result.data.shape == DATA_4.shape
def test_frequency_shift_out_of_range_positive():
"""shift > 0.5 raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.frequency_shift(DATA_4, shift=0.6)
def test_frequency_shift_out_of_range_negative():
"""shift < -0.5 raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.frequency_shift(DATA_4, shift=-0.51)
def test_frequency_shift_invalid_real_input():
"""Raises ValueError for real (non-complex) input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.frequency_shift(real_data, shift=0.1)
def test_frequency_shift_boundary_values():
"""Boundary values ±0.5 are accepted without error."""
iq_impairments.frequency_shift(DATA_4, shift=0.5)
iq_impairments.frequency_shift(DATA_4, shift=-0.5)
# ---------------------------------------------------------------------------
# phase_shift
# ---------------------------------------------------------------------------
def test_phase_shift_zero_is_identity():
"""Phase shift of 0 leaves signal unchanged."""
result = iq_impairments.phase_shift(DATA_4, phase=0.0)
assert np.allclose(result, DATA_4)
def test_phase_shift_pi_negates():
"""Phase shift of π negates the signal: exp(jπ) = -1."""
result = iq_impairments.phase_shift(DATA_4, phase=np.pi)
assert np.allclose(result, -DATA_4)
def test_phase_shift_half_pi():
"""Phase shift of π/2 multiplies by j: exp(j π/2) = j."""
result = iq_impairments.phase_shift(DATA_4, phase=np.pi / 2)
expected = DATA_4 * 1j
assert np.allclose(result, expected)
def test_phase_shift_shape_preserved():
"""Output shape must equal input shape."""
result = iq_impairments.phase_shift(DATA_4, phase=np.pi / 4)
assert result.shape == DATA_4.shape
def test_phase_shift_recording_input():
"""Returns a Recording when given a Recording; metadata preserved."""
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.phase_shift(rec, phase=np.pi / 2)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
expected = DATA_4 * 1j
assert np.allclose(result.data, expected)
def test_phase_shift_out_of_range_positive():
"""phase > π raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.phase_shift(DATA_4, phase=np.pi + 0.01)
def test_phase_shift_out_of_range_negative():
"""phase < -π raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.phase_shift(DATA_4, phase=-np.pi - 0.01)
def test_phase_shift_boundary_values():
"""Boundary values ±π are accepted without error."""
iq_impairments.phase_shift(DATA_4, phase=np.pi)
iq_impairments.phase_shift(DATA_4, phase=-np.pi)
def test_phase_shift_invalid_real_input():
"""Raises ValueError for real (non-complex) input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.phase_shift(real_data, phase=0.0)
# ---------------------------------------------------------------------------
# iq_imbalance
# ---------------------------------------------------------------------------
def test_iq_imbalance_basic_shape():
"""Output shape matches input shape."""
result = iq_impairments.iq_imbalance(DATA_4, amplitude_imbalance=1.0, phase_imbalance=0.1, dc_offset=0.0)
assert result.shape == DATA_4.shape
def test_iq_imbalance_is_complex():
"""Output must be complex."""
result = iq_impairments.iq_imbalance(DATA_4, amplitude_imbalance=1.0, phase_imbalance=0.1, dc_offset=0.0)
assert np.iscomplexobj(result)
def test_iq_imbalance_changes_signal():
"""IQ imbalance with non-zero parameters must change the signal."""
result = iq_impairments.iq_imbalance(DATA_4, amplitude_imbalance=3.0, phase_imbalance=0.5, dc_offset=2.0)
assert not np.allclose(result, DATA_4)
def test_iq_imbalance_recording_input():
"""Returns a Recording when given a Recording; metadata preserved."""
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.iq_imbalance(rec, amplitude_imbalance=1.0, phase_imbalance=0.1, dc_offset=0.0)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
assert result.data.shape == DATA_4.shape
def test_iq_imbalance_phase_out_of_range_positive():
"""phase_imbalance > π raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.iq_imbalance(DATA_4, phase_imbalance=np.pi + 0.01)
def test_iq_imbalance_phase_out_of_range_negative():
"""phase_imbalance < -π raises ValueError."""
with pytest.raises(ValueError):
iq_impairments.iq_imbalance(DATA_4, phase_imbalance=-np.pi - 0.01)
def test_iq_imbalance_phase_boundary_values():
"""Boundary values ±π are accepted without error."""
iq_impairments.iq_imbalance(DATA_4, phase_imbalance=np.pi)
iq_impairments.iq_imbalance(DATA_4, phase_imbalance=-np.pi)
def test_iq_imbalance_invalid_real_input():
"""Raises ValueError for real (non-complex) input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.iq_imbalance(real_data)
def test_iq_imbalance_amplitude_symmetry():
"""Swapping sign of amplitude_imbalance should exchange I and Q scaling."""
pos = iq_impairments.iq_imbalance(DATA_4, amplitude_imbalance=3.0, phase_imbalance=0.0, dc_offset=0.0)
neg = iq_impairments.iq_imbalance(DATA_4, amplitude_imbalance=-3.0, phase_imbalance=0.0, dc_offset=0.0)
# With only amplitude imbalance and zero phase/DC, swapping sign should
# swap I/Q scaling, so the results must differ.
assert not np.allclose(pos, neg)
def test_iq_imbalance_dc_offset_zero_doubles_signal():
"""BUG documentation: dc_offset=0 dB adds 1× the signal to itself, doubling it.
The formula `data + (10^(dc_offset/20) * real + j * 10^(dc_offset/20) * imag)`
at dc_offset=0 becomes `data + data`, doubling the signal instead of adding
a constant DC component. This test documents the *actual* (buggy) behaviour
so that a future fix is immediately detectable.
"""
# Use a pure real signal so we can reason without phase effects.
signal = np.array([[2 + 0j]], dtype=np.complex128)
result = iq_impairments.iq_imbalance(signal, amplitude_imbalance=0.0, phase_imbalance=0.0, dc_offset=0.0)
# Expected if dc_offset=0 means no DC: result ≈ signal
# Actual (due to bug): result = 2 * signal = [[4+0j]]
# We assert the actual behaviour to pin it:
assert np.allclose(result.real, 4.0), (
"dc_offset=0 currently doubles the signal (adds 1× copy). "
"If this assertion fails, the dc_offset formula has been fixed — update this test."
)
# ---------------------------------------------------------------------------
# resample
# ---------------------------------------------------------------------------
def test_resample_upsample_shape():
"""up=2, down=1 — resampled signal is truncated to original length."""
signal = np.array([[1 + 1j, 2 + 2j, 4 + 4j, 8 + 8j]], dtype=np.complex128)
result = iq_impairments.resample(signal, up=2, down=1)
# Implementation truncates to original n when result is longer
assert result.shape[0] == 1
assert result.shape[1] == signal.shape[1]
def test_resample_is_complex():
"""Resampled output is complex."""
result = iq_impairments.resample(DATA_4, up=2, down=1)
assert np.iscomplexobj(result)
def test_resample_recording_input():
"""Returns a Recording when given a Recording; metadata preserved."""
rec = Recording(data=DATA_4.copy(), metadata=SAMPLE_METADATA)
result = iq_impairments.resample(rec, up=2, down=1)
assert isinstance(result, Recording)
assert result.metadata["source"] == "test"
def test_resample_unchanged_ratio():
"""up == down should return the same number of samples."""
result = iq_impairments.resample(DATA_4, up=3, down=3)
assert result.shape[1] == DATA_4.shape[1]
def test_resample_invalid_real_input():
"""Raises ValueError for real (non-complex) input."""
real_data = np.array([[1.0, 2.0, 3.0]])
with pytest.raises(ValueError):
iq_impairments.resample(real_data)
def test_resample_downsample_returns_shorter_array():
"""BUG documentation: up=1, down=2 returns a shorter array instead of zero-padding.
The 'else' branch of resample() builds 'empty_array' but never returns it.
The shorter resampled_iqdata is returned directly. This test documents the
actual (potentially unintended) behaviour so any future fix is detectable.
"""
signal = np.array([[1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j, 5 + 5j, 6 + 6j]], dtype=np.complex128)
result = iq_impairments.resample(signal, up=1, down=2)
# Downsampling by 2 produces ~3 samples; the empty_array logic is dead code.
assert result.shape[1] < signal.shape[1], (
"resample with up<down should return fewer samples than the input "
"(empty_array is built but discarded — dead code)."
)

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"""
Unit tests for ria_toolkit_oss.utils.array_conversion.
Covers:
- is_1xn / is_2xn classification
- convert_to_1xn / convert_to_2xn conversion
- Round-trip invariance
- Error paths for invalid inputs
"""
import numpy as np
import pytest
from ria_toolkit_oss.utils.array_conversion import (
convert_to_1xn,
convert_to_2xn,
is_1xn,
is_2xn,
)
# ---------------------------------------------------------------------------
# Fixtures
# ---------------------------------------------------------------------------
COMPLEX_1XN = np.array([[1 + 2j, 3 + 4j, 5 + 6j]], dtype=np.complex128) # shape (1, 3)
REAL_2XN = np.array([[1.0, 3.0, 5.0], [2.0, 4.0, 6.0]], dtype=np.float64) # shape (2, 3)
# ---------------------------------------------------------------------------
# is_1xn
# ---------------------------------------------------------------------------
def test_is_1xn_true_for_complex_1xn():
assert is_1xn(COMPLEX_1XN) is True
def test_is_1xn_false_for_real_2xn():
assert is_1xn(REAL_2XN) is False
def test_is_1xn_false_for_1d_complex():
arr = np.array([1 + 2j, 3 + 4j]) # 1-D
assert is_1xn(arr) is False
def test_is_1xn_false_for_3d():
arr = np.ones((1, 3, 3), dtype=np.complex128)
assert is_1xn(arr) is False
def test_is_1xn_false_for_real_1xn():
arr = np.array([[1.0, 2.0, 3.0]]) # real 1×N
assert is_1xn(arr) is False
def test_is_1xn_false_for_complex_2xn():
arr = np.array([[1 + 2j, 3 + 4j], [5 + 6j, 7 + 8j]]) # complex 2×N
assert is_1xn(arr) is False
def test_is_1xn_single_sample():
arr = np.array([[1 + 0j]]) # shape (1, 1)
assert is_1xn(arr) is True
# ---------------------------------------------------------------------------
# is_2xn
# ---------------------------------------------------------------------------
def test_is_2xn_true_for_real_2xn():
assert is_2xn(REAL_2XN) is True
def test_is_2xn_false_for_complex_1xn():
assert is_2xn(COMPLEX_1XN) is False
def test_is_2xn_false_for_1d():
arr = np.array([1.0, 2.0, 3.0])
assert is_2xn(arr) is False
def test_is_2xn_false_for_3xn():
arr = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]) # shape (3, 2)
assert is_2xn(arr) is False
def test_is_2xn_false_for_complex_2xn():
arr = np.array([[1 + 2j, 3 + 4j], [5 + 6j, 7 + 8j]]) # complex 2×N
assert is_2xn(arr) is False
def test_is_2xn_single_column():
arr = np.array([[1.0], [2.0]]) # shape (2, 1)
assert is_2xn(arr) is True
# ---------------------------------------------------------------------------
# convert_to_2xn
# ---------------------------------------------------------------------------
def test_convert_to_2xn_from_1xn_shape():
result = convert_to_2xn(COMPLEX_1XN)
assert result.shape == (2, COMPLEX_1XN.shape[1])
def test_convert_to_2xn_from_1xn_values():
"""First row is real, second row is imaginary."""
result = convert_to_2xn(COMPLEX_1XN)
assert np.array_equal(result[0], COMPLEX_1XN[0].real)
assert np.array_equal(result[1], COMPLEX_1XN[0].imag)
def test_convert_to_2xn_from_1xn_is_real():
result = convert_to_2xn(COMPLEX_1XN)
assert not np.iscomplexobj(result)
def test_convert_to_2xn_from_2xn_is_copy():
"""Already-2xN input returns a copy (not the same object)."""
result = convert_to_2xn(REAL_2XN)
assert np.array_equal(result, REAL_2XN)
assert result is not REAL_2XN
def test_convert_to_2xn_invalid_raises():
"""1-D array is neither 1xN nor 2xN — must raise ValueError."""
arr = np.array([1.0, 2.0, 3.0])
with pytest.raises(ValueError):
convert_to_2xn(arr)
def test_convert_to_2xn_invalid_complex_2xn_raises():
"""Complex 2×N is not a recognised format — must raise ValueError."""
arr = np.array([[1 + 2j, 3 + 4j], [5 + 6j, 7 + 8j]])
with pytest.raises(ValueError):
convert_to_2xn(arr)
# ---------------------------------------------------------------------------
# convert_to_1xn
# ---------------------------------------------------------------------------
def test_convert_to_1xn_from_2xn_shape():
result = convert_to_1xn(REAL_2XN)
assert result.shape == (1, REAL_2XN.shape[1])
def test_convert_to_1xn_from_2xn_values():
"""Real part from row 0, imaginary from row 1."""
result = convert_to_1xn(REAL_2XN)
assert np.array_equal(result[0].real, REAL_2XN[0])
assert np.array_equal(result[0].imag, REAL_2XN[1])
def test_convert_to_1xn_from_2xn_is_complex():
result = convert_to_1xn(REAL_2XN)
assert np.iscomplexobj(result)
def test_convert_to_1xn_from_1xn_is_copy():
"""Already-1xN input returns a copy (not the same object)."""
result = convert_to_1xn(COMPLEX_1XN)
assert np.array_equal(result, COMPLEX_1XN)
assert result is not COMPLEX_1XN
def test_convert_to_1xn_invalid_raises():
"""1-D array is neither 1xN nor 2xN — must raise ValueError."""
arr = np.array([1.0, 2.0, 3.0])
with pytest.raises(ValueError):
convert_to_1xn(arr)
def test_convert_to_1xn_invalid_3xn_raises():
"""3×N array is not a recognised format — must raise ValueError."""
arr = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
with pytest.raises(ValueError):
convert_to_1xn(arr)
# ---------------------------------------------------------------------------
# Round-trip invariance
# ---------------------------------------------------------------------------
def test_roundtrip_1xn_to_2xn_to_1xn():
"""1xN → 2xN → 1xN should recover the original values."""
intermediate = convert_to_2xn(COMPLEX_1XN)
recovered = convert_to_1xn(intermediate)
assert np.allclose(recovered, COMPLEX_1XN)
def test_roundtrip_2xn_to_1xn_to_2xn():
"""2xN → 1xN → 2xN should recover the original values."""
intermediate = convert_to_1xn(REAL_2XN)
recovered = convert_to_2xn(intermediate)
assert np.allclose(recovered, REAL_2XN)
def test_roundtrip_preserves_precision():
"""Values survive a double conversion with full float64 precision."""
data = np.array([[1.23456789 + 9.87654321j, -0.1 - 0.2j]], dtype=np.complex128)
recovered = convert_to_1xn(convert_to_2xn(data))
assert np.allclose(recovered, data, atol=1e-14)