pw_sensor Python package#

A modular way to see the world

Experimental Python C++17

  • Configure Sensors: Update the sensor configurations to match your requirements. Sensor configurations can be checked at compile time using a YAML sensor description.

  • 2 Phase Reading: Design your own pipeline and priorities. Sensor can be read on one thread (or no thread if DMA is available) and the data can be decoded on another thread/core/device.

The pw_sensor Python package provides utilities for generating data and code for Pigweed sensor drivers.

Warning

This package is under development and the APIs are VERY likely to change.

Using the package#

Typical users of pw_sensor begin by writing a YAML description of their sensor using the metadata_schema.json format, e.g.:

deps:
   - "pw_sensor/channels.yaml"
   - "pw_sensor/attributes.yaml"
compatible:
   org: "Bosch"
   part: "BMA4xx"
channels:
   acceleration: []
   die_temperature: []

pw_sensor provides a validator which will resolve any ‘default’ properties and make the final YAML easier for code generators to consume. The returned dictionary uses the resolved_schema.json format.

Every platform/language may implement their own generator. Generators consume the validated (schema-compliant) YAML and may produce many types of outputs, such as a PDF datasheet, a C++ abstract class definition, or a Zephyr header of definitions describing the sensor.

Describing a sensor#

When describing a sensor from the user’s perspective, there are 3 primary points of interaction:

  1. compatible descriptor

  2. channels

  3. attributes

  4. triggers

Note

Compatible string in Linux’s devicetree are used to detail what a hardware device is. They include a manufacturer and a model name in the format: <manufacturer>,<model>. In order to make this a bit more generic and still functional with devicetree, Pigweed’s compatible node consists of 2 separate properties instead of a single string: org and part. This abstracts away the devicetree model such that generators may produce other targeted code. To read more about the compatible property, see Understanding the compatible Property

Both channels and attributes covered in 0120: Sensor Configuration, while the compatible descriptor allows us to have a unique identifier for each sensor. Next, we need a way to describe a sensor in a platform and language agnostic way.

What are channels?#

A channel is something that we can measure from a sensor. It’s reasonable to ask “why not call it a measurement”? The answer is that a measurement isn’t specific enough. A single illuminance sensor might provide a lux reading for: - Total lux (amount of light per square meter) - Red lux (amount of red light per square meter) - Green lux (amount of green light per square meter) - Blue lux (amount of blue light per square meter) - UV lux (amount of UV light per square meter) - IR lux (amount of infra-red light per square meter)

All these are a “measurement” of light intensity, but they’re different channels. When defining a channel we need to provide units. In the example above, the units are lux. Represented by the symbol “lx”. It’s likely that when verbose logging is needed or when generating documentation we might want to also associate a name and a longer description for the channel. This leaves us with the following structure for a channel:

<channel_id>:
   "name": "string"
   "description": "string"
   "units": <string_units_id>

When we construct the final sensor metadata, we can list the channels supported by that sensor. In some cases, the same channel may be available more than once. This happens at times with temperature sensors. In these cases, we can list multiple instances of a channel. Generally, if no instances are provided, it will be assumed that there’s 1 instance of the channel. Otherwise, we might have something like:

channels:
   ambient_temperature:
      -  name: "-X"
         description: "temperature measured in the -X direction"
         units: "temperature"
      -  name: "X"
         description: "temperature measured in the +X direction"
         units: "temperature"

What are attributes?#

Attributes are used to change the behavior of a sensor. They’re defined using the attributes key and are structured by associating the defined attribute type with a channel along with units and a representation (float, signed, or unsigned). Here’s an example:

attributes:
   -  attribute: "sample_rate"
      channel: "acceleration"
      units: "frequency"
      representation: "float"

When associated with a sensor, attributes define specific instances of configurable states for that sensor:

compatible: ...
channels: ...
attributes:
   -  {}

What are triggers?#

Triggers are events that have an interrupt associated with them. We can define common triggers which sensors can individually subscribe to. The definition looks like:

triggers:
   fifo_watermark:
      name: "FIFO watermark"
      description: "Interrupt when the FIFO watermark has been reached (set as an attribute)"

When associated with a sensor, we simply need to match the right key in a list:

compatible: ...
channels: ...
attributes: ...
triggers:
   -  fifo_watermark

The Validator class#

The Validator class is used to take a sensor spec YAML file and expand it while verifying that all the information is available. It consists of 2 layers: 1. Declarations 2. Definitions

The declaration YAML#

The declaration YAML files allow projects to define new sensor channels and attributes for their drivers. This allows proprietary functionality of sensors which cannot be made public. Pigweed will provide some baseline set of channels and attributes.

The following YAML file is used to create a sensor which counts cakes. The sensor provides the ability to get the total cake count or a separate large/small cake count (for a total of 3 channels):

# File: my/org/sensors/cakes.yaml
units:
   cake:
      symbol: "cakes"
channels:
  cakes:
      description: "The number of cakes seen by the sensor"
      units: "cake"
   cakes_small:
      description: "The number of cakes measuring 6 inches or less"
      units: "cake"
   cakes_large:
      description: "The number of cakes measuring more than 6 inches"
      units: "cake"

The above YAML file will enable a 3 new channels: cakes, cakes_small, and cakes_large. All 3 channels will use a unit cake. A sensor implementing this channel would provide a definition file:

# File: my/org/sensors/cake/sensor.yaml
deps:
   - "my/org/sensors/cakes.yaml"
compatible:
   org: "myorg"
   part: "cakevision"
channels:
   cakes: []
   cakes_small: []
   cakes_large: []

When validated, the above YAML will be converted to fill in the defined values. This means that channels/cakes will be automatically filled with:

  • name: "cakes": automatically derived from the name sinde the definition did not provide a name.

  • description: "The number of cakes seen by the sensor": attained from the definition file.

  • units

    • name: "cake": derived from the definition’s symbol since name is not explicitly specified

    • symbol: "cake": attained from definition file

Output#

The resulting output uses references. At times described above, things such as units will be referenced from inside a sensor’s channel. When validated, the corresponding units entry is guaranteed to be found at the top level units map. Currently, there will be 5 keys in the returned dictionary: sensors, channels, attributes, units, and triggers.

The sensors key is a dictionary mapping unique identifiers generated from the sensor’s compatible string to the resolved values. There will always be exactly 1 of these since each sensor spec is required to only describe a single sensor (we’ll see an example soon for how these are merged to create a project level sensor description). Each sensor will contain: name string, description description struct, compatible struct, channels dictionary, attributes list, and triggers list.

The difference between the /sensors/channels and /channels dictionaries is that the former can be thought of as instantiating the latter.

Sensor descriptor script#

A descriptor script is added to Pigweed via the pw sensor-desc subcommand. This command allows validating multiple sensor descriptors and passing the unified descriptor to a generator.

CLI Flags#

Flag(s)

Description

--include-path, -I

Directories in which to search for dependency files.

--verbose, -v

Increase the verbosity level (can be used multiple times). Default verbosity is WARNING, so additional flags increase it to INFO then DEBUG.

--generator, -g

Generator ommand to run along with any flags. Data will be passed into the generator as YAML through stdin.

-o

Write output to file instead of stdout.

What are the include paths used for?#

The sensor descriptor includes a deps list with file names which define various attributes used by the sensor. We wouldn’t want to check in absolute paths in these lists, so instead, it’s possible to list a relative path to the root of the project, then add include paths to the tool which will help resolve the dependencies. This should look familiar to header file resolution in C/C++.

What is a generator?#

The sensor descriptor script validates each sensor descriptor file then creates a superset of all sensors and channels (making sure there aren’t conflicts). Once complete, it will call the generator (if available) and pass the string YAML representation of the superset into the generator via stdin. Some ideas for generators:

  • Create a header with a list of all channels, assigning each channel a unique ID.

  • Generate RST file with documentation on each supported sensor.

  • Generate stub driver implementation by knowing which channels and attributes are supported.

Example run (prints to stdout):

$ pw --no-banner sensor-desc -I pw_sensor/ \
  -g "python3 pw_sensor/py/pw_sensor/constants_generator.py --package pw.sensor" \
  pw_sensor/sensor.yaml