Metadata-Version: 2.1
Name: ess_streaming_data_types
Version: 0.21.0
Summary: Python utilities for handling ESS streamed data
Home-page: https://github.com/ess-dmsc/python-streaming-data-types
Author: ScreamingUdder
License: BSD 2-Clause License
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE


# Python Streaming Data Types
Utilities for working with the FlatBuffers schemas used at the European
Spallation Source ERIC for data transport.

https://github.com/ess-dmsc/streaming-data-types

## FlatBuffer Schemas

|name|description|
|----|-----------|
|hs00|Histogram schema (deprecated in favour of hs01)|
|hs01|Histogram schema|
|ns10|NICOS cache entry schema|
|pl72|Run start|
|6s4t|Run stop|
|f142|Log data (deprecated in favour of f144)|
|f144|Log data|
|ev42|Event data (deprecated in favour of ev44)|
|ev43|Event data from multiple pulses|
|ev44|Event data with signed data types|
|x5f2|Status messages|
|tdct|Timestamps|
|ep00|EPICS connection info (deprecated in favour of ep01)|
|ep01|EPICS connection info|
|rf5k|Forwarder configuration update|
|answ|File-writer command response|
|wrdn|File-writer finished writing|
|NDAr|**Deprecated**|
|ADAr|EPICS areaDetector data|
|al00|Alarm/status messages used by the Forwarder and NICOS|
|senv|**Deprecated**|
|se00|Arrays with optional timestamps, for example waveform data. Replaces _senv_. |

### hs00 and hs01
Schema for histogram data. It is one of the more complicated to use schemas.
It takes a Python dictionary as its input; this dictionary needs to have correctly
named fields.

The input histogram data for serialisation and the output deserialisation data
have the same dictionary "layout".
Example for a 2-D histogram:
```json
hist = {
    "source": "some_source",
    "timestamp": 123456,
    "current_shape": [2, 5],
    "dim_metadata": [
        {
            "length": 2,
            "unit": "a",
            "label": "x",
            "bin_boundaries": np.array([10, 11, 12]),
        },
        {
            "length": 5,
            "unit": "b",
            "label": "y",
            "bin_boundaries": np.array([0, 1, 2, 3, 4, 5]),
        },
    ],
    "last_metadata_timestamp": 123456,
    "data": np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]]),
    "errors": np.array([[5, 4, 3, 2, 1], [10, 9, 8, 7, 6]]),
    "info": "info_string",
}
```
The arrays passed in for `data`, `errors` and `bin_boundaries` can be NumPy arrays
or regular lists, but on deserialisation they will be NumPy arrays.


## Developer documentation

See [README_DEV.md](README_DEV.md)
