<commit_before>tsplot
------

The `tsplot.py` script is a wrapper around matplotlib for displaying a collection of
time series plots.

## Input data

`tsplot` reads timeseries in JSON format, according to the following conventions.

```
{
    "units": <units>
    "name":  <name>
    <other key-value metadata>
    "data": {
        "time": [ <time values> ]
        <trace name>: [ <trace values> ]
    }
}
```

The `data` object must contain numeric arrays, with at least one with the key `time`;
other members of `data` correspond to traces sampled at the corresponding time values.

The other members of the top level object are regarded as metadata, with some keys
treated specially:
 * `units` are used to distinguish different axes for plotting, and the labels for those
   axes. It's value is either a string, where the specified unit is taken as applying to
   all included traces, or an object representing a mapping of trace names to their<commit_msg>Tiny documentation fix: tsplot vs tsplot.py<commit_after>tsplot
------

The `tsplot` script is a wrapper around matplotlib for displaying a collection of
time series plots.

## Input data

`tsplot` reads timeseries in JSON format, according to the following conventions.

```
{
    "units": <units>
    "name":  <name>
    <other key-value metadata>
    "data": {
        "time": [ <time values> ]
        <trace name>: [ <trace values> ]
    }
}
```

The `data` object must contain numeric arrays, with at least one with the key `time`;
other members of `data` correspond to traces sampled at the corresponding time values.

The other members of the top level object are regarded as metadata, with some keys
treated specially:
 * `units` are used to distinguish different axes for plotting, and the labels for those
   axes. It's value is either a string, where the specified unit is taken as applying to
   all included traces, or an object representing a mapping of trace names to their
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