Stream Buffer API

class joulescope.stream_buffer.StreamBuffer

Efficient real-time Joulescope data buffering.

Parameters:
  • duration – The total length of the buffering in seconds.
  • reductions – The list of reduction integers. Each integer represents the reduction amount for each resuting sample in units of samples of the previous reduction. Reduction 0 is in raw sample units.
data_buffer

Get the underlying data buffer.

WARNING: Don’t use this! It should only be used for unit testing.

data_get()

Get the samples with statistics.

Parameters:
  • start – The starting sample id (inclusive).
  • stop – The ending sample id (exclusive).
  • increment – The number of raw samples.
  • out – The optional output np.ndarray((N, STATS_FIELD_COUNT), dtype=DTYPE) to populate with the result. None (default) will construct and return a new array.
Returns:

The np.ndarray((N, STATS_FIELD_COUNT), dtype=DTYPE) data.

This method provides fast access to statistics data, primarily for graphical display. Applications should prefer using samples_get() which provides metadata along with the samples.

get_reduction()

Get reduction data directly (for testing only).

Parameters:
  • idx – The reduction index.
  • start – The starting sample_id (inclusive).
  • stop – The ending sample_id (exclusive).
Returns:

The The np.ndarray((N, STATS_FIELD_COUNT), dtype=DTYPE) reduction data which normally is memory mapped to the underlying data, but will be copied on rollover.

This method should not be used by production code. Use data_get() or samples_get().

has_raw

Query if this instance provides raw sample data.

Returns:True if samples_get supports ‘raw’, False otherwise.
insert()

Insert new device USB data into the buffer.

Parameters:data – The new data to insert.
Returns:False to continue streaming, True to end.
insert_raw()

Insert raw data into the buffer

Parameters:data – The np.array of np.uint16 data to insert.
Returns:False to continue streaming, True to end.
limits_samples

Get the sample limits.

Returns:(start, stop) where start is inclusive and stop is exclusive.
In other words:
self.limits_time == (b.sample_id_to_time(b.limits_samples[0]),
b.sample_id_to_time(b.limits_samples[1]))
limits_time

Get the time limits.

Returns:(start, stop). Stop corresponds to the exclusive sample returned by b.limits_samples[1].
sample_id_range

Get the range of sample ids currently available in the buffer.

Returns:Tuple of sample_id start, sample_id end. Start and stop follow normal python indexing: start is inclusive, end is exclusive
samples_get()

Get exact sample data without any skips or reductions.

Parameters:
  • start – The starting sample id (inclusive).
  • stop – The ending sample id (exclusive).
  • fields –

    The single field or list of field names to return. None (default) is equivalent to [‘current’, ‘voltage’, ‘power’, ‘current_range’, ‘current_lsb’, ‘voltage_lsb’, ‘raw’]. The available fields are:

    • raw: The raw u16 data from Joulescope. Equivalent to self.raw_get(start, stop)
    • raw_current: The raw 14-bit current data in LSBs.
    • raw_voltage: The raw 14-bit voltage data in LSBs.
    • current: The calibrated float32 current data array in amperes.
    • voltage: The calibrated float32 voltage data array in volts.
    • current_voltage: The calibrated float32 Nx2 array of current, voltage.
    • power: The calibrated float32 power data array in watts.
    • bits: The (voltage_lsb << 5) | (current_lsb << 4) | current_range
    • current_range: The current range. 0 = 10A, 6 = 18 uA, 7=off.
    • current_lsb: The current LSB, which can be assign to a general purpose input.
    • voltage_lsb: The voltage LSB, which can be assign to a general purpose input.
Returns:

The dict containing top-level ‘time ‘ and ‘signals’ keys. The ‘time’ value is a dict contain the timing metadata for these samples. The ‘signals’ value is a dict with one key for each field in fields. Each field value is also a dict with entries ‘value’ and ‘units’. However, if single field string is provided to fields, then just return that field’s value.
statistics_get()

Get exact statistics over the specified range.

Parameters:
  • start – The starting sample_id (inclusive).
  • stop – The ending sample_id (exclusive).
  • out – The optional output np.ndarray(STATS_FIELD_COUNT, dtype=DTYPE). None (default) creates and outputs a new record.
Returns:

The tuple of (np.ndarray(STATS_FIELD_COUNT, dtype=DTYPE), [start, stop]). The values of start and stop will be constrained to the available range.