Пример #1
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def PrimaryFilteringStream():
    ''' Filter the stream for just primary results.

        **Stream Inputs**

            md : dict
                No requirements

            data : dict
                must have a 2D np.ndarray with one of accepted detector
                keys
        **Stream Outputs**
            Two streams are outputted, sout and serr

            sout : the stream with valid data
                Outputs from zero to any number streams
                (depends on how many detectors were found)
                md :
                    detector_key : the detector key (string)
                data :
                    data with only one image as detector key
                    if there was more than one, it selects one of them
                    Note this has unspecified behaviour.
            serr : the stream with bad data. This can be sinked to an error
                stream

        Examples
        --------
        >>> # A typical workflow is as follows:
        >>> # instantiate the main stream input
        >>> from streamz import Stream
        >>> s = Stream()
        >>> # create the filtering stream
        >>> from SciStreams.streams.XS_Streams import PrimaryFilteringStream
        >>> sin, sout = PrimaryFilteringStream()
        >>> s.connect(sin)
        >>> import numpy as np
        >>> # create dummy detector image, from pilatus300
        >>> img = np.random.random((619, 487))
        >>> from SciStreams.core.StreamDoc import StreamDoc
        >>> sdoc = StreamDoc(kwargs=dict(pilatus300_image=img))
        >>> # save result in a list L that you can review later
        >>> L = sout.sink_to_list()
        >>> # emit the data
        >>> s.emit(sdoc)

        Returns
        -------
        sin : Stream instance
            the source stream (see Stream Inputs)

        sout : Stream instance
            the output stream (see Stream Outputs)
    '''
    sin = sc.Stream(stream_name="Primary Filter")
    # a primary filter, data will not go through if does not match attributes
    sout = sin.filter(filter_attributes)
    # get the error streams attributes (to output to some log)
    serr = sin.filter(lambda x: not filter_attributes)
    serr = scs.get_attributes(serr)
    serr = scs.add_attributes(serr, error="primary_filter")
    sout = sc.map(sout, pick_allowed_detectors)
    # turn list into individual streams
    # (if empty list, emits nothing, this is sort of like filter)
    sout = sout.concat()
    # just some checks to see if it's good data, else ignore
    return sin, sout, serr
Пример #2
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def clear_attributes(child):
    return streamz.map(child, StreamDoc_core.clear_attributes)
Пример #3
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def to_attributes(child):
    ''' send a function's args and kwargs to attributes, also clearing the args
    and kwargs'''
    return streamz.map(child, StreamDoc_core.to_attributes)
Пример #4
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def get_attributes(child):
    return streamz.map(child, StreamDoc_core.get_attributes)
Пример #5
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def add_attributes(child, **kwargs):
    return streamz.map(child, StreamDoc_core.add_attributes, attributes=kwargs)
Пример #6
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def merge(child):
    return streamz.map(child, StreamDoc_core.merge)
Пример #7
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def select(child, *mapping):
    return streamz.map(child, StreamDoc_core.select, *mapping)
Пример #8
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def squash(child):
    return streamz.map(child, StreamDoc_core.squash)