pysight.nd_hist_generator package¶
Submodules¶
pysight.nd_hist_generator.allocation_tools module¶
pysight.nd_hist_generator.censor_tools module¶
pysight.nd_hist_generator.gating_tools module¶
__author__ = Hagai Hargil
pysight.nd_hist_generator.movie_tools module¶
pysight.nd_hist_generator.output_tools module¶
pysight.nd_hist_generator.photon_df_tools module¶
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class
pysight.nd_hist_generator.photon_df_tools.
PhotonDF
(dict_of_data, num_of_channels=1) → None[source]¶ Bases:
object
Create initial photon dataframe and set the channel as its index
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dict_of_data
¶
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gen_df
()[source]¶ If a single PMT channel exists, create a df_photons object. Else, concatenate the two data channels into a single dataframe.
Return pd.DataFrame: Photon data
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num_of_channels
¶
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pysight.nd_hist_generator.tag_bits_tools module¶
pysight.nd_hist_generator.tag_tools_v2 module¶
pysight.nd_hist_generator.volume_gen module¶
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class
pysight.nd_hist_generator.volume_gen.
VolumeGenerator
(frames, data_shape, MAX_BYTES_ALLOWED=300000000) → None[source]¶ Bases:
object
Generate the list of volume chunks to be processed. Main method is “create_frame_slices”, which returns a generator containing slice objects that signify the chunks of volumes to be processed simultaneously. Inputs: :param frames pd.DataFrame: Frames for the entire dataset. Should not contain a closing, right-edge, frame. :param data_shape tuple: Shape of the final n-dimensional array (from the Output object) :param MAX_BYTES_ALLOWED int: Number of bytes that can be held in RAM (“magic number”)
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MAX_BYTES_ALLOWED
¶
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bytes_per_frames
¶
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create_frame_slices
(create_slices=True) → Generator[source]¶ Main method for the pipeline. Returns a generator with slices that signify the start time and end time of all frames.
Parameters: bool (create_slices) – Used for testing, always keep true.
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data_shape
¶
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frame_per_chunk
¶
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frame_slices
¶
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frames
¶
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full_frame_chunks
¶
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num_of_chunks
¶
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num_of_frames
¶
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Module contents¶
__author__ = Hagai Hargil