PySight Output Object

If the In Memory option was checked in the GUI or enabled in the configuration file, PySight will return a PySightOuput instance containing the processed data and useful methods to work with it.

class pysight.nd_hist_generator.outputs.DataShape(t, x, y, z)

Bases: tuple

t

Alias for field number 0

x

Alias for field number 1

y

Alias for field number 2

z

Alias for field number 3

class pysight.nd_hist_generator.outputs.MultiDimensionalData(full, time_summed, data_shape)

Bases: object

Internal representation of a stack of data.

Parameters:

• full (np.ndarray) – The entirety of the data.
• time_summed (np.ndarray) – All data summed across the time dimension.
• _data_shape (DataShape) – List of valid dimensions.
• z_summed (np.ndarray) – All data summed across the z dimension.

class pysight.nd_hist_generator.outputs.OutputParser(output_dict, filename, num_of_frames=1, flim_downsampling_time=1, x_pixels=512, y_pixels=512, z_pixels=1, channels=CategoricalIndex([1], categories=[1], ordered=False, dtype='category'), binwidth=1e-10, reprate=80000000.0, lst_metadata=NOTHING, file_pointer_created=True, cache_size=10737418240, debug=False)

Bases: object

Parse the wanted outputs and produce a dictionary with file pointers to the needed outputs # TODO: Handle the interleaved case

binwidth

cache_size

channels

data_shape

Tuple of (num_of_frames, x, y, z, tau)

debug

determine_data_shape_full()

Return the tuple that describes the shape of the final dataset. Dimension order: [FRAME, X, Y, Z]

file_pointer_created

filename

flim_downsampling_time

lst_metadata

num_of_channels

num_of_frames

output_dict

outputs

Dictionary with data - either the full or summed stack, with a list of zarr objects as channels

reprate

run()

Parse what the user required, creating a list of zarr dataset pointers for each channel

x_pixels

y_pixels

z_pixels

class pysight.nd_hist_generator.outputs.PySightOutput(photons, summed_mem, stack, channels, data_shape, config, flim=None)

Bases: object

Keeps the relevant data from the run of the algorithm for later in-memory processing.

Parameters:

• photons (pd.DataFrame) – The ‘raw’ photon DataFrame.
• _summed_mem (dict) – Summed-over-time arrays of the data - one per channel.
• _stack (dict) – Full data arrays, one per channel.
• _channels (pd.CategoricalIndex) – Actual data channels analyzed.
• _data_shape (tuple) – Data dimensions
• optional flim (Dict[np.ndarray],) – FLIM data or None
• config (Dict[str,Any]) – Configuration file used in this run.

pysight.nd_hist_generator.outputs.trunc_end_of_file(name) → str

Take only the start of the filename to avoid error with Python and Windows

Parameters:name (str) – Filename to truncate Return str: