pept.scanners.adac_forte

pept.scanners.adac_forte(filepath, sample_size=None, overlap=None, verbose=True)

Initialise PEPT lines of response (LoRs) from a binary file outputted by the ADAC Forte parallel screen detector list mode (common file extension “.da01”).

Parameters

filepathstr

The path to a ADAC Forte-generated binary file from which the LoRs will be read into the LineData format. If you have multiple files, use a wildcard (*) after their common substring to concatenate them, e.g. “DS1.da*” will add [“DS1.da01”, “DS1.da02”, “DS1.da02_02”].

sample_sizeint, default 0

An int that defines the number of lines that should be returned when iterating over lines. A sample_size of 0 yields all the data as one single sample. A good starting value would be 200 times the maximum number of tracers that would be tracked.

overlapint, default 0

An int that defines the overlap between two consecutive samples that are returned when iterating over lines. An overlap of 0 implies consecutive samples, while an overlap of (sample_size - 1) means incrementing the samples by one. A negative overlap means skipping values between samples. An error is raised if overlap is larger than or equal to sample_size.

verbosebool, default True

An option that enables printing the time taken for the initialisation of an instance of the class. Useful when reading large files (10gb files for PEPT data is not unheard of).

Returns

LineData

The initialised LoRs.

Raises

FileNotFoundError

If the input filepath does not exist.

ValueError

If overlap >= sample_size. Overlap has to be smaller than sample_size. Note that it can also be negative.

See also

pept.LineData

Encapsulate LoRs for ease of iteration and plotting.

pept.PointData

Encapsulate points for ease of iteration and plotting.

pept.read_csv

Fast CSV file reading into numpy arrays.

PlotlyGrapher

Easy, publication-ready plotting of PEPT-oriented data.

Examples

Initialise a ParallelScreens array for three LoRs on a parallel screens PEPT scanner (i.e. each line is defined by two points each) with a head separation of 500 mm:

>>> lors = pept.scanners.adac_forte("binary_data_adac.da01")
Initialised the PEPT data in 0.011 s.

>>> lors
LineData
--------
sample_size = 0
overlap =     0
samples =     1
lines =
  [[0.00000000e+00 1.62250000e+02 3.60490000e+02 ... 4.14770000e+02
    3.77010000e+02 3.10000000e+02]
   [4.19512195e-01 2.05910000e+02 2.68450000e+02 ... 3.51640000e+02
    2.95000000e+02 3.10000000e+02]
   [8.39024390e-01 3.16830000e+02 1.26260000e+02 ... 2.74350000e+02
    3.95300000e+02 3.10000000e+02]
   ...
   [1.98255892e+04 2.64320000e+02 2.43080000e+02 ... 2.25970000e+02
    4.01200000e+02 3.10000000e+02]
   [1.98263928e+04 3.19780000e+02 3.38660000e+02 ... 2.75530000e+02
    5.19200000e+02 3.10000000e+02]
   [1.98271964e+04 2.41310000e+02 4.15360000e+02 ... 2.91460000e+02
    4.63150000e+02 3.10000000e+02]]
lines.shape = (32526, 7)
columns = ['t', 'x1', 'y1', 'z1', 'x2', 'y2', 'z2']

Initialising Scanner Data (pept.scanners) pept.scanners.parallel_screens