Module pept.scanners.parallel_screens
Source code
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# File : __init__.py
# License: License: GNU v3.0
# Author : Andrei Leonard Nicusan <a.l.nicusan@bham.ac.uk>
# Date : 20.08.2019
from .parallel_screens import ParallelScreens
__all__ = [
'ParallelScreens'
]
__author__ = "Andrei Leonard Nicusan"
__credits__ = ["Andrei Leonard Nicusan", "Kit Windows-Yule", "Sam Manger"]
__license__ = "GNU v3.0"
__version__ = "0.1.0"
__maintainer__ = "Andrei Leonard Nicusan"
__email__ = "a.l.nicusan@bham.ac.uk"
__status__ = "Development"
Sub-modules
pept.scanners.parallel_screens.parallel_screens
Classes
class ParallelScreens (data_file, separation, sample_size=200, overlap=0, skiprows=0, max_rows=None, verbose=True)
-
A subclass of
LineData
that reads PEPT data for parallel screens detectors.Provides the same functionality as the
LineData
class while initialisingline_data
from a given file. This is a helper class for PEPT scanners with two parallel screens.ParallelScreens
can read data from a.csv
or.a0n
file or equivalent. The expected data row in the file is[time, x1, y1, x2, y2]
. This will then be automatically transformed into the standardline_data
format with every row being[time, x1, y1, z1, x2, y2, z2]
, wherez1 = 0
andz2 = separation
.Parameters
data_file
:str
- A string with the (absolute or relative) path to the data file from which the PEPT data will be read. It should include the full file name, along with the extension (.csv, .a01, etc.)
sample_size
:int
, optional- An
int`` that defines the number of lines that should be returned when iterating over
line_data. A
sample_size` of 0 yields all the data as one single sample. (Default is 200) overlap
:int
, optional- An
int
that defines the overlap between two consecutive samples that are returned when iterating overline_data
. An overlap of 0 means 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 ifoverlap
is larger than or equal tosample_size
. (Default is 0) separation
:float
, optional- The separation (in mm) between the two PEPT screens corresponding
to the
z
coordinate of the second point defining each line. The attributeline_data
, with each row being[time, x1, y1, z1, x2, y2, z2]
, will havez1 = 0
andz2 = separation
. (Default is 712) skiprows
:int
, optional- The number of rows to skip from the beginning of the data file. Useful when the data file includes a header of text that should be skipped. (Default is 0)
max_rows
:int
, optional- The maximum number of rows that will be read from the data file.
(Default is
None
) verbose
:bool
, optional- 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). (Default is True)
Attributes
line_data
: (N
,7
)numpy.ndarray
- An (N, 7) numpy array that stores the PEPT LoRs as time and
cartesian (3D) coordinates of two points defining a line, in mm.
Each row is then
[time, x1, y1, z1, x2, y2, z2]
. sample_size
:int
- An
int
that defines the number of lines that should be returned when iterating overline_data
. (Default is 200) overlap
:int
- An
int
that defines the overlap between two consecutive samples that are returned when iterating overline_data
. An overlap of 0 means consecutive samples, while an overlap of (sample_size
- 1) means incrementing the samples by one. A negative overlap means skipping values between samples. It has to be smaller thansample_size
. (Default is 0) number_of_lines
:int
- An
int
that corresponds to len(line_data
), or the number of LoRs stored byline_data
.
Raises
ValueError
- If
overlap
>=sample_size
. Overlap has to be smaller thansample_size
. Note that it can also be negative. ValueError
- If the data file does not have (N, 5) shape.
Notes
The class saves
line_data
as a contiguous numpy array for efficient access in C functions. It should not be changed after instantiating the class.Source code
class ParallelScreens(LineData): '''A subclass of `LineData` that reads PEPT data for parallel screens detectors. Provides the same functionality as the `LineData` class while initialising `line_data` from a given file. This is a helper class for **PEPT scanners with two parallel screens**. `ParallelScreens` can read data from a `.csv` or `.a0n` file or equivalent. **The expected data row in the file is `[time, x1, y1, x2, y2]`**. This will then be automatically transformed into the standard `line_data` format with every row being `[time, x1, y1, z1, x2, y2, z2]`, where `z1 = 0` and `z2 = separation`. Parameters ---------- data_file : str A string with the (absolute or relative) path to the data file from which the PEPT data will be read. It should include the full file name, along with the extension (.csv, .a01, etc.) sample_size : int, optional An `int`` that defines the number of lines that should be returned when iterating over `line_data`. A `sample_size` of 0 yields all the data as one single sample. (Default is 200) overlap : int, optional An `int` that defines the overlap between two consecutive samples that are returned when iterating over `line_data`. An overlap of 0 means 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`. (Default is 0) separation : float, optional The separation (in *mm*) between the two PEPT screens corresponding to the `z` coordinate of the second point defining each line. The attribute `line_data`, with each row being `[time, x1, y1, z1, x2, y2, z2]`, will have `z1 = 0` and `z2 = separation`. (Default is 712) skiprows : int, optional The number of rows to skip from the beginning of the data file. Useful when the data file includes a header of text that should be skipped. (Default is 0) max_rows : int, optional The maximum number of rows that will be read from the data file. (Default is `None`) verbose : bool, optional 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). (Default is True) Attributes ---------- line_data : (N, 7) numpy.ndarray An (N, 7) numpy array that stores the PEPT LoRs as time and cartesian (3D) coordinates of two points defining a line, **in mm**. Each row is then `[time, x1, y1, z1, x2, y2, z2]`. sample_size : int An `int` that defines the number of lines that should be returned when iterating over `line_data`. (Default is 200) overlap : int An `int` that defines the overlap between two consecutive samples that are returned when iterating over `line_data`. An overlap of 0 means consecutive samples, while an overlap of (`sample_size` - 1) means incrementing the samples by one. A negative overlap means skipping values between samples. It has to be smaller than `sample_size`. (Default is 0) number_of_lines : int An `int` that corresponds to len(`line_data`), or the number of LoRs stored by `line_data`. Raises ------ ValueError If `overlap` >= `sample_size`. Overlap has to be smaller than `sample_size`. Note that it can also be negative. ValueError If the data file does not have (N, 5) shape. Notes ----- The class saves `line_data` as a **contiguous** numpy array for efficient access in C functions. It should not be changed after instantiating the class. ''' def __init__(self, data_file, separation, sample_size = 200, overlap = 0, skiprows = 0, max_rows = None, verbose = True): if verbose: start = time.time() # Read the LoR data from `data_file` # Row: [time, X1, Y1, X2, Y2] line_data = np.loadtxt(data_file, skiprows = skiprows, max_rows = max_rows) # Verify that line_data has shape (N, 5) if line_data.ndim != 2 or line_data.shape[1] != 5: raise ValueError('\n[ERROR]: line_data (that was read from data_file) should have dimensions (N, 5). Received {}\n'.format(line_data.shape)) number_of_lines = len(line_data) # Add Z1 and Z2 columns => [time, X1, Y1, Z1, X2, Y2, Z2] # Z1 = 0 line_data = np.insert(line_data, 3, np.zeros(number_of_lines), axis = 1) # Z2 = `separation` line_data = np.append(line_data, separation * np.ones((number_of_lines, 1)), axis = 1) # Call the constructor of the superclass `LineData` to initialise all # the inner parameters of the class (_index, etc.) super().__init__(line_data, sample_size = sample_size, overlap = overlap, verbose = False) if verbose: end = time.time() print("Initialising the PEPT data took {} seconds\n".format(end - start))
Ancestors
Inherited members