374 standardise task input and output

[sophie22]

HazenTask class objects to be initialised with a list of file paths to DICOM images (input_data: list), which are then used directly in tasks that process multiple images at once, or a single_dcm attribute is being created for tasks that process a single image at a time.

The result dictionary now has a standardised structure, consisting of the following elements:

results_dict = {
    "task": "task_name",
    "file": "DCM description or list of descriptions",
    "measurement": {dict of key value pairs},
    "report_image": [OPTIONAL list of paths to report images]
}

Furthermore, the values displayed in the result dictionary are being rounded to the appropriate precision and units are displayed in the key.

!!!CHANGE to OUTPUT!!! The Slice position task now returns only the maximum and average of slice positions, rather than a list of 40 values as previously.

Behind the scene changes for processing the ACR images and slight improvements to the slice_width and snr_map task scripts.

resolves #374

[github-actions[bot]]

Coverage Report

File	Stmts	Miss	Cover	Missing
hazenlib
ACRObject.py	106	11	90%	72, 75–77, 82–85, 123, 166–167
HazenTask.py	29	3	90%	41–43
__init__.py	57	15	74%	153, 183–185, 188–190, 202–204, 218–222, 226
exceptions.py	21	5	76%	17–21, 38
utils.py	189	43	77%	61, 65, 75, 80, 117, 124–129, 140, 143–150, 170–172, 190–192, 211–213, 222, 227, 233, 284, 287, 295–300, 303, 346, 355, 371
hazenlib/tasks
acr_geometric_accuracy.py	119	63	47%	41–86, 96–121, 134–168
acr_ghosting.py	108	44	59%	34–54, 80–82, 112–114, 148–190
acr_slice_position.py	136	49	64%	46–68, 194–241
acr_slice_thickness.py	136	61	55%	34–54, 163–225
acr_snr.py	132	61	54%	41–84, 94, 164–174, 208–223, 256–273
acr_spatial_resolution.py	206	69	67%	58–86, 131, 174, 187–196, 278–330
acr_uniformity.py	82	34	59%	35–57, 113–139
ghosting.py	151	51	66%	19–36, 51, 113–114, 118, 128–129, 155–157, 174–176, 222–259
relaxometry.py	291	89	69%	207–208, 210, 221–224, 230–236, 268–312, 353, 387–405, 580, 626–628, 695, 769–791, 809–824
slice_position.py	118	36	69%	27–53, 105–106, 132, 212, 220–238
slice_width.py	352	52	85%	36–38, 42, 107, 166–187, 441, 446–447, 453, 458, 516–517, 767–809
snr.py	166	67	60%	58, 75–80, 176–194, 209–218, 236–246, 273–283, 288–298, 329–343, 348–356, 385–399
snr_map.py	108	1	99%	152
spatial_resolution.py	249	44	82%	41–43, 47, 68, 153, 212, 338–375
uniformity.py	79	19	76%	47–49, 53, 95–96, 103, 137–152
TOTAL	2860	817	71%

Tests	Skipped	Failures	Errors	Time
201	0 :zzz:	0 :x:	0 :fire:	3m 51s :stopwatch:

[sophie22]

Stage 1: standardise input for task.run() function - complete and tests have been adapted

[sophie22]

Stage 2: round measurement results to decimal points agreed with the physicists - complete, tests have been adapted

[sophie22]

Stage 3: standardise structure of output dictionary to be like:

results = {
    "task": "task_name",
    "file": "DCM description or list of descriptions",
    "measurement": {dict of key value pairs},
    "report_image": [list of paths to report images]
}

[sophie22]

task_results.txt ^updated output results, including changes to SNR task results

@YassineAzma @elizaGSTT if you have time and capacity, please check that the wording, units and precision is sensible in all task outputs.

[sophie22]

HazenTask objects expect a dcm_list input, single_dcm attribute is created in relevant task classes