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Merge pull request #26 from wtclarke/python_3_11
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Python 3.11
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@wtclarke
wtclarke authored Jan 10, 2023
2 parents 81e2170 + 5890578 commit 7fa36d8
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17 changes: 17 additions & 0 deletions .github/workflows/publish.yml
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name: Publish to PyPI.org
on:
release:
types: [published]
jobs:
pypi:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v3
with:
fetch-depth: 0
- run: python3 -m pip install --upgrade build && python3 -m build
- name: Publish package
uses: pypa/gh-action-pypi-publish@release/v1
with:
password: ${{ secrets.PYPI_API_TOKEN }}
11 changes: 11 additions & 0 deletions CHANGELOG.md
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This document contains the pymapvbvd release history in reverse chronological order.

0.5.0 (Tuesday 10th January 2023)
---------------------------------
- Enable support for Python 3.11
- Remove support for Python 3.6
- AUtomatic Pypi upload on publication

0.4.8 (Thursday 27th January 2022)
----------------------------------
- Release to enable Zenodo automatic archiving
119 changes: 83 additions & 36 deletions mapvbvd/mapVBVD.py
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from dataclasses import dataclass
from sys import stdout
from sys import stdout, version_info

import numpy as np
from tqdm.auto import tqdm
Expand Down Expand Up @@ -198,49 +198,96 @@ class MDH: # byte pos
SlicePos: np.single
aushIceProgramPara: np.uint16
aushFreePara: np.uint16
lMeasUID: np.uint32 = data_uint32[:, 2 - 1] # 5 : 8
ulScanCounter: np.uint32 = data_uint32[:, 3 - 1] # 9 : 12
ulTimeStamp: np.uint32 = data_uint32[:, 4 - 1] # 13 : 16
ulPMUTimeStamp: np.uint32 = data_uint32[:, 5 - 1] # 17 : 20
aulEvalInfoMask: np.uint32 = data_uint32[:, 5:7] # 21 : 28
ushSamplesInScan: np.uint16 = data_uint16[:, 1 - 1] # 29 : 30
ushUsedChannels: np.uint16 = data_uint16[:, 2 - 1] # 31 : 32
sLC: np.uint16 = data_uint16[:, 2:16] # 33 : 60
sCutOff: np.uint16 = data_uint16[:, 16:18] # 61 : 64
ushKSpaceCentreColumn: np.uint16 = data_uint16[:, 19 - 1] # 66 : 66
ushCoilSelect: np.uint16 = data_uint16[:, 20 - 1] # 67 : 68
fReadOutOffcentre: np.single = data_single[:, 1 - 1] # 69 : 72
ulTimeSinceLastRF: np.uint32 = data_uint32[:, 19 - 1] # 73 : 76
ushKSpaceCentreLineNo: np.uint16 = data_uint16[:, 25 - 1] # 77 : 78
ushKSpaceCentrePartitionNo: np.uint16 = data_uint16[:, 26 - 1] # 79 : 80
lMeasUID: np.uint32
ulScanCounter: np.uint32
ulTimeStamp: np.uint32
ulPMUTimeStamp: np.uint32
aulEvalInfoMask: np.uint32
ushSamplesInScan: np.uint16
ushUsedChannels: np.uint16
sLC: np.uint16
sCutOff: np.uint16
ushKSpaceCentreColumn: np.uint16
ushCoilSelect: np.uint16
fReadOutOffcentre: np.single
ulTimeSinceLastRF: np.uint32
ushKSpaceCentreLineNo: np.uint16
ushKSpaceCentrePartitionNo: np.uint16

if isVD:
mdh = MDH(ulPackBit, ulPCI_rx, data_single[:, 3:10], data_uint16[:, 40:64], data_uint16[:, 64:68])
index_SlicePos = (slice(None), slice(3, 10))
index_aushIceProgramPara = (slice(None), slice(40, 64))
index_aushFreePara = (slice(None), slice(64, 68))
else:
mdh = MDH(ulPackBit, ulPCI_rx, data_single[:, 7:14], data_uint16[:, 26:30], data_uint16[:, 30:34])
index_SlicePos = (slice(None), slice(7, 14))
index_aushIceProgramPara = (slice(None), slice(26, 30))
index_aushFreePara = (slice(None), slice(30, 34))

mdh = MDH(
ulPackBit,
ulPCI_rx,
data_single[index_SlicePos], # SlicePos
data_uint16[index_aushIceProgramPara], # aushIceProgramPara
data_uint16[index_aushFreePara], # aushFreePara
data_uint32[:, 2 - 1], # lMeasUID 5 : 8
data_uint32[:, 3 - 1], # ulScanCounter 9 : 12
data_uint32[:, 4 - 1], # ulTimeStamp 13 : 16
data_uint32[:, 5 - 1], # ulPMUTimeStamp 17 : 20
data_uint32[:, 5:7], # aulEvalInfoMask 21 : 28
data_uint16[:, 1 - 1], # ushSamplesInScan 29 : 30
data_uint16[:, 2 - 1], # ushUsedChannels 31 : 32
data_uint16[:, 2:16], # sLC 33 : 60
data_uint16[:, 16:18], # sCutOff 61 : 64
data_uint16[:, 19 - 1], # ushKSpaceCentreColumn 66 : 66
data_uint16[:, 20 - 1], # ushCoilSelect 67 : 68
data_single[:, 1 - 1], # fReadOutOffcentre 69 : 72
data_uint32[:, 19 - 1], # ulTimeSinceLastRF 73 : 76
data_uint16[:, 25 - 1], # ushKSpaceCentreLineNo 77 : 78
data_uint16[:, 26 - 1]) # ushKSpaceCentrePartitionNo 79 : 80

evalInfoMask1 = mdh.aulEvalInfoMask[:, 0]

if version_info[1] > 8:
mdh_type = np.ndarray[int, np.uint32]
else:
mdh_type = np.ndarray

@dataclass
class MASK:
MDH_ACQEND = np.minimum(evalInfoMask1 & 2 ** 0, 1)
MDH_RTFEEDBACK = np.minimum(evalInfoMask1 & 2 ** 1, 1)
MDH_HPFEEDBACK = np.minimum(evalInfoMask1 & 2 ** 2, 1)
MDH_SYNCDATA = np.minimum(evalInfoMask1 & 2 ** 5, 1)
MDH_RAWDATACORRECTION = np.minimum(evalInfoMask1 & 2 ** 10, 1)
MDH_REFPHASESTABSCAN = np.minimum(evalInfoMask1 & 2 ** 14, 1)
MDH_PHASESTABSCAN = np.minimum(evalInfoMask1 & 2 ** 15, 1)
MDH_SIGNREV = np.minimum(evalInfoMask1 & 2 ** 17, 1)
MDH_PHASCOR = np.minimum(evalInfoMask1 & 2 ** 21, 1)
MDH_PATREFSCAN = np.minimum(evalInfoMask1 & 2 ** 22, 1)
MDH_PATREFANDIMASCAN = np.minimum(evalInfoMask1 & 2 ** 23, 1)
MDH_REFLECT = np.minimum(evalInfoMask1 & 2 ** 24, 1)
MDH_NOISEADJSCAN = np.minimum(evalInfoMask1 & 2 ** 25, 1)
MDH_VOP = np.minimum(mdh.aulEvalInfoMask[:, 1] & 2 ** (53 - 32),
1) # WTC modified this as the original matlab code didn't make sense
MDH_IMASCAN = np.ones(Nmeas, dtype=np.uint32)

mask = MASK()
MDH_ACQEND: mdh_type
MDH_RTFEEDBACK: mdh_type
MDH_HPFEEDBACK: mdh_type
MDH_SYNCDATA: mdh_type
MDH_RAWDATACORRECTION: mdh_type
MDH_REFPHASESTABSCAN: mdh_type
MDH_PHASESTABSCAN: mdh_type
MDH_SIGNREV: mdh_type
MDH_PHASCOR: mdh_type
MDH_PATREFSCAN: mdh_type
MDH_PATREFANDIMASCAN: mdh_type
MDH_REFLECT: mdh_type
MDH_NOISEADJSCAN: mdh_type
MDH_VOP: mdh_type
MDH_IMASCAN: mdh_type

mask = MASK(
np.minimum(evalInfoMask1 & 2 ** 0, 1),
np.minimum(evalInfoMask1 & 2 ** 1, 1),
np.minimum(evalInfoMask1 & 2 ** 2, 1),
np.minimum(evalInfoMask1 & 2 ** 5, 1),
np.minimum(evalInfoMask1 & 2 ** 10, 1),
np.minimum(evalInfoMask1 & 2 ** 14, 1),
np.minimum(evalInfoMask1 & 2 ** 15, 1),
np.minimum(evalInfoMask1 & 2 ** 17, 1),
np.minimum(evalInfoMask1 & 2 ** 21, 1),
np.minimum(evalInfoMask1 & 2 ** 22, 1),
np.minimum(evalInfoMask1 & 2 ** 23, 1),
np.minimum(evalInfoMask1 & 2 ** 24, 1),
np.minimum(evalInfoMask1 & 2 ** 25, 1),
np.minimum(
mdh.aulEvalInfoMask[:, 1] & 2 ** (53 - 32),
1), # WTC modified this as the original matlab code didn't make sense
np.ones(Nmeas, dtype=np.uint32))

noImaScan = (mask.MDH_ACQEND | mask.MDH_RTFEEDBACK | mask.MDH_HPFEEDBACK
| mask.MDH_PHASCOR | mask.MDH_NOISEADJSCAN | mask.MDH_PHASESTABSCAN
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5 changes: 5 additions & 0 deletions setup.py
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license_file='LICENSE',
classifiers=[
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent", ],
python_requires='>=3.7')

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