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  • paulmc/fslpy
  • ndcn0236/fslpy
  • seanf/fslpy
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with 684 additions and 123 deletions
......@@ -74,9 +74,7 @@ class MelodicImage(fslimage.Image):
dataFile = self.getDataFile()
if dataFile is not None:
dataImage = fslimage.Image(dataFile,
loadData=False,
calcRange=False)
dataImage = fslimage.Image(dataFile)
if dataImage.ndim >= 4:
self.__tr = dataImage.pixdim[3]
......
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......@@ -11,9 +11,14 @@
looksLikeVestLutFile
loadVestLutFile
loadVestFile
generateVest
"""
import textwrap as tw
import io
import numpy as np
......@@ -76,3 +81,70 @@ def loadVestLutFile(path, normalise=True):
else:
return colours
def loadVestFile(path, ignoreHeader=True):
"""Loads numeric data from a VEST file, returning it as a ``numpy`` array.
:arg ignoreHeader: if ``True`` (the default), the matrix shape specified
in the VEST header information is ignored, and the shape
inferred from the data. Otherwise, if the number of
rows/columns specified in the VEST header information
does not match the matrix shape, a ``ValueError`` is
raised.
:returns: a ``numpy`` array containing the matrix data in the
VEST file.
"""
data = np.loadtxt(path, comments=['#', '/'])
if not ignoreHeader:
nrows, ncols = None, None
with open(path, 'rt') as f:
for line in f:
if 'NumWaves' in line: ncols = int(line.split()[1])
elif 'NumPoints' in line: nrows = int(line.split()[1])
else: continue
if (ncols is not None) and (nrows is not None):
break
if tuple(data.shape) != (nrows, ncols):
raise ValueError(f'Invalid VEST file ({path}) - data shape '
f'({data.shape}) does not match header '
f'({nrows}, {ncols})')
return data
def generateVest(data):
"""Generates VEST-formatted text for the given ``numpy`` array.
:arg data: A 1D or 2D numpy array.
:returns: A string containing a VEST header, and the ``data``.
"""
data = np.asanyarray(data)
if len(data.shape) not in (1, 2):
raise ValueError(f'unsupported number of dimensions: {data.shape}')
data = np.atleast_2d(data)
if np.issubdtype(data.dtype, np.integer): fmt = '%d'
else: fmt = '%0.12f'
sdata = io.StringIO()
np.savetxt(sdata, data, fmt=fmt)
sdata = sdata.getvalue()
nrows, ncols = data.shape
vest = tw.dedent(f"""
/NumWaves {ncols}
/NumPoints {nrows}
/Matrix
""").strip() + '\n' + sdata
return vest.strip()
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