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fixed index_set helper function #7

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Merged
passscoed merged 4 commits into from
Feb 24, 2026
Merged

fixed index_set helper function #7

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885f12f
fixed index_set helper function
passscoed Feb 24, 2026
8f1b01d
version 1.1.0
passscoed Feb 24, 2026
d190183
Auto code format
passscoed Feb 24, 2026
0dc4918
Merge pull request #6 from NFFT/python-code-format-patches
passscoed Feb 24, 2026
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ build-backend = "hatchling.build"

[project]
name = "pyGroupedTransforms"
version = "1.0.0"
version = "1.1.0"
authors = [
{ name="Felix Wirth", email="fwi012001@gmail.com" },
]
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5 changes: 2 additions & 3 deletions src/pyGroupedTransforms/NFCTtools.py
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Expand Up @@ -77,8 +77,7 @@ def nfct_index_set(
if d == 1:
return np.array([i for i in range(0, bandwidths[0])], "int")

bandwidths = bandwidths[::-1]
tmp = tuple([list(range(0, bw)) for bw in bandwidths])
tmp = tuple([list(range(0, bw)) for bw in bandwidths[::-1]])
tmp = itertools.product(*(tmp[::-1]))

freq = np.empty((d, np.prod(bandwidths)), dtype=int)
Expand Down Expand Up @@ -127,7 +126,7 @@ def get_transform(
if bandwidths.ndim > 1 or bandwidths.dtype != "int32":
return "Please use an zero or one-dimensional numpy.array with dtype 'int32' as input"

(M, d) = X.shape
M, d = X.shape

if len(bandwidths) == 0:
return DeferredLinearOperator(
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5 changes: 2 additions & 3 deletions src/pyGroupedTransforms/NFFTtools.py
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Expand Up @@ -88,7 +88,7 @@ def nfft_index_set(
list(range(int(-bandwidths[0] / 2), int(bandwidths[0] / 2))), dtype="int"
)

tmp = [list(range(int(-bw / 2), int(bw / 2))) for bw in bandwidths]
tmp = [list(range(int(-bw / 2), int(bw / 2))) for bw in bandwidths[::-1]]
tmp = itertools.product(*(tmp[::-1]))

freq = np.empty((d, np.prod(bandwidths)), dtype=int)
Expand Down Expand Up @@ -134,11 +134,10 @@ def get_transform(
# Output:
* `F::LinearMap{ComplexF64}` ... Linear map of the Fourier-transform implemented by the NFFT
"""

if bandwidths.ndim > 1 or bandwidths.dtype != "int32":
return "Please use an zero or one-dimensional numpy.array with dtype 'int32' as input"

(M, d) = np.shape(X)
M, d = np.shape(X)

if len(bandwidths) == 0:
return DeferredLinearOperator(
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