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Fix numpy 2 deprecated aliases #712

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Merged
merged 3 commits into from
Mar 17, 2025
Merged

Fix numpy 2 deprecated aliases #712

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df83483
fix numpy 2 errors with: ruff check py4DSTEM --select NPY201 --fix
sezelt Mar 14, 2025
bea0dab
remove numpy restriction in setup.py
sezelt Mar 14, 2025
2303563
unpin ncempy version
sezelt Mar 14, 2025
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34 changes: 17 additions & 17 deletions py4DSTEM/io/legacy/legacy13/v13_emd_classes/io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -127,61 +127,61 @@ def Metadata_to_h5(metadata, group):
# None
if v is None:
v = "_None"
v = np.string_(v) # convert to byte string
v = np.bytes_(v) # convert to byte string
dset = grp.create_dataset(k, data=v)
dset.attrs["type"] = np.string_("None")
dset.attrs["type"] = np.bytes_("None")

# strings
elif isinstance(v, str):
v = np.string_(v) # convert to byte string
v = np.bytes_(v) # convert to byte string
dset = grp.create_dataset(k, data=v)
dset.attrs["type"] = np.string_("string")
dset.attrs["type"] = np.bytes_("string")

# bools
elif isinstance(v, bool):
dset = grp.create_dataset(k, data=v, dtype=bool)
dset.attrs["type"] = np.string_("bool")
dset.attrs["type"] = np.bytes_("bool")

# numbers
elif isinstance(v, Number):
dset = grp.create_dataset(k, data=v, dtype=type(v))
dset.attrs["type"] = np.string_("number")
dset.attrs["type"] = np.bytes_("number")

# arrays
elif isinstance(v, np.ndarray):
dset = grp.create_dataset(k, data=v, dtype=v.dtype)
dset.attrs["type"] = np.string_("array")
dset.attrs["type"] = np.bytes_("array")

# tuples
elif isinstance(v, tuple):
# of numbers
if isinstance(v[0], Number):
dset = grp.create_dataset(k, data=v)
dset.attrs["type"] = np.string_("tuple")
dset.attrs["type"] = np.bytes_("tuple")

# of tuples
elif any([isinstance(v[i], tuple) for i in range(len(v))]):
dset_grp = grp.create_group(k)
dset_grp.attrs["type"] = np.string_("tuple_of_tuples")
dset_grp.attrs["type"] = np.bytes_("tuple_of_tuples")
dset_grp.attrs["length"] = len(v)
for i, x in enumerate(v):
dset_grp.create_dataset(str(i), data=x)

# of arrays
elif isinstance(v[0], np.ndarray):
dset_grp = grp.create_group(k)
dset_grp.attrs["type"] = np.string_("tuple_of_arrays")
dset_grp.attrs["type"] = np.bytes_("tuple_of_arrays")
dset_grp.attrs["length"] = len(v)
for i, ar in enumerate(v):
dset_grp.create_dataset(str(i), data=ar, dtype=ar.dtype)

# of strings
elif isinstance(v[0], str):
dset_grp = grp.create_group(k)
dset_grp.attrs["type"] = np.string_("tuple_of_strings")
dset_grp.attrs["type"] = np.bytes_("tuple_of_strings")
dset_grp.attrs["length"] = len(v)
for i, s in enumerate(v):
dset_grp.create_dataset(str(i), data=np.string_(s))
dset_grp.create_dataset(str(i), data=np.bytes_(s))

else:
er = f"Metadata only supports writing tuples with numeric and array-like arguments; found type {type(v[0])}"
Expand All @@ -192,23 +192,23 @@ def Metadata_to_h5(metadata, group):
# of numbers
if isinstance(v[0], Number):
dset = grp.create_dataset(k, data=v)
dset.attrs["type"] = np.string_("list")
dset.attrs["type"] = np.bytes_("list")

# of arrays
elif isinstance(v[0], np.ndarray):
dset_grp = grp.create_group(k)
dset_grp.attrs["type"] = np.string_("list_of_arrays")
dset_grp.attrs["type"] = np.bytes_("list_of_arrays")
dset_grp.attrs["length"] = len(v)
for i, ar in enumerate(v):
dset_grp.create_dataset(str(i), data=ar, dtype=ar.dtype)

# of strings
elif isinstance(v[0], str):
dset_grp = grp.create_group(k)
dset_grp.attrs["type"] = np.string_("list_of_strings")
dset_grp.attrs["type"] = np.bytes_("list_of_strings")
dset_grp.attrs["length"] = len(v)
for i, s in enumerate(v):
dset_grp.create_dataset(str(i), data=np.string_(s))
dset_grp.create_dataset(str(i), data=np.bytes_(s))

else:
er = f"Metadata only supports writing lists with numeric and array-like arguments; found type {type(v[0])}"
Expand Down Expand Up @@ -490,7 +490,7 @@ def PointList_to_h5(pointlist, group):
# Add data
for f, t in zip(pointlist.fields, pointlist.types):
group_current_field = grp.create_dataset(f, data=pointlist.data[f])
group_current_field.attrs.create("dtype", np.string_(t))
group_current_field.attrs.create("dtype", np.bytes_(t))
# group_current_field.create_dataset(
# "data",
# data = pointlist.data[f]
Expand Down
2 changes: 1 addition & 1 deletion py4DSTEM/process/classification/featurization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -967,7 +967,7 @@ def _gmm_single(x, cv, components, num_models, random_seed=None, return_all=True
gmm_list = []
gmm_labels = []
gmm_proba = []
lowest_bic = np.infty
lowest_bic = np.inf
bic_temp = 0
if random_seed is None:
rng = np.random.RandomState(seed=42)
Expand Down
4 changes: 2 additions & 2 deletions py4DSTEM/process/utils/elliptical_coords.py
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Expand Up @@ -320,8 +320,8 @@ def elliptical_resample(

# Get (qx,qy) corresponding to the coordinates distorted by the ellipse
xr, yr = np.mgrid[0:Nx, 0:Ny]
xr0 = xr.astype(np.float_) - qx0
yr0 = yr.astype(np.float_) - qy0
xr0 = xr.astype(np.float64) - qx0
yr0 = yr.astype(np.float64) - qy0
xr = xr0 * np.cos(-theta) - yr0 * np.sin(-theta)
yr = xr0 * np.sin(-theta) + yr0 * np.cos(-theta)
qx = qx0 + xr * np.cos(theta) - yr * (b / a) * np.sin(theta)
Expand Down
4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -23,11 +23,11 @@
keywords="STEM,4DSTEM",
python_requires=">=3.10",
install_requires=[
"numpy >= 1.19, < 2.0",
"numpy >= 1.19",
"scipy >= 1.5.2",
"h5py >= 3.2.0",
"hdf5plugin >= 4.1.3",
"ncempy >= 1.8.1, <= 1.11.2",
"ncempy >= 1.8.1",
"matplotlib >= 3.2.2",
"scikit-image >= 0.17.2",
"scikit-learn >= 0.23.2, < 1.5",
Expand Down