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Merge pull request #5 from cdtools-developers/numpy2

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Add support for numpy 2.0
This commit is contained in:
clemisch
2024-11-08 15:17:39 +01:00
committed by GitHub
parent 26f4eb4cd1 40651eaf54
commit ce16fbcedc
6 changed files with 49 additions and 47 deletions
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src/cdtools/tools/analysis/analysis.py
+1 -2
View File
@@ -352,8 +352,7 @@ def synthesize_reconstructions(probes, objects, use_probe=False, obj_slice=None,
else:
shift = ip.find_shift(synth_obj[obj_slice],obj[obj_slice], resolution=50)
obj = ip.sinc_subpixel_shift(obj,np.array(shift))
obj = ip.sinc_subpixel_shift(obj, shift)
if len(probe.shape) == 3:
probe = t.stack([ip.sinc_subpixel_shift(p,tuple(shift))
src/cdtools/tools/data/data.py
+17 -16
View File
@@ -134,18 +134,18 @@ def get_sample_info(cxi_file):
metadata[attr] = np.float32(s1[attr][()])
if 'unit_cell' in s1:
metadata['unit_cell'] = np.array(s1['unit_cell']).astype(np.float32)
metadata['unit_cell'] = s1['unit_cell'][()].astype(np.float32)
if 'geometry_1/orientation' in s1:
orient = np.array(s1['geometry_1/orientation']).astype(np.float32)
orient = s1['geometry_1/orientation'][()].astype(np.float32)
xvec = orient[:3] / np.linalg.norm(orient[:3])
yvec = orient[3:] / np.linalg.norm(orient[3:])
metadata['orientation'] = np.array([xvec,yvec,
np.cross(xvec,yvec)])
if 'geometry_1/surface_normal' in s1:
snorm = np.array(s1['geometry_1/surface_normal']).astype(np.float32)
snorm = s1['geometry_1/surface_normal'][()].astype(np.float32)
xvec = np.cross(np.array([0.,1.,0.]), snorm)
xvec /= np.linalg.norm(xvec)
yvec = np.cross(snorm, xvec)
@@ -218,7 +218,7 @@ def get_detector_geometry(cxi_file):
d1 = i1['detector_1']
if 'detector_1/basis_vectors' in i1:
basis_vectors = np.array(d1['basis_vectors'])
basis_vectors = d1['basis_vectors'][()]
if basis_vectors.shape == (2,3):
basis_vectors = basis_vectors.T
else:
@@ -244,11 +244,11 @@ def get_detector_geometry(cxi_file):
[-x_pixel_size,0,0]]).transpose()
try:
distance = np.float32(d1['distance'])
distance = np.float32(d1['distance'][()])
except:
distance = None
try:
corner_position = np.array(d1['corner_position'])
corner_position = d1['corner_position'][()]
except:
corner_position = None
@@ -292,7 +292,7 @@ def get_mask(cxi_file):
i1 = cxi_file['entry_1/instrument_1']
if 'detector_1/mask' in i1:
mask = np.array(i1['detector_1/mask']).astype(np.uint32)
mask = i1['detector_1/mask'][()].astype(np.uint32)
mask_on = np.equal(mask,np.uint32(0))
mask_has_signal = np.equal(mask,np.uint32(0x00001000))
return np.logical_or(mask_on,mask_has_signal).astype(bool)
@@ -324,7 +324,7 @@ def get_dark(cxi_file):
i1 = cxi_file['entry_1/instrument_1']
if 'detector_1/data_dark' in i1:
darks = np.array(i1['detector_1/data_dark'])
darks = i1['detector_1/data_dark'][()]
dims = tuple(range(len(darks.shape) - 2))
darks = np.nanmean(darks,axis=dims)
else:
@@ -426,7 +426,7 @@ def get_shot_to_shot_info(cxi_file, field_name):
else:
raise KeyError('Data is not defined within cxi file')
return np.array(cxi_file[pull_from]).astype(np.float32)
return cxi_file[pull_from][()].astype(np.float32)
def get_ptycho_translations(cxi_file):
@@ -485,9 +485,9 @@ def add_entry_info(cxi_file, metadata):
# included in case the cxi spec becomes more permissive
for key, value in metadata.items():
if isinstance(value,(str,bytes)):
cxi_file['entry_1'][key] = np.string_(value)
cxi_file['entry_1'][key] = np.bytes_(value)
elif isinstance(value, datetime.datetime):
cxi_file['entry_1'][key] = np.string_(value.isoformat())
cxi_file['entry_1'][key] = np.bytes_(value.isoformat())
elif isinstance(value, numbers.Number):
cxi_file['entry_1'][key] = value
elif isinstance(value, (np.ndarray,list,tuple)):
@@ -525,9 +525,9 @@ def add_sample_info(cxi_file, metadata):
if key == 'orientation':
continue # this is a special case
if isinstance(value,(str,bytes)):
s1[key] = np.string_(value)
s1[key] = np.bytes_(value)
elif isinstance(value, datetime.datetime):
s1[key] = np.string_(value.isoformat())
s1[key] = np.bytes_(value.isoformat())
elif isinstance(value, numbers.Number):
s1[key] = value
elif isinstance(value, (np.ndarray,list,tuple)):
@@ -701,7 +701,7 @@ def add_data(cxi_file, data, axes=None, compression='gzip',
axes_str = ':'.join(axes)
else:
axes_str = str(axes)
det1['data'].attrs['axes'] = np.string_(axes_str)
det1['data'].attrs['axes'] = np.bytes_(axes_str)
def add_shot_to_shot_info(cxi_file, data, field_name):
@@ -851,11 +851,12 @@ def h5_to_nested_dict(h5_file):
for key in h5_file.keys():
value = h5_file[key]
if isinstance(value, h5py.Dataset):
arr = np.array(value)
arr = value[()]
if arr.dtype == object:
d[key] = arr.ravel()[0].decode('utf-8')
elif arr.ndim == 0:
d[key] = arr.ravel()[0]
# TODO is this needed with arr = value[()]?
d[key] = arr.ravel()[0]
else:
d[key] = arr
src/cdtools/tools/initializers/initializers.py
+1 -1
View File
@@ -57,7 +57,7 @@ def exit_wave_geometry(det_basis, det_shape, wavelength, distance, oversampling=
# This method should work for a general parallelogram-shaped detector
det_shape = det_basis * det_shape.to(t.float32)
pinv_basis = t.tensor(np.linalg.pinv(det_shape).transpose()).to(t.float32)
pinv_basis = t.linalg.pinv(det_shape).transpose(0,1)
real_space_basis = pinv_basis * wavelength * distance
return real_space_basis
tests/conftest.py
+14 -14
View File
@@ -77,28 +77,28 @@ def ptycho_cxi_1():
expected['entry metadata'] = {}
e1e = expected['entry metadata']
e1e['start_time'] = datetime.datetime.now()
e1f['start_time'] = np.string_(e1e['start_time'].isoformat())
e1f['start_time'] = np.bytes_(e1e['start_time'].isoformat())
e1e['end_time'] = datetime.datetime.now()
e1f['end_time'] = np.string_(e1e['end_time'].isoformat())
e1f['end_time'] = np.bytes_(e1e['end_time'].isoformat())
e1e['experiment_identifier'] = 'Fake Experiment 1'
e1f['experiment_identifier'] = np.string_(e1e['experiment_identifier'])
e1f['experiment_identifier'] = np.bytes_(e1e['experiment_identifier'])
e1e['experiment_description'] = 'A fully defined ptychography experiment to test the data loading'
e1f['experiment_description'] = np.string_(e1e['experiment_description'])
e1f['experiment_description'] = np.bytes_(e1e['experiment_description'])
e1e['program_name'] = 'cdtools'
e1f['program_name'] = np.string_(e1e['program_name'])
e1f['program_name'] = np.bytes_(e1e['program_name'])
e1e['title'] = 'The one experiment we did'
e1f['title'] = np.string_(e1e['title'])
e1f['title'] = np.bytes_(e1e['title'])
# Set up the sample info
s1f = e1f.create_group('sample_1')
expected['sample info'] = {}
s1e = expected['sample info']
s1e['name'] = 'Fake Sample'
s1f['name'] = np.string_(s1e['name'])
s1f['name'] = np.bytes_(s1e['name'])
s1e['description'] = 'A sample that isn\'t real'
s1f['description'] = np.string_(s1e['description'])
s1f['description'] = np.bytes_(s1e['description'])
s1e['unit_cell_group'] = 'P1'
s1f['unit_cell_group'] = np.string_(s1e['unit_cell_group'])
s1f['unit_cell_group'] = np.bytes_(s1e['unit_cell_group'])
s1e['concentration'] = np.float32(np.random.rand())
s1f['concentration'] = s1e['concentration']
s1e['mass'] = np.float32(np.random.rand())
@@ -151,7 +151,7 @@ def ptycho_cxi_1():
d1f.create_dataset('data',data=data)
data1f['data'] = h5py.SoftLink('/entry_1/instrument_1/detector_1/data')
d1f['data'].attrs['axes'] = np.string_('translation:y:x')
d1f['data'].attrs['axes'] = np.bytes_('translation:y:x')
expected['axes'] = ['translation','y','x']
g1f = s1f.create_group('geometry_1')
@@ -196,7 +196,7 @@ def ptycho_cxi_2():
expected['entry metadata'] = {}
e1e = expected['entry metadata']
e1e['title'] = 'The one experiment we did'
e1f['title'] = np.string_(e1e['title'])
e1f['title'] = np.bytes_(e1e['title'])
# Set up the sample info
s1f = e1f.create_group('sample_1')
@@ -277,9 +277,9 @@ def ptycho_cxi_3():
expected['entry metadata'] = {}
e1e = expected['entry metadata']
e1e['start_time'] = datetime.datetime.now()
e1f['start_time'] = np.string_(e1e['start_time'].isoformat())
e1f['start_time'] = np.bytes_(e1e['start_time'].isoformat())
e1e['end_time'] = datetime.datetime.now()
e1f['end_time'] = np.string_(e1e['end_time'].isoformat())
e1f['end_time'] = np.bytes_(e1e['end_time'].isoformat())
# Set up the sample info
expected['sample info'] = None
@@ -314,7 +314,7 @@ def ptycho_cxi_3():
expected['data'] = data
data1f.create_dataset('data',data=data)
data1f['data'].attrs['axes'] = np.string_('translation:y:x')
data1f['data'].attrs['axes'] = np.bytes_('translation:y:x')
expected['axes'] = ['translation','y','x']
translations = np.arange(300).reshape((100,3)).astype(np.float32)
tests/tools/test_data.py
+15 -13
View File
@@ -182,11 +182,11 @@ def test_add_detector(tmp_path):
# Check this directly since we want to make sure it saved
# the pixel sizes
d1 = f['entry_1/instrument_1/detector_1']
read_basis = np.array(d1['basis_vectors'])
read_x_pix = np.float32(d1['x_pixel_size'])
read_y_pix = np.float32(d1['y_pixel_size'])
read_distance = np.float32(d1['distance'])
read_corner = np.array(d1['corner_position'])
read_basis = d1['basis_vectors'][()]
read_x_pix = d1['x_pixel_size'][()]
read_y_pix = d1['y_pixel_size'][()]
read_distance = d1['distance'][()]
read_corner = d1['corner_position'][()]
assert np.isclose(distance, read_distance)
assert np.allclose(basis, read_basis)
@@ -232,8 +232,8 @@ def test_add_data(tmp_path):
with h5py.File(tmp_path / 'test_add_data.cxi','r') as f:
# Check this directly since we want to make sure it saved
# it in all the places it should have
read_data_1 = np.array(f['entry_1/data_1/data'])
read_data_2 = np.array(f['entry_1/instrument_1/detector_1/data'])
read_data_1 = f['entry_1/data_1/data'][()]
read_data_2 = f['entry_1/instrument_1/detector_1/data'][()]
read_axes = str(f['entry_1/instrument_1/detector_1/data'].attrs['axes'].decode())
assert np.allclose(fake_data, read_data_1)
@@ -261,9 +261,10 @@ def test_add_shot_to_shot_info(tmp_path):
with h5py.File(tmp_path / 'test_add_shot_to_shot_info.cxi') as f:
# Check this directly since we want to make sure it saved
# it in all the places it should have
read_analyzer_1 = np.array(f['entry_1/data_1/analyzer_angle'])
read_analyzer_2 = np.array(f['entry_1/instrument_1/detector_1/analyzer_angle'])
read_analyzer_3 = np.array(f['entry_1/sample_1/geometry_1/analyzer_angle'])
read_analyzer_1 = f['entry_1/data_1/analyzer_angle'][()]
read_analyzer_2 = \
f['entry_1/instrument_1/detector_1/analyzer_angle'][()]
read_analyzer_3 = f['entry_1/sample_1/geometry_1/analyzer_angle'][()]
assert np.allclose(analyzer, read_analyzer_1)
assert np.allclose(analyzer, read_analyzer_2)
@@ -280,9 +281,10 @@ def test_add_ptycho_translations(tmp_path):
with h5py.File(tmp_path / 'test_add_ptycho_translations.cxi','r') as f:
# Check this directly since we want to make sure it saved
# it in all the places it should have
read_translations_1 = np.array(f['entry_1/data_1/translation'])
read_translations_2 = np.array(f['entry_1/instrument_1/detector_1/translation'])
read_translations_3 = np.array(f['entry_1/sample_1/geometry_1/translation'])
read_translations_1 = f['entry_1/data_1/translation'][()]
read_translations_2 = \
f['entry_1/instrument_1/detector_1/translation'][()]
read_translations_3 = f['entry_1/sample_1/geometry_1/translation'][()]
assert np.allclose(-translations, read_translations_1)
assert np.allclose(-translations, read_translations_2)
tests/tools/test_measurements.py
+1 -1
View File
@@ -6,7 +6,7 @@ import numpy as np
def test_intensity():
wavefields = t.rand((5,10,10)) + 1j * t.rand((5,10,10))
epsilon=1e-6
np_result = np.abs(t.as_tensor(wavefields))**2 + epsilon
np_result = np.abs(wavefields.numpy())**2 + epsilon
assert t.allclose(measurements.intensity(wavefields,epsilon=epsilon),
t.as_tensor(np_result))