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from __future__ import annotations
import h5py
import numpy as np
import pytest
def pytest_configure():
"""Incantations to create an in-memory file in h5py."""
pytest.h5_in_memory = {"driver": "core", "backing_store": False}
@pytest.fixture
def nxmx_example():
with h5py.File(" ", mode="w", **pytest.h5_in_memory) as f:
entry = f.create_group("/entry")
entry.attrs["NX_class"] = "NXentry"
entry["definition"] = "NXmx"
entry["start_time"] = "2021-09-10T06:54:37Z"
entry["end_time"] = "2021-09-10T06:55:09Z"
entry["end_time_estimated"] = "2021-09-10T06:55:09Z"
source = entry.create_group("source")
source.attrs["NX_class"] = "NXsource"
source_name = source.create_dataset("name", data="Diamond")
source_name.attrs["short_name"] = "DLS"
instrument = entry.create_group("instrument")
instrument.attrs["NX_class"] = "NXinstrument"
name = instrument.create_dataset(
"name", data=np.bytes_(b"DIAMOND BEAMLINE I03")
)
name.attrs["short_name"] = "I03"
beam = instrument.create_group("beam")
beam.attrs["NX_class"] = "NXbeam"
beam.create_dataset("incident_beam_size", data=np.array([3e-5, 3e-5]))
beam["incident_beam_size"].attrs["units"] = b"m"
beam["incident_wavelength"] = 0.976223
beam["incident_wavelength"].attrs["units"] = b"angstrom"
beam["total_flux"] = 1e12
beam["total_flux"].attrs["units"] = b"Hz"
detector = instrument.create_group("detector")
detector.attrs["NX_class"] = "NXdetector"
detector["beam_center_x"] = 2079.79727597266
detector["beam_center_y"] = 2225.38773853771
detector["count_time"] = 0.00285260857097799
detector["depends_on"] = "/entry/instrument/detector/transformations/det_z"
detector["description"] = "Eiger 16M"
detector["distance"] = 0.237015940260233
detector.create_dataset("data", data=np.zeros((100, 100)))
detector["sensor_material"] = "Silicon"
detector["sensor_thickness"] = 0.00045
detector["sensor_thickness"].attrs["units"] = b"m"
detector["x_pixel_size"] = 7.5e-05
detector["y_pixel_size"] = 7.5e-05
detector["underload_value"] = 0
detector["saturation_value"] = 9266
detector["frame_time"] = 0.1
detector["frame_time"].attrs["units"] = "s"
detector["bit_depth_readout"] = np.array(32)
detector["bit_depth_image"] = np.array(32)
detector_transformations = detector.create_group("transformations")
detector_transformations.attrs["NX_class"] = "NXtransformations"
det_z = detector_transformations.create_dataset("det_z", data=np.array([289.3]))
det_z.attrs["depends_on"] = b"."
det_z.attrs["transformation_type"] = b"translation"
det_z.attrs["units"] = b"mm"
det_z.attrs["vector"] = np.array([0.0, 0.0, 1.0])
module = detector.create_group("module")
module.attrs["NX_class"] = "NXdetector_module"
module.create_dataset("data_origin", data=np.array([0.0, 0.0]))
module.create_dataset("data_size", data=np.array([4362, 4148]))
fast_pixel_direction = module.create_dataset(
"fast_pixel_direction", data=7.5e-5
)
fast_pixel_direction.attrs["transformation_type"] = "translation"
fast_pixel_direction.attrs["depends_on"] = (
"/entry/instrument/detector/module/module_offset"
)
fast_pixel_direction.attrs["vector"] = np.array([-1.0, 0.0, 0.0])
fast_pixel_direction.attrs["offset"] = np.array([0.0, 0.0, 0.0])
fast_pixel_direction.attrs["offset_units"] = b"m"
fast_pixel_direction.attrs["units"] = b"m"
slow_pixel_direction = module.create_dataset(
"slow_pixel_direction", data=7.5e-5
)
slow_pixel_direction.attrs["transformation_type"] = "translation"
slow_pixel_direction.attrs["depends_on"] = (
"/entry/instrument/detector/module/module_offset"
)
slow_pixel_direction.attrs["vector"] = np.array([0.0, -1.0, 0.0])
slow_pixel_direction.attrs["offset"] = np.array([0.0, 0.0, 0.0])
slow_pixel_direction.attrs["offset_units"] = b"m"
slow_pixel_direction.attrs["units"] = b"m"
module_offset = module.create_dataset("module_offset", data=0)
module_offset.attrs["transformation_type"] = "translation"
module_offset.attrs["depends_on"] = detector["depends_on"]
module_offset.attrs["vector"] = np.array([1.0, 0.0, 0.0])
module_offset.attrs["offset"] = np.array([0.155985, 0.166904, -0])
module_offset.attrs["offset_units"] = b"m"
module_offset.attrs["units"] = b"m"
sample = entry.create_group("sample")
sample.attrs["NX_class"] = "NXsample"
sample["name"] = "mysample"
sample["depends_on"] = b"/entry/sample/transformations/phi"
sample["temperature"] = 273
sample["temperature"].attrs["units"] = b"K"
transformations = sample.create_group("transformations")
transformations.attrs["NX_class"] = "NXtransformations"
omega = transformations.create_dataset("omega", data=np.arange(0, 1, 0.1))
omega.attrs["depends_on"] = b"."
omega.attrs["transformation_type"] = b"rotation"
omega.attrs["units"] = b"deg"
omega.attrs["vector"] = np.array([-1.0, 0.0, 0.0])
omega.attrs["omega_offset"] = np.array([0.0, 0.0, 0.0])
transformations.create_dataset("omega_end", data=np.arange(0.1, 1.1, 0.1))
transformations.create_dataset("omega_increment_set", data=0.1)
phi = transformations.create_dataset("phi", data=np.array([0.0]))
phi.attrs["depends_on"] = b"/entry/sample/transformations/chi"
phi.attrs["transformation_type"] = b"rotation"
phi.attrs["units"] = b"deg"
phi.attrs["vector"] = np.array([-1.0, 0, 0])
chi = transformations.create_dataset("chi", data=0.0) # scalar dataset
chi.attrs["depends_on"] = b"/entry/sample/transformations/omega"
chi.attrs["transformation_type"] = b"rotation"
chi.attrs["units"] = b"deg"
chi.attrs["vector"] = np.array([0, 0, 1])
data = entry.create_group("data")
data.attrs["NX_class"] = "NXdata"
yield f
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