def get_settings_from_file(
filename: str,
) -> Tuple[DictionaryTreeBrowser, DictionaryTreeBrowser, DictionaryTreeBrowser]:
"""Return metadata with parameters from NORDIF setting file.
Parameters
----------
filename
File path of NORDIF setting file.
Returns
-------
md
Metadata complying with HyperSpy's metadata structure.
omd
Metadata that does not fit into HyperSpy's metadata structure.
scan_size
Information on image size, scan size and scan steps.
"""
f = open(filename, "r", encoding="latin-1") # Avoid byte strings
content = f.read().splitlines()
# Get line numbers of setting blocks
blocks = {
"[NORDIF]": -1,
"[Microscope]": -1,
"[EBSD detector]": -1,
"[Detector angles]": -1,
"[Acquisition settings]": -1,
"[Area]": -1,
"[Specimen]": -1,
}
for i, line in enumerate(content):
for block in blocks:
if block in line:
blocks[block] = i
l_nordif = blocks["[NORDIF]"]
l_mic = blocks["[Microscope]"]
l_det = blocks["[EBSD detector]"]
l_ang = blocks["[Detector angles]"]
l_acq = blocks["[Acquisition settings]"]
l_area = blocks["[Area]"]
l_specimen = blocks["[Specimen]"]
# Create metadata and original metadata structures
md = ebsd_metadata()
sem_node, ebsd_node = metadata_nodes(["sem", "ebsd"])
omd = DictionaryTreeBrowser()
omd.set_item("nordif_header", content)
# Get metadata values from settings file using regular expressions
azimuth_angle = get_string(content, "Azimuthal\t(.*)\t", l_ang + 4, f)
md.set_item(ebsd_node + ".azimuth_angle", float(azimuth_angle))
beam_energy = get_string(
content, "Accelerating voltage\t(.*)\tkV", l_mic + 5, f
)
md.set_item(sem_node + ".beam_energy", float(beam_energy))
detector = get_string(content, "Model\t(.*)\t", l_det + 1, f)
detector = re.sub("[^a-zA-Z0-9]", repl="", string=detector)
md.set_item(ebsd_node + ".detector", "NORDIF " + detector)
elevation_angle = get_string(content, "Elevation\t(.*)\t", l_ang + 5, f)
md.set_item(ebsd_node + ".elevation_angle", float(elevation_angle))
exposure_time = get_string(content, "Exposure time\t(.*)\t", l_acq + 3, f)
md.set_item(ebsd_node + ".exposure_time", float(exposure_time) / 1e6)
frame_rate = get_string(content, "Frame rate\t(.*)\tfps", l_acq + 1, f)
md.set_item(ebsd_node + ".frame_rate", int(frame_rate))
gain = get_string(content, "Gain\t(.*)\t", l_acq + 4, f)
md.set_item(ebsd_node + ".gain", float(gain))
magnification = get_string(content, "Magnification\t(.*)\t#", l_mic + 3, f)
md.set_item(sem_node + ".magnification", int(magnification))
mic_manufacturer = get_string(content, "Manufacturer\t(.*)\t", l_mic + 1, f)
mic_model = get_string(content, "Model\t(.*)\t", l_mic + 2, f)
md.set_item(sem_node + ".microscope", mic_manufacturer + " " + mic_model)
sample_tilt = get_string(content, "Tilt angle\t(.*)\t", l_mic + 7, f)
md.set_item(ebsd_node + ".sample_tilt", float(sample_tilt))
scan_time = get_string(content, "Scan time\t(.*)\t", l_area + 7, f)
scan_time = time.strptime(scan_time, "%H:%M:%S")
scan_time = datetime.timedelta(
hours=scan_time.tm_hour,
minutes=scan_time.tm_min,
seconds=scan_time.tm_sec,
).total_seconds()
md.set_item(ebsd_node + ".scan_time", int(scan_time))
version = get_string(content, "Software version\t(.*)\t", l_nordif + 1, f)
md.set_item(ebsd_node + ".version", version)
working_distance = get_string(
content, "Working distance\t(.*)\tmm", l_mic + 6, f
)
md.set_item(sem_node + ".working_distance", float(working_distance))
md.set_item(ebsd_node + ".grid_type", "square")
md.set_item(ebsd_node + ".manufacturer", "NORDIF")
specimen = get_string(content, "Name\t(.*)\t", l_specimen + 1, f)
pmd = _phase_metadata()
pmd["material_name"] = specimen
md.set_item("Sample.Phases.1", pmd)
# Get scan size values
scan_size = DictionaryTreeBrowser()
num_samp = get_string(content, "Number of samples\t(.*)\t#", l_area + 6, f)
ny, nx = [int(i) for i in num_samp.split("x")]
scan_size.set_item("nx", int(nx))
scan_size.set_item("ny", int(ny))
pattern_size = get_string(content, "Resolution\t(.*)\tpx", l_acq + 2, f)
sx, sy = [int(i) for i in pattern_size.split("x")]
scan_size.set_item("sx", int(sx))
scan_size.set_item("sy", int(sy))
step_size = get_string(content, "Step size\t(.*)\t", l_area + 5, f)
scan_size.set_item("step_x", float(step_size))
scan_size.set_item("step_y", float(step_size))
return md, omd, scan_size
def file_writer(
filename: str,
signal,
add_scan: Optional[bool] = None,
scan_number: int = 1,
**kwargs,
):
"""Write an :class:`~kikuchipy.signals.EBSD` or
:class:`~kikuchipy.signals.LazyEBSD` signal to an existing,
but not open, or new h5ebsd file.
Only writing to kikuchipy's h5ebsd format is supported.
Parameters
----------
filename
Full path of HDF file.
signal : kikuchipy.signals.EBSD or kikuchipy.signals.LazyEBSD
Signal instance.
add_scan
Add signal to an existing, but not open, h5ebsd file. If it does
not exist it is created and the signal is written to it.
scan_number
Scan number in name of HDF dataset when writing to an existing,
but not open, h5ebsd file.
kwargs
Keyword arguments passed to :meth:`h5py:Group.require_dataset`.
"""
# Set manufacturer and version to use in file
from kikuchipy.release import version as ver_signal
man_ver_dict = {"manufacturer": "kikuchipy", "version": ver_signal}
# Open file in correct mode
mode = "w"
if os.path.isfile(filename) and add_scan:
mode = "r+"
try:
f = h5py.File(filename, mode=mode)
except OSError:
raise OSError("Cannot write to an already open file.")
if os.path.isfile(filename) and add_scan:
check_h5ebsd(f)
man_file, ver_file = manufacturer_version(f)
if man_ver_dict["manufacturer"].lower() != man_file.lower():
f.close()
raise IOError(
f"Only writing to kikuchipy's (and not {man_file}'s) h5ebsd "
"format is supported."
)
man_ver_dict["version"] = ver_file
# Get valid scan number
scans_file = [f[k] for k in f["/"].keys() if "Scan" in k]
scan_nos = [int(i.name.split()[-1]) for i in scans_file]
for i in scan_nos:
if i == scan_number:
q = f"Scan {i} already in file, enter another scan number:\n"
scan_number = _get_input_variable(q, int)
if scan_number is None:
raise IOError("Invalid scan number.")
else: # File did not exist
dict2h5ebsdgroup(man_ver_dict, f["/"], **kwargs)
scan_group = f.create_group("Scan " + str(scan_number))
# Create scan dictionary with EBSD and SEM metadata
# Add scan size, image size and detector pixel size to dictionary to write
data_shape = [1] * 4 # (ny, nx, sy, sx)
data_scales = [1] * 4 # (y, x, dy, dx)
nav_extent = [0, 1, 0, 1] # (x0, x1, y0, y1)
am = signal.axes_manager
nav_axes = am.navigation_axes
nav_dim = am.navigation_dimension
if nav_dim == 1:
nav_axis = nav_axes[0]
if nav_axis.name == "y":
data_shape[0] = nav_axis.size
data_scales[0] = nav_axis.scale
nav_extent[2:] = am.navigation_extent
else: # nav_axis.name == "x" or something else
data_shape[1] = nav_axis.size
data_scales[1] = nav_axis.scale
nav_extent[:2] = am.navigation_extent
elif nav_dim == 2:
data_shape[:2] = [i.size for i in nav_axes][::-1]
data_scales[:2] = [i.scale for i in nav_axes][::-1]
nav_extent = am.navigation_extent
data_shape[2:] = am.signal_shape
data_scales[2:] = [i.scale for i in am.signal_axes]
ny, nx, sy, sx = data_shape
scale_ny, scale_nx, scale_sy, _ = data_scales
md = signal.metadata.deepcopy()
sem_node, ebsd_node = metadata_nodes(["sem", "ebsd"])
md.set_item(ebsd_node + ".pattern_width", sx)
md.set_item(ebsd_node + ".pattern_height", sy)
md.set_item(ebsd_node + ".n_columns", nx)
md.set_item(ebsd_node + ".n_rows", ny)
md.set_item(ebsd_node + ".step_x", scale_nx)
md.set_item(ebsd_node + ".step_y", scale_ny)
md.set_item(ebsd_node + ".detector_pixel_size", scale_sy)
# Separate EBSD and SEM metadata
det_str, ebsd_str = ebsd_node.split(".")[-2:] # Detector and EBSD nodes
md_sem = md.get_item(sem_node).copy().as_dictionary() # SEM node as dict
md_det = md_sem.pop(det_str) # Remove/assign detector node from SEM node
md_ebsd = md_det.pop(ebsd_str)
# Phases
if md.get_item("Sample.Phases") is None:
md = _update_phase_info(md, _phase_metadata()) # Add default phase
md_ebsd["Phases"] = md.Sample.Phases.as_dictionary()
for phase in md_ebsd["Phases"].keys(): # Ensure coordinates are arrays
atom_coordinates = md_ebsd["Phases"][phase]["atom_coordinates"]
for atom in atom_coordinates.keys():
atom_coordinates[atom]["coordinates"] = np.array(
atom_coordinates[atom]["coordinates"]
)
scan = {"EBSD": {"Header": md_ebsd}, "SEM": {"Header": md_sem}}
# Write scan dictionary to HDF groups
dict2h5ebsdgroup(scan, scan_group)
# Write signal to file
man_pats = manufacturer_pattern_names()
dset_pattern_name = man_pats["kikuchipy"]
overwrite_dataset(
scan_group.create_group("EBSD/Data"),
signal.data.reshape(nx * ny, sy, sx),
dset_pattern_name,
signal_axes=(2, 1),
**kwargs,
)
nx_start, nx_stop, ny_start, ny_stop = nav_extent
sample_pos = {
"y_sample": np.tile(np.linspace(ny_start, ny_stop, ny), nx),
"x_sample": np.tile(np.linspace(nx_start, nx_stop, nx), ny),
}
dict2h5ebsdgroup(sample_pos, scan_group["EBSD/Data"])
f.close()
