def set_phase_parameters(
self,
number: int = 1,
atom_coordinates: Optional[dict] = None,
formula: Optional[str] = None,
info: Optional[str] = None,
lattice_constants: Union[None, np.ndarray, List[float],
List[int]] = None,
laue_group: Optional[str] = None,
material_name: Optional[str] = None,
point_group: Optional[str] = None,
setting: Optional[int] = None,
source: Optional[str] = None,
space_group: Optional[int] = None,
symmetry: Optional[int] = None,
):
"""Set parameters for one phase in signal metadata.
A phase node with default values is created if none is present
in the metadata when this method is called.
Parameters
----------
number
Phase number.
atom_coordinates
Dictionary of dictionaries with one or more of the atoms in
the unit cell, on the form `{'1': {'atom': 'Ni',
'coordinates': [0, 0, 0], 'site_occupation': 1,
'debye_waller_factor': 0}, '2': {'atom': 'O',... etc.`
`debye_waller_factor` in units of nm^2, and
`site_occupation` in range [0, 1].
formula
Phase formula, e.g. 'Fe2' or 'Ni'.
info
Whatever phase info the user finds relevant.
lattice_constants
Six lattice constants a, b, c, alpha, beta, gamma.
laue_group
Phase Laue group.
material_name
Name of material.
point_group
Phase point group.
setting
Space group's origin setting.
source
Literature reference for phase data.
space_group
Number between 1 and 230.
symmetry
Phase symmetry.
See Also
--------
set_simulation_parameters
Examples
--------
>>> s.metadata.Sample.Phases.Number_1.atom_coordinates.Number_1
├── atom =
├── coordinates = array([0., 0., 0.])
├── debye_waller_factor = 0.0
└── site_occupation = 0.0
>>> s.set_phase_parameters(
... number=1, atom_coordinates={
... '1': {'atom': 'Ni', 'coordinates': [0, 0, 0],
... 'site_occupation': 1,
... 'debye_waller_factor': 0.0035}})
>>> s.metadata.Sample.Phases.Number_1.atom_coordinates.Number_1
├── atom = Ni
├── coordinates = array([0., 0., 0.])
├── debye_waller_factor = 0.0035
└── site_occupation = 1
"""
# Ensure atom coordinates are numpy arrays
if atom_coordinates is not None:
for phase, val in atom_coordinates.items():
atom_coordinates[phase]["coordinates"] = np.array(
atom_coordinates[phase]["coordinates"])
inputs = {
"atom_coordinates": atom_coordinates,
"formula": formula,
"info": info,
"lattice_constants": lattice_constants,
"laue_group": laue_group,
"material_name": material_name,
"point_group": point_group,
"setting": setting,
"source": source,
"space_group": space_group,
"symmetry": symmetry,
}
# Remove None values
phase = {k: v for k, v in inputs.items() if v is not None}
_update_phase_info(self.metadata, phase, number)
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()
def edaxheader2dicts(
scan_group: h5py.Group, md: DictionaryTreeBrowser
) -> Tuple[DictionaryTreeBrowser, DictionaryTreeBrowser, DictionaryTreeBrowser]:
"""Return scan metadata dictionaries from an EDAX TSL h5ebsd file.
Parameters
----------
scan_group : h5py:Group
HDF group of scan data and header.
md
Dictionary with empty fields from kikuchipy's metadata.
Returns
-------
md
kikuchipy ``metadata`` elements available in EDAX file.
omd
All metadata available in EDAX file.
scan_size
Scan, image, step and detector pixel size available in EDAX
file.
"""
# Get header group as dictionary
pattern_dset_names = list(manufacturer_pattern_names().values())
hd = hdf5group2dict(
group=scan_group["EBSD/Header"],
data_dset_names=pattern_dset_names,
recursive=True,
)
# Populate metadata dictionary
sem_node, ebsd_node = metadata_nodes(["sem", "ebsd"])
md.set_item(ebsd_node + ".azimuth_angle", hd["Camera Azimuthal Angle"])
md.set_item(ebsd_node + ".elevation_angle", hd["Camera Elevation Angle"])
grid_type = hd["Grid Type"]
if grid_type == "SqrGrid":
md.set_item(ebsd_node + ".grid_type", "square")
else:
raise IOError(
f"Only square grids are supported, however a {grid_type} grid was "
"passed."
)
md.set_item(ebsd_node + ".sample_tilt", hd["Sample Tilt"])
md.set_item("General.authors", hd["Operator"])
md.set_item("General.notes", hd["Notes"])
md.set_item(ebsd_node + ".xpc", hd["Pattern Center Calibration"]["x-star"])
md.set_item(ebsd_node + ".ypc", hd["Pattern Center Calibration"]["y-star"])
md.set_item(ebsd_node + ".zpc", hd["Pattern Center Calibration"]["z-star"])
md.set_item(sem_node + ".working_distance", hd["Working Distance"])
if "SEM-PRIAS Images" in scan_group.keys():
md.set_item(
sem_node + ".magnification",
scan_group["SEM-PRIAS Images/Header/Mag"][0],
)
# Loop over phases in group and add to metadata
for phase_no, phase in hd["Phase"].items():
phase["material_name"] = phase["MaterialName"]
phase["lattice_constants"] = [
phase["Lattice Constant a"],
phase["Lattice Constant b"],
phase["Lattice Constant c"],
phase["Lattice Constant alpha"],
phase["Lattice Constant beta"],
phase["Lattice Constant gamma"],
]
md = _update_phase_info(md, phase, phase_no)
# Populate original metadata dictionary
omd = DictionaryTreeBrowser({"edax_header": hd})
# Populate scan size dictionary
scan_size = DictionaryTreeBrowser()
scan_size.set_item("sx", hd["Pattern Width"])
scan_size.set_item("sy", hd["Pattern Height"])
scan_size.set_item("nx", hd["nColumns"])
scan_size.set_item("ny", hd["nRows"])
scan_size.set_item("step_x", hd["Step X"])
scan_size.set_item("step_y", hd["Step Y"])
scan_size.set_item("delta", 1.0)
return md, omd, scan_size
def brukerheader2dicts(
scan_group: h5py.Group, md: DictionaryTreeBrowser
) -> Tuple[DictionaryTreeBrowser, DictionaryTreeBrowser, DictionaryTreeBrowser]:
"""Return scan metadata dictionaries from a Bruker h5ebsd file.
Parameters
----------
scan_group : h5py:Group
HDF group of scan data and header.
md : hyperspy.misc.utils.DictionaryTreeBrowser
Dictionary with empty fields from kikuchipy's metadata.
Returns
-------
md
kikuchipy ``metadata`` elements available in Bruker file.
omd
All metadata available in Bruker file.
scan_size
Scan, image, step and detector pixel size available in Bruker
file.
"""
# Get header group and data group as dictionaries
pattern_dset_names = list(manufacturer_pattern_names().values())
hd = hdf5group2dict(
group=scan_group["EBSD/Header"],
data_dset_names=pattern_dset_names,
recursive=True,
)
dd = hdf5group2dict(
group=scan_group["EBSD/Data"], data_dset_names=pattern_dset_names,
)
# Populate metadata dictionary
sem_node, ebsd_node = metadata_nodes(["sem", "ebsd"])
md.set_item(ebsd_node + ".elevation_angle", hd["CameraTilt"])
grid_type = hd["Grid Type"]
if grid_type == "isometric":
md.set_item(ebsd_node + ".grid_type", "square")
else:
raise IOError(
f"Only square grids are supported, however a {grid_type} grid was "
"passed."
)
md.set_item(ebsd_node + ".sample_tilt", hd["SampleTilt"])
md.set_item(ebsd_node + ".xpc", np.mean(dd["PCX"]))
md.set_item(ebsd_node + ".ypc", np.mean(dd["PCY"]))
md.set_item(ebsd_node + ".zpc", np.mean(dd["DD"]))
md.set_item(ebsd_node + ".static_background", hd["StaticBackground"])
md.set_item(sem_node + ".working_distance", hd["WD"])
md.set_item(sem_node + ".beam_energy", hd["KV"])
md.set_item(sem_node + ".magnification", hd["Magnification"])
# Loop over phases
for phase_no, phase in hd["Phases"].items():
phase["material_name"] = phase["Name"]
phase["space_group"] = phase["IT"]
phase["atom_coordinates"] = {}
for key, val in phase["AtomPositions"].items():
atom = val.split(",")
atom[1:] = list(map(float, atom[1:]))
phase["atom_coordinates"][key] = {
"atom": atom[0],
"coordinates": atom[1:4],
"site_occupation": atom[4],
"debye_waller_factor": atom[5],
}
md = _update_phase_info(md, phase, phase_no)
# Populate original metadata dictionary
omd = DictionaryTreeBrowser({"bruker_header": hd})
# Populate scan size dictionary
scan_size = DictionaryTreeBrowser()
scan_size.set_item("sx", hd["PatternWidth"])
scan_size.set_item("sy", hd["PatternHeight"])
scan_size.set_item("nx", hd["NCOLS"])
scan_size.set_item("ny", hd["NROWS"])
scan_size.set_item("step_x", hd["XSTEP"])
scan_size.set_item("step_y", hd["YSTEP"])
scan_size.set_item(
"delta", hd["DetectorFullHeightMicrons"] / hd["UnClippedPatternHeight"]
)
return md, omd, scan_size
def brukerheader2dicts(
scan_group: h5py.Group, md: DictionaryTreeBrowser
) -> Tuple[DictionaryTreeBrowser, DictionaryTreeBrowser,
DictionaryTreeBrowser]:
"""Return scan metadata dictionaries from a Bruker h5ebsd file.
Parameters
----------
scan_group : h5py:Group
HDF group of scan data and header.
md : hyperspy.misc.utils.DictionaryTreeBrowser
Dictionary with empty fields from kikuchipy's metadata.
Returns
-------
md
kikuchipy ``metadata`` elements available in Bruker file.
omd
All metadata available in Bruker file.
scan_size
Scan, image, step and detector pixel size available in Bruker
file.
"""
# Get header group and data group as dictionaries
pattern_dset_names = list(manufacturer_pattern_names().values())
hd = hdf5group2dict(
group=scan_group["EBSD/Header"],
data_dset_names=pattern_dset_names,
recursive=True,
)
dd = hdf5group2dict(group=scan_group["EBSD/Data"],
data_dset_names=pattern_dset_names)
# Populate metadata dictionary
sem_node, ebsd_node = metadata_nodes(["sem", "ebsd"])
md.set_item(ebsd_node + ".elevation_angle", hd["CameraTilt"])
grid_type = hd["Grid Type"]
if grid_type == "isometric":
md.set_item(ebsd_node + ".grid_type", "square")
else:
raise IOError(
f"Only square grids are supported, however a {grid_type} grid was passed"
)
# Values: data set name, data group, function to apply, node
dset_mapping = {
"sample_tilt": ["SampleTilt", hd, None, ebsd_node],
"xpz": ["PCX", dd, np.nanmean, ebsd_node],
"ypc": ["PCY", dd, np.nanmean, ebsd_node],
"zpc": ["DD", dd, np.nanmean, ebsd_node],
"static_background": ["StaticBackground", hd, None, ebsd_node],
"working_distance": ["WD", hd, None, sem_node],
"beam_energy": ["KV", hd, None, sem_node],
"magnification": ["Magnification", hd, None, sem_node],
}
for k, v in dset_mapping.items():
dset_name, dset_group, func, node = v
try:
dset = dset_group[dset_name]
if func:
dset = func(dset)
except KeyError:
dset = None
md.set_item(node + f".{k}", dset)
# Loop over phases
for phase_no, phase in hd["Phases"].items():
phase["material_name"] = phase["Name"]
phase["space_group"] = phase["IT"]
phase["atom_coordinates"] = {}
for key, val in phase["AtomPositions"].items():
atom = val.split(",")
atom[1:] = list(map(float, atom[1:]))
phase["atom_coordinates"][key] = {
"atom": atom[0],
"coordinates": atom[1:4],
"site_occupation": atom[4],
"debye_waller_factor": atom[5],
}
md = _update_phase_info(md, phase, phase_no)
# Populate original metadata dictionary
omd = DictionaryTreeBrowser({"bruker_header": hd})
# Initialize scan size dictionary
scan_size = DictionaryTreeBrowser()
# Get region of interest (ROI, only rectangular shape supported)
try:
sd = hdf5group2dict(group=scan_group["EBSD/SEM"])
ir = sd["IY"][()]
ic = sd["IX"][()]
roi = True
except KeyError:
roi = False
nr = hd["NROWS"]
nc = hd["NCOLS"]
if roi:
nr_roi, nc_roi, is_rectangular = _bruker_roi_is_rectangular(ir, ic)
if is_rectangular:
nr = nr_roi
nc = nc_roi
# Get indices of patterns in the 2D map
idx = np.array([ir - np.min(ir), ic - np.min(ic)])
scan_size["indices"] = np.ravel_multi_index(idx,
(nr, nc)).argsort()
else:
raise ValueError(
"Only a rectangular region of interest is supported")
# Populate scan size dictionary
scan_size.set_item("sx", hd["PatternWidth"])
scan_size.set_item("sy", hd["PatternHeight"])
scan_size.set_item("nx", nc)
scan_size.set_item("ny", nr)
scan_size.set_item("step_x", hd["XSTEP"])
scan_size.set_item("step_y", hd["YSTEP"])
scan_size.set_item(
"delta",
hd["DetectorFullHeightMicrons"] / hd["UnClippedPatternHeight"])
return md, omd, scan_size