CHAP.common.models.integration

Module Contents

Classes

Detector	Detector class to represent a single detector used in the experiment.
IntegrationConfig	Class representing the configuration for a raw detector data integration.

Functions

azimuthal_integrator	Return the azimuthal integrator from a PONI file
get_mask_array	Return a mask array associated with a detector loaded from a tiff file.
get_azimuthal_adjustments	Fix chi discontinuity at 180 degrees and return the adjusted chi range, offset, and discontinuty.
get_azimuthal_integrators	Return a list of AzimuthalIntegrator objects generated from PONI files.
get_multi_geometry_integrator	Return a MultiGeometry instance that can be used for azimuthal or cake integration.
get_integrated_data_coordinates	Return a dictionary of coordinate arrays for the specified radial and/or azimuthal integration ranges.

API

class CHAP.common.models.integration.Detector

Bases: pydantic.BaseModel

Detector class to represent a single detector used in the experiment.

Parameters:

• prefix (str) – Prefix of the detector in the SPEC file.

• poni_file (str) – Path to the poni file.

• mask_file (str, optional) – Optional path to the mask file.

prefix: constr(strip_whitespace=True, min_length=1)

None

poni_file: pydantic.FilePath

None

mask_file: Optional[pydantic.FilePath]

None

classmethod validate_poni_file(poni_file)

Validate the poni file by checking if it’s a valid PONI file.

Parameters:

poni_file (str) – Path to the poni file.

Raises:

ValueError – If poni_file is not a valid PONI file.

Returns:

Absolute path to the poni file.

Return type:

str

classmethod validate_mask_file(mask_file, values)

Validate the mask file. If a mask file is provided, it checks if it’s a valid TIFF file.

Parameters:

• mask_file (str or None) – Path to the mask file.

• values (dict) – A dictionary of the Detector fields.

Raises:

• ValueError – If mask_file is provided and it’s not a valid TIFF file.

• ValueError – If 'poni_file' is not provided in values.

Returns:

Absolute path to the mask file or None.

Return type:

str or None

property azimuthal_integrator

Return the azimuthal integrator associated with this detector.

property mask_array

Return the mask array assocated with this detector.

CHAP.common.models.integration.azimuthal_integrator(poni_file: str)

Return the azimuthal integrator from a PONI file

Parameters:

poni_file (str) – path to a PONI file

Returns:

azimuthal integrator

Return type:

pyFAI.azimuthal_integrator.AzimuthalIntegrator

CHAP.common.models.integration.get_mask_array(mask_file: str, poni_file: str)

Return a mask array associated with a detector loaded from a tiff file.

Parameters:

• mask_file (str) – path to a .tiff file

• poni_file (str) – path to a PONI file

Returns:

the mask array loaded from mask_file

Return type:

numpy.ndarray

class CHAP.common.models.integration.IntegrationConfig

Bases: pydantic.BaseModel

Class representing the configuration for a raw detector data integration.

Variables:

• tool_type – type of integration tool; always set to “integration”

• title – title of the integration

• integration_type – type of integration, one of “azimuthal”, “radial”, or “cake”

• detectors – list of detectors used in the integration

• radial_units – radial units for the integration, defaults to 'q_A^-1'

• radial_min – minimum radial value for the integration range

• radial_max – maximum radial value for the integration range

• radial_npt – number of points in the radial range for the integration

• azimuthal_units – azimuthal units for the integration

• azimuthal_min – minimum azimuthal value for the integration range

• azimuthal_max – maximum azimuthal value for the integration range

• azimuthal_npt – number of points in the azimuthal range for the integration

• error_model – error model for the integration, one of “poisson” or “azimuthal”

tool_type: Literal[integration]

‘integration’

title: constr(strip_whitespace=True, min_length=1)

None

integration_type: Literal[azimuthal, radial, cake]

None

detectors: conlist(item_type=Detector, min_length=1)

None

radial_units: str

‘q_A^-1’

radial_min: confloat(ge=0)

None

radial_max: confloat(gt=0)

None

radial_npt: conint(gt=0)

1800

azimuthal_units: str

‘chi_deg’

azimuthal_min: confloat(ge=-180)

None

azimuthal_max: confloat(le=360)

180

azimuthal_npt: conint(gt=0)

3600

error_model: Optional[Literal[poisson, azimuthal]]

None

sequence_index: Optional[conint(gt=0)]

None

classmethod validate_radial_units(radial_units)

Validate the radial units for the integration.

Parameters:

radial_units (str) – unvalidated radial units for the integration

Raises:

ValueError – if radial units are not one of the recognized radial units

Returns:

validated radial units

Return type:

str

classmethod validate_azimuthal_units(azimuthal_units)

Validate that azimuthal_units is one of the keys in the pyFAI.units.AZIMUTHAL_UNITS dictionary.

Parameters:

azimuthal_units (str) – The string representing the unit to be validated.

Raises:

ValueError – If azimuthal_units is not one of the keys in pyFAI.units.AZIMUTHAL_UNITS

Returns:

The original supplied value, if is one of the keys in pyFAI.units.AZIMUTHAL_UNITS.

Return type:

str

validate_range_max()

Validate the maximum value of an integration range.

Parameters:

range_name (str) – The name of the integration range (e.g. radial, azimuthal).

Returns:

The callable that performs the validation.

Return type:

callable

_validate_radial_max

‘(…)’

_validate_azimuthal_max

‘(…)’

validate_for_map_config(map_config: pydantic.BaseModel)

Validate the existence of the detector data file for all scan points in map_config.

Parameters:

map_config (MapConfig) – The MapConfig instance to validate against.

Raises:

RuntimeError – If a detector data file could not be found for a scan point occurring in map_config.

Returns:

None

Return type:

None

get_azimuthal_adjustments()

To enable a continuous range of integration in the azimuthal direction for radial and cake integration, obtain adjusted values for this IntegrationConfig’s azimuthal_min and azimuthal_max values, the angle amount by which those values were adjusted, and the proper location of the discontinuity in the azimuthal direction.

Returns:

Adjusted chi_min, adjusted chi_max, chi_offset, chi_discontinuity

Return type:

tuple[float,float,float,float]

get_azimuthal_integrators()

Get a list of AzimuthalIntegrators that correspond to the detector configurations in this instance of IntegrationConfig.

The returned AzimuthalIntegrators are (if need be) artificially rotated in the azimuthal direction to achieve a continuous range of integration in the azimuthal direction.

Returns:

A list of AzimuthalIntegrators appropriate for use by this IntegrationConfig tool

Return type:

list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator]

get_multi_geometry_integrator()

Get a MultiGeometry integrator suitable for use by this instance of IntegrationConfig.

Returns:

A MultiGeometry integrator

Return type:

pyFAI.multi_geometry.MultiGeometry

get_azimuthally_integrated_data(spec_scans: pydantic.BaseModel, scan_number: int, scan_step_index: int)

Return azimuthally-integrated data for the scan step specified.

Parameters:

• spec_scans (SpecScans) – An instance of SpecScans containing the scan step requested.

• scan_number (int) – The number of the scan containing the scan step requested.

• scan_step_index (int) – The index of the scan step requested.

Returns:

A 1D array of azimuthally-integrated raw detector intensities.

Return type:

np.ndarray

get_radially_integrated_data(spec_scans: pydantic.BaseModel, scan_number: int, scan_step_index: int)

Return radially-integrated data for the scan step specified.

Parameters:

• spec_scans (SpecScans) – An instance of SpecScans containing the scan step requested.

• scan_number (int) – The number of the scan containing the scan step requested.

• scan_step_index (int) – The index of the scan step requested.

Returns:

A 1D array of radially-integrated raw detector intensities.

Return type:

np.ndarray

get_cake_integrated_data(spec_scans: pydantic.BaseModel, scan_number: int, scan_step_index: int)

Return cake-integrated data for the scan step specified.

Parameters:

• spec_scans (SpecScans) – An instance of SpecScans containing the scan step requested.

• scan_number (int) – The number of the scan containing the scan step requested.

• scan_step_index (int) – The index of the scan step requested.

Returns:

A 2D array of cake-integrated raw detector intensities.

Return type:

np.ndarray

get_integrated_data(spec_scans: pydantic.BaseModel, scan_number: int, scan_step_index: int)

Return integrated data for the scan step specified.

Parameters:

• spec_scans (SpecScans) – An instance of SpecScans containing the scan step requested.

• scan_number (int) – The number of the scan containing the scan step requested.

• scan_step_index (int) – The index of the scan step requested.

Returns:

An array of integrated raw detector intensities.

Return type:

np.ndarray

property integrated_data_coordinates

Return a dictionary of coordinate arrays for navigating the dimension(s) of the integrated data produced by this instance of IntegrationConfig.

Returns:

A dictionary with either one or two keys: ‘azimuthal’ and/or ‘radial’, each of which points to a 1-D numpy array of coordinate values.

Return type:

dict[str,np.ndarray]

property integrated_data_dims

Return a tuple of the coordinate labels for the integrated data produced by this instance of IntegrationConfig.

property integrated_data_shape

Return a tuple representing the shape of the integrated data produced by this instance of IntegrationConfig for a single scan step.

CHAP.common.models.integration.get_azimuthal_adjustments(chi_min: float, chi_max: float)

Fix chi discontinuity at 180 degrees and return the adjusted chi range, offset, and discontinuty.

If the discontinuity is crossed, obtain the offset to artificially rotate detectors to achieve a continuous azimuthal integration range.

Parameters:

• chi_min (float) – The minimum value of the azimuthal range.

• chi_max (float) – The maximum value of the azimuthal range.

Returns:

The following four values: the adjusted minimum value of the azimuthal range, the adjusted maximum value of the azimuthal range, the value by which the chi angle was adjusted, the position of the chi discontinuity.

CHAP.common.models.integration.get_azimuthal_integrators(poni_files: tuple, chi_offset=0)

Return a list of AzimuthalIntegrator objects generated from PONI files.

Parameters:

• poni_files (tuple) – Tuple of strings, each string being a path to a PONI file.

• chi_offset (float, optional) – The angle in degrees by which the AzimuthalIntegrator objects will be rotated, defaults to 0.

Returns:

List of AzimuthalIntegrator objects

Return type:

list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator]

CHAP.common.models.integration.get_multi_geometry_integrator(poni_files: tuple, radial_unit: str, radial_range: tuple, azimuthal_range: tuple)

Return a MultiGeometry instance that can be used for azimuthal or cake integration.

Parameters:

• poni_files (tuple) – Tuple of PONI files that describe the detectors to be integrated.

• radial_unit (str) – Unit to use for radial integration range.

• radial_range (tuple[float,float]) – Tuple describing the range for radial integration.

• azimuthal_range (tuple[float,float]) – Tuple describing the range for azimuthal integration.

Returns:

MultiGeometry instance that can be used for azimuthal or cake integration.

Return type:

pyFAI.multi_geometry.MultiGeometry

CHAP.common.models.integration.get_integrated_data_coordinates(azimuthal_range: tuple = None, azimuthal_npt: int = None, radial_range: tuple = None, radial_npt: int = None)

Return a dictionary of coordinate arrays for the specified radial and/or azimuthal integration ranges.

Parameters:

• azimuthal_range (tuple[float,float], optional) – Tuple specifying the range of azimuthal angles over which to generate coordinates, in the format (min, max), defaults to None.

• azimuthal_npt (int, optional) – Number of azimuthal coordinate points to generate, defaults to None.

• radial_range (tuple[float,float], optional) – Tuple specifying the range of radial distances over which to generate coordinates, in the format (min, max), defaults to None.

• radial_npt (int, optional) – Number of radial coordinate points to generate, defaults to None.

Returns:

A dictionary with either one or two keys: ‘azimuthal’ and/or ‘radial’, each of which points to a 1-D numpy array of coordinate values.

Return type:

dict[str,np.ndarray]