29. 2-D resolution functions

sasmodels.resolution2d

#This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #See the license text in license.txt

class sasmodels.resolution2d.Pinhole2D(data=None, index=None, nsigma=3.0, accuracy='Low', coords='polar')

Bases: Resolution

Gaussian Q smearing class for SAS 2d data

__annotate_func__ = None

__annotations_cache__ = {'q': 'np.ndarray', 'q_calc': 'np.ndarray'}

__class__

alias of type

__delattr__(name, /)

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'sasmodels.resolution2d', '__firstlineno__': 29, '__doc__': '\nGaussian Q smearing class for SAS 2d data\n', '__init__': <function Pinhole2D.__init__>, '_init_data': <function Pinhole2D._init_data>, '_calc_res': <function Pinhole2D._calc_res>, 'apply': <function Pinhole2D.apply>, '__static_attributes__': ('coords', 'data', 'dqx_data', 'dqy_data', 'index', 'nphi', 'nr', 'nsigma', 'q_calc', 'q_calc_weights', 'q_data', 'qx_data', 'qy_data'), '__annotations_cache__': {'q': 'np.ndarray', 'q_calc': 'np.ndarray'}})

__dir__()

Default dir() implementation.

__doc__ = '\nGaussian Q smearing class for SAS 2d data\n'

__eq__(value, /)

Return self==value.

__firstlineno__ = 29

__format__(format_spec, /)

Default object formatter.

Return str(self) if format_spec is empty. Raise TypeError otherwise.

__ge__(value, /)

Return self>=value.

__getattribute__(name, /)

Return getattr(self, name).

__getstate__()

Helper for pickle.

__gt__(value, /)

Return self>value.

__hash__()

Return hash(self).

__init__(data=None, index=None, nsigma=3.0, accuracy='Low', coords='polar')

Assumption: equally spaced bins in dq_r, dq_phi space.

Parameters:

• data – 2d data used to set the smearing parameters

• index – 1d array with len(data) to define the range of the calculation: elements are given as True or False

• nr – number of bins in dq_r-axis

• nphi – number of bins in dq_phi-axis

• coord – coordinates [string], ‘polar’ or ‘cartesian’

classmethod __init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__(value, /)

Return self<=value.

__lt__(value, /)

Return self<value.

__module__ = 'sasmodels.resolution2d'

__ne__(value, /)

Return self!=value.

classmethod __new__(*args, **kwargs)

__reduce__()

Helper for pickle.

__reduce_ex__(protocol, /)

Helper for pickle.

__repr__()

Return repr(self).

__setattr__(name, value, /)

Implement setattr(self, name, value).

__sizeof__()

Size of object in memory, in bytes.

__static_attributes__ = ('coords', 'data', 'dqx_data', 'dqy_data', 'index', 'nphi', 'nr', 'nsigma', 'q_calc', 'q_calc_weights', 'q_data', 'qx_data', 'qy_data')

__str__()

Return str(self).

classmethod __subclasshook__(object, /)

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object

_calc_res()

Over sampling of r_nbins times phi_nbins, calculate Gaussian weights, then find smeared intensity

_init_data(data, index)

Get qx_data, qy_data, dqx_data,dqy_data, and calculate phi_data=arctan(qx_data/qy_data)

apply(theory)

Smear theory by the resolution function, returning Iq.

q: ndarray = None

q_calc: ndarray = None

class sasmodels.resolution2d.Slit2D(q, q_length, q_width=0.0, q_calc=None, accuracy='low')

Bases: Resolution

Slit aperture with resolution function on an oriented sample.

q points at which the data is measured.

q_length slit length (long axis); assumed to be in the direction of qx

q_width slit width (short axis); assumed to be in the direction of qy; current implementation requires a fixed q_width for all q points.

Please note that this assumption of laboratory-frame qx and qy directions can be inverted by adding or subtracting 90 degrees from the model orientation. For the particular case of USANS, which has a vertical slit of width q_width sweeping through qx, add 90 degrees to the fitted phi angle to find the orientation relative to laboratory frame.

q_calc is the list of q points to calculate, or None if this should be estimated from the q and qx_width.

accuracy determines the number of q_width points to compute for each q. The values are stored in sasmodels.resolution2d.N_SLIT_PERP. The default values are: low=101, med=401, high=1001, xhigh=2001

__annotate_func__ = None

__annotations_cache__ = {'q': 'np.ndarray', 'q_calc': 'np.ndarray'}

__class__

alias of type

__delattr__(name, /)

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'sasmodels.resolution2d', '__firstlineno__': 177, '__doc__': '\nSlit aperture with resolution function on an oriented sample.\n\n*q* points at which the data is measured.\n\n*q_length* slit length (long axis); assumed to be in the direction of qx\n\n*q_width* slit width (short axis); assumed to be in the direction of qy; current implementation requires a fixed\nq_width for all q points.\n\nPlease note that this assumption of laboratory-frame qx and qy directions can be inverted by adding or subtracting\n90 degrees from the model orientation.  For the particular case of USANS, which has a vertical slit of width\n*q_width* sweeping through qx, add 90 degrees to the fitted phi angle to find the orientation relative to laboratory\nframe.\n\n*q_calc* is the list of q points to calculate, or None if this\nshould be estimated from the *q* and *qx_width*.\n\n*accuracy* determines the number of *q_width* points to compute for each *q*.\nThe values are stored in sasmodels.resolution2d.N_SLIT_PERP.  The default\nvalues are: low=101, med=401, high=1001, xhigh=2001\n', '__init__': <function Slit2D.__init__>, 'apply': <function Slit2D.apply>, '__static_attributes__': ('dy', 'nx', 'ny', 'q', 'q_calc', 'q_length', 'q_width', 'qx_calc', 'qy_calc', 'weights'), '__annotations_cache__': {'q': 'np.ndarray', 'q_calc': 'np.ndarray'}})

__dir__()

Default dir() implementation.

__doc__ = '\nSlit aperture with resolution function on an oriented sample.\n\n*q* points at which the data is measured.\n\n*q_length* slit length (long axis); assumed to be in the direction of qx\n\n*q_width* slit width (short axis); assumed to be in the direction of qy; current implementation requires a fixed\nq_width for all q points.\n\nPlease note that this assumption of laboratory-frame qx and qy directions can be inverted by adding or subtracting\n90 degrees from the model orientation.  For the particular case of USANS, which has a vertical slit of width\n*q_width* sweeping through qx, add 90 degrees to the fitted phi angle to find the orientation relative to laboratory\nframe.\n\n*q_calc* is the list of q points to calculate, or None if this\nshould be estimated from the *q* and *qx_width*.\n\n*accuracy* determines the number of *q_width* points to compute for each *q*.\nThe values are stored in sasmodels.resolution2d.N_SLIT_PERP.  The default\nvalues are: low=101, med=401, high=1001, xhigh=2001\n'

__eq__(value, /)

Return self==value.

__firstlineno__ = 177

__format__(format_spec, /)

Default object formatter.

Return str(self) if format_spec is empty. Raise TypeError otherwise.

__ge__(value, /)

Return self>=value.

__getattribute__(name, /)

Return getattr(self, name).

__getstate__()

Helper for pickle.

__gt__(value, /)

Return self>value.

__hash__()

Return hash(self).

__init__(q, q_length, q_width=0.0, q_calc=None, accuracy='low')

classmethod __init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__(value, /)

Return self<=value.

__lt__(value, /)

Return self<value.

__module__ = 'sasmodels.resolution2d'

__ne__(value, /)

Return self!=value.

classmethod __new__(*args, **kwargs)

__reduce__()

Helper for pickle.

__reduce_ex__(protocol, /)

Helper for pickle.

__repr__()

Return repr(self).

__setattr__(name, value, /)

Implement setattr(self, name, value).

__sizeof__()

Size of object in memory, in bytes.

__static_attributes__ = ('dy', 'nx', 'ny', 'q', 'q_calc', 'q_length', 'q_width', 'qx_calc', 'qy_calc', 'weights')

__str__()

Return str(self).

classmethod __subclasshook__(object, /)

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object

apply(theory)

Smear theory by the resolution function, returning Iq.

q: ndarray = None

q_calc: ndarray = None