ptypy.experiment.ID16Anfp.ID16AScan#

class ptypy.experiment.ID16Anfp.ID16AScan(pars=None, **kwargs)#

Bases: PtyScan

Subclass of PtyScan for ID16A beamline (specifically for near-field ptychography).

Default data parameters. See scan.data

__init__(pars=None, **kwargs)#: Create a PtyScan object that will load ID16A data.

Methods

`__init__`([pars])	Create a PtyScan object that will load ID16A data.
`auto`(frames)	Repeated calls to this function will process the data.
`check`(frames[, start])	This method checks how many frames the preparation routine may process, starting from frame start at a request of frames.
`correct`(raw, weights, common)	Place holder for dark and flatfield correction.
`get_data_chunk`(chunksize[, start])	This function prepares a container that is compatible to data package.
`initialize`()	Begins the Data preparation and intended as the first method that does read-write access on (large) data.
`load`(indices)	Loads data according to node specific scanpoint indices that have been determined by `LoadManager` or otherwise.
`load_common`()	Loads anything that is common to all frames and stores it in dict.
`load_positions`()	Loads all positions for all diffraction patterns in this scan.
`load_weight`()	Function description see parent class.
`post_initialize`()	Placeholder.
`report`([what, shout])	Make a report on internal structure.

Attributes

`CODES`
`DEFAULT`
`EOS`
`METAKEYS`	Keys to store in meta param
`WAIT`
`abort`
`end_of_scan`
`frames_accessible`
`num_frames`	Total number of frames to prepare / load.
`min_frames`	Minimum number of frames to prepare / load with call of `auto()`
`info`	`Param` container that stores all input parameters.

METAKEYS = ['version', 'num_frames', 'label', 'shape', 'psize', 'energy', 'center', 'distance']#: Keys to store in meta param

auto(frames)#

Repeated calls to this function will process the data.

Parameters:

frames (int) – Number of frames to process.

Returns:

one of the following

WAIT, if scan’s end is not reached, but no data could be prepared yet
EOS, if scan’s end is reached
a data package otherwise

Return type:

variable

check(frames, start=0)#

This method checks how many frames the preparation routine may process, starting from frame start at a request of frames. Returns the number of frames available from starting index start, and whether the end of the scan was reached.

Parameters:

frames (int or None) – Number of frames requested
start (int or None) – Scanpoint index to start checking from

Returns:

frame_accessible (int) – Number of frames readable from a starting point start
end_of_scan (bool or None) – Check if the end of scan was reached, otherwise None if this routine doesn’t know

correct(raw, weights, common)#

Place holder for dark and flatfield correction. Apply (eventual) corrections to the raw frames. Convert from “raw” frames to usable data.

Parameters:

raw (dict) – Dict containing index matched data frames (np.array).
weights (dict) – Dict containing possible weights.
common (dict) – Dict containing possible dark and flat frames.

Returns:

data, weights – Flat and dark-corrected data dictionaries. These dictionaries must have the same keys as the input raw and contain corrected frames (data) and statistical weights (weights)

Return type:

dict

Note

If the negative values results from the calculation, they will be forced to be equal to 0.

get_data_chunk(chunksize, start=None)#

This function prepares a container that is compatible to data package.

This function is called from the auto() function.

info#: Param container that stores all input parameters.

initialize()#

Begins the Data preparation and intended as the first method that does read-write access on (large) data. Does the following:

Creates a *.ptyd data file at location specified by dfile (master node only)
Calls load_weight(), load_positions() load_common() (master node only for load_parallel==None or load_parallel=='data')
Sets num_frames if needed
Calls post_initialize()

load(indices)#

Loads data according to node specific scanpoint indices that have been determined by LoadManager or otherwise.

Returns:: raw, pos, weight – Dictionaries whose keys are the given scan point indices and whose values are the respective frame / position according to the scan point index. weight and positions may be empty
Return type:: dict

Note

If one weight (mask) is to be used for the whole scan, it should be loaded with load_weights(). The same goes for the positions, which sould be loade with load_positions().

load_common()#

Loads anything that is common to all frames and stores it in dict.

Returns:: common – contains information common to all frames such as dark, flat-field, detector flat-field, normalization couter, and distortion files
Return type:: dict

load_positions()#

Loads all positions for all diffraction patterns in this scan.

Returns:: Positions – A (N,2)-array where N is the number of positions.
Return type:: ndarray

load_weight()#

Function description see parent class. For now, this function will be used to load the mask.

Returns:: weight2d – A two-dimensional array with a shape compatible to the raw diffraction data frames if provided from file
Return type:: ndarray

min_frames#: Minimum number of frames to prepare / load with call of auto()

num_frames#: Total number of frames to prepare / load. Set by num_frames

post_initialize()#

Placeholder. Called at the end of initialize() by all processes.

Use this method to benefit from ‘hard-to-retrieve but now available’ information after initialize.

report(what=None, shout=True)#: Make a report on internal structure.