ptypy.experiment.nanomax3d.NanomaxBraggJune2017#

class ptypy.experiment.nanomax3d.NanomaxBraggJune2017(pars=None, **kwargs)#

Bases: PtyScan

Reads an early Bragg 3d ptycho format from Nanomax, multiple fly scans are run with rocking angle steps in between.

__init__(pars=None, **kwargs)#

Class creation with minimum set of parameters, see PtyScan.DEFAULT Please note that class creation is not meant to load data.

Call initialize to begin loading and data file creation.

Methods

`__init__`([pars])	Class creation with minimum set of parameters, see `PtyScan.DEFAULT` Please note that class creation is not meant to load data.
`auto`(frames)	Repeated calls to this function will process the data.
`check`([frames, start])	Override in subclass for custom implementation
`correct`(raw, weights, common)	Override in subclass for custom implementation
`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)	This function returns diffraction image indexed from top left as viewed along the beam, i e they have (-q1, q2) indexing.
`load_common`()	We have to communicate the number of rocking positions that the model should expect, otherwise it never knows when there is data for a complete POD.
`load_positions`()	For the 3d Bragg model, load_positions returns N-by-4 positions, (angle, x, z, y).
`load_weight`()	Override in subclass for custom implementation
`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=None, start=None)#

Override in subclass for custom implementation

This method checks how many frames the preparation routine may process, starting from frame start at a request of frames.

This method is supposed to return the number of accessible frames for preparation and should determine if data acquisition for this scan is finished. Its main purpose is to allow for a data acquisition scheme, where the number of frames is not known when PtyScan is constructed, i.e. a data stream or an on-the-fly reconstructions.

Note

If num_frames is set on __init__() of the subclass, this method can be left as it is.

Parameters:

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

Returns:

frames_accessible (int) – Number of frames readable.
end_of_scan (int or None) – is one of the following, - 0, end of the scan is not reached - 1, end of scan will be reached or is - None, can’t say

correct(raw, weights, common)#

Override in subclass for custom implementation

Place holder for dark and flatfield correction. If load already provides data in the form of photon counts, and no frame specific weight is needed, this method may be left as it is.

May get merged with load in future.

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) which are zero for invalid or masked pixel other the number of detector counts that correspond to one photon count
Return type:: dict

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)#: This function returns diffraction image indexed from top left as viewed along the beam, i e they have (-q1, q2) indexing. PtyScan can always flip/rotate images.

load_common()#: We have to communicate the number of rocking positions that the model should expect, otherwise it never knows when there is data for a complete POD. We also have to specify a single number for the rocking step size.

load_positions()#

For the 3d Bragg model, load_positions returns N-by-4 positions, (angle, x, z, y). The angle can be relative or absolute, the model doesn’t care, but it does have to be uniformly spaced for the analysis to make any sense.

Let’s load the positions (and images) in the order they were acquired: x fastest, then y, then scan number in the order provided.

load_weight()#

Override in subclass for custom implementation

Called in initialize()

Loads a common (2d)-weight for all diffraction patterns. The weight loaded here will be available by all processes through the attribute self.weight2d. If a per-frame-weight is specified in load() , this function has no effect.

The purpose of this function is to avoid reloading and parallel reads. If that is not critical to the implementation, reimplementing this function in a subclass can be ignored.

If load_parallel is set to all or common`, this function is executed by all nodes, otherwise the master node executes this function and broadcasts the results to other nodes.

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

Note

For now, weights will be converted to a mask, mask = weight2d > 0 for use in reconstruction algorithms. It is planned to use a general weight instead of a mask in future releases.

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.